Assessment of Cerebral Perfusion Asymmetry in Chronic Migraine Patients using Intravoxel Incoherent Motion (IVIM)–Derived Pseudodiffusion Coefficient and Perfusion Fraction

Assessment of Cerebral Perfusion Asymmetry in Chronic Migraine Patients using Intravoxel Incoherent Motion (IVIM)–Derived Pseudodiffusion Coefficient and Perfusion Fraction | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Assessment of Cerebral Perfusion Asymmetry in Chronic Migraine Patients using Intravoxel Incoherent Motion (IVIM)–Derived Pseudodiffusion Coefficient and Perfusion Fraction Yunus Emre Senturk, Ahmet Peker, Sabahattin Yuzkan, Huseyin Ekin Ergin, and 2 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9349009/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Purpose Chronic migraine (CM) is associated with persistent neurobiological alterations beyond episodic attacks. Cerebral microvascular perfusion change during the interictal phase of CM is underexplored. Emerging Intravoxel incoherent motion (IVIM) imaging provides diffusion-derived pseudo-perfusion parameters that reflect regional microvascular alterations in the brain parenchyma. This study aimed to investigate the right-to-left hemispheric asymmetry of IVIM-derived perfusion parameters in migraine-implicated cortical and subcortical regions during the interictal phase of CM. Methods Thirty patients with CM imaged during the interictal phase, and 30 age- and sex-matched healthy controls underwent IVIM imaging. IVIM parameters, including the pseudo-diffusion coefficient (D*), perfusion fraction (f), and their composite metric (fD*), were estimated using segmented bi-exponential fitting. The circular region-of-interest analysis was performed bilaterally in migraine-implicated cortical and subcortical regions, as described in contemporary literature. Asymmetry indices of IVIM parameters were measured and compared between groups using false discovery rate correction. Results No significant increase in hemispheric asymmetry was observed in cortical regions in patients with CM compared to controls. In contrast, the posterior thalamus, comprising the ventroposteromedial and pulvinar nuclei, demonstrated significantly greater fD* asymmetry in CM (median asymmetry index: 27.91 vs 10.43; p = 0.002, q = 0.017). Inter-rater agreement of ROI placement was excellent for D* (ҡ = 0.94) and good for f (ҡ = 0.79) for each measurement. Conclusion Chronic migraine is associated with increased hemispheric asymmetry of IVIM-derived microperfusion in the posterior thalamus during the interictal phase, suggesting lateralized thalamic microvascular alterations in CM. Chronic Migraine Magnetic Resonance Imaging (MRI) Intravoxel Incoherent Motion (IVIM) Asymmetry Index (AI) Headache Figures Figure 1 Figure 2 Figure 3 INTRODUCTION Chronic migraine (CM) is a disabling condition that affects 1–2% of people globally, characterized by the presence of headache for more than 15 days per month or meeting the International Classification of Headache Disorders, 3rd edition (ICHD-3) criteria for migraine for more than 8 days per month [ 1 , 2 ]. CM is more frequently associated with comorbid conditions than episodic migraine, including sleep disturbances, anxiety, and allodynia [ 3 ]. Unlike episodic migraine, CM may be characterized by persistent neurobiological changes. Resting-state functional MRI (rs-fMRI) connectivity studies have demonstrated altered brain networks in migraine patients compared to healthy controls, highlighting the role of ongoing symptoms and central sensitization during the interictal phase, especially in CM [ 4 ]. Migraine is clinically characterized by recurrent unilateral or side-predominant headache, sometimes accompanied by lateralized sensory symptoms. Repeated activation of the trigeminovascular system in conjunction with cortical spreading depression is postulated to initially propagate within a single hemisphere before spreading bilaterally. Regional engagement of these mechanisms during the early phase of migraine attacks is associated with vasodilation during the ictal period, followed by subsequent vasoconstriction [ 5 ]. These pathophysiological processes have prompted neuroimaging studies to investigate regional perfusion differences during the peri-ictal state [ 6 , 7 ]. Although several studies reported asymmetric cortical network activation during the pain-free interictal phase, it remains unclear whether a persistent hemispheric difference of cerebral regional perfusion exists during the interictal phase of CM [ 8 , 9 ]. Non-contrast perfusion imaging techniques, such as arterial spin labeling (ASL), have attracted increasing attention in migraine research. In this context, intravoxel incoherent motion diffusion-weighted imaging (IVIM-DWI) has emerged as a promising non-contrast MRI technique capable of distinguishing true tissue diffusion of water molecules from microvascular perfusion, which was originally proposed by Le Bihan et al [ 10 ]. The IVIM concept is hypothesized to estimate perfusion in tissue via incoherent motion of water molecules within random capillaries, formerly reported as a pseudo-diffusion effect at low diffusion-sensitizing gradients (b-values typically between 0 and 200 s/mm²), which is not concurrently observed in the higher b-values in addition to normal diffusion signal decay [ 11 ]. IVIM-derived parameters, including the pseudo-diffusion coefficient (D*) , perfusion fraction (f) , and their composite metric (fD*) , may provide an opportunity to assess tissue-level quantification of microvascular perfusion while simultaneously characterizing true molecular diffusion of water. To the best of our knowledge, the role of IVIM-DWI-derived perfusion in migraine is underexplored either during the attack or interictal phase. In the present study, our objective was to explore right-to-left cerebral hemispheric differences in IVIM-derived perfusion parameters in previously defined migraine-implicated brain regions during the interictal phase of patients with CM. MATERIAL AND METHOD Ethics information This single-center retrospective study was performed in accordance with the Declaration of Helsinki. Institutional review board approval was obtained from the local ethics committee (IRB no: 2025.623.IRB2.281). The requirement for written informed consent was waived by the ethics committee. Study Population This single-center retrospective study was conducted between January 2023 and November 2025 and included patients presenting to the outpatient clinic with chronic headache. Among these patients, the diagnosis of CM was established in accordance with the ICHD-3. Diagnostic criteria included headache (migraine-like or tension-type-like) occurring on ≥ 15 days per month for more than 3 months, or headache occurring on ≥ 8 days per month for at least 3 months that fulfilled criteria for migraine with aura with at least five attacks or migraine without aura that was not better accounted for by another headache disorder [ 12 ]. The brain MRI with IVIM-DWI was performed to rule out secondary intracranial pathology or any emergent causes of chronic headache for each case. The inclusion criteria comprised patients with CM who underwent brain MRI with IVIM-DWI during the interictal phase, defined as the absence of headache, aura, or other migraine-related symptoms at the time of imaging, and with at least 48 hours having elapsed since the most recent migraine attack. The exclusion criteria were as follows: (i) brain MRI with IVIM-DWI performed during an active migraine attack, defined by the presence of headache, aura, or other migraine-related symptoms at the time of imaging or within 48 hours after such symptoms. (ii) non-migraine type primary chronic headache disorders, such as trigeminal autonomic cephalalgias, or cluster headache; (iii) secondary headache disorders, including those attributed to head trauma, vascular disorders, substance or medication withdrawal, intracranial tumors, intracranial hypotension or hypertension, or pathology of the paranasal sinuses or aerodigestive tract; (iv) age younger than 18 years; (v) presence of incidental intracranial imaging abnormalities, regardless of clinical relevance to headache, including demyelinating lesions, acute or chronic cerebral infarction, vascular malformations, tumors, or equivalent structural abnormalities on brain MRI; (vi) presence of major concurrent systemic disorders, such as diabetes mellitus, hypertension, vasculitis, or renal failure; and (vii) inadequate image quality due to significant motion artifacts, geometric distortion, poor signal-to-noise ratio, or incomplete IVIM-DWI or fluid-attenuated inversion recovery (FLAIR) sequences. During the study period, 177 patients with chronic headache underwent brain MRI with IVIM-DWI to evaluate for potential secondary causes. Among these, 25 patients had experienced an active headache within the preceding 48 hours, as documented on the MRI request forms. Of the remaining 152 patients who underwent brain MRI with IVIM-DWI during a headache-free period, only 30 fulfilled the diagnostic criteria for CM in the interictal phase. The study group selection process is summarized in Fig. 1 as a flowchart. Thirty age- and sex-matched healthy control subjects were randomly recruited from individuals undergoing routine health check-up examinations to undergo IVIM-DWI imaging. Controls had no history of migraine or other primary or secondary headache disorders, no headache within the preceding 48 hours, and no aura-suggesting symptoms within the past 12 months. Individuals with a history of neurologic or systemic disorders, illicit drug use, long-term medication use, or current use of analgesic or vasoactive medications were excluded. All control subjects had no clinically significant abnormalities on brain MRI. Intravoxel Incoherent Motion MRI Protocol Intravoxel Incoherent Motion MRI Protocol DWI was acquired using a single-shot echo-planar imaging sequence on a 1.5-T MRI system (Aera; Siemens Healthineers, Erlangen, Germany). Imaging was performed using a standard 16-channel receiver head coil. DWI was acquired in the axial plane with the following parameters: repetition time/echo time (TR/TE), 5100/115 ms; field of view (FOV), 230 × 230 mm; slice thickness (ST), 3.0 mm; and flip angle (FA), 90°. Multiple diffusion-sensitizing gradients were applied (b = 0, 50, 100, 150, 200, 250, 300, 350, 400, 600, and 800 s/mm²) to enable IVIM analysis. The IVIM signal decay was modeled using the following bi-exponential function: $$\:S\left(b\right)=S0\left[f.{e}^{-bD*}+\left(1-f\right).{e}^{-bD}\right]$$ D represents the true diffusion coefficient, D* the pseudo-diffusion coefficient associated with microvascular perfusion, and f represents the perfusion fraction. The classical method of segmented fitting was utilized to measure perfusion-related parameters, D* and f maps. First, D was estimated by applying a linear mono-exponential diffusion fit to higher b-value data (b \(\:\ge\:200\) s/mm²), where the contribution of perfusion on the diffusion decay curve is negligible. Subsequently, f and D* were derived by fitting the fixed D value into the non-linear bi-exponential diffusion function using low-b value data (b = 0, 50, 100, 150 s/mm²), where the perfusion-related effect upon the diffusion function is most prominent. The D* and f maps were registered rigidly with FLAIR images to increase the spatial conspicuity of the cerebral cortex as well as deep gray nuclei and to eliminate any geometrical distortion attributed to echo-planar DWI. The following parameters were used to acquire FLAIR imaging: time to inversion (TI), 2300 ms; TR/TE, 7500/85 ms; FOV, 230 × 230 mm; ST, 3.0 mm; and FA 150°. The entire segmented-fitting-based IVIM-DWI modelling and generation of D* and f maps, followed by rigid registration with FLAIR imaging, was computed in Olea Sphere® version 3.0 software (Olea Medical, La Ciotat, France). ROI-based Analysis of Brain Parenchyma Based on functional imaging–derived evidence from the contemporary literature, eight key anatomical locations were selected for region-of-interest (ROI) placement to measure IVIM parameters. Since performing ROI analysis across the entire gyral system is not feasible, ROI placement was restricted to six cortical regions implicated in migraine, along with the posterior thalamus and the dorsal pontine region, resulting in a total of eight regions. The hypothesized associations between ROI-placed regions and CM pathophysiology are summarized in Table 1 , together with relevant supportive literature [ 13 – 17 ]. After co-registration of the D* and f maps with the FLAIR images, circular ROIs with an area of 30–60 mm² were placed, with the exact size adjusted according to the cortical thickness of six cortical regions considered relevant in migraine pathophysiology. ROI placement was performed on the FLAIR series to ensure optimal conspicuity and to allow precise delineation within the cerebral cortex, avoiding inclusion of underlying subcortical white matter. The initial ROI positions were subsequently verified on the rigidly registered D* and f maps to exclude spatial misregistration. Mild geometric distortions were observed only in the amygdala and dorsomedial prefrontal cortex (dmPFC), attributable to echo-planar DWI–related susceptibility effects adjacent to the cranial base, which were visually corrected using the D* maps. Similar ROI placement was achieved by precisely mirroring each ROI to the anatomically corresponding contralateral cortical location. Measurements of the posterior thalamus and pontine tegmentum were likewise obtained using exact contralateral mirrored ROIs. Specifically, the posterior thalamic ROI encompassed the pulvinar and ventroposteromedial (VPM) nuclei, consistent with the probabilistic 3D subsegmentation model proposed by Chen et al [ 18 ]. The ROI placement method is illustrated in Fig. 2 . All measurements were performed by two raters: a central rater with 8 years of experience in neuroimaging (Y.E.S.) and a co-rater with 7 years of experience (A.P.), who independently performed ROI placement and measurements for the entire cohort. Table 1 Regions of Interest and proposed pathophysiological roles in migraine *Region of interest locations (ROI) Proposed pathophysiological role in migraine Insula Salience and interoceptive integration of pain Anterior cingulate gyrus (ACC) Affective pain processing and modulation Dorsomedial prefrontal cortex (dmPFC) Cognitive top-down modulation of pain Postcentral gyrus facial homunculus (S1) Sensory–discriminative pain processing Primary visual cortex (V1) Cortical hyperexcitability, cortical spreading depolarization, and visual sensitivity Amygdala Emotional modulation of pain and stress Posterior thalamus (Ventroposteromedial and pulvinar nuclei) Thalamocortical sensory integration Pontine tegmentum Pain modulation and attack-related trigeminovascular activity *ROI selection was guided by converging evidence from prior functional neuroimaging and experimental studies implicating distributed