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.
Read More
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, Division of Diagnostic Imaging, The University of Texas MD Anderson Cancer Center, Houston, TX
Assistant Professor (Joint appointment), Department of Biostatistics, Division of Diagnostic Imaging, 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
Academic Appointments
Postdoctoral Fellow, Department of Oden Institute for Computational Engineering and Sciences, The University of Texas at Austin, Austin, Texas, 2020 - 2023
Other Appointments/Responsibilities
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
| 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 | Travel Grants for the Association for Women in Mathematics 2023 Research Symposium, AWM |
| 2023 | USNCCM17 Best Presentation Award (second place in postdoc category), Female Researchers Chapter (FRC) of the International Association for Computational Mechanics (IACM) |
| 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 | Trainee Stipend for ISMRM 28th Annual Meeting, ISMRM |
| 2020 | Graduate Student Professional Development Award, The University of Texas at Austin |
| 2020 | Cockrell School of Engineering fellowship, The University of Texas at Austin |
| 2020 | Magna Cum Laude 2020 ISMRM Merit Award, ISMRM |
| 2020 | Selected Attendee of Rising Stars 2020 Workshop, Rising Star |
| 2019 | Trainee Stipend for ISMRM 27th Annual Meeting, ISMRM |
| 2019 | Cockrell School of Engineering fellowship, The University of Texas at Austin |
| 2018 | Cockrell School of Engineering fellowship, The University of Texas at Austin |
| 2017 | Cockrell School of Engineering fellowship, The University of Texas at Austin |
| 2016 | Honorary Rank (Top 3%), USTC |
| 2016 | Cockrell School of Engineering fellowship, The University of Texas at Austin |
| 2016 | Excellent Graduation Thesis (Top 5%), USTC |
| 2015 | Grants for Training Plan of National Basic Subject Top-Notch Talent, Ministry of Education of China |
| 2015 | Yang Ya Foundation Scholarship (Top 5%), Yang Ya Foundation |
| 2015 | J. Z. Chen Scholarship for Research Potential, ZLR Valeon Scholar Program |
| 2014 | Grants for Training Plan of National Basic Subject Top-Notch Talent, Ministry of Education of China |
| 2014 | Outstanding Student Scholarship, silver medalist (Top 5%), USTC |
| 2013 | Grants for Training Plan of National Basic Subject Top-Notch Talent, Ministry of Education of China |
| 2013 | National Scholarship (Top 3%), Ministry of Education of China |
| 2012 | 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 Publications
Peer-Reviewed Articles
- 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. PMID: 38844842.
- 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. Radiol Artif Intell None(None):e240124, 2024. PMID: 39503605.
- Christenson, C, LaMonica, M, Yankeelov, TE, Yankeelov, TE, Yankeelov, TE, Hormuth, DA, Yankeelov, TE, Wu, C, Hormuth, DA, Stowers, CE, Yankeelov, TE, Wu, C, 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. PMID: None.
- 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. PMID: 39032243.
- Wu, C, Hormuth, DA, 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. Journal of Medical Imaging 11(2), 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.
- 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. PMID: None.
- Phillips CM, Lima E, Wu C, Jarrett AM, Zhou Z, Elshafeey N, Ma J, Rauch GM, Yankeelov TE. Assessing the invertibility of model selection frameworks for the prediction of patient outcomes in the clinical breast cancer setting. Journal of Computational Science 69(102006), 2023. e-Pub 2023. PMID: None.
- 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, 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.
- 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, 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. 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.
- 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. PMID: None.
- 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.
- Wu C, Hormuth DA, Easley TO, Pineda F, Karczmar GS, Yankeelov TE. Systematic evaluation of MRI-based characterization of tumor-associated vascular morphology and hemodynamics via a dynamic digital phantom. Journal of Medical Imaging. PMID: None.
Other Articles
- 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. 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. 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. 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. PMID: 34208448.
Grant & Contract Support
| 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 |
| Title: | Foundational advancement toward practical integration of digital twins into a clinical workflow |
| Funding Source: | Internal Pilot Project, The Joint Center for Computational Oncology (JCCO) |
| Role: | PI |
| 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 |
| Title: | Radiopathology-based computational models to predict and improve triple-negative breast cancer response to neoadjuvant therapy |
| Funding Source: | NIH/NCI |
| Role: | PI |
| Title: | Modeling the spatial biophysical dynamics of the brain tumor microenvironment |
| Funding Source: | Mayo Clinic |
| Role: | PI |
| Title: | Targeting Cancer-related Bone Loss for Cognitive Impairment and Neuropathy in Breast Cancer Patients |
| Funding Source: | Department of Defense (DOD) |
| Role: | Co-I |
| Title: | Evaluating and improving breast cancer risk prediction tools for Mexican-American women |
| Funding Source: | Cancer Prevention & Research Institute of Texas (CPRIT) |
| Role: | Co-I |
| Title: | Radio-Pathological Image Fusion |
| Funding Source: | Biostatistics and Research Decision Sciences (BARDS)/Merck |
| Role: | PI |
| Title: | Radio-pathological image fusion to improve cancer outcome prediction and microenvironment interpretation |
| Funding Source: | American Cancer Society (ACS) |
| Role: | PI |
| Title: | An ethical, equitable, and explainable (3E) multimodal AI algorithm to assess the risk of harboring and developing breast cancer |
| Funding Source: | NIH/OD |
| Role: | Co-I |
| Title: | Automatic longitudinal mammography analysis in a large prospective breast cancer screening cohort |
| Funding Source: | The Fund for Innovation in Cancer Informatics |
| Role: | Principal Investigator-MDACC |
Patient Reviews
CV information above last modified November 14, 2024