Early quantitative stress-perfusion cardiac magnetic resonance identifies coronary microvascular dysfunction in MINOCA patients with otherwise normal cardiac magnetic resonance findings

Early quantitative stress-perfusion cardiac magnetic resonance identifies coronary microvascular dysfunction in MINOCA patients with otherwise normal cardiac magnetic resonance findings | 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 Article Early quantitative stress-perfusion cardiac magnetic resonance identifies coronary microvascular dysfunction in MINOCA patients with otherwise normal cardiac magnetic resonance findings Ramin Sahar, Joel Lenell, Bertil Lindahl, Anne-Marie Montelius, and 4 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8903448/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 5 You are reading this latest preprint version Abstract Coronary microvascular dysfunction (CMD) is a proposed mechanism of myocardial infarction with non-obstructive coronary arteries (MINOCA), but the value of early quantitative stress-perfusion CMR (Q-CMR) in this setting is not fully established. We aimed to assess the prevalence of CMD using Q-CMR in patients with a working diagnosis of MINOCA and otherwise normal CMR findings. Of 46 consecutive MINOCA patients referred for CMR between 2021 and 2024, 23 had normal findings on the CMR at rest and were included. They were compared with age- and sex-matched healthy controls without coronary artery disease, confirmed by coronary CT angiography. All underwent dual-sequence first-pass perfusion CMR at rest and during regadenoson stress. Automated AI-based analysis quantified myocardial blood flow (MBF) and myocardial perfusion reserve (MPR). CMR at rest was considered normal in the absence of edema, late gadolinium enhancement, or other pathology. The MINOCA patients (mean age 63 ± 10 years, 61% female) were scanned a median of 15 days after admission. Compared with controls, they had lower MPR (1.88 ± 0.59 vs. 2.30 ± 0.55; p = 0.013) and lower stress MBF (2.56 ± 0.81 vs. 2.96 ± 0.53 mL/g/min; p = 0.044), while rest MBF was similar. CMD criteria were met in 43% of MINOCA patients and in none of the controls. In conclusions, early Q-CMR identifies reduced stress MBF and MPR in MINOCA patients with otherwise normal CMR and reveals CMD in nearly half of them, supporting microvascular dysfunction as a potential mechanism of myocardial injury. Health sciences/Cardiology Health sciences/Diseases Health sciences/Medical research Cardiac magnetic resonance (CMR) quantitative stress-perfusion CMR (Q-CMR) myocardial infarction with non-obstructive coronary arteries (MINOCA) coronary microvascular dysfunction (CMD) Figures Figure 1 Figure 2 Figure 3 Figure 4 Introduction Myocardial infarction with non-obstructive coronary arteries (MINOCA) represents a diagnostically challenging syndrome with multiple underlying mechanisms, including plaque disruption, coronary embolism, vasospasm, and coronary microvascular dysfunction (CMD). Differentiating these entities is essential because prognosis and treatment strategies vary by etiology 1 . Standard cardiac magnetic resonance (CMR) is recommended to identify conditions such as myocarditis, Takotsubo syndrome, or cardiomyopathies, which account for a substantial proportion of MINOCA presentations 2 – 4 . However, a considerable subset of patients has normal CMR findings despite biochemical evidence of myocardial injury. CMD has emerged as a plausible explanation for ischemic symptoms and troponin elevation when epicardial arteries are unobstructed. Functional abnormalities in the coronary microcirculation - such as impaired vasodilatory capacity, increased resistance, and endothelial dysfunction - can cause reduced perfusion during stress, while resting flow remains preserved. Although increasingly recognized, CMD remains underdiagnosed, partly because conventional imaging lacks the sensitivity to detect subtle microvascular abnormalities. Quantitative stress-perfusion CMR (Q-CMR) offers a noninvasive, radiation-free approach for quantifying myocardial blood flow (MBF) and myocardial perfusion reserve (MPR). Technical advances such as dual-sequence acquisition 5 – 6 and automated pixel-wise perfusion mapping 1 , 7 – 9 have markedly improved reproducibility and clinical applicability 10 . Despite these strengths, the role of Q-CMR in evaluating MINOCA has not been comprehensively defined. We hypothesized that CMD is under-recognized among MINOCA patients with normal conventional CMR and that quantitative perfusion indices would reveal impaired stress perfusion compared with healthy individuals. Therefore, we conducted a prospective evaluation of stress and rest MBF and MPR in MINOCA patients and matched controls using automated dual-sequence Q-CMR. Methods Study population Consecutive patients with a working diagnosis of MINOCA referred for CMR at Uppsala University Hospital between January 2021 and August 2024 were included in the Swedish Web-system for enhancement and Development of Evidence-based care in Heart disease Evaluated According to Recommended Therapies (SWEDEHEART) registry 11 , which prospectively collects nationwide data from patients admitted to coronary care units or other specialized facilities because of suspected acute coronary syndrome. A working diagnosis of MINOCA was defined as: (1) fulfillment of the Universal Definition of Myocardial Infarction criteria, (2) absence of coronary artery stenosis ≥ 50%, and (3) no identified alternative cause for the MI presentation 2 , 4 . The control group consisted of age- and sex-matched healthy individuals without angina and with normal coronary computed tomography (CT) angiography, defined as CAD-RADS 0 (no stenosis or plaque) according to the CAD-RADS™ 2.0 12 consensus document, performed within 5 years prior to inclusion as a part of the Swedish CardioPulmonary bioImage Study (SCAPIS) 13 . Coronary angiography All patients underwent invasive coronary angiography during hospitalization and prior to CMR as part of the diagnostic work-up. Angiographic data were retrieved from the SWEDEHEART registry. CMR protocol CMR protocol The CMR imaging was performed on a Philips 1.5 T Multiva scanner with a 32-channel dStream Torso coil (Philips Diagnosis & Treatment, Best, The Netherlands). Patients with a working diagnosis of MINOCA and healthy volunteers underwent first-pass perfusion CMR during pharmacological stress with intravenous regadenoson (standard dose of 320 µg) and at rest following intravenous theophylline to reverse vasodilatation. Perfusion imaging used a vendor-supplied research dual-sequence acquisition 5 , in which a single bolus of gadobutrol (Gadovist, Bayer AB, Solna, Sweden, 0.05 mmol/kg) was administered during the simultaneous acquisition of two distinct image series: one for arterial input function (AIF) measurement (voxel size 6.8 × 2.6 × 10.0 mm3, saturation time 30 ms, single basal slice) and another for myocardial enhancement (voxel size 2.6 × 2.6 × 10.0 mm3, saturation time 90 ms, three short-axis slices basal/midventricular/apical). ECG-triggered acquisition was performed at one frame per heartbeat during 80 heartbeats under free breathing. The single-shot spoiled gradient echo readouts were made with a flip angle (FA) 15°, and echo time (TE) 1.2 ms, a repetition time (TR) of 2.7 ms, and field of view (FOV) 288 × 316 mm 2 , bandwidth 865 Hz/pixel, partial Fourier factor 0.75, and compressed sensing under-sampling factor 2.3. Additional routine sequences included Late Gadolinium (LGE), Phase-sensitive inversion recovery (PSIR), cine balanced steady-state free precession (cine bSSFP), short tau inversion recovery (STIR), T2 mapping and T1 mapping before and after contrast administration (see Fig. 2 ). Patients were abstained from caffeine for 24 h and nicotine for 12 h prior to the CMR examination. Adequate hemodynamic response was defined as a systolic blood pressure decrease by > 10 mmHg and/or a heart rate increase by > 10 bpm. Fully automated AI-based Circle CVI42™ (CVI), version 5.13 (Circle Cardiovascular Imaging Inc., Calgary, AB, Canada) software was used for automated calculation of myocardial blood flow at stress (stress MBF, mL/g/min), and at rest (rest MBF), and myocardial perfusion reserve (MPR), defined as the ratio of stress to rest MBF, at segmental, coronary territory, and global level. The calculations were based on the perfusion data and the native T1-mapping. Coronary microvascular dysfunction was defined using proposed cut-off values as stress MBF < 2.25 ml/g/min or MPR < 2.0 14 in the absence of any other pathological CMR findings. A normal CMR scan was defined as absence of myocardial LGE, edema and no other CMR findings (e.g., cardiomyopathies). Ethics This study was approved by the Regional Ethical Review Boards in Lund (Dnr 2021 − 01517) and