4D-CTA Collateral Status Predicts Functional Outcome and Parenchymal Hematoma in Anterior Circulation Large Vessel Occlusion Stroke

4D-CTA Collateral Status Predicts Functional Outcome and Parenchymal Hematoma in Anterior Circulation Large Vessel Occlusion Stroke | 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 4D-CTA Collateral Status Predicts Functional Outcome and Parenchymal Hematoma in Anterior Circulation Large Vessel Occlusion Stroke Jiacai Zuo, La Liu, Longzhou Yin, Zhaokun Li, Xinyu Zou, Xiaochen Gong, and 2 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8778505/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 Background Functional recovery after endovascular thrombectomy (EVT) for anterior-circulation large-vessel occlusion (LVO) stroke remains heterogeneous. Four-dimensional computed tomography angiography (4D-CTA) enables dynamic collateral assessment, but its utility for EVT triage remains uncertain. Methods We retrospectively analyzed 196 anterior-circulation LVO patients who underwent 4D-CTA. Collaterals were graded on a 0–4 scale and categorized as poor (0–1), intermediate (2), or good (3–4); for parenchymal hematoma (PH), collaterals were dichotomized as poor (0–1) versus non-poor (2–4). Primary outcomes were 90-day modified Rankin Scale (mRS) shift and PH occurrence. Multivariable ordinal logistic regression assessed mRS shift, and Firth logistic regression assessed PH. EVT subgroup models additionally adjusted for reperfusion status. Results Among 196 patients (59.2% EVT), median mRS (interquartile range [IQR]) improved across collateral tiers: 3 (1–4), 2 (1–3), and 1 (0–1) for poor, intermediate, and good collaterals, respectively ( P < 0.001). Favorable outcome (mRS 0–2) increased from 46.2% to 96.2%. After adjustment, good collaterals predicted a favorable mRS shift (cOR 0.24, 95% confidence interval [CI] 0.08–0.66; P = 0.005). PH occurred in 7.7%, with rates of 23.1%, 7.8%, and 0% across collateral tiers. Non-poor collaterals were protective against PH (odds ratio [OR] 0.18, 95% CI 0.04–0.80; P = 0.024), including in the EVT subgroup (OR 0.13, 95% CI 0.03–0.70; P = 0.018). No collateral-by-EVT interaction was observed ( P for interaction = 0.523). Conclusions 4D-CTA collateral status independently predicts 90-day functional outcomes and PH risk. Poor collaterals alone should not preclude EVT in otherwise eligible patients. acute ischemic stroke collateral circulation four-dimensional CTA functional outcome parenchymal hematoma Figures Figure 1 Figure 2 Figure 3 Figure 4 Introduction Acute ischemic stroke (AIS) remains a leading cause of mortality and morbidity. Despite successful reperfusion therapies, particularly endovascular thrombectomy (EVT) for large-vessel occlusion (LVO) 1 , functional outcomes remain heterogeneous 2 . This variability is not solely attributable to treatment latency or recanalization success; rather, downstream perfusion and microvascular integrity are pivotal. Leptomeningeal collateral circulation critically determines tissue viability following arterial occlusion. Collateral flow sustains perfusion distal to occlusion. Inadequate collateral recruitment accelerates infarct expansion and penumbral loss 3 , 4 , whereas preserved collaterals maintain tissue viability and enhance neurological recovery. Collateral status is conventionally assessed via single-phase computed tomography angiography (sCTA), which provides only a static snapshot of contrast transit, potentially overlooking delayed collateral filling and underestimating collateral robustness 3 , 5 – 7 . Robust collaterals correlate with reduced 90-day disability, whereas poor collateralization increases severe hemorrhagic transformation risk 8 – 10 . Recent studies suggest that time-resolved imaging—specifically four-dimensional CTA (4D-CTA)—offers a more accurate representation of collateral dynamics than sCTA by capturing delayed and asynchronous flow patterns 3 , 8 . Prior studies often used heterogeneous grading systems, focused disproportionately on EVT-treated populations, or lacked comprehensive safety analyses. Data on standardized 4D-CTA collateral assessment in real-world cohorts including non-EVT patients remain sparse. The present study evaluates the association between collateral status assessed by 4D-CTA and 90-day functional outcomes, as well as the risk of parenchymal hematoma (PH), in a retrospective cohort of AIS patients. We hypothesize that poor 4D-CTA collateral status predicts unfavorable 90-day functional outcomes and parenchymal hematoma. Methods Study Population This retrospective, observational, real-world cohort study was conducted at Mianyang Central Hospital. We screened consecutive adult patients with AIS who underwent 4D-CTA during the acute phase between June 2020 and June 2023. The Biomedical Ethics Committee of Mianyang Central Hospital approved the study and waived informed consent due to the retrospective and anonymous nature of the data. Inclusion criteria were: (1) age ≥ 18 years; (2) clinical diagnosis of AIS; and (3) unilateral anterior-circulation LVO of the middle cerebral artery (MCA) confirmed on baseline 4D-CTA. Exclusion criteria were: (1) inadequate image quality precluding reliable collateral grading on 4D-CTA; or (2) substantial pre-stroke disability (modified Rankin Scale (mRS) 11 > 2). Data Collection Clinical Data Collection The following baseline data were extracted: (1) demographics: age, sex, body mass index (BMI) ; (2) clinical metrics: the National Institutes of Health Stroke Scale (NIHSS) (range 0–42) 12 , onset-to-computed tomography (CT) time (from symptom onset or last known well); (3) imaging: Alberta Stroke Program Early CT Score (ASPECTS) 13 and occlusion laterality; (4) vascular risk factors: hypertension, diabetes, atrial fibrillation, and coronary heart disease; (5) laboratory parameters: glycated hemoglobin (HbA1c), low-density lipoprotein cholesterol (LDL-C), homocysteine, and N-terminal pro–B-type natriuretic peptide (NT-proBNP); and (6) acute treatments: intravenous thrombolysis (IVT) and EVT. Imaging Data Collection Dynamic contrast-enhanced CT was performed using a dual-source CT scanner (Somatom Force, Siemens Healthineers, Forchheim, Germany). After intravenous administration of iopamidol (40 mL; Bracco, Shanghai, China) and saline flush (40 mL at 5 mL/s), dynamic acquisition began 4 s post-injection using shuttle-mode (80 kV, 130 mAs, 114 mm coverage, 0.625 mm slice). Twenty-nine acquisitions over 56 s were reconstructed as 4D-CTA datasets using the Dynamic Analysis module (uWS-CT, version R006; United Imaging Healthcare, Shanghai, China) for collateral assessment. Baseline ischemic changes were quantified using the ASPECTS on non-contrast CT (NCCT) or CTA source images. Collateral status was graded on 4D-CTA using the modified American Society of Interventional and Therapeutic Neuroradiology/Society of Interventional Radiology (ASITN/SIR) collateral grading system (score 0–4) 14 : 0, no visible collaterals to the ischemic territory; 1, slow collaterals to the periphery with persistence of some defect; 2, rapid collaterals to the periphery with persistence of some defect; 3, collaterals with slow but complete angiographic blood flow of the ischemic bed by the late venous phase; and 4, complete and rapid collateral blood flow to the vascular bed in the entire ischemic territory. For descriptive and stratified analyses, scores were categorized into three tiers: poor (0–1), intermediate (2), and good (3–4). For the primary hemorrhagic safety analysis, collateral status was dichotomized as poor (0–1) vs. non-poor (2–4). Collateral assessment was independently conducted by two blinded readers, with discrepancies resolved by consensus or adjudication by a senior neuroradiologist. Treatment Classification Standard medical management (SMM) followed guideline-based practices, including antiplatelet therapy, anticoagulation (as needed), statins, and supportive care. IVT was provided to eligible patients within the therapeutic window. EVT was performed by a dedicated neurointerventional team per institutional protocols and national guidelines. Techniques included aspiration thrombectomy, stent-retriever thrombectomy, balloon angioplasty, and intracranial stenting. Post-procedural reperfusion was evaluated using the expanded Thrombolysis in Cerebral Infarction (eTICI) scale 15 . For prespecified analyses in the EVT subgroup, successful reperfusion was defined as eTICI grade of 2b67 or higher. Outcomes The primary efficacy outcome was the 90-day functional outcome assessed by the full distribution of the mRS (0–6), analyzed using an ordinal shift approach. A secondary efficacy outcome was functional independence at 90 days, defined as mRS 0–2. Intracranial hemorrhages were identified on follow-up CT or magnetic resonance imaging (MRI) within 7 days after admission or before discharge, as well as on additional imaging obtained during neurological deterioration. Hemorrhages were categorized using the Heidelberg Bleeding Classification (HBC) 16 . The primary safety endpoint was PH, specifically PH1 or PH2 (HBC categories 3 and 4). PH was chosen as the primary safety marker for severe hemorrhagic transformation, excluding milder hemorrhagic patterns due to their lower clinical impact 17 . Statistical Analysis Continuous variables were summarized as mean ± standard deviation (SD) or median [IQR], and categorical variables as frequencies (percentages). Baseline characteristics were compared across collateral categories using one-way analysis of variance (ANOVA) or Kruskal-Wallis test for continuous variables, and χ² test or Fisher exact test. For the primary endpoint (90-day mRS