Predicting Non-Small-Cell Lung Cancer Survival after Curative Surgery via Deep Learning of Diffusion MRI.

ABSTRACT:

Background

the objective of this study is to evaluate the predictive power of the survival model using deep learning of diffusion-weighted images (DWI) in patients with non-small-cell lung cancer (NSCLC).

Methods

DWI at b-values of 0, 100, and 700 sec/mm² (DWI₀, DWI₁₀₀, DWI₇₀₀) were preoperatively obtained for 100 NSCLC patients who underwent curative surgery (57 men, 43 women; mean age, 62 years). The ADC_0-100 (perfusion-sensitive ADC), ADC_100-700 (perfusion-insensitive ADC), ADC_0-100-700, and demographic features were collected as input data and 5-year survival was collected as output data. Our survival model adopted transfer learning from a pre-trained VGG-16 network, whereby the softmax layer wa

SUBMITTER: Moon JW 

PROVIDER: S-EPMC10417371 | biostudies-literature | 2023 Aug

REPOSITORIES: biostudies-literature