Stockholm (Dnr 2020–05953; amendment Dnr 2024-06698-02). All participants provided written informed consent. The study followed the principles of the 1975 Declaration of Helsinki. Statistical methods Continuous variables were assessed for normality using the Shapiro–Wilk test and visual inspection of histograms and Q–Q plots. Normally distributed variables are presented as mean ± standard deviation (SD), whereas non-normally distributed variables are reported as median with interquartile range (IQR). Categorical variables are summarized as counts and percentages. Between-group comparisons of continuous variables (MINOCA vs. healthy controls) were performed using the independent-samples Student’s t -test for normally distributed data and the Mann–Whitney U test for non-normally distributed data. Categorical variables were compared using the Chi-square test or Fisher’s exact test when appropriate. Global myocardial blood flow (MBF), coronary territory–specific MBF, and myocardial perfusion reserve (MPR) were compared using the same criteria for test selection based on distribution. All tests were two-sided, and a p -value < 0.05 was considered statistically significant. No adjustments were made for multiple comparisons given the exploratory nature of the study. Statistical analyses were performed using IBM SPSS Statistics version 28 (IBM Corp., Armonk, NY, USA). Results Stress-perfusion CMR was performed in 46 patients with a working diagnosis of MINOCA and 30 healthy age-matched controls. The selection process is illustrated in Fig. 1 . Among the MINOCA cohort,10 patients (22%) were diagnosed with myocarditis, 7 (15%) with embolic MI, 2 (4%) with Takotsubo syndrome, and 2 (4%) with other conditions and were therefore excluded. One patient was excluded due to the presence of coronary stenosis on re-evaluation of the coronary angiography, and one due to suboptimal image quality. In the control group, two individuals with evidence of silent myocardial infarction, one with claustrophobia, and one with poor scan quality were excluded. The final study population thus comprised 23 MINOCA patients with normal routine CMR findings and 26 healthy controls. Mean age and sex distribution did not differ between MINOCA patients and healthy controls (62.6 ± 9.7 years, 61% females and 61.1 ± 3.6 years, 54% females, respectively). Compared with controls, MINOCA patients had higher rates of smoking, cardiovascular risk factors, medications, and higher concentrations of cardiac biomarkers (Table 1 ). Table 1 Baseline characteristics of patients with MINOCA and otherwise normal CMR scan, and healthy controls. Clinical data MINOCA n = 23 Healthy controls n = 26 p-value Demographics Age, y, mean± SD 62.6 ± 9.7 61.1 ± 3.6 0.492 Female sex, n (%) 14 (60.9) 14 (53.8) 0.620 BSA, m2, mean± SD 1.93 ± 0.25 1.97 ± 0.25 0.542 Smoking, n (%) 10 (43.5) 1 (3.8) < 0.001 Co-morbidities, n (%) Hypertension 10 (43.5) 4 (15.4) 0.030 Diabetes 2 (8.7) 0 (0) 0.125 Hyperlipidemia 10 (43.5) 3 (11.5) 0.011 Medications n (%) ACE-I/ARB 13 (56.5) 4 (15.4) 0.010 Beta-blockers 6 (26.1) 0 (0) 0.040 Calcium channel blockers 4 (17.4) 1 (3.8) 0.141 Statins 19 (82.6) 1 (3.8) < 0.001 Laboratory results, median(IQR) Troponin T, ng/L 157 (71;265) 6 (5;9) < 0.001 NT-proBNP, ng/L 203 (76;514) 76 (50;98) 0.006 BSA, body surface area; ACE-I, angiotensin converting enzyme inhibitor; ARB, angiotensin receptor blocker. There were no significant differences in left ventricular volumes, mass, systolic function (LVEF, GLS), or tissue characterization parameters (native and post-contrast T1, ECV, T2) between groups (Table 2 ). Table 2 Results of CMR studies. MINOCA n = 23 Healthy controls n = 26 p-value LV EDV, mL 135.4 ± 39.3 150.8 ± 38.1 0.171 LV EDVi, mL/m 2 69.4 ± 15.4 76.3 ± 13.8 0.108 LV ESV, mL 48.7 ± 18.1 52.7 ± 18.1 0.445 LV ESVi, mL/m 2 24.9 ± 7.7 26.6±7.7 0.446 LV SV, mL 86.8 ± 23.0 98.3 ± 22.8 0.086 LV SVi, mL/m 2 44.7 ± 8.9 49.8 ± 8.0 0.040 LV mass, g 94.7 ± 27.6 96.1 ± 26.5 0.855 LV mass i, g/m 2 48.6 ± 10.1 48.8±10.7 0.946 LV EF, % 64.8 ± 4.7 65.6 ± 5.4 0.573 LV GLS, % 18.8 ± 2.5 19.1 ± 1.6 0.620 LV GCS, % 21.0 ± 2.0 20.8 ± 2.2 0.655 Native T1, ms 1008 ± 28 1011 ± 22 0.681 Native T2, ms 47 ± 2 46 ± 2 0.891 ECV, % 25.7 ± 2.3 26.2 ± 2.3 0.440 LV, left ventricle; EDV, end-diastolic volume; EDVi, indexed end-diastolic volume; ESV, end-systolic volume; ESVi, indexed end-systolic volume; SV, stroke volume; SVi, indexed stroke volume; EF, ejection fraction; GLS, global longitudinal strain; GCS, global circumferential strain; ECV, extracellular volume fraction. In contrast, quantitative perfusion revealed significant differences. MINOCA patients demonstrated lower global stress MBF (2.56 ± 0.81 vs. 2.96 ± 0.53 mL/g/min, p = 0.044) and lower MPR (1.88 ± 0.59 vs. 2.30 ± 0.55, p = 0.013), whereas global rest MBF did not differ between the groups (1.42 ± 0.26 vs. 1.37 ± 0.32 mL/g/min, p = 0.539). Perfusion differences were consistent across coronary territories (Table 3 ). Table 3 Results of quantitative perfusion analysis. Perfusion CMR data MINOCA n = 23 Healthy controls n = 26 p-value Hemodynamic response Heart rate at rest, bpm 75 ± 14 74 ± 14 0.745 Heart rate at stress, bpm 97 ± 13 92 ± 11 0.164 SBP at rest, mmHg 138 ± 18 132 ± 13 0.156 SBP at stress, mmHg 138 ± 20 131 ± 14 0.194 Rest myocardial blood flow (MBF) Global 1.42 ± 0.26 1.37 ± 0.32 0.539 LAD-territory 1.48 ± 0.30 1.42 ± 0.37 0.575 LCX-territory 1.47 ± 0.32 1.45 ± 0.41 0.921 RCA-territory 1.28 ± 0.25 1.16 ± 0.27 0.112 Stress myocardial blood flow (MBF) Global 2.56 ± 0.81 2.96 ± 0.53 0.044 LAD-territory 2.58 ± 0.85 3.08 ± 0.56 0.018 LCX-territory 2.55 ± 0.82 3.05 ± 0.50 0.013 RCA-territory 2.39 ± 0.80 2.75 ± 0.57 0.076 Myocardial perfusion reserve (MPR) Global 1.88 ± 0.59 2.30 ± 0.55 0.013 LAD-territory 1.78 ± 0.57 2.28 ± 0.62 0.005 LCX-territory 1.77 ± 0.57 2.21 ± 0.59 0.012 RCA-territory 1.92 ± 0.65 2.46 ± 0.60 0.004 bpm, beats per minute; SBP, systolic blood pressure; DBP, diastolic blood pressure; MBF, myocardial blood flow; MPR, myocardial perfusion reserve; LAD, left anterior descending artery; LCX, left circumflex artery; RCA, right coronary artery. Using predefined thresholds for CMD 14 , 10 of 23 (43%) MINOCA patients (43%) met criteria for coronary microvascular dysfunction, compared with none in the control group. Quantitative perfusion values for rest MBF, stress MBF, and MPR are shown in Fig. 3, and representative perfusion maps are displayed in Fig. 4. Figure 3. Rest MBF, stress MBF, and MPR in patients with MINOCA compared with healthy controls. MBF myocardial blood flow; MPR, myocardial perfusion reserve Figure 4. Representative examples of quantitative perfusion maps in stress and rest of a MINOCA patient with and without CMD. (A) The first patient shows normal CMR findings and normal perfusion. The polar maps demonstrate normal stress myocardial blood flow (MBF) and normal myocardial perfusion reserve (MPR). (B) The second patient shows normal CMR findings and normal coronary angiography, but an abnormal perfusion. The polar maps reveal reduced stress MBF and MPR, while rest perfusion remains normal—findings consistent with coronary microvascular dysfunction (CMD). Both patients showed an appropriate hemodynamic response to regadenoson stress, as illustrated by the heart rate changes and arterial input function curves on the right. Finally, 69.6% of MINOCA patients had evidence of non-obstructive atherosclerotic plaque on coronary angiography, despite normal CMR findings. Discussion Our results show that nearly half of the MINOCA patients with otherwise normal CMR findings exhibit significantly reduced stress MBF and impaired MPR, consistent with coronary microvascular dysfunction. This suggests that CMD may be an important and under-recognized mechanism of myocardial injury in MINOCA, even when routine imaging does not reveal any structural abnormalities. Microvascular impairment as a substrate for MINOCA has biological plausibility: functional abnormalities of the coronary microcirculation, like limited vasodilatory reserve or increased microvascular resistance, can restrict perfusion during stress despite patent epicardial arteries 15 . In our cohort, the combination of normal MBF at rest, but reduced stress MBF and MPR, indicates preserved basal perfusion yet an impaired ability to increase flow during demand, which are hallmark features of CMD. Our findings are consistent with prior invasive physiology studies. Milzi et al. 16 showed that angiography-derived index of microvascular resistance (aIMR) was elevated across all three coronary territories in MINOCA patients, regardless of subtype (takotsubo, inflammatory, or “unclear”). Their “unclear” subgroup – characterized by normal CMR findings and a demographic profile similar to our cohort - had significantly higher microvascular resistance than controls (30.6 ± 8.5 vs. 22.1 ± 5.9, p < 0.001). Notably, this subgroup represented 45% of all MINOCA patients, which relates to a proportion of normal CMR findings in our cohort. Importantly, Milzi et al.