Chengyue Wu, PhD
Department of Imaging Physics, Division of Diagnostic Imaging
About Dr. Chengyue Wu
Dr. Chengyue Wu is an Assistant Professor in the Department of Imaging Physics, University of Texas MD Anderson Cancer Center, with joint appointments in the Department of Biostatistics and Breast Imaging, and affiliation with Institute for Data Science in Oncology. Dr. Wu’s research interests focus on computational oncology, especially integrating emerging biomedical imaging techniques with computational modeling, to improve the diagnosis, prognosis, and treatment of human cancers. She has authored or co-authored over 25 journal articles and over 60 conference abstracts or papers, and has been regularly serving as a co-organizer, executive committee member, and moderator/reviewer for multiple scientific conferences. She was awarded the prestigious H. D. Landahl Mathematical Biophysics Award in 2023 from the Society of Mathematical Biology for her contributions to both diagnosing breast cancers and predicting their response to therapy, as well as the ready generalizability of her techniques to other solid tumor types.
Present Title & Affiliation
Primary Appointment
Assistant Professor, Department of Imaging Physics - Research, Division of Diagnostic Imaging, The University of Texas MD Anderson Cancer Center, Houston, TX
Assistant Professor (Joint appointment), Department of Breast Imaging, The University of Texas MD Anderson Cancer Center, Houston, TX
Assistant Professor (Joint appointment), Department of Biostatistics, The University of Texas MD Anderson Cancer Center, Houston, TX
Dual/Joint/Adjunct Appointment
Assistant Professor, Department of Breast Imaging, The University of Texas MD Anderson Cancer Center, Houston, TX
Assistant Professor, Department of Biostatistics, The University of Texas MD Anderson Cancer Center, Houston, TX
Assistant Professor, Department of Imaging Physics - Research, The University of Texas MD Anderson Cancer Center, Houston, TX
Education & Training
Degree-Granting Education
| 2020 | The University of Texas at Austin, Austin, Texas, US, Biomedical Engineering, Ph.D |
| 2016 | University of Science & Technology of China (USTC), Heifei, CN, Biosciences, BS |
Postgraduate Training
| 2020-2023 | Postdoctoral Fellow, Oden Institute for Computational Engineering and Sciences, Austin, Texas |
Experience & Service
Faculty Academic Appointments
Postdoctoral Fellow, Department of Oden Institute for Computational Engineering and Sciences, The University of Texas at Austin, Austin, Texas, 2020 - 2023
Other Professional Positions
Regular Member, The University of Texas MD Anderson Cancer Center, Houston, TX, 2024 - 2029
Graduate Research Assistant, The University of Texas at Austin, Austin, TX, 2016 - 2020
Honors & Awards
| 2025 - Present | USNCCM18 Travel Award, U.S. National Congress on Computational Mechanics |
| 2024 | Nominated Member, Academy’s Council of Early Career Investigators in Imaging (CECI²) Class of 2024 - 2025 |
| 2023 | NSF Sponsored Scholarship for attending The Academic Life Workshop, 17th U.S. National Congress on Computational Mechanics |
| 2023 | H. D. Landahl Mathematical Biophysics Award, Society of Mathematical Biology |
| 2023 | USNCCM17 Best Presentation Award (second place in postdoc category), Female Researchers Chapter (FRC) of the International Association for Computational Mechanics (IACM) |
| 2023 | Travel Grants for the Association for Women in Mathematics 2023 Research Symposium, AWM |
| 2022 | Travel Grants for the Association for Women in Mathematics 2022 Research Symposium, AWM |
| 2022 | Trainee Stipend for Joint Annual Meeting ISMRM-ESMRMB & ISMRT 31st Annual Meeting, ISMRM |
| 2022 | Trainee Stipend for ISMRM Workshop on Cancer Imaging, ISMRM |
| 2022 | Travel Award for NIDDK Pancreatic Disease Workshop Short Talk Speaker, NIDDK |
| 2021 | Finalist, ISMRM Junior Fellow Symposium: Shark Tank, ISMRM |
| 2020 | Selected Attendee of Rising Stars 2020 Workshop, Rising Star |
| 2020 | Trainee Stipend for ISMRM 28th Annual Meeting, ISMRM |
| 2020 | Magna Cum Laude 2020 ISMRM Merit Award, ISMRM |
| 2020 | Graduate Student Professional Development Award, The University of Texas at Austin |
| 2019 | Trainee Stipend for ISMRM 27th Annual Meeting, ISMRM |
| 2016 | Excellent Graduation Thesis (Top 5%), USTC |
| 2016 | Honorary Rank (Top 3%), USTC |
| 2016 - 2020 | Cockrell School of Engineering fellowship, The University of Texas at Austin |
| 2015 | J. Z. Chen Scholarship for Research Potential, ZLR Valeon Scholar Program |
| 2015 | Yang Ya Foundation Scholarship (Top 5%), Yang Ya Foundation |
| 2014 | Outstanding Student Scholarship, silver medalist (Top 5%), USTC |
| 2013 | National Scholarship (Top 3%), Ministry of Education of China |
| 2012 - 2015 | Grants for Training Plan of National Basic Subject Top-Notch Talent, Ministry of Education of China |
| 2012 | Excellent Freshman Award, USTC Initiative Foundation |
Professional Memberships
Selected Presentations & Talks
Local Presentations
- 2025. Predicting Cervical Cancer Response to Chemoradiation Using MRI-Based Mathematical Modeling. Poster. IEEE 22nd International Symposium on Biomedical Imaging. Houston, Texas, US.