cortical and subcortical networks involved in pain processing, sensory integration, salience attribution, cortical excitability, and brainstem modulation in migraine (see the references 13–17 for details). For each ROI-based measurement, the asymmetry index (AI) was calculated from the derived IVIM perfusion parameters (f, D*, and fD*). An absolute AI value greater than 10% was considered indicative of asymmetric perfusion between the right and left relevant cortical ROI-based measurements [ 6 , 19 ]. $$\:Asymmetry\:Index=\frac{|{\varvec{R}\varvec{O}\varvec{I}}_{\varvec{r}\varvec{i}\varvec{g}\varvec{h}\varvec{t}}-{\varvec{R}\varvec{O}\varvec{I}}_{\varvec{l}\varvec{e}\varvec{f}\varvec{t}}|}{({\varvec{R}\varvec{O}\varvec{I}}_{\varvec{r}\varvec{i}\varvec{g}\varvec{h}\varvec{t}}+{\varvec{R}\varvec{O}\varvec{I}}_{\varvec{l}\varvec{e}\varvec{f}\varvec{t}})}\:\times\:100$$ Statistical Analysis Statistical analyses were conducted using SPSS (version 28.0; IBM Corp., Armonk, NY, USA). Normality was evaluated with the Shapiro-Wilk test. Group comparisons were performed using independent-samples Student’s t tests for normally distributed variables and Mann-Whitney U tests for non-parametric variables. ROI-based hemispheric asymmetry indices from eight brain regions were compared between CM patients and healthy controls. Multiple comparisons were controlled using false discovery rate (FDR) correction based on the Benjamini-Hochberg (BH) method. Inter-rater agreement of ROI placement on D* and f maps was assessed using the intraclass correlation coefficient (ICC), calculated with a two-way random-effects model for absolute agreement between both raters. RESULTS The mean age was 36.2 ± 12.3 years in the CM group (18 females / 12 males) and 36.8 ± 13.1 years in the healthy control group (18 females / 12 males), with no significant difference between groups (p = 0.68). Among the 8 different brain locations, the distributions of absolute D*, f , and fD* were not significantly different between the right and left cerebral hemispheres ( Table 2 ). Inter-rater agreement of ROI placement between the two raters was excellent for D* (ҡ = 0.94) and good for f (ҡ = 0.79) measurements. Table 2 Hemispheric comparison of ROI-based absolute IVIM parameters in chronic migraine and control groups ROI Chronic Migraine Group (n:30) Control subjects (n:30) Parameter Right Hemisphere Left Hemisphere p Right Hemisphere Left Hemisphere p Anterior Cingulate Cortex fD* 0.78 ± 0.44 0.63 ± 0.47 0.19ᵃ 0.69 ± 0.32 0.72 ± 0.35 0.71ᵃ Anterior Cingulate Cortex D* 11.44 ± 5.00 12.94 ± 5.56 0.13ᵃ 13.46 ± 4.33 13.43 ± 4.51 0.98ᵃ Anterior Cingulate Cortex f 0.07 (0.05) 0.04 (0.04) 0.11ᵇ 0.05 ± 0.02 0.06 ± 0.03 0.32ᵃ Insula fD* 0.90 ± 0.55 0.77 ± 0.45 0.24ᵃ 0.66 (0.53) 0.68 (0.40) 0.81ᵇ Insula D* 15.72 ± 4.17 12.09 ± 4.19 0.06ᵃ 13.30 ± 3.27 12.85 ± 4.75 0.66ᵃ Insula f 0.06 ± 0.04 0.07 ± 0.04 0.34ᵃ 0.06 (0.04) 0.06 (0.03) 0.79ᵇ Primary visual cortex (V1) fD* 0.77 ± 0.53 0.86 ± 0.55 0.49ᵃ 0.81 (0.58) 0.94 (0.65) 0.58ᵇ Primary visual cortex (V1) D* 12.61 ± 4.17 12.02 ± 3.93 0.51ᵃ 12.52 ± 3.52 12.73 ± 4.18 0.81ᵃ Primary visual cortex (V1) f 0.05 (0.07) 0.06 (0.05) 0.22ᵇ 0.08 ± 0.05 0.08 ± 0.04 0.55ᵃ Postcentral gyrus facial homunculus (S1) fD* 0.62 (0.76) 0.88 (0.89) 0.14ᵇ 0.80 (0.78) 1.09 (1.39) 0.11ᵇ Postcentral gyrus facial homunculus (S1) D* 12.94 ± 3.67 13.14 ± 4.03 0.77ᵃ 14.90 ± 3.71 13.59 ± 5.24 0.19ᵃ Postcentral gyrus facial homunculus (S1) f 0.05 (0.05) 0.06 (0.06) 0.15ᵇ 0.07 ± 0.05 0.10 ± 0.08 0.04ᵃ Dorsomedial Prefrontal Cortex (dmPFC) fD* 0.69 ± 0.44 0.53 ± 0.30 0.10ᵃ 0.75 ± 0.47 0.79 ± 0.41 0.60ᵃ Dorsomedial Prefrontal Cortex (dmPFC) D* 13.51 ± 5.25 14.82 ± 4.43 0.28ᵃ 13.02 ± 3.94 14.20 ± 4.41 0.24ᵃ Dorsomedial Prefrontal Cortex (dmPFC) f 0.05 (0.03) 0.03 (0.03) 0.10ᵇ 0.06 ± 0.04 0.06 ± 0.04 0.95ᵃ Amygdala fD* 0.68 ± 0.32 0.83 ± 0.55 0.12ᵃ 0.68 ± 0.24 0.87 ± 0.43 0.02ᵃ Amygdala D* 15.38 ± 3.61 15.18 ± 5.52 0.84ᵃ 14.76 (5.56) 15.89 (5.45) 0.31ᵇ Amygdala f 0.05 (0.03) 0.05 (0.04) 0.24ᵇ 0.05 ± 0.02 0.06 ± 0.04 0.13ᵃ Posterior thalamus fD* 0.87 ± 0.41 0.87 ± 0.42 0.99ᵃ 0.87 (0.45) 0.77 (0.51) 0.70ᵇ Posterior thalamus D* 17.13 ± 2.97 16.78 ± 3.51 0.62ᵃ 16.48 ± 3.68 15.93 ± 3.35 0.61ᵃ Posterior thalamus f 0.05 ± 0.02 0.05 ± 0.02 0.96ᵃ 0.05 ± 0.02 0.05 ± 0.02 0.07ᵃ Pontine Tegmentum fD* 0.93 ± 0.42 0.94 ± 0.45 0.92ᵃ 0.96 ± 0.48 0.95 ± 0.44 0.89ᵃ Pontine Tegmentum D* 16.30 ± 2.81 15.68 ± 4.31 0.46ᵃ 15.87 ± 3.25 16.10 ± 3.94 0.69ᵃ Pontine Tegmentum f 0.06 ± 0.02 0.06 ± 0.03 0.68ᵃ 0.06 ± 0.03 0.06 ± 0.03 0.76ᵃ a: Student’s t-test b: Mann-Whitney U test Units : D*, fD* (×10⁻³ mm²/s); f (unitless). ROI , Region of Interest; IVIM , Intravoxel incoherent motion Analysis of hemispheric AI for IVIM-derived diffusion and perfusion parameters ( D*, f, and fD* ) demonstrated a mild degree of right–left asymmetry in both the CM group and healthy controls. After BH correction for multiple comparisons, no significant increase in the AI of IVIM parameters was noted in the CM group compared to the control group across six cortical regions or in the pontine tegmentum ( Table 3 ) . In contrast, the median fD* AI of the posterior thalamus was 27.91 (IQR: 16.87) in the CM group and 10.43 (IQR: 19.58) in the control group, indicating a significantly greater absolute right–left asymmetry of combined perfusion fraction and pseudo-diffusion in CM patients compared to controls (p = 0.002, q = 0.017 after FDR correction). Table 3 Group comparison of the asymmetry index of IVIM-based perfusion parameters in chronic migraine and the control group Region Parameter Chronic Migraine (n:30) Healthy Control (n:30) p q (BH/FDR) Anterior Cingulate Cortex fD* AI 33.65 ± 18.22 23.20 ± 16.79 0.024ᵃ 0.098 Anterior Cingulate Cortex D* AI 16.85 (16.64) 11.92 (17.89) 0.348ᵇ 0.813 Anterior Cingulate Cortex f AI 30.05 (24.90) 20.00 (30.04) 0.062ᵇ 0.214 Insula fD* AI 27.82 (23.44) 25.53 (30.00) 0.888ᵇ 0.888 Insula D* AI 16.69 (17.24) 16.21 (17.76) 0.540ᵇ 0.813 Insula f AI 23.66 (28.83) 15.65 (35.14) 0.525ᵇ 0.700 Primary visual cortex (V1) fD* AI 23.94 (26.18) 16.98 (29.73) 0.673ᵇ 0.888 Primary visual cortex (V1) D* AI 12.97 (16.08) 10.27 (16.83) 0.610ᵇ 0.813 Primary visual cortex (V1) f AI 20.26 (34.98) 19.30 (39.75) 0.706ᵇ 0.706 Postcentral gyrus facial homunculus (S1) fD* AI 24.30 (26.96) 32.90 (28.17) 0.830ᵇ 0.888 Postcentral gyrus facial homunculus (S1) D* AI 11.24 (10.61) 10.51 (17.10) 0.807ᵇ 0.819 Postcentral gyrus facial homunculus (S1) f AI 29.85 (32.18) 28.04 (24.63) 0.684ᵇ 0.706 Dorsomedial Prefrontal Cortex (dmPFC) fD* AI 30.77 ± 24.53 20.39 ± 14.15 0.051ᵃ 0.135 Dorsomedial Prefrontal Cortex (dmPFC) D* AI 11.47 (18.51) 11.85 (12.02) 0.819ᵇ 0.819 Dorsomedial Prefrontal Cortex (dmPFC) f AI 29.72 (28.77) 19.34 (26.40) 0.093ᵇ 0.214 Amygdala fD* AI 25.77 ± 16.70 23.53 ± 15.43 0.592ᵃ 0.888 Amygdala D* AI 13.07 (14.11) 12.65 (7.83) 0.530ᵇ 0.813 Amygdala f AI 29.81 ± 20.55 25.48 ± 18.65 0.396ᵃ 0.633 Posterior Thalamus fD* AI 27.91 (16.87) 10.43 (19.58) 0.002ᵇ 0.017 Posterior Thalamus D* AI 6.89 (6.70) 11.26 (13.77) 0.018ᵇ 0.147 Posterior Thalamus f AI 21.61 (17.56) 10.14 (15.77) 0.016ᵇ 0.125 Pontine Tegmentum fD* AI 18.97 (17.47) 11.07 (16.46) 0.070ᵇ 0.140 Pontine Tegmentum D* AI 10.10 (9.93) 5.58 (13.57) 0.066ᵇ 0.263 Pontine Tegmentum f AI 15.41 (22.99) 10.78 (11.00) 0.107ᵇ 0.214 a Student’s t-test b Mann-Whitney U test AI , Asymmetry index; BH-FDR , Benjamini-Hochberg-False Discovery Rate; IVIM , intravoxel incoherent motion The median D* AI of the posterior thalami was 6.89 (IQR: 6.70) in the CM group and 11.26 (IQR: 13.77) in the control group (p = 0.018). Similarly, the median f asymmetry index was 21.61 (IQR: 17.56) in the CM group and 10.14 (IQR: 15.77) in control subjects (p = 0.016). Although both D* and f asymmetry indices showed significance in the initial uncorrected analyses, neither remained significant after BH correction for multiple comparisons (q = 0.147 and q = 0.125, respectively). Figure 3 illustrates the distribution of right–left hemispheric asymmetry of IVIM-DWI–derived perfusion parameters in the posterior thalami. Although the fD* AI in the anterior cingulate cortex was higher in CM patients than in healthy controls, this effect did not remain significant after BH correction and was therefore considered likely to represent a false-positive finding (p = 0.024, q = 0.098; Table 3 ). In contrast, fD* asymmetry in the bilateral thalamic nuclei remained statistically significant after correction for multiple comparisons. DISCUSSION The present study investigated cerebral microvascular alterations in patients with CM during the interictal phase. Using an IVIM-derived perfusion technique, we demonstrated a significantly increased hemispheric asymmetry of the combined perfusion parameter, fD* , in the posterior thalami. In contrast, IVIM-derived perfusion parameters in cortical regions implicated in migraine initiation, propagation, and pain modulation did not show significant lateralized perfusion differences between the cerebral hemispheres. These preliminary findings suggest that persistent hemispheric imbalance in posterior thalamic microvascular perfusion may be involved in CM, potentially reflecting altered function of dorsal thalamic nuclei in the modulation of lateralized nociceptive processing in migraineurs and associated changes in blood–brain barrier permeability in the posterior thalamus. The posterior thalamus, including pulvinar nuclei and VPM, plays a key role in nociceptive processing of the trigeminovascular hypothesis, where the VPM nuclei act as the principal relay for nociceptive transmission to the cortical region in pain perception [ 20 , 21 ]. Another important function of the posterior thalamus is the modulation of pain and visual information [ 22 ]. During the migraine attack, proposed sterile inflammatory signaling originating at the dura mater is conveyed via afferent trigeminothalamic projections to the VPM nuclei of the thalamus, playing a key role in central sensitization and allodynia [ 23 ]. The experimental study by Noseda et al. provides direct electrophysiological evidence from in vivo experiments with rats that posterior thalamic nuclei, including VPM nuclei of the thalamus, responded selectively to mechanical, chemical, and electrical stimulation of the dura mater, therefore named as dura-sensitive nuclei. In the same series, the dura-sensitive posterior thalamic neurons function as high-order relays, showing a variety of projections and evoked potentials to visual, parietal, and retrosplenial cortices. The widespread thalamocortical divergence in this in vivo study suggests that nociceptive dural stimuli are associated with visual, cognitive, and perceptual domains of migraine [ 24 ]. Diffusion tensor imaging–based probabilistic tractography by Maleki et al. demonstrated non-visual direct pathways from the optic nerve to the pulvinar nuclei and from the pulvinar to multiple associative cortical regions, providing a structural basis for the pulvinar as an important relay of photic signals. This network may allow selective activation of the pulvinar during migraine attacks and offers a mechanistic explanation for visual and other sensory symptoms through its widespread cortical associations [ 25 ]. Similar to this, Sower et al. proposed that optogenic stimulation or CGRP injection to the posterior thalami elicited the photophobic light aversive behavior, like in migraineurs [ 26 ]. Beyond the role of posterior thalami in aural symptoms, a rs-fMRI study seeking functional connectivity analysis in migraineurs at the interictal phase demonstrated that migraineurs with cutaneous allodynia presented increased directional inflow from the right medial prefrontal cortex to the right posterior thalamus, along with reduced inflow from the left dorsomedial prefrontal cortex to the left posterior thalamus. In the same study, correlation analysis further revealed disrupted functional connectivity between the posterior thalamus and the cuneus, as well as frontal cortical regions, in migraine patients with allodynia [ 9 ]. The asymmetrical functional connectivity of the bilateral thalamus in migraine with the interictal phase has not yet been shown in perfusion-based imaging studies. Fu et al. reported decreased cerebral blood flow (CBF) in the bilateral thalamus in migraine with aura compared to healthy controls in the pediatric population at interictal period, whereas they did not report abnormal lateralization in thalamic CBF in pseudo-continuous ASL MRI [ 27 ]. In our cohort, increased IVIM-derived fD* asymmetry in patients with CM and high attack frequency may reflect lateralized alterations in microvascular regulation or neurovascular coupling between the bilateral posterior thalamic nuclei, supporting the concept of a persistent hemispheric imbalance in regional vascular demand within the thalami. In the present study, although the perfusion fraction f alone did not reach statistical significance after BH false discovery rate correction, its combination with the less asymmetric pseudo-diffusion coefficient D* resulted in a synergistic effect, rendering the composite fD* parameter sensitive to interhemispheric differences. According to IVIM biophysical principles, D* represents flow-related pseudo-diffusion associated with blood velocity and incoherent microvascular motion, whereas the f parameter reflects the fractional volume of blood within the microvascular compartment [ 28 ]. Notably, the magnitude of asymmetry was substantially greater for f than for D* , suggesting that the observed hemispheric fD* imbalance in our study is driven primarily by asymmetric capillary recruitment or microvascular density within the posterior thalamic nuclei, a pattern more consistent with chronicity rather than transient migraine-related alterations. In contrast to f, D* is thought to be influenced by flow dynamics and vascular permeability that may be relatively associated with the integrity of the blood–brain barrier and therefore less susceptible to subtle changes in CM during pain-free interictal phase. Supporting this interpretation, Wu et al. demonstrated that the perfusion fraction f provides a more stable and reproducible surrogate of CBF, whereas D* had limited robustness in normal brain parenchyma [ 29 ]. Notably, despite these methodological considerations, D* measurements in the present study demonstrated excellent inter-observer reliability, indicating that observed differences reflect biological rather than technical variability. Beyond the thalamic findings discussed above, the lack of increased asymmetry of any IVIM-derived perfusion parameter across the cerebral cortex in migraine pathophysiology can be interpreted as the lack of microvascular flow imbalance in the migraine-implicated cortical locations at the symptom-free interictal phase. Consistent with our results, Bai et al. reported no significant right–left asymmetry or abnormal CBF values in migraine-related cortical regions in a cohort of 18 CM patients studied using pseudo-continuous ASL MRI. In contrast to our findings, their study