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. 2025 Jun 15;17(6):4546–4561. doi: 10.62347/XCXK6861

Collateral circulation significantly improves prognosis in cerebral infarction: a meta-analysis

Huafei Liu 1, Nengyun Yao 1, Haoyue Hu 1, Zhiwen Xiao 1, Yidi Tang 1, Songlin Tang 1
PMCID: PMC12261181  PMID: 40672639

Abstract

Objective: To systematically evaluate the association between collateral circulation and prognosis in patients with cerebral infarction through a meta-analysis. Methods: A comprehensive literature search was conducted across multiple databases to identify studies examining the relationship between collateral circulation and outcomes in cerebral infarction. Studies were screened based on predefined inclusion and exclusion criteria. Data were extracted and pooled using standard meta-analytic techniques. Results: A total of 41 studies encompassing 10,510 patients were included. Meta-analysis revealed that good collateral circulation was significantly associated with a favorable prognosis (pooled odds ratio [OR] = 1.67, 95% confidence interval [CI]: 1.35-2.07; P < 0.001). Subgroup analyses confirmed this association across different geographic regions and sample sizes. Conclusion: Collateral circulation is a critical determinant of prognosis in cerebral infarction. Enhancing collateral circulation may serve as a promising therapeutic strategy to improve clinical outcomes in affected patients.

Keywords: Collateral circulation, cerebral infarction, prognosis, meta-analysis

Introduction

Cerebral infarction is a major cerebrovascular disorder characterized by high incidence, disability, and mortality rates, posing a serious threat to human health and quality of life. Despite continuous advancements in medical technology and the widespread application of treatments such as intravenous thrombolysis and endovascular intervention, many patients with acute cerebral infarction still experience poor prognoses and varying degrees of neurological impairment. Therefore, identifying key prognostic factors and developing precise, individualized treatment strategies have become critical and urgent areas of research in the field of neuroscience.

Collateral circulation has garnered increasing attention for its pivotal role in the onset and progression of cerebral infarction. It refers to the physiological compensatory mechanism wherein, in cases of major cerebral artery stenosis or occlusion, alternative vascular pathways maintain perfusion to ischemic brain tissue [1]. Numerous studies have demonstrated a strong association between collateral status and clinical outcomes in cerebral infarction. For example, Gao et al. [2] reported a significant correlation between collateral circulation scores and the recurrence of acute cerebral infarction, suggesting that robust collateral flow may effectively lower recurrence risk. Similarly, Zhang et al. [3] found that well-developed collateral networks contribute to long-term cognitive improvement, underscoring the enduring neuroprotective effects of adequate collateral circulation.

Recent evidence has elucidated the multifactorial mechanisms through which collateral circulation influences prognosis. Studies [4] indicate that beyond improving perfusion, collateral pathways help regulate the metabolic microenvironment of ischemic tissue, mitigate the accumulation of neurotoxic substances, and support neuronal survival and repair. Furthermore, other investigations [5,6] suggest that strong collateral circulation enhances responsiveness to treatment, improving thrombolytic efficacy and reducing the risk of hemorrhagic transformation.

However, inconsistencies in study populations, collateral assessment methods, follow-up durations, and outcome measures have led to heterogeneous conclusions regarding the prognostic value of collateral circulation in cerebral infarction. To address these discrepancies, this meta-analysis employs rigorous statistical methodologies to comprehensively evaluate the true relationship between collateral status and clinical outcomes. By synthesizing available data, this study aims to provide robust, evidence-based insights to inform clinical practice. Ultimately, the findings may clarify the prognostic significance of collateral circulation, support its role as a therapeutic target, and contribute to enhanced management strategies for cerebral infarction.

Materials and methods

Literature search strategy

A comprehensive literature search was conducted in electronic databases including PubMed, Embase, Web of Science, and the Cochrane Library, covering publications from database inception to December 2024. Search terms included “collateral circulation”, “cerebral infarction”, “stroke”, “prognosis”, “outcome”, along with relevant synonyms and Medical Subject Headings (MeSH). In addition, the reference lists of all included studies were manually screened to ensure thorough identification of relevant literature. This study has been registered in the International Prospective Register of Systematic Reviews (PROSPERO; registration number: CRD42025639536).

