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AJNR. American journal of neuroradiology

September 17, 2026 · via Europe PMC

Imaging Modalities to Visualize Deep Cerebral Perforating Arteries: A Systematic Review and Meta-Analysis.

Sadigh Y, Gahrmann R, Hendrikse J, Dirven CMF, Dippel DWJ, Schouten JW, Dammers R, Volovici V.

ReviewAbstract only — full text under license

AI summary — for doctors, generated from the abstract only

7T MRA showed the highest detection rate (94%) for deep cerebral perforating arteries, though most studies lacked anatomic validation.

What was studied

Systematic review and meta-analysis of 106 studies (6785 participants) using 7T, 3T, 1.5T MRI/MRA, CTA, CT, DSA or ultrasound to visualize perforating arteries.

Key findings

  • Pooled detection rate 94% at 7T and 85% at 3T
  • Substantial heterogeneity (I2 64-84%)
  • Only one study validated detection intraoperatively

Clinical relevance

This suggests high-field MRA is best for perforator visualization in research, but reported rates may overestimate true visualization and clinical reliability is unproven.

Who should care

Neuroradiology

Limitations

Mostly healthy volunteers, heterogeneous studies, and lack of in vivo validation.

7T MRA sees perforating arteries best, but accuracy is unverified.

This is an AI-generated summary of the published abstract, not a clinical recommendation. It may not reflect the full text or subsequent updates — verify against the original source before acting on it.

Abstract

Background

The reliable visualization of deep cerebral perforating arteries is a challenge. Despite the advancements in high-resolution imaging, the optimal technique to depict deep cerebral perforating arteries remains unclear.

Purpose

The purpose of this systematic review was to provide an overview of the imaging modalities used to visualize perforating arteries and to evaluate their diagnostic performance.

Data sources

EMBASE, Ovid Medline, the Web of Science Core Collection, Google Scholar, and Cochrane Central Register of Controlled Trials were searched from database inception to April 15, 2025.

Study selection

Original studies using imaging modalities to depict perforating arteries in human subjects were included. The search strategy yielded 3857 articles, of which 1725 remained after removing duplicates. After the initial sift phase, 215 articles remained to be assessed for eligibility based on full-text sifting. Finally, 106 studies (6785 participants; 14,041 hemispheres) were included.

Data analysis

As a performance measure, detection rate was defined as the percentage of participants in which at least 1 perforating artery in 1 arterial territory could be detected. Pooled estimate (%) of detection rate per imaging technique was calculated using a random-effects model with 95% CI.

Data synthesis

Studies used 7T MRA/MRI (n=56), 3T MRA/MRI (n=32), 1.5T MRA/MRI (n=6), CTA (n=4), CT (n=1), DSA (n=14), and transcranial ultrasound (n=3). Pooled estimates found a detection rate of 94% (95% CI, 0.90-0.97; I2 = 64%) for 7T MRA/MRI and 85% (95% CI, 0.63-0.95; I2 = 84%) for 3T MRA/MRI. One 3T MRA study performed an in vivo diagnostic validation study by direct intraoperative evaluation.

Limitations

Our findings have not been validated in vivo.

Conclusions

Multiple imaging modalities, including 7T, 3T, and 1.5T MRA/MRI, CTA, and DSA, have been used to visualize deep cerebral perforating arteries. High-resolution MRI, particularly 7T MRA, shows the highest detection rates (up to 94%), although most studies were performed in healthy volunteers and lacked anatomic validation. Consequently, reported detection rates may overestimate true vessel visualization. Future research should prioritize rigorous in vivo validation of these techniques to establish their clinical reliability.

DOI

10.3174/ajnr.a9312

PMID

41881569

Research metadata (titles, abstracts, authors, publication dates) is sourced from Europe PMC, which aggregates content from PubMed/MEDLINE, PubMed Central, and other providers under the U.S. National Library of Medicine (NLM/NCBI). NLM does not claim copyright on abstracts; the original journal publishers or authors may hold rights to the full articles. AI-generated summaries are derived only from the abstract, never the full text, and are always labeled as AI-generated.

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