demonstrated bilateral thalamic hyperperfusion without evidence of hemispheric CBF asymmetry in the thalami of CM patients [ 30 ]. It is presumed that aura and visual symptoms arise from cortical spreading depression, a neurophysiological phenomenon accompanied by transient, biphasic alterations in cortical CBF during the aura phase. This process is believed to originate in the occipital cortex and propagate across adjacent cortical regions, often with an initial unilateral predominance [ 31 ]. During the symptom-free interictal phase, in the absence of aura or headache, alterations in CBF within primary and secondary associative cortices, as well as pain-modulatory regions, are not expected to manifest as sustained hypo- or hyperperfusion. Despite the high attack frequency characteristic of CM, neither prior ASL studies nor our IVIM-derived microperfusion findings demonstrated consistent inter-hemispheric cortical perfusion asymmetry that could be considered a defining feature of the interictal phase in migraine with or without aura [ 32 , 33 ]. Our study presents several limitations. First, the retrospective design and relatively low sample size may limit the reproducibility of our preliminary results. Second, IVIM-derived parameters, particularly the pseudo-diffusion coefficient D* , are known to be sensitive to noise and organ-specific local factors [ 34 ]. However, in the current study, D* demonstrated excellent inter-rater reliability, and the use of a segmented-fitting approach together with rigid registration to FLAIR imaging enhanced the consistency of ROI-based D* measurements. Third, ROI-based analysis was restricted to predefined cortical and subcortical regions implicated in migraine pathophysiology, which may overlook additional cortical regions associated with perfusion asymmetry on interictal phase of CM. Fourth, imaging was performed exclusively during the interictal phase, and without correlation with the most recent and most frequent attack laterality, disease duration, or treatment status. Finally, due to the cross-sectional design of the present study, longitudinal changes in IVIM-derived perfusion parameters, including their hemispheric asymmetry, as well as the effects of preventive treatments on D, f , and fD* , were not assessed. Overall, these limitations highlight the necessity for larger, prospective studies with longitudinal imaging to establish the robustness, temporal dynamics, and clinical relevance of IVIM-derived perfusion parameters in CM. CONCLUSIONS IVIM-DWI-based clinical study offers insights into the parenchymal microvascular correlates of CM during the interictal phase. The observed hemispheric asymmetry of IVIM-derived microperfusion parameters in the posterior thalamus supports the concept that side-predominant activation of the trigeminothalamic nociceptive network may drive regional perfusion alterations, thereby contributing to a better understanding of migraine pathophysiology and asymmetric initiation of the proposed cortical spreading depression theory. Future studies with larger cohorts are warranted to validate these results and to further elucidate the potential clinical role of IVIM-DWI during the ictal phases of migraine. Abbreviations ACC anterior cingulate cortex AI asymmetry index ASL arterial spin labeling BH Benjamini–Hochberg CM chronic migraine CSD cortical spreading depression, D = true diffusion coefficient D* pseudo-diffusion coefficient dmPFC dorsomedial prefrontal cortex DWI diffusion-weighted imaging FA flip angle FLAIR fluid-attenuated inversion recovery f perfusion fraction fD* composite perfusion parameter FDR false discovery rate FOV field of view IVIM intravoxel incoherent motion ROI region of interest S1 primary somatosensory cortex V1 primary visual cortex VPM ventroposteromedial nucleus. Declarations Conflict of interest Y.E.Senturk, A.Peker, S.Yuzkan, H.E.Ergin, E.Bulus, and M.S. Shazeeb declare that they have no competing interests. Author Contribution The first draft of the manuscript was written by [Yunus Emre Senturk] and [Huseyin Ekin Ergin]. [Sabahattin Yuzkan], [Mohammed Salman Shazeeb], and [Ahmet Peker] contributed to the study conception and design. [Sabahattin Yuzkan], [Yunus Emre Senturk], [Eser Bulus], and [Huseyin Ekin Ergin] contributed to the material preparation, data collection, and analysis. [Ahmet Peker] and [Mohammed Salman Shazeeb] reviewed and edited the manuscript. All authors made substantial contributions to the interpretation of data. All authors critically revised the manuscript. All authors approved the version to be published and agree to be accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved. References Eigenbrodt AK, Ashina H, Khan S et al (2021) Diagnosis and management of migraine in ten steps. Nat Rev Neurol 17:501–514 Arnold M (2018) Headache classification committee of the International Headache Society (IHS) the international classification of headache disorders. Cephalalgia 38:1–211 Katsarava Z, Buse DC, Manack AN et al (2012) Defining the differences between episodic migraine and chronic migraine. Curr Pain Headache Rep 16:86–92 Chou BC, Lerner A, Barisano G et al (2023) Functional MRI and diffusion tensor imaging in migraine: a review of migraine functional and white matter microstructural changes. J Cent Nerv Syst Dis 15:11795735231205413 Burstein R, Noseda R, Borsook D (2015) Migraine: multiple processes, complex pathophysiology. J Neurosci 35:6619–6629 Shimoda M, Hoshikawa K, Oda S et al (2024) Cortical hyperperfusion on MRI arterial spin-labeling during the interictal period of patients with migraine headache. AJNR Am J Neuroradiol 45:686–692 Kellner-Weldon F, El-Koussy M, Jung S et al (2018) Cerebellar hypoperfusion in migraine attack: incidence and significance. AJNR Am J Neuroradiol 39:435–440 Xue T, Yuan K, Cheng P et al (2013) Alterations of regional spontaneous neuronal activity and corresponding brain circuit changes during resting state in migraine without aura. NMR Biomed 26:1051–1058 Wang T, Chen N, Zhan W et al (2015) Altered effective connectivity of posterior thalamus in migraine with cutaneous allodynia: a resting-state fMRI study with Granger causality analysis. J Headache Pain 17:17 Le Bihan D, Breton E, Lallemand D et al (1986) MR imaging of intravoxel incoherent motions: application to diffusion and perfusion in neurologic disorders. Radiology 161:401–407 Le Bihan D (2019) What can we see with IVIM. MRI? Neuroimage 187:56–67 Olesen J (2018) International classification of headache disorders. Lancet Neurol 17:396–397 Dai W, Liu RH, Qiu E et al (2021) Cortical mechanisms in migraine. Mol Pain 17:17448069211050246 Burke MJ, Joutsa J, Cohen AL et al (2020) Mapping migraine to a common brain network. Brain 143:541–553 Maleki N, Becerra L, Brawn J et al (2012) Concurrent functional and structural cortical alterations in migraine. Cephalalgia 32:607–620 Tolner EA, Chen SP, Eikermann-Haerter K (2019) Current understanding of cortical structure and function in migraine. Cephalalgia 39:1683–1699 Hougaard A, Amin FM, Christensen CE et al (2017) Increased brainstem perfusion, but no blood–brain barrier disruption, during attacks of migraine with aura. Brain 140:1633–1642 Chen Z, Jia Z, Chen X et al (2017) Volumetric abnormalities of thalamic subnuclei in medication-overuse headache. J Headache Pain 18:82 Hauf M, Slotboom J, Nirkko A et al (2009) Cortical regional hyperperfusion in nonconvulsive status epilepticus measured by dynamic brain perfusion CT. AJNR Am J Neuroradiol 30:693–698 Ferrari MD, Goadsby PJ, Burstein R et al (2022) Migraine Nat Rev Dis Primers 8:2 Goadsby PJ (2012) Pathophysiology of migraine. Ann Indian Acad Neurol 15(Suppl 1):S15–22 Herrero MT, Barcia C, Navarro JM (2002) Functional anatomy of thalamus and basal ganglia. Childs Nerv Syst 18:386–404 Burstein R, Yamamura H, Malick A et al (1998) Chemical stimulation of the intracranial dura induces enhanced responses to facial stimulation in brain stem trigeminal neurons. J Neurophysiol 79:964–982 Noseda R, Jakubowski M, Kainz V et al (2011) Cortical projections of functionally identified thalamic trigeminovascular neurons: implications for migraine headache and its associated symptoms. J Neurosci 31:14204–14217 Maleki N, Becerra L, Upadhyay J et al (2012) Direct optic nerve pulvinar connections defined by diffusion MR tractography in humans: implications for photophobia. Hum Brain Mapp 33:75–88 Sowers LP, Wang M, Rea BJ et al (2020) Stimulation of posterior thalamic nuclei induces photophobic behavior in mice. Headache 60:1961–1981 Fu T, Liu L, Huang X et al (2022) Cerebral blood flow alterations in migraine patients with and without aura: an arterial spin labeling study. J Headache Pain 23:131 Iima M, Le Bihan D (2016) Clinical intravoxel incoherent motion and diffusion MR imaging: past, present, and future. Radiology 278:13–32 Wu WC, Chen YF, Tseng HM et al (2015) Caveat of measuring perfusion indexes using intravoxel incoherent motion magnetic resonance imaging in the human brain. Eur Radiol 25:2485–2492 Bai X, Wang W, Zhang X et al (2022) Cerebral perfusion variance in new daily persistent headache and chronic migraine: an arterial spin-labeled MR imaging study. J Headache Pain 23:156 Moskowitz MA (2025) Rethinking migraine with aura: why cortical spreading depolarization (depression), not aura, causes headaches. Cephalalgia 45:03331024251370629 Russo A, Silvestro M, Tessitore A et al (2023) Arterial spin labeling MRI applied to migraine: current insights and future perspectives. J Headache Pain 24:71 Gil-Gouveia R, Pinto J, Figueiredo P et al (2017) An arterial spin labeling MRI perfusion study of migraine without aura attacks. Front Neurol 8:280 Sharifzadeh Javidi S, Shirazinodeh A, Saligheh Rad H (2023) Intravoxel incoherent motion quantification dependent on measurement SNR and tissue perfusion: a simulation study. J Biomed Phys Eng 13:555–562 Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-9349009","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":626239071,"identity":"464a5234-edbd-410a-92b4-ec1d3dc5759a","order_by":0,"name":"Yunus Emre Senturk","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA6ElEQVRIie3OMYvCMBTA8QcHuvTsmi56H+FJIQ4n3FcJCHbpcCCIo1NdAn4WF6cbIoFO78za6SgInW5ol5svFQdd0o4O+S95JO8HAfD5njgMAxgAqHYWPfbtIkbynqg+BKkvQaPzS5P9xDERL4E0hMMUX5ovBymWCZ6yFeffcoZQaIjkL4KqXCTg7JSJOTd2gFrbm9QSx8/QmL8rifc38tFJVDpoCcdXaYn9GLIOEhVLzugsYkb5mglKAkbVpyIHGRldsc1aTPdycWR1/j4Od4tDuXGQt4c3ARC0pwMATLauV5/P5/O1/QPcp1guxIFYVwAAAABJRU5ErkJggg==","orcid":"","institution":"Koç University","correspondingAuthor":true,"prefix":"","firstName":"Yunus","middleName":"Emre","lastName":"Senturk","suffix":""},{"id":626239074,"identity":"1d773bc2-62cb-46fc-ba5d-46794cb37fc0","order_by":1,"name":"Ahmet Peker","email":"","orcid":"","institution":"Koç University","correspondingAuthor":false,"prefix":"","firstName":"Ahmet","middleName":"","lastName":"Peker","suffix":""},{"id":626239078,"identity":"9df17922-7584-498a-9381-66ae97a434f5","order_by":2,"name":"Sabahattin Yuzkan","email":"","orcid":"","institution":"Koç University","correspondingAuthor":false,"prefix":"","firstName":"Sabahattin","middleName":"","lastName":"Yuzkan","suffix":""},{"id":626239081,"identity":"f325a476-f5c4-4114-a5e1-f9ecc0c46234","order_by":3,"name":"Huseyin Ekin Ergin","email":"","orcid":"","institution":"Koç University","correspondingAuthor":false,"prefix":"","firstName":"Huseyin","middleName":"Ekin","lastName":"Ergin","suffix":""},{"id":626239082,"identity":"02fed215-6083-4492-92b6-e05cdf4369d6","order_by":4,"name":"Eser Bulus","email":"","orcid":"","institution":"Koç University","correspondingAuthor":false,"prefix":"","firstName":"Eser","middleName":"","lastName":"Bulus","suffix":""},{"id":626239083,"identity":"16de0894-7a4d-4ca7-8c8b-d2b8166b6afd","order_by":5,"name":"Mohammed Salman Shazeeb","email":"","orcid":"","institution":"University of Massachusetts Chan Medical School","correspondingAuthor":false,"prefix":"","firstName":"Mohammed","middleName":"Salman","lastName":"Shazeeb","suffix":""}],"badges":[],"createdAt":"2026-04-07 19:53:47","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-9349009/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-9349009/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":107832580,"identity":"02595085-7e7f-4bf7-9929-1f68dd94823b","added_by":"auto","created_at":"2026-04-26 15:34:28","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":974799,"visible":true,"origin":"","legend":"\u003cp\u003eFlow chart summary of study group selection\u003c/p\u003e","description":"","filename":"Figure1.png","url":"https://assets-eu.researchsquare.com/files/rs-9349009/v1/1d68380e4d005af7f8eebf77.png"},{"id":107832581,"identity":"3cba6064-a17c-4208-8754-ad62c7cae891","added_by":"auto","created_at":"2026-04-26 15:34:28","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":1195817,"visible":true,"origin":"","legend":"\u003cp\u003eSampling of the regions. IVIM-derived D* color-coded map \u003cstrong\u003e(a)\u003c/strong\u003e and the native axial FLAIR image \u003cstrong\u003e(b)\u003c/strong\u003e. After rigid registration of the FLAIR and D* images, ROIs were manually delineated on the FLAIR images, with the sampled regions demonstrated in panels \u003cstrong\u003e(c)\u003c/strong\u003e primary visual cortex, \u003cstrong\u003e(d)\u003c/strong\u003e pontine tegmentum, \u003cstrong\u003e(e)\u003c/strong\u003e posterior thalami, including pulvinar and ventroposteromedial nuclei, \u003cstrong\u003e(f)\u003c/strong\u003e facial segment of postcentral gyrus, \u003cstrong\u003e(g)\u003c/strong\u003e amygdala, \u003cstrong\u003e(h)\u003c/strong\u003e anterior cingulate cortex, and \u003cstrong\u003e(i) \u003c/strong\u003edorsomedial prefrontal cortex (black ROIs) and insular cortex (white ROIs). The ROI area was 60 mm² for panel \u003cstrong\u003e(e)\u003c/strong\u003e, which presents magnified images of the thalami, and approximately 30 mm² for all other regions. The definition of the posterior thalamic ROI encompassing both the ventroposteromedial and pulvinar nuclei follows the method described in reference (18).\u003cem\u003e IVIM\u003c/em\u003e,\u003cem\u003e \u003c/em\u003eintravoxel incoherent motion; \u003cem\u003eD*\u003c/em\u003e, diffusion coefficient; \u0026nbsp;\u003cem\u003eFLAIR, \u003c/em\u003efluid attenuated inversion recovery; \u003cem\u003eROI\u003c/em\u003e, \u003cem\u003eregion of interest;\u003c/em\u003e\u003c/p\u003e","description":"","filename":"Figure2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-9349009/v1/64e7e2c5cdbaa20b048f38b5.jpg"},{"id":107832582,"identity":"3059e051-92de-488c-a759-a8da6dd4d41c","added_by":"auto","created_at":"2026-04-26 15:34:28","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":1759998,"visible":true,"origin":"","legend":"\u003cp\u003eIllustration of the distribution of right-to-left asymmetry indices (AI) of the IVIM-derived parameters in the posterior thalamus of patients with chronic migraine during the interictal phase and healthy controls. A significantly higher AI is observed for the composite IVIM parameter \u003cem\u003efD*\u003c/em\u003ein the chronic migraine group compared with controls, which remained significant after correction. By contrast, the interhemispheric AIs of individual parameters \u003cem\u003eD*\u003c/em\u003e and \u003cem\u003ef \u003c/em\u003eare not significantly different from control subjects after correction analysis. These results may suggest enhanced interhemispheric difference of posterior thalamic perfusion at the capillary level, as reflected by the increased asymmetry of the combined IVIM-derived \u003cem\u003efD*\u003c/em\u003e parameter.