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
Dual/Joint/Adjunct Appointment
Assistant Professor, Department of Breast Imaging, Division of Diagnostic Imaging, The University of Texas MD Anderson Cancer Center, Houston, TX
Assistant Professor, Department of Biostatistics, Division of Basic Science Research, The University of Texas MD Anderson Cancer Center, Houston, TX
Education & Training
Degree-Granting Education
| 2020 | The University of Texas at Austin, Austin, TX, USA, PHD, Biomedical Engineering |
| 2016 | University of Science & Technology of China (USTC), Heifei, CHN, BS, Biosciences |
Selected Publications
Peer-Reviewed Articles
- Yankeelov TE, Hormuth DA, Lima EABF, 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 2023. PMID: 38169893.
- 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.
- 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 2022. PMID: 36468624.
- Chaudhuri A, Pash G, Hormuth DA, Lorenzo G, Kapteyn M, Wu C, Lima EABF, 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.
- 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. 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, Lorenzo G, Hormuth DA, Lima EABF, 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.
- 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.
- Hormuth DA, Phillips CM, Wu C, Lima EABF, 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.
- 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, Lima EABF, 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. 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. PMID: 30854441.
- 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 2018. PMID: 30368906.
- 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. PMID: 30854448.
- 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. e-Pub 2018. PMID: 29570895.
Patient Reviews
CV information above last modified September 09, 2024