Generation and Dissemination of Enhanced AI/ML-ready Prostate Cancer Imaging Datasets for Public Use

Brigham And Women'S Hospital, Boston MA

Investigators

Linked publications & trials

Abstract

PROJECT SUMMARY Summary of parent grant The Advanced Technologies-National Center for Image guided Therapy (AT-NCIGT) is a research and technology center with the mission of advancing patient care, by developing novel innovative tools for image guided Therapy (IGT). The three technologies encompass Imaging Cancer Heterogeneity, Deep learning and Intraoperative devices for image guided therapy which will be investigated both individually and in cross TR&D combinations. The parent AT-NCIGT project includes development of the open source platform to support management and analysis of imaging data collected during image-guided procedures. This platform is being developed in one of the aims under the TRD2. The work proposed under this supplement is within the scope of work being done in AT-NCIGT Deep Learning TRD specifically, since it is proposing to develop technology that will support enriching the datasets collected for an application of priority for AT-NCIGT - prostate cancer - with the metadata to make it AI/ML ready. The tools developed for harmonizing and enriching prostate cancer MRI datasets will support integration of the platform with the latest AI/ML analysis tools and their evaluation, both by the project investigators and by the external collaborators, while the publicly available curated dataset released as a deliverable of the supplement will support external development of AI/ML tools in prostate cancer imaging. Goals of the supplement project We propose to make prostate cancer imaging data more AI/ML ready by performing the following, 1) Automatically generate critical missing metadata regarding the type of MRI scan perform including the modality, use of contrast, and presence of an endorectal coil, 2) Enhance public datasets and a BWH dataset with this metadata and share the results, and 3) Demonstrate how to use the enhanced data in an AI/ML application and distribute teaching materials. Through this project, we will be able to provide publicly available enriched datasets in standardized formats that are suitable for AI and ML development of methods for the detection and risk assessment of prostate cancer.