Collateral status correlates with stroke outcomes mediated by early infarct growth rate in patients with acute large vessel occlusion

Introduction

Acute large vessel occlusion is a major subtype of acute ischemic stroke (AIS), accounting for approximately 60% of post-stroke disability and 95% of post-stroke mortality (1). However, nearly 50% of AIS patients undergoing endovascular thrombectomy (EVT) still fail to achieve functional independence, primarily due to the rapid progression of infarct core (2). The early infarct growth rate (EIGR), defined as the rate of infarct growth prior to imaging or treatment, has been strongly correlated with 90-day clinical outcomes in patients receiving EVT (3). Moreover, some studies have reported that patients with a rapid EIGR may derive greater benefit from reperfusion therapy than slow progressors within an early time window (4,5). Therefore, identifying EIGR status is crucial for clinical decision-making.

Cerebral collaterals, composed of a complex network of arteries, capillaries, and veins, are robust predictors of prognosis in AIS. They determine the initial ischemic core volume (ICV) and its subsequent expansion. Patients with abundant pial arterial collaterals (PACs) or lower hypoperfusion intensity ratio (HIR) tended to exhibit slower EIGR and more favorable long-term functional outcomes (6-13). Moderate-to-good PACs were also considered a favorable indicator for EVT eligibility (14). A favorable venous outflow (VO) profile, which represents efficient tissue perfusion, has been linked to a slower rate of early edema progression, a higher rate of vessel successful reperfusion and more favorable long-term functional outcomes (15-17). However, the intricate relationship among collaterals, EIGR and stroke outcomes remains insufficiently understood, and a comprehensive understanding of these correlations may improve prognostic predictions in AIS. Therefore, we aimed to evaluate the collateral status at the arterial, tissue and VO levels, and assess EIGR distribution in patients with different clinical and imaging outcomes. We present this article in accordance with the STROBE reporting checklist (available at https://qims.amegroups.com/article/view/10.21037/qims-2024-2709/rc).

Methods

Study population

We retrospectively recruited patients with AIS presenting to our stroke center between May 2018 to March 2022 within 24 hours of symptom onset.

Inclusion criteria included: (I) age ≥18 years; (II) availability of admission computed tomography perfusion (CTP) and computed tomography angiography (CTA) images; (III) acute large vessel occlusions of intracranial internal carotid artery (ICA), M1 or proximal M2 segment of the middle cerebral artery or tandem occlusions; (IV) follow-up non-contrast CT (NCCT) or diffusion weighted imaging (DWI) at 2–7 days post-presentation; (V) assessment of the functional outcome measurement using the modified Rankin Scales (mRS) at 90 days.

Exclusion criteria included: (I) symptom onset beyond 24 hours; (II) baseline intracranial hemorrhage; (III) occlusion or stenosis of other intracranial arteries; (IV) severe motion artifacts or poor scan quality; (V) absence of follow-up NCCT, DWI or mRS at 90 days.

Patient demographic and clinical data were collected, including age, sex, medical history, relevant laboratory tests, admission National Institutes of Health Stroke Scale (NIHSS) score, occlusion site, etiological subtype [Trial of Org10172 in Acute Stroke Treatment classification (TOAST)], treatment methods and the time interval from last known well (LKW) to imaging. The study was conducted in accordance with the Declaration of Helsinki and its subsequent amendments. This study was approved by the Ethics Committee of Huashan Hospital, Fudan University (No. KY2021-965). Informed consent was waived due to the retrospective nature of this study.

Image acquisition

Patients with suspected AIS symptoms underwent NCCT of the head followed by CTP and CTA imaging in accordance with early patient management guidelines (18). Imaging was performed using a 64-detector CT scanner (Discovery CT750 HD, GE Healthcare, Indiana, USA). CTP was acquired using volume shuttle mode with a perfusion coverage of 80 mm, initiating scans 5–10 seconds after administering 50 mL ioversol at 5 mL/s. Twenty-six scans were obtained at 5-second intervals over a total duration of 41.39 seconds, covering the skull base to vertex. CTP parameters were: tube voltage 80 kVp, tube current 300 mA, rotation time 0.4 s, and slice thickness 5 mm. CTA was performed during injection of 80 mL ioversol at 4 mL/s followed by 40 mL saline at the same rate. CTA parameters were: tube voltage 140 kVp, tube current 630 mA, rotation time 0.5 seconds, and slice thickness 0.625 mm, with coverage extending from the aortic arch to the cranial vertex.

