Project Grant R01CA290438

Award Date 3/12/25
Completion Date 2/28/30
Dollars Obligated $718K
Federal Grant Program
93.394
Assistance Type
Project Grant
Place of Performance
New York, USA
Similar Awards
This $700,611 Project Grant award from the National Cancer Institute (NCI) under the Cancer Cause and Prevention Research program (CFDA 93.393) aims to conduct a practical randomized controlled trial to evaluate the use of artificial intelligence (AI) for improving melanoma diagnosis. The study, led by the Sloan-Kettering Institute for Cancer Research, will determine the potential benefits and barriers of AI technology adoption by clinicians, and assess the impact of real-time AI feedback on...
The National Cancer Institute (NCI) awarded a $680,433 project grant under the Cancer Detection and Diagnosis Research program (CFDA 93.394) to The Regents of the University of California, San Francisco (UCSF) to conduct research aimed at improving prognostic estimation and understanding of prostate cancer biology and heterogeneity. The 5-year project seeks to: Evaluate the competitive and additive relationships between standard-of-care genomic expression and pathology artificial...
This $256,000 National Science Foundation Project Grant under the Engineering (47.041) program will support the development of an artificial intelligence-based system for analyzing multiparametric magnetic resonance imaging (MRI) scans to detect prostate lesions. The awardee, Taurus Diagnostics, Inc., will create a novel prostate cancer diagnostic platform leveraging artificial intelligence image analysis for high sensitivity and specificity. Key objectives include developing methods to...
This Project Grant award from the National Cancer Institute (CFDA 93.396 Cancer Biology Research) provides $539,633 to support research at Albert Einstein College of Medicine focused on investigating the role of aberrant androgen receptor signaling in prostate cancer development and progression, particularly in the African American population. The project aims to leverage new animal models and advanced techniques like single-cell RNA sequencing to study how genetic factors like shorter...
This federal Project Grant award from the National Cancer Institute (CFDA Program 93.394 - Cancer Detection and Diagnosis Research) provides $568,151 to the Regents of the University of Michigan to develop a real-time photoacoustic imaging platform for sensitive detection and characterization of prostate cancer aggressiveness. The research aims to optimize photoacoustic nanoprobes to enable quantitative assessment of prostate gland microarchitecture and tumor microenvironment, with the goal...
This Project Grant award from the National Cancer Institute's Cancer Detection and Diagnosis Research program (CFDA 93.394) aims to evaluate the performance of four commercial mammography-based artificial intelligence (AI) algorithms for breast cancer risk prediction. The $989,122 award will fund a study using a large, diverse screening population to assess the accuracy and equity of these AI-based risk models compared to traditional clinical risk factor models. The study will be conducted at...
This $607,131 Project Grant award from the National Cancer Institute's Cancer Detection and Diagnosis Research program (CFDA 93.394) is funding a research project to develop an MRI-guided robotic system for minimally invasive, personalized prostate cancer surgery. The overarching goal is to replace invasive radical prostatectomy with targeted, image-guided focal resection of prostate tumors. The key products/services being developed include: 1) Fast intraoperative low-field MRI imaging to...
This $535,334 federal Project Grant award from the National Cancer Institute's Cancer Biology Research program (CFDA 93.396) will support research by the Albert Einstein College of Medicine to investigate the non-autonomous role of androgen signaling in prostate tumorigenesis. The project aims to determine how aberrant androgen receptor activation in prostatic stromal cells, specifically those expressing the Gli1 protein, can promote the oncogenic transformation of prostate epithelial cells...
This $435,827 Project Grant from the National Cancer Institute (NCI) under the CFDA 93.394 Cancer Detection and Diagnosis Research program supports research conducted by New York University (NYU) School of Medicine to develop deep learning methods for analyzing mass spectrometry imaging (MSI) data. The goal is to make MSI data more accessible to existing machine learning workflows by expanding the dimensionality of the data structure to treat each metabolite or lipid as an individual...
The National Institute of Biomedical Imaging and Bioengineering awarded a $693,156 Project Grant (Award ID: R21EB035247) to the Dana-Farber Cancer Institute, Inc. through the Discovery and Applied Research for Technological Innovations to Improve Human Health (CFDA 93.286) federal grant program. The funding supports the development of artificial intelligence (AI) algorithms to predict prognosis and aid in treatment selection for cutaneous squamous cell carcinomas (CSCC), a highly prevalent...

This $717,667 federal Project Grant awarded by the National Cancer Institute (CFDA 93.394 - Cancer Detection and Diagnosis Research) to the Icahn School of Medicine at Mount Sinai aims to develop an AI-enabled, stroma-weighted automated grading system (SWAG) to improve risk stratification and early detection of lethal prostate cancer phenotypes in Black men.

The key objectives are to: 1) Annotate H&E and multiphoton microscopy/second harmonic generation images to develop the AI-powered SWAG system for prostate cancer risk prediction, and 2) Define and validate the molecular drivers of racial disparities in prostate cancer outcomes using spatial transcriptomics and multiplexed CRISPR approaches. This 5-year project (3/12/2025 - 2/28/2030) seeks to introduce innovative, label-free imaging techniques and advanced data analytics to enhance early detection and prognostication of aggressive prostate cancer, particularly in the Black patient population.

Generated 4/8/25, 3:55 AM