Inclusion and exclusion criteria

Inclusion criteria: (1) Studies involving patients clinically diagnosed with cerebral infarction; (2) Evaluation of collateral circulation using objective imaging modalities such as digital subtraction angiography (DSA), computed tomography angiography (CTA), or magnetic resonance angiography (MRA); (3) Prognosis as a primary outcome, including indicators such as neurological recovery (e.g., NIH Stroke Scale [NIHSS], Modified Rankin Scale [mRS]), Barthel Index (BI), mortality, recurrence, or long-term disability rates; (4) Study design: prospective or retrospective cohort studies; (5) Sufficient data reported to calculate the odds ratio (OR) and 95% confidence interval (CI) based on multivariate analysis, or data that allowed such estimates to be derived.

Exclusion criteria: (1) Animal studies, review articles, conference abstracts, and case reports; (2) Studies lacking a clear investigation of the relationship between collateral circulation and prognosis, or studies with insufficient data for analysis; (3) Duplicate publications (in such cases, the most complete and recent study was retained).

Data extraction

Two independent, trained reviewers extracted data from the included studies. Extracted information included: Study characteristics (first author, publication year, region, study design); Participant details (sample size, age, sex); Method and results of collateral circulation assessment; Prognostic indicators and corresponding outcomes. Discrepancies or missing data were resolved by consulting the original articles, contacting authors, or involving a third reviewer.

Quality assessment

The quality of included cohort studies was assessed using the Newcastle-Ottawa Scale, which evaluates studies based on three domains: selection of study participants, comparability of groups, and assessment of outcomes. The maximum score is 9, with higher scores indicating higher methodological quality.

Statistical analysis

Meta-analysis was performed using RevMan 5.3 software. Heterogeneity among studies was assessed using the I2 statistic. If I2 ≤ 50%, a fixed-effect model was used. If I2 > 50%, indicating substantial heterogeneity, a random-effects model was applied.

Sources of heterogeneity were explored via subgroup analyses.

Pooled ORs with corresponding 95% CIs were calculated to assess the association between collateral circulation and cerebral infarction prognosis.

Subgroups were defined based on collateral circulation assessment method (e.g., DSA, CTA, MRA, transcranial Doppler), study region (e.g., Asia, Europe/North America) and sample size (categorized into large or small based on the median value).

Within each subgroup, heterogeneity was re-evaluated and effect sizes recalculated to determine differences in associations and assess potential sources of heterogeneity.

To test result robustness, sensitivity analysis was conducted by sequentially removing individual studies and observing changes in the pooled effect size and heterogeneity. If heterogeneity markedly decreased without significant changes in the pooled OR, the removed study was considered a potential source of heterogeneity.

Both funnel plots and Egger’s test were used to assess publication bias. Funnel plots were visually inspected for symmetry. A symmetric funnel shape suggests minimal publication bias, whereas asymmetry may indicate its presence. Egger’s test, a linear regression-based approach, assessed funnel plot asymmetry. The standard normal deviate (effect size divided by standard error) was regressed against the standard error. A P-value < 0.05 for the intercept term indicated potential publication bias.

Results

Literature search results

A total of 183 articles were initially retrieved. After screening titles, abstracts, and full texts based on inclusion and exclusion criteria, 41 eligible studies were included in the final analysis [7-47], comprising a total of 10,510 patients with cerebral infarction. The detailed study selection process is illustrated in Figure 1.

Figure 1.

Figure 1

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The literature screening process.

Basic characteristics of included studies

The basic characteristics of the included studies are summarized in Table 1. These studies were conducted across various countries and regions worldwide. Of the 41 studies, 18 were prospective cohort studies and 23 were retrospective cohort studies.

Table 1.

