Six New Cancer Projects Receive Funding in Joint Collaboration Between MD Anderson, Oden Institute and TACC

AUSTIN, TX - The Oden Institute for Computational Engineering and Sciences, The University of Texas MD Anderson Cancer Center, and the Texas Advanced Computing Center (TACC) at The University of Texas at Austin announced funding for six cancer research projects as part of the Joint Center for Computational Oncology.

This collaborative initiative aims to accelerate breakthroughs addressing unmet needs for cancer patients by combining the Oden Institute’s expertise in computational science, MD Anderson’s leadership in oncology and data science, and TACC’s high-performance computing strength.

This is the fifth round of funding since the program began in 2020 which provides $50,000 to each new project, split between MD Anderson and UT Austin researchers. The projects also can utilize TACC’s high performance computing platforms and are eligible for supplemental funding of post-doctoral fellows as funding allows.

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. 

"We had an excellent set of applications this year, and I am delighted to report that we were able to fund six projects, more than we have supported in previous years,” said Yankeelov. “These projects represent innovative applications of mathematical and computational modeling to attack problems in cancers of the liver, rectum, breast and brain. We also have a project, led by two rising investigators, focused on overcoming the practical issues of integrating digital twin frameworks into the clinical workflow. It will be very exciting to see how these projects develop over the next year.” Yankeelov is also professor of biomedical engineering at UT’s Cockrell School of Engineering.

The 2024 funded research projects include:

Integrating machine learning-based histopathology with biology-based models of high-grade glioma growth and response to radiotherapy

• Led by David Hormuth, research scientist at the Center for Computational Oncology at the Oden Institute, and David Fuentes, associate professor of Imaging Physics at MD Anderson, this project seeks to combine novel machine learning techniques with existing mathematical modeling to predict tumor growth and treatment response for high-grade gliomas.

Computational and Preclinical Modeling to Predict Liver Growth in Patients with Liver Malignancy Undergoing Portal Vein Blockade

• Led by Edward Castillo, affiliated faculty at the Oden Institute and associate professor of biomedical engineering at UT's Cockrell School of Engineering, Steven Huang, professor of Interventional Radiology at MD Anderson, and Marites Melancon, professor of Interventional Radiology at MD Anderson, this team hopes to develop an automated and robust computational model that uses liver perfusion images to assess liver hypertrophy following portal vein embolization.

Fast Comprehensive 3D Imaging of Rectal Cancer

• Jon Tamir, affiliated faculty at the Oden Institute and assistant professor of electrical & computer engineering at UT's Cockrell School of Engineering, Gaiane Rauch, professor of Diagnostic Radiology at MD Anderson, and Ken-Pin Hwang, associate professor of Imaging Physics at MD Anderson, are working to develop a machine learning based 3D magnetic resonance imaging (MRI) rectal cancer imaging technique. Their eventual goal is to reduce scan time and alleviate the workload on radiologists.

Predicting Local Rectal Tumor Relapse in Patients Receiving Non-Operative Management

• Jack Virostko, affiliated faculty at the Oden Institute and associate professor of Diagnostic Medicine at Dell Medical School, and Venkateswar Surabhi, professor of Diagnostic Radiology at MD Anderson, are tackling the problem of differentiating active rectal tumors in patients receiving non-operative management. Their plans include longitudinal surveillance MRI and to develop biology-based mathematical models to predict rectal tumor recurrence. 

Foundational advancement toward practical integration of digital twins into a clinical workflow

• Michael Kapteyn, research associate at the Oden Institute with the Willcox Reserach Group, and Chengyue Wu, Postdoctoral Research Fellow and assistant professor of Imaging Physics at MD Anderson, hope to integrate digital twin technology into oncology by developing a prototype cancer patient digital twins (CPDTs) deployment platform designed for integration into clinical workflow.

Advancing High-Grade Glioma Diagnosis and Treatment: Explainable MRI and Genomic Correlations of Invasive Non- Enhancing Tumors

• James Carson, Life Sciences Computing Directorate at TACC, and Christopher Chad Quarles, professor of Cancer Systems Imaging at MD Anderson, aim to develop computational models to identify novel magnetic resonance imaging (MRI) based biomarkers. Their goal is to enhance diagnostic precision and ultimately improve future target therapies. 

“This collaboration with UT Austin faculty underscores the importance of multidisciplinary approaches to overcome the toughest challenges in cancer research,” Hazle said. “We hope these new projects will build on the successes of previous years and lead to impactful externally funded awards.” 

Update on 2023 seed funding projects:

Imaging-based forecasting of prostate cancer histopathology and progression during active surveillance

• Thomas J.R. Hughes, of UT Austin's Department of Aerospace Engineering and Engineering Mechanics and lead of the Oden Institute's Computational Mechanics Group, and Aradhana Venkatesan, professor of Abdominal Imaging at MD Anderson and Guillermo  Lorenzo, at the Oden Institute said through their research, they have constructed a computational pipeline that integrates MRI and clinical data within a patient-specific biomechanistic model to forecast prostate cancer growth over the specific organ anatomy of the patient. "Using local and global biomechanistic metrics calculated from our predictions, we can also forecast the risk of clinical progression of prostate cancer, which is a central driver of oncological decision-making."

Predicting the response of sarcoma to neoadjuvant therapy via imaging-based modeling

• PIs David Hormuth at the Oden Institute and Behrang Amini, with MD Anderson, developed an image-based model of undifferentiated pleomorphic sarcoma (UPS, a rare soft-tissue sarcoma) response to chemotherapy and radiotherapy. Using their model, they were able to predict total tumor cellularity at the end of chemotherapy and radiotherapy with a high degree of accuracy (concordance correlation coefficient > 0.71 and 0.91 respectively). Their work was presented at the Biomedical Engineering Society Annual Meeting (October 23-26,2024). 

Development of a processing pipeline for automated longitudinal mammography analysis in a large prospective breast cancer screening cohort

• Edward Castillo and Chengyue Wu, both at the Oden Institute and Olena Weaver, associate professor of Breast Imaging at MD Anderson said they have developed a pipeline that uses Natural Language Processing to generate maps that help localize masses referenced in Radiology reports, and a framework to longitudinally analyze mammography with serial image registration. "Integration of our NLP and longitudinal analysis methodology provided a novel opportunity to quantitatively track temporal evolution of breast features in suspicious areas observed during screening, so as to improve specificity of breast cancer early detection.” The team was granted a no-cost extension to the end of 2025.

 

Jointly released with The University of Texas MD Anderson Cancer Center

The Oden Institute for Computational Engineering and Sciences mission is to provide the inclusive interdisciplinary environment that enables outstanding research, fosters high-impact collaborations, and advances graduate education in the field of computational science and engineering. The Institute brings together 132 faculty representing 23 academic departments and research units, and 6 schools and colleges, including the Cockrell School of Engineering, the College of Natural Sciences, the Dell Medical School, the Jackson School of Geosciences, the School of Information Sciences, and the McCombs School of Business.

Oden Institute for Computational Engineering and Sciences
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