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Neuroimaging
Original research
Brain edema growth after thrombectomy is associated with comprehensive collateral blood flow
  1. Tobias D Faizy1,
  2. Laurens Winkelmeier1,
  3. Michael Mlynash2,
  4. Gabriel Broocks1,
  5. Christian Heitkamp1,
  6. Christian Thaler1,
  7. Noel van Horn1,
  8. Pierre Seners3,
  9. Helge Kniep1,
  10. Paul Stracke4,
  11. Kamil Zelenak5,6,
  12. Maarten G Lansberg2,
  13. Gregory W Albers7,
  14. Max Wintermark8,
  15. Jens Fiehler1,
  16. Jeremy J Heit9
  1. 1Department of Diagnostic and Interventional Neuroradiology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
  2. 2Department of Neurology, Stanford Stroke Center, Stanford University, Stanford, California, USA
  3. 3Neurology, Fondation Rothschild, Paris, France
  4. 4Section of Interventional Neuroradiology, University Hospital Munster, Munster, Germany
  5. 5Clinic of Radiology, Comenius University in Bratislava Jessenius Faculty of Medicine in Martin, Martin, Slovakia
  6. 6Clinic of Radiology, University Hospital Martin, Martin, Slovakia
  7. 7Stanford Stroke Center, Stanford Medicine, Stanford, California, USA
  8. 8Department of Neuroradiology, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA
  9. 9Radiology, Neuroadiology and Neurointervention Division, Stanford University, Stanford, California, USA
  1. Correspondence to Dr Tobias D Faizy, Neuroradiology, University Medical Center Hamburg-Eppendorf, Hamburg, Hamburg, Germany; t.faizy{at}uke.de

Abstract

Background We determined whether a comprehensive assessment of cerebral collateral blood flow is associated with ischemic lesion edema growth in patients successfully treated by thrombectomy.

Methods This was a multicenter retrospective study of ischemic stroke patients who underwent thrombectomy treatment of large vessel occlusions. Collateral status was determined using the cerebral collateral cascade (CCC) model, which comprises three components: arterial collaterals (Tan Scale) and venous outflow profiles (Cortical Vein Opacification Score) on CT angiography, and tissue-level collaterals (hypoperfusion intensity ratio) on CT perfusion. Quantitative ischemic lesion net water uptake (NWU) was used to determine edema growth between admission and follow-up non-contrast head CT (ΔNWU). Three groups were defined: CCC+ (good pial collaterals, tissue-level collaterals, and venous outflow), CCC− (poor pial collaterals, tissue-level collaterals, and venous outflow), and CCCmixed (remainder of patients). Primary outcome was ischemic lesion edema growth (ΔNWU). Multivariable regression models were used to assess the primary and secondary outcomes.

Results 538 patients were included. 157 patients had CCC+, 274 patients CCCmixed, and 107 patients CCC− profiles. Multivariable regression analysis showed that compared with patients with CCC+ profiles, CCC− (β 1.99, 95% CI 0.68 to 3.30, P=0.003) and CCC mixed (β 1.65, 95% CI 0.75 to 2.56, P<0.001) profiles were associated with greater ischemic lesion edema growth (ΔNWU) after successful thrombectomy treatment. ΔNWU (OR 0.74, 95% CI 0.68 to 0.8, P<0.001) and CCC+ (OR 13.39, 95% CI 4.88 to 36.76, P<0.001) were independently associated with functional independence.

Conclusion A comprehensive assessment of cerebral collaterals using the CCC model is strongly associated with edema growth and functional independence in acute stroke patients successfully treated by endovascular thrombectomy.

  • Stroke
  • Thrombectomy
  • Vein

Data availability statement

Data are available upon reasonable request. All data that supported our work will be available from the corresponding author upon reasonable request.

http://creativecommons.org/licenses/by-nc/4.0/

This is an open access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited, appropriate credit is given, any changes made indicated, and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/.

https://doi.org/10.1136/jnis-2023-020921

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    WHAT IS ALREADY KNOWN ON THIS TOPIC

    • Cerebral collaterals play a pivotal role in the maintenance of blood flow to and through ischemic brain tissue. Ischemic brain edema results from impaired cerebral perfusion due to poor collateral blood flow. Recent neurobiology studies presumed that collateral blood flow should ideally be determined at different levels of the cerebral vascular circuit. Whether a comprehensive assessment of cerebral collaterals is viable and associated with brain edema development after stroke treatment is unknown.