Basic characteristics of the included studies

Number Author/year Area Study type Sample size Male Ag (years) Collateral circulation assessment NOS
[7] Kucinski 2003 Germany Retrospective 111 84 13-76 DSA 8
[8] Mangiafico 2014 Italy Prospective 103 55 71 (60-77) CCS 7
[9] Sperti 2023 Italy Retrospective 520 215 Mean 75.04 (SD 14) dichotomic Menon scale 7
[10] Cuccione 2016 Italy Retrospective 182 - - 4D CTA-CS 7
[11] Liu 2022 China Prospective 58 - - ASL 7
[12] de Havenon 2017 America Retrospective 38 19 Mean 61 (SD 20) ASL 7
[13] Wu 2023 China Retrospective 55 - - ASL 7
[14] Bang 2011 America/South Korea Retrospective 222 119 Mean 65 ASITN/SIR 8
[15] van der Hoeven 2016 Netherlands Prospective 149 98 Mean 65 (SD 15) PC-CS 7
[16] Alves 2018 Netherlands Retrospective 195 119 - MR CLEAN trial 7
[17] Jeon 2024 Korea Prospective 214 - - 4D CTA-CS 6
[18] Kim 2020 Korea Prospective 154 99 69±13 MAC 6
[19] Yeo 2015 Singapore Retrospective 200 137 63 (35-92) Miteff System 7
[20] Lee 2023 Korea Prospective 148 96 68±13 ASL 6
[21] Park 2018 Korea Retrospective 119 60 72.9±11.9 LMC score 7
[22] Lima 2010 America Prospective 196 85 69±17 LMC score 6
[23] García-Tornel 2016 Canada Retrospective 108 47 69.6±13 mCTA 7
[24] Otani 2023 Korea Retrospective 81 49 Mean 70.3 tomography angiography score and posterior circulation collateral score 7
[25] Cao 2019 China Retrospective 34 19 71.1±11.5 4D CTA 7
[26] Yu 2021 China Prospective 40 27 60.12±11.84 CTA-MIP 7
[27] Gong 2024 China Retrospective 338 - - Tan scale 6
[28] Miteff 2009 Australia Prospective 92 39 Mean 75 CTA 6
[29] Derraz 2021 France Prospective 326 170 Mean 68.5 FLAIR sequence 7
[30] van den Wijngaard 2015 Netherlands Retrospective 70 36 Mean 68 (SD 14) Tan Collateral grading system 6
[31] Cao 2024 China Retrospective 126 - - 4D CTA 7
[32] Chen 2024 China Retrospective 80 48 Median 66.00 CTA 6
[33] Broocks 2019 Germany Retrospective 176 102 Median 76 5-point scoring system 7
[34] Cappellari 2022 Italy Prospective 95 44 70.6 (11-6) - 6
[35] Rocha 2014 Portugal Prospective 230 122 Median 72 ASPECTS 7
[36] Xin 2024 China Prospective 62 32 69.63±5.00 MRA 6
[37] Flores 2015 Spain Prospective 82 - 65.1±13.83 mCTA 6
[38] JU 2019 China Retrospective 73 - - CTA 7
[39] Wang 2017 China Retrospective 40 - - DSA 7
[40] Zhang 2023 China Retrospective 4483 - - CTA 7
[41] Gao 2021 China Prospective 187 147 60 (range: 23-80) ACGS-BAO 7
[42] van den Wijngaard 2016 Netherlands Prospective 61 34 median 67 dynamic CTA 7
[43] Luo 2018 China Prospective 69 57 Mean 59 ASPECTS 7
[44] Wang 2022 China Retrospective 100 80 63.0±10.7 - 8
[45] Wang 2018 China Retrospective 115 - - rLMC 8
[46] Boers 2018 Netherlands Prospective 442 - 66 (54-76) CTA 8
[47] Zhang 2022 China Retrospective 258 - 72.90±12.41 - 7
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CTA: Computed Tomography angiography; mCTA: multiphase CTA; 4D CTA-CS: four-dimensional computed tomography angiography; DSA: digital subtraction angiography; ASL: arterial spin labeling; MIP: maximum intensity projection; TOF: time-of-flight; MRA: MR angiography; PC-CS: posterior circulation collateral score; MR: Multicenter Randomized; CLEAN: Clinical Trial of Endovascular Treatment of Acute Ischemic Stroke in the Netherlands; MAC: MR acute ischemic stroke collateral; ASITN: American Society of Interventional and Therapeutic Neuroradiology; SIR: Society of Interventional Radiology; ASPECTS: Alberta Stroke Program Early CT; ACGS-BAO: angiographic collateral grading system for BAO; LMC: Leptomeningeal Collateral; rLMC: regional leptomeningeal; CCS: Collateral Circulation Scale; FLAIR: Fluid-Attenuated Inversion Recovery; NOS: Newcastle-Ottawa.