Imaging analysis

ICV and HIR were derived from CTP datasets using the automatic post-processing software, RAPID (Version 5.0.4, iSchema View, Menlo Park, CA, USA). ICV was defined as the volume of tissue with relative cerebral brain flow (rCBF) <30%. The HIR, representing tissue-level collaterals (TLCs) status, was calculated as the ratio of the volume of ischemic brain tissue with a time-to-maximum of the tissue residue function (Tmax) delay of >10 seconds to the volume of brain tissue with a Tmax delay of >6 seconds. Based on a prior study (11), HIR ≤0.4 indicated favorable TLCs, while HIR >0.4 indicated poor TLCs.

PACs and VO were evaluated on CTA images. Modified Tan (mTan) score was used to determine PACs, with >50% middle cerebral artery territory filling by leptomeningeal anastomoses defined as favorable. Cortical vein opacification score (COVES) graded venous circulation based on 0 = no opacification, 1 = partial, 2 = full opacification of the Labbe vein, sphenoparietal sinus, and middle superficial cerebral vein. Scores of 3–6 indicated favorable and 0–2 unfavorable VO. Successful reperfusion was identified as Modified Treatment in Cerebral Ischemia Scale (mTICI) score ≥2b on DSA or the modified Arterial Occlusive Lesion score =3 on CTA at 24 hours.

All imaging analyses were independently performed by two radiologists with 5 and 8 years of clinical experience, respectively. Both were blinded to all clinical information except the occlusion site. Consensus was reached in cases of disagreement. Schematic diagram of collaterals evaluation is shown in Figure S1.

EIGR definition

EIGR was defined as the ICV (rCBF <30%) on the baseline CTP divided by the time elapsed from LKW to CTP imaging. Given the current lack of a standardized EIGR cut-off, patients were stratified into two groups based on previous literature (3): an EIGR of ≥10 mL/h was defined as rapid progressors, while <10 mL/h indicated slow progressors.

Study outcomes

Study outcomes encompassed both imaging and clinical parameters. The imaging outcome was measured by final infarct volume (FIV), determined from follow-up NCCT or DWI, with preference given to DWI when available. Lesion segmentation was manually performed using a semi-automated ITK-SNAP software (Version 4.0, https://sourceforge.net/projects/itk-snap/) by two radiologists with 5 and 8 years of clinical experience. Both were blinded to all imaging and clinical information, and the average of their measurements was used as the final FIV. FIV was identified as a hyperintense region on DWI or a low-density area on NCCT. Clinical outcome was measured by mRS at 90 days. A good clinical outcome was defined as functional independence (mRS 0–2), while a poor clinical outcome was defined as mRS ˃2.

Statistical analysis

Continuous variables were assessed for normality using Kolmogorov-Smirnov or Shapiro-Wilk tests and presented as mean ± standard deviation or median (interquartile range), as appropriate. Categorical variables were reported as counts/frequencies. Patient demographics, clinical variables and imaging data were compared between subgroups by Student’s t-test or Mann-Whitney U tests, Chi-square test or Fisher’s exact test. Partial correlation analyses were performed to evaluate the associations between the collaterals and EIGR, as well as between EIGR and stroke outcomes. Risk factors associated with the outcomes were identified using linear and logistic regression analyses, and prediction models were developed based on the significant results. Mediation analyses were performed using PROCESS macro (Version 4.1, Hayes, 2009) to further explore the relationships among collaterals, EIGR, and outcomes after adjusting for age, sex, prestroke mRS and reperfusion status. Data processing and analyses were performed using SPSS (Version 26.0) and R software (Version 4.4). P<0.05 was considered to be statistically significant.

Results

Clinical characteristics of patients

Figure 1 depicts the flowchart of patient inclusion. A total of 166 patients met the inclusion criteria, among whom 61 achieved a good clinical outcome, and 105 had a poor clinical outcome.