- 2025. Spatio-Temporal Attention Fusion Model for Breast Cancer Detection. Poster. IEEE 22nd International Symposium on Biomedical Imaging. Houston, Texas, US.
- 2025. Image-guided cancer patient digital twins for personalized healthcare. Invited Seminar Talk, Institute for Data Science in Oncology Focus Area Forum. Houston, Texas, US.
National Presentations
- 2025. MRI-informed mathematical model to practically guide patient-specific optimization of triple-negative breast cancer response to neoadjuvant chemotherapy. Poster. 18th U.S. National Congress on Computational Mechanics (USNCCM18). Chicago, IL, US.
- 2025. MRI-informed personalized predictions of tumor progression to inform active surveillance of prostate cancer. Poster. 18th U.S. National Congress on Computational Mechanics (USNCCM18). Chicago, IL, US.
- 2025. Applying an MRI-based mathematical model to predict the response of cervical cancer to chemoradiation: Preliminary results. Poster. ISMRM Annual Meeting. Honolulu, HI, US.
- 2025. Intravoxel Incoherent Motion (IVIM) MRI of the Human Pancreas Detects Altered Glucose-Stimulated Pancreas Perfusion in Type 1 Diabetes. Poster. ISMRM Annual Meeting. Honolul, HI, US.
- 2025. Predicting and optimizing the response of breast cancer patients to neoadjuvant therapy using a multiscale computational model. Poster. AACR Annual Meeting 2025. Chicago, IL, US.
- 2025. Image-guided cancer patient digital twins for personalized healthcare. Invited, US.
- 2025. MRI-informed mathematical model to guide patient-specific optimization triple negative breast cancer response to neoadjuvant chemotherapy. Invited. 2025 Joint Mathematics Meetings (JMM 2025). Seattle, WA, US.
- 2024. Retrospective validation of digital twin-based predictions of personalized triple negative breast cancer response to neoadjuvant therapy regimens. Poster. San Antonio, TX, US.
- 2024. Using pre-treatment MRI data to drive an integrated mechanism- and data-driven model to predict the response of breast cancer to therapy. Invited. SIAM Conference in Imaging Science. Atlanta, GA, US.
- 2023. Optimizing therapeutic regimens via digital twins to improve triple negative breast cancer response to neoadjuvant therapy. Poster. San Antonio Breast Cancer Symposium. San Antonio, TX, US.
- 2023. Integrating mechanism-based and data-driven modeling to predict the response of triple negative breast cancer to therapy. Poster. San Antonio Breast Cancer Symposium. San Antonio, TX, US.
- 2023. Optimized Patient-Specific Catheter Placement for Convection-Enhanced Nanoparticle Delivery in Recurrent Glioblastoma. Invited. NCI 9th Computational Approaches for Cancer Workshop. Denver, CO, US.
- 2023. Introducing mechanical stress into a reduced order model for breast cancer response to chemotherapy. Invited. Biomedical Engineering Society annual meeting. Seattle, WA, US.
- 2023. Personalized MRI-informed predictions of prostate cancer growth during active surveillance. Invited. SMB Annual Meeting. Columbus, OH, US.
- 2023. Optimization of a longitudinal imaging protocol to monitor the response of breast cancer to neoadjuvant therapy via Bayesian-based data assimilation. Invited. SMB Annual Meeting. Columbus, OH, US.
- 2023. Patient-specific, imaging-informed computational forecasting of prostate cancer growth during active surveillance. Invited. 17th US National Conference on Computational Mechanics. Albuquerque, NM, US.
- 2023. Developing MRI-based digital-twins via mathematical modeling and deep learning to predict the response of triple-negative breast cancer to neoadjuvant therapy. Conference. AACR Annual Meeting. Orlando, FL, US.
