Publications

2023

Yankeelov TE, Hormuth II DA, Lima EABF, Lorenzo G, Wu C, Okereke LC, Rauch GM, Venkatesan A, Chung C. Designing clinical trials for patients who are not average. iScience, 2023. https://doi.org/10.1016/j.isci.2023.108589

Christenson C, Wu C, Hormuth II DA, Huang S, Bao A, Brenner A, Yankeelov TE. Predicting the spatio-temporal response of recurrent glioblastoma treated with rhenium-186 labelled nanoliposomes. Brain Multiphysics, 2023;5:100084. https://doi.org/10.1016/j.brain.2023.100084

Chaudhuri A, Pash G, Hormuth II DA, Lorenzo G, Kapteyn M, Wu C, Lima EA, Yankeelov TE, Willcox K. Predictive Digital Twin for Optimizing Patient-Specific Radiotherapy Regimens under Uncertainty in High-Grade Gliomas. Frontiers in Artificial Intelligence. 2023;6. https://doi.org/10.3389/frai.2023.1222612

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. 2023;69:102006. https://doi.org/10.1016/j.jocs.2023.102006

Slavkova KP, DiCarlo JC, Wadhwa V, Wu C, Virostko J, Kumar S, Yankeelov TE, Tamir JI. An untrained deep learning method for reconstructing dynamic magnetic resonance images from accelerated model-based data. Magnetic Resonance in Medicine. 2023;89(4):1617-1633. https://doi.org/10.1002/mrm.29547

2022

Wu C, Jarrett AM, Zhou Z, Elshafeey N, Adrada BE, Candelaria RP, Mohamed R, Boge M, Huo L, White J, Tripathy D, Valero V, Litton J, 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 Research. 2022;82(18):3394–3404. https://doi.org/10.1158/0008-5472.CAN-22-1329

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 digital twins for clinical oncology. Biophysics Reviews. 2022;3(2):021304. https://doi.org/10.1063/5.0086789

Wu C, Hormuth DA, Lorenzo G, Jarrett AM, Pineda F, Karczmar GS, Yankeelov TE. Towards patient-specific optimization of neoadjuvant treatment protocols for breast cancer based on image-based fluid dynamics. IEEE Transactions on Biomedical Engineering. 2022. https://doi.org/10.1109/TBME.2022.3168402

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. International Journal for Numerical Methods in Biomedical Engineering. 2022;38(7):e3612. https://doi.org/10.1002/cnm.3612

2021

Wu C, Hormuth DA, Easley T, Pineda F, Eijkhout V, Karczmar GS, Yankeelov TE. An in silico validation framework of quantitative DCE-MRI techniques based on digital phantom. Medical Image Analysis. 2021;73:102186. https://doi.org/10.1016/j.media.2021.102186

Hormuth DA II, 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. 2021; 13(12):3008. https://doi.org/10.3390/cancers13123008

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. Nature Protocols. 2021;16(11):5309-5338. https://doi.org/10.1038/s41596-021-00617-y

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. 2021;7:045012. https://doi.org/10.1088/2057-1976/ac02a6

Hormuth DA, Jarrett AM, Lorenzo G, Lima EABF, Wu C, Chung C, Patt D, Yankeelov TE. Math, magnets, and medicine: enabling personalized oncology. Expert Review of Precision Medicine and Drug Development. 2021;6(2):79-81. https://doi.org/10.1080/23808993.2021.1878023

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. European Journal of Radiology. 2021;136:109534. https://doi.org/10.1016/j.ejrad.2021.109534

2020

Wu C, Hormuth DA, Oliver TA, Pineda F, Karczmar GS, Lorenzo G, Moser RD, Yankeelov TE. Patient-specific characterization of breast cancer hemodynamics using image-guided computational fluid dynamics. IEEE Transactions on Medical Imaging. 2020;39(9):2760-2771. https://doi.org/10.1109/TMI.2020.2975375

Jarrett AM, Hormuth II 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. 2020;22(12):820-30. https://doi.org/10.1016/j.neo.2020.10.011

Bell LC, Semmineh N, An H, Eldeniz C, Wahl R, Schmainda KM, Prah MA, Erickson BJ, Korfiatis P, Wu C, Sorace AG. 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. 2020;6(2):203. https://doi.org/10.18383/j.tom.2020.00012

2019

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. Magnetic Resonance in Medicine. 2019;81(3):2147-2160. https://doi.org/10.1002/mrm.27529

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. 2019;116(3):323a-324a. https://doi.org/10.1016/j.bpj.2018.11.1754

Woodall RT, Hormuth DA, Abdelmalik MRA, Wu C, Feng X, Phillips WT, Bao A, Hughes TJR, Brenner AJ, Yankeelov TE. Integrating quantitative imaging and computational modeling to predict the spatiotemporal distribution of 186Re nanoliposomes for recurrent glioblastoma treatment.  Medical Imaging 2019: Physics of Medical Imaging. International Society for Optics and Photonics. 2019;10948:109483M. https://doi.org/10.1117/12.2512867

Virostko J, Sorace AG, Wu C, Ekrut DA, 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. 2019;5(1):44. https://doi.org/10.18383/j.tom.2018.00019

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 multi-site rCBV consistency from DSC-MRI imaging protocols and post-processing software across the NCI Quantitative Imaging Network sites using a Digital Reference Object (DRO). Tomography. 2019;5(1):110. https://doi.org/10.18383/j.tom.2018.00041

2018

Sorace AG, Wu C, Barnes SL, Jarrett AM, Avery S, Patt D, Goodgame B, Luci JJ, Kang H, Abramson RG, Yankeelov TE. Repeatability, reproducibility, and accuracy of quantitative MRI of the breast in the community radiology setting. Journal of Magnetic Resonance Imaging. 2018;48(3):695-707. https://doi.org/10.1002/jmri.26011