A mathematical model for predicting the spatiotemporal response of breast cancer cells treated with doxorubicin.
Miniere HJM, Lima EABF, Lorenzo G, Hormuth DA 2nd, Ty S, Brock A, Yankeelov TE
Cancer biology & therapy. 2024 Feb 27; 25: 2321769. doi: 10.1080/15384047.2024.2321769
PMID: 38411436
Patient-Specific, Mechanistic Models of Tumor Growth Incorporating Artificial Intelligence and Big Data.
Lorenzo G, Ahmed SR, Hormuth DA, Vaughn B, Kalpathy-Cramer J, Solorio L, Yankeelov TE, Gomez H
Annual review of biomedical engineering. 2024 Jun 20; 26: 529-560. doi: 10.1146/annurev-bioeng-081623-025834
PMID: 38594947
Breast Multiparametric MRI for Prediction of Neoadjuvant Chemotherapy Response in Breast Cancer: The BMMR2 Challenge.
Li W, Partridge SC, Newitt DC, Steingrimsson J, Marques HS, Bolan PJ, Hirano M, Bearce BA, Kalpathy-Cramer J, Boss MA, Teng X, Zhang J, Cai J, Kontos D, Cohen EA, Mankowski WC, Liu M, Ha R, Pellicer-Valero OJ, Maier-Hein K, Rabinovici-Cohen S, Tlusty T, Ozery-Flato M, Parekh VS, Jacobs MA, Yan R, Sung K, Kazerouni AS, DiCarlo JC, Yankeelov TE, Chenevert TL, Hylton NM
Radiology. Imaging cancer. ; 6: e230033. doi: 10.1148/rycan.230033
PMID: 38180338
Bilateral asymmetry of quantitative parenchymal kinetics at ultrafast DCE-MRI predict response to neoadjuvant chemotherapy in patients with HER2+ breast cancer.
Ren Z, Pineda FD, Howard FM, Fan X, Nanda R, Abe H, Kulkarni K, Karczmar GS
Magnetic resonance imaging. 2023 Aug 21; 104: 9-15. doi: 10.1016/j.mri.2023.08.003
PMID: 37611646
Designing clinical trials for patients who are not average.
Yankeelov TE, Hormuth DA 2nd, Lima EABF, Lorenzo G, Wu C, Okereke LC, Rauch GM, Venkatesan AM, Chung C
iScience. 2023 Nov 29; 27: 108589. doi: 10.1016/j.isci.2023.108589
PMID: 38169893
Predictive digital twin for optimizing patient-specific radiotherapy regimens under uncertainty in high-grade gliomas.
Chaudhuri A, Pash G, Hormuth DA 2nd, Lorenzo G, Kapteyn M, Wu C, Lima EABF, Yankeelov TE, Willcox K
Frontiers in artificial intelligence. 2023 Oct 11; 6: 1222612. doi: 10.3389/frai.2023.1222612
PMID: 37886348
Predicting response to combination evofosfamide and immunotherapy under hypoxic conditions in murine models of colon cancer.
Lima EABF, Song PN, Reeves K, Larimer B, Sorace AG, Yankeelov TE
Mathematical biosciences and engineering : MBE. ; 20: 17625-17645. doi: 10.3934/mbe.2023783
PMID: 38052529
Vascularized Hepatocellular Carcinoma on a Chip to Control Chemoresistance through Cirrhosis, Inflammation and Metabolic Activity.
Özkan A, Stolley DL, Cressman ENK, McMillin M, Yankeelov TE, Rylander MN
Small structures. 2023 Feb 17; 4: . pii: 2200403. doi: 10.1002/sstr.202200403
PMID: 38073766
Co-Clinical Imaging Metadata Information (CIMI) for Cancer Research to Promote Open Science, Standardization, and Reproducibility in Preclinical Imaging.