Collateral circulation was assessed using diverse methods, grouped as follows:

Imaging modalities (10 types): including CTA, 4D CTA, four-dimensional CTA with contrast score, multiphase CTA, dynamic CTA, DSA, time-of-flight MRA, CTA-MIP (maximum intensity projection), Fluid-Attenuated Inversion Recovery sequence, and arterial spin labeling (ASL).

Scoring systems (10 types): including the 5-point grading system, angiographic collateral grading system for basilar artery occlusion, MR Acute Ischemic Stroke Collateral (MAC) score, CT angiography score, posterior circulation collateral score (PC-CS), leptomeningeal collateral score, Alberta Stroke Program Early CT, Tan scale, and Tan collateral grading system.

Specific rating scales (3 types): including the dichotomized Menon scale, Miteff system, and Collateral Circulation Scale.

Trial-based/organizational criteria (2 types): including the Multicenter Randomized Clinical Trial of Endovascular Treatment of Acute Ischemic Stroke in the Netherlands trial and American Society of Interventional and Therapeutic Neuroradiology/Society of Interventional Radiology collateral grading system.

All included studies had a Newcastle-Ottawa Scale score ≥ 6, indicating good methodological quality.

Meta-analysis results: association between collateral circulation and cerebral infarction prognosis

(1) Overall association: Meta-analysis of the 41 studies demonstrated that collateral circulation was significantly associated with favorable outcomes in patients with cerebral infarction (pooled OR = 1.67, 95% CI: 1.35-2.07, P < 0.001), indicating that better collateral status increases the likelihood of a good prognosis. See Figure 2.

Figure 2.

Figure 2

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Forest map of the correlation between collateral circulation and prognosis of cerebral infarction.

(2) Subgroup analyses: By evaluation method: Studies were stratified by the method used to assess collateral circulation into CTA, ASL, and DSA groups. Subgroup analysis (Figure 3) revealed no statistically significant association between collateral circulation and prognosis in the CTA group (both P > 0.05), whereas significant associations were observed in the ASL and DSA groups (both P < 0.05). Differences in pooled ORs among subgroups suggest that assessment method may influence the strength of the observed correlation.

Figure 3.

Figure 3

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Forest plot of subgroup analysis by evaluation method. A. Computed Tomography angiography (CTA). B. Arterial spin labeling (ASL). C. Digital subtraction angiography (DSA).

By study region: Studies were categorized into two regional groups: Europe/North America and Asia. Both subgroups demonstrated a significant association between good collateral circulation and favorable prognosis (P < 0.05), with comparable pooled ORs (Figure 4), indicating consistent findings across geographic regions.

Figure 4.

Figure 4

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Forest plot of subgroup analysis by study region. A. European and American region group. B. Asian region group.

By sample size: Studies were divided into large-sample and small-sample groups based on the median sample size (n = 119). Both groups showed a significant association between collateral circulation and favorable prognosis (P < 0.05; Figure 5). Notably, the pooled OR in the large-sample group was more stable, suggesting higher reliability in larger studies.

Figure 5.

Figure 5

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Forest plot of subgroup analysis by sample size. A. Large-sample group (≥ 119). B. Small-sample group (< 119).

Sensitivity analysis

Sensitivity analysis was performed by sequentially removing individual studies to assess the impact on heterogeneity and overall effect size. Results showed that exclusion of certain studies reduced heterogeneity without significantly altering the pooled OR, indicating those studies may have contributed to heterogeneity. Overall, the findings remained stable and robust (Figures 6, 7, 8 and 9).

Figure 6.

Figure 6

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Sensitivity analysis of the correlation between collateral circulation and the prognosis of cerebral infarction.

Figure 7.

Figure 7

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Sensitivity analysis of the subgroup by evaluation method. A. Computed Tomography angiography (CTA). B. Arterial spin labeling (ASL).

Figure 8.

