A Medical Imaging Informatics (MII) system for Decision Support in Radiation Therapy Treatment Planning
The primary goal of Radiation Therapy is to target the tumor with maximum radiation dose in order to provide local tumor control. However, it is impractical to conform exactly to the three dimensional tumor outline because of technical limitations. This results in unwanted and often harmful radiation dose being delivered to healthy tissue surrounding the tumor, leading to Normal Tissue Complications. Striking the right balance between delivering the required radiation dose to the tumor and minimizing the dose to surrounding organs is often a challenge for clinicians, since there is no way to arrive at the most optimal treatment plan parameters either mathematically or computationally. Our goal is to enhance the clinician's personal experience by utilizing a knowledge base of historical/ past treatment plans developed by a variety of treatment planners in order to provide recommendations to the clinician of what treatment parameters might work best for the current patient at hand based on what has worked for previous patients. This bridges the gap between the clinician and treatment optimization algorithms. Our ultimate goal is to include outcomes data into this ePR system in order to provide a true evaluation tool to clinicians that will predict the patient's outcome based on the current plan parameters.
Figure 1: The data model for radiation therapy treatment planning and follow-up data objects, including both DICOM and non-DICOM data.
Figure 2: System architecture and data flow of a Radiation Therapy ePR system
Figure 3: Development, testing and evaluation set-up at IPILab
Anh Le, Brent Liu, Reinhard Schulte, HK Huang, "Intelligent ePR system for evidence-based research in radiotherapy: proton therapy for prostate cancer", Int J Comput Assist Radiol Surg. 2011 Nov; 6(6):769-84