´s data support the view that CMD is not merely an epiphenomenon but may represent a core pathophysiological feature of MINOCA. Additional support comes from long-term imaging studies. In the SMINC-2 cohort, Johansson et al. 17 reported persistently reduced stress perfusion years after the index MINOCA event, despite normal baseline CMR findings. Their results, obtained using quantitative stress perfusion imaging, mirror our observations and suggest that CMD may represent a chronic microvascular phenotype rather than a transient event-related abnormality. In our study, 42% of MINOCA patients with normal CMR findings met established quantitative perfusion thresholds for CMD 14 . Although the causal relationship between CMD and myocardial injury in MINOCA remains incompletely understood, the clinical significance of CMD is increasingly recognized. CMD has been linked to angina, impaired quality of life, and an elevated risk of major adverse cardiovascular events in patients without obstructive coronary artery disease. Detecting CMD in MINOCA may therefore have important diagnostic and prognostic information and may inform future therapeutic strategies, even though optimal treatment in this population is not yet defined. Notably, more than two-thirds (69.6%) of MINOCA patients with normal CMR demonstrated non-obstructive atherosclerotic plaque on coronary angiography. This observation suggests a potential interplay between non-obstructive atherosclerosis and microvascular dysfunction. Previous studies have reported similar associations 15 , indicating that shared mechanisms such as endothelial dysfunction, inflammation, or diffuse microvascular remodeling may contribute to both processes. The exact nature of this relationship warrants further investigation. In summary, we found that a substantial proportion of MINOCA patients with entirely normal conventional CMR demonstrate impaired stress perfusion and reduced myocardial perfusion reserve on early quantitative stress-perfusion CMR. These abnormalities reveal a high prevalence of coronary microvascular dysfunction that is not detectable with routine imaging. Our data suggest that CMD represents a plausible and underappreciated mechanism of myocardial injury in MINOCA and highlight the added diagnostic value of incorporating quantitative perfusion CMR into the evaluation of patients with unclear causes of myocardial injury. Limitations This study has several limitations. First, the sample size was modest and derived from a single center, which may limit the generalizability of the findings. Second, although the control group was age- and sex-matched, differences in cardiovascular risk factors and medication use between groups may have influenced perfusion measurements. Third, we did not perform invasive coronary microvascular assessment, which precludes direct comparison between invasive and noninvasive measures of CMD. Fourth, the absence of longitudinal follow-up prevents assessment of the prognostic implications of CMD identified on quantitative stress-perfusion CMR. Finally, although automated perfusion analysis reduces operator dependence, technical factors such as slice selection, motion artifacts, and hemodynamic variability during regadenoson stress may have affected quantitative perfusion values. Conclusions Early quantitative stress-perfusion CMR identifies impaired stress myocardial blood flow and myocardial perfusion reserve in substantial proportion of MINOCA patients who otherwise demonstrate normal findings on conventional CMR. These abnormalities reveal coronary microvascular dysfunction in nearly half of such patients, underscoring CMD as a plausible and under-recognized mechanism of myocardial injury in this heterogeneous clinical syndrome. Our findings highlight the added diagnostic value of quantitative perfusion CMR and support its integration into the evaluation of patients with MINOCA when routine imaging does not clarify the underlying cause. Declarations Competing interests The author(s) declare no competing interests. Funding No external funding was received. Open access funding was provided by Uppsala University. Author Contribution R.S. participated in the patient inclusion, image acquisition, performed image, data and statistical analysis, as well as drafted the manuscript. J.L. and B.L. participated in the design of the study, interpretation of data and revised the manuscript. A-M.M. participated in patient inclusion and image acquisition. J.B. participated in image acquisition and sequence optimization. K-H.G. and A.M. participated in interpretation of data and revised manuscript. T.B. participated in the design of the study and patient inclusion, as well as supervised image acquisition, data and statistical analysis and revised the manuscript. All authors read and approved the final manuscript. The patients provided written informed consent to publish their individual data on group level as well as anonymized images in this manuscript. The consent forms are held in the clinical notes of the patients and are available for the Editor-in-Chief for review. 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Cardiol. 113 (12), 1622–1628. 10.1007/s00392-023-02294-1 (2024). Steffen Johansson, R., Tornvall, P., Sörensson, P. & Nickander, J. Reduced stress perfusion in myocardial infarction with nonobstructive coronary arteries. Sci. Rep. 13 (1), 22094. 10.1038/s41598-023-49223-w (2023). Additional Declarations No competing interests reported. Cite Share Download PDF Status: Under Review Version 1 posted Reviewers invited by journal 05 May, 2026 Editor invited by journal 10 Mar, 2026 Editor assigned by journal 18 Feb, 2026 Submission checks completed at journal 18 Feb, 2026 First submitted to journal 17 Feb, 2026 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. 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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-8903448","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":635079095,"identity":"7d583bc1-9da0-475c-b553-142645254baa","order_by":0,"name":"Ramin Sahar","email":"","orcid":"","institution":"Uppsala University","correspondingAuthor":false,"prefix":"","firstName":"Ramin","middleName":"","lastName":"Sahar","suffix":""},{"id":635079097,"identity":"db0033c5-c4dd-4ae9-8056-37bf4d1c40ae","order_by":1,"name":"Joel Lenell","email":"","orcid":"","institution":"Uppsala University","correspondingAuthor":false,"prefix":"","firstName":"Joel","middleName":"","lastName":"Lenell","suffix":""},{"id":635079099,"identity":"e5765217-cc9c-4b96-9280-cc92f9cf5bd5","order_by":2,"name":"Bertil Lindahl","email":"","orcid":"","institution":"Uppsala University","correspondingAuthor":false,"prefix":"","firstName":"Bertil","middleName":"","lastName":"Lindahl","suffix":""},{"id":635079100,"identity":"ab00da2a-b7aa-43c1-a220-5d959eb22690","order_by":3,"name":"Anne-Marie Montelius","email":"","orcid":"","institution":"Uppsala University","correspondingAuthor":false,"prefix":"","firstName":"Anne-Marie","middleName":"","lastName":"Montelius","suffix":""},{"id":635079101,"identity":"6b1e992c-79af-452c-9d0a-18f3066497e3","order_by":4,"name":"Johan Berglund","email":"","orcid":"","institution":"Uppsala University","correspondingAuthor":false,"prefix":"","firstName":"Johan","middleName":"","lastName":"Berglund","suffix":""},{"id":635079102,"identity":"cb994c74-2a7f-48e8-b1a6-ddd93bd7f426","order_by":5,"name":"Karl-Henrik Grinnemo","email":"","orcid":"","institution":"Uppsala University","correspondingAuthor":false,"prefix":"","firstName":"Karl-Henrik","middleName":"","lastName":"Grinnemo","suffix":""},{"id":635079104,"identity":"5e759af7-2a88-4dc3-8626-c339be908421","order_by":6,"name":"Andrei Malinovschi","email":"","orcid":"","institution":"Uppsala University","correspondingAuthor":false,"prefix":"","firstName":"Andrei","middleName":"","lastName":"Malinovschi","suffix":""},{"id":635079106,"identity":"373593e1-ad24-48e7-8604-295876a50237","order_by":7,"name":"Tomasz Baron","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA4UlEQVRIiWNgGAWjYBCDBDD5gRilPMhaGGeQrIWZB7dCBLBn7078+OMPQx7/7MPHHtu22eUzSOQYMP6owGMLz9nN0jw8DMUS59LSjXPbki0bgFqYec7g0SKRu0GaQYIhseEMj5l0btsBA5AtzIxteLVs/vnDgCFxPkiLJVQL489/eLVsk+BJYEjcANLCCNXCwNuAR8uZs9useQ5IFBueYUuT7DmXbMDG86zgMM8x3FrY23s33/zxxyZP7gzzMYkfZXYG/OzJGx/+qMGtBQokEEw2ID5AUMMoGAWjYBSMArwAAOfNRKr80ho1AAAAAElFTkSuQmCC","orcid":"","institution":"Uppsala University","correspondingAuthor":true,"prefix":"","firstName":"Tomasz","middleName":"","lastName":"Baron","suffix":""}],"badges":[],"createdAt":"2026-02-17 17:53:16","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-8903448/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-8903448/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":109298013,"identity":"53e25b10-ff23-4851-8831-a12ca49dfa4b","added_by":"auto","created_at":"2026-05-15 09:08:17","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":49294,"visible":true,"origin":"","legend":"\u003cp\u003eFlow chart illustrating the selection of the study population, including patients with a working diagnosis of MINOCA and healthy controls.