shift), multivariable ordinal logistic regression was used 18 . Collateral status was treated as a three-level categorical variable, with the poor group as the reference. A test for trend was conducted by coding collateral status as an ordinal variable. For the primary safety outcome, logistic regression was performed with collateral status prespecified as poor (0–1) vs. non-poor (2–4) to address sparse-data bias, given no PH events in the collateral 3–4 group. In the EVT subgroup, models were additionally adjusted for successful reperfusion (eTICI ≥ 2b67). Sensitivity analyses included Firth bias-reduced logistic regression and modeling collateral grade as a continuous variable. All tests were two-sided, with P < 0.05 considered significant. Analyses were performed using R version 4.5.2 (R Foundation for Statistical Computing, Vienna, Austria). Results Study population. A total of 196 consecutive patients with AIS who underwent 4D-CTA and had complete clinical, radiological, and 90-day follow-up data were included in the final analysis. Among the cohort, 116 patients (59.2%) underwent EVT, while 80 patients (40.8%) received medical management alone. Baseline characteristics categorized by 4D-CTA collateral status are summarized in Table 1. Inter-rater reliability for 4D-CTA collateral grading was high (weighted Cohen’s kappa (κw) = 0.924; exact agreement = 91.84%) (Supplementary Table S10). Based on collateral scores, 39 patients (19.9%) were classified as having poor collaterals (score 0–1), 77 (39.3%) as intermediate (score 2), and 80 (40.8%) as good (score 3–4). Patients with better collaterals showed lower baseline stroke severity and limited early ischemic changes. Median NIHSS scores decreased across collateral categories (15.0 [12.0--18.5], 12.0 [8.0--16.0], and 4.0 [2.0--8.0]; P < 0.001), while ASPECTS increased (6.0 [5.5--7.0], 7.0 [6.0--8.0], and 9.0 [8.0--9.0]; P < 0.001). The proportion of patients undergoing EVT differed significantly across groups: 84.6% in the poor collateral group, 74.0% in the intermediate group, and 32.5% in the good collateral group ( P <0.001). Other demographic profiles and vascular risk factors were largely balanced across the strata. Extended laboratory and metabolic variables showed no clinically meaningful differences across collateral strata (Supplementary Table S1). Functional outcomes Functional outcomes at 90 days differed according to collateral status (Table 2A). Median mRS scores showed graded improvement across categories: 3 [1–4] for poor, 2 [1–3] for intermediate, and 1 [0–1] for good collaterals ( P < 0.001). Favorable outcomes (mRS 0–2) increased from 46.2% (poor) to 67.5% (intermediate) and 96.2% (good) ( P < 0.001), demonstrating a collateral-dependent gradient (Fig. 1). In multivariable ordinal logistic regression analyses adjusting for age, sex, baseline NIHSS, ASPECTS, onset-to-CT time, IVT, and EVT (Table 2B), robust collateral status was independently associated with a favorable shift toward lower mRS scores at 90 days. Compared with the poor collateral group (0–1), patients with good collaterals (3–4) exhibited significantly better functional outcomes (adjusted cOR, 0.24; 95% CI, 0.09–0.64; P = 0.005), whereas the association for intermediate collaterals did not reach statistical significance. Notably, no significant interaction was observed between collateral status and EVT regarding functional outcomes ( P for interaction = 0.523) (Supplementary Table S9). In the EVT subgroup, after additional adjustment for successful reperfusion (eTICI ≥ 2b67), collateral status was no longer independently associated with mRS shift ( P for trend = 0.321), although the direction of effect remained consistent (Supplementary Table S3). Parenchymal Hematoma PH occurred in 15 patients (7.7%). The PH rate decreased across collateral grades (0–1: 23.1%, 2: 7.8%, 3–4: 0%) (Fig. 2 and Supplementary Table S4). For the primary safety analysis, collateral status was dichotomized into poor (0–1) and non-poor (2–4) to ensure model stability, given the absence of PH events in the highest collateral category (3–4) (Table 3). PH occurred significantly higher in patients with poor collaterals than in those with non-poor collaterals (23.1% vs. 3.8%). After multivariable adjustment, non-poor collateral status was independently associated with a markedly reduced risk of PH (adjusted OR, 0.18; 95% CI, 0.04–0.80; P = 0.024). Among patients undergoing EVT, PH was observed in 27.3% of those with poor collaterals compared with 6.0% of those with non-poor collaterals. This protective association remained robust after adjustment including successful reperfusion (eTICI ≥ 2b67) (adjusted OR, 0.13; 95% CI, 0.03–0.70; P = 0.018). Sensitivity analyses Sensitivity analyses confirmed the robustness of the primary findings. When the collateral grade was modeled as a continuous variable (per 1-point increase), higher collateral score was independently associated with better functional outcome in the overall cohort (adjusted cOR, 0.50; 95% CI, 0.34–0.75; P = 0.001) (Supplementary Table S6). Similarly, higher collateral score was associated with a lower risk of PH in both the overall cohort (adjusted OR, 0.36; 95% CI, 0.14–0.89; P = 0.027) and the EVT subgroup (adjusted OR, 0.31; 95% CI, 0.10–0.95; P = 0.041). Additional sensitivity analyses using three-category collateral classification with Firth bias-reduced regression yielded consistent effect directions and significant ordinal trends (Supplementary Tables S4 and S5). After inverse probability of treatment weighting (IPTW) and doubly robust adjustment 19,20 , the associations between EVT and both 90-day functional outcome and PH were substantially attenuated and no longer statistically significant (Supplementary Table S7 and S8). In receiver operating characteristic (ROC) analyses, the model incorporating collateral status showed a modest improvement in discrimination compared with the clinical model alone (AUC = 0.86 vs. AUC = 0.848) (Supplementary Fig. S1). Discussion In this single-center cohort of acute anterior-circulation LVO stroke, 4D-CTA collateral status was associated with 90-day functional outcome and PH risk, supporting time-resolved collateral assessment for early risk stratification. Because this retrospective cohort included patients treated with EVT and those managed without EVT, confounding by indication is likely. Propensity score–based sensitivity analyses (including IPTW and doubly robust adjustment) suggested that unadjusted differences in functional outcome and PH were largely attributable to baseline severity and treatment selection, rather than EVT itself. We therefore adjusted for treatment status and performed stratified analyses when evaluating the prognostic value of collateral status. Functional outcomes improved stepwise across collateral tiers (median mRS 3, 2, and 1 for grades 0–1, 2, and 3–4). After adjustment, better collateral status remained associated with a favorable mRS shift in the overall cohort ( P for trend < 0.001). No significant interaction was observed between collateral status and EVT regarding functional outcomes. The high rate of mRS 0–2 in the good-collateral group likely reflects slower infarct progression and milder early symptoms, which can delay care-seeking and prolong onset-to-CT time. Good collaterals are also linked to lower baseline stroke severity and better penumbral preservation. Time-resolved 4D-CTA may further enrich the highest collateral tier by more stringently capturing sustained and delayed filling. Poor collaterals were associated with higher PH risk, whereas non-poor collaterals (2–4) were protective in both the overall cohort and the EVT subgroup after adjustment for reperfusion status. Sensitivity analyses modeling the collateral score as a continuous variable yielded consistent associations for both functional independence and PH risk, further underscoring the reliability of these findings. Our results are consistent with prior work showing that better collaterals are associated with smaller infarct burden and improved outcomes 3 , 4 , 8 , 21 . Time-resolved imaging may offer additional prognostic value over sCTA by reducing underestimation of delayed collateral recruitment 3 , 5 . Secondary analyses of EVT trials also support this interpretation. In the TENSION trial, collateral status and EVT were independently associated with mRS shift, and the EVT effect was not significantly modified by collateral grade 22 . This is consistent with our non-significant collateral-by-EVT interaction and suggests that collateral status is a strong prognostic marker rather than an exclusion criterion for EVT. In routine practice, EVT-treated patients often present with greater stroke severity, lower ASPECTS, and poorer collaterals; such baseline imbalances may further limit power to detect interaction effects. Regarding hemorrhagic outcomes, impaired collaterals have been linked to higher hemorrhagic transformation risk after reperfusion. In a 4D-CTA–based study, Cao et al. reported higher hemorrhagic transformation rates in patients with poor collaterals after EVT 9 . Registry studies using the modified ASITN/SIR scale have similarly associated collateral robustness with hemorrhagic risk and functional outcome, although effect sizes vary by population 23 , 24 . By focusing on PH as a clinically meaningful and homogeneous safety endpoint, our study extends these observations and demonstrates that 4D-CTA assessment is highly informative for identifying patients at elevated risk for severe hemorrhagic complications. Mechanistically, the contrasting cases in Figs. 3 – 4 illustrate that robust collaterals may sustain penumbral perfusion, slow core