Deciphering 18F-DOPA uptake in SDH-related head and neck paragangliomas: a radiomics approach.

Abstract

Purpose: To investigate the influence of germline succinate dehydrogenase (SDHx) pathogenic variants on 6-[¹⁸F]-fluoro-3,4-dihydroxyphenylalanine (¹⁸F-DOPA) Positron Emission Tomography (PET) radiomic signature of head and neck paragangliomas (HNPGLs).

Methods: Forty-seven patients (20 SDH pathogenic variants carriers) harboring 55 HNPGLs were retrospectively included. HNPGLs were delineated using Nestle adaptive threshold. 128 radiomic features were extracted and harmonized to correct for batch effects. Principal Component Analysis (PCA) was performed to remove redundancy and avoid collinearity. The most representative feature of each component was tested with multivariate stepwise logistic binary regression analysis (LBRA) to identify variables predictive of genetic status.

Results: ¹⁸F-DOPA Positron Emission Tomography/Computed Tomography (PET/CT) detected 28/29 carotid body HNPGLs, 23/23 jugulotympanic HNPGLs, and 4/4 vagal HNPGLs. SUVmax was significantly higher in SDH-related HNPGLs (p = 0.003). PCA allowed identification of 4 Components. The most representative variables of Component 1 and 2 (including intensity and intensity-related textural features, and not intensity-related textural features, respectively) were Intensity-based (IB)-SUVmedian and Grey Level Run Length Matrix-Long Run Low Gray Level Emphasis (GLRLM-LRLGLE). SDHx HNPGLs exhibited higher activity scores and more homogeneous texture. At patient level, SDHx cases showed significantly higher IB-SUVmedian values (p < 0.001), and lower GLRLM-LRLGLE than sporadic patients (p = 0.005). IB-SUVmedian was found to be an independent predictor of genetic status at lesion (71.0%) and patient level (77.8%).

Conclusion: The present study pioneers the application of ¹⁸F-DOPA PET radiomics for HNPGLs, suggesting the influence of germline SDH pathogenic variants on ¹⁸F-FDOPA uptake intensity and textural heterogeneity. Integrating radiomics with genetic data provides new insights into the correlation between PET features and underlying molecular dysregulation.