{"title":"Development and validation of the SYSU-score for MRI-based transmural healing assessment in Crohn's disease: a dual-center study.","authors":"Qingzhu Zheng, Qiaochu Zhao, Weitao He, Lili Huang, Xiaodi Shen, Luyao Wu, Yaoqi Ke, Weikai Zheng, Yangdi Wang, Yujun Chen, Ren Mao, Zhenpeng Peng, Shi-Ting Feng, Ruonan Zhang, Xuehua Li","doi":"10.1007/s00330-026-12701-6","DOIUrl":null,"url":null,"abstract":"<p><strong>Objectives: </strong>Standardizing magnetic resonance enterography (MRE)-defined transmural healing (TH) remains challenging in Crohn's disease (CD) despite its prognostic superiority. We aimed to evaluate seven conventional MRE-defined TH criteria and develop a machine-learning-optimized model for improved TH assessment.</p><p><strong>Materials and methods: </strong>In this double-center study, 467 active CD patients with 1263 MRE scans were stratified into three cohorts. Cohort 1 (n = 341) enabled retrospectively dual-metric comparison (attainment rate/prognostic protection) of seven MRE-defined TH criteria. Leveraging their strengths, we developed five machine-learning models for TH assessment to identify the optimal one. Semi-external validation was performed in prospective Ustekinumab (n = 92) and Upadacitinib (n = 34) cohorts.</p><p><strong>Results: </strong>Among seven conventional TH criteria, magnetic resonance index of activity (MaRIA), C-score, and simplified MaRIA (sMaRIA) demonstrated higher attainment rates (23.75%/28.74%/41.64%) and lower disease progression rates (14.81%/18.37%/25.35%). Random forest (RF) model showed the most favorable overall performance across cohorts: Cohort 1 (AUC, 0.82 vs. 0.71-0.81), Ustekinumab (AUC, 0.83 vs. 0.73-0.81), and Upadacitinib (AUC, 0.80 vs. 0.58-0.80) cohorts. Dual-metric evaluation identified the RF model and C-score as clinically applicable tools. Notably, the RF model (namely SYSU-score) was more strongly associated with lower progression risk than C-score: in the Ustekinumab cohort, SYSU-score-defined TH showed lower disease progression risk (HR = 0.07, p < 0.001) than C-score (HR = 0.15, p < 0.001); Upadacitinib cohort validated SYSU-score as the only system significantly associated with lower progression risk (HR = 0.20, p < 0.05).</p><p><strong>Conclusions: </strong>We established a validated machine-learning-derived TH criterion integrating the strengths of conventional MRE-defined systems. SYSU-score-defined TH status was associated with lower progression risk with robust prognostic discrimination, advancing standardized TH assessment for clinical implementation.</p><p><strong>Key points: </strong>Question Among available MRI-based transmural healing (TH) criteria for Crohn's disease (CD), which are the most clinically applicable, and can a new model improve standardized prognostic assessment? Findings MaRIA, C-score, and sMaRIA showed relatively favorable clinical applicability, and the machine-learning-derived SYSU-score demonstrated robust prognostic performance in internal and semi-external validation. Clinical relevance SYSU-score may support more standardized MRI-based assessment of TH and improve risk stratification for disease progression in patients with CD.</p>","PeriodicalId":12076,"journal":{"name":"European Radiology","volume":" ","pages":"8465-8478"},"PeriodicalIF":6.0000,"publicationDate":"2026-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"European Radiology","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1007/s00330-026-12701-6","RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2026/6/19 0:00:00","PubModel":"Epub","JCR":"Q1","JCRName":"RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING","Score":null,"Total":0}
引用次数: 0
Abstract
Objectives: Standardizing magnetic resonance enterography (MRE)-defined transmural healing (TH) remains challenging in Crohn's disease (CD) despite its prognostic superiority. We aimed to evaluate seven conventional MRE-defined TH criteria and develop a machine-learning-optimized model for improved TH assessment.
Materials and methods: In this double-center study, 467 active CD patients with 1263 MRE scans were stratified into three cohorts. Cohort 1 (n = 341) enabled retrospectively dual-metric comparison (attainment rate/prognostic protection) of seven MRE-defined TH criteria. Leveraging their strengths, we developed five machine-learning models for TH assessment to identify the optimal one. Semi-external validation was performed in prospective Ustekinumab (n = 92) and Upadacitinib (n = 34) cohorts.
Results: Among seven conventional TH criteria, magnetic resonance index of activity (MaRIA), C-score, and simplified MaRIA (sMaRIA) demonstrated higher attainment rates (23.75%/28.74%/41.64%) and lower disease progression rates (14.81%/18.37%/25.35%). Random forest (RF) model showed the most favorable overall performance across cohorts: Cohort 1 (AUC, 0.82 vs. 0.71-0.81), Ustekinumab (AUC, 0.83 vs. 0.73-0.81), and Upadacitinib (AUC, 0.80 vs. 0.58-0.80) cohorts. Dual-metric evaluation identified the RF model and C-score as clinically applicable tools. Notably, the RF model (namely SYSU-score) was more strongly associated with lower progression risk than C-score: in the Ustekinumab cohort, SYSU-score-defined TH showed lower disease progression risk (HR = 0.07, p < 0.001) than C-score (HR = 0.15, p < 0.001); Upadacitinib cohort validated SYSU-score as the only system significantly associated with lower progression risk (HR = 0.20, p < 0.05).
Conclusions: We established a validated machine-learning-derived TH criterion integrating the strengths of conventional MRE-defined systems. SYSU-score-defined TH status was associated with lower progression risk with robust prognostic discrimination, advancing standardized TH assessment for clinical implementation.
Key points: Question Among available MRI-based transmural healing (TH) criteria for Crohn's disease (CD), which are the most clinically applicable, and can a new model improve standardized prognostic assessment? Findings MaRIA, C-score, and sMaRIA showed relatively favorable clinical applicability, and the machine-learning-derived SYSU-score demonstrated robust prognostic performance in internal and semi-external validation. Clinical relevance SYSU-score may support more standardized MRI-based assessment of TH and improve risk stratification for disease progression in patients with CD.
期刊介绍:
European Radiology (ER) continuously updates scientific knowledge in radiology by publication of strong original articles and state-of-the-art reviews written by leading radiologists. A well balanced combination of review articles, original papers, short communications from European radiological congresses and information on society matters makes ER an indispensable source for current information in this field.
This is the Journal of the European Society of Radiology, and the official journal of a number of societies.
From 2004-2008 supplements to European Radiology were published under its companion, European Radiology Supplements, ISSN 1613-3749.