expansion, and preserve microvascular integrity 25 , which could reduce reperfusion injury and PH 26 . Prior time-resolved imaging studies have linked dynamic collateral measures to infarct growth and hypoperfusion burden, supporting this biological rationale 3 , 4 , 9 , 27 . Conversely, poor collaterals may reflect more severe ischemia and blood–brain barrier disruption, increasing susceptibility to reperfusion injury and PH. Limitations The retrospective single-center design limits generalizability and may introduce selection bias; residual confounding from treatment selection or unmeasured variables cannot be excluded. The small number of PH events may limit precision, particularly in subgroup analyses; we used Firth’s penalized logistic regression to mitigate small-sample bias. Collateral grading is semi-quantitative and subject to inter-rater variability, and performance may vary with acquisition and reconstruction protocols 14 , 28 . Standardized imaging and scoring procedures are therefore needed. Prospective multicenter studies are needed to validate these findings and to define the incremental clinical value of 4D-CTA–based collateral assessment for treatment decision-making. Conclusion 4D-CTA collateral status was independently associated with 90-day functional outcome and PH risk in anterior-circulation LVO stroke. The graded association supports time-resolved collateral assessment for early risk stratification. Although poor collaterals were linked to higher PH risk, collateral status alone should not exclude otherwise eligible patients from EVT. Declarations Data availability The data in this study were obtained from the corresponding author upon a reasonable request. Acknowledgements The authors acknowledge institutional support from a research project of the Sichuan Medical Association (Project No. S21023). Funding This study received no external funding. Author Contributions J.Z. and L.L. developed the study methodology, conducted the data analysis, interpreted the results, and drafted the initial manuscript. L.L. and L.Y. assisted with data acquisition. X.Z. and X.G. assisted with data curation. Z.L. and Y.Y. verified and summarized the analysis results. J.Z. and Y.T. planned the study and provided critical revisions of the manuscript. All authors read and approved the final manuscript. Ethics declarations Ethics approval and consent to participate This study was conducted in accordance with the Declaration of Helsinki (as revised in 2013) and was approved by the Biomedical Ethics Committee of Mianyang Central Hospital (institutional review board approval number: S20240222-01). The requirement for informed consent was waived due to the retrospective nature of the study and the use of de-identified data. Consent for publication Not applicable. Competing interests The authors declare no competing interests. References Goyal M, Menon BK, van Zwam WH, et al. Endovascular thrombectomy after large-vessel ischaemic stroke: A meta-analysis of individual patient data from five randomised trials. Lancet. 2016;387(10029):1723–31. 10.1016/S0140-6736(16)00163-X . 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Baseline characteristics by collateral group (0-1, 2, 3-4) Variable Collateral 0–1 (n=39) Collateral 2 (n=77) Collateral 3–4 (n=80) P value Age, years 74.0 [61.5, 81.0] 72.0 [64.0, 78.0] 68.0 [58.0, 76.2] 0.063 Onset-to-CT time, h 4.0 [2.0, 7.0] 5.0 [2.0, 8.0] 6.0 [3.0, 10.0] 0.046 NIHSS on admission 15.0 [12.0, 18.5] 12.0 [8.0, 16.0] 4.0 [2.0, 8.0] <0.001 ASPECTS 6.0 [5.5, 7.0] 7.0 [6.0, 8.0] 9.0 [8.0, 9.0] <0.001 Male sex 26 (66.7%) 45 (58.4%) 59 (73.8%) 0.090 Left MCA occlusion 19 (48.7%) 37 (48.1%) 39 (48.8%) 0.997 Hypertension 28 (71.8%) 58 (75.3%) 54 (67.5%) 0.594 Diabetes 7 (17.9%) 17 (22.1%) 10 (12.5%) 0.280 Atrial fibrillation 18 (46.2%) 34 (44.2%) 27 (33.8%) 0.293 IVT 7 (17.9%) 13 (16.9%) 14 (17.5%) 0.989 EVT 33 (84.6%) 57 (74.0%) 26 (32.5%) <0.001 CT, computed tomography; NIHSS, National Institutes of Health Stroke Scale; ASPECTS, Alberta Stroke Program Early CT Score; MCA, middle cerebral artery; IVT, intravenous thrombolysis; EVT, Endovascular therapy. Between-group comparisons used Kruskal–Wallis tests for continuous variables and χ² tests (or Fisher’s exact tests when appropriate) for categorical variables. Table 2. Collateral status and 90-day functional outcome Table 2A. Descriptive 90-day outcomes by collateral group Outcome Collateral 0–1 (n=39) Collateral 2 (n=77) Collateral 3–4 (n=80) P value mRS score at 90 days, median (IQR) 3 (1–4) 2 (1–3) 1 (0–1) <0.001 mRS 0–2, n (%) 18 (46.2) 52 (67.5) 77 (96.2) <0.001 mRS 3–6, n (%) 21 (53.8) 25 (32.5) 3 (3.8) <0.001 Table 2B. Association of collateral status with 90-day modified Rankin Scale shift Cohort Comparison Adjusted cOR (95% CI) P value P for trend Overall cohort (N=196) a Collateral 2 vs 0–1 0.72 (0.33–1.53) 0.395 Collateral 3–4 vs 0–1 0.24 (0.09–0.64) 0.005 0.004 EVT subgroup (N=116) b Collateral 2 vs 0–1 0.82 (0.35–1.94) 0.652 Collateral 3–4 vs 0–1 0.51 (0.14–1.81) 0.296 0.321 IQR, interquartile range; mRS, modified Rankin Scale; EVT, Endovascular therapy; cOR, common odds ratio; CI, confidence interval. a Overall cohort model was adjusted for age, sex, baseline NIHSS, ASPECTS, onset-to-CT time, intravenous thrombolysis, and endovascular therapy. b EVT subgroup model was additionally adjusted for successful reperfusion, defined as expanded Thrombolysis in Cerebral Infarction (eTICI) grade ≥2b67. In the ordinal shift analysis, a common odds ratio (cOR) < 1 indicates a shift toward lower mRS scores, corresponding to a more favorable functional outcome. P for trend was obtained by modeling collateral status as an ordinal variable in the adjusted proportional odds model (coded as 0–1, 2, and 3–4). Table 3. Association of collateral status (0-1 vs 2-4) with parenchymal hematoma (PH) Overall cohort (N=196) Collateral group PH, n/N (%) Adjusted OR (95% CI) P value 0–1 (reference) 9/39 (23.1%) 1.00 (reference) — 2–4 6/157 (3.8%) 0.18 (0.04–0.80) 0.024 EVT subgroup (N=116) Collateral group PH, n/N (%) Adjusted OR (95% CI) P value 0–1 (reference) 9/33 (27.3%) 1.00 (reference) — 2–4 5/83 (6.0%) 0.13 (0.03–0.70) 0.018 PH, parenchymal hematoma; OR, odds ratio; CI, confidence interval; EVT, Endovascular therapy. Overall cohort model adjusted for age, sex, NIHSS, ASPECTS, onset-to-CT time, IVT, and EVT. EVT subgroup model adjusted for age, sex, NIHSS, ASPECTS, onset-to-CT time, IVT, and eTICI_success (eTICI ≥2b67). Additional Declarations No competing interests reported. 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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-8778505","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":592105053,"identity":"7dcaac18-3878-4c43-aa1c-b00548bfd2a4","order_by":0,"name":"Jiacai Zuo","email":"","orcid":"","institution":"Mianyang Central Hospital, University of Electronic Science and Technology of China","correspondingAuthor":false,"prefix":"","firstName":"Jiacai","middleName":"","lastName":"Zuo","suffix":""},{"id":592105056,"identity":"d89d0f9b-2500-44ac-b617-37076f58f989","order_by":1,"name":"La Liu","email":"","orcid":"","institution":"Zigong First People’s Hospital, Zigong Academy of Medical Sciences","correspondingAuthor":false,"prefix":"","firstName":"La","middleName":"","lastName":"Liu","suffix":""},{"id":592105059,"identity":"b3e64380-e818-44c7-9fe0-4a9ccdec8080","order_by":2,"name":"Longzhou Yin","email":"","orcid":"","institution":"Mianyang Central Hospital, University of Electronic Science and Technology of China","correspondingAuthor":false,"prefix":"","firstName":"Longzhou","middleName":"","lastName":"Yin","suffix":""},{"id":592105062,"identity":"2e84dd9d-0abf-452b-9f8a-4c99994c3ec2","order_by":3,"name":"Zhaokun Li","email":"","orcid":"","institution":"Mianyang Central Hospital, University of Electronic Science and Technology of China","correspondingAuthor":false,"prefix":"","firstName":"Zhaokun","middleName":"","lastName":"Li","suffix":""},{"id":592105064,"identity":"1e084f7a-3f9b-4cd1-a5a8-1d42d9ec2f10","order_by":4,"name":"Xinyu Zou","email":"","orcid":"","institution":"Mianyang Central Hospital, University of Electronic Science and Technology of China","correspondingAuthor":false,"prefix":"","firstName":"Xinyu","middleName":"","lastName":"Zou","suffix":""},{"id":592105067,"identity":"303c9b20-2bae-4333-9bed-8fdc7b405ae5","order_by":5,"name":"Xiaochen Gong","email":"","orcid":"","institution":"Mianyang Central Hospital, University of Electronic Science and Technology of China","correspondingAuthor":false,"prefix":"","firstName":"Xiaochen","middleName":"","lastName":"Gong","suffix":""},{"id":592105069,"identity":"15f69bc6-3436-4b9f-a998-3bc5cd01250c","order_by":6,"name":"Yi Yang","email":"","orcid":"","institution":"Mianyang Central Hospital, University of Electronic Science and Technology of China","correspondingAuthor":false,"prefix":"","firstName":"Yi","middleName":"","lastName":"Yang","suffix":""},{"id":592105071,"identity":"0fe2642c-fb38-4150-be9b-7ec7bdc59951","order_by":7,"name":"Yufeng Tang","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAxklEQVRIiWNgGAWjYDCCA0BcAcT8zMwHHxCv5QwQS7azJRuQpsXgPI+ZAFE6+G6fMZM4UHHHbvNhBjMGhhqbaIJaJM/lALWceZa87TBD2gOGY2m5DYS0GJzhMZP+2HY42ewww3EDxobDxGmROPjvcLJxM2ObBAlaGg7bGTAzsxGnRfIMW7HFgWOHEyQOszEbJBDjF74zzBtvHKg5bM/ff/7jgw81NoS1MDBwgCMwEawygbByEGB/ACLtiVM8CkbBKBgFIxIAACPdQ8qkjjkkAAAAAElFTkSuQmCC","orcid":"","institution":"Mianyang Central Hospital, University of Electronic Science and Technology of China","correspondingAuthor":true,"prefix":"","firstName":"Yufeng","middleName":"","lastName":"Tang","suffix":""}],"badges":[],"createdAt":"2026-02-03 16:40:31","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-8778505/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-8778505/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":103050017,"identity":"8e55a91e-c315-42b4-b379-9a6ba3ddc089","added_by":"auto","created_at":"2026-02-20 07:47:40","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":54088,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eDistribution of 90-day mRS scores by collateral status. \u003c/strong\u003ePatients were grouped as poor (0–1, n=39), intermediate (2, n=77), and good (3–4, n=80). Higher collateral scores were associated with a greater proportion of favorable outcomes (mRS 0–2).