Explainable machine learning via intra-tumoral radiomics feature mapping for patient stratification in adjuvant chemotherapy for locoregionally advanced nasopharyngeal carcinoma

Xinzhi Teng, Jiang Zhang, Xinyang Han, Jiachen Sun, Sai Kit Lam, Qi Yong Hemis Ai, Zongrui Ma, Francis Kar Ho Lee, Kwok Hung Au, Celia Wai Yi Yip, James Chung Hang Chow, Victor Ho Fun Lee, Jing Cai

Research output: Journal article publicationJournal articleAcademic researchpeer-review

3 Citations (Scopus)

Abstract

Purpose: This study aimed to discover intra-tumor heterogeneity signature and validate its predictive value for adjuvant chemotherapy (ACT) following concurrent chemoradiotherapy (CCRT) in locoregionally advanced nasopharyngeal carcinoma (LA-NPC). Materials and methods: 397 LA-NPC patients were retrospectively enrolled. Pre-treatment contrast-enhanced T1-weighted (CET1-w) MR images, clinical variables, and follow-up were retrospectively collected. We identified single predictive radiomic feature from primary gross tumor volume (GTVnp) and defined predicted subvolume by calculating voxel-wised feature mapping and within GTVnp. We independently validate predictive value of identified feature and associated predicted subvolume. Results: Only one radiomic feature, gldm_DependenceVariance in 3 mm-sigma LoG-filtered image, was discovered as a signature. In the high-risk group determined by the signature, patients received CCRT + ACT achieved 3-year disease free survival (DFS) rate of 90% versus 57% (HR, 0.20; 95%CI, 0.05–0.94; P = 0.007) for CCRT alone. The multivariate analysis showed patients receiving CCRT + ACT had a HR of 0.21 (95%CI: 0.06–0.68, P = 0.009) for DFS compared to those receiving CCRT alone. The predictive value can also be generalized to the subvolume with multivariate HR of 0.27 (P = 0.017) for DFS. Conclusion: The signature with its heterogeneity mapping could be a reliable and explainable ACT decision-making tool in clinical practice.

Original languageEnglish
JournalRadiologia Medica
DOIs
Publication statusAccepted/In press - 2023

Keywords

  • Adjuvant chemotherapy
  • NPC
  • Radiomics
  • Tumor heterogeneity map

ASJC Scopus subject areas

  • Radiology Nuclear Medicine and imaging

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