- 2023. Quantification of tumor-associated vasculature as an imaging biomarker for monitoring the response of triple-negative breast cancer to neoadjuvant chemotherapy. Conference. AACR Annual Meeting. Orlando, FL, US.
- 2023. Patient-specific, organ-scale forecasting of prostate cancer growth during active surveillance. Poster. AACR Annual Meeting. Orlando, FL, US.
- 2022. MRI-based digital twins forecast patient-specific treatment responses to neoadjuvant chemotherapy in triple-negative breast cancer. Invited. ISMRM Workshop on Cancer Imaging: From Discovery to Diagnosis. Pacific Grove, CA, US.
- 2022. Forecasting treatment response to neoadjuvant therapy in triple-negative breast cancer via an image-guided digital twin. Poster. AACR Annual Meeting. New Orleans, LA, US.
- 2022. A biology-based, mathematical model to predict the response of recurrent glioblastoma to treatment with 186Re-labeled nanoliposomes. Poster. AACR Annual Meeting. New Orleans, LA, US.
- 2021. Towards image-guided modeling of patient-specific rhenium-186 nanoliposome distribution via convection-enhanced delivery for glioblastoma multiforme. Poster. SNO Annual Meeting. Boston, MA, US.
- 2021. Optimized patient-specific catheter placement for convection-enhanced nanoparticle delivery in GBM. Invited. BMES Annual Meeting. Orlando, FL, US.
- 2021. Kinetic parameters derived from ultrafast DCE-MRI to predict breast cancer response to neoadjuvant chemotherapy. Poster. ISMRM & SMRT Annual Meeting & Exhibition - An Online Experience, US.
- 2021. Predicting therapeutic response via quantitative MRI. Poster. ISMRM & SMRT Annual Meeting & Exhibition - An Online Experience, US.
- 2021. Towards patient-specific optimization of neoadjuvant treatment protocols for breast cancer based on image-based fluid dynamics. Poster. AACR Annual Meeting, US.
- 2020. The Rate of Parenchymal Enhancement During DCE-MRI Reflects Response to Neoadjuvant Therapy. Poster. 43rd Annual SABCS, US.
- 2020. Investigating the feasibility of performing quantitative DCE-MRI in an abbreviated breast examination. Poster. 43rd Annual SABCS, US.
- 2020. Optimizing neoadjuvant regimens for individual breast cancer patients generated by a mathematical model utilizing quantitative magnetic resonance imaging data: Preliminary results. Poster. 43rd Annual SABCS, US.
- 2020. Systematic Evaluation and Optimization of Methods for Characterizing Vascular Features on MRI via a Dynamic Digital Phantom. Invited. BMES Annual Meeting, US.
- 2020. Evaluating the use of rCBV as a tumor grade classifier across NCI Quantitative Imaging Network sites with varying imaging protocols and post-processing methods: Phase II of the DSC-MRI DRO Challenge. Poster. ISMRM & SMRT Virtual Conference & Exhibition, US.
- 2020. Quantifying heterogeneity in DW-MRI and DCE-MRI data of breast cancer for the prediction of treatment response: Preliminary results. Poster. ISMRM & SMRT Virtual Conference & Exhibition, US.
- 2020. Modeling of the spatio-temporal evolution of tumor vasculature to improve predictions of breast cancer response to neoadjuvant chemotherapy regimens. Invited. SMB Annual Meeting, US.
- 2020. Characterization of patient-specific drug delivery for breast cancer using image-guided computational fluid dynamics. Poster. AACR Annual Meeting, US.
- 2020. Patient-specific neoadjuvant regimens for breast cancer generated by a mathematical model utilizing quantitative magnetic resonance imaging data. Poster. AACR Annual Meeting, US.
- 2020. Validation of dynamic contrast-enhanced MRI analyses via virtual MRI simulation on a dynamic digital phantom. Poster. ISMRM & SMRT Virtual Conference & Exhibition, US.
- 2020. A dynamic digital phantom with realistic vasculature and perfusion based on MR histology. Invited. ISMRM & SMRT Virtual Conference & Exhibition, US.
- 2019. SCIDOT-38. Development of an image-informed mathematical model of convection-enhanced delivery of nanoliposomes for individual patients. Poster. SNO 24th Annual Meeting & Education Day. Phoenix, AZ, US.
- 2019. Linking multi-scale imaging with multi-scale modeling to predict the response of tumors to therapy. Invited. BPS 63rd Annual Meeting. Baltimore, MD, US.