\u003c/p\u003e","description":"","filename":"OnlineFigure1.png","url":"https://assets-eu.researchsquare.com/files/rs-8778505/v1/8d149e38074f7b983cad4fd8.png"},{"id":102991380,"identity":"64e1d060-b000-4ad6-818d-61072beaeaf5","added_by":"auto","created_at":"2026-02-19 11:31:51","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":39495,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eParenchymal hematoma rates by collateral group. \u003c/strong\u003eParenchymal hematoma (PH) incidence is shown across collateral strata (0–1, 2, and 3–4) assessed on 4D-CTA.\u003c/p\u003e","description":"","filename":"OnlineFigure2.png","url":"https://assets-eu.researchsquare.com/files/rs-8778505/v1/bfb19581275ab768de02c7b5.png"},{"id":103050685,"identity":"6099ab3b-a562-4401-bda5-b66de11d62ef","added_by":"auto","created_at":"2026-02-20 07:53:24","extension":"jpg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":510696,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eDynamic 4D-CTA of right M1 occlusion with good collateral Status and corresponding MRI.\u003c/strong\u003e Panels A–F show sequential phases of 4D-CTA demonstrating dynamic collateral filling over time. Panel G shows diffusion-weighted imaging (DWI) on magnetic resonance imaging (MRI) with a small infarct lesion. Panel H shows susceptibility-weighted imaging (SWI) on MRI with no hemorrhagic transformation in the infarcted region.\u003c/p\u003e","description":"","filename":"Figure3.jpg","url":"https://assets-eu.researchsquare.com/files/rs-8778505/v1/92cb34345550edc85f1d6f36.jpg"},{"id":103050024,"identity":"9713d619-a3f7-4e3f-99c9-d9b0b9cc3820","added_by":"auto","created_at":"2026-02-20 07:47:45","extension":"jpg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":463659,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eDynamic 4D-CTA of left M1 occlusion with intermediate collateral Status and corresponding MRI.\u003c/strong\u003e \u0026nbsp;Panels A–F show sequential phases of 4D-CTA demonstrating left middle cerebral artery (MCA) M1 occlusion with delayed collateral filling. Panel G shows diffusion-weighted imaging (DWI) on magnetic resonance imaging (MRI) with a large infarct lesion. Panel H shows susceptibility-weighted imaging (SWI) on MRI demonstrating hemorrhagic transformation within the infarcted region.\u003c/p\u003e","description":"","filename":"Figure4.jpg","url":"https://assets-eu.researchsquare.com/files/rs-8778505/v1/95b9b115c6057f920c7f54d9.jpg"},{"id":104895118,"identity":"b30e59d2-c389-4e45-9cdc-27f654301f29","added_by":"auto","created_at":"2026-03-18 11:41:57","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2218676,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8778505/v1/00169e5e-0d02-44ad-b977-169a15c87e6e.pdf"},{"id":103049887,"identity":"9ecae177-46fa-4ec6-ac5f-893e5ff3d109","added_by":"auto","created_at":"2026-02-20 07:47:03","extension":"docx","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":2664532,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryMaterials.docx","url":"https://assets-eu.researchsquare.com/files/rs-8778505/v1/ecbe66b27fa1d6619552442e.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"4D-CTA Collateral Status Predicts Functional Outcome and Parenchymal Hematoma in Anterior Circulation Large Vessel Occlusion Stroke","fulltext":[{"header":"Introduction","content":"\u003cp\u003eAcute ischemic stroke (AIS) remains a leading cause of mortality and morbidity. Despite successful reperfusion therapies, particularly endovascular thrombectomy (EVT) for large-vessel occlusion (LVO) \u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u003c/sup\u003e, functional outcomes remain heterogeneous\u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e. This variability is not solely attributable to treatment latency or recanalization success; rather, downstream perfusion and microvascular integrity are pivotal. Leptomeningeal collateral circulation critically determines tissue viability following arterial occlusion.\u003c/p\u003e \u003cp\u003eCollateral flow sustains perfusion distal to occlusion. Inadequate collateral recruitment accelerates infarct expansion and penumbral loss\u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e,\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u003c/sup\u003e, whereas preserved collaterals maintain tissue viability and enhance neurological recovery. Collateral status is conventionally assessed via single-phase computed tomography angiography (sCTA), which provides only a static snapshot of contrast transit, potentially overlooking delayed collateral filling and underestimating collateral robustness\u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e,\u003cspan additionalcitationids=\"CR6\" citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eRobust collaterals correlate with reduced 90-day disability, whereas poor collateralization increases severe hemorrhagic transformation risk\u003csup\u003e\u003cspan additionalcitationids=\"CR9\" citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u003c/sup\u003e. Recent studies suggest that time-resolved imaging\u0026mdash;specifically four-dimensional CTA (4D-CTA)\u0026mdash;offers a more accurate representation of collateral dynamics than sCTA by capturing delayed and asynchronous flow patterns\u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e,\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003ePrior studies often used heterogeneous grading systems, focused disproportionately on EVT-treated populations, or lacked comprehensive safety analyses. Data on standardized 4D-CTA collateral assessment in real-world cohorts including non-EVT patients remain sparse.\u003c/p\u003e \u003cp\u003eThe present study evaluates the association between collateral status assessed by 4D-CTA and 90-day functional outcomes, as well as the risk of parenchymal hematoma (PH), in a retrospective cohort of AIS patients. We hypothesize that poor 4D-CTA collateral status predicts unfavorable 90-day functional outcomes and parenchymal hematoma.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eStudy Population\u003c/h2\u003e \u003cp\u003eThis retrospective, observational, real-world cohort study was conducted at Mianyang Central Hospital. We screened consecutive adult patients with AIS who underwent 4D-CTA during the acute phase between June 2020 and June 2023. The Biomedical Ethics Committee of Mianyang Central Hospital approved the study and waived informed consent due to the retrospective and anonymous nature of the data.\u003c/p\u003e \u003cp\u003eInclusion criteria were: (1) age\u0026thinsp;\u0026ge;\u0026thinsp;18 years; (2) clinical diagnosis of AIS; and (3) unilateral anterior-circulation LVO of the middle cerebral artery (MCA) confirmed on baseline 4D-CTA. Exclusion criteria were: (1) inadequate image quality precluding reliable collateral grading on 4D-CTA; or (2) substantial pre-stroke disability (modified Rankin Scale (mRS)\u003csup\u003e11\u003c/sup\u003e \u0026gt; 2).\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eData Collection\u003c/h3\u003e\n\u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eClinical Data Collection\u003c/h2\u003e \u003cp\u003eThe following baseline data were extracted: (1) demographics: age, sex, body mass index (BMI) ; (2) clinical metrics: the National Institutes of Health Stroke Scale (NIHSS) (range 0\u0026ndash;42)\u003csup\u003e\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u003c/sup\u003e, onset-to-computed tomography (CT) time (from symptom onset or last known well); (3) imaging: Alberta Stroke Program Early CT Score (ASPECTS)\u003csup\u003e\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u003c/sup\u003e and occlusion laterality; (4) vascular risk factors: hypertension, diabetes, atrial fibrillation, and coronary heart disease; (5) laboratory parameters: glycated hemoglobin (HbA1c), low-density lipoprotein cholesterol (LDL-C), homocysteine, and N-terminal pro\u0026ndash;B-type natriuretic peptide (NT-proBNP); and (6) acute treatments: intravenous thrombolysis (IVT) and EVT.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eImaging Data Collection\u003c/h3\u003e\n\u003cp\u003eDynamic contrast-enhanced CT was performed using a dual-source CT scanner (Somatom Force, Siemens Healthineers, Forchheim, Germany). After intravenous administration of iopamidol (40 mL; Bracco, Shanghai, China) and saline flush (40 mL at 5 mL/s), dynamic acquisition began 4 s post-injection using shuttle-mode (80 kV, 130 mAs, 114 mm coverage, 0.625 mm slice). Twenty-nine acquisitions over 56 s were reconstructed as 4D-CTA datasets using the Dynamic Analysis module (uWS-CT, version R006; United Imaging Healthcare, Shanghai, China) for collateral assessment. Baseline ischemic changes were quantified using the ASPECTS on non-contrast CT (NCCT) or CTA source images.