Figure 1 Flowchart of patient inclusion. AIS, acute ischemic stroke; LVO, large vessel occlusion.

Patients with poor clinical outcomes were older and had higher presentation NIHSS scores, elevated fasting blood glucose, and a greater prevalence of atrial fibrillation (all P<0.05). They also exhibited a higher incidence of ICA + M1 tandem occlusion (P=0.020). No significant differences were observed between subgroups in terms of sex ratio, time from LKW to exam, TOAST classification, treatment methods selection, or successful recanalization rate (Table 1).

In terms of imaging findings, patients with good clinical outcomes exhibited lower values of ICV, EIGR, and FIV compared to those with poor clinical outcomes. Specifically, the median EIGR and FIV were 2.0 mL/h and 14.4 mL in the good clinical outcome group, compared to 11.3 mL/h and 126.5 mL in the poor outcome group (both P<0.001). Patients with different clinical outcomes exhibited distinct, significantly collateral profiles. Those with good clinical outcome had higher rates of favorable PACs, TLCs, and VO (all P<0.001, Table 1).

The correlation between collaterals and EIGR

Patients with unfavorable collaterals had higher EIGR values (Table S1), suggesting a greater propensity for rapid infarct progression. After adjusting for potential confounders, including age and sex, correlation analyses revealed that the mTan score (r=−0.456, P<0.001) was more closely associated with EIGR than the HIR (r=0.314, P<0.001) and the COVES score (r=−0.300, P<0.001).

The correlation between EIGR and stroke outcomes

In this study, imaging and clinical outcomes were defined as FIV and mRS at 90 days, respectively. After adjusting for age, sex, prestroke mRS, and reperfusion status, correlation analyses revealed a significant positive association between EIGR and FIV (r=0.537, P<0.001), as well as a moderate association between EIGR and mRS (r=0.453, P<0.001). To further characterize this relationship, patients were stratified into rapid and slow progressors based on an EIGR cut-off of 10 mL/h. The good clinical outcome group had a significantly greater proportion of slow progressors than the poor clinical outcome group (P<0.001, Table 1). Additionally, slow progressors had significantly smaller FIV compared to rapid progressors [19.2 (IQR, 7.1–49.7) vs. 171.9 (IQR, 93.3–252.5) mL, P<0.001; Figure 2]. Figure 2 depicts the distribution of FIV and mRS at 90 days by EIGR category.

Figure 2 The distribution of FIV and mRS based on EIGR in patients with AIS. AIS, acute ischemic stroke; EIGR, early infarct growth rate; FIV, final infarct volume; mRS, modified Rankin Scale.

Exploratory analysis of slow progressors with various clinical outcomes

We observed that a subset of patients, despite exhibiting slow infarct progression, had large FIV and poor clinical outcomes. To investigate this discrepancy, we conducted a comparative analysis comparing the clinical and imaging characteristics of slow progressors stratified by clinical outcomes. We found that slow progressors with good clinical outcomes were younger, had lower presentation NIHSS scores and fasting blood glucose levels, a lower prevalence of atrial fibrillation, smaller ICV, and more favorable collateral profiles across arterial, tissue, and VO levels (all P<0.05, Table S2).

Determinants of stroke outcomes

Regression analyses were performed to determine the risk factors associated with FIV and mRS in AIS patients (Table 2). After adjusting for prestroke mRS and reperfusion status, multivariate analysis revealed that higher presentation NIHSS score, greater EIGR and HIR values, and poorer PACs were independently associated with larger FIV. Predictors of good clinical outcome included younger age, lower presentation NIHSS score, and lower EIGR. Notably, presentation NIHSS score and EIGR emerged as co-factors independently associated with both FIV and mRS at 90 days.