Moore SM, Quirk JD, Lassiter AW, Laforest R, Ayers GD, Badea CT, Fedorov AY, Kinahan PE, Holbrook M, Larson PEZ, Sriram R, Chenevert TL, Malyarenko D, Kurhanewicz J, Houghton AM, Ross BD, Pickup S, Gee JC, Zhou R, Gammon ST, Manning HC, Roudi R, Daldrup-Link HE, Lewis MT, Rubin DL, Yankeelov TE, Shoghi KI
Tomography (Ann Arbor, Mich.). 2023 May 11; 9: 995-1009. doi: 10.3390/tomography9030081
PMID: 37218941
Atrial fibrillation ablation outcome prediction with a machine learning fusion framework incorporating cardiac computed tomography.
Razeghi O, Kapoor R, Alhusseini MI, Fazal M, Tang S, Roney CH, Rogers AJ, Lee A, Wang PJ, Clopton P, Rubin DL, Narayan SM, Niederer S, Baykaner T
Journal of cardiovascular electrophysiology. 2023 Apr 27; 34: 1164-1174. doi: 10.1111/jce.15890
PMID: 36934383
RANK is a poor prognosis marker and a therapeutic target in ER-negative postmenopausal breast cancer.
Ciscar M, Trinidad EM, Perez-Chacon G, Alsaleem M, Jimenez M, Jimenez-Santos MJ, Perez-Montoyo H, Sanz-Moreno A, Vethencourt A, Toss M, Petit A, Soler-Monso MT, Lopez V, Gomez-Miragaya J, Gomez-Aleza C, Dobrolecki LE, Lewis MT, Bruna A, Mouron S, Quintela-Fandino M, Al-Shahrour F, Martinez-Aranda A, Sierra A, Green AR, Rakha E, Gonzalez-Suarez E
EMBO molecular medicine. 2023 Mar 7; 15: e16715. doi: 10.15252/emmm.202216715
PMID: 36880458
An untrained deep learning method for reconstructing dynamic MR images from accelerated model-based data.
Slavkova KP, DiCarlo JC, Wadhwa V, Kumar S, Wu C, Virostko J, Yankeelov TE, Tamir JI
Magnetic resonance in medicine. 2022 Dec 5; 89: 1617-1633. doi: 10.1002/mrm.29547
PMID: 36468624
An Online Repository for Pre-Clinical Imaging Protocols (PIPs).
Gammon ST, Cohen AS, Lehnert AL, Sullivan DC, Malyarenko D, Manning HC, Hormuth DA, Daldrup-Link HE, An H, Quirk JD, Shoghi K, Pagel MD, Kinahan PE, Miyaoka RS, Houghton AM, Lewis MT, Larson P, Sriram R, Blocker SJ, Pickup S, Badea A, Badea CT, Yankeelov TE, Chenevert TL
Tomography (Ann Arbor, Mich.). 2023 Mar 27; 9: 750-758. doi: 10.3390/tomography9020060
PMID: 37104131
Animal Models and Their Role in Imaging-Assisted Co-Clinical Trials.
Peehl DM, Badea CT, Chenevert TL, Daldrup-Link HE, Ding L, Dobrolecki LE, Houghton AM, Kinahan PE, Kurhanewicz J, Lewis MT, Li S, Luker GD, Ma CX, Manning HC, Mowery YM, O'Dwyer PJ, Pautler RG, Rosen MA, Roudi R, Ross BD, Shoghi KI, Sriram R, Talpaz M, Wahl RL, Zhou R
Tomography (Ann Arbor, Mich.). 2023 Mar 16; 9: 657-680. doi: 10.3390/tomography9020053
PMID: 36961012
Analysis of simplicial complexes to determine when to sample for quantitative DCE MRI of the breast.
DiCarlo JC, Jarrett AM, Kazerouni AS, Virostko J, Sorace A, Slavkova KP, Woodard S, Avery S, Patt D, Goodgame B, Yankeelov TE
Magnetic resonance in medicine. 2022 Nov 2; 89: 1134-1150. doi: 10.1002/mrm.29511
PMID: 36321574
Mathematical modelling of the dynamics of image-informed tumor habitats in a murine model of glioma.
Slavkova KP, Patel SH, Cacini Z, Kazerouni AS, Gardner AL, Yankeelov TE, Hormuth DA 2nd
Scientific reports. 2023 Feb 20; 13: 2916. doi: 10.1038/s41598-023-30010-6
PMID: 36804605
Evaluation of Apparent Diffusion Coefficient Repeatability and Reproducibility for Preclinical MRIs Using Standardized Procedures and a Diffusion-Weighted Imaging Phantom.
