El-Baz Receives NIH Grant for Renal Research

May 17, 2018

 Bioengineering Chair Dr. Ayman El-Baz is leading a team of researchers working on a non-invasive computer aided diagnosis system to detect acute renal transplant rejection. The project, entitled ‘Big Data in Acute Renal Rejection,’ is designed to minimize not only the efficiency, but the cost of determining the viability of a transplant by integrating MRI image analyses with clinical biomarkers.

“The current technology, it uses biopsy. But there is the cost of the biopsy is more than 20K," said El-Baz. "The blood, it shows abnormality. There is no technique. We use a blood test. Basically, right now, we need to develop something that is non-invasive, and inexpensive. Biopsies are very expensive.”

Even if matched prior to an invasive surgery, a kidney may be rejected by the host after the operation. El-Baz hopes to employ his research to help determine in a non-intrusive and affordable way for both the patient and medical industry, the viability of a transplant.

A collaboration with the University of Michigan and University of Mansoura in Egypt, who the University recently completed a memorandum of understanding with, the project is funded by a substantial NIH grant that has previously seen proof of concept funding in the past. El-Baz hopes to use input images from an MRI Scanner to detect perfusion and diffusion parameters, using a machine learning fusion system to determine if a kidney qualifies as a non-rejection, or if the transplanted organ is suffering acute rejection.

Building on his background in bioimaging, new probability models, and model-based algorithms, he explains, “This is another way of using AI to advance the finding in the field of medicine.”