\u003c/p\u003e","description":"","filename":"Figure3.png","url":"https://assets-eu.researchsquare.com/files/rs-9349009/v1/d61731331014cf59a389b2ff.png"},{"id":108493697,"identity":"d95473ee-7a47-450d-bb56-f47653c7a24f","added_by":"auto","created_at":"2026-05-05 10:01:21","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":5417147,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-9349009/v1/25065aa3-d927-4235-a7b1-bddcaf7db296.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Assessment of Cerebral Perfusion Asymmetry in Chronic Migraine Patients using Intravoxel Incoherent Motion (IVIM)–Derived Pseudodiffusion Coefficient and Perfusion Fraction","fulltext":[{"header":"INTRODUCTION","content":"\u003cp\u003eChronic migraine (CM) is a disabling condition that affects 1\u0026ndash;2% of people globally, characterized by the presence of headache for more than 15 days per month or meeting the International Classification of Headache Disorders, 3rd edition (ICHD-3) criteria for migraine for more than 8 days per month [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. CM is more frequently associated with comorbid conditions than episodic migraine, including sleep disturbances, anxiety, and allodynia [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. Unlike episodic migraine, CM may be characterized by persistent neurobiological changes. Resting-state functional MRI (rs-fMRI) connectivity studies have demonstrated altered brain networks in migraine patients compared to healthy controls, highlighting the role of ongoing symptoms and central sensitization during the interictal phase, especially in CM [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eMigraine is clinically characterized by recurrent unilateral or side-predominant headache, sometimes accompanied by lateralized sensory symptoms. Repeated activation of the trigeminovascular system in conjunction with cortical spreading depression is postulated to initially propagate within a single hemisphere before spreading bilaterally. Regional engagement of these mechanisms during the early phase of migraine attacks is associated with vasodilation during the ictal period, followed by subsequent vasoconstriction [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. These pathophysiological processes have prompted neuroimaging studies to investigate regional perfusion differences during the peri-ictal state [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. Although several studies reported asymmetric cortical network activation during the pain-free interictal phase, it remains unclear whether a persistent hemispheric difference of cerebral regional perfusion exists during the interictal phase of CM [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eNon-contrast perfusion imaging techniques, such as arterial spin labeling (ASL), have attracted increasing attention in migraine research. In this context, intravoxel incoherent motion diffusion-weighted imaging (IVIM-DWI) has emerged as a promising non-contrast MRI technique capable of distinguishing true tissue diffusion of water molecules from microvascular perfusion, which was originally proposed by Le Bihan et al [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. The IVIM concept is hypothesized to estimate perfusion in tissue via incoherent motion of water molecules within random capillaries, formerly reported as a pseudo-diffusion effect at low diffusion-sensitizing gradients (b-values typically between 0 and 200 s/mm\u0026sup2;), which is not concurrently observed in the higher b-values in addition to normal diffusion signal decay [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. IVIM-derived parameters, including the pseudo-diffusion coefficient \u003cem\u003e(D*)\u003c/em\u003e, perfusion fraction \u003cem\u003e(f)\u003c/em\u003e, and their composite metric \u003cem\u003e(fD*)\u003c/em\u003e, may provide an opportunity to assess tissue-level quantification of microvascular perfusion while simultaneously characterizing true molecular diffusion of water.\u003c/p\u003e \u003cp\u003eTo the best of our knowledge, the role of IVIM-DWI-derived perfusion in migraine is underexplored either during the attack or interictal phase. In the present study, our objective was to explore right-to-left cerebral hemispheric differences in IVIM-derived perfusion parameters in previously defined migraine-implicated brain regions during the interictal phase of patients with CM.\u003c/p\u003e"},{"header":"MATERIAL AND METHOD","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eEthics information\u003c/h2\u003e \u003cp\u003e This single-center retrospective study was performed in accordance with the Declaration of Helsinki. Institutional review board approval was obtained from the local ethics committee (IRB no: 2025.623.IRB2.281). The requirement for written informed consent was waived by the ethics committee.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eStudy Population\u003c/h3\u003e\n\u003cp\u003eThis single-center retrospective study was conducted between January 2023 and November 2025 and included patients presenting to the outpatient clinic with chronic headache. Among these patients, the diagnosis of CM was established in accordance with the ICHD-3. Diagnostic criteria included headache (migraine-like or tension-type-like) occurring on \u0026ge;\u0026thinsp;15 days per month for more than 3 months, or headache occurring on \u0026ge;\u0026thinsp;8 days per month for at least 3 months that fulfilled criteria for migraine with aura with at least five attacks or migraine without aura that was not better accounted for by another headache disorder [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. The brain MRI with IVIM-DWI was performed to rule out secondary intracranial pathology or any emergent causes of chronic headache for each case. The inclusion criteria comprised patients with CM who underwent brain MRI with IVIM-DWI during the interictal phase, defined as the absence of headache, aura, or other migraine-related symptoms at the time of imaging, and with at least 48 hours having elapsed since the most recent migraine attack. The exclusion criteria were as follows: (i) brain MRI with IVIM-DWI performed during an active migraine attack, defined by the presence of headache, aura, or other migraine-related symptoms at the time of imaging or within 48 hours after such symptoms. (ii) non-migraine type primary chronic headache disorders, such as trigeminal autonomic cephalalgias, or cluster headache; (iii) secondary headache disorders, including those attributed to head trauma, vascular disorders, substance or medication withdrawal, intracranial tumors, intracranial hypotension or hypertension, or pathology of the paranasal sinuses or aerodigestive tract; (iv) age younger than 18 years; (v) presence of incidental intracranial imaging abnormalities, regardless of clinical relevance to headache, including demyelinating lesions, acute or chronic cerebral infarction, vascular malformations, tumors, or equivalent structural abnormalities on brain MRI; (vi) presence of major concurrent systemic disorders, such as diabetes mellitus, hypertension, vasculitis, or renal failure; and (vii) inadequate image quality due to significant motion artifacts, geometric distortion, poor signal-to-noise ratio, or incomplete IVIM-DWI or fluid-attenuated inversion recovery (FLAIR) sequences. During the study period, 177 patients with chronic headache underwent brain MRI with IVIM-DWI to evaluate for potential secondary causes. Among these, 25 patients had experienced an active headache within the preceding 48 hours, as documented on the MRI request forms. Of the remaining 152 patients who underwent brain MRI with IVIM-DWI during a headache-free period, only 30 fulfilled the diagnostic criteria for CM in the interictal phase. The study group selection process is summarized in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e as a flowchart.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eThirty age- and sex-matched healthy control subjects were randomly recruited from individuals undergoing routine health check-up examinations to undergo IVIM-DWI imaging. Controls had no history of migraine or other primary or secondary headache disorders, no headache within the preceding 48 hours, and no aura-suggesting symptoms within the past 12 months. Individuals with a history of neurologic or systemic disorders, illicit drug use, long-term medication use, or current use of analgesic or vasoactive medications were excluded. All control subjects had no clinically significant abnormalities on brain MRI.\u003c/p\u003e\n\u003ch3\u003eIntravoxel Incoherent Motion MRI Protocol\u003c/h3\u003e\n\u003cdiv class=\"Heading\"\u003eIntravoxel Incoherent Motion MRI Protocol\u003c/div\u003e \u003cp\u003eDWI was acquired using a single-shot echo-planar imaging sequence on a 1.5-T MRI system (Aera; Siemens Healthineers, Erlangen, Germany). Imaging was performed using a standard 16-channel receiver head coil. DWI was acquired in the axial plane with the following parameters: repetition time/echo time (TR/TE), 5100/115 ms; field of view (FOV), 230 \u0026times; 230 mm; slice thickness (ST), 3.0 mm; and flip angle (FA), 90\u0026deg;. Multiple diffusion-sensitizing gradients were applied (b\u0026thinsp;=\u0026thinsp;0, 50, 100, 150, 200, 250, 300, 350, 400, 600, and 800 s/mm\u0026sup2;) to enable IVIM analysis. The IVIM signal decay was modeled using the following bi-exponential function:\u003cdiv id=\"Equa\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equa\" name=\"EquationSource\"\u003e\n$$\\:S\\left(b\\right)=S0\\left[f.{e}^{-bD*}+\\left(1-f\\right).{e}^{-bD}\\right]$$\u003c/div\u003e\u003c/div\u003e\u003c/p\u003e \u003cp\u003e\u003cem\u003eD\u003c/em\u003e represents the true diffusion coefficient, \u003cem\u003eD*\u003c/em\u003e the pseudo-diffusion coefficient associated with microvascular perfusion, and \u003cem\u003ef\u003c/em\u003e represents the perfusion fraction. The classical method of segmented fitting was utilized to measure perfusion-related parameters, \u003cem\u003eD*\u003c/em\u003e and \u003cem\u003ef\u003c/em\u003e maps. First, \u003cem\u003eD\u003c/em\u003e was estimated by applying a linear mono-exponential diffusion fit to higher b-value data (b \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\ge\\:200\\)\u003c/span\u003e\u003c/span\u003e s/mm\u0026sup2;), where the contribution of perfusion on the diffusion decay curve is negligible. Subsequently, \u003cem\u003ef\u003c/em\u003e and \u003cem\u003eD*\u003c/em\u003e were derived by fitting the fixed \u003cem\u003eD\u003c/em\u003e value into the non-linear bi-exponential diffusion function using low-b value data (b\u0026thinsp;=\u0026thinsp;0, 50, 100, 150 s/mm\u0026sup2;), where the perfusion-related effect upon the diffusion function is most prominent. The \u003cem\u003eD*\u003c/em\u003e and \u003cem\u003ef\u003c/em\u003e maps were registered rigidly with FLAIR images to increase the spatial conspicuity of the cerebral cortex as well as deep gray nuclei and to eliminate any geometrical distortion attributed to echo-planar DWI. The following parameters were used to acquire FLAIR imaging: time to inversion (TI), 2300 ms; TR/TE, 7500/85 ms; FOV, 230 \u0026times; 230 mm; ST, 3.0 mm; and FA 150\u0026deg;. The entire segmented-fitting-based IVIM-DWI modelling and generation of \u003cem\u003eD*\u003c/em\u003e and \u003cem\u003ef\u003c/em\u003e maps, followed by rigid registration with FLAIR imaging, was computed in Olea Sphere\u0026reg; version 3.0 software (Olea Medical, La Ciotat, France).\u003c/p\u003e\n\u003ch3\u003eROI-based Analysis of Brain Parenchyma\u003c/h3\u003e\n\u003cp\u003eBased on functional imaging\u0026ndash;derived evidence from the contemporary literature, eight key anatomical locations were selected for region-of-interest (ROI) placement to measure IVIM parameters. Since performing ROI analysis across the entire gyral system is not feasible, ROI placement was restricted to six cortical regions implicated in migraine, along with the posterior thalamus and the dorsal pontine region, resulting in a total of eight regions. The hypothesized associations between ROI-placed regions and CM pathophysiology are summarized in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e, together with relevant supportive literature [\u003cspan additionalcitationids=\"CR14 CR15 CR16\" citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. After co-registration of the \u003cem\u003eD*\u003c/em\u003e and f maps with the FLAIR images, circular ROIs with an area of 30\u0026ndash;60 mm\u0026sup2; were placed, with the exact size adjusted according to the cortical thickness of six cortical regions considered relevant in migraine pathophysiology. ROI placement was performed on the FLAIR series to ensure optimal conspicuity and to allow precise delineation within the cerebral cortex, avoiding inclusion of underlying subcortical white matter. The initial ROI positions were subsequently verified on the rigidly registered \u003cem\u003eD*\u003c/em\u003e and \u003cem\u003ef\u003c/em\u003e maps to exclude spatial misregistration. Mild geometric distortions were observed only in the amygdala and dorsomedial prefrontal cortex (dmPFC), attributable to echo-planar DWI\u0026ndash;related susceptibility effects adjacent to the cranial base, which were visually corrected using the \u003cem\u003eD*\u003c/em\u003e maps. Similar ROI placement was achieved by precisely mirroring each ROI to the anatomically corresponding contralateral cortical location. Measurements of the posterior thalamus and pontine tegmentum were likewise obtained using exact contralateral mirrored ROIs. Specifically, the posterior thalamic ROI encompassed the pulvinar and ventroposteromedial (VPM) nuclei, consistent with the probabilistic 3D subsegmentation model proposed by Chen et al [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. The ROI placement method is illustrated in Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e. All measurements were performed by two raters: a central rater with 8 years of experience in neuroimaging (Y.E.S.) and a co-rater with 7 years of experience (A.P.), who independently performed ROI placement and measurements for the entire cohort.