    WHAT THIS STUDY ADDS

    • The novel diagnostic concept of the cerebral collateral cascade (CCC) delineates arterial collaterals, tissue-level collaterals, and venous outflow profiles in one comprehensive model. This study demonstrates that favorable CCC profiles are strongly associated with brain edema growth after successful thrombectomy of a large vessel occlusion.

    HOW THIS STUDY MIGHT AFFECT RESEARCH, PRACTICE OR POLICY

    • Our findings point to the possibility that a comprehensive assessment of cerebral collaterals during treatment triage may be a useful and robust imaging biomarker to predict brain edema development and functional outcomes in stroke patients treated by thrombectomy. Future studies should assess the transferability of this novel method to the clinical routine.

    Introduction

    Endovascular thrombectomy (EVT) has become the standard of care for the treatment of patients with acute ischemic stroke and large vessel occlusion (AIS-LVO).1 Timely restoration of blood flow to ischemic brain tissue is crucial for a potential neurological recovery of these patients. However, poor clinical outcomes are still observed in a substantial number of patients treated by EVT despite successful vessel reperfusion.2 3 One explanation for that may be the occurrence of extensive brain edema formation, which is strongly related to collateral blood flow during the period of brain ischemia.4 5 Consequently, reliable imaging biomarkers that identify patients at risk of brain edema growth are needed.

    Cerebral edema can be quantified directly by ischemic lesion net water uptake (NWU) using densitometry of hypoattenuated infarct areas on non-contrast head CT.6 Extensive ischemic lesion NWU correlates with poor microvascular perfusion status and more severe ischemic damage to the brain tissue.5 7 However, successful vessel reperfusion during EVT was found to be associated with reduced formation of ischemic brain edema.5 8–12

    Notably, quantitative changes of NWU over time also seem to be linked to the cerebral collateral status.8 11 13–16 A favorable collateral status is associated with better procedural and clinical outcomes of AIS-LVO patients after thrombectomy treatment.17 However, conventional radiological measurements of cerebral collateralization are usually limited to a single-parameter assessment of collateral blood flow.18 19

    Recently, a novel diagnostic framework for a comprehensive assessment of the cerebral collateral status was introduced.20 This cerebral collateral cascade (CCC) model combines collateral measures from three levels of the collateral circuit and allows for a more comprehensive assessment of collateral blood flow to and through the ischemic brain tissue into subsequent cortical veins.20 21 However, it remains unclear whether the CCC model correlates with ischemic brain edema growth following thrombectomy in AIS-LVO patients.

    In this study, we aimed to investigate whether distinct collateral blood flow patterns determined by the CCC model are associated with brain edema growth in AIS-LVO patients successfully treated by thrombectomy. We hypothesized that favorable collateral profiles on all three distinct levels of the collateral cascade are associated with reduced brain edema growth compared with patients with less favorable collateral profiles, and that both less edema growth and favorable collateral profiles are correlated with good clinical outcomes. Our findings may have important implications for cerebral edema biology and stroke pathophysiology in the setting of AIS-LVO.

    Methods

    Study design

    This was a retrospective multicenter cohort study of AIS-LVO patients treated by endovascular thrombectomy at two comprehensive stroke centers (University Medical Center Hamburg-Eppendorf, Germany, and Stanford University Hospital, USA) between May 2015 and December 2021.

    Standard protocol approvals, registrations, and patient consents

    The study protocol was approved by the institutional review boards of both study centers (ID 689–15), complied with the Health Insurance Portability and Accountability Act (HIPAA), and followed the guidelines of the Declaration of Helsinki. Patient informed consent was waived by our review boards for this retrospective study. This study reports against the STROBE (Strengthening the Reporting of Observational Studies in Epidemiology) guidelines for medical research.

