Wang ZD, Nan HJ, Li SX, Li LH, Liu ZC, Guo HH, Li L, Liu SY, Li H, Bai YL, Dang XW. Development and validation of a radiomics-based prediction model for variceal bleeding in patients with Budd-Chiari syndrome-related gastroesophageal varices. World J Gastroenterol 2025; 31(19): 104563 [PMID: 40497088 DOI: 10.3748/wjg.v31.i19.104563]
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08339959
Submitted on:
May 31, 2025, 06:08
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Reader Comments:
This study by Wang et al. presents a compelling advancement in the noninvasive prediction of variceal bleeding risk in Budd-Chiari syndrome (BCS) patients using a combined radiomics and clinical model (R+C model). The integration of high-dimensional radiomics features with clinical parameters to stratify bleeding risk is both innovative and clinically relevant. The authors should be commended for conducting a multicenter study with an external validation cohort, which strengthens the generalizability of their findings.
Strengths of the Study:
Innovative Use of Radiomics: The application of radiomics in BCS—a relatively rare and under-studied condition—represents a novel contribution. The extraction of hepatic and splenic texture features from CT images enhances the predictive capability beyond conventional clinical models.
Robust Methodology: The use of LASSO Cox regression for feature selection and validation of the model using an external cohort adds credibility. The model’s performance metrics, such as the C-index (0.906 for training and 0.859 for validation), demonstrate excellent discriminative ability.
Clinical Utility: The development of an accessible online tool for individualized risk prediction (https://bcsvh.shinyapps.io/BCS_Variceal_Bleeding_Risk_Tool/) is a practical step towards clinical translation, potentially aiding in decision-making for prophylactic interventions.
Risk Stratification: The ability to categorize patients into low-, medium-, and high-risk groups offers a framework for personalized management strategies, which could reduce unnecessary interventions in low-risk patients and prioritize high-risk individuals for aggressive preventive therapies.
Limitations and Areas for Improvement:
Retrospective Design: As with all retrospective studies, the potential for selection bias and unmeasured confounding exists. Prospective validation in diverse populations, including Western cohorts where thrombophilic etiologies of BCS predominate, is necessary.
Limited Radiomics Scope: The use of single-slice regions of interest (ROIs) for liver and spleen may not capture the full heterogeneity of these organs. A volumetric or multi-slice approach could improve robustness.
Generalizability: The study population is entirely Chinese, with BCS cases predominantly due to membranous obstruction—an etiology not common in other geographic regions. Thus, external validation in populations with differing BCS etiologies is crucial.
Anticoagulation Risk Interpretation: While anticoagulation was found to be an independent risk factor for bleeding, the model does not differentiate between anticoagulant types or dosing strategies. Given the importance of anticoagulation in BCS, further work is needed to clarify safe therapeutic windows.
Manual Segmentation: The reliance on manual ROI delineation is resource-intensive and may limit scalability. Incorporating semi-automated or AI-driven segmentation could enhance reproducibility and feasibility in routine clinical settings
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