and ABSTRACT The clinical outcome of radiation therapy depends on delivering the highest possible absorbed dose to the tumor(s) while limiting the dose to normal tissues. Unfortunately, unlike external beam radiotherapy (EBRT), current RT prescription methods do not consider absorbed dose to individual patients but instead use empirically derived or standard methods. Thus, up to 50% of these patients receive sub-optimal prescriptions leading to sub-optimal clinical outcomes including under-dosing of the tumor or severe toxicity in healthy tissues. Clearly this violates the basic tenants of radiation oncology because the radiation doses received by these patients are neither justified nor optimized. Our solution, RAPID (Radionuclide Assessment Platform for Internal Dosimetry), will be the first commercialized desktop Monte Carlo radionuclide dosimetry system. It will utilize a heterogeneous CPU/GPU (Graphical Processing Units) architecture that will minimize the computational complexity stemming from problems encountered in RT dosimetry. RAPID will provide accurate radiation dosimetry results within a clinically acceptable timeframe of less than 5 minutes. The long-term objective of this project is to develop the first FDA approved patient-specific treatment planning software for RT that is completely accessible. Health care systems, drug companies, and clinical researchers are expected to access this technology to provide the best possible care for cancer patients.

Public Health Relevance

Millions of patients are treated with radionuclide therapy each year. Unfortunately, current radionuclide prescription methods do not consider absorbed dose to individual patients but instead use empirically derived or standard methods leading to suboptimal treatment outcomes in some patients. Our solution, RAPID (Radionuclide Assessment Platform for Internal Dosimetry), will be the first commercialized Monte Carlo radionuclide dosimetry software that will permit patient-specific treatment planning.

Agency
National Institute of Health (NIH)
Institute
National Cancer Institute (NCI)
Type
Small Business Innovation Research Grants (SBIR) - Phase I (R43)
Project #
1R43CA221491-01A1
Application #
9558692
Study Section
Special Emphasis Panel (ZRG1)
Program Officer
Canaria, Christie A
Project Start
2018-04-01
Project End
2019-03-31
Budget Start
2018-04-01
Budget End
2019-03-31
Support Year
1
Fiscal Year
2018
Total Cost
Indirect Cost
Name
Voximetry, LLC
Department
Type
DUNS #
080208141
City
Madison
State
WI
Country
United States
Zip Code
53719