ESTRO 2024 - Abstract Book

S1360

Clinical - Head & neck

ESTRO 2024

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Digital Poster

Deep learning prediction model for CVA in patient with NPC after completing CCRT

JENG YOU WU 1,2 , Min-Huei Hsu 3,4 , Chia-Yu Emily Su 2,5

1 Wan Fang Hospital, Department of Radiation Oncology, Taipei, Taiwan. 2 Taipei Medical University, Graduate Institute of Biomedical Informatics, Taipei, Taiwan. 3 Taipei Medical University, Graduate Institute of Data Science, Taipei, Taiwan. 4 Shuang Ho Hospital, Department of Neurosurgery, Taipei, Taiwan. 5 Taipei Medical University Hospital, Clinical Big Data Research Center, Taipei, Taiwan

Purpose/Objective:

A multicenter real-world study was conducted to investigate the survivorship of nasopharyngeal carcinoma (NPC) patients. The incidence of cerebrovascular accidents (CVA) in NPC patients was higher than in the general population. Consequently, deep learning was utilized to further predict the occurrence of CVA in these patients after receiving concurrent chemoradiotherapy (CCRT). The aim was also to compare their predictive efficiency, between different models.

Material/Methods:

Between 2002 and 2019, Taipei Medical University Hospital, Shuang-Ho Hospital, and Wan-Fang Hospital treated a total of 976 patients diagnosed with nasopharyngeal carcinoma. Out of these, 504 patients were newly diagnosed with NPC and underwent treatment with concurrent chemoradiotherapy.