Malyarenko D, Amouzandeh G, Pickup S, Zhou R, Manning HC, Gammon ST, Shoghi KI, Quirk JD, Sriram R, Larson P, Lewis MT, Pautler RG, Kinahan PE, Muzi M, Chenevert TL
Tomography (Ann Arbor, Mich.). 2023 Feb 7; 9: 375-386. doi: 10.3390/tomography9010030
PMID: 36828382
Towards integration of time-resolved confocal microscopy of a 3D in vitro microfluidic platform with a hybrid multiscale model of tumor angiogenesis.
Phillips CM, Lima EABF, Gadde M, Jarrett AM, Rylander MN, Yankeelov TE
PLoS computational biology. 2023 Jan 18; 19: e1009499. doi: 10.1371/journal.pcbi.1009499
PMID: 36652468
A data assimilation framework to predict the response of glioma cells to radiation.
Liu J, Ii DAH, Yang J, Yankeelov TE
Mathematical biosciences and engineering : MBE. 2022 Oct 8; 20: 318-336. doi: 10.3934/mbe.2023015
PMID: 36650768
Optimizing combination therapy in a murine model of HER2+ breast cancer.
Lima EABF, Wyde RAF, Sorace AG, Yankeelov TE
Computer methods in applied mechanics and engineering. 2022 Aug 17; 402: . pii: 115484
PMID: 37800167
Proteogenomic Markers of Chemotherapy Resistance and Response in Triple-Negative Breast Cancer.
Anurag M, Jaehnig EJ, Krug K, Lei JT, Bergstrom EJ, Kim BJ, Vashist TD, Huynh AMT, Dou Y, Gou X, Huang C, Shi Z, Wen B, Korchina V, Gibbs RA, Muzny DM, Doddapaneni H, Dobrolecki LE, Rodriguez H, Robles AI, Hiltke T, Lewis MT, Nangia JR, Nemati Shafaee M, Li S, Hagemann IS, Hoog J, Lim B, Osborne CK, Mani DR, Gillette MA, Zhang B, Echeverria GV, Miles G, Rimawi MF, Carr SA, Ademuyiwa FO, Satpathy S, Ellis MJ
Cancer discovery. ; 12: 2586-2605. doi: 10.1158/2159-8290.CD-22-0200
PMID: 36001024
Towards Patient-Specific Optimization of Neoadjuvant Treatment Protocols for Breast Cancer Based on Image-Guided Fluid Dynamics.
Wu C, Hormuth DA, Lorenzo G, Jarrett AM, Pineda F, Howard FM, Karczmar GS, Yankeelov TE
IEEE transactions on bio-medical engineering. 2022 Oct 19; 69: 3334-3344. doi: 10.1109/TBME.2022.3168402
PMID: 35439121
Differences Between Ipsilateral and Contralateral Early Parenchymal Enhancement Kinetics Predict Response of Breast Cancer to Neoadjuvant Therapy.
Ren Z, Pineda FD, Howard FM, Hill E, Szasz T, Safi R, Medved M, Nanda R, Yankeelov TE, Abe H, Karczmar GS
Academic radiology. 2022 Mar 26; 29: 1469-1479. doi: 10.1016/j.acra.2022.02.008
PMID: 35351365
MRI-Based Digital Models Forecast Patient-Specific Treatment Responses to Neoadjuvant Chemotherapy in Triple-Negative Breast Cancer.
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
Cancer research. ; 82: 3394-3404. doi: 10.1158/0008-5472.CAN-22-1329
PMID: 35914239
Machine Learning-Enabled Multimodal Fusion of Intra-Atrial and Body Surface Signals in Prediction of Atrial Fibrillation Ablation Outcomes.
