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Analysis of outcomes in radiation oncology: An integrated computational platform
Author(s) -
Liu Dezhi,
Ajlouni Munther,
Jin JianYue,
Ryu Samuel,
Siddiqui Farzan,
Patel Anushka,
Movsas Benjamin,
Chetty Indrin J.
Publication year - 2009
Publication title -
medical physics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.473
H-Index - 180
eISSN - 2473-4209
pISSN - 0094-2405
DOI - 10.1118/1.3114022
Subject(s) - medical physics , dicom , computer science , radiation oncology , radiation therapy , radiation treatment planning , software , outcome (game theory) , graphical user interface , plan (archaeology) , medicine , radiology , artificial intelligence , mathematics , operating system , history , mathematical economics , archaeology
Radiotherapy research and outcome analyses are essential for evaluating new methods of radiation delivery and for assessing the benefits of a given technology on locoregional control and overall survival. In this article, a computational platform is presented to facilitate radiotherapy research and outcome studies in radiation oncology. This computational platform consists of (1) an infrastructural database that stores patient diagnosis, IMRT treatment details, and follow‐up information, (2) an interface tool that is used to import and export IMRT plans in DICOM RT and AAPM/RTOG formats from a wide range of planning systems to facilitate reproducible research, (3) a graphical data analysis and programming tool that visualizes all aspects of an IMRT plan including dose, contour, and image data to aid the analysis of treatment plans, and (4) a software package that calculates radiobiological models to evaluate IMRT treatment plans. Given the limited number of general‐purpose computational environments for radiotherapy research and outcome studies, this computational platform represents a powerful and convenient tool that is well suited for analyzing dose distributions biologically and correlating them with the delivered radiation dose distributions and other patient‐related clinical factors. In addition the database is web‐based and accessible by multiple users, facilitating its convenient application and use.