In current radiation therapy (RT) practice, image quality is still assessed subjectively or by utilizing physically-based metrics. Recently, a novel theory for objective task-based image quality assessment (IQA) in RT was proposed by use of area under therapeutic operating characteristic curve (AUTOC) as the figure-of-merit (FOM).
In this study, we present a comprehensive and practical modular IQA-in-RT simulation framework of this novel theory and evaluate its performance with case studies. The IQA-in-RT simulation framework is created that utilizes new learning-based stochastic object models (SOM) to obtain known organ boundaries, generates ensemble of images directly from the numerical phantoms created with the SOM, and automates the image segmentation and treatment planning steps of a common radiation therapy workflow. By use of this simulation framework, therapeutic operating characteristic (TOC) curves can be computed and the AUTOC can be employed as a FOM to guide optimization of different components of RT process.
1. Steven Dolly, Mark Anastasio, Hua Li*, “Task-Based Image Quality Assessment in Radiation Therapy: Initial Characterization and Demonstration with CT Simulation Images”, SPIE Medical Imaging Conference Proceedings, 2017, Proceeding Volume 10136. Oral Presentation, doi:10.1117/12.2254063.
2. Hua Li*, Lifeng Yu, Mark A. Anastasio, Hsin-Chen Chen, Jun Tan, Hiram Gay, Jeff M. Michalski, Daniel A. Low, Sasa Mutic, “Automatic CT Simulation Optimization for Radiation Therapy: A General Strategy”, Medical Physics, 2014, Vol. 41, No.3, 031708.
3. Lifeng Yu, Hua Li, Joel G. Fletcher, Cynthia H. McCollough, “Automatic Selection of Tube Potential for Radiation Dose Reduction in CT: A General Strategy”, Medical Physics, 2010, Vol. 37, No. 1, pp:234-243.
4. Hua Li, Lifeng Yu, Michael R. Bruesewitz, James M. Kofler, Joel G. Fletcher, Cynthia H. McCollough, “Experimental Thorax Phantom Study of a Novel Automatic kV Selection Strategy for Radiation Dose Reduction in CT”, RSNA Annual Meeting, 2009. (Trainee Research Prize)