The associations between collaterals, EIGR and stroke outcomes

Mediation analyses were conducted to further elucidate the intricate interplay among collateral status, EIGR and stroke outcomes. We defined collaterals at the arterial, tissue and VO levels as the predictors (X), EIGR as the mediator (M), and FIV or mRS as the outcomes (Y). The results showed that all collaterals and EIGR directly correlated with the imaging and clinical outcomes significantly. In addition, the collaterals had a direct and significant effect on EIGR. After adjusting for age, sex, prestroke mRS and reperfusion status, EIGR emerged as a key mediator in the relationships between PACs, TLCs, VO and FIV, with mediation effect ratios of 28.2%, 27.9% and 32.2%, respectively (Figure 3). Similarly, EIGR partially mediated the effects of PACs, TLCs, and VO on mRS at 90 days, with mediation ratios of 33.7%, 25.9%, and 35.9%, respectively (Figure 3).

Figure 3 Mediation analyses between mTan, HIR, COVES (X) and FIV/mRS (Y), with EIGR as mediator (M). c and c’ represent total effect coefficient and direct effect coefficient, respectively, with standard errors in parentheses. **, P<0.01; ***, P<0.001. COVES, cortical vein opacification score; EIGR, early infarct growth rate; FIV, final infarct volume; HIR, hypoperfusion intensity ratio; mRS, modified Rankin Scale; mTan, modified Tan.

Discussion

In this study, we investigated the relationships among collateral status at the arterial, tissue and VO levels, EIGR and the clinical and imaging outcomes in patients with AIS. We found the collateral profiles at each level were significantly associated with EIGR and EIGR was found to be a co-factor in predicting both FIV and 90-day mRS. Furthermore, EIGR acted as a partial mediator in the relationship between collaterals and imaging or clinical outcomes.

EIGR has received considerable attention in recent years due to its pivotal role in determining infarct progression patterns, treatment response, and prognosis in AIS. Patients with initially small infarct core may experience fast progression, leading to large FIV and poor clinical outcome, whereas those with slow progression may benefit from the late thrombectomy (19). EIGR has been recognized as an independent predictor for both early and long-term neurological improvement in AIS patients (6,7,20). In our study, EIGR emerged as a co-factor closely related to FIV and mRS at 90 days. More importantly, EIGR may contribute to individualized clinical decision-making. The DAWN and DEFUSE 3 trials have extended the treatment window of EVT to 24 hours post-onset. Patients with slower EIGR may have a longer therapeutic window than those with rapid EIGR (4). Conversely, growing evidence suggests that the rapid progressors may derive greater benefit from earlier revascularization and a more substantial tissue-saving effect of EVT than the slow progressors within <4.5-hour time window (4,5,21). Identifying EIGR subtypes may thus optimize patient triage, interhospital transfer and clinical neuroprotection strategy in stroke centers.

In our cohort, close correlations were recognized between EIGR and collaterals at all three levels. Mediation analyses revealed that each collateral type exerted a significant direct effect on EIGR. Patients with unfavorable collaterals were more likely to experience rapid progress prior to treatment. Considerable variations in EIGR exist among individuals, and collateral profiles, which mainly refer to PACs and TLCs, were consistently found to be primary contributors to infarction growth rate in prior studies (6,8,9). PACs are widely recognized as key determinants in the occurrence, progress, and prognosis of AIS. Regenhardt et al. identified PACs as the only determinant of 24-hour infarction growth rate (19). Regarding TLCs, researchers found that lower HIR was associated with slower EIGR, and HIR ≥0.5 predicted an 83% probability of significant core growth during transfer for thrombectomy (6,22). Favorable VO profiles have been linked to reduced cerebral edema and served as strong predictors for good clinical outcome (20,23,24). To our knowledge, no prior studies have investigated the relationship between VO and EIGR. Our study also revealed a significant association between VO and EIGR. Moreover, the correlation between PACs and EIGR was slightly stronger than that of TLCs or VO, suggesting that PACs may exert a greater influence on early infarction growth. This could be attributed to the direct role of arterial occlusion in AIS pathophysiology, whereas the contributions of TLCs and VO may be modulated by other factors affecting ischemic tissue tolerance.