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eRegions of Interest and proposed pathophysiological roles in migraine\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"2\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003e*Region of interest locations (ROI)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eProposed pathophysiological role in migraine\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eInsula\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSalience and interoceptive integration of pain\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAnterior cingulate gyrus (ACC)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAffective pain processing and modulation\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDorsomedial prefrontal cortex (dmPFC)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCognitive top-down modulation of pain\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePostcentral gyrus facial homunculus (S1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSensory\u0026ndash;discriminative pain processing\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePrimary visual cortex (V1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCortical hyperexcitability, cortical spreading depolarization, and visual sensitivity\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAmygdala\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eEmotional modulation of pain and stress\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePosterior thalamus (Ventroposteromedial and pulvinar nuclei)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eThalamocortical sensory integration\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePontine tegmentum\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePain modulation and attack-related trigeminovascular activity\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"2\"\u003e*ROI selection was guided by converging evidence from prior functional neuroimaging and experimental studies implicating distributed cortical and subcortical networks involved in pain processing, sensory integration, salience attribution, cortical excitability, and brainstem modulation in migraine (see the references 13\u0026ndash;17 for details).\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eFor each ROI-based measurement, the asymmetry index (AI) was calculated from the derived IVIM perfusion parameters \u003cem\u003e(f, D*, and fD*).\u003c/em\u003e An absolute AI value greater than 10% was considered indicative of asymmetric perfusion between the right and left relevant cortical ROI-based measurements [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e].\u003cdiv id=\"Equb\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equb\" name=\"EquationSource\"\u003e\n$$\\:Asymmetry\\:Index=\\frac{|{\\varvec{R}\\varvec{O}\\varvec{I}}_{\\varvec{r}\\varvec{i}\\varvec{g}\\varvec{h}\\varvec{t}}-{\\varvec{R}\\varvec{O}\\varvec{I}}_{\\varvec{l}\\varvec{e}\\varvec{f}\\varvec{t}}|}{({\\varvec{R}\\varvec{O}\\varvec{I}}_{\\varvec{r}\\varvec{i}\\varvec{g}\\varvec{h}\\varvec{t}}+{\\varvec{R}\\varvec{O}\\varvec{I}}_{\\varvec{l}\\varvec{e}\\varvec{f}\\varvec{t}})}\\:\\times\\:100$$\u003c/div\u003e\u003c/div\u003e\u003c/p\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003eStatistical Analysis\u003c/h2\u003e \u003cp\u003eStatistical analyses were conducted using SPSS (version 28.0; IBM Corp., Armonk, NY, USA). Normality was evaluated with the Shapiro-Wilk test. Group comparisons were performed using independent-samples Student\u0026rsquo;s t tests for normally distributed variables and Mann-Whitney U tests for non-parametric variables. ROI-based hemispheric asymmetry indices from eight brain regions were compared between CM patients and healthy controls. Multiple comparisons were controlled using false discovery rate (FDR) correction based on the Benjamini-Hochberg (BH) method. Inter-rater agreement of ROI placement on \u003cem\u003eD*\u003c/em\u003e and \u003cem\u003ef\u003c/em\u003e maps was assessed using the intraclass correlation coefficient (ICC), calculated with a two-way random-effects model for absolute agreement between both raters.\u003c/p\u003e \u003c/div\u003e"},{"header":"RESULTS","content":"\u003cp\u003eThe mean age was 36.2\u0026thinsp;\u0026plusmn;\u0026thinsp;12.3 years in the CM group (18 females / 12 males) and 36.8\u0026thinsp;\u0026plusmn;\u0026thinsp;13.1 years in the healthy control group (18 females / 12 males), with no significant difference between groups (p\u0026thinsp;=\u0026thinsp;0.68). Among the 8 different brain locations, the distributions of absolute \u003cem\u003eD*, f\u003c/em\u003e, and \u003cem\u003efD*\u003c/em\u003e were not significantly different between the right and left cerebral hemispheres \u003cb\u003e(\u003c/b\u003eTable\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e\u003cb\u003e).\u003c/b\u003e Inter-rater agreement of ROI placement between the two raters was excellent for \u003cem\u003eD*\u003c/em\u003e (ҡ = 0.94) and good for \u003cem\u003ef\u003c/em\u003e (ҡ = 0.79) measurements.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eHemispheric comparison of ROI-based absolute IVIM parameters in chronic migraine and control groups\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"8\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eROI\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c5\" namest=\"c3\"\u003e \u003cp\u003eChronic Migraine Group (n:30)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c8\" namest=\"c6\"\u003e \u003cp\u003eControl subjects (n:30)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eParameter\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eRight Hemisphere\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eLeft Hemisphere\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003ep\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eRight Hemisphere\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eLeft Hemisphere\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003ep\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAnterior Cingulate Cortex\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003efD*\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.78\u0026thinsp;\u0026plusmn;\u0026thinsp;0.44\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.63\u0026thinsp;\u0026plusmn;\u0026thinsp;0.47\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.19ᵃ\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.69\u0026thinsp;\u0026plusmn;\u0026thinsp;0.32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.72\u0026thinsp;\u0026plusmn;\u0026thinsp;0.35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.71ᵃ\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAnterior Cingulate Cortex\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eD*\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e11.44\u0026thinsp;\u0026plusmn;\u0026thinsp;5.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e12.94\u0026thinsp;\u0026plusmn;\u0026thinsp;5.56\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.13ᵃ\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e13.46\u0026thinsp;\u0026plusmn;\u0026thinsp;4.33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e13.43\u0026thinsp;\u0026plusmn;\u0026thinsp;4.51\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.98ᵃ\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAnterior Cingulate Cortex\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003ef\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.07 (0.05)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.04 (0.04)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.11ᵇ\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.05\u0026thinsp;\u0026plusmn;\u0026thinsp;0.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.06\u0026thinsp;\u0026plusmn;\u0026thinsp;0.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.32ᵃ\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eInsula\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003efD*\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.90\u0026thinsp;\u0026plusmn;\u0026thinsp;0.55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.77\u0026thinsp;\u0026plusmn;\u0026thinsp;0.45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.24ᵃ\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.66 (0.53)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.68 (0.40)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.81ᵇ\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eInsula\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eD*\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e15.72\u0026thinsp;\u0026plusmn;\u0026thinsp;4.17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e12.09\u0026thinsp;\u0026plusmn;\u0026thinsp;4.19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.06ᵃ\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e13.30\u0026thinsp;\u0026plusmn;\u0026thinsp;3.27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e12.85\u0026thinsp;\u0026plusmn;\u0026thinsp;4.75\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.66ᵃ\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eInsula\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003ef\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.06\u0026thinsp;\u0026plusmn;\u0026thinsp;0.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.07\u0026thinsp;\u0026plusmn;\u0026thinsp;0.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.34ᵃ\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.06 (0.04)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.06 (0.03)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.79ᵇ\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePrimary visual cortex (V1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003efD*\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.77\u0026thinsp;\u0026plusmn;\u0026thinsp;0.53\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.86\u0026thinsp;\u0026plusmn;\u0026thinsp;0.55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.49ᵃ\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.81 (0.58)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.94 (0.65)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.58ᵇ\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePrimary visual cortex (V1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eD*\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e12.61\u0026thinsp;\u0026plusmn;\u0026thinsp;4.17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e12.02\u0026thinsp;\u0026plusmn;\u0026thinsp;3.93\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.51ᵃ\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e12.52\u0026thinsp;\u0026plusmn;\u0026thinsp;3.52\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e12.73\u0026thinsp;\u0026plusmn;\u0026thinsp;4.18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.81ᵃ\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePrimary visual cortex (V1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003ef\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.05 (0.07)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.06 (0.05)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.22ᵇ\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.08\u0026thinsp;\u0026plusmn;\u0026thinsp;0.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.08\u0026thinsp;\u0026plusmn;\u0026thinsp;0.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.55ᵃ\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePostcentral gyrus facial homunculus (S1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003efD*\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.62 (0.76)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.88 (0.89)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.14ᵇ\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.80 (0.78)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.09 (1.39)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.11ᵇ\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePostcentral gyrus facial homunculus (S1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eD*\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e12.94\u0026thinsp;\u0026plusmn;\u0026thinsp;3.67\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e13.14\u0026thinsp;\u0026plusmn;\u0026thinsp;4.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.77ᵃ\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e14.90\u0026thinsp;\u0026plusmn;\u0026thinsp;3.71\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e13.59\u0026thinsp;\u0026plusmn;\u0026thinsp;5.24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.19ᵃ\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePostcentral gyrus facial homunculus (S1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003ef\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.05 (0.05)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.06 (0.06)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.15ᵇ\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.07\u0026thinsp;\u0026plusmn;\u0026thinsp;0.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.10\u0026thinsp;\u0026plusmn;\u0026thinsp;0.08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.04ᵃ\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDorsomedial Prefrontal Cortex (dmPFC)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003efD*\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.69\u0026thinsp;\u0026plusmn;\u0026thinsp;0.44\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.53\u0026thinsp;\u0026plusmn;\u0026thinsp;0.30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.10ᵃ\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.75\u0026thinsp;\u0026plusmn;\u0026thinsp;0.47\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.79\u0026thinsp;\u0026plusmn;\u0026thinsp;0.41\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.60ᵃ\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDorsomedial Prefrontal Cortex (dmPFC)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eD*\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e13.51\u0026thinsp;\u0026plusmn;\u0026thinsp;5.25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e14.82\u0026thinsp;\u0026plusmn;\u0026thinsp;4.43\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.28ᵃ\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e13.02\u0026thinsp;\u0026plusmn;\u0026thinsp;3.94\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e14.20\u0026thinsp;\u0026plusmn;\u0026thinsp;4.41\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.24ᵃ\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDorsomedial Prefrontal Cortex (dmPFC)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003ef\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.05 (0.03)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.03 (0.03)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.10ᵇ\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.06\u0026thinsp;\u0026plusmn;\u0026thinsp;0.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.06\u0026thinsp;\u0026plusmn;\u0026thinsp;0.