\u003c/p\u003e \u003cp\u003eCollateral status was graded on 4D-CTA using the modified American Society of Interventional and Therapeutic Neuroradiology/Society of Interventional Radiology (ASITN/SIR) collateral grading system (score 0\u0026ndash;4)\u003csup\u003e14\u003c/sup\u003e: 0, no visible collaterals to the ischemic territory; 1, slow collaterals to the periphery with persistence of some defect; 2, rapid collaterals to the periphery with persistence of some defect; 3, collaterals with slow but complete angiographic blood flow of the ischemic bed by the late venous phase; and 4, complete and rapid collateral blood flow to the vascular bed in the entire ischemic territory.\u003c/p\u003e \u003cp\u003eFor descriptive and stratified analyses, scores were categorized into three tiers: poor (0\u0026ndash;1), intermediate (2), and good (3\u0026ndash;4). For the primary hemorrhagic safety analysis, collateral status was dichotomized as poor (0\u0026ndash;1) vs. non-poor (2\u0026ndash;4). Collateral assessment was independently conducted by two blinded readers, with discrepancies resolved by consensus or adjudication by a senior neuroradiologist.\u003c/p\u003e\n\u003ch3\u003eTreatment Classification\u003c/h3\u003e\n\u003cp\u003e Standard medical management (SMM) followed guideline-based practices, including antiplatelet therapy, anticoagulation (as needed), statins, and supportive care. IVT was provided to eligible patients within the therapeutic window.\u003c/p\u003e \u003cp\u003e EVT was performed by a dedicated neurointerventional team per institutional protocols and national guidelines. Techniques included aspiration thrombectomy, stent-retriever thrombectomy, balloon angioplasty, and intracranial stenting. Post-procedural reperfusion was evaluated using the expanded Thrombolysis in Cerebral Infarction (eTICI) scale\u003csup\u003e\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u003c/sup\u003e. For prespecified analyses in the EVT subgroup, successful reperfusion was defined as eTICI grade of 2b67 or higher.\u003c/p\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eOutcomes\u003c/h2\u003e \u003cp\u003eThe primary efficacy outcome was the 90-day functional outcome assessed by the full distribution of the mRS (0\u0026ndash;6), analyzed using an ordinal shift approach. A secondary efficacy outcome was functional independence at 90 days, defined as mRS 0\u0026ndash;2.\u003c/p\u003e \u003cp\u003eIntracranial hemorrhages were identified on follow-up CT or magnetic resonance imaging (MRI) within 7 days after admission or before discharge, as well as on additional imaging obtained during neurological deterioration. Hemorrhages were categorized using the Heidelberg Bleeding Classification (HBC) \u003csup\u003e\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u003c/sup\u003e. The primary safety endpoint was PH, specifically PH1 or PH2 (HBC categories 3 and 4). PH was chosen as the primary safety marker for severe hemorrhagic transformation, excluding milder hemorrhagic patterns due to their lower clinical impact\u003csup\u003e\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003eStatistical Analysis\u003c/h2\u003e \u003cp\u003eContinuous variables were summarized as mean\u0026thinsp;\u0026plusmn;\u0026thinsp;standard deviation (SD) or median [IQR], and categorical variables as frequencies (percentages). Baseline characteristics were compared across collateral categories using one-way analysis of variance (ANOVA) or Kruskal-Wallis test for continuous variables, and χ\u0026sup2; test or Fisher exact test.\u003c/p\u003e \u003cp\u003eFor the primary endpoint (90-day mRS shift), multivariable ordinal logistic regression was used\u003csup\u003e\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u003c/sup\u003e. Collateral status was treated as a three-level categorical variable, with the poor group as the reference. A test for trend was conducted by coding collateral status as an ordinal variable.\u003c/p\u003e \u003cp\u003eFor the primary safety outcome, logistic regression was performed with collateral status prespecified as poor (0\u0026ndash;1) vs. non-poor (2\u0026ndash;4) to address sparse-data bias, given no PH events in the collateral 3\u0026ndash;4 group. In the EVT subgroup, models were additionally adjusted for successful reperfusion (eTICI\u0026thinsp;\u0026ge;\u0026thinsp;2b67). Sensitivity analyses included Firth bias-reduced logistic regression and modeling collateral grade as a continuous variable.\u003c/p\u003e \u003cp\u003eAll tests were two-sided, with \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05 considered significant. Analyses were performed using R version 4.5.2 (R Foundation for Statistical Computing, Vienna, Austria).\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003e\u003cstrong\u003eStudy population.\u0026nbsp;\u003c/strong\u003eA total of 196 consecutive patients with AIS who underwent 4D-CTA and had complete clinical, radiological, and 90-day follow-up data were included in the final analysis. Among the cohort, 116 patients (59.2%) underwent EVT, while 80 patients (40.8%) received medical management alone.\u003c/p\u003e\n\u003cp\u003eBaseline characteristics categorized by 4D-CTA collateral status are summarized in Table 1. Inter-rater reliability for 4D-CTA collateral grading was high (weighted Cohen\u0026rsquo;s kappa (\u0026kappa;w) = 0.924; exact agreement = 91.84%) (Supplementary Table S10). Based on collateral scores, 39 patients (19.9%) were classified as having poor collaterals (score 0\u0026ndash;1), 77 (39.3%) as intermediate (score 2), and 80 (40.8%) as good (score 3\u0026ndash;4).\u003c/p\u003e\n\u003cp\u003ePatients with better collaterals showed lower baseline stroke severity and limited early ischemic changes. Median NIHSS scores decreased across collateral categories (15.0 [12.0--18.5], 12.0 [8.0--16.0], and 4.0 [2.0--8.0]; \u003cem\u003eP\u0026nbsp;\u003c/em\u003e\u0026lt; 0.001), while ASPECTS increased (6.0 [5.5--7.0], 7.0 [6.0--8.0], and 9.0 [8.0--9.0]; \u003cem\u003eP\u0026nbsp;\u003c/em\u003e\u0026lt; 0.001). The proportion of patients undergoing EVT differed significantly across groups: 84.6% in the poor collateral group, 74.0% in the intermediate group, and 32.5% in the good collateral group (\u003cem\u003eP\u003c/em\u003e \u0026lt;0.001). Other demographic profiles and vascular risk factors were largely balanced across the strata. Extended laboratory and metabolic variables showed no clinically meaningful differences across collateral strata (Supplementary Table S1).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunctional outcomes\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eFunctional outcomes at 90 days differed according to collateral status (Table 2A). Median mRS scores showed graded improvement across categories: 3 [1\u0026ndash;4] for poor, 2 [1\u0026ndash;3] for intermediate, and 1 [0\u0026ndash;1] for good collaterals (\u003cem\u003eP\u003c/em\u003e \u0026lt; 0.001). Favorable outcomes (mRS 0\u0026ndash;2) increased from 46.2% (poor) to 67.5% (intermediate) and 96.2% (good) (\u003cem\u003eP\u003c/em\u003e \u0026lt; 0.001), demonstrating a collateral-dependent gradient (Fig. 1).\u003c/p\u003e\n\u003cp\u003eIn multivariable ordinal logistic regression analyses adjusting for age, sex, baseline NIHSS, ASPECTS, onset-to-CT time, IVT, and EVT (Table 2B), robust collateral status was independently associated with a favorable shift toward lower mRS scores at 90 days. Compared with the poor collateral group (0\u0026ndash;1), patients with good collaterals (3\u0026ndash;4) exhibited significantly better functional outcomes (adjusted cOR, 0.24; 95% CI, 0.09\u0026ndash;0.64; \u003cem\u003eP\u0026nbsp;\u003c/em\u003e= 0.005), whereas the association for intermediate collaterals did not reach statistical significance. Notably, no significant interaction was observed between collateral status and EVT regarding functional outcomes (\u003cem\u003eP\u0026nbsp;\u003c/em\u003efor interaction\u003cem\u003e\u003csub\u003e\u0026nbsp;\u003c/sub\u003e\u003c/em\u003e= 0.523) (Supplementary Table S9).\u003c/p\u003e\n\u003cp\u003eIn the EVT subgroup, after additional adjustment for successful reperfusion (eTICI \u0026ge; 2b67), collateral status was no longer independently associated with mRS shift (\u003cem\u003eP\u0026nbsp;\u003c/em\u003efor trend\u003cem\u003e\u003csub\u003e\u0026nbsp;\u003c/sub\u003e\u003c/em\u003e= 0.321), although the direction of effect remained consistent (Supplementary Table S3).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eParenchymal Hematoma\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003ePH occurred in 15 patients (7.7%). The PH rate decreased across collateral grades (0\u0026ndash;1: 23.1%, 2: 7.8%, 3\u0026ndash;4: 0%) (Fig. 2 and Supplementary Table S4). For the primary safety analysis, collateral status was dichotomized into poor (0\u0026ndash;1) and non-poor (2\u0026ndash;4) to ensure model stability, given the absence of PH events in the highest collateral category (3\u0026ndash;4) (Table 3).\u003c/p\u003e\n\u003cp\u003ePH occurred significantly higher in patients with poor collaterals than in those with non-poor collaterals (23.1% vs. 3.8%). After multivariable adjustment, non-poor collateral status was independently associated with a markedly reduced risk of PH (adjusted OR, 0.18; 95% CI, 0.04\u0026ndash;0.80; \u003cem\u003eP\u0026nbsp;\u003c/em\u003e= 0.024).\u003c/p\u003e\n\u003cp\u003eAmong patients undergoing EVT, PH was observed in 27.3% of those with poor collaterals compared with 6.0% of those with non-poor collaterals. This protective association remained robust after adjustment including successful reperfusion (eTICI \u0026ge; 2b67) (adjusted OR, 0.13; 95% CI, 0.03\u0026ndash;0.70; \u003cem\u003eP\u0026nbsp;\u003c/em\u003e= 0.018).