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Computational Model Can Help Treat Ulcers in Patients with Spinal Cord Injury

Treating ulcers in spinal cord injury patients is still a challenge, but researchers have developed a computational model to aid the process.

Understanding, diagnosing, and treating ulcers related to spinal cord injury has gotten easier thanks to a computational model, according to findings published in PLOS Computational Biology.

Researchers from the University of Pittsburgh created an agent based model (ABM) of ischemia/ reperfusion induced inflammation and pressure ulcers (PUABM) in order to investigate potential treatments. The computational, or “in silico,” model of the process was based on serial photographs of ulcers which developed in spinal cord injury patients enrolled at Pitt’s Rehabilitation Engineering Research Center on Spinal Cord Injury. The photos were taken at the time of ulcer diagnosis, three times per week in the acute stage, and once per week as the ulcer was resolved.

The investigators noted that pressure ulcers (PU) remain a significant burden in cost of care as well as quality of life, despite an improvement in understanding and advanced interventions. They analyzed tissue level features of the PUABM and visual patterns of ulcer formation among patients with spinal cord injury.

The researchers determined that the morphological features, simulated cell counts, and mediator concentrations suggest that the influence of inflammatory dynamics caused the simulations to be committed to “better” versus “worse” outcomes by 4 days of simulated time and prior to ulcer formation.

If the researchers first manipulated the in silico model in a single round area over a virtual bony protuberance and altered the environment (such as inflammatory mediators or tissue oxygenation), a variety of irregularly shaped ulcers were produced, similar to what is commonly seen in practice. Then they conducted two virtual trials of potential therapies.

“Computational models like this one might one day be able to predict the clinical course of a disease or injury, as well as make it possible to do less expensive testing of experimental drugs and interventions to see whether they are worth pursuing with human trials,” study author Yoram Vodovotz, PhD, said in a statement. “They hold great potential as a diagnostic and research tool.”

In order to treat the lesions, the authors believe, anti-inflammatory measures had to be implemented early — well before the first clinical signs of ulcer formations.

In the future, better measurements at the bedside of the affected patients would allow for the computational model to be used to its potential. Analyzing such data could provide would healing phenotypes, the authors wrote, which could predict appropriate treatment courses and design and test new therapy regimens.