# Diagnostic Performance of Photon-Counting CT Angiography in Vascular Stenosis Assessment: A Systematic Review and Meta-Analysis

**Authors:** Nasser M. Alzahrani, Awad Alzahrani, Zyad M. Almutlaq, Ahmed Alghamdi, Yazeed Almukhlifi, Sultan A. Alotaibi, Jaber Alyami

PMC · DOI: 10.3390/diagnostics16060881 · Diagnostics · 2026-03-16

## TL;DR

Photon-counting CT angiography shows high accuracy in detecting and measuring vascular stenosis, especially for coronary arteries, outperforming traditional CT methods.

## Contribution

This study systematically evaluates and quantifies the diagnostic accuracy of photon-counting CT angiography for vascular stenosis detection.

## Key findings

- Photon-counting CT (PCD-CT) demonstrated 96.1% pooled sensitivity and 87.5% specificity for detecting coronary stenosis.
- PCD-CT outperformed conventional CT in specificity and positive predictive value for coronary artery stenosis.
- PCD-CT reclassified stenosis severity in up to 49% of patients due to improved quantification accuracy.

## Abstract

Objective: To evaluate the performance of photon-counting detector CT (PCD-CT) angiography for the detection and quantification of vascular stenosis. Methods: Web of Science, PubMed, and Cochrane databases were searched from January 1980 to December 2025 to identify studies assessing PCD-CT angiography for the detection and quantification of vascular stenosis, using invasive angiography as the reference standard. The risk of bias of the included studies was assessed using the Quality Assessment of Diagnostic Accuracy Studies-2 (QUADAS-2) tool. Diagnostic performance metrics, including sensitivity and specificity and quantification values, were extracted from the included studies and a formal narrative synthesis was performed. The meta-analysis included studies reporting true-positive, false-positive, true-negative, and false-negative data. A meta-analysis was conducted only when a minimum of two eligible studies assessed diagnostic performance within the given vascular territory. Statistical analyses were performed using R software (v4.5.0), applying a random-effects model for the meta-analysis. Results: Of 415 identified studies, 20 were included in the systematic review, comprising a total of 9165 participants, with the majority (17/20, 85%) focusing on coronary artery stenosis. In the meta-analysis of three studies, ultra-high-resolution (UHR) PCD-CT demonstrated excellent diagnostic performance for detecting coronary stenosis for patients with ≥50%, having a pooled sensitivity of 96.1% (95% confidence level (CI): 89.3–99.6), specificity of 87.5% (95% CI: 78.2–93.3), positive predictive value (PPV) of 91.9% (95% CI: 70.3–98.2), and negative predictive value (NPV) of 94.8% (95% CI: 86.0–98.6). Compared with conventional energy-integrating detector CT (EID-CT), PCD-CT consistently showed superior diagnostic performance, particularly in the specificity and PPV. In terms of stenosis quantification, PCD-CT showed closer agreement with reference standards than EID-CT, leading to the reclassification of coronary stenosis severity in up to 49% of patients. Evidence for non-coronary vascular territories, including intracranial and peripheral arteries remains limited but suggests promising diagnostic performance. For lower-limb arterial stenosis, the reported sensitivity was 77.4–91%, and specificity was 72.1–91%. For intracranial in-stent stenosis, PCD-CT demonstrated a sensitivity of 100% and a specificity of 89%. Conclusions: PCD-CT angiography provides high diagnostic performance and improved stenosis quantification for coronary artery stenosis. UHR PCD-CT has excellent diagnostic performance for detecting coronary stenosis and consistently outperforms conventional EID-CT, especially in the specificity and positive predictive value.

## Full-text entities

- **Diseases:** Vascular Stenosis (MESH:D003251), arterial stenosis (MESH:D012078), coronary artery stenosis (MESH:D023921)
- **Species:** Homo sapiens (human, species) [taxon 9606]

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## References

76 references — full list in the complete paper: https://tomesphere.com/paper/PMC13024787/full.md

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Source: https://tomesphere.com/paper/PMC13024787