\u003c/p\u003e","description":"","filename":"Picture1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-8903448/v1/cfbc84e642ca01f1785089a5.jpg"},{"id":109296386,"identity":"2ea4dfb1-72de-40f2-abc3-82ae71aeb5e9","added_by":"auto","created_at":"2026-05-15 08:46:46","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":74552,"visible":true,"origin":"","legend":"\u003cp\u003eRegadenoson CMR stress-perfusion protocol. Survey imaging, native T1 mapping, native T2 mapping, and STIR sequences are acquired first, followed stress perfusion imaging. Regadenoson is administered to induce hyperemia, and theophylline is subsequently given to reverse its effects. Cine imaging and rest perfusion are then performed, and late gadolinium enhancement is acquired last. The total duration of the protocol is approximately 50 minutes.\u003c/p\u003e","description":"","filename":"Picture2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-8903448/v1/b54cb1836a7fb776a28884b8.jpg"},{"id":109286360,"identity":"d4bc3f06-b2ba-49d7-af5f-7155eeb751ec","added_by":"auto","created_at":"2026-05-15 02:33:50","extension":"jpg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":24236,"visible":true,"origin":"","legend":"\u003cp\u003eRest MBF, stress MBF, and MPR in patients with MINOCA compared with healthy controls.\u003c/p\u003e","description":"","filename":"Picture3.jpg","url":"https://assets-eu.researchsquare.com/files/rs-8903448/v1/a74546416e06a789082d188b.jpg"},{"id":109296333,"identity":"9cecc665-c997-424f-a7f8-e75ad0da9300","added_by":"auto","created_at":"2026-05-15 08:46:32","extension":"jpg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":90889,"visible":true,"origin":"","legend":"\u003cp\u003eRepresentative examples of quantitative perfusion maps in stress and rest of a MINOCA patient with and without CMD.\u003c/p\u003e\n\u003cp\u003e(A) The first patient shows normal CMR findings and normal perfusion. The polar maps demonstrate normal stress myocardial blood flow (MBF) and normal myocardial perfusion reserve (MPR).\u003c/p\u003e\n\u003cp\u003e(B) The second patient shows normal CMR findings and normal coronary angiography, but an abnormal perfusion. The polar maps reveal reduced stress MBF and MPR, while rest perfusion remains normal—findings consistent with coronary microvascular dysfunction (CMD).\u003c/p\u003e\n\u003cp\u003eBoth patients showed an appropriate hemodynamic response to regadenoson stress, as illustrated by the heart rate changes and arterial input function curves on the right.\u003c/p\u003e","description":"","filename":"Picture4.jpg","url":"https://assets-eu.researchsquare.com/files/rs-8903448/v1/e65c829716b75c812e1d0814.jpg"},{"id":109298861,"identity":"7ebc6fb5-4695-4915-aaeb-4168b0f7b3d7","added_by":"auto","created_at":"2026-05-15 09:16:02","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":504413,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8903448/v1/4629eb97-f42a-4506-b596-740a830139e9.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"\u003cp\u003eEarly quantitative stress-perfusion cardiac magnetic resonance identifies coronary microvascular dysfunction in MINOCA patients with otherwise normal cardiac magnetic resonance findings\u003c/p\u003e","fulltext":[{"header":"Introduction","content":"\u003cp\u003eMyocardial infarction with non-obstructive coronary arteries (MINOCA) represents a diagnostically challenging syndrome with multiple underlying mechanisms, including plaque disruption, coronary embolism, vasospasm, and coronary microvascular dysfunction (CMD). Differentiating these entities is essential because prognosis and treatment strategies vary by etiology\u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u003c/sup\u003e. Standard cardiac magnetic resonance (CMR) is recommended to identify conditions such as myocarditis, Takotsubo syndrome, or cardiomyopathies, which account for a substantial proportion of MINOCA presentations\u003csup\u003e\u003cspan additionalcitationids=\"CR3\" citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u003c/sup\u003e. However, a considerable subset of patients has normal CMR findings despite biochemical evidence of myocardial injury.\u003c/p\u003e \u003cp\u003eCMD has emerged as a plausible explanation for ischemic symptoms and troponin elevation when epicardial arteries are unobstructed. Functional abnormalities in the coronary microcirculation - such as impaired vasodilatory capacity, increased resistance, and endothelial dysfunction - can cause reduced perfusion during stress, while resting flow remains preserved. Although increasingly recognized, CMD remains underdiagnosed, partly because conventional imaging lacks the sensitivity to detect subtle microvascular abnormalities.\u003c/p\u003e \u003cp\u003eQuantitative stress-perfusion CMR (Q-CMR) offers a noninvasive, radiation-free approach for quantifying myocardial blood flow (MBF) and myocardial perfusion reserve (MPR). Technical advances such as dual-sequence acquisition\u003csup\u003e\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u003c/sup\u003e and automated pixel-wise perfusion mapping\u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e,\u003cspan additionalcitationids=\"CR8\" citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u003c/sup\u003e have markedly improved reproducibility and clinical applicability\u003csup\u003e\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u003c/sup\u003e. Despite these strengths, the role of Q-CMR in evaluating MINOCA has not been comprehensively defined.\u003c/p\u003e \u003cp\u003eWe hypothesized that CMD is under-recognized among MINOCA patients with normal conventional CMR and that quantitative perfusion indices would reveal impaired stress perfusion compared with healthy individuals. Therefore, we conducted a prospective evaluation of stress and rest MBF and MPR in MINOCA patients and matched controls using automated dual-sequence Q-CMR.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eStudy population\u003c/h2\u003e \u003cp\u003eConsecutive patients with a working diagnosis of MINOCA referred for CMR at Uppsala University Hospital between January 2021 and August 2024 were included in the Swedish Web-system for enhancement and Development of Evidence-based care in Heart disease Evaluated According to Recommended Therapies (SWEDEHEART) registry\u003csup\u003e\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u003c/sup\u003e, which prospectively collects nationwide data from patients admitted to coronary care units or other specialized facilities because of suspected acute coronary syndrome. A working diagnosis of MINOCA was defined as: (1) fulfillment of the Universal Definition of Myocardial Infarction criteria, (2) absence of coronary artery stenosis\u0026thinsp;\u0026ge;\u0026thinsp;50%, and (3) no identified alternative cause for the MI presentation\u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e,\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eThe control group consisted of age- and sex-matched healthy individuals without angina and with normal coronary computed tomography (CT) angiography, defined as CAD-RADS 0 (no stenosis or plaque) according to the CAD-RADS\u0026trade; 2.0\u003csup\u003e12\u003c/sup\u003e consensus document, performed within 5 years prior to inclusion as a part of the Swedish CardioPulmonary bioImage Study (SCAPIS)\u003csup\u003e\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eCoronary angiography\u003c/h3\u003e\n\u003cp\u003eAll patients underwent invasive coronary angiography during hospitalization and prior to CMR as part of the diagnostic work-up. Angiographic data were retrieved from the SWEDEHEART registry.\u003c/p\u003e\n\u003ch3\u003eCMR protocol\u003c/h3\u003e\n\u003cdiv class=\"Heading\"\u003eCMR protocol\u003c/div\u003e \u003cp\u003eThe CMR imaging was performed on a Philips 1.5 T Multiva scanner with a 32-channel dStream Torso coil (Philips Diagnosis \u0026amp; Treatment, Best, The Netherlands).