While adaptive therapy has been studied before, none of the previous studies deals with the unique challenges (range uncertainties) and unique capabilities (beamlet optimization and prompt gamma imaging) of proton therapy. This proposal will for the first time address these aspects by developing innovative hardware and software methodologies. We envision treatment planning and delivery to be fully adaptive in terms of intra- fractional changes in patient geometry. This proposal aims at predicting the dose distribution (or a surrogate thereof) in the patient immediately prior to treatment delivery and correct for any discrepancies between the measured and intended dose in less than 2 minutes. This will enable us to deliver (proton) radiation therapy in an adaptive setting and much reduced target volume margins (2mm isotropic plus 2mm range margin in proton therapy in the beam direction) daily while the patient is positioned on the treatment table. We propose to achieve this goal by simultaneously developing fast hardware and software tools that take advantage of in-room prompt gamma and cone-beam CT imaging in combination with fast dose calculation. We will combine this technology with a novel framework on beamlet adaptation. While some of our methods will improve photon therapy as well, we will focus on proton therapy because it offers unique opportunities to dose verification in vivo as well as unique challenges due to range uncertainties. Our methodology will be made available to the entire proton therapy community.

Public Health Relevance

With this proposal we aim at reducing radiation therapy uncertainty margins substantially using in-vivo treatment verification as well as daily delivery adaptation. We will develop hardware and software to allow daily treatment delivery adaptation while the patient is in the room for radiation therapy. After completion of this research we will be able to predict the dose distribution (or a surrogate thereof) in the patient and correct for any discrepancies between the measured and intended position of the dose delivery in less than 2 minutes. This will be a paradigm shift to current clinical practice of treating based on pre-treatment geometrical patient information only.

Agency
National Institute of Health (NIH)
Institute
National Cancer Institute (NCI)
Type
Research Project (R01)
Project #
1R01CA229178-01A1
Application #
9728281
Study Section
Radiation Therapeutics and Biology Study Section (RTB)
Program Officer
Obcemea, Ceferino H
Project Start
2019-04-01
Project End
2024-03-31
Budget Start
2019-04-01
Budget End
2020-03-31
Support Year
1
Fiscal Year
2019
Total Cost
Indirect Cost
Name
Massachusetts General Hospital
Department
Type
DUNS #
073130411
City
Boston
State
MA
Country
United States
Zip Code
02114