- 2019. Mechanism-based, mathematical modeling to predict the response of breast cancer to neoadjuvant therapy using patient-specific MRI data. Invited. The Cancer Imaging Program’s Quantitative Imaging Network (QIN) Annual meeting. Rockville, MD, US.
- 2019. Linking multi-scale imaging with multi-scale modeling to predict the response of tumors to therapy. Invited. Joint Mathematics Meetings (AMS-MAA). Baltimore, MD, US.
- 2018. Quantitative breast MRI to predict response to neoadjuvant therapy in community imaging centers: Preliminary results. Poster. 41st Annual SABCS. San Antonio, TX, US.
- 2018. Computational fluid dynamics characterizing flow through breast tumors using patient-specific geometries. Invited. BMES Annual Meeting. Atlanta, GA, US.
- 2018. Evaluating & Predicting Response of Breast Cancer to Neoadjuvant Therapy with an Imaging-Driven, Mathematical Model Accounting for Patient-Specific Therapeutic Regimens. Invited. ISMRM Workshop on Breast MRI: Advancing the State of the Art. Las Vegas, US.
- 2018. Quantitative MRI during neoadjuvant therapy for predicting breast cancer response in the community setting. Poster. AACR annual meeting. Chicago, IL, US.
- 2018. Magnetization transfer MRI performed during neoadjuvant therapy of breast cancer correlates with declines in tumor size. Poster. AACR-SNMMI Joint Conference on State-of-the-Art Molecular Imaging in Cancer Biology and Therapy. San Diego, CA, US.
- 2017. Repeatability and reproducibility of quantitative breast MRI in community imaging centers: Preliminary results. Poster. 40th Annual SABCS. San Antonio, TX, US.
- 2017. Automatic Tumor Associated Vasculature Detection and Dynamic Modeling: Preliminary Results. Invited. Frontiers in Biomedical Imaging Science VI. Nashville, TN, US.
- 2017. Automatic Segmentation and Tracking of Tumor Associated Vasculature Using High-temporal Resolution Dynamic Contrast Enhanced MRI of the Breast: Preliminary Results. Poster. ISMRM 25th Annual Meeting & Exhibition. Honolulu, HI, US.
- 2016. Detecting outliers in images of DNA molecules using functional data depth and morphological features. Invited. ENAR 2016 Spring Meeting. Austin, TX, US.
International Presentations
- 2025. MRI-informed mechanistic model to guide patient-specific optimization triple-negative breast cancer response to neoadjuvant chemotherapy. Invited. XI International Conference on Coupled Problems in Science and Engineering. Villasimius, IT.
- 2024. Patient-specific optimization of therapeutic regimens via digital twins to improve triple negative breast cancer response to neoadjuvant therapy. Invited. The 16th World Congress on Computational Mechanics (WCCM 2024). British Columbia, CA.
- 2024. Predicting the response of I-SPY 2 breast cancer patients to treatment using a biology-based mathematical model calibrated with quantitative MRI. Poster. ISMRM & ISMRT Annual Meeting & Exhibition. Singapore, SG.
- 2023. Integrating quantitative MRI with computational modeling to predict the response of breast cancers to neoadjuvant therapy. Invited. 10th International Congress on Industrial and Applied Mathematics. Tokyo, JP.
- 2022. Reduced Field-of-View Intravoxel Incoherent Motion of the Human Pancreas Reflects BiphasicResponse to Glucose Ingestion. Poster. Joint Annual Meeting ISMRM-ESMRMB. London, GB.
- 2019. Employing quantitative imaging data to personalize mathematical models of the tumor microenvironment and response to therapies. Invited. CRUK-AACR Joint Conference on Engineering and Physical Sciences in Oncology. London, GB.
- 2019. A new approach to quantitative measurement of breast tumor blood flow, capillary permeability, and interstitial pressure. Poster. ISMRM 27th Annual meeting & Exhibition. Motnreal, CA.
- 2019. Parenchymal Enhancement in Peritumoral Breast Tissue During DCE-MRI Reflects Response to Neoadjuvant Therapy. Poster. ISMRM 27th Annual Meeting & Exhibition. Montreal, CA.
- 2019. Evaluating multi-site rCBV consistency from DSC-MRI imaging protocols and post-processing software across the NCI Quantitative Imaging Network (QIN) sites using a Digital Reference Object (DRO). Poster. ISMRM 27th Annual Meeting & Exhibition. Montreal, CA.
- 2019. Patient-specific characterization of breast tumor-associated flow using image-guided computational fluid dynamics. Poster. ISMRM 27th Annual Meeting & Exhibition. Montreal, CA.