\u003c/p\u003e \u003cp\u003ePatients with a working diagnosis of MINOCA and healthy volunteers underwent first-pass perfusion CMR during pharmacological stress with intravenous regadenoson (standard dose of 320 \u0026micro;g) and at rest following intravenous theophylline to reverse vasodilatation. Perfusion imaging used a vendor-supplied research dual-sequence acquisition\u003csup\u003e\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u003c/sup\u003e, in which a single bolus of gadobutrol (Gadovist, Bayer AB, Solna, Sweden, 0.05 mmol/kg) was administered during the simultaneous acquisition of two distinct image series: one for arterial input function (AIF) measurement (voxel size 6.8 \u0026times; 2.6 \u0026times; 10.0 mm3, saturation time 30 ms, single basal slice) and another for myocardial enhancement (voxel size 2.6 \u0026times; 2.6 \u0026times; 10.0 mm3, saturation time 90 ms, three short-axis slices basal/midventricular/apical). ECG-triggered acquisition was performed at one frame per heartbeat during 80 heartbeats under free breathing. The single-shot spoiled gradient echo readouts were made with a flip angle (FA) 15\u0026deg;, and echo time (TE) 1.2 ms, a repetition time (TR) of 2.7 ms, and field of view (FOV) 288 \u0026times; 316 mm\u003csup\u003e2\u003c/sup\u003e, bandwidth 865 Hz/pixel, partial Fourier factor 0.75, and compressed sensing under-sampling factor 2.3.\u003c/p\u003e \u003cp\u003eAdditional routine sequences included Late Gadolinium (LGE), Phase-sensitive inversion recovery (PSIR), cine balanced steady-state free precession (cine bSSFP), short tau inversion recovery (STIR), T2 mapping and T1 mapping before and after contrast administration (see Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003ePatients were abstained from caffeine for 24 h and nicotine for 12 h prior to the CMR examination. Adequate hemodynamic response was defined as a systolic blood pressure decrease by \u0026gt;\u0026thinsp;10 mmHg and/or a heart rate increase by \u0026gt;\u0026thinsp;10 bpm.\u003c/p\u003e \u003cp\u003eFully automated AI-based Circle CVI42\u0026trade; (CVI), version 5.13 (Circle Cardiovascular Imaging Inc., Calgary, AB, Canada) software was used for automated calculation of myocardial blood flow at stress (stress MBF, mL/g/min), and at rest (rest MBF), and myocardial perfusion reserve (MPR), defined as the ratio of stress to rest MBF, at segmental, coronary territory, and global level. The calculations were based on the perfusion data and the native T1-mapping.\u003c/p\u003e \u003cp\u003eCoronary microvascular dysfunction was defined using proposed cut-off values as stress MBF\u0026thinsp;\u0026lt;\u0026thinsp;2.25 ml/g/min or MPR\u0026thinsp;\u0026lt;\u0026thinsp;2.0\u003csup\u003e14\u003c/sup\u003e in the absence of any other pathological CMR findings. A normal CMR scan was defined as absence of myocardial LGE, edema and no other CMR findings (e.g., cardiomyopathies).\u003c/p\u003e\n\u003ch3\u003eEthics\u003c/h3\u003e\n\u003cp\u003e This study was approved by the Regional Ethical Review Boards in Lund (Dnr 2021\u0026thinsp;\u0026minus;\u0026thinsp;01517) and Stockholm (Dnr 2020\u0026ndash;05953; amendment Dnr 2024-06698-02). All participants provided written informed consent. The study followed the principles of the 1975 Declaration of Helsinki.\u003c/p\u003e\n\u003ch3\u003eStatistical methods\u003c/h3\u003e\n\u003cp\u003eContinuous variables were assessed for normality using the Shapiro\u0026ndash;Wilk test and visual inspection of histograms and Q\u0026ndash;Q plots. Normally distributed variables are presented as mean\u0026thinsp;\u0026plusmn;\u0026thinsp;standard deviation (SD), whereas non-normally distributed variables are reported as median with interquartile range (IQR). Categorical variables are summarized as counts and percentages.\u003c/p\u003e \u003cp\u003eBetween-group comparisons of continuous variables (MINOCA vs. healthy controls) were performed using the independent-samples Student\u0026rsquo;s \u003cem\u003et\u003c/em\u003e-test for normally distributed data and the Mann\u0026ndash;Whitney \u003cem\u003eU\u003c/em\u003e test for non-normally distributed data. Categorical variables were compared using the Chi-square test or Fisher\u0026rsquo;s exact test when appropriate. Global myocardial blood flow (MBF), coronary territory\u0026ndash;specific MBF, and myocardial perfusion reserve (MPR) were compared using the same criteria for test selection based on distribution.\u003c/p\u003e \u003cp\u003eAll tests were two-sided, and a \u003cem\u003ep\u003c/em\u003e-value\u0026thinsp;\u0026lt;\u0026thinsp;0.05 was considered statistically significant. No adjustments were made for multiple comparisons given the exploratory nature of the study. Statistical analyses were performed using IBM SPSS Statistics version 28 (IBM Corp., Armonk, NY, USA).\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003eStress-perfusion CMR was performed in 46 patients with a working diagnosis of MINOCA and 30 healthy age-matched controls. The selection process is illustrated in Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eAmong the MINOCA cohort,10 patients (22%) were diagnosed with myocarditis, 7 (15%) with embolic MI, 2 (4%) with Takotsubo syndrome, and 2 (4%) with other conditions and were therefore excluded. One patient was excluded due to the presence of coronary stenosis on re-evaluation of the coronary angiography, and one due to suboptimal image quality. In the control group, two individuals with evidence of silent myocardial infarction, one with claustrophobia, and one with poor scan quality were excluded.\u003c/p\u003e \u003cp\u003eThe final study population thus comprised 23 MINOCA patients with normal routine CMR findings and 26 healthy controls. Mean age and sex distribution did not differ between MINOCA patients and healthy controls (62.6\u0026thinsp;\u0026plusmn;\u0026thinsp;9.7 years, 61% females and 61.1\u0026thinsp;\u0026plusmn;\u0026thinsp;3.6 years, 54% females, respectively). Compared with controls, MINOCA patients had higher rates of smoking, cardiovascular risk factors, medications, and higher concentrations of cardiac biomarkers (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\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\u003eBaseline characteristics of patients with MINOCA and otherwise normal CMR scan, and healthy controls.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\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 \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eClinical data\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMINOCA\u003c/p\u003e \u003cp\u003en\u0026thinsp;=\u0026thinsp;23\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eHealthy controls\u003c/p\u003e \u003cp\u003en\u0026thinsp;=\u0026thinsp;26\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e \u003cp\u003e\u003cem\u003eDemographics\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge, y, mean\u0026plusmn; SD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e62.6 \u0026plusmn; 9.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e61.1 \u0026plusmn; 3.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.492\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFemale sex, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e14 (60.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e14 (53.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.620\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBSA, m2, mean\u0026plusmn; SD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.93 \u0026plusmn; 0.25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.97 \u0026plusmn; 0.25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.542\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSmoking, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e10 (43.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1 (3.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e \u003cp\u003e\u003cem\u003eCo-morbidities, n (%)\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHypertension\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e10 (43.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4 (15.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.030\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDiabetes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2 (8.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0 (0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.125\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHyperlipidemia\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e10 (43.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3 (11.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.011\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e \u003cp\u003e\u003cem\u003eMedications n (%)\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eACE-I/ARB\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e13 (56.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4 (15.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.010\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBeta-blockers\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6 (26.