Newswise — CLEVELAND—Researchers at Case Western Reserve University and the University of Washington expect to gain valuable new insights into highly aggressive prostate cancer by combining Artificial Intelligence (AI)-powered diagnostic imaging with three-dimensional (3D) tissue imaging.
This new AI-3D collaboration will provide a never-before-seen, expanded view and understanding of prostate cancer cells, made possible by a new approach called “light sheet microscopy,” the researchers said.
Prostate cancer is the most common non-skin cancer in the United States. One in eight men nationally will be diagnosed with prostate cancer in his lifetime, and one in 40 will die from the disease, according to the Prostate Cancer Foundation.
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Anant Madabhushi, director of the Center for Computational Imaging and Personalized Diagnostics at Case Western Reserve, and Jonathan Liu, a professor of mechanical engineering and bioengineering at the University of Washington (UW), are co-leaders in the new work and will split the funding. The National Cancer Institute (NCI), part of the National Institutes of Health, is supporting the research with a five-year, $3.13 million grant.
“This is an unprecedented meshing of the two most powerful technologies in this area,” said Madabhushi, also the Donnell Institute Professor of Biomedical Engineering at the Case School of Engineering. “We’ll take the AI we’ve developed and, for the first time, be able to apply it to 3D tissue-imaging that the University of Washington excels in—and gain fine, granular detail.”
Liu said collaboration with Madabhushi’s lab at Case Western Reserve was “an obvious and ideal choice since developing explainable AI methods will facilitate clinical adoption of a new imaging technology such as ours.”
Identifying aggressive cancer
That fine detail will hopefully reveal even more information about how to identify which prostate cancer cases will be more aggressive in patients, Madabhushi said.
Knowing that could help clinicians determine who would benefit from surgery or radiation therapy—and which patients might be actively monitored instead, he said.
Further, the prostate cancer study could also lay the groundwork to develop what are called “pathomic-based classifiers” of disease outcome for a host of other cancers, Madabhushi said.
Pathomics refers to the application of computer vision and AI to extract a large number of features from tissue images using data-characterization algorithms. The features can then help uncover tumors and other characteristics usually invisible to the naked eye.
