Identifying and resolving dose errors in radiation oncology Radiation therapy is the standard of care for the treatment of many cancers. To avoid unnecessary recurrences or toxicity, the correct dose must be delivered to the tumor within 5% of what is prescribed. The radiation dose to the patient is determined with a treatment planning computer calculation, the accuracy of which depends strongly on the input parameters used by the individual clinic to describe their radiation fields. Audits of centers participating in national radiation therapy clinical trials have found that that 18% of audited cases in the United States do not deliver the radiation dose within 7% of the intended dose. One possible cause for these errors is the inaccurate characterization of the radiation field in the institution?s computational model. This project will develop tools that can identify when this important cause of dose errors is relevant, identify which parameters are most important for the accurate calculation of radiation dose, and then directly interact with those hospitals with identified problems to resolve those errors. This advances our long term goal of improving survival and decreasing normal tissue toxicity in radiation oncology by ensuring accurate dose delivery. Our hypothesis is that a linear accelerator model-specific computational system can identify and resolve 50% of treatment errors in radiation oncology (those showing >5% error), which would be a substantial step towards improved quality.
Specific Aim 1 will develop the infrastructure to identify computational errors in radiation therapy dose calculations using reference radiation beam characteristics. It will then test the performance of hundreds of institutions in calculating radiotherapy doses.
Specific Aim 2 will determine which basic radiotherapy parameters are most important for accurate dose calculation under clinical conditions.
Specific Aim 3 will develop infrastructure to interact with institutions where computational errors have been identified. We will work with the institution to improve their dose calculation models, and verify that their new models are more accurate at calculating dose. Because the calculation model is used to determine the dose to all patients, this improvement will benefit all patients treated at that institution.

Public Health Relevance

Radiation therapy is a standard treatment for many cancers, and hundreds of thousands of people receive this treatment in the United States each year. To be effective, the correct dose of radiation must be delivered to the patient; however, this is relatively challenging and many clinics do not deliver the dose correctly. This project will help improve the safety and quality of radiation therapy by identifying and resolving a major cause of errors in radiation therapy.

Agency
National Institute of Health (NIH)
Institute
National Cancer Institute (NCI)
Type
Research Project (R01)
Project #
5R01CA214526-03
Application #
9692252
Study Section
Radiation Therapeutics and Biology Study Section (RTB)
Program Officer
Obcemea, Ceferino H
Project Start
2017-05-01
Project End
2021-04-30
Budget Start
2019-05-01
Budget End
2020-04-30
Support Year
3
Fiscal Year
2019
Total Cost
Indirect Cost
Name
University of Texas MD Anderson Cancer Center
Department
Radiation-Diagnostic/Oncology
Type
Hospitals
DUNS #
800772139
City
Houston
State
TX
Country
United States
Zip Code
77030
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Kerns, James R; Stingo, Francesco; Followill, David S et al. (2017) Treatment Planning System Calculation Errors Are Present in Most Imaging and Radiation Oncology Core-Houston Phantom Failures. Int J Radiat Oncol Biol Phys 98:1197-1203
Kry, Stephen F; Dromgoole, Lainy; Alvarez, Paola et al. (2017) Radiation Therapy Deficiencies Identified During On-Site Dosimetry Visits by the Imaging and Radiation Oncology Core Houston Quality Assurance Center. Int J Radiat Oncol Biol Phys 99:1094-1100