Prognostic generalization of multi‐level CT‐dose fusion dosiomics from primary tumor and lymph node in nasopharyngeal carcinoma

摘要

Abstract Purpose To investigate the prognostic performance of multi‐level computed tomography (CT)‐dose fusion dosiomics at the image‐, matrix‐, and feature‐levels from the gross tumor volume (GTV) at nasopharynx and the involved lymph node for nasopharyngeal carcinoma (NPC) patients. Methods Two hundred and nineteen NPC patients (175 vs. 44 for training vs. internal validation) were used to train prediction model, and 32 NPC patients were used for external validation. We first extracted CT and dose information from intratumoral nasopharynx (GTV_nx) and lymph node (GTV_nd) regions. Then, the corresponding peritumoral regions (RING_3?mm and RING_5?mm) were also considered. Thus, the individual and combination of intratumoral and peritumoral regions were as follows: GTV_nx, GTV_nd, RING_3?mm_nx, RING_3?mm_nd, RING_5?mm_nx, RING_5?mm_nd, GTV_nxnd, RING_3?mm_nxnd, RING_5?mm_nxnd, GTV?+?RING_3?mm_nxnd, and GTV?+?RING_5?mm_nxnd. For each region, 11 models were built by combining five clinical parameters and 127 features from: (1) dose images alone; (2–7) fused dose and CT images via wavelet‐based fusion using CT weights of 0.2, 0.4, 0.6, and 0.8, gradient transfer fusion, and guided‐filtering‐based fusion (GFF); (8) fused matrices (sumMat); (9–10) fused features derived via feature averaging (avgFea) and feature concatenation (conFea); and finally, (11) CT images alone. The concordance index (C‐index) and Kaplan–Meier curves with log‐rank test were used to assess model performance. Results The fusion models’ performance was better than single CT/dose model on both internal and external validation. Models that combined the information from both GTV_nx and GTV_nd regions outperformed the single region model. For internal validation, GTV?+?RING_3?mm_nxnd GFF model achieved the highest C‐index both in recurrence‐free survival (RFS) and metastasis‐free survival (MFS) predictions (RFS: 0.822; MFS: 0.786). The highest C‐index in external validation set was achieved by RING_3?mm_nxnd model (RFS: 0.762; MFS: 0.719). The GTV?+?RING_3?mm_nxnd GFF model is able to significantly separate patients into high‐risk and low‐risk groups compared to dose‐only or CT‐only models. Conclusion Fusion dosiomics model combining the primary tumor, the involved lymph node, and 3?mm peritumoral information outperformed single‐modality models for different outcome predictions, which is helpful for clinical decision‐making and the development of personalized treatment.