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The feasibility of MRI-based radiomics model in presurgical evaluation of tumor budding in locally advanced rectal cancer
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The feasibility of MRI-based radiomics model in presurgical evaluation of tumor budding in locally advanced rectal cancer
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The feasibility of MRI-based radiomics model in presurgical evaluation of tumor budding in locally advanced rectal cancer
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Journal Article
The feasibility of MRI-based radiomics model in presurgical evaluation of tumor budding in locally advanced rectal cancer
2022
Overview
PurposeTo build and validate a magnetic resonance imaging-based radiomics model to preoperatively evaluate tumor budding (TB) in locally advanced rectal cancer (LARC).MethodsPathologically confirmed LARC cases submitted to preoperative rectal MRI in two distinct hospitals were enrolled in this retrospective study and assigned to cohort 1 (training set, n = 77; test set, n = 51) and cohort 2 (validation set, n = 96). Radiomics features were obtained from multiple sequences, comprising high-resolution T2, contrast-enhanced T1, and diffusion-weighted imaging (T2WI, CE-T1WI, and DWI, respectively). The least absolute shrinkage and selection operator (LASSO) was utilized to select the optimal features from T2WI, CE-T1WI, DWI, and the combination of multi-sequences, respectively. A support vector machine (SVM) classifier was utilized to construct various radiomics models for discriminating the TB grades. Receiver operating characteristic curve analysis and decision curve analysis (DCA) were carried out to determine the diagnostic value.ResultsFive optimal features associated with TB grade were determined from combined multi-sequence data. Accordingly, a radiomics model based on combined multi-sequences had an area under the curve of 0.796, with an accuracy of 81.2% in the validation set, showing a better performance in comparison with other models in both cohorts (p < 0.05). DCA exhibited a clinical benefit for this radiomics model.ConclusionThe novel MRI-based radiomics model combining multiple sequences is an effective and non-invasive approach for evaluating TB grade preoperatively in patients with LARC.
Publisher
Springer Nature B.V
Subject