    Patient inclusion, population, and clinical data

    Patient data were obtained from prospectively maintained stroke databases at each center. Inclusion criteria were: (1) patients with AIS-LVO treated by thrombectomy; (2) multimodal imaging assessment on patient admission including non-contrast head CT, CT angiography with homogeneous opacification of the superior sagittal, transverse, and sigmoid dural venous sinuses to allow for CT angiography collateral status, and venous outflow determination and interpretable CT perfusion imaging studies; (3) anterior circulation large vessel occlusion of the internal carotid artery or first (M1) or second (M2) segment of the middle cerebral artery; (4) successful vessel recanalization during EVT (defined as modified Thrombolysis In Cerebral Infarction Score (TICI) 2b-3); (5) availability of a non-contrast head CT 24–48 hours following EVT to determine post-treatment NWU.

    Exclusion criteria were: (1) poor CT angiography image quality due to excessive patient motion or incomplete contrast opacification of target cerebral arteries and veins20; (2) poor CT perfusion image quality due to excessive motion degradation or failed contrast bolus.

    Imaging analysis

    All perfusion imaging studies were automatically analyzed with RAPID (iSchemaView, Menlo Park, CA).22

    The three components of the CCC model were analyzed according to the approach described by Faizy et al.20

    Pial arterial collaterals were assessed using the Tan scale on CT angiography images by consensus reading of two neuroradiologists (TDF and JH with 11 and 16 years of experience, respectively).23 Good collaterals were defined as filling of ≥50%, and poor collaterals were defined as <50% filling of the middle cerebral artery territory.

    The hypoperfusion intensity ratio (HIR), defined as volume of brain tissue with a delay of Tmax >10 s divided by the volume of brain tissue with a Tmax delay of >6 s, was automatically derived from CT perfusion imaging to determine tissue-level collaterals.22 Favorable tissue-level collaterals were defined as HIR ≤0.4, whereas poor tissue-level collaterals were defined as HIR >0.4.19 24

    Venous outflow profiles were determined by two experienced neuroradiologists (TDF, JH) in the vein of Labbé, sphenoparietal sinus, and superficial middle cerebral vein using the Cortical Vein Opacification Score (COVES) on single-phase CT angiography.25 Discrepancies were settled by consensus. Favorable venous outflow was defined as a score of 3–6 and unfavorable venous outflow was regarded a score of 0–2.24

    Successful vessel recanalization after thrombectomy treatment was defined as modified TICI scores of 2b-3.

    The Alberta Stroke Program Early CT Score (ASPECTS) was determined on pre-treatment head non-contrast CT images.26

    Ischemic lesion NWU (%) was determined on both admission and follow-up non-contrast head CT images as described by Broocks et al.5 The density of ischemic tissue was measured in a region of interest (ROI) defining the demarcated hypoattenuated ischemic lesion on non-contrast head CTs. The corresponding normal density was determined as an ROI mirrored symmetrically to the non-ischemic hemisphere and adjusted anatomically to exclude sulci and cerebrospinal fluid. NWU was calculated per volume of infarct. Ischemic lesion edema growth (ΔNWU) was specified as the difference of NWU at follow-up and on admission.5

    Study group definitions

    A favorable (CCC+) profile was defined as: Tan ≥50%, HIR ≤0.4, and COVES of 3–6. An unfavorable (CCC−) profile was regarded as: Tan <50%, HIR >0.4, and COVES of 0–2. CCCmixed profiles were assigned to patients who did not fulfill the criteria of the CCC+ or CCC− groups.20

    Outcome measures

    Primary outcome was ischemic lesion edema growth (ΔNWU) between patient admission and follow-up after thrombectomy treatment. Secondary outcome was favorable functional outcome defined as functional independence (mRS score of 0–2) 90 days after thrombectomy treatment.

    Statistical analysis

    Continuous and ordinal variables were described by median (IQR) and categorical variables by N (%). Patient demographics, clinical variables, and neuroimaging data were compared between either two or three CCC groups using χ2 tests, and Mann Whitney U or Kruskal-Wallis tests, or trend statistics (Cochran-Armitage Trend Test or Jonckheere-Terpstra Test for Ordered Alternatives), respectively.

    Clinical and imaging variables association with ΔNWU and functional outcome was assessed using multivariable models: univariate general linear model, and binary logistic regression, respectively. The models were adjusted for imbalances between CCC groups: age, presentation National Institutes of Health Stroke Scale (NIHSS), serum glucose at enrollment, penumbra and estimated core volumes determined by CT perfusion, admission ASPECTS, and vessel occlusion localization. ΔNWU was added as an independent variable for functional outcome model.

