Madabhushi’s lab, established in 2012, has become a global leader in the field, specializing in the detection, diagnosis and characterization of various cancers and other diseases by meshing medical imaging, machine learning and AI.

Until now, that machine learning has been focused entirely on two-dimensional images.


“We believe that we’ll be able to train our AI to interrogate 3D tissue images with the same success we have had with two-dimensional images,” Madabhushi said. “But there are so many new possibilities for finding new information in 3D.”

How 3D fits in

Liu and his team have developed a new, non-destructive method that images entire 3D biopsies instead of just a slice. This technique provides full-view images of the tissue and improved predictions of whether the patient had an aggressive cancer.

“With the success of our open-top light-sheet microscopy technologies, an obvious next challenge to overcome was processing and analyzing the massive feature-rich 3D datasets that we were generating from clinical specimens,” Liu said. He said collaborating 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.”

“This (grant) will help us to scale up our existing collaboration to demonstrate that computational 3D pathology can improve critical treatment decisions for diverse populations of men with prostate cancer,” Liu said.

The 3D images, of course, provide more information than a 2D image. In this case, that means details about the intricate tree-like structure of the glands throughout the tissue.

The advances in 3D technology made by Liu were detailed in a paper published in December 2021 in the journal Cancer Research. Madabushi and three others at Case Western Reserve contributed to the academic paper.

The UW researchers reported in that paper that the 3D features made it easier for a computer to identify which patients were more likely to have cancer return within five years.

Liu had said in a UW news blog that this “non-destructive 3D pathology” would become increasingly valuable in clinical decision-making, such as which patients would require more aggressive treatment or respond to certain drugs.

This new NCI grant complements work supported in an ongoing U.S. Department of Defense grant led by Madabhushi, with Liu as a collaborator. That project combines AI and light sheet-based 3D tissue-imaging technology for studying health disparities in prostate cancer.

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