Automated Closed- and Open-Loop Validation of Knowledge-Based Planning Routines Across Multiple Disease Sites.

Purpose: Knowledge-based planning (KBP) clinical implementation necessitates significant upfront effort, even within a single disease site. The purpose of this study was to demonstrate an efficient method for clinicians to assess the noninferiority of KBP across multiple disease sites and estimate any systematic dosimetric differences after implementation. We sought to establish these endpoints in a plurality of previously treated patients (validation set) with both closed-loop (training set overlapping validation set) and open-loop (independent training set) KBP routines.

Geometric and dosimetric evaluation of atlas based auto-segmentation of cardiac structures in breast cancer patients.

Background And Purpose: Auto-segmentation represents an efficient tool to segment organs on CT imaging. Primarily used in clinical setting, auto-segmentation plays an increasing role in research, particularly when analyzing thousands of images in the "big data" era. In this study we evaluate the accuracy of cardiac dosimetric endpoints derived from atlas based auto-segmentation compared to gold standard manual segmentation.

Stereotactic Body Radiation Therapy Versus Surgery for Early Lung Cancer Among US Veterans.

Background: Stereotactic body radiation therapy (SBRT) has been proposed as a potential alternative to surgery for early lung cancer, although we lack well-powered prospective randomized data comparing these treatments, and existing studies suffer from incomplete information on confounders that can bias results. Here, we evaluated the comparative effectiveness of surgery and SBRT in lung cancer treatment using a large extensively detailed database from the Veteran's Affairs system.

Methods: We identified veterans with biopsy-proven clinical stage I non-small cell lung cancer diagnosed between 2006 and 2015 from within the Veteran's Affairs Informatics and Computing Infrastructure.