Imaging-Based Prediction of Molecular Therapy Targets in NSCLC by Radiogenomics and AI Approaches: A Systematic Review.

ABSTRACT: The objective of this systematic review was to analyze the current state of the art of imaging-derived biomarkers predictive of genetic alterations and immunotherapy targets in lung cancer. We included original research studies reporting the development and validation of imaging feature-based models. The overall quality, the standard of reporting and the advancements towards clinical practice were assessed. Eighteen out of the 24 selected articles were classified as "high-quality" studies according to the Quality Assessment of Diagnostic Accuracy Studies 2 (QUADAS-2). The 18 "high-quality papers" adhered to Transparent Reporting of a multivariable prediction model for Individual Prognosis or Diagnosis (TRIPOD) with a mean of 62.9%. The majority of "high-quality" studies (16/18) were classi

SUBMITTER: Ninatti G 

PROVIDER: S-EPMC7345054 | biostudies-literature | 2020 May

REPOSITORIES: biostudies-literature