Two Indian researchers Pallavi Tiwari and Satish Vishwanath, faculty member in the Case Western Reserve School of Medicine and lead researchers in the Centre for Computational Imaging and Personal Diagnostics (CCPID) at the Case School of Engineering have been awarded with USD 1 million to build AI tools for tumor diagnosis to cut down on unnecessary second surgeries in cancer patients.
Cancer patients have to undergo second surgeries unnecessary because the damaged tissues by chemotherapy or radiation resemble a recurring tumor on an MRI scan, which can be confirmed non-cancerous only after removing suspected tissue. Both Indian researchers believe that the AI tools for tumor diagnosis under development will be able to detect the difference between recurring tumors and non-cancerous tissues on post-operative MRI scans. The AI tool will be mainly for a brain tumor and colorectal cancer. Satish Vishwanath specializes in colorectal cancer and Pallavi Tiwari in brain tumors.
The two Indian researchers are examining both types of tumors in this project. In such solid tumors, significant medical trouble identifies individuals who have reacted well to treatment with no or little tumor from those who still have expanding or recurrent tumors after treatment. If the tissue is not taken out, no one can tell if it’s a tumor or a dying tissue.
This means patients are being overtreated i.e., being recommended for an aggressive surgery that they do not need. Alternatively, clinicians risk not doing a second surgery when it is actually necessary to remove the recurrent tumor, implying that they sometimes risk undertreating the patient as well. – said Pallavi Tiwari
The AI tool will be developed to check routine MRI scans and capture specific information from them, which can measure physiology characteristics that can help distinguish between recurring tumors and damaged tissues. The researchers will work on multiple platforms for extensive research, test them across institutions, and conduct limited clinical trials to develop the AI tool in the next 3 years. The researchers will also face challenges such as pulling together post-therapy databases and detailed clinical information and ensuring that AI tools work accurately on post-therapy MRI scans.
“The biggest clinical impact of the work will be in enabling fewer unnecessary surgeries to remove suspect tissue which needs to be confirmed as non-cancerous after initial therapy.” – said Satish Vishwanath
The use of AI can transform and change the future of healthcare. It can help in deep learning of diagnosing a disease, reducing operational costs, helping in precise analysis in pathology, and building smart medical devices. Developing more AI tools in the healthcare field will be a revolutionizing clinical decision.