    α was set at the 0.05 level, and all reported results are two-sided. Statistical analysis was done using IBM SPSS statistics, v. 28.0 and SAS 9.4.

    Results

    A total number of 813 patients underwent thrombectomy triage, and 538 met inclusion criteria (online supplemental figure 1). There were 157 patients in the CCC+, 274 patients in the CCCmixed, and 107 patients in the CCC− groups.

    Supplemental material

    Patient demographics and presentation details

    CCC+ patients were younger (median (IQR) 72 years (61–80)) than CCCmixed (75 years (64–83)) and CCC− patients (77 years (68–83)) (P=0.002) and had lower presentation NIHSS scores (median (IQR) 10 (6–14)) compared with CCCmixed (15 (10–19)) and CCC− (18 (15–21)) (P<0.001). Blood glucose on admission was slightly lower in CCC+ patients (median (IQR) 116 mg/dL (99–141)) compared with CCCmixed (122 mg/dL (105–153)) and CCC− patients (121 mg/dL (106–157)) (P=0.032). A greater proportion of CCC+ patients (61%) received treatment with intravenous alteplase compared with CCCmixed (49%) and CCC− (45%) patients. All other patient characteristics are displayed in table 1.

    View this table:
    Table 1

    Patient characteristics and stroke presentation details

    Imaging characteristics and clinical outcomes

    On baseline imaging evaluation, CCC+ patients had the highest ASPECTS (median (IQR) 9 (8–10) vs 8 (6–9) in CCCmixed and 6 (5–8) in CCC− patients; P<0.001), smaller estimated baseline ischemic core volumes (median (IQR) 0 mL (0–7) vs 13 mL (0–28) in CCCmixed and 44 (18–87) in CCC− patients; P<0.001), smaller penumbra volumes (Tmax >6 s delay) on perfusion imaging (median (IQR) 90 mL (58–130) vs 129 mL (75–171) in CCCmixed and 174 (25–229) in CCC− patients; P<0.001), and smaller final infarct volumes (median (IQR) 9 mL (4–20) vs 27 mL (10–67) in CCCmixed and 57 mL (25–139) in CCC−). CCC+ patients were less likely to have a more proximal vessel occlusion compared with CCCmixed and CCC− patients (P<0.001).

    CCC+ patients had more favorable functional outcomes on the modified Rankin Scale (mRS) 90 days after successful EVT treatment (median (IQR) mRS 1 (0–2)) compared with CCCmixed (4 (1–5)) and CCC− (5 (4–6)) (P<0.001) patients (table 2).

    View this table:
    Table 2

    Imaging and clinical outcomes

    Ischemic lesion edema assessment

    CCC+ patients exhibited less median NWU on admission non-contrast head CT (median (IQR) 2.42% (0.99–3.96%)) compared with CCCmixed (6.54% (3.46–8.93%)) and CCC− (8.38% (6.72–11.18%)) (P<0.001). In addition, the median ischemic lesion NWU at follow-up was lower in CCC+ patients (median (IQR) 6.94% (3.87–9.38%)) when compared with patients with CCCmixed (13.94% (7.75–18.58%)) and CCC− (16.66% (11.20–22.96%)) (P<0.001) profiles. Finally, the ischemic lesion edema growth (ΔNWU) measured at patient admission and after EVT treatment was found to be significantly lower in patients with a CCC+ profile (median (IQR) 3.88% (2.80–5.55%)) vs patients with CCCmixed (7.01% (4.01–9.99%)) and unfavorable CCC− profiles (8.51% (5.25–11.21%)) (P<0.001) (table 2, figure 1).

    Figure 1
    Figure 1

    Extent of cerebral edema growth after thrombectomy stratified by the distinct cerebral collateral cascade (CCC). Boxplots display the extent of ischemic edema formation growth assessed in patients with distinct CCC profiles. Ischemic lesion net water uptake (NWU, %) was used to quantify edema growth on non-contrast head CT images between patient admission and follow-up (ΔNWU). A favorable CCC (CCC+) profile was defined as: Tan ≥50%, hypoperfusion intensity ratio (HIR) ≤0.4, Cortical Vein Opacification Score (COVES) 3–6. An unfavorable CCC (CCC−) profile was regarded as: Tan <50%, HIR >0.4, COVES 0–2. CCCmixed profiles were assigned to patients who did not fulfill the criteria of the CCC+ or CCC− groups. Patients who exhibited CCC+ profiles had significantly lower ΔNWU percentages compared with patients with CCCmixed and CCC− profiles after successful thrombectomy treatment.