Tang S, Razeghi O, Kapoor R, Alhusseini MI, Fazal M, Rogers AJ, Rodrigo Bort M, Clopton P, Wang PJ, Rubin DL, Narayan SM, Baykaner T
Circulation. Arrhythmia and electrophysiology. 2022 Jul 22; 15: e010850. doi: 10.1161/CIRCEP.122.010850
PMID: 35867397
Opportunities for improving brain cancer treatment outcomes through imaging-based mathematical modeling of the delivery of radiotherapy and immunotherapy.
Hormuth DA 2nd, Farhat M, Christenson C, Curl B, Chad Quarles C, Chung C, Yankeelov TE
Advanced drug delivery reviews. 2022 May 30; 187: 114367. doi: 10.1016/j.addr.2022.114367
PMID: 35654212
Genomic and epigenomic BRCA alterations predict adaptive resistance and response to platinum-based therapy in patients with triple-negative breast and ovarian carcinomas.
Menghi F, Banda K, Kumar P, Straub R, Dobrolecki L, Rodriguez IV, Yost SE, Chandok H, Radke MR, Somlo G, Yuan Y, Lewis MT, Swisher EM, Liu ET
Science translational medicine. 2022 Jul 6; 14: eabn1926. doi: 10.1126/scitranslmed.abn1926
PMID: 35857626
Integrating mechanism-based modeling with biomedical imaging to build practical digital twins for clinical oncology.
Wu C, Lorenzo G, Hormuth DA 2nd, Lima EABF, Slavkova KP, DiCarlo JC, Virostko J, Phillips CM, Patt D, Chung C, Yankeelov TE
Biophysics reviews. 2022 May 17; 3: 021304. doi: 10.1063/5.0086789
PMID: 35602761
Quantifying Tumor Heterogeneity via MRI Habitats to Characterize Microenvironmental Alterations in HER2+ Breast Cancer.
Kazerouni AS, Hormuth DA 2nd, Davis T, Bloom MJ, Mounho S, Rahman G, Virostko J, Yankeelov TE, Sorace AG
Cancers. 2022 Apr 6; 14: . doi: 10.3390/cancers14071837
PMID: 35406609
Quantification of long-term doxorubicin response dynamics in breast cancer cell lines to direct treatment schedules.
Howard GR, Jost TA, Yankeelov TE, Brock A
PLoS computational biology. 2022 Mar 31; 18: e1009104. doi: 10.1371/journal.pcbi.1009104
PMID: 35358172
Bayesian calibration of a stochastic, multiscale agent-based model for predicting in vitro tumor growth.
Lima EABF, Faghihi D, Philley R, Yang J, Virostko J, Phillips CM, Yankeelov TE
PLoS computational biology. 2021 Nov 29; 17: e1008845. doi: 10.1371/journal.pcbi.1008845
PMID: 34843457
Quantitative multiparametric MRI predicts response to neoadjuvant therapy in the community setting.
Virostko J, Sorace AG, Slavkova KP, Kazerouni AS, Jarrett AM, DiCarlo JC, Woodard S, Avery S, Goodgame B, Patt D, Yankeelov TE
Breast cancer research : BCR. 2021 Nov 27; 23: 110. doi: 10.1186/s13058-021-01489-6
PMID: 34838096
Quantitative magnetic resonance imaging and tumor forecasting of breast cancer patients in the community setting.
Jarrett AM, Kazerouni AS, Wu C, Virostko J, Sorace AG, DiCarlo JC, Hormuth DA 2nd, Ekrut DA, Patt D, Goodgame B, Avery S, Yankeelov TE
Nature protocols. 2021 Sep 22; 16: 5309-5338. doi: 10.1038/s41596-021-00617-y
PMID: 34552262
An in silico validation framework for quantitative DCE-MRI techniques based on a dynamic digital phantom.
Wu C, Hormuth DA 2nd, Easley T, Eijkhout V, Pineda F, Karczmar GS, Yankeelov TE
Medical image analysis. 2021 Jul 20; 73: 102186. doi: 10.1016/
PMID: 34329903
A time-resolved experimental-mathematical model for predicting the response of glioma cells to single-dose radiation therapy.
Liu J, Hormuth DA, Davis T, Yang J, McKenna MT, Jarrett AM, Enderling H, Brock A, Yankeelov TE
Integrative biology : quantitative biosciences from nano to