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSensitivity analyses\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eSensitivity analyses confirmed the robustness of the primary findings. When the collateral grade was modeled as a continuous variable (per 1-point increase), higher collateral score was independently associated with better functional outcome in the overall cohort (adjusted cOR, 0.50; 95% CI, 0.34\u0026ndash;0.75; \u003cem\u003eP\u003c/em\u003e = 0.001) (Supplementary Table S6).\u003c/p\u003e\n\u003cp\u003eSimilarly, higher collateral score was associated with a lower risk of PH in both the overall cohort (adjusted OR, 0.36; 95% CI, 0.14\u0026ndash;0.89; \u003cem\u003eP\u003c/em\u003e = 0.027) and the EVT subgroup (adjusted OR, 0.31; 95% CI, 0.10\u0026ndash;0.95; \u003cem\u003eP\u003c/em\u003e = 0.041).\u0026nbsp;Additional sensitivity analyses using three-category collateral classification with Firth bias-reduced regression yielded consistent effect directions and significant ordinal trends (Supplementary Tables S4 and S5).\u003c/p\u003e\n\u003cp\u003eAfter inverse probability of treatment weighting (IPTW) and doubly robust adjustment\u003csup\u003e19,20\u003c/sup\u003e, the associations between EVT and both 90-day functional outcome and PH were substantially attenuated and no longer statistically significant (Supplementary Table S7 and S8). In receiver operating characteristic (ROC) analyses, the model incorporating collateral status showed a modest improvement in discrimination compared with the clinical model alone (AUC = 0.86 vs. AUC = 0.848) (Supplementary Fig. S1).\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eIn this single-center cohort of acute anterior-circulation LVO stroke, 4D-CTA collateral status was associated with 90-day functional outcome and PH risk, supporting time-resolved collateral assessment for early risk stratification.\u003c/p\u003e \u003cp\u003eBecause this retrospective cohort included patients treated with EVT and those managed without EVT, confounding by indication is likely. Propensity score\u0026ndash;based sensitivity analyses (including IPTW and doubly robust adjustment) suggested that unadjusted differences in functional outcome and PH were largely attributable to baseline severity and treatment selection, rather than EVT itself. We therefore adjusted for treatment status and performed stratified analyses when evaluating the prognostic value of collateral status.\u003c/p\u003e \u003cp\u003eFunctional outcomes improved stepwise across collateral tiers (median mRS 3, 2, and 1 for grades 0\u0026ndash;1, 2, and 3\u0026ndash;4). After adjustment, better collateral status remained associated with a favorable mRS shift in the overall cohort (\u003cem\u003eP\u003c/em\u003e for trend\u0026thinsp;\u0026lt;\u0026thinsp;0.001). No significant interaction was observed between collateral status and EVT regarding functional outcomes.\u003c/p\u003e \u003cp\u003eThe high rate of mRS 0\u0026ndash;2 in the good-collateral group likely reflects slower infarct progression and milder early symptoms, which can delay care-seeking and prolong onset-to-CT time. Good collaterals are also linked to lower baseline stroke severity and better penumbral preservation. Time-resolved 4D-CTA may further enrich the highest collateral tier by more stringently capturing sustained and delayed filling.\u003c/p\u003e \u003cp\u003ePoor collaterals were associated with higher PH risk, whereas non-poor collaterals (2\u0026ndash;4) were protective in both the overall cohort and the EVT subgroup after adjustment for reperfusion status. Sensitivity analyses modeling the collateral score as a continuous variable yielded consistent associations for both functional independence and PH risk, further underscoring the reliability of these findings.\u003c/p\u003e \u003cp\u003eOur results are consistent with prior work showing that better collaterals are associated with smaller infarct burden and improved outcomes\u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e,\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e,\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e,\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u003c/sup\u003e. Time-resolved imaging may offer additional prognostic value over sCTA by reducing underestimation of delayed collateral recruitment\u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e,\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eSecondary analyses of EVT trials also support this interpretation. In the TENSION trial, collateral status and EVT were independently associated with mRS shift, and the EVT effect was not significantly modified by collateral grade\u003csup\u003e\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e\u003c/sup\u003e. This is consistent with our non-significant collateral-by-EVT interaction and suggests that collateral status is a strong prognostic marker rather than an exclusion criterion for EVT. In routine practice, EVT-treated patients often present with greater stroke severity, lower ASPECTS, and poorer collaterals; such baseline imbalances may further limit power to detect interaction effects.\u003c/p\u003e \u003cp\u003eRegarding hemorrhagic outcomes, impaired collaterals have been linked to higher hemorrhagic transformation risk after reperfusion. In a 4D-CTA\u0026ndash;based study, Cao \u003cem\u003eet al.\u003c/em\u003e reported higher hemorrhagic transformation rates in patients with poor collaterals after EVT\u003csup\u003e\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u003c/sup\u003e. Registry studies using the modified ASITN/SIR scale have similarly associated collateral robustness with hemorrhagic risk and functional outcome, although effect sizes vary by population\u003csup\u003e\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e,\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e\u003c/sup\u003e. By focusing on PH as a clinically meaningful and homogeneous safety endpoint, our study extends these observations and demonstrates that 4D-CTA assessment is highly informative for identifying patients at elevated risk for severe hemorrhagic complications.\u003c/p\u003e \u003cp\u003eMechanistically, the contrasting cases in Figs.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e\u0026ndash;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e illustrate that robust collaterals may sustain penumbral perfusion, slow core expansion, and preserve microvascular integrity\u003csup\u003e\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e\u003c/sup\u003e, which could reduce reperfusion injury and PH\u003csup\u003e26\u003c/sup\u003e. Prior time-resolved imaging studies have linked dynamic collateral measures to infarct growth and hypoperfusion burden, supporting this biological rationale\u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e,\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e,\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e,\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e\u003c/sup\u003e. Conversely, poor collaterals may reflect more severe ischemia and blood\u0026ndash;brain barrier disruption, increasing susceptibility to reperfusion injury and PH.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003eLimitations\u003c/h2\u003e \u003cp\u003eThe retrospective single-center design limits generalizability and may introduce selection bias; residual confounding from treatment selection or unmeasured variables cannot be excluded. The small number of PH events may limit precision, particularly in subgroup analyses; we used Firth\u0026rsquo;s penalized logistic regression to mitigate small-sample bias. Collateral grading is semi-quantitative and subject to inter-rater variability, and performance may vary with acquisition and reconstruction protocols\u003csup\u003e\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e,\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e\u003c/sup\u003e. Standardized imaging and scoring procedures are therefore needed. Prospective multicenter studies are needed to validate these findings and to define the incremental clinical value of 4D-CTA\u0026ndash;based collateral assessment for treatment decision-making.\u003c/p\u003e \u003c/div\u003e"},{"header":"Conclusion","content":"\u003cp\u003e4D-CTA collateral status was independently associated with 90-day functional outcome and PH risk in anterior-circulation LVO stroke. The graded association supports time-resolved collateral assessment for early risk stratification. Although poor collaterals were linked to higher PH risk, collateral status alone should not exclude otherwise eligible patients from EVT.\u003c/p\u003e "},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eData availability\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe data in this study were obtained from the corresponding author upon a reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors acknowledge institutional support from a research project of the Sichuan Medical Association (Project No. S21023).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study received no external funding.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor Contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eJ.Z. and L.L. developed the study methodology, conducted the data analysis, interpreted the results, and drafted the initial manuscript. L.L. and L.Y. assisted with data acquisition. X.Z. and X.G. assisted with data curation. Z.L. and Y.Y. verified and summarized the analysis results. J.Z. and Y.T. planned the study and provided critical revisions of the manuscript. All authors read and approved the final manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics declarations\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was conducted in accordance with the Declaration of Helsinki (as revised in 2013) and was approved by the Biomedical Ethics Committee of Mianyang Central Hospital (institutional review board approval number: S20240222-01). The requirement for informed consent was waived due to the retrospective nature of the study and the use of de-identified data.