Clustering of dosimetric profiles reveals distinct local control probabilities after SABR in oligometastatic head and neck cancer: insights from the OMET phase II trial quality assurance Process

Abstract

Background: Stereotactic ablative radiotherapy (SABR) is increasingly used in the management of oligometastatic disease. However, variability in SABR plans raises questions about their impact on local control at SABR-treated lesions (LC). We aimed to explore whether quantitative dosimetric parameters could predict LC in head and neck squamous cell carcinoma (HNSCC) patients in the OMET (GORTEC 2014-04) trial.

Methods: OMET is a multicentre randomized phase II trial comparing SABR-alone versus chemo-SABR in patients with ≤ 3 PET-confirmed oligometastases. A post-hoc analysis of all irradiated lesions (N = 98) from 69 patients was performed. Twenty spatial and dosimetric indices, together with conventional metrics including Dmin, Dmean, Dmax, total target volume and homogeneity/conformity indices, were extracted from the DICOM files. Hierarchical clustering was used to identify phenotypes of plan quality. Kaplan-Meier analyses evaluated associations with LC.

Results: Wide inter-patient variability in dosimetric parameters and three clusters was observed, despite SABR standardization per trial protocol. The cluster of lesions (N = 13) with high intra-tumoral dose heterogeneity and non-optimal conformity was associated with significantly improved LC. In contrast, a more homogeneous and conformal phenotype was linked to inferior LC (N = 14). The largest cluster (N = 69) showed no clearly distinctive pattern and had intermediate LC.

Conclusions: In SABR for oligometastatic HNSCC, intra-tumoral dose heterogeneity may be more predictive of LC than strict conformity, particularly in high-dose per fraction regimens. A quantitative, phenotype-based machine learning approach using unsupervised clustering of composite dosimetric metrics may be explored further within SABR quality assurance frameworks beyond binary expert review alone.

Keywords: Clustering; Dosimetric predictors; Head and neck neoplasms; Local tumor control; Oligometastatic disease; Radiotherapy quality assurance; Stereotactic ablative radiotherapy (SABR)/ Stereotactic body radiotherapy (SBRT).