- 2018. Quantitative analysis of ultra-fast DCE-MRI to identify vascular inputs and outputs in breast tumors. Poster. Joint Annual Meeting ISMRM-ESMRMB. Paris, FR.
- 2018. Magnetization Transfer MRI of Breast Cancer Response to Neoadjuvant Therapy: Preliminary Results. Poster. Joint Annual Meeting ISMRM-ESMRMB. Paris, FR.
- TBD. Invited. The 16th World Congress on Computational Mechanics (WCCM 2024), CA.
Formal Peers
- 2024. Image-guided mathematical modeling for patient-specific prediction and optimization of breast cancer response to neoadjuvant therapy. Invited. Portland, OR, US.
- 2023. Forecasting patient-specific treatment response to neoadjuvant systemic therapy in triple negative breast cancer via MRI-based digital twins. Invited.
- 2023. Towards a practical framework for n = 1 clinical trials. Invited. Albuquerque, NM, US.
- 2023. MRI-based digital twins to forecast treatment response in breast cancer patients. Invited.
- 2023. : MRI-based digital twins for the patient-specific prediction and optimization of neoadjuvant chemotherapy response in triple-negative breast cancer. Invited.
- 2023. Introduce the applications of medical imaging and computational modeling in the investigation of tissue microenvironments with research examples. Visiting. Austin, TX, US.
- 2022. Forecasting patient-specific treatment response to neoadjuvant chemotherapy in triple-negative breast cancer via MRI-based digital twins. Invited. Bethesda, MD, US.
- 2022. MRI Reflects Increases in Pancreas Perfusion Following Glucose Ingestion. Invited. Bethesda, MD, US.
- 2022. Forecasting patient-specific treatment response to neoadjuvant systemic therapy in triple negative breast cancer via mathematical modeling and quantitative magnetic resonance imaging. Invited, US.
- 2022. Introduce the applications of medical imaging and computational modeling in the investigation of tissue microenvironments with research examples. Visiting. Austin, TX, US.
- 2021. Image-informed Mathematical Modeling to Predict Patient-Specific Treatment Response to Neoadjuvant Systemic Therapy in Triple Negative Breast Cancer. Invited. Austin, TX, US.
- 2021. Image-guided drug delivery and tumor growth model for predicting breast cancer response to neoadjuvant therapy. Invited.
- 2021. Towards patient-specific prediction of breast cancer response to neoadjuvant therapy. Invited.
- 2021. Optimization of patient-specific neoadjuvant therapy regimens for breast cancer via image-guided fluid dynamics modeling. Invited, US.
- 2021. Introduce the applications of medical imaging and computational modeling in the investigation of tissue microenvironments with research examples. Visiting. Austin, TX, US.
- 2020. Patient-specific optimization of drug injection protocols for breast cancer based on image-based fluid dynamics simulation. Invited.
- 2020. Introduce the applications of medical imaging and computational modeling in the investigation of tissue microenvironments with research examples. Visiting. Austin, TX, US.
Grant & Contract Support
| Date: | 2025 - 2026 |
| Title: | Automated AI Pipeline for Interpretable Longitudinal Mammography Analysis |
| Funding Source: | The Fund for Innovation in Cancer Informatics |
| Role: | PI |
| ID: | FP00025060 |
| Date: | 2024 - 2026 |
| Title: | Identify imaging biomarkers associated with interval breast cancer in women with a personal history of breast cancer |
| Funding Source: | MDACC Internal Research Grant |
| Role: | PI |
| Date: | 2024 - 2025 |
| Title: | Foundational advancement toward practical integration of digital twins into a clinical workflow |
| Funding Source: | The Joint Center for Computational Oncology (JCCO) |
| Role: | PI |
| Date: | 2023 - 2025 |
| Title: | Development of a processing pipeline for automated longitudinal mammography analysis in a large prospective breast cancer screening cohort |
| Funding Source: | The Joint Center for Computational Oncology (JCCO) |
| Role: | Co-PI |
| ID: | 62935 |
Selected Publications
Peer-Reviewed Articles
- Christenson, C, Wu, C, Hormuth, DA, Ma, J, Yam, C, Rauch, GM, Yankeelov, TE. Personalizing neoadjuvant chemotherapy regimens for triple-negative breast cancer using a biology-based digital twin. npj Systems Biology and Applications 11(1), 2025. e-Pub 2025. PMID: 40410237.