    Assessment of the primary outcome (ΔNWU)

    For the primary outcome analysis, 481 patients were included in a general linear model, which was adjusted for baseline imbalances and predictors of ΔNWU. Fifty-seven patients were excluded due to unknown presentation NIHSS, core and penumbra volumes, or blood glucose values. Compared with patients with CCC+ profiles, CCC− (β 1.99, 95% CI 0.68 to 3.30, P=0.003) and CCCmixed (β 1.65, 95% CI 0.75 to 2.56, P<0.001) profiles were independently associated with higher ischemic edema growth (ΔNWU) in AIS-LVO patients who were successfully treated by endovascular thrombectomy, after controlling for blood glucose, age, presentation NIHSS, baseline ASPECTS, vessel occlusion localization, penumbra, and ischemic core volume. However, when comparing patients with a CCCmixed and CCC− profile, we did not find any difference in association with ΔNWU for these respective patients (β −0.34, 95% CI −1.40 to 0.72, P=0.532) (table 3). Online supplemental figures 2 and 3 demonstrate patient examples for distinct CCC profiles.

    View this table:
    Table 3

    Primary outcome analysis (ΔNWU)—general linear model analysis

    Assessment of the secondary outcome (mRS 0–2)

    For the secondary outcome analysis, 468 patients were included in a multivariable binary logistic regression model (online supplemental table 1). We included the same covariables as in the primary outcome model with the addition of ΔNWU as independent variable. We found that an increase in ΔNWU was independently associated with less odds of functional independence at 90 days (OR 0.74, 95% CI 0.68 to 0.8, P<0.001). In addition, we found that patients with more favorable collateral blood flow to and through ischemic tissue, as reflected by the CCC model, had higher odds for achieving good functional outcomes after successful thrombectomy treatment. Compared with CCC− (OR 13.39, 95% CI 4.88 to 36.76, P<0.001) and CCCmixed (OR 4.55, 95% CI 2.33 to 8.33, P<0.001) profiles, we found that CCC+ profiles were independently associated with good functional outcomes 90 days after successful endovascular treatment. Interestingly, patients who exhibited CCCmixed profiles still had higher odds of achieving good functional outcomes when compared with patients with CCC− profiles (OR 3.00, 95% CI 1.26 to 7.14, P=0.01).

    Discussion

    In this study, we determined whether comprehensive assessment of cerebral collateral status is associated with ischemic lesion edema growth in AIS-LVO patients successfully treated with thrombectomy. Comprehensive cerebral collateral blood flow was assessed using the CCC framework and we evaluated the impact of different collateral profiles on quantitative ischemic lesion NWU changes between patient admission and follow-up (ΔNWU) and clinical outcomes. We found that CCC+ patients developed less ischemic brain edema growth after successful thrombectomy compared with CCC– and CCCmixed patients. More favorable CCC profiles and decreased ΔNWU were independently associated with functional independence 90 days after treatment. Our findings suggest that unhampered collateral blood flow from pial arteries through microvascular tissue-level vessels into draining cerebral cortical veins reflects robust cerebral microperfusion during brain ischemia, which is directly associated with less ischemic damage to the brain.9 27

    Our findings have important implications for AIS-LVO patients eligible for EVT. A substantial proportion of AIS-LVO patients still exhibit poor clinical outcomes despite timely and successful vessel reperfusion.2 28–31 Besides other parameters, extensive ischemic brain edema formation is a known cause of poor clinical outcomes despite successful reperfusion.5 8 Our findings indicate that CCC− and CCCmixed patients are at an increased risk of brain edema progression, which may result in less favorable functional outcomes. Therefore, new treatments designed to reduce brain edema progression may be optimally tested in these patients.

