Team studies CT image features for lung adenocarcinoma prognostication

Monday, November 27 | 3:40 p.m.-3:50 p.m. | M7-SSCH04-5 | Room E352

Deep learning-based analysis of morphological and histopathological features on CT can successfully predict survival in lung adenocarcinomas, according to this retrospective dual-institution study.

Taehee Lee of Seoul National University Hospital in Seoul, South Korea, and colleagues developed and validated CT-based deep-learning models for simultaneously predicting five morphological and histopathological features using preoperative chest CT scans from patients with resected lung adenocarcinomas. In testing, they found that the resulting CT-based prognostic score successfully predicted survival. 

"Collective CT-based deep learning of morphological and histopathological features successfully predicted lung adenocarcinoma prognosis, facilitating the selection of surgical modalities and identification of neoadjuvant therapy candidates," the researchers wrote.

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