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Funding Rolls in for Computational Imaging Research



Last fall’s issue of the Biomedical Engineering Department’s newsletter included a profile of the Center for Computational Imaging and Personalized Diagnostics (CCIPD) directed by Anant Madabhushi, the F. Alex Nason Professor II of biomedical engineering at Case Western Reserve University. The overarching goal of the CCIPD is to extract as much value as possible from medical imaging scans to predict disease presence, prognosis and treatment response in order to facilitate patient management and appropriate therapy. 
Between 2015 and 2017, the CCIPD received more than $13 million in total funding. That figure has since grown almost 70 percent, with the center receiving nearly $9 million in funding so far in 2018. “What is so exciting about this funding is that it’s a recognition that you need decision support tools to complement and augment human decision-making. These tools are meant to empower pathologists, radiologists and oncologists, not obviate them,” says Madabhushi. “The funding is truly a validation of the need and utility of this kind of technology.”
The CCIPD focuses on four broad subject areas: image guided interventions, digital pathology, machine learning and personalized medicine, and computational diagnostics. The center’s most recent awards touch upon all these areas.


Lung Cancer Risk Stratification
National Cancer Institute
The National Cancer Institute (NCI) awarded the CCIPD a five-year, $3.15 million R01 grant to more accurately determine which early-stage lung cancer patients would most benefit from chemotherapy following surgery and which would not. Using computer analysis of digitized tissue biopsy images, researchers are attempting to identify patients who could get additional therapeutic help from chemotherapy, while avoiding the adverse side effects of the therapy for other patients who don’t require such an intervention.
“The goal of this computerized tissue analysis is to generate a risk score to then inform oncologists about the need for chemotherapy,” says Madabhushi, who is the principal investigator of the project. Dr. Vamsidhar Velcheti, MD, a thoracic oncologist at Cleveland Clinic serves as the co-principal investigator. Also involved in the project is Florida-based cancer diagnostics company Inspirata Inc. They hope the NCI grant will result in the first validated predictive tool for identifying which early-stage lung cancer patients will benefit from chemotherapy after surgery.
Risk Stratification of Head and Neck Cancers
National Cancer Institute
The CCIPD also received a $3.15 million R01 grant from the NCI for a head and neck cancer project in collaboration with Cleveland Clinic, Vanderbilt University and Inspirata Inc. The goal of the research is utilize images of tissue specimens to predict and stratify risk for oropharyngeal cancers. 
“There are a lot of head and neck tumors that end up being treated fairly aggressively,” says Madabhushi. “The question is how can we identify patients that could benefit from de-escalation of therapy?” Clinical trials to demonstrate that a reduction in therapy is appropriate in some patients have not yet been conducted, in part, because there’s a lack of prognostic biomarkers for risk stratification. Funding from the NCI will help the CCIPD establish a validated prognostic test, which in turn could set the stage for development of clinical trials to demonstrate that de-escalation is warranted in some of these less aggressive tumors.
Predicting Treatment Response for Brain Tumors
Congressionally Directed Medical Research Program (CDMRP)
In 2017, brain cancer was added to the list of disorders eligible for study by the Department of Defense’s (DoD) Peer Reviewed Cancer Research Program (PRCRP). In February, Pallavi Tiwari, an assistant professor of biomedical engineering in Case’s School of Medicine, landed a $577,280 grant from the DoD for her work developing neuroinformatics techniques for evaluating the presence of brain tumors and response to treatment of the disease.
The three-year grant, which begins in July, will allow Tiwari’s team in the CCIPD to develop artificial intelligence and computational imaging tool to identify from MRI scans which brain tumor patients are most likely to respond to therapy. “We are interested in identifying which patients will respond to chemo radiation and which ones will not,” says Tiwari. “If we are successful, clinicians can use our noninvasive model to help guide their patients’ treatment decisions. They will be able to figure out what treatments should be given if chemo radiation is not going to work out.”
Tiwari's team, in collaboration with Jennifer Yu, from Cleveland Clinic's Brain Tumor and Neuro-Oncology Center, also was awarded a three-year, $200,000 grant from the Dana Foundation to develop neuroimaging tools for predicting treatment response to metastatic brain tumors following chemo-radiation. The Dana Foundation is a private philanthropic organization that supports brain research through grants, publications and educational programs.
Lung Cancer Screening
Congressionally Directed Medical Research Program (CDMRP)
The DoD awarded $608,000 to researchers at the CCIPD to conduct a lung tumor screening project. “We know that CT scan screening saves lives,” says Madabhushi. “However, if something shows up on a CT scan, the challenge is figuring out if what you are looking at is malignant or benign.”
There is a high false-positive rate associated with lung nodules on CT scans, so patients often undergo unnecessary biopsies, bronchoscopies and even wedge resections. “With the DoD project, we are developing decision support tools and algorithms that include risk characterization of these nodules from CT scans,” says Madabhushi. “This could allow us to distinguish between what are truly benign and truly malignant nodules.”
The work is also supported via a $125,000 grant from the Case-Coulter Translational Research Partnership and a $75,000 grant from the Ohio Third Frontier Technology Validation Fund.
Breast Cancer Project
United States – India Science and Technology Endowment Fund
For more than two years, the CCIPD has collaborated with the Tata Memorial Centre, a national cancer center in Mumbai, India, focused on cancer prevention, treatment and research. Earlier this year, the U.S. - India Science and Technology Endowment Fund awarded the partners and Inspirata Inc. a two-year, $356,000 grant. “We are partnering with Tata to develop and validate a low-cost tissue image-based predictor for identifying women with early stage breast cancer to figure out who will benefit from chemotherapy and who may not need it,” says Madabhushi. 
It would be advantageous for patients to avoid costly chemotherapy, if possible, especially in a country like India. “It’s a lower-middle income country, so economics play a much greater role in deciding treatment options,” says Madabhushi. The CCIPD and Tata Memorial Centre hope to begin prospective testing during the course of the grant.
Digital Pathology Analysis of Kidney Biopsies
NephCure Kidney International
The CCIPD received the 2017 Neptune Ancillary Study Award from NephCure Kidney International, an organization committed exclusively to supporting research related to focal segmental glomerulosclerosis (FSGS) and the diseases that cause Nephrotic Syndrome. FSGS is a rare disease that attacks the kidney’s filtering units, causing serious scarring that leads to permanent kidney disease and, in some cases, kidney failure.
The $150,000 award will fund a one-year pilot study led by Madabhushi to develop and apply novel machine learning tools for notation of structures within kidney pathology images. This will allow for construction of annotated kidney atlases, which could lead to the discovery of prognostic morphologic outcome signatures for FSGS. More information on the project can be found at under the "Recent News" tab.
Prostate Cancer Stratification
Congressionally Directed Medical Research Program (CDMRP)
The DoD awarded a 3-year, $542,000 grant to researchers to study noninvasive risk stratification of prostate cancer patients using radiomic features derived from magnetic resonance fingerprinting (MRF) and MRI. The tools can be used to capture subtle sub-visual differences between benign and cancerous tumors, as well as ascertain the different grades of cancer.
“This funding will enable development of computational imaging-based methods to determine the risk or aggressiveness of disease of a prostate cancer patient,” says Rakesh Shiradkar, principal investigator and a senior research associate in CCIPD. “The current standard of care uses core needle biopsies and blood tests, which are both painful and inaccurate. Leveraging radiomics and machine learning methods using MRF and MRI can definitely advance management and care of prostate cancer patients.”