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.95ᵃ\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAmygdala\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003efD*\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.68\u0026thinsp;\u0026plusmn;\u0026thinsp;0.32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.83\u0026thinsp;\u0026plusmn;\u0026thinsp;0.55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.12ᵃ\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.68\u0026thinsp;\u0026plusmn;\u0026thinsp;0.24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.87\u0026thinsp;\u0026plusmn;\u0026thinsp;0.43\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.02ᵃ\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAmygdala\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eD*\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e15.38\u0026thinsp;\u0026plusmn;\u0026thinsp;3.61\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e15.18\u0026thinsp;\u0026plusmn;\u0026thinsp;5.52\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.84ᵃ\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e14.76 (5.56)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e15.89 (5.45)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.31ᵇ\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAmygdala\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003ef\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.05 (0.03)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.05 (0.04)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.24ᵇ\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.05\u0026thinsp;\u0026plusmn;\u0026thinsp;0.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.06\u0026thinsp;\u0026plusmn;\u0026thinsp;0.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.13ᵃ\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePosterior thalamus\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003efD*\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.87\u0026thinsp;\u0026plusmn;\u0026thinsp;0.41\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.87\u0026thinsp;\u0026plusmn;\u0026thinsp;0.42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.99ᵃ\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.87 (0.45)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.77 (0.51)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.70ᵇ\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePosterior thalamus\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eD*\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e17.13\u0026thinsp;\u0026plusmn;\u0026thinsp;2.97\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e16.78\u0026thinsp;\u0026plusmn;\u0026thinsp;3.51\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.62ᵃ\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e16.48\u0026thinsp;\u0026plusmn;\u0026thinsp;3.68\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e15.93\u0026thinsp;\u0026plusmn;\u0026thinsp;3.35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.61ᵃ\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePosterior thalamus\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003ef\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.05\u0026thinsp;\u0026plusmn;\u0026thinsp;0.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.05\u0026thinsp;\u0026plusmn;\u0026thinsp;0.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.96ᵃ\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.05\u0026thinsp;\u0026plusmn;\u0026thinsp;0.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.05\u0026thinsp;\u0026plusmn;\u0026thinsp;0.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.07ᵃ\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePontine Tegmentum\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003efD*\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.93\u0026thinsp;\u0026plusmn;\u0026thinsp;0.42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.94\u0026thinsp;\u0026plusmn;\u0026thinsp;0.45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.92ᵃ\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.96\u0026thinsp;\u0026plusmn;\u0026thinsp;0.48\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.95\u0026thinsp;\u0026plusmn;\u0026thinsp;0.44\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.89ᵃ\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePontine Tegmentum\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eD*\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e16.30\u0026thinsp;\u0026plusmn;\u0026thinsp;2.81\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e15.68\u0026thinsp;\u0026plusmn;\u0026thinsp;4.31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.46ᵃ\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e15.87\u0026thinsp;\u0026plusmn;\u0026thinsp;3.25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e16.10\u0026thinsp;\u0026plusmn;\u0026thinsp;3.94\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.69ᵃ\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePontine Tegmentum\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003ef\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.06\u0026thinsp;\u0026plusmn;\u0026thinsp;0.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.06\u0026thinsp;\u0026plusmn;\u0026thinsp;0.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.68ᵃ\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.06\u0026thinsp;\u0026plusmn;\u0026thinsp;0.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.06\u0026thinsp;\u0026plusmn;\u0026thinsp;0.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.76ᵃ\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"8\" nameend=\"c8\" namest=\"c1\"\u003e \u003cp\u003ea: \u003cem\u003eStudent\u0026rsquo;s t-test\u003c/em\u003e\u003c/p\u003e \u003cp\u003eb: \u003cem\u003eMann-Whitney U test\u003c/em\u003e\u003c/p\u003e \u003cp\u003e\u003cem\u003eUnits\u003c/em\u003e: D*, fD* (\u0026times;10⁻\u0026sup3; mm\u0026sup2;/s); f (unitless).\u003c/p\u003e \u003cp\u003e\u003cem\u003eROI\u003c/em\u003e, Region of Interest; \u003cem\u003eIVIM\u003c/em\u003e, Intravoxel incoherent motion\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eAnalysis of hemispheric AI for IVIM-derived diffusion and perfusion parameters (\u003cem\u003eD*, f, and fD*\u003c/em\u003e) demonstrated a mild degree of right\u0026ndash;left asymmetry in both the CM group and healthy controls. After BH correction for multiple comparisons, no significant increase in the AI of IVIM parameters was noted in the CM group compared to the control group across six cortical regions or in the pontine tegmentum \u003cb\u003e(\u003c/b\u003eTable\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e\u003cb\u003e)\u003c/b\u003e. In contrast, the median \u003cem\u003efD*\u003c/em\u003e AI of the posterior thalamus was 27.91 (IQR: 16.87) in the CM group and 10.43 (IQR: 19.58) in the control group, indicating a significantly greater absolute right\u0026ndash;left asymmetry of combined perfusion fraction and pseudo-diffusion in CM patients compared to controls (p\u0026thinsp;=\u0026thinsp;0.002, q\u0026thinsp;=\u0026thinsp;0.017 after FDR correction).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eGroup comparison of the asymmetry index of IVIM-based perfusion parameters in chronic migraine and the control group\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRegion\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eParameter\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eChronic Migraine (n:30)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eHealthy Control (n:30)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003ep\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eq (BH/FDR)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAnterior Cingulate Cortex\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003efD* AI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e33.65\u0026thinsp;\u0026plusmn;\u0026thinsp;18.22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e23.20\u0026thinsp;\u0026plusmn;\u0026thinsp;16.79\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.024ᵃ\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.098\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAnterior Cingulate Cortex\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eD* AI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e16.85 (16.64)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e11.92 (17.89)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.348ᵇ\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.813\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAnterior Cingulate Cortex\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ef AI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e30.05 (24.90)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e20.00 (30.04)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.062ᵇ\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.214\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eInsula\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003efD* AI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e27.82 (23.44)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e25.53 (30.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.888ᵇ\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.888\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eInsula\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eD* AI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e16.69 (17.24)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e16.21 (17.76)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.540ᵇ\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.813\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eInsula\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ef AI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e23.66 (28.83)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e15.65 (35.14)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.525ᵇ\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.700\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePrimary visual cortex (V1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003efD* AI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e23.94 (26.18)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e16.98 (29.73)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.673ᵇ\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.888\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePrimary visual cortex (V1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eD* AI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e12.97 (16.08)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e10.27 (16.83)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.610ᵇ\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.813\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePrimary visual cortex (V1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ef AI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e20.26 (34.98)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e19.30 (39.75)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.706ᵇ\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.706\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePostcentral gyrus facial homunculus (S1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003efD* AI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e24.30 (26.96)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e32.90 (28.17)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.830ᵇ\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.888\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePostcentral gyrus facial homunculus (S1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eD* AI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e11.24 (10.61)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e10.51 (17.10)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.807ᵇ\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.819\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePostcentral gyrus facial homunculus (S1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ef AI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e29.85 (32.18)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e28.04 (24.63)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.684ᵇ\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.706\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDorsomedial Prefrontal Cortex (dmPFC)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003efD* AI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e30.77\u0026thinsp;\u0026plusmn;\u0026thinsp;24.53\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e20.39\u0026thinsp;\u0026plusmn;\u0026thinsp;14.15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.051ᵃ\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.135\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDorsomedial Prefrontal Cortex (dmPFC)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eD* AI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e11.47 (18.51)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e11.85 (12.02)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.819ᵇ\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.819\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDorsomedial Prefrontal Cortex (dmPFC)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ef AI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e29.72 (28.77)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e19.34 (26.40)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.093ᵇ\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.214\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAmygdala\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003efD* AI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e25.77\u0026thinsp;\u0026plusmn;\u0026thinsp;16.70\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e23.53\u0026thinsp;\u0026plusmn;\u0026thinsp;15.43\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.592ᵃ\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.888\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAmygdala\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eD* AI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e13.07 (14.11)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e12.65 (7.83)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.530ᵇ\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.813\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAmygdala\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ef AI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e29.81\u0026thinsp;\u0026plusmn;\u0026thinsp;20.55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e25.48\u0026thinsp;\u0026plusmn;\u0026thinsp;18.65\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.396ᵃ\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.633\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePosterior Thalamus\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003efD* AI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e27.91 (16.87)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e10.43 (19.58)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.002ᵇ\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e0.017\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePosterior Thalamus\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eD* AI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6.89 (6.70)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e11.26 (13.77)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.018ᵇ\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.147\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePosterior Thalamus\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ef AI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e21.61 (17.56)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e10.14 (15.77)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.016ᵇ\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.125\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePontine Tegmentum\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003efD* AI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e18.97 (17.47)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e11.07 (16.46)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.070ᵇ\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.140\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePontine Tegmentum\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eD* AI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10.10 (9.93)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5.58 (13.57)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.066ᵇ\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.263\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePontine Tegmentum\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ef AI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e15.41 (22.99)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e10.78 (11.