- Valenzuela Perez, RF, Duran Sierra, EJ, Antony, M, Amini, B, Lo, S, Torres, KE, Benjamin, RS, Ma, J, Hwang, K, Stafford, RJ, Araujo, DM, Bishop, AJ, Ratan, R, Wang, W, Espinoza, J, Valenzuela, PV, Wu, C, Madewell, JE, Murphy Jr, WA, Costelloe, C. Building a pre-surgical multiparametric-MRI-based morphologic, qualitative, semiquantitative, first and high-order radiomic predictive treatment response model for undifferentiated pleomorphic sarcoma to replace RECIST. Cancer Imaging 25(1), 2025. e-Pub 2025. PMID: 40281609.
- Wu C, Lima EABF, Stowers CE, Xu Z, Yam C, Son JB, Ma J, Rauch GM, Yankeelov TE. MRI-based digital twins to improve treatment response of breast cancer by optimizing neoadjuvant chemotherapy regimens. NPJ Digit Med 8(1):195, 2025. e-Pub 2025. PMID: 40195521.
- Stowers CE, Wu C, Xu Z, Kumar S, Yam C, Son JB, Ma J, Tamir JI, Rauch GM, Yankeelov TE. Combining Biology-based and MRI Data-driven Modeling to Predict Response to Neoadjuvant Chemotherapy in Patients with Triple-Negative Breast Cancer. Radiology: Artificial Intelligence 7(1), 2025. e-Pub 2025. PMID: 39503605.
- Xie, T, Gong, J, Zhao, Q, Wu, C, Wu, S, Peng, W, Gu, Y. Development and validation of peritumoral vascular and intratumoral radiomics to predict pathologic complete responses to neoadjuvant chemotherapy in patients with triple-negative breast cancer. BMC medical imaging 24(1), 2024. e-Pub 2024. PMID: 38844842.
- Christenson, C, Wu, C, Hormuth, DA, Stowers, CE, LaMonica, M, Ma, J, Rauch, GM, Yankeelov, TE. Fast model calibration for predicting the response of breast cancer to chemotherapy using proper orthogonal decomposition. Journal of Computational Science 82, 2024. e-Pub 2024. PMID: 40303598.
- Wu, C, Hormuth, DA, Christenson, C, Woodall, RT, Abdelmalik, MR, Phillips, WT, Hughes, TJ, Brenner, AJ, Yankeelov, TE. Image-guided patient-specific optimization of catheter placement for convection-enhanced nanoparticle delivery in recurrent glioblastoma. Computers in Biology and Medicine 179, 2024. e-Pub 2024. PMID: 39032243.
- Valenzuela RF, Duran-Sierra E, Canjirathinkal M, Amini B, Torres KE, Benjamin RS, Ma J, Wang WL, Hwang KP, Stafford RJ, Wu C, Zarzour AM, Bishop AJ, Lo S, Madewell JE, Kumar R, Murphy WA, Costelloe CM. Perfusion-weighted imaging with dynamic contrast enhancement (PWI/DCE) morphologic, qualitative, semiquantitative, and radiomics features predicting undifferentiated pleomorphic sarcoma (UPS) treatment response. Sci Rep, 2024. e-Pub 2024. PMID: 39289469.
- Wu C, Hormuth DA 2nd, Easley T, Pineda F, Karczmar GS, Yankeelov TE. Systematic evaluation of MRI-based characterization of tumor-associated vascular morphology and hemodynamics via a dynamic digital phantom. J Med Imaging (Bellingham) 11(2):024002, 2024. e-Pub 2024. PMID: 38463607.
- Christenson C, Wu C, Hormuth DA, Huang S, Bao A, Brenner A, Yankeelov TE. Predicting the spatio-temporal response of recurrent glioblastoma treated with rhenium-186 labelled nanoliposomes. Brain Multiphys 5, 2023. e-Pub 2023. PMID: 38187909.
- Chaudhuri A, Pash G, Hormuth DA, Lorenzo G, Kapteyn M, Wu C, EABF L, Yankeelov TE, Willcox K. Predictive digital twin for optimizing patient-specific radiotherapy regimens under uncertainty in high-grade gliomas. Front Artif Intell 6:1222612, 2023. e-Pub 2023. PMID: 37886348.
- Phillips, C, Lima, EA, Wu, C, Jarrett, AM, Zhou, Z, Elshafeey, N, Ma, J, Rauch, GM, Yankeelov, TE. Assessing the identifiability of model selection frameworks for the prediction of patient outcomes in the clinical breast cancer setting. Journal of Computational Science 69, 2023. e-Pub 2023.
- Slavkova KP, DiCarlo JC, Wadhwa V, Kumar S, Wu C, Virostko J, Yankeelov TE, Tamir JI. An untrained deep learning method for reconstructing dynamic MR images from accelerated model-based data. Magn Reson Med 89(4):1617-1633, 2023. e-Pub 2023. PMID: 36468624.
