Radiogenomic markers enable risk stratification and inference of mutational pathway states in head and neck cancer

• Authors: SPIELVOGEL Clemens P; STOIBER Stefan; PAPP Laszlo; KRAJNC Denis; GRAHOVAC Marko; GURNHOFER Elisabeth; TRACHTOVÁ Karolína; BYSTRÝ Vojtěch; LEISSER Asha; JANK Bernhard; SCHNOELL Julia; KADLETZ Lorenz; HEIDUSCHKA Gregor; BEYER Thomas; HACKER Marcus; KENNER Lukas; HAUG Alexander R
• Year of publication: 2023
• Type: Article in Periodical
• Magazine / Source: European Journal of Nuclear Medicine and Molecular Imaging
• MU Faculty or unit: Central European Institute of Technology
• Web: https://link.springer.com/article/10.1007/s00259-022-05973-9
• Doi: http://dx.doi.org/10.1007/s00259-022-05973-9
• Keywords: Head and neck cancer; Biomarkers; Radiomics; Machine learning; Artificial intelligence; Cancer genomics
• Description: Purpose Head and neck squamous cell carcinomas (HNSCCs) are a molecularly, histologically, and clinically heterogeneous set of tumors originating from the mucosal epithelium of the oral cavity, pharynx, and larynx. This heterogeneous nature of HNSCC is one of the main contributing factors to the lack of prognostic markers for personalized treatment. The aim of this study was to develop and identify multi-omics markers capable of improved risk stratification in this highly heterogeneous patient population.