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0 (0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.040\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCalcium channel blockers\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4 (17.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1 (3.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.141\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eStatins\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e19 (82.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1 (3.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e \u003cp\u003e\u003cem\u003eLaboratory results, median(IQR)\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTroponin T, ng/L\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e157 (71;265)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6 (5;9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNT-proBNP, ng/L\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e203 (76;514)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e76 (50;98)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.006\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\u003eBSA, body surface area; ACE-I, angiotensin converting enzyme inhibitor; ARB, angiotensin receptor blocker.\u003c/p\u003e \u003cp\u003eThere were no significant differences in left ventricular volumes, mass, systolic function (LVEF, GLS), or tissue characterization parameters (native and post-contrast T1, ECV, T2) between groups (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\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\u003eResults of CMR studies.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMINOCA\u003c/p\u003e \u003cp\u003en\u0026thinsp;=\u0026thinsp;23\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eHealthy controls\u003c/p\u003e \u003cp\u003en\u0026thinsp;=\u0026thinsp;26\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLV EDV, mL\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e135.4 \u0026plusmn; 39.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e150.8 \u0026plusmn; 38.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.171\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLV EDVi, mL/m\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e69.4 \u0026plusmn; 15.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e76.3 \u0026plusmn; 13.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.108\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLV ESV, mL\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e48.7 \u0026plusmn; 18.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e52.7 \u0026plusmn; 18.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.445\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLV ESVi, mL/m\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e24.9 \u0026plusmn; 7.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e26.6\u0026plusmn;7.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.446\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLV SV, mL\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e86.8 \u0026plusmn; 23.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e98.3 \u0026plusmn; 22.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.086\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLV SVi, mL/m\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e44.7 \u0026plusmn; 8.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e49.8 \u0026plusmn; 8.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.040\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLV mass, g\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e94.7 \u0026plusmn; 27.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e96.1 \u0026plusmn; 26.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.855\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLV mass i, g/m\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e48.6 \u0026plusmn; 10.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e48.8\u0026plusmn;10.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.946\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLV EF, %\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e64.8 \u0026plusmn; 4.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e65.6 \u0026plusmn; 5.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.573\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLV GLS, %\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e18.8 \u0026plusmn; 2.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e19.1 \u0026plusmn; 1.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.620\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLV GCS, %\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e21.0 \u0026plusmn; 2.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e20.8 \u0026plusmn; 2.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.655\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNative T1, ms\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e1008 \u0026plusmn; 28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e1011 \u0026plusmn; 22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.681\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNative T2, ms\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e47 \u0026plusmn; 2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e46 \u0026plusmn; 2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.891\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eECV, %\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e25.7 \u0026plusmn; 2.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e26.2 \u0026plusmn; 2.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.440\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\u003eLV, left ventricle; EDV, end-diastolic volume; EDVi, indexed end-diastolic volume; ESV, end-systolic volume; ESVi, indexed end-systolic volume; SV, stroke volume; SVi, indexed stroke volume; EF, ejection fraction; GLS, global longitudinal strain; GCS, global circumferential strain; ECV, extracellular volume fraction.\u003c/p\u003e \u003cp\u003eIn contrast, quantitative perfusion revealed significant differences. MINOCA patients demonstrated lower global stress MBF (2.56\u0026thinsp;\u0026plusmn;\u0026thinsp;0.81 vs. 2.96\u0026thinsp;\u0026plusmn;\u0026thinsp;0.53 mL/g/min, p\u0026thinsp;=\u0026thinsp;0.044) and lower MPR (1.88\u0026thinsp;\u0026plusmn;\u0026thinsp;0.59 vs. 2.30\u0026thinsp;\u0026plusmn;\u0026thinsp;0.55, p\u0026thinsp;=\u0026thinsp;0.013), whereas global rest MBF did not differ between the groups (1.42\u0026thinsp;\u0026plusmn;\u0026thinsp;0.26 vs. 1.37\u0026thinsp;\u0026plusmn;\u0026thinsp;0.32 mL/g/min, p\u0026thinsp;=\u0026thinsp;0.539). Perfusion differences were consistent across coronary territories (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e).\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\u003eResults of quantitative perfusion analysis.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\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 \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePerfusion CMR data\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMINOCA\u003c/p\u003e \u003cp\u003en\u0026thinsp;=\u0026thinsp;23\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eHealthy controls\u003c/p\u003e \u003cp\u003en\u0026thinsp;=\u0026thinsp;26\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e \u003cp\u003e\u003cem\u003eHemodynamic response\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHeart rate at rest, bpm\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e75 \u0026plusmn; 14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e74 \u0026plusmn; 14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.745\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHeart rate at stress, bpm\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e97 \u0026plusmn; 13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e92 \u0026plusmn; 11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.164\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSBP at rest, mmHg\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e138 \u0026plusmn; 18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e132 \u0026plusmn; 13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.156\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSBP at stress, mmHg\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e138 \u0026plusmn; 20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e131 \u0026plusmn; 14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.194\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e \u003cp\u003e\u003cem\u003eRest myocardial blood flow (MBF)\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eGlobal\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e1.42\u003c/b\u003e \u0026plusmn; \u003cb\u003e0.26\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e1.37\u003c/b\u003e \u0026plusmn; \u003cb\u003e0.32\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e0.539\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLAD-territory\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.48 \u0026plusmn; 0.30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.42 \u0026plusmn; 0.37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.575\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLCX-territory\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.47 \u0026plusmn; 0.32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.45 \u0026plusmn; 0.41\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.921\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRCA-territory\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.28 \u0026plusmn; 0.25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.16 \u0026plusmn; 0.27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.112\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e \u003cp\u003e\u003cem\u003eStress myocardial blood flow (MBF)\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eGlobal\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e2.56\u003c/b\u003e \u0026plusmn; \u003cb\u003e0.81\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e2.96\u003c/b\u003e \u0026plusmn; \u003cb\u003e0.53\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e0.044\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLAD-territory\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.58 \u0026plusmn; 0.85\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.08 \u0026plusmn; 0.56\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.018\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLCX-territory\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.55 \u0026plusmn; 0.82\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.05 \u0026plusmn; 0.50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.013\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRCA-territory\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.39 \u0026plusmn; 0.80\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.75 \u0026plusmn; 0.57\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.076\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e \u003cp\u003e\u003cem\u003eMyocardial perfusion reserve (MPR)\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eGlobal\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e1.88\u003c/b\u003e \u0026plusmn; \u003cb\u003e0.59\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e2.30\u003c/b\u003e \u0026plusmn; \u003cb\u003e0.55\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e0.013\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLAD-territory\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.78 \u0026plusmn; 0.57\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.28 \u0026plusmn; 0.62\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.005\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLCX-territory\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.77 \u0026plusmn; 0.57\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.21 \u0026plusmn; 0.59\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.012\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRCA-territory\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.92 \u0026plusmn; 0.65\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.46 \u0026plusmn; 0.60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.004\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\u003ebpm, beats per minute; SBP, systolic blood pressure; DBP, diastolic blood pressure; MBF, myocardial blood flow; MPR, myocardial perfusion reserve; LAD, left anterior descending artery; LCX, left circumflex artery; RCA, right coronary artery.\u003c/p\u003e \u003cp\u003eUsing predefined thresholds for CMD\u003csup\u003e\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u003c/sup\u003e, 10 of 23 (43%) MINOCA patients (43%) met criteria for coronary microvascular dysfunction, compared with none in the control group.\u003c/p\u003e \u003cp\u003eQuantitative perfusion values for rest MBF, stress MBF, and MPR are shown in Fig.\u0026nbsp;3, and representative perfusion maps are displayed in Fig.\u0026nbsp;4.\u003c/p\u003e \u003cp\u003eFigure 3. Rest MBF, stress MBF, and MPR in patients with MINOCA compared with healthy controls.\u003c/p\u003e \u003cp\u003e MBF myocardial blood flow; MPR, myocardial perfusion reserve\u003c/p\u003e \u003cp\u003eFigure 4. Representative examples of quantitative perfusion maps in stress and rest of a MINOCA patient with and without CMD.\u003c/p\u003e \u003cp\u003e \u003col\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003e(A) The first patient shows normal CMR findings and normal perfusion. The polar maps demonstrate normal stress myocardial blood flow (MBF) and normal myocardial perfusion reserve (MPR).\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003e(B) The second patient shows normal CMR findings and normal coronary angiography, but an abnormal perfusion. The polar maps reveal reduced stress MBF and MPR, while rest perfusion remains normal\u0026mdash;findings consistent with coronary microvascular dysfunction (CMD).\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003c/ol\u003e \u003c/p\u003e \u003cp\u003eBoth patients showed an appropriate hemodynamic response to regadenoson stress, as illustrated by the heart rate changes and arterial input function curves on the right.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eFinally, 69.6% of MINOCA patients had evidence of non-obstructive atherosclerotic plaque on coronary angiography, despite normal CMR findings.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eOur results show that nearly half of the MINOCA patients with otherwise normal CMR findings exhibit significantly reduced stress MBF and impaired MPR, consistent with coronary microvascular dysfunction. This suggests that CMD may be an important and under-recognized mechanism of myocardial injury in MINOCA, even when routine imaging does not reveal any structural abnormalities.\u003c/p\u003e \u003cp\u003eMicrovascular impairment as a substrate for MINOCA has biological plausibility: functional abnormalities of the coronary microcirculation, like limited vasodilatory reserve or increased microvascular resistance, can restrict perfusion during stress despite patent epicardial arteries\u003csup\u003e\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eIn our cohort, the combination of normal MBF at rest, but reduced stress MBF and MPR, indicates preserved basal perfusion yet an impaired ability to increase flow during demand, which are hallmark features of CMD.\u003c/p\u003e \u003cp\u003eOur findings are consistent with prior invasive physiology studies. Milzi et al.\u003csup\u003e16\u003c/sup\u003e showed that angiography-derived index of microvascular resistance (aIMR) was elevated across all three coronary territories in MINOCA patients, regardless of subtype (takotsubo, inflammatory, or \u0026ldquo;unclear\u0026rdquo;). Their \u0026ldquo;unclear\u0026rdquo; subgroup \u0026ndash; characterized by normal CMR findings and a demographic profile similar to our cohort - had significantly higher microvascular resistance than controls (30.6\u0026thinsp;\u0026plusmn;\u0026thinsp;8.5 vs. 22.1\u0026thinsp;\u0026plusmn;\u0026thinsp;5.9, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Notably, this subgroup represented 45% of all MINOCA patients, which relates to a proportion of normal CMR findings in our cohort. Importantly, Milzi et al.\u0026acute;s data support the view that CMD is not merely an epiphenomenon but may represent a core pathophysiological feature of MINOCA.\u003c/p\u003e \u003cp\u003eAdditional support comes from long-term imaging studies. In the SMINC-2 cohort, Johansson et al.\u003csup\u003e17\u003c/sup\u003e reported persistently reduced stress perfusion years after the index MINOCA event, despite normal baseline CMR findings. Their results, obtained using quantitative stress perfusion imaging, mirror our observations and suggest that CMD may represent a chronic microvascular phenotype rather than a transient event-related abnormality.\u003c/p\u003e \u003cp\u003eIn our study, 42% of MINOCA patients with normal CMR findings met established quantitative perfusion thresholds for CMD\u003csup\u003e\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u003c/sup\u003e. Although the causal relationship between CMD and myocardial injury in MINOCA remains incompletely understood, the clinical significance of CMD is increasingly recognized. CMD has been linked to angina, impaired quality of life, and an elevated risk of major adverse cardiovascular events in patients without obstructive coronary artery disease. Detecting CMD in MINOCA may therefore have important diagnostic and prognostic information and may inform future therapeutic strategies, even though optimal treatment in this population is not yet defined.