- Wu C, Hormuth DA, Lorenzo G, Jarrett AM, Pineda F, Howard FM, Karczmar GS, Yankeelov TE. Towards Patient-Specific Optimization of Neoadjuvant Treatment Protocols for Breast Cancer Based on Image-Guided Fluid Dynamics. IEEE Trans Biomed Eng 69(11):3334-3344, 2022. e-Pub 2022. PMID: 35439121.
- Wu C, Jarrett AM, Zhou Z, Elshafeey N, Adrada BE, Candelaria RP, Mohamed RMM, Boge M, Huo L, White JB, Tripathy D, Valero V, Litton JK, Yam C, Son JB, Ma J, Rauch GM, Yankeelov TE. MRI-Based Digital Models Forecast Patient-Specific Treatment Responses to Neoadjuvant Chemotherapy in Triple-Negative Breast Cancer. Cancer Res 82(18):3394-3404, 2022. e-Pub 2022. PMID: 35914239.
- Fritz M, Köppl T, Oden JT, Wagner A, Wohlmuth B, Wu C. A 1D-0D-3D coupled model for simulating blood flow and transport processes in breast tissue. Int J Numer Method Biomed Eng 38(7):e3612, 2022. e-Pub 2022. PMID: 35522186.
- Wu C, Hormuth DA, Easley T, Eijkhout V, Pineda F, Karczmar GS, Yankeelov TE. An in silico validation framework for quantitative DCE-MRI techniques based on a dynamic digital phantom. Med Image Anal 73:102186, 2021. e-Pub 2021. PMID: 34329903.
- Woodall RT, Hormuth Ii DA, Wu C, Abdelmalik MRA, Phillips WT, Bao A, Hughes TJR, Brenner AJ, Yankeelov TE. Patient specific, imaging-informed modeling of rhenium-186 nanoliposome delivery via convection-enhanced delivery in glioblastoma multiforme. Biomed Phys Eng Express 7(4), 2021. e-Pub 2021. PMID: 34050041.
- Virostko J, Kuketz G, Higgins E, Wu C, Sorace AG, DiCarlo JC, Avery S, Patt D, Goodgame B, Yankeelov TE. The rate of breast fibroglandular enhancement during dynamic contrast-enhanced MRI reflects response to neoadjuvant therapy. Eur J Radiol 136:109534, 2021. e-Pub 2021. PMID: 33454460.
- Hormuth DA, Jarrett AM, Lorenzo G, EABF L, Wu C, Chung C, Patt D, Yankeelov TE. Math, magnets, and medicine: enabling personalized oncology. Expert Rev Precis Med Drug Dev 6(2):79-81, 2021. e-Pub 2021. PMID: 34027102.
- Jarrett AM, Hormuth DA, Wu C, Kazerouni AS, Ekrut DA, Virostko J, Sorace AG, DiCarlo JC, Kowalski J, Patt D, Goodgame B, Avery S, Yankeelov TE. Evaluating patient-specific neoadjuvant regimens for breast cancer via a mathematical model constrained by quantitative magnetic resonance imaging data. Neoplasia 22(12):820-830, 2020. e-Pub 2020. PMID: 33197744.
- Wu C, Hormuth DA, Oliver TA, Pineda F, Lorenzo G, Karczmar GS, Moser RD, Yankeelov TE. Patient-Specific Characterization of Breast Cancer Hemodynamics Using Image-Guided Computational Fluid Dynamics. IEEE Trans Med Imaging 39(9):2760-2771, 2020. e-Pub 2020. PMID: 32086203.
- Bell LC, Semmineh N, An H, Eldeniz C, Wahl R, Schmainda KM, Prah MA, Erickson BJ, Korfiatis P, Wu C, Sorace AG, Yankeelov TE, Rutledge N, Chenevert TL, Malyarenko D, Liu Y, Brenner A, Hu LS, Zhou Y, Boxerman JL, Yen YF, Kalpathy-Cramer J, Beers AL, Muzi M, Madhuranthakam AJ, Pinho M, Johnson B, Quarles CC. Evaluating the Use of rCBV as a Tumor Grade and Treatment Response Classifier Across NCI Quantitative Imaging Network Sites: Part II of the DSC-MRI Digital Reference Object (DRO) Challenge. Tomography 6(2):203-208, 2020. e-Pub 2020. PMID: 32548297.