    NWU in ischemic tissue can be directly quantified as an imaging biomarker of ischaemic edema.12 While NWU assessment is currently still predominantly used in a research environment, this technique illustrates a well-understood and important pathophysiological phenomenon, namely brain edema development by compromised water hemostasis in ischemic brain tissue.5 15 Brain edema biology is complex and governed by multiple mechanisms associated with impaired cerebral tissue microperfusion.15 27 32 33 In addition, aggravated brain edema increases the risk for malignant infarction, which is associated with poor outcomes.12 Over time, extensive brain edema itself impairs microvascular blood flow and prior studies have demonstrated a strong link between hampered collateral blood flow and aggravated edema formation in AIS-LVO patients.10 11 14 While the extent of tissue edema can be directly quantified by means of quantitative NWU, several different ways exist to quantify collateral vessels on radiological imaging.18 One major drawback of many conventional collateral scores is that these approaches are only able to assess a minor proportion of the collateral circuit, thus they are unable to provide comprehensive assessment of collateral blood flow. However, critical patterns of cerebral hypoperfusion are likely reflected by the most distal arteries and their subsequent venous drainage, which are typically not determined by conventional collateral scores.34

    The recent introduction of the CCC framework provides a comprehensive collateral vessel assessment in AIS-LVO patients. A previous study found that a multiparametric evaluation of the collateral status during endovascular treatment triage was strongly associated with radiological and long-term clinical outcomes compared with a single-parameter approach alone, which is in line with our findings.20 However, the aforementioned study also included patients with unsuccessful vessel reperfusion status (TICI 0-2a) after thrombectomy and did not assess brain edema formation. The findings of this study suggest that hampered comprehensive collateral blood flow may result in aggravated brain edema despite successful vessel reperfusion, which likely promotes the exhibition of poor functional outcomes in this group of patients. Brain edema development represents one of the pathophysiological hallmarks of ischemic stroke pathophysiology and is inherently linked to clinical outcomes and neurological recovery.5 In addition, the individual collateral status has strong implications for maintaining microvascular blood flow during AIS-LVO, thus indirectly affecting cerebral water hemostasis. Consequently, our study provides an important link between edema development and collateral blood flow status.15 As brain edema formation and collateral blood flow are both linked to early clinical recovery and long-term functional outcomes after mechanical thrombectomy, a deeper knowledge and proper assessment of these parameters would provide important information to neurointerventionalists and physicians alike before and after treatment.

    Interestingly, other studies found that the components of the CCC model were associated with early edema progression (defined as estimated edema growth from the time of symptom onset to patient admission) and the magnitude of edema formation after thrombectomy.11 13–15 While one study did not find a significant association between pial arterial collaterals and edema formation after treatment, others reported a strong correlation between arterial collaterals and edema development over time.7 10 11 Another study found a strong link between tissue-level collaterals and venous outflow profiles with respect to clinical outcomes in patients treated by thrombectomy.24 However, differences in the aforementioned findings may result from the use of different collateral scores for pial arterial collateral assessment, different patient characteristics and treatment protocols. In addition, it is important to note that large infarcts do not necessarily have higher ischemic lesion NWU measures and vice versa. In particular, also small infarcts can exhibit elevated NWU percentages indicating more severe tissue damage, which may lead to worse clinical outcomes despite smaller infarct volumes.12 However, this mechanism is still not well understood and requires additional research. Further prospective studies are needed to investigate the impact of distinct collateral profiles on patient outcomes and thrombectomy efficacy in more detail. Finally, to date, a comprehensive collateral assessment using the CCC model is time consuming. Thus, an automated approach to determine the vasculature of the CCC model would hold appeal.

    Our study has limitations. The retrospective design may introduce bias and limit the generalizability of our findings. Although we only included patients with complete opacification of the sigmoid sinuses, the potential technical limitations for the use of single-phase CT angiography images to determine venous outflow have been discussed before.15 The use of other imaging scores to determine pial arterial collaterals and utilization of different processing software to determine perfusion imaging derived parameters may have led to different results.

    In conclusion, in AIS-LVO patients, a comprehensive assessment of the collateral status using the CCC model is strongly associated with ischemic lesion NWU development determined between patient admission and 24–48 hours after successful thrombectomy treatment. This study highlights the importance of a more holistic approach towards collateral blood flow assessment in AIS-LVO patients, and elucidates the crucial role of unhampered cerebral collateral blood flow with regards to cerebral edema formation in ischemic brains.

    Data availability statement

    Data are available upon reasonable request. All data that supported our work will be available from the corresponding author upon reasonable request.

