This U24 project will help disseminate FireVoxel, a freely available, user-friendly software package to process and extract quantitative information form dynamic MRI, CT and PET images. The software will help radiologists, oncologist and biomedical researchers to make better use of acquired data. Our emphasis is on dynamic imaging and model fitting. The software has been developed by a team of scientists over the past 15 years in the context of a busy radiology practice at NYU School of Medicine. It is a mature product, with fully functional workflows, well beyond the proof-of-principle stage. It contains extensive tools for image statistics (radiomics), segmentation, coregistration, motion correction and modeling. FireVoxel has been already used in approximately 300 published studies. Approximately 1000 users across the globe are currently helping to validate and improve the program. Three years are needed to develop a comprehensive documentation and put together an automatic build-test system to assure industrial quality level needed for a wide dissemination. We will implement a comprehensive database of clinically representative cases and corresponding metrics to eliminate software defects and assure consistent output after each new software version. The depository of sample cases will be complemented by relevant tutorials, cloud-based documentation and user guides. These additions will make the software attractive to a broad user base. We will also extend FireVoxel's capabilities to include three novel, fully automatic measures: (a) a reliable arterial input function (AIF) for the use in dynamic- contrast MRI modeling; (b) AIF-free single-kidney function (glomerulal filtraction rate); and (c) T1rho parametric mapping.

Public Health Relevance

This dissemination project will deliver to radiologists, oncologists and biomedical researchers a user-friendly software package to process dynamic MRI, CT and PET images. Comprehensive documentation and an automatic build test system will assure quality level needed for wide dissemination. Several novel, fully automatic measures will be added.

Agency
National Institute of Health (NIH)
Institute
National Institute of Biomedical Imaging and Bioengineering (NIBIB)
Type
Resource-Related Research Projects--Cooperative Agreements (U24)
Project #
1U24EB028980-01
Application #
9882387
Study Section
Special Emphasis Panel (ZEB1)
Program Officer
Shabestari, Behrouz
Project Start
2019-09-24
Project End
2022-06-30
Budget Start
2019-09-24
Budget End
2020-06-30
Support Year
1
Fiscal Year
2019
Total Cost
Indirect Cost
Name
New York University
Department
Radiation-Diagnostic/Oncology
Type
Schools of Medicine
DUNS #
121911077
City
New York
State
NY
Country
United States
Zip Code
10016