[68Ga]DOTATOC PET-derived radiomics to predict genetic background of head and neck paragangliomas: a pilot investigation.

Abstract

To investigate the [68Ga]DOTATOC PET radiomic profile of head and neck paragangliomas (HNPGLs) and identify radiomic characteristics useful as predictors of succinate dehydrogenase genes (SDHx) pathogenic variants. Sporadic and SDHx HNPGL patients, who underwent [68Ga]DOTATOC PET/CT, were retrospectively included. HNPGLs were analyzed using LIFEx software, and extracted features were harmonized to correct for batch effects and confronted testing for multiple comparison. Stepwise discriminant analysis was conducted to remove redundancy and identify best discriminating features. ROC analysis was used to define optimal cut-offs. Multivariate decision-tree analysis was performed using CHAID method. 34 patients harboring 60 HNPGLs (51 SDHx in 25 patients) were included. Three sporadic and nine SDHx HNPGLs were metastatic. At stepwise discriminant analysis, both GLSZM-Zone Size Non-Uniformity (ZSNU, reflecting tumor heterogeneity) and IB-TLSRE (total lesion somatostatin receptor expression) were independent predictors of genetic status, with 96.4% of lesions and 91.6% of patients correctly classified after cross validation (p < 0.001). Among non-metastatic patients, GLSZM-ZSNU and IB-TLSRE were significantly higher in sporadic than SDHx HNPGLs (p < 0.001). No differences were revealed in metastatic patients. Decision-tree analysis highlights multifocality and IB-TLSRE as useful variables, correctly identifying 6/9 sporadic and 24/25 SDHx patients. Model failed to classify one SDHA and three sporadic patients (2 metastatic). Radiomics features GLSZM-ZSNU and IB-TLSRE appear to reflect HNPGLs SDHx status and tumor behavior (metastatic vs. non-metastatic). If validated, especially IB-TLSRE might represent a simple and time-efficient radiomic index for SDHx variants early screening and prediction of tumor behavior in HNPGL cases.