Prostate, Mammography Analysis & Imaging Methods to be Tackled in Latest Texas Computational Oncology Collaboration

The Oden Institute for Computational Engineering and Sciences, The University of Texas MD Anderson Cancer Center, and the Texas Advanced Computing Center (TACC) announced funding for five cancer research projects as part of the program in Oncological Data and Computational Science.

This collaborative effort, launched in 2020, is designed to support research that can accelerate approaches to address unmet needs for patients with cancer. The program aligns the computational research and mathematical modeling strengths of TACC and the Oden Institute with MD Anderson’s oncology and data science expertise, including the institution’s recently launched Institute for Data Science in Oncology.

This year marks the fourth round of seed funding. The program has funded three new projects which bring together collaborators from research units across MD Anderson and UT Austin, and has continued support for two previous seed projects over this funding cycle.

Each new seed project receives grant funding of $50,000, split between both MD Anderson and UT Austin. Computational elements of each project can also tap into TACC’s high performance computing platforms. Ernesto Lima, a research associate at the Oden Institute’s Center for Computational Oncology, will support researchers with the implementation of these project elements. 

Tom Yankeelov, director of the Oden Institute’s Center for Computational Oncology and John Hazle, chair of Imaging Physics at MD Anderson, co-lead the collaborative effort. 

“I am enthusiastic about this year’s cohort of funded projects, which represent a combination of translational and clinical research," Yankeelov said. “We are hopeful this innovative work will yield clinically actionable predictions that can improve outcomes for patients with a variety of cancers.”

The funded research projects include:

• Imaging-based forecasting of prostate cancer histopathology and progression during active surveillance
  This project is spearheaded by Thomas J.R. Hughes, lead of the Computational Mechanics Group, and core faculty member at the Oden Institute, and Aradhana Venkatesan, professor of Abdominal Imaging at MD Anderson. Their work seeks to minimize under- and over-treatment of prostate cancer using mathematical modelling of patient-specific MRI data that analyzes tissues as cancers grow. 
   
• Developing a pipeline to automate longitudinal mammography analysis in a large prospective breast cancer screening cohort
  A research team led by Olena Weaver, associate professor of Breast Imaging at MD Anderson, and Edward Castillo, associate professor of Biomedical Engineering and affiliated faculty member at the Oden Institute, seeks to develop a comprehensive, computerized system for rapid mammography analysis. The team hopes to improve the accuracy and specificity with which breast cancers can be diagnosed by using longitudinal mammography and clinical reports analyzed by deep learning and natural language processing. 
   
• Safe, accurate assessment of treatment response via dynamic contrast enhanced multispectral optoacoustic tomography imaging of tumor perfusion
  Tumor perfusion, which refers to the passage of blood and fluid through a tumor, can be of critically important in determining the efficacy of specific cancer therapies. Mark Pagel, professor of Cancer Systems Imaging at MD Anderson, and Umberto Villa, research scientist at the Oden Institute’s Center for Predictive Engineering and Computational Sciences and OPTIMUS Center, respectively, aim to develop robust optical imaging techniques to measure blood flow. These will serve as potential tools to monitor treatment responses across a wide range of cancers. By blending multispectral and optoacoustic imaging methods, this project aims to reduce imaging risk while enhancing the predictive accuracy of treatment analysis.  

Previously funded seed project receiving continued support 

• Single-cell network-based transfer learning model for designing precision medicine in colorectal cancer
  By using pre-trained machine learning models, Stephen Yi, who is director of the Bioinformatics and the Developmental Therapeutics Lab at Dell Medical School and Oden Institute affiliated faculty member, and Scott Kopetz, professor of Gastrointestinal Medical Oncology at MD Anderson, are working to design personalized medicine solutions for colorectal cancers. This is a previously funded seed project receiving continued support in this funding cycle. 
   
• Rapid, motion-robust MRI for fast and affordable prostate cancer screening and surveillance
  In an effort to make prostate MRIs faster and more accurate, reducing the rate of unnecessary biopsies, Ken-Pin Hwang, assistant professor of Imaging Physics at MD Anderson, and Jon Tamir, assistant professor with UT Austin’s Department of Electrical and Computer Engineering and Oden Institute affiliated faculty, will blend mathematical modeling and massively parallel distributed computing. This is a previously funded seed project receiving continued support in this funding cycle.

“The collaboration between MD Anderson and UT Austin faculty demonstrates the power of team science in addressing significant cancer challenges,” Hazle said. “We’ve seen exciting results from prior funded projects, and we are optimistic that these current projects will lead to highly impactful, externally funded awards.”

Jointly released with The University of Texas MD Anderson Cancer Center

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Media Specialist Contact: Clayton Boldt, Ph.D.
CRBoldt@MDAnderson.org

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