Artificial intelligence-integrated multimodal data-assisted magnetic resonance imaging for neoadjuvant chemoradiotherapy decision-making in cT1-2N0 rectal cancer

Figure 1 Patient selection flowchart. dMMR: DNA mismatch repair; MRI: Magnetic resonance imaging; MSI-H: Microsatellite instability-high.

Figure 2 Schematic of Clinical, Hematologic, Oncopathologic, and Radiomic Decision machine-learning model construction and validation. A-C: They delineate the high-throughput radiomics feature extraction pipeline embedded within the Clinical, Hematologic, Oncopathologic, and Radiomic Decision framework; D: It illustrates the rigorous preprocessing of multidimensional clinical variables; E: It summarizes the comparative benchmarking of candidate models and the subsequent SHapley Additive exPlanations-driven post-hoc interpretability analysis. AUC: Area under the curve; DWI: Diffusion weighted imaging; GBM: Gradient boosting machine; KNN: K-nearest neighbors; LASSO: Least absolute shrinkage and selection operator; ROC: Receiver operating characteristic; ROI: Regions of interest; SVM: Support vector machine; 3D: Three-dimensional.

Figure 3 Performance evaluation of the radiomics machine-learning model in internal validation and of the Clinical, Hematologic, Oncopathologic, and Radiomic Decision model in both internal and external validation. A-C: They display receiver operating characteristic curves; D-F: They show confusion matrices; G-I: They present calibration plots; J-L: Thet depict decision-curve analyses. AUC: Area under the curve; GBM: Gradient boosting machine; KNN: K-nearest neighbors; ROC: Receiver operating characteristic; SVM: Support vector machine.

Figure 4 SHapley Additive exPlanations interpretation of the XGBoost model. A: SHapley Additive exPlanations (SHAP) summary bar plot; B: SHAP summary bee-swarm plot; C: SHAP force plot for individual explanation; D and E: SHAP waterfall plots for individual explanation; F: SHAP partial dependence plot for serum triglycerides and Eastern Cooperative Oncology Group performance score; G: SHAP partial dependence plot for serum triglycerides and serum potassium. ALT: Alanine aminotransferase; ECOG: Eastern Cooperative Oncology Group; SHAP: SHapley Additive exPlanations.

Figure 5 Individual prediction and analysis of patient No. 112 using the Clinical, Hematologic, Oncopathologic, and Radiomic Decision Model. A: Axial section of the patient’s T2-weighted (T2W) magnetic resonance imaging (MRI) image; B: Coronal section of the patient’s T2W MRI image; C: Sagittal section of the patient’s T2W MRI image; D: The patient’s diffusion weighted imaging MRI image; E: Axial section of the patient’s T2W MRI image with radiologist’s segmentation; F: Coronal section of the patient’s T2W MRI image with radiologist’s segmentation; G: Sagittal section of the patients T2W MRI image with radiologist’s segmentation; H: The patient’s diffusion weighted imaging MRI image with radiologist’s segmentation; I: Web deployment of the Clinical, Hematologic, Oncopathologic, and Radiomic Decision model and individual prediction results; J: Bar chart of decisions made by Clinical, Hematologic, Oncopathologic, and Radiomic Decision and other machine-learning models; K: Bar chart of SHapley Additive exPlanations contributions of the patient’s features. CHORD: Clinical, Hematologic, Oncopathologic, and Radiomic Decision; ECOG: Eastern Cooperative Oncology Group; GBM: Gradient boosting machine; KNN: K-nearest neighbors; SHAP: SHapley Additive exPlanations; SVM: Support vector machine.