Figure 8

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Sensitivity analysis of the subgroup by study region. A. European and American region group. B. Asian region group.

Figure 9.

Figure 9

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Sensitivity analysis of the subgroup by sample size. A. Large-sample group (≥ 119). B. Small-sample group (< 119).

Assessment of publication bias

Funnel plot analysis and Egger’s test were conducted to evaluate publication bias. The funnel plot appeared symmetric, and all studies were evenly distributed (Figure 10). Egger’s test yielded a P value of 0.264 (> 0.05), suggesting no significant publication bias.

Figure 10.

Figure 10

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Funnel plot. A. Sensitivity analysis of the correlation between collateral circulation and the prognosis of cerebral infarction. B. European and American region group. C. Asian region group. D. Large-sample group (≥ 119). E. Small-sample group (< 119).

Discussion

This meta-analysis of 41 studies systematically investigated the association between collateral circulation and the prognosis of cerebral infarction, offering important implications for both research and clinical practice. The key finding is that good collateral circulation is significantly associated with favorable clinical outcomes. This is consistent with previous studies [48], as adequate collateral blood flow during ischemia can reduce infarct size, preserve neurological function, and increase the likelihood of recovery. Collateral circulation serves as an “emergency channel” for the brain, helping to sustain physiological function under critical conditions.

Subgroup analyses revealed notable differences based on the evaluation method. No significant association was observed in studies using CTA, whereas significant correlations were found in those using ASL and DSA, albeit with slightly varying pooled ORs. While CTA is widely used for visualizing vascular anatomy due to its speed and accessibility, it has limited capacity to assess hemodynamic status and tissue perfusion [49]. In contrast, ASL, a perfusion MRI technique, provides quantitative cerebral blood flow measurements [50], and DSA remains the gold standard for detailed visualization of vascular anatomy and collateral pathways [51]. Therefore, the choice of collateral evaluation method in both clinical and research settings should be tailored to the diagnostic objective to ensure accurate assessment.

Subgroup analysis by geographic region showed consistent findings across both European/American and Asian populations, with similar pooled ORs. This suggests that the protective role of collateral circulation is likely driven by common pathophysiological mechanisms, regardless of genetic, environmental, or healthcare differences [14]. These results support the global relevance of collateral circulation in ischemic stroke prognosis and emphasize the importance of incorporating collateral assessment into routine clinical protocols across regions.

Sample size-based subgroup analysis demonstrated significant associations in both large- and small-sample studies, with more stable pooled ORs observed in the large-sample group. This highlights the methodological robustness of larger studies, which are better able to control for confounding variables and minimize random error [52]. Incorporating large-sample studies into meta-analyses enhances both precision and reliability of the findings.

Sensitivity analysis, performed by sequentially excluding individual studies, identified one study that contributed substantially to heterogeneity. Its exclusion notably reduced heterogeneity without markedly altering the pooled effect size, suggesting that the overall findings are robust and not driven by any single study. Additional subgroup-based sensitivity analyses (by evaluation method, region, and sample size) also demonstrated consistent results, underscoring the overall reliability and internal stability of the analysis [53].

Nevertheless, several limitations must be acknowledged. Operational variations in collateral evaluation methods and parameter settings across studies may have introduced bias. The regional categorization into only two broad groups (European/American vs. Asian) may have overlooked more granular ethnic, lifestyle, or healthcare system differences. Additionally, dividing sample sizes based solely on the median may not fully reflect the statistical power of each study. Although funnel plots and Egger’s test showed no apparent publication bias, the presence of potential bias cannot be entirely excluded. Future research should adopt more refined designs and standardized methodologies to address these limitations.

Conclusion

This meta-analysis provides robust evidence that good collateral circulation is significantly associated with favorable outcomes in patients with cerebral infarction. Although evaluation methods, study regions, and sample sizes may influence the strength of this association, the overall results are consistent and stable. Future studies should focus on optimizing collateral assessment techniques and conducting large-scale, multicenter trials to further elucidate the mechanisms by which collateral circulation affects prognosis. Enhanced international collaboration will be essential to advancing the global understanding and management of cerebral infarction.

Disclosure of conflict of interest

None.

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