Comparative analysis shows habitat assessment enhances risk stratification for nasopharyngeal carcinoma, indicating improved survival predictions.
Habitat analysis enables spatial characterization of intratumoral heterogeneity; however, its application in nasopharyngeal carcinoma (NPC), particularly regarding metastatic lymph node (MLN), remains limited. This study aims to systematically compare the prognostic performance of various models using different sequences and spatial region combinations for predicting overall survival in NPC. The study retrospectively included 725 NPC patients (543 training, 182 testing). Habitat analysis was conducted based on T1, T1C, and T2 sequences in three regional strategies: primary gross tumor volume (GTVp), metastatic lymph nodes (MLNs), and the combined region of GTVp-MLN. The tumor area was divided into six subregions, and a multi-region spatial interaction (MSI) matrix was constructed to extract MSI features. On this basis, a radiomics model (R Model) and a clinical–radiomics model (CR Model) were established, and the model performance was evaluated using C-index and Kaplan–Meier survival analysis. The results show that the combined GTVp-MLN model based on the T1 sequence achieved the best overall predictive performance (R Model: C-index = 0.693; CR Model: C-index = 0.722). Significant survival differences were observed between the high- and low-risk groups. These findings suggest that habitat analysis incorporating the combined GTVp–MLN region may improve prognostic prediction and risk stratification in patients with NPC.
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Huang et al. (2026) studied this question.
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