On December 20, 2019 Case Western Reserve University cancer researcher reported that it has shown 90% accuracy in pinpointing brain tumors and will soon be tested in real-time with patients at Cleveland Clinic under a three-year, $600,000 V Foundation grant (Press release, Case Western Reserve University, DEC 20, 2019, View Source [SID1234553317]).

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Pallavi Tiwari

The grant was awarded to Pallavi Tiwari, an assistant professor of biomedical engineering at Case Western Reserve with dual appointments in the School of Medicine and Case School of Engineering, and Alireza Mohammadi, an assistant professor of neurosurgery at Cleveland Clinic.

The V Foundation, named for former college basketball coach Jim Valvano, funds innovative cancer research and has awarded more than $200 million since being founded in 1993, the year Valvano died from adenocarcinoma.

The need for neural precision
Tiwari said one particular aspect of the existing clinical workflow for managing treatment for brain tumor patients is imprecise: A post-operative MRI scan can’t effectively discern whether cancer has returned or if the lesion has been altered by what neurologists call a "benign treatment effect."

"So both radiation effects and tumor recurrence have similar clinical symptoms and appearances on routine MRI scans," said Tiwari, a lead faculty member in the Center for Computational Imaging and Personalized Diagnostics in Biomedical Engineering and a member of the Case Comprehensive Cancer Center at the School of Medicine.

"Additionally, a highly invasive brain biopsy is currently the only option for confirmation of disease presence—and each biopsy procedure costs $20,000 to $50,000 per patient," she said. "And more than 15% of patients who undergo a second biopsy will then get an incorrect diagnosis due to the difficulty in sampling of reliable locations of the tumor."

To address those issues, a team led by Tiwari has developed new image-based biomarkers drawn from routine MRI scans to differentiate between these two conditions with an accuracy of 92% on about 200 cases so far.

‘GPS maps’ reveal recurring cancer
Actual images of brain tissue scans showing ‘hot’ areas where cancer is present
An image from the research underpinning the ‘brain GPS’ work done by Tiwari and her team.
They’re calling it a "GPS map" or "heat map" for the brain, as it is expected to reliably show by use of colors which part of a tumor has a recurrence of cancer, or whether it has been instead altered by the radiation.

"We’ll use the routinely acquired MRI scans, feed them into our computational algorithm and create a GPS map that the surgeon can use—one that will have a ‘heat map’ of hot-spots for cancer to guide him or her in finding the correct biopsy site within the lesion," Tiwari said.

Mohammadi said the next step in the project is critical in saving patients and money.

"The first part of this study was done retrospectively, meaning that looking at cases in which they already knew the outcome, but the accuracy was very impressive," Mohammadi said, referring to studies on the mapping Tiwari led in 2016 and early 2019. "Now we are trying to validate this in clinical trials, and if we have that same high accuracy, we won’t need to do that second, expensive biopsy."

Actual brain scan images showing color-coded areas where neurosurgeons would look to find a tumor
Brain scan images used to detect which areas of the lesion should be biopsied.
Clinical trials are expected in the final year of the grant, in late 2021 or early 2022, Tiwari said. In the meantime, researchers will be working to perfect the computational algorithms across multi-institutional data.

Stan Gerson, director of the Case Comprehensive Cancer Center and professor of medicine and environmental health sciences at the School of Medicine, said the new grant will allow to researchers to "focus on patient benefit."

"It enables us to link incredible insight from imaging computational technology with a critical medical need, linking our biomedical engineers to our diagnostic physicians," he said. "I like to say that we are ‘turning clinicians into prognosticators.’ "

Tiwari said the clinical trials are one step closer toward realizing those bringing real benefits.

"We develop these cool technologies and we get excited about 90% accuracy, but it doesn’t mean anything until you can prove it in clinical trials—because that’s when patients can begin to get the benefits," she said. "That’s why this is so exciting for me."