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare no competing interests.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eGoyal M, Menon BK, van Zwam WH, et al. Endovascular thrombectomy after large-vessel ischaemic stroke: A meta-analysis of individual patient data from five randomised trials. 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Eur Radiol. 2022;32(9):6097\u0026ndash;107. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1007/s00330-022-08706-6\u003c/span\u003e\u003cspan address=\"10.1007/s00330-022-08706-6\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"},{"header":"Tables","content":"\u003cp\u003e\u003cstrong\u003eTable 1. Baseline characteristics by collateral group (0-1, 2, 3-4)\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"3\" cellpadding=\"0\"\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 129px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eVariable\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 111px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCollateral 0\u0026ndash;1 (n=39)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 111px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCollateral 2 (n=77)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 111px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCollateral 3\u0026ndash;4 (n=80)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 73px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eP value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 129px;\"\u003e\n \u003cp\u003eAge, years\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 111px;\"\u003e\n \u003cp\u003e74.0 [61.5, 81.0]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 111px;\"\u003e\n \u003cp\u003e72.0 [64.0, 78.0]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 111px;\"\u003e\n \u003cp\u003e68.0 [58.0, 76.2]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 73px;\"\u003e\n \u003cp\u003e0.063\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 129px;\"\u003e\n \u003cp\u003eOnset-to-CT time, h\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 111px;\"\u003e\n \u003cp\u003e4.0 [2.0, 7.0]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 111px;\"\u003e\n \u003cp\u003e5.0 [2.0, 8.0]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 111px;\"\u003e\n \u003cp\u003e6.0 [3.0, 10.0]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 73px;\"\u003e\n \u003cp\u003e0.046\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 129px;\"\u003e\n \u003cp\u003eNIHSS on admission\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 111px;\"\u003e\n \u003cp\u003e15.0 [12.0, 18.5]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 111px;\"\u003e\n \u003cp\u003e12.0 [8.0, 16.0]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 111px;\"\u003e\n \u003cp\u003e4.0 [2.0, 8.0]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 73px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 129px;\"\u003e\n \u003cp\u003eASPECTS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 111px;\"\u003e\n \u003cp\u003e6.0 [5.5, 7.0]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 111px;\"\u003e\n \u003cp\u003e7.0 [6.0, 8.0]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 111px;\"\u003e\n \u003cp\u003e9.0 [8.0, 9.0]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 73px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 129px;\"\u003e\n \u003cp\u003eMale sex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 111px;\"\u003e\n \u003cp\u003e26 (66.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 111px;\"\u003e\n \u003cp\u003e45 (58.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 111px;\"\u003e\n \u003cp\u003e59 (73.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 73px;\"\u003e\n \u003cp\u003e0.090\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 129px;\"\u003e\n \u003cp\u003eLeft MCA occlusion\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 111px;\"\u003e\n \u003cp\u003e19 (48.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 111px;\"\u003e\n \u003cp\u003e37 (48.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 111px;\"\u003e\n \u003cp\u003e39 (48.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 73px;\"\u003e\n \u003cp\u003e0.997\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 129px;\"\u003e\n \u003cp\u003eHypertension\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 111px;\"\u003e\n \u003cp\u003e28 (71.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 111px;\"\u003e\n \u003cp\u003e58 (75.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 111px;\"\u003e\n \u003cp\u003e54 (67.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 73px;\"\u003e\n \u003cp\u003e0.594\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 129px;\"\u003e\n \u003cp\u003eDiabetes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 111px;\"\u003e\n \u003cp\u003e7 (17.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 111px;\"\u003e\n \u003cp\u003e17 (22.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 111px;\"\u003e\n \u003cp\u003e10 (12.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 73px;\"\u003e\n \u003cp\u003e0.280\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 129px;\"\u003e\n \u003cp\u003eAtrial fibrillation\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 111px;\"\u003e\n \u003cp\u003e18 (46.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 111px;\"\u003e\n \u003cp\u003e34 (44.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 111px;\"\u003e\n \u003cp\u003e27 (33.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 73px;\"\u003e\n \u003cp\u003e0.293\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 129px;\"\u003e\n \u003cp\u003eIVT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 111px;\"\u003e\n \u003cp\u003e7 (17.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 111px;\"\u003e\n \u003cp\u003e13 (16.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 111px;\"\u003e\n \u003cp\u003e14 (17.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 73px;\"\u003e\n \u003cp\u003e0.989\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 129px;\"\u003e\n \u003cp\u003eEVT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 111px;\"\u003e\n \u003cp\u003e33 (84.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 111px;\"\u003e\n \u003cp\u003e57 (74.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 111px;\"\u003e\n \u003cp\u003e26 (32.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 73px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cem\u003eCT,\u003c/em\u003e \u003cem\u003ecomputed tomography; NIHSS, National Institutes of Health Stroke Scale; ASPECTS, Alberta Stroke Program Early CT Score; MCA, middle cerebral artery; IVT, intravenous thrombolysis;\u003c/em\u003e \u003cem\u003eEVT, Endovascular therapy.\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eBetween-group comparisons used Kruskal\u0026ndash;Wallis tests for continuous variables and \u0026chi;\u0026sup2; tests (or Fisher\u0026rsquo;s exact tests when appropriate) for categorical variables.\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 2. Collateral status and 90-day functional outcome\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 2A. Descriptive 90-day outcomes by collateral group\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"3\" cellpadding=\"0\"\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eOutcome\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eCollateral 0\u0026ndash;1 (n=39)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eCollateral 2 (n=77)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eCollateral 3\u0026ndash;4 (n=80)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eP\u003c/em\u003e\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003emRS score at 90 days, median (IQR)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e3 (1\u0026ndash;4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e2 (1\u0026ndash;3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1 (0\u0026ndash;1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003emRS 0\u0026ndash;2, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e18 (46.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e52 (67.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e77 (96.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003emRS 3\u0026ndash;6, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e21 (53.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e25 (32.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e3 (3.