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.107ᵇ\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.214\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"6\" nameend=\"c6\" namest=\"c1\"\u003e \u003cp\u003e\u003csup\u003e\u003cem\u003ea\u003c/em\u003e\u003c/sup\u003e \u003cem\u003eStudent\u0026rsquo;s t-test\u003c/em\u003e\u003c/p\u003e \u003cp\u003e\u003csup\u003e\u003cem\u003eb\u003c/em\u003e\u003c/sup\u003e \u003cem\u003eMann-Whitney U test\u003c/em\u003e\u003c/p\u003e \u003cp\u003e\u003cem\u003eAI\u003c/em\u003e, Asymmetry index; \u003cem\u003eBH-FDR\u003c/em\u003e, Benjamini-Hochberg-False Discovery Rate; \u003cem\u003eIVIM\u003c/em\u003e, intravoxel incoherent motion\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eThe median \u003cem\u003eD*\u003c/em\u003e AI of the posterior thalami was 6.89 (IQR: 6.70) in the CM group and 11.26 (IQR: 13.77) in the control group (p\u0026thinsp;=\u0026thinsp;0.018). Similarly, the median \u003cem\u003ef\u003c/em\u003e asymmetry index was 21.61 (IQR: 17.56) in the CM group and 10.14 (IQR: 15.77) in control subjects (p\u0026thinsp;=\u0026thinsp;0.016). Although both \u003cem\u003eD*\u003c/em\u003e and \u003cem\u003ef\u003c/em\u003e asymmetry indices showed significance in the initial uncorrected analyses, neither remained significant after BH correction for multiple comparisons (q\u0026thinsp;=\u0026thinsp;0.147 and q\u0026thinsp;=\u0026thinsp;0.125, respectively).\u003c/p\u003e \u003cp\u003eFigure \u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e illustrates the distribution of right\u0026ndash;left hemispheric asymmetry of IVIM-DWI\u0026ndash;derived perfusion parameters in the posterior thalami. Although the \u003cem\u003efD*\u003c/em\u003e AI in the anterior cingulate cortex was higher in CM patients than in healthy controls, this effect did not remain significant after BH correction and was therefore considered likely to represent a false-positive finding (p\u0026thinsp;=\u0026thinsp;0.024, q\u0026thinsp;=\u0026thinsp;0.098; Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). In contrast, \u003cem\u003efD*\u003c/em\u003e asymmetry in the bilateral thalamic nuclei remained statistically significant after correction for multiple comparisons.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e"},{"header":"DISCUSSION","content":"\u003cp\u003eThe present study investigated cerebral microvascular alterations in patients with CM during the interictal phase. Using an IVIM-derived perfusion technique, we demonstrated a significantly increased hemispheric asymmetry of the combined perfusion parameter, \u003cem\u003efD*\u003c/em\u003e, in the posterior thalami. In contrast, IVIM-derived perfusion parameters in cortical regions implicated in migraine initiation, propagation, and pain modulation did not show significant lateralized perfusion differences between the cerebral hemispheres. These preliminary findings suggest that persistent hemispheric imbalance in posterior thalamic microvascular perfusion may be involved in CM, potentially reflecting altered function of dorsal thalamic nuclei in the modulation of lateralized nociceptive processing in migraineurs and associated changes in blood\u0026ndash;brain barrier permeability in the posterior thalamus.\u003c/p\u003e \u003cp\u003eThe posterior thalamus, including pulvinar nuclei and VPM, plays a key role in nociceptive processing of the trigeminovascular hypothesis, where the VPM nuclei act as the principal relay for nociceptive transmission to the cortical region in pain perception [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. Another important function of the posterior thalamus is the modulation of pain and visual information [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. During the migraine attack, proposed sterile inflammatory signaling originating at the dura mater is conveyed via afferent trigeminothalamic projections to the VPM nuclei of the thalamus, playing a key role in central sensitization and allodynia [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. The experimental study by Noseda et al. provides direct electrophysiological evidence from in vivo experiments with rats that posterior thalamic nuclei, including VPM nuclei of the thalamus, responded selectively to mechanical, chemical, and electrical stimulation of the dura mater, therefore named as dura-sensitive nuclei. In the same series, the dura-sensitive posterior thalamic neurons function as high-order relays, showing a variety of projections and evoked potentials to visual, parietal, and retrosplenial cortices. The widespread thalamocortical divergence in this in vivo study suggests that nociceptive dural stimuli are associated with visual, cognitive, and perceptual domains of migraine [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eDiffusion tensor imaging\u0026ndash;based probabilistic tractography by Maleki et al. demonstrated non-visual direct pathways from the optic nerve to the pulvinar nuclei and from the pulvinar to multiple associative cortical regions, providing a structural basis for the pulvinar as an important relay of photic signals. This network may allow selective activation of the pulvinar during migraine attacks and offers a mechanistic explanation for visual and other sensory symptoms through its widespread cortical associations [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. Similar to this, Sower et al. proposed that optogenic stimulation or CGRP injection to the posterior thalami elicited the photophobic light aversive behavior, like in migraineurs [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. Beyond the role of posterior thalami in aural symptoms, a rs-fMRI study seeking functional connectivity analysis in migraineurs at the interictal phase demonstrated that migraineurs with cutaneous allodynia presented increased directional inflow from the right medial prefrontal cortex to the right posterior thalamus, along with reduced inflow from the left dorsomedial prefrontal cortex to the left posterior thalamus. In the same study, correlation analysis further revealed disrupted functional connectivity between the posterior thalamus and the cuneus, as well as frontal cortical regions, in migraine patients with allodynia [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe asymmetrical functional connectivity of the bilateral thalamus in migraine with the interictal phase has not yet been shown in perfusion-based imaging studies. Fu et al. reported decreased cerebral blood flow (CBF) in the bilateral thalamus in migraine with aura compared to healthy controls in the pediatric population at interictal period, whereas they did not report abnormal lateralization in thalamic CBF in pseudo-continuous ASL MRI [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]. In our cohort, increased IVIM-derived \u003cem\u003efD*\u003c/em\u003e asymmetry in patients with CM and high attack frequency may reflect lateralized alterations in microvascular regulation or neurovascular coupling between the bilateral posterior thalamic nuclei, supporting the concept of a persistent hemispheric imbalance in regional vascular demand within the thalami. In the present study, although the perfusion fraction \u003cem\u003ef\u003c/em\u003e alone did not reach statistical significance after BH false discovery rate correction, its combination with the less asymmetric pseudo-diffusion coefficient \u003cem\u003eD*\u003c/em\u003e resulted in a synergistic effect, rendering the composite \u003cem\u003efD*\u003c/em\u003e parameter sensitive to interhemispheric differences.\u003c/p\u003e \u003cp\u003eAccording to IVIM biophysical principles, \u003cem\u003eD*\u003c/em\u003e represents flow-related pseudo-diffusion associated with blood velocity and incoherent microvascular motion, whereas the \u003cem\u003ef\u003c/em\u003e parameter reflects the fractional volume of blood within the microvascular compartment [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. Notably, the magnitude of asymmetry was substantially greater for \u003cem\u003ef\u003c/em\u003e than for \u003cem\u003eD*\u003c/em\u003e, suggesting that the observed hemispheric \u003cem\u003efD*\u003c/em\u003e imbalance in our study is driven primarily by asymmetric capillary recruitment or microvascular density within the posterior thalamic nuclei, a pattern more consistent with chronicity rather than transient migraine-related alterations. In contrast to \u003cem\u003ef, D*\u003c/em\u003e is thought to be influenced by flow dynamics and vascular permeability that may be relatively associated with the integrity of the blood\u0026ndash;brain barrier and therefore less susceptible to subtle changes in CM during pain-free interictal phase. Supporting this interpretation, Wu et al. demonstrated that the perfusion fraction \u003cem\u003ef\u003c/em\u003e provides a more stable and reproducible surrogate of CBF, whereas \u003cem\u003eD*\u003c/em\u003e had limited robustness in normal brain parenchyma [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]. Notably, despite these methodological considerations, \u003cem\u003eD*\u003c/em\u003e measurements in the present study demonstrated excellent inter-observer reliability, indicating that observed differences reflect biological rather than technical variability.\u003c/p\u003e \u003cp\u003eBeyond the thalamic findings discussed above, the lack of increased asymmetry of any IVIM-derived perfusion parameter across the cerebral cortex in migraine pathophysiology can be interpreted as the lack of microvascular flow imbalance in the migraine-implicated cortical locations at the symptom-free interictal phase. Consistent with our results, Bai et al. reported no significant right\u0026ndash;left asymmetry or abnormal CBF values in migraine-related cortical regions in a cohort of 18 CM patients studied using pseudo-continuous ASL MRI. In contrast to our findings, their study demonstrated bilateral thalamic hyperperfusion without evidence of hemispheric CBF asymmetry in the thalami of CM patients [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]. It is presumed that aura and visual symptoms arise from cortical spreading depression, a neurophysiological phenomenon accompanied by transient, biphasic alterations in cortical CBF during the aura phase. This process is believed to originate in the occipital cortex and propagate across adjacent cortical regions, often with an initial unilateral predominance [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]. During the symptom-free interictal phase, in the absence of aura or headache, alterations in CBF within primary and secondary associative cortices, as well as pain-modulatory regions, are not expected to manifest as sustained hypo- or hyperperfusion. Despite the high attack frequency characteristic of CM, neither prior ASL studies nor our IVIM-derived microperfusion findings demonstrated consistent inter-hemispheric cortical perfusion asymmetry that could be considered a defining feature of the interictal phase in migraine with or without aura [\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e, \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eOur study presents several limitations. First, the retrospective design and relatively low sample size may limit the reproducibility of our preliminary results. Second, IVIM-derived parameters, particularly the pseudo-diffusion coefficient \u003cem\u003eD*\u003c/em\u003e, are known to be sensitive to noise and organ-specific local factors [\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e]. However, in the current study, \u003cem\u003eD*\u003c/em\u003e demonstrated excellent inter-rater reliability, and the use of a segmented-fitting approach together with rigid registration to FLAIR imaging enhanced the consistency of ROI-based \u003cem\u003eD*\u003c/em\u003e measurements. Third, ROI-based analysis was restricted to predefined cortical and subcortical regions implicated in migraine pathophysiology, which may overlook additional cortical regions associated with perfusion asymmetry on interictal phase of CM. Fourth, imaging was performed exclusively during the interictal phase, and without correlation with the most recent and most frequent attack laterality, disease duration, or treatment status. Finally, due to the cross-sectional design of the present study, longitudinal changes in IVIM-derived perfusion parameters, including their hemispheric asymmetry, as well as the effects of preventive treatments on \u003cem\u003eD, f\u003c/em\u003e, and \u003cem\u003efD*\u003c/em\u003e, were not assessed. Overall, these limitations highlight the necessity for larger, prospective studies with longitudinal imaging to establish the robustness, temporal dynamics, and clinical relevance of IVIM-derived perfusion parameters in CM.