AI developed for PET/CT lung cancer imaging

A group led by Dr. Hongyue Zhao from The First Affiliated Hospital of Harbin Medical University in Harbin, China, trained a deep-learning model on 189 preoperative F-18 FDG-PET/CT images from patients with non-small cell lung cancer (NSCLC). In testing, the model performed well in distinguishing between the two most common forms of NSCLC: lung adenocarcinoma (ADC) and lung squamous cell carcinoma (SqCC).

“In many cases, doctors must make subjective judgments on the pathological subtypes of NSCLC by combining laboratory markers and imaging findings,” the authors wrote. “Consequently,…