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 2B. Association of collateral status with 90-day modified Rankin Scale shift\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"3\" cellpadding=\"0\" width=\"558\"\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 148px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCohort\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 130px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eComparison\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 149px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAdjusted cOR (95% CI)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eP\u003c/em\u003e\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eP\u003c/em\u003e\u003c/strong\u003e\u003cstrong\u003e\u003cem\u003e\u0026nbsp;\u003c/em\u003e\u003c/strong\u003e\u003cstrong\u003efor trend\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 148px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eOverall cohort (N=196)\u003c/strong\u003e\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 130px;\"\u003e\n \u003cp\u003eCollateral 2 vs 0\u0026ndash;1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 149px;\"\u003e\n \u003cp\u003e0.72 (0.33\u0026ndash;1.53)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e0.395\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 148px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 130px;\"\u003e\n \u003cp\u003eCollateral 3\u0026ndash;4 vs 0\u0026ndash;1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 149px;\"\u003e\n \u003cp\u003e0.24 (0.09\u0026ndash;0.64)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e0.005\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e0.004\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 148px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eEVT subgroup (N=116)\u003c/strong\u003e\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 130px;\"\u003e\n \u003cp\u003eCollateral 2 vs 0\u0026ndash;1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 149px;\"\u003e\n \u003cp\u003e0.82 (0.35\u0026ndash;1.94)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e0.652\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 148px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 130px;\"\u003e\n \u003cp\u003eCollateral 3\u0026ndash;4 vs 0\u0026ndash;1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 149px;\"\u003e\n \u003cp\u003e0.51 (0.14\u0026ndash;1.81)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e0.296\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e0.321\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cem\u003eIQR, interquartile range; mRS, modified Rankin Scale;\u003c/em\u003e \u003cem\u003eEVT, Endovascular therapy;\u003c/em\u003e \u003cem\u003ecOR, common odds ratio;\u003c/em\u003e \u003cem\u003eCI, confidence interval.\u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e\u003csup\u003ea\u003c/sup\u003e\u003c/em\u003e\u003cem\u003e\u0026nbsp;Overall cohort model was adjusted for age, sex, baseline NIHSS, ASPECTS, onset-to-CT time, intravenous thrombolysis, and endovascular therapy.\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e\u003csup\u003eb\u003c/sup\u003e\u003c/em\u003e\u003cem\u003e\u0026nbsp;EVT subgroup model was additionally adjusted for successful reperfusion, defined as expanded Thrombolysis in Cerebral Infarction (eTICI) grade \u0026ge;2b67.\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eIn the ordinal shift analysis, a common odds ratio (cOR) \u0026lt; 1 indicates a shift toward lower mRS scores, corresponding to a more favorable functional outcome.\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eP for trend was obtained by modeling collateral status as an ordinal variable in the adjusted proportional odds model (coded as 0\u0026ndash;1, 2, and 3\u0026ndash;4).\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 3. Association of collateral status (0-1 vs 2-4) with parenchymal hematoma (PH)\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eOverall cohort (N=196)\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"3\" cellpadding=\"0\"\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 158px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCollateral group\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 121px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePH, n/N (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 178px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAdjusted OR (95% CI)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 82px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eP value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 158px;\"\u003e\n \u003cp\u003e0\u0026ndash;1 (reference)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 121px;\"\u003e\n \u003cp\u003e9/39 (23.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 178px;\"\u003e\n \u003cp\u003e1.00 (reference)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 82px;\"\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 158px;\"\u003e\n \u003cp\u003e2\u0026ndash;4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 121px;\"\u003e\n \u003cp\u003e6/157 (3.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 178px;\"\u003e\n \u003cp\u003e0.18 (0.04\u0026ndash;0.80)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 82px;\"\u003e\n \u003cp\u003e0.024\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003eEVT subgroup (N=116)\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"3\" cellpadding=\"0\"\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 158px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCollateral group\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 121px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePH, n/N (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 178px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAdjusted OR (95% CI)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 82px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eP value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 158px;\"\u003e\n \u003cp\u003e0\u0026ndash;1 (reference)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 121px;\"\u003e\n \u003cp\u003e9/33 (27.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 178px;\"\u003e\n \u003cp\u003e1.00 (reference)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 82px;\"\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 158px;\"\u003e\n \u003cp\u003e2\u0026ndash;4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 121px;\"\u003e\n \u003cp\u003e5/83 (6.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 178px;\"\u003e\n \u003cp\u003e0.13 (0.03\u0026ndash;0.70)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 82px;\"\u003e\n \u003cp\u003e0.018\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cem\u003ePH, parenchymal hematoma; OR, odds ratio; CI, confidence interval; EVT, Endovascular therapy.\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eOverall cohort model adjusted for age, sex, NIHSS, ASPECTS, onset-to-CT time, IVT, and EVT.\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eEVT subgroup model adjusted for age, sex, NIHSS, ASPECTS, onset-to-CT time, IVT, and eTICI_success (eTICI \u0026ge;2b67).\u003c/em\u003e\u003c/p\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":"acute ischemic stroke, collateral circulation, four-dimensional CTA, functional outcome, parenchymal hematoma","lastPublishedDoi":"10.21203/rs.3.rs-8778505/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8778505/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eFunctional recovery after endovascular thrombectomy (EVT) for anterior-circulation large-vessel occlusion (LVO) stroke remains heterogeneous. Four-dimensional computed tomography angiography (4D-CTA) enables dynamic collateral assessment, but its utility for EVT triage remains uncertain.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eWe retrospectively analyzed 196 anterior-circulation LVO patients who underwent 4D-CTA. Collaterals were graded on a 0\u0026ndash;4 scale and categorized as poor (0\u0026ndash;1), intermediate (2), or good (3\u0026ndash;4); for parenchymal hematoma (PH), collaterals were dichotomized as poor (0\u0026ndash;1) versus non-poor (2\u0026ndash;4). Primary outcomes were 90-day modified Rankin Scale (mRS) shift and PH occurrence. Multivariable ordinal logistic regression assessed mRS shift, and Firth logistic regression assessed PH. EVT subgroup models additionally adjusted for reperfusion status.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eAmong 196 patients (59.2% EVT), median mRS (interquartile range [IQR]) improved across collateral tiers: 3 (1\u0026ndash;4), 2 (1\u0026ndash;3), and 1 (0\u0026ndash;1) for poor, intermediate, and good collaterals, respectively (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Favorable outcome (mRS 0\u0026ndash;2) increased from 46.2% to 96.2%. After adjustment, good collaterals predicted a favorable mRS shift (cOR 0.24, 95% confidence interval [CI] 0.08\u0026ndash;0.66; \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.005). PH occurred in 7.7%, with rates of 23.1%, 7.8%, and 0% across collateral tiers. Non-poor collaterals were protective against PH (odds ratio [OR] 0.18, 95% CI 0.04\u0026ndash;0.80; \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.024), including in the EVT subgroup (OR 0.13, 95% CI 0.03\u0026ndash;0.70; \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.018). No collateral-by-EVT interaction was observed (\u003cem\u003eP\u003c/em\u003e for interaction\u0026thinsp;=\u0026thinsp;0.523).\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e \u003cp\u003e4D-CTA collateral status independently predicts 90-day functional outcomes and PH risk. Poor collaterals alone should not preclude EVT in otherwise eligible patients.\u003c/p\u003e","manuscriptTitle":"4D-CTA Collateral Status Predicts Functional Outcome and Parenchymal Hematoma in Anterior Circulation Large Vessel Occlusion Stroke","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-02-19 11:31:46","doi":"10.21203/rs.3.rs-8778505/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":"5fa00ed6-1a4f-4423-99b3-f5a094228ec7","owner":[],"postedDate":"February 19th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2026-03-18T11:40:54+00:00","versionOfRecord":[],"versionCreatedAt":"2026-02-19 11:31:46","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8778505","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8778505","identity":"rs-8778505","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}