Characterization of Intratumoral Heterogeneity via MRI-Based Radiomic Habitats in Osteosarcoma.
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BACKGROUND: Accurate risk stratification for osteosarcoma is hindered by intratumoral heterogeneity. Conventional radiomics often treats tumors as homogeneous entities, overlooking spatial subregions and limiting prognostic accuracy. PURPOSE: To evaluate the prognostic value of an MRI-based radiomic habitat approach-partitioning the tumor into biologically distinct subregions-for post-treatment recurrence in osteosarcoma, comparing its performance with conventional whole-tumor analysis. STUDY TYPE: Retrospective cohort study. POPULATION: Eighty-eight osteosarcoma patients (including 56 males, 63.6%) and a temporal independent validation cohort of 80 sarcoma patients (including 52 males, 65%). FIELD STRENGTH/SEQUENCE: 3.0 T; T1-weighted spin-echo (SE), T2-weighted fast spin-echo (FSE), and contrast-enhanced T1-weighted (CE-T1WI) spin-echo sequences. ASSESSMENT: Tumors segmented on pre-treatment images were partitioned into four habitats using k-means clustering. Support Vector Machine (SVM) models were developed using features from habitats versus the entire tumor to predict 1-year recurrence. Unsupervised clustering identified prognostic subtypes. STATISTICAL TESTS: The DeLong test was used to compare Area Under the Curve (AUC) values. Kaplan-Meier survival analysis (Log-rank test) and Chi-square tests were employed for prognostic stratification. A p-value < 0.05 was considered statistically significant. RESULTS: The habitat-SVM model achieved the best performance, with an AUC of 0.839 (95% CI: 0.759-0.929) in the training cohort and 0.815 (95% CI: 0.782-0.999) in the temporal independent validation cohort. This performance was significantly superior to the best conventional model (AUC = 0.803). Unsupervised analysis identified four radiomic subtypes with significantly distinct recurrence rates (7.7%-76.7%) and disease-free survival outcomes. DATA CONCLUSION: MRI-based radiomic habitat analysis may help to characterize intratumoral heterogeneity in osteosarcoma, providing superior risk stratification for post-treatment recurrence. This non-invasive strategy offers a promising tool for individualized prognostic assessment. Limitations include the single-center design and small sample size. EVIDENCE LEVEL: 3. TECHNICAL EFFICACY: Stage 2.