    Ethics statements

    Patient consent for publication

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    Supplementary materials

    • Supplementary Data

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    Footnotes

    • Twitter @WinkelmeierMD, @noelvanhorn, @stanfordNRAD, @Fie0815, @JeremyHeitMDPHD

    • Contributors The authors of this study contributed as follows: TDF: Study design and conceptualization. Acquisition of the data. Image processing. Image analysis. Data analysis. Drafting the manuscript and revising it critically. Approving a final version of the manuscript to be published. LW: Study design and conceptualization. Acquisition of the data. Image processing. Drafting the manuscript and revising it critically. Approving a final version of the manuscript to be published. CH: Study design and conceptualization. Acquisition of the data. Image processing. Image analysis. Data analysis. Drafting the manuscript and revising it critically. Approving a final version of the manuscript to be published. MM: Acquisition of the data. Data analysis. Statistical supervisor and statistical analysis. Drafting the manuscript and revising it critically. Approving a final version of the manuscript to be published. CT: Acquisition of the data. Image processing. Data analysis. Drafting the manuscript and revising it critically. Approving a final version of the manuscript to be published. NvH: Acquisition of the data. Image processing. Data analysis. Drafting the manuscript and revising it critically. Approving a final version of the manuscript to be published. GB: Data analysis. Drafting the manuscript and revising it critically. Approving a final version of the manuscript to be published. HK: Data analysis. Drafting the manuscript and revising it critically. Approving a final version of the manuscript to be published. PSe: Data analysis. Data interpretation. Drafting the manuscript and revising it critically. Approving a final version of the manuscript to be published. PSt: Data analysis. Data interpretation. Drafting the manuscript and revising it critically. Approving a final version of the manuscript to be published. KZ: Acquisition of the data. Image processing. Data analysis. Drafting the manuscript and revising it critically. Approving a final version of the manuscript to be published. MGL: Data interpretation. Supervision. Drafting the manuscript and revising it critically. Approving a final version of the manuscript to be published. Approving a final version of the manuscript to be published. GWA: Conceptualization of the study. Data interpretation. Supervision. Drafting the manuscript and revising it critically. Approving a final version of the manuscript to be published. JF: Data interpretation. Supervision. Drafting the manuscript and revising it critically. Approving a final version of the manuscript to be published. MW: Conceptualization of the study. Data interpretation. Supervision. Drafting the manuscript and revising it critically. Approving a final version of the manuscript to be published. JJH: Study design and conceptualization. Acquisition of the data. Image processing. Image analysis. Data analysis. Supervision. Drafting the manuscript and revising it critically. Approving a final version of the manuscript to be published. TDF is guarantor of the work.

    • Funding Tobias Djamsched Faizy was funded by the German Research Foundation (DFG) for his work as a postdoctoral research scholar at Stanford University, Department of Neuroradiology (Project Number: 411621970).

    • Competing interests TDF reports research grants from the German Research Foundation (DFG, Project Number: 411621970) for his work as a postdoctoral scholar at Stanford University. GB reports research grants from the German Research Foundation (DFG) outside of the submitted work. GWA reports equity and consulting for iSchemaView and consulting from Medtronic. MW reports grants and funding from the NIH under the grant numbers (1U01 NS086872-01, 1U01 NS087748-01 and 1R01 NS104094). He reports compensation from Subtle Medical, Magnetic Insight, Icometrix and EMTensor for consultant services and employment by the University of Texas MD Anderson Cancer Center. JF reports stock holdings in Tegus Medical and grants and personal fees from Acandis, Cerenovus, MicroVention, Medtronic, Stryker, Phenox and grants from Route 92 outside the submitted work. JJH reports consulting for Medtronic and MicroVention and Medical and Scientific Advisory Board membership for iSchemaView.

    • Provenance and peer review Not commissioned; externally peer reviewed.

    • Supplemental material This content has been supplied by the author(s). It has not been vetted by BMJ Publishing Group Limited (BMJ) and may not have been peer-reviewed. Any opinions or recommendations discussed are solely those of the author(s) and are not endorsed by BMJ. BMJ disclaims all liability and responsibility arising from any reliance placed on the content. Where the content includes any translated material, BMJ does not warrant the accuracy and reliability of the translations (including but not limited to local regulations, clinical guidelines, terminology, drug names and drug dosages), and is not responsible for any error and/or omissions arising from translation and adaptation or otherwise.