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By Sherry DiBari 

Khan Iftekharuddin, Ph.D., a professor in the Electrical and Computer Engineering Department at �Թϱ��� and the director of the Virginia Beach Data Science Institute, has received a $2.3 million grant from the National Institutes of Health. This grant will fund his work on creating new AI tools and computer models to help doctors identify whether glioblastoma — a type of brain cancer — has returned or if changes in the brain are due to treatment. His research might also help identify how aggressive different types of glioblastoma tumors are. 

The results of this research could allow doctors to choose more personalized treatments for patients. In some situations, it might mean patients can avoid surgery and focus on improving their quality of life. 

Glioblastoma is the most aggressive and deadly type of brain cancer, killing about 10,000 Americans each year and accounting for half of all brain cancer deaths in the U.S. The fast-growing cancer spreads as tiny cancer cells move into the healthy tissues. The survivability of these patients is usually limited to 18 to 24 months from the diagnosis.  

Even after aggressive treatment protocol including surgery, radiation and chemotherapy, the disease recurs in 90% of cases within six to nine months, contributing to its poor overall prognosis. 

Diagnosing recurrence is challenging because treatment-related changes in the brain tissues, such as scarring and swelling, can appear similar to tumor tissue on standard imaging scans like MRIs. Currently, the only way to confirm if the tumor has returned is through an invasive brain biopsy. Dr. Iftekharuddin’s research will investigate how non-invasive AI and machine learning methods and modeling can help distinguish true tumor recurrence without surgery. 

The grant builds on Dr. Iftekharuddin’s 2016 award from the National Institute of Biomedical Imaging and Bioengineering, which focused on more accurate methods to model, analyze and segment brain tumor and other abnormal tissue volumes, track tumor growth, classify tumors and predict patient survival rates. 

The new grant focuses on identifying glioblastoma recurrence and classifying tumor subtypes, which could help doctors predict the aggressiveness of the recurrence.  

“I think it is going to be critical to understand recurrent glioblastoma and its aggressive subtype and how well we can quantify it, given the limited lifespan of these patients after diagnosis,” he said. “If we can detect this subtype with confidence, treatment protocols could be individualized for each patient.” 

Dr. Iftekharuddin is collaborating with clinicians at medical facilities across the country, including The Ohio State University, Children’s Hospital of Philadelphia, Jefferson Medical University, and the University of San Diego and Veterans Affairs. Using large datasets from histopathology, genomics, molecular studies and MRI scans, they are building computational models and AI methods that radiologists, oncologists and other specialists will review to ensure accuracy and reliability. 

“This new award will enable Dr. Iftekharuddin to continue the important work he and his team started on diagnostics in the treatment of brain tumors to reduce risk and improve the treatment effectiveness, and ultimately outcomes for patients,” said Jeffrey Fergus, Ph.D., dean of the Batten College of Engineering and Technology.