Cancer is a significant health problem with an estimated 1,699,780 new cases of cancer and 600,920 deaths in the US during 2017. Approximately 50% of cancer patients will have radiation therapy as part of their course of treatment. Standard x-ray radiation therapy treatment beams suffer from high entrance doses. The physics of x-ray radiation therapy fundamentally limits the amount of radiation that can be delivered to a target while sparing the surrounding normal tissues. Proton therapy is a rapidly growing radiation therapy modality with significant clinical potential to overcome these limitations. The reduction of doses to normal tissue may be significant in pediatric patients where studies have shown that proton therapy can significantly lower rates of secondary malignancies. Greater doses to targets, such as those achievable by proton therapy, can improve local control and greater overall survival. Proton therapy has the potential to significantly reduce radiation doses to normal tissue while increasing the dose to targets however its clinical benefit has been limited by delivery accuracy. Proton therapy has the distinct advantage of being able to deliver a high dose at deep depths while potentially sparing healthy tissue proximal and distal to the target position. This advantage is physically manifested by the Bragg peak in which the proton deposits a significant portion of its dose immediately before reaching the end of its range. The position of the Bragg peak in tissue is determined using the stopping power ratio (SPR) relative to water. Errors in the determined SPR translate to positional inaccuracies of the Bragg peak within the patient relative to the planned dose delivery position. Proton range uncertainty has been cited as the main factor limiting the ability for proton therapy to spare normal tissues to their full potential. Recently, we developed a novel method to determine mean ionization potential, Im, (and SPR) using MRI which will allow for more highly tailored conformal proton therapy treatments. This methodology has distinct advantages over current methods due to our method?s tissue sensitivity and stability to noise. To our knowledge, no equally effective method is currently being employed by any other teams anywhere in the world. The goal of this project is to improve the accuracy of proton therapy treatments using a novel multi-modal imaging technique with the potential for practical application in most clinics. To achieve this goal, we must further develop this method to create accurate SPR maps in phantoms (Aim 1), validate these SPR maps in ex vivo animal tissues and determine uncertainties (Aim 2), and conduct a prospective virtual clinical trial to test the hypothesis that reduced SPR uncertainties lead to improvements on dosimetry and outcomes (Aim 3). The work proposed builds on our initial theory and supporting data that show the potential for high accuracy in SPR determination. The innovation of this project is in the potential to significantly reduce proton range uncertainties allowing for highly tailored conformal proton therapy treatments. No clinically available methodology has been shown to achieve accuracy and stability to noise as ours does.

Public Health Relevance

Cancer is a significant health problem with an estimated 1,699,780 new cases of cancer and 600,920 deaths in the US during 2017. Proton therapy has the potential to significantly reduce radiation doses to normal tissue while increasing the dose to targets for the 50% of cancer patients receiving radiation therapy, however its clinical benefit has been limited by delivery accuracy. The goal of this project is to improve the accuracy of proton therapy treatments using a novel multi-modal imaging technique.

Agency
National Institute of Health (NIH)
Institute
National Institute of Biomedical Imaging and Bioengineering (NIBIB)
Type
Exploratory/Developmental Grants (R21)
Project #
5R21EB026086-02
Application #
9668141
Study Section
Radiation Therapeutics and Biology Study Section (RTB)
Program Officer
Zubal, Ihor George
Project Start
2018-04-01
Project End
2021-01-31
Budget Start
2019-02-01
Budget End
2020-01-31
Support Year
2
Fiscal Year
2019
Total Cost
Indirect Cost
Name
University of California San Francisco
Department
Radiation-Diagnostic/Oncology
Type
Schools of Medicine
DUNS #
094878337
City
San Francisco
State
CA
Country
United States
Zip Code
94118