- Virostko J, Sorace AG, Wu C, Ekrut D, Jarrett AM, Upadhyaya RM, Avery S, Patt D, Goodgame B, Yankeelov TE. Magnetization Transfer MRI of Breast Cancer in the Community Setting: Reproducibility and Preliminary Results in Neoadjuvant Therapy. Tomography 5(1):44-52, 2019. e-Pub 2019. PMID: 30854441.
- Bell LC, Semmineh N, An H, Eldeniz C, Wahl R, Schmainda KM, Prah MA, Erickson BJ, Korfiatis P, Wu C Sorace AG, Yankeelov TE, Rutledge N, Chenevert TL, Malyarenko D, Liu Y, Brenner A, Hu LS, Zhou Y, Boxerman JL, Yen YF, Kalpathy-Cramer J, Beers AL, Muzi M, Madhuranthakam AJ, Pinho M, Johnson B, Quarles CC. Evaluating Multisite rCBV Consistency from DSC-MRI Imaging Protocols and Postprocessing Software Across the NCI Quantitative Imaging Network Sites Using a Digital Reference Object (DRO). Tomography 5(1):110-117, 2019. e-Pub 2019. PMID: 30854448.
- Wu C, Pineda F, Hormuth DA, Karczmar GS, Yankeelov TE. Quantitative analysis of vascular properties derived from ultrafast DCE-MRI to discriminate malignant and benign breast tumors. Magn Reson Med 81(3):2147-2160, 2019. e-Pub 2019. PMID: 30368906.
- Yankeelov T, Hormuth D, Jarrett A, Ernesto L, Wu C, Woodall R, Philips C. Multi-Scale Imaging to Enable Multi-Scale Modeling for Predicting Tumor Growth and Treatment Response. Biophysical Journal 116(3):323a-324a, 2019. e-Pub 2019.
- Sorace AG, Wu C, Barnes SL, Jarrett AM, Avery S, Patt D, Goodgame B, Luci JJ, Kang H, Abramson RG, Yankeelov TE, Virostko J. Repeatability, reproducibility, and accuracy of quantitative mri of the breast in the community radiology setting. J Magn Reson Imaging, 2018. e-Pub 2018. PMID: 29570895.
Review Articles
- Wu C, Andaloussi MA, Hormuth DA 2nd, Lima EABF, Lorenzo G, Stowers CE, Ravula S, Levac B, Dimakis AG, Tamir JI, Brock KK, Chung C, Yankeelov TE. A critical assessment of artificial intelligence in magnetic resonance imaging of cancer. Npj Imaging 3(1):15, 2025. e-Pub 2025. PMID: 40226507.
- Yankeelov TE, Hormuth DA, EABF L, Lorenzo G, Wu C, Okereke LC, Rauch GM, Venkatesan AM, Chung C. Designing clinical trials for patients who are not average. iScience 27(1):108589, 2024. e-Pub 2024. PMID: 38169893.
- Wu C, Lorenzo G, Hormuth DA, EABF L, Slavkova KP, DiCarlo JC, Virostko J, Phillips CM, Patt D, Chung C, Yankeelov TE. Integrating mechanism-based modeling with biomedical imaging to build practical digital twins for clinical oncology. Biophys Rev (Melville) 3(2):021304, 2022. e-Pub 2022. PMID: 35602761.
- Jarrett AM, Kazerouni AS, Wu C, Virostko J, Sorace AG, DiCarlo JC, Hormuth DA, Ekrut DA, Patt D, Goodgame B, Avery S, Yankeelov TE. Quantitative magnetic resonance imaging and tumor forecasting of breast cancer patients in the community setting. Nat Protoc 16(11):5309-5338, 2021. e-Pub 2021. PMID: 34552262.
- Hormuth DA, Phillips CM, Wu C, EABF L, Lorenzo G, Jha PK, Jarrett AM, Oden JT, Yankeelov TE. Biologically-Based Mathematical Modeling of Tumor Vasculature and Angiogenesis via Time-Resolved Imaging Data. Cancers (Basel) 13(12), 2021. e-Pub 2021. PMID: 34208448.
Patents
- Yankeelov, Karcsmar T, Wu G, Hormuth C, Oliver D, Moser TA, Pineda RD, Easley F, Barber T, Kim RF, Sheth B, Oto D, Abe A, Medved H, Fan M, Chatterjee X, Wang A, Shiyang. Characterization of Lesions via Determination of Vascular Metrics Using MRI Data. Patent Number: WO2021067853.
- Yankeelov, Jarrett T, Hormuth A, II Kazerouni DA, Wu A, Barnes C, Stephanie. Quantitative Magnetic Resonance Imaging and Tumor Forecasting. Patent Number: WO/2023/049207.
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CV information above last modified July 30, 2025