Multi-window CT based Radiomic signatures in differentiating indolent versus aggressive lung cancers in the National Lung Screening Trial: a retrospective study.

Background: We retrospectively evaluated the capability of radiomic features to predict tumor growth in lung cancer screening and compared the performance of multi-window radiomic features and single window radiomic features.

Methods: One hundred fifty lung nodules among 114 screen-detected, incident lung cancer patients from the National Lung Screening Trial (NLST) were investigated. Volume double time (VDT) was calculated as the difference between continuous two scans and used to define indolent and aggressive lung cancers.

Semiautomated Measure of Abdominal Adiposity Using Computed Tomography Scan Analysis.

Background: The obesity epidemic has prompted the need to better understand the impact of adipose tissue on human pathophysiology. However, accurate, efficient, and replicable models of quantifying adiposity have yet to be developed and clinically implemented. We propose a novel semiautomated radiologic method of measuring the visceral fat area (VFA) using computed tomography scan analysis.

Prediction of pathological nodal involvement by CT-based Radiomic features of the primary tumor in patients with clinically node-negative peripheral lung adenocarcinomas.

Purpose: The purpose of this study was to investigate the potential of computed tomography (CT) based radiomic features of primary tumors to predict pathological nodal involvement in clinically node-negative (N0) peripheral lung adenocarcinomas.

Methods: A total of 187 patients with clinical N0 peripheral lung adenocarcinomas who underwent preoperative CT scan and subsequently received systematic lymph node dissection were retrospectively reviewed. 219 quantitative 3D radiomic features of primary lung tumor were extracted; meanwhile, nine radiological semantic features were evaluated.

Radiologic Features of Small Pulmonary Nodules and Lung Cancer Risk in the National Lung Screening Trial: A Nested Case-Control Study.

Purpose To extract radiologic features from small pulmonary nodules (SPNs) that did not meet the original criteria for a positive screening test and identify features associated with lung cancer risk by using data and images from the National Lung Screening Trial (NLST). Materials and Methods Radiologic features in SPNs in baseline low-dose computed tomography (CT) screening studies that did not meet NLST criteria to be considered a positive screening examination were extracted. SPNs were identified for 73 incident case patients who were given a diagnosis of lung cancer at either the first or second follow-up screening study and for 157 control subjects who had undergone three consecutive negative screening studies.

Radiomic Features Are Associated With EGFR Mutation Status in Lung Adenocarcinomas.

Background: In this study we retrospectively evaluated the capability of computed tomography (CT)-based radiomic features to predict epidermal growth factor receptor (EGFR) mutation status in surgically-resected peripheral lung adenocarcinomas in an Asian cohort of patients.

Patients And Methods: Two hundred ninety-eight patients with surgically resected peripheral lung adenocarcinomas were investigated in this institutional review board-approved retrospective study with requirement waived to obtain informed consent. Two hundred nineteen quantitative 3-D features were extracted from segmented volumes of each tumor, and 59 of these, which were considered independent features, were included in the analysis.