\u003c/p\u003e \u003cp\u003eNotably, more than two-thirds (69.6%) of MINOCA patients with normal CMR demonstrated non-obstructive atherosclerotic plaque on coronary angiography. This observation suggests a potential interplay between non-obstructive atherosclerosis and microvascular dysfunction. Previous studies have reported similar associations\u003csup\u003e\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u003c/sup\u003e, indicating that shared mechanisms such as endothelial dysfunction, inflammation, or diffuse microvascular remodeling may contribute to both processes. The exact nature of this relationship warrants further investigation.\u003c/p\u003e \u003cp\u003eIn summary, we found that a substantial proportion of MINOCA patients with entirely normal conventional CMR demonstrate impaired stress perfusion and reduced myocardial perfusion reserve on early quantitative stress-perfusion CMR. These abnormalities reveal a high prevalence of coronary microvascular dysfunction that is not detectable with routine imaging. Our data suggest that CMD represents a plausible and underappreciated mechanism of myocardial injury in MINOCA and highlight the added diagnostic value of incorporating quantitative perfusion CMR into the evaluation of patients with unclear causes of myocardial injury.\u003c/p\u003e"},{"header":"Limitations","content":"\u003cp\u003eThis study has several limitations. First, the sample size was modest and derived from a single center, which may limit the generalizability of the findings. Second, although the control group was age- and sex-matched, differences in cardiovascular risk factors and medication use between groups may have influenced perfusion measurements. Third, we did not perform invasive coronary microvascular assessment, which precludes direct comparison between invasive and noninvasive measures of CMD. Fourth, the absence of longitudinal follow-up prevents assessment of the prognostic implications of CMD identified on quantitative stress-perfusion CMR. Finally, although automated perfusion analysis reduces operator dependence, technical factors such as slice selection, motion artifacts, and hemodynamic variability during regadenoson stress may have affected quantitative perfusion values.\u003c/p\u003e"},{"header":"Conclusions","content":"\u003cp\u003eEarly quantitative stress-perfusion CMR identifies impaired stress myocardial blood flow and myocardial perfusion reserve in substantial proportion of MINOCA patients who otherwise demonstrate normal findings on conventional CMR. These abnormalities reveal coronary microvascular dysfunction in nearly half of such patients, underscoring CMD as a plausible and under-recognized mechanism of myocardial injury in this heterogeneous clinical syndrome. Our findings highlight the added diagnostic value of quantitative perfusion CMR and support its integration into the evaluation of patients with MINOCA when routine imaging does not clarify the underlying cause.\u003c/p\u003e "},{"header":"Declarations","content":"\u003cp\u003e \u003ch2\u003eCompeting interests\u003c/h2\u003e \u003cp\u003eThe author(s) declare no competing interests.\u003c/p\u003e \u003c/p\u003e\u003ch2\u003eFunding\u003c/h2\u003e \u003cp\u003eNo external funding was received. Open access funding was provided by Uppsala University.\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eR.S. participated in the patient inclusion, image acquisition, performed image, data and statistical analysis, as well as drafted the manuscript. J.L. and B.L. participated in the design of the study, interpretation of data and revised the manuscript. A-M.M. participated in patient inclusion and image acquisition. J.B. participated in image acquisition and sequence optimization. K-H.G. and A.M. participated in interpretation of data and revised manuscript. T.B. participated in the design of the study and patient inclusion, as well as supervised image acquisition, data and statistical analysis and revised the manuscript. All authors read and approved the final manuscript. The patients provided written informed consent to publish their individual data on group level as well as anonymized images in this manuscript. The consent forms are held in the clinical notes of the patients and are available for the Editor-in-Chief for review.\u003c/p\u003e\u003ch2\u003eData Availability\u003c/h2\u003e\u003cp\u003eData supporting the findings in this study are available from the corresponding author upon reasonable request.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eAgarwal, A., Patel, R. \u0026amp; Khalique, O. K. 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Rep.\u003c/em\u003e \u003cb\u003e13\u003c/b\u003e (1), 22094. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1038/s41598-023-49223-w\u003c/span\u003e\u003cspan address=\"10.1038/s41598-023-49223-w\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2023).\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"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":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Cardiac magnetic resonance (CMR), quantitative stress-perfusion CMR (Q-CMR), myocardial infarction with non-obstructive coronary arteries (MINOCA), coronary microvascular dysfunction (CMD)","lastPublishedDoi":"10.21203/rs.3.rs-8903448/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8903448/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eCoronary microvascular dysfunction (CMD) is a proposed mechanism of myocardial infarction with non-obstructive coronary arteries (MINOCA), but the value of early quantitative stress-perfusion CMR (Q-CMR) in this setting is not fully established. We aimed to assess the prevalence of CMD using Q-CMR in patients with a working diagnosis of MINOCA and otherwise normal CMR findings. Of 46 consecutive MINOCA patients referred for CMR between 2021 and 2024, 23 had normal findings on the CMR at rest and were included. They were compared with age- and sex-matched healthy controls without coronary artery disease, confirmed by coronary CT angiography. All underwent dual-sequence first-pass perfusion CMR at rest and during regadenoson stress. Automated AI-based analysis quantified myocardial blood flow (MBF) and myocardial perfusion reserve (MPR). CMR at rest was considered normal in the absence of edema, late gadolinium enhancement, or other pathology. The MINOCA patients (mean age 63\u0026thinsp;\u0026plusmn;\u0026thinsp;10 years, 61% female) were scanned a median of 15 days after admission. Compared with controls, they had lower MPR (1.88\u0026thinsp;\u0026plusmn;\u0026thinsp;0.59 vs. 2.30\u0026thinsp;\u0026plusmn;\u0026thinsp;0.55; p\u0026thinsp;=\u0026thinsp;0.013) and lower stress MBF (2.56\u0026thinsp;\u0026plusmn;\u0026thinsp;0.81 vs. 2.96\u0026thinsp;\u0026plusmn;\u0026thinsp;0.53 mL/g/min; p\u0026thinsp;=\u0026thinsp;0.044), while rest MBF was similar. CMD criteria were met in 43% of MINOCA patients and in none of the controls. In conclusions, early Q-CMR identifies reduced stress MBF and MPR in MINOCA patients with otherwise normal CMR and reveals CMD in nearly half of them, supporting microvascular dysfunction as a potential mechanism of myocardial injury.\u003c/p\u003e","manuscriptTitle":"Early quantitative stress-perfusion cardiac magnetic resonance identifies coronary microvascular dysfunction in MINOCA patients with otherwise normal cardiac magnetic resonance findings","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-05-15 02:33:46","doi":"10.21203/rs.3.rs-8903448/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"reviewersInvited","content":"","date":"2026-05-05T23:49:41+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2026-03-10T05:37:23+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-02-18T05:08:01+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2026-02-18T05:06:22+00:00","index":"","fulltext":""},{"type":"submitted","content":"Scientific Reports","date":"2026-02-17T17:42:05+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"f1d43b51-7228-4be2-8ea7-e387281a0f5d","owner":[],"postedDate":"May 15th, 2026","published":true,"recentEditorialEvents":[{"type":"reviewersInvited","content":"7","date":"2026-05-05T23:49:41+00:00","index":"","fulltext":""}],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[{"id":68153527,"name":"Health sciences/Cardiology"},{"id":68153528,"name":"Health sciences/Diseases"},{"id":68153529,"name":"Health sciences/Medical research"}],"tags":[],"updatedAt":"2026-05-15T02:33:46+00:00","versionOfRecord":[],"versionCreatedAt":"2026-05-15 02:33:46","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8903448","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8903448","identity":"rs-8903448","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}