Objectives To assess the methodological quality of radiomics research for ruptured intracranial aneurysms (IAs) using the radiomics quality score (RQS) and METhodological radiomICs score (METRICS), and to evaluate the transportability of reported radiomics features using an independent multi-center dataset. Materials and methods We systematically reviewed radiomics articles for ruptured IAs classification. Included articles underwent a quality assessment via RQS and METRICS. Then, the identified radiomics feature sets were evaluated in the MIRACLE Cohort, which comprises IA cases from five centers with automated segmentation and feature extraction. The internal performance was assessed for each of the validated feature sets. Results After screening 252 studies, 26 were analyzed, yielding a mean RQS of 9.7 (SD, 5.2) and a median METRICS score of 72.5% (IQR, 58.5%–76.2%). Two individual articles reached a maximum RQS of 18 and a METRICS of 84.6%, respectively. Fifteen studies were selected for transportability evaluation. In the primary transportability analysis, the AUCs ranged from 0.59 to 0.70 in the training dataset, and from 0.51 to 0.61 in the external testing dataset. The original_shape_Elongation feature was the most frequently utilized feature (9/15). When comparing radiomics features derived from manual and automatic segmentations, original_shape_VoxelVolume, MeshVolume, and SurfaceArea showed the highest stability, all achieving an intraclass correlation coefficient (ICC) > 0.9. Conclusions Radiomics studies for distinguishing ruptured IAs exhibit an evolving but heterogeneous methodology, with certain features demonstrating high stability but modest transportability. Methodological deficiencies remain, including limited external validation, suboptimal model generalizability, and insufficient adherence to open science. Future research should address these gaps to enhance study quality and clinical relevance. Trial registration MIRACLE Cohort, ChiCTR2400084601. Registered 21 May 2024, <a href="https://www.chictr.org.cn/showprojEN.html?proj=229047">https://www.chictr.org.cn/showprojEN.html?proj=229047</a>. Key Points <Emphasis Type="BoldItalic">Question</Emphasis> To evaluate the methodological quality of radiomics research for IA rupture using RQS/METRICS and assess feature transportability using independent multi-center data. <Emphasis Type="BoldItalic">Findings</Emphasis> Methodological heterogeneities persist despite field growth. Independent assessment reveals that most reported radiomics features demonstrate modest transportability, with performance dropping across different centers. <Emphasis Type="BoldItalic">Clinical relevance</Emphasis> Addressing methodological gaps, specifically insufficient external validation and limited transparency, is essential to facilitate the reliable translation of radiomics from academic research into clinical applications for aneurysm management. Graphical Abstract

Radiomics for differentiating ruptured intracranial aneurysms: overview, methodological quality evaluation using METRICS and RQS, and feature transportability validation using independent multi-center dataset

期刊论文
发表日期：

2026年4月2日

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Dongqin Zhu,
Mengmeng Xu,
Jingru Wang,
Jian Xu,
Cunke Miao,
Fei Yao,
Yunjun Yang

摘要

Objectives

To assess the methodological quality of radiomics research for ruptured intracranial aneurysms (IAs) using the radiomics quality score (RQS) and METhodological radiomICs score (METRICS), and to evaluate the transportability of reported radiomics features using an independent multi-center dataset.

Materials and methods

We systematically reviewed radiomics articles for ruptured IAs classification. Included articles underwent a quality assessment via RQS and METRICS. Then, the identified radiomics feature sets were evaluated in the MIRACLE Cohort, which comprises IA cases from five centers with automated segmentation and feature extraction. The internal performance was assessed for each of the validated feature sets.

Results

After screening 252 studies, 26 were analyzed, yielding a mean RQS of 9.7 (SD, 5.2) and a median METRICS score of 72.5% (IQR, 58.5%–76.2%). Two individual articles reached a maximum RQS of 18 and a METRICS of 84.6%, respectively. Fifteen studies were selected for transportability evaluation. In the primary transportability analysis, the AUCs ranged from 0.59 to 0.70 in the training dataset, and from 0.51 to 0.61 in the external testing dataset. The original_shape_Elongation feature was the most frequently utilized feature (9/15). When comparing radiomics features derived from manual and automatic segmentations, original_shape_VoxelVolume, MeshVolume, and SurfaceArea showed the highest stability, all achieving an intraclass correlation coefficient (ICC) > 0.9.

Conclusions

Radiomics studies for distinguishing ruptured IAs exhibit an evolving but heterogeneous methodology, with certain features demonstrating high stability but modest transportability. Methodological deficiencies remain, including limited external validation, suboptimal model generalizability, and insufficient adherence to open science. Future research should address these gaps to enhance study quality and clinical relevance.

Trial registration

MIRACLE Cohort, ChiCTR2400084601. Registered 21 May 2024, https://www.chictr.org.cn/showprojEN.html?proj=229047.

Key Points

Question To evaluate the methodological quality of radiomics research for IA rupture using RQS/METRICS and assess feature transportability using independent multi-center data.

Findings Methodological heterogeneities persist despite field growth. Independent assessment reveals that most reported radiomics features demonstrate modest transportability, with performance dropping across different centers.

Clinical relevance Addressing methodological gaps, specifically insufficient external validation and limited transparency, is essential to facilitate the reliable translation of radiomics from academic research into clinical applications for aneurysm management.

Graphical Abstract