A new imaging approach to assess donor livers before transplantation could provide a much more comprehensive view of the condition of the whole organ, complementing conventional pathology tests that are typically restricted to localized areas.
In a study published in Science Translational Medicine, researchers at the University of Oklahoma used polarization-sensitive optical coherence tomography (PS-OCT) to noninvasively measure multiple relevant parameters across the entire surface of donor livers. Using polarized light, this imaging technique was able to detect signs of steatosis, fibrosis, inflammation, and necrosis in donor livers—all of which are critical indicators of transplant viability.
“PS-OCT offers a noninvasive assessment of liver viability by quantifying hepatic parameters across the entire donor liver, effectively complementing current pathological analysis,” write the authors of the study, led by Qinggong Tang, PhD, associate professor of biomedical engineering at the University of Oklahoma. “These results suggest that PS-OCT provides a robust approach to assessing donor liver viability, which could potentially decrease the discard rate of high-risk livers, thereby expanding the donor pool.”
Liver transplants are limited by a shortage of viable donor livers, which is driven by a high demand for donor livers and high rates of organ discard. In the U.S. alone, there are over 9,000 people on the liver transplant waitlist, which has driven healthcare providers to progressively expand the criteria used to evaluate potential donors.
Assessing whether a donor liver is viable for transplantation currently relies on biopsies. However, these are invasive procedures that only provide information about the specific location within the liver the sample was taken from. As a result, this approach can sometimes miss critical signs of damage or disease elsewhere in the organ, potentially increasing the risk of transplanting a compromised liver.
Tang and colleagues first evaluated the performance of PS-OCT imaging in discarded human donor livers, comparing the results to biopsies and functional tests. Using a machine learning algorithm to analyze the imaging data enabled the identification of key signs of injury and disease with 80% accuracy compared to conventional pathology assessments. The team then scanned five viable donor livers slated for transplantation and stratified them into different risk categories, accurately predicting clinical outcomes a week after transplantation.
While biopsy tests can take several days to give back results, PS-OCT scans can produce a complete picture of the condition of the entire liver within about 15 minutes, offering a fast and noninvasive tool to assess multiple markers of transplant viability. Although the imaging technique is not intended to replace current evaluation methods, it could significantly reduce sampling error and add valuable information when screening potential donors. Ultimately, improving the assessment of donor livers could address the urgent need for increasing transplant numbers while simultaneously improving clinical outcomes for transplant recipients.
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