\u003c/p\u003e"},{"header":"CONCLUSIONS","content":"\u003cp\u003eIVIM-DWI-based clinical study offers insights into the parenchymal microvascular correlates of CM during the interictal phase. The observed hemispheric asymmetry of IVIM-derived microperfusion parameters in the posterior thalamus supports the concept that side-predominant activation of the trigeminothalamic nociceptive network may drive regional perfusion alterations, thereby contributing to a better understanding of migraine pathophysiology and asymmetric initiation of the proposed cortical spreading depression theory. Future studies with larger cohorts are warranted to validate these results and to further elucidate the potential clinical role of IVIM-DWI during the ictal phases of migraine.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cdiv class=\"DefinitionList\"\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eACC\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eanterior cingulate cortex\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eAI\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003easymmetry index\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eASL\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003earterial spin labeling\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eBH\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eBenjamini\u0026ndash;Hochberg\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eCM\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003echronic migraine\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eCSD\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003ecortical spreading depression, \u003cb\u003eD\u003c/b\u003e\u0026thinsp;=\u0026thinsp;true diffusion coefficient\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eD*\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003epseudo-diffusion coefficient\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003edmPFC\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003edorsomedial prefrontal cortex\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eDWI\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003ediffusion-weighted imaging\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eFA\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eflip angle\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eFLAIR\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003efluid-attenuated inversion recovery\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003ef\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eperfusion fraction\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003efD*\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003ecomposite perfusion parameter\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eFDR\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003efalse discovery rate\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eFOV\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003efield of view\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eIVIM\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eintravoxel incoherent motion\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eROI\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eregion of interest\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eS1\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eprimary somatosensory cortex\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eV1\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eprimary visual cortex\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eVPM\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eventroposteromedial nucleus.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003c/div\u003e"},{"header":"Declarations","content":"\u003ch2\u003eConflict of interest\u003c/h2\u003e\n\u003cp\u003eY.E.Senturk, A.Peker, S.Yuzkan, H.E.Ergin, E.Bulus, and M.S. Shazeeb declare that they have no competing interests.\u003c/p\u003e\n\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\n\u003cp\u003eThe first draft of the manuscript was written by [Yunus Emre Senturk] and [Huseyin Ekin Ergin]. [Sabahattin Yuzkan], [Mohammed Salman Shazeeb], and [Ahmet Peker] contributed to the study conception and design. [Sabahattin Yuzkan], [Yunus Emre Senturk], [Eser Bulus], and [Huseyin Ekin Ergin] contributed to the material preparation, data collection, and analysis. [Ahmet Peker] and [Mohammed Salman Shazeeb] reviewed and edited the manuscript. All authors made substantial contributions to the interpretation of data. All authors critically revised the manuscript. All authors approved the version to be published and agree to be accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eEigenbrodt AK, Ashina H, Khan S et al (2021) Diagnosis and management of migraine in ten steps. Nat Rev Neurol 17:501\u0026ndash;514\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eArnold M (2018) Headache classification committee of the International Headache Society (IHS) the international classification of headache disorders. Cephalalgia 38:1\u0026ndash;211\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKatsarava Z, Buse DC, Manack AN et al (2012) Defining the differences between episodic migraine and chronic migraine. Curr Pain Headache Rep 16:86\u0026ndash;92\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eChou BC, Lerner A, Barisano G et al (2023) Functional MRI and diffusion tensor imaging in migraine: a review of migraine functional and white matter microstructural changes. J Cent Nerv Syst Dis 15:11795735231205413\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBurstein R, Noseda R, Borsook D (2015) Migraine: multiple processes, complex pathophysiology. J Neurosci 35:6619\u0026ndash;6629\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eShimoda M, Hoshikawa K, Oda S et al (2024) Cortical hyperperfusion on MRI arterial spin-labeling during the interictal period of patients with migraine headache. AJNR Am J Neuroradiol 45:686\u0026ndash;692\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKellner-Weldon F, El-Koussy M, Jung S et al (2018) Cerebellar hypoperfusion in migraine attack: incidence and significance. AJNR Am J Neuroradiol 39:435\u0026ndash;440\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eXue T, Yuan K, Cheng P et al (2013) Alterations of regional spontaneous neuronal activity and corresponding brain circuit changes during resting state in migraine without aura. NMR Biomed 26:1051\u0026ndash;1058\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWang T, Chen N, Zhan W et al (2015) Altered effective connectivity of posterior thalamus in migraine with cutaneous allodynia: a resting-state fMRI study with Granger causality analysis. J Headache Pain 17:17\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLe Bihan D, Breton E, Lallemand D et al (1986) MR imaging of intravoxel incoherent motions: application to diffusion and perfusion in neurologic disorders. Radiology 161:401\u0026ndash;407\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLe Bihan D (2019) What can we see with IVIM. MRI? Neuroimage 187:56\u0026ndash;67\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eOlesen J (2018) International classification of headache disorders. Lancet Neurol 17:396\u0026ndash;397\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDai W, Liu RH, Qiu E et al (2021) Cortical mechanisms in migraine. Mol Pain 17:17448069211050246\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBurke MJ, Joutsa J, Cohen AL et al (2020) Mapping migraine to a common brain network. Brain 143:541\u0026ndash;553\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMaleki N, Becerra L, Brawn J et al (2012) Concurrent functional and structural cortical alterations in migraine. Cephalalgia 32:607\u0026ndash;620\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTolner EA, Chen SP, Eikermann-Haerter K (2019) Current understanding of cortical structure and function in migraine. Cephalalgia 39:1683\u0026ndash;1699\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHougaard A, Amin FM, Christensen CE et al (2017) Increased brainstem perfusion, but no blood\u0026ndash;brain barrier disruption, during attacks of migraine with aura. Brain 140:1633\u0026ndash;1642\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eChen Z, Jia Z, Chen X et al (2017) Volumetric abnormalities of thalamic subnuclei in medication-overuse headache. J Headache Pain 18:82\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHauf M, Slotboom J, Nirkko A et al (2009) Cortical regional hyperperfusion in nonconvulsive status epilepticus measured by dynamic brain perfusion CT. AJNR Am J Neuroradiol 30:693\u0026ndash;698\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFerrari MD, Goadsby PJ, Burstein R et al (2022) Migraine Nat Rev Dis Primers 8:2\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGoadsby PJ (2012) Pathophysiology of migraine. Ann Indian Acad Neurol 15(Suppl 1):S15\u0026ndash;22\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHerrero MT, Barcia C, Navarro JM (2002) Functional anatomy of thalamus and basal ganglia. Childs Nerv Syst 18:386\u0026ndash;404\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBurstein R, Yamamura H, Malick A et al (1998) Chemical stimulation of the intracranial dura induces enhanced responses to facial stimulation in brain stem trigeminal neurons. J Neurophysiol 79:964\u0026ndash;982\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eNoseda R, Jakubowski M, Kainz V et al (2011) Cortical projections of functionally identified thalamic trigeminovascular neurons: implications for migraine headache and its associated symptoms. J Neurosci 31:14204\u0026ndash;14217\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMaleki N, Becerra L, Upadhyay J et al (2012) Direct optic nerve pulvinar connections defined by diffusion MR tractography in humans: implications for photophobia. Hum Brain Mapp 33:75\u0026ndash;88\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSowers LP, Wang M, Rea BJ et al (2020) Stimulation of posterior thalamic nuclei induces photophobic behavior in mice. Headache 60:1961\u0026ndash;1981\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFu T, Liu L, Huang X et al (2022) Cerebral blood flow alterations in migraine patients with and without aura: an arterial spin labeling study. J Headache Pain 23:131\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eIima M, Le Bihan D (2016) Clinical intravoxel incoherent motion and diffusion MR imaging: past, present, and future. Radiology 278:13\u0026ndash;32\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWu WC, Chen YF, Tseng HM et al (2015) Caveat of measuring perfusion indexes using intravoxel incoherent motion magnetic resonance imaging in the human brain. Eur Radiol 25:2485\u0026ndash;2492\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBai X, Wang W, Zhang X et al (2022) Cerebral perfusion variance in new daily persistent headache and chronic migraine: an arterial spin-labeled MR imaging study. J Headache Pain 23:156\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMoskowitz MA (2025) Rethinking migraine with aura: why cortical spreading depolarization (depression), not aura, causes headaches. Cephalalgia 45:03331024251370629\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRusso A, Silvestro M, Tessitore A et al (2023) Arterial spin labeling MRI applied to migraine: current insights and future perspectives. J Headache Pain 24:71\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGil-Gouveia R, Pinto J, Figueiredo P et al (2017) An arterial spin labeling MRI perfusion study of migraine without aura attacks. Front Neurol 8:280\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSharifzadeh Javidi S, Shirazinodeh A, Saligheh Rad H (2023) Intravoxel incoherent motion quantification dependent on measurement SNR and tissue perfusion: a simulation study. J Biomed Phys Eng 13:555\u0026ndash;562\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Chronic Migraine, Magnetic Resonance Imaging (MRI), Intravoxel Incoherent Motion (IVIM), Asymmetry Index (AI), Headache","lastPublishedDoi":"10.21203/rs.3.rs-9349009/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-9349009/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003ePurpose\u003c/h2\u003e \u003cp\u003eChronic migraine (CM) is associated with persistent neurobiological alterations beyond episodic attacks. Cerebral microvascular perfusion change during the interictal phase of CM is underexplored. Emerging Intravoxel incoherent motion (IVIM) imaging provides diffusion-derived pseudo-perfusion parameters that reflect regional microvascular alterations in the brain parenchyma. This study aimed to investigate the right-to-left hemispheric asymmetry of IVIM-derived perfusion parameters in migraine-implicated cortical and subcortical regions during the interictal phase of CM.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eThirty patients with CM imaged during the interictal phase, and 30 age- and sex-matched healthy controls underwent IVIM imaging. IVIM parameters, including the pseudo-diffusion coefficient (D*), perfusion fraction (f), and their composite metric (fD*), were estimated using segmented bi-exponential fitting. The circular region-of-interest analysis was performed bilaterally in migraine-implicated cortical and subcortical regions, as described in contemporary literature. Asymmetry indices of IVIM parameters were measured and compared between groups using false discovery rate correction.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eNo significant increase in hemispheric asymmetry was observed in cortical regions in patients with CM compared to controls. In contrast, the posterior thalamus, comprising the ventroposteromedial and pulvinar nuclei, demonstrated significantly greater fD* asymmetry in CM (median asymmetry index: 27.91 vs 10.43; p\u0026thinsp;=\u0026thinsp;0.002, q\u0026thinsp;=\u0026thinsp;0.017). Inter-rater agreement of ROI placement was excellent for \u003cem\u003eD*\u003c/em\u003e (ҡ = 0.94) and good for \u003cem\u003ef\u003c/em\u003e (ҡ = 0.79) for each measurement.\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e \u003cp\u003eChronic migraine is associated with increased hemispheric asymmetry of IVIM-derived microperfusion in the posterior thalamus during the interictal phase, suggesting lateralized thalamic microvascular alterations in CM.\u003c/p\u003e","manuscriptTitle":"Assessment of Cerebral Perfusion Asymmetry in Chronic Migraine Patients using Intravoxel Incoherent Motion (IVIM)–Derived Pseudodiffusion Coefficient and Perfusion Fraction","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-04-26 15:34:24","doi":"10.21203/rs.3.rs-9349009/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"b8433aa5-5515-4ee3-b010-10793147c332","owner":[],"postedDate":"April 26th, 2026","published":true,"recentEditorialEvents":[{"type":"decision","content":"Rejected","date":"2026-05-04T12:30:25+00:00","index":"","fulltext":""}],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2026-05-04T12:40:14+00:00","versionOfRecord":[],"versionCreatedAt":"2026-04-26 15:34:24","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-9349009","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-9349009","identity":"rs-9349009","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}