To date, many studies have investigated the correlations among the three types of collaterals and found that they were strongly interrelated, and jointly contributing to the maintenance of cerebral blood flow and protection of ischemic brain tissue (23-26). In this circulatory context, PACs primarily facilitate blood delivery to the ischemic brain, while TLCs are linked to microvascular perfusion. VO, serving as an indicator of blood drainage and waste elimination, has been strongly associated with functional outcome in cases of distal tissue obstruction (16,23,27). Several researchers have proposed that a more comprehensive vascular imaging assessment is conducive to may improve the understanding and prediction of infarct occurrence, progression and prognosis (27,28). Our findings build upon and extend this body of literature.

Prognostic studies have shown that collaterals, coordinated with clinical and physiological parameters such as age, presentation NIHSS, and genetic variation, are significant influencing factors of infarct growth, ultimately determining the individual clinical outcome (6,7,29). Consequently, robust correlations exist among collateral status, EIGR, and stroke outcomes. We hypothesized that EIGR may serve as a mediating factor linking collaterals to stroke outcomes. Mediation analyses were exploratively applied and the results revealed that both FIV and mRS were influenced by all three types of collaterals, with this effect being partially mediated by EIGR. Furthermore, both EIGR and collaterals had significant and direct effects on outcome measures. These findings highlighted that both collaterals and EIGR were important influencing factors of prognosis, while EIGR accounts for a portion of the collateral influence on stroke outcomes. Notably, regression analyses revealed that EIGR, rather than collaterals, emerged as a stronger predictor of outcomes. We theorize that while collaterals maintain a direct correlation with FIV and mRS, their predictive effect on outcomes may be eclipsed by that of EIGR. Therefore, EIGR may exert a more substantial influence on outcomes than collateral status. But this conjecture warrants validation in larger cohorts.

Limitations

There are several limitations in the present study. First, this work was confined to a single-center design and the infarct progression showed a left-sided skew, with the majority of patients classified as slow progressors. Second, the 64-detector CT used in this study had limited temporal and spatial resolution for perfusion imaging, which may underestimate the ischemic area. Compared to similar research (7,30), patients in our cohort had a longer time from LKW to image. This may potentially result in an underestimation of EIGR and reduced accuracy in HIR. Furthermore, there is currently no consensus regarding the optimal EIGR cut-off value, necessitating additional investigation to determine its applicability across various clinical scenarios. Third, some factors that may affect the outcomes were not included in the evaluation, such as cerebral small vessel disease burden and genetic variability. Prior studies have identified leukoaraiosis as an imaging biomarker for cerebrovascular reserve, and greater leukoaraiosis severity has been associated with faster infarct progression and worse functional outcomes (31-33). However, those factors are difficult to obtain before therapy in the acute stroke setting. Lastly, the treatment effect and prognosis may vary across different EIGR subgroups (4). Further hierarchical studies on EIGR and treatment methods are necessary in large cohorts.

Conclusions

We comprehensively discussed the relationships among collaterals at arterial, tissue, and VO levels, EIGR, and stroke outcomes in patients with AIS. We found that collaterals, particularly PACs, were closely associated with EIGR, which emerged as a robust co-predictor of FIV and 90-day mRS. In addition, EIGR served as a mediating factor in the relationships of collaterals and stroke outcomes. By integrating multi-level collateral evaluation with EIGR analysis, our work offered a more nuanced understanding of how collateral circulation influences infarct progression and stroke outcomes.

Acknowledgments

None.

Footnote

Reporting Checklist: The authors have completed the STROBE reporting checklist. Available at https://qims.amegroups.com/article/view/10.21037/qims-2024-2709/rc

Data Sharing Statement: Available at https://qims.amegroups.com/article/view/10.21037/qims-2024-2709/dss

Funding: This work was supported by National Natural Science Foundation of China (No. 81971598), Shanghai Hospital Development Center (No. SHDC2020CR3020A), Greater Bay Area Institute of Precision Medicine (Guangzhou) (No. KCH2310094), Shanghai Academic Research Leader Program (No. 21XD1420900), Shanghai Municipal Commission of Health Program (No. 20224Z0002), Zhejiang Medical Health Science and Technology Project from Zhejiang Provincial Health Commission (No. 2024KY1492), and Key Research and Development Project of Xuzhou Science and Technology Bureau (No. KC23208).

Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://qims.amegroups.com/article/view/10.21037/qims-2024-2709/coif). The authors have no conflicts of interest to declare.

Ethical Statement: The authors are accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved. The study was conducted in accordance with the Declaration of Helsinki and its subsequent amendments. This study was approved by the Ethics Committee of Huashan Hospital, Fudan University (No. KY2021-965). Informed consent was waived due to the retrospective nature of this study.

Open Access Statement: This is an Open Access article distributed in accordance with the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International License (CC BY-NC-ND 4.0), which permits the non-commercial replication and distribution of the article with the strict proviso that no changes or edits are made and the original work is properly cited (including links to both the formal publication through the relevant DOI and the license). See: https://creativecommons.org/licenses/by-nc-nd/4.0/.

References

1. Saini V, Guada L, Yavagal DR. Global Epidemiology of Stroke and Access to Acute Ischemic Stroke Interventions. Neurology 2021;97:S6-S16. [Crossref] [PubMed]
2. Saber H, Liebeskind DS. Infarct Progression in the Early and Late Phases of Acute Ischemic Stroke. Neurology 2021;97:S60-7. [Crossref] [PubMed]
3. Sarraj A, Hassan AE, Grotta J, Blackburn S, Day A, Abraham M, et al. Early Infarct Growth Rate Correlation With Endovascular Thrombectomy Clinical Outcomes: Analysis From the SELECT Study. Stroke 2021;52:57-69. [Crossref] [PubMed]
4. Lin L, Zhang H, Chen C, Bivard A, Butcher K, Garcia-Esperon C, Spratt NJ, Levi CR, Parsons MW, Li GINSPIRE Study Group. Stroke Patients With Faster Core Growth Have Greater Benefit From Endovascular Therapy. Stroke 2021;52:3998-4006. [Crossref] [PubMed]
5. Lin L, Zhang H, Liu F, Chen C, Chen C, Bivard A, Parsons MW, Li G. for INSPIRE. Bridging Thrombolysis Before Endovascular Therapy in Stroke Patients With Faster Core Growth. Neurology 2023;100:e2083-92. [Crossref] [PubMed]
6. Seners P, Yuen N, Olivot JM, Mlynash M, Heit JJ, Christensen S, et al. Factors Associated With Fast Early Infarct Growth in Patients With Acute Ischemic Stroke With a Large Vessel Occlusion. Neurology 2023;101:e2126-37. [Crossref] [PubMed]
7. Ospel JM, McDonough R, Demchuk AM, Menon BK, Almekhlafi MA, Nogueira RG, McTaggart RA, Poppe AY, Buck BH, Roy D, Haussen DC, Chapot R, Field TS, Jayaraman MV, Tymianski M, Hill MD, Goyal MESCAPE-NA1 investigators. Predictors and clinical impact of infarct progression rate in the ESCAPE-NA1 trial. J Neurointerv Surg 2022;14:886-91. [Crossref] [PubMed]
8. Jiang B, Ball RL, Michel P, Li Y, Zhu G, Ding V, Su B, Naqvi Z, Eskandari A, Desai M, Wintermark M. Factors influencing infarct growth including collateral status assessed using computed tomography in acute stroke patients with large artery occlusion. Int J Stroke 2019;14:603-12. [Crossref] [PubMed]
9. Ospel JM, Hill MD, Kappelhof M, Demchuk AM, Menon BK, Mayank A, Dowlatshahi D, Frei D, Rempel JL, Baxter B, Goyal M. Which Acute Ischemic Stroke Patients Are Fast Progressors?: Results From the ESCAPE Trial Control Arm. Stroke 2021;52:1847-50. [Crossref] [PubMed]
10. Faizy TD, Kabiri R, Christensen S, Mlynash M, Kuraitis G, Broocks G, Hanning U, Nawabi J, Lansberg MG, Marks MP, Albers GW, Fiehler J, Wintermark M, Heit JJ. Perfusion imaging-based tissue-level collaterals predict ischemic lesion net water uptake in patients with acute ischemic stroke and large vessel occlusion. J Cereb Blood Flow Metab 2021;41:2067-75. [Crossref] [PubMed]
11. Olivot JM, Mlynash M, Inoue M, Marks MP, Wheeler HM, Kemp S, Straka M, Zaharchuk G, Bammer R, Lansberg MG, Albers GW. Hypoperfusion intensity ratio predicts infarct progression and functional outcome in the DEFUSE 2 Cohort. Stroke 2014;45:1018-23. [Crossref] [PubMed]
12. de Havenon A, Mlynash M, Kim-Tenser MA, Lansberg MG, Leslie-Mazwi T, Christensen S, McTaggart RA, Alexander M, Albers G, Broderick J, Marks MP, Heit JJ. DEFUSE 3 Investigators. Results From DEFUSE 3: Good Collaterals Are Associated With Reduced Ischemic Core Growth but Not Neurologic Outcome. Stroke 2019;50:632-8. [Crossref] [PubMed]
13. Christoforidis GA, Mohammad Y, Kehagias D, Avutu B, Slivka AP. Angiographic assessment of pial collaterals as a prognostic indicator following intra-arterial thrombolysis for acute ischemic stroke. AJNR Am J Neuroradiol 2005;26:1789-97.
14. Goyal M, Demchuk AM, Menon BK, Eesa M, Rempel JL, Thornton J, et al. Randomized assessment of rapid endovascular treatment of ischemic stroke. N Engl J Med 2015;372:1019-30. [Crossref] [PubMed]
15. Stokum JA, Kurland DB, Gerzanich V, Simard JM. Mechanisms of astrocyte-mediated cerebral edema. Neurochem Res 2015;40:317-28. [Crossref] [PubMed]
16. van Horn N, Heit JJ, Kabiri R, Broocks G, Christensen S, Mlynash M, Meyer L, Schoenfeld MH, Lansberg MG, Albers GW, Fiehler J, Wintermark M, Faizy TD. Venous outflow profiles are associated with early edema progression in ischemic stroke. Int J Stroke 2022;17:1078-84. [Crossref] [PubMed]
17. Faizy TD, Kabiri R, Christensen S, Mlynash M, Kuraitis G, Mader MM, Albers GW, Lansberg MG, Fiehler J, Wintermark M, Marks MP, Heit JJ. Association of Venous Outflow Profiles and Successful Vessel Reperfusion After Thrombectomy. Neurology 2021;96:e2903-11. [Crossref] [PubMed]
18. Powers WJ, Rabinstein AA, Ackerson T, Adeoye OM, Bambakidis NC, Becker K, Biller J, Brown M, Demaerschalk BM, Hoh B, Jauch EC, Kidwell CS, Leslie-Mazwi TM, Ovbiagele B, Scott PA, Sheth KN, Southerland AM, Summers DV, Tirschwell DL. Guidelines for the Early Management of Patients With Acute Ischemic Stroke: 2019 Update to the 2018 Guidelines for the Early Management of Acute Ischemic Stroke: A Guideline for Healthcare Professionals From the American Heart Association/American Stroke Association. Stroke 2019;50:e344-418. [Crossref] [PubMed]
19. Regenhardt RW, González RG, He J, Lev MH, Singhal AB. Symmetric CTA Collaterals Identify Patients with Slow-progressing Stroke Likely to Benefit from Late Thrombectomy. Radiology 2022;302:400-7. [Crossref] [PubMed]
20. Faizy TD, Mlynash M, Kabiri R, Christensen S, Kuraitis G, Meyer L, Bechstein M, Van Horn N, Lansberg MG, Albers G, Fiehler J, Wintermark M, Heit JJ. Favourable arterial, tissue-level and venous collaterals correlate with early neurological improvement after successful thrombectomy treatment of acute ischaemic stroke. J Neurol Neurosurg Psychiatry 2022; Epub ahead of print. [Crossref]
21. Renú Jornet A, Urra X, Laredo C, Montejo C, Rudilosso S, Llull L, Blasco J, Amaro S, Torne R, Obach V, Macho J, Chamorro A. Benefit from mechanical thrombectomy in acute ischemic stroke with fast and slow progression. J Neurointerv Surg 2020;12:132-5. [Crossref] [PubMed]
22. Guenego A, Mlynash M, Christensen S, Kemp S, Heit JJ, Lansberg MG, Albers GW. Hypoperfusion ratio predicts infarct growth during transfer for thrombectomy. Ann Neurol 2018;84:616-20. [Crossref] [PubMed]
23. Faizy TD, Kabiri R, Christensen S, Mlynash M, Kuraitis GM, Broocks G, Flottmann F, Marks MP, Lansberg MG, Albers GW, Fiehler J, Wintermark M, Heit JJ. Favorable Venous Outflow Profiles Correlate With Favorable Tissue-Level Collaterals and Clinical Outcome. Stroke 2021;52:1761-7. [Crossref] [PubMed]
24. Faizy TD, Kabiri R, Christensen S, Mlynash M, Kuraitis G, Meyer L, Marks MP, Broocks G, Flottmann F, Lansberg MG, Albers GW, Fiehler J, Wintermark M, Heit JJ. Venous Outflow Profiles Are Linked to Cerebral Edema Formation at Noncontrast Head CT after Treatment in Acute Ischemic Stroke Regardless of Collateral Vessel Status at CT Angiography. Radiology 2021;299:682-90. [Crossref] [PubMed]
25. Guenego A, Fahed R, Albers GW, Kuraitis G, Sussman ES, Martin BW, Marcellus DG, Olivot JM, Marks MP, Lansberg MG, Wintermark M, Heit JJ. Hypoperfusion intensity ratio correlates with angiographic collaterals in acute ischaemic stroke with M1 occlusion. Eur J Neurol 2020;27:864-70. [Crossref] [PubMed]
26. Li X, Lin L, Zhang J, Fan Y, Xing S, Jiang L, Yang Z, Zhao J, Li J. Microvascular dysfunction associated with unfavorable venous outflow in acute ischemic stroke patients. J Cereb Blood Flow Metab 2023;43:106-15. [Crossref] [PubMed]
27. Faizy TD, Kabiri R, Christensen S, Mlynash M, Kuraitis G, Broocks G, Flottmann F, Meyer L, Leischner H, Lansberg MG, Albers GW, Marks MP, Fiehler J, Wintermark M, Heit JJ. Distinct intra-arterial clot localization affects tissue-level collaterals and venous outflow profiles. Eur J Neurol 2021;28:4109-16. [Crossref] [PubMed]
28. Liebeskind DS. Mapping the collaterome for precision cerebrovascular health: Theranostics in the continuum of stroke and dementia. J Cereb Blood Flow Metab 2018;38:1449-60. [Crossref] [PubMed]
29. Anadani M, Finitsis S, Clarençon F, Richard S, Marnat G, Bourcier R, et al. Collateral status reperfusion and outcomes after endovascular therapy: insight from the Endovascular Treatment in Ischemic Stroke (ETIS) Registry. J Neurointerv Surg 2022;14:551-7. [Crossref] [PubMed]
30. Malikova H, Kremenova K, Lukavsky J, Holesta M, Lauer D, Koznar B, Weichet J. Early and late infarct growth rate in ischemic stroke patients after successful endovascular treatment in early time window: correlation of imaging and clinical factors with clinical outcome. Quant Imaging Med Surg 2023;13:5770-82. [Crossref] [PubMed]
31. Shimoyama T, Kimura K, Uemura J, Saji N, Shibazaki K. Elevated glucose level adversely affects infarct volume growth and neurological deterioration in non-diabetic stroke patients, but not diabetic stroke patients. Eur J Neurol 2014;21:402-10. [Crossref] [PubMed]
32. Zhong G, Yan S, Zhang S, Chen Q, Lai Y, Lou M. Association between Leukoaraiosis and Poor Outcome is not due to Reperfusion Inefficiency after Intravenous Thrombolysis. Transl Stroke Res 2016;7:439-45. [Crossref] [PubMed]
33. He G, Fang H, Xue B, Wei L, Lu H, Deng J, Zhu Y. Impact of leukoaraiosis on the infarct growth rate and clinical outcome in acute large vessel occlusion stroke after endovascular thrombectomy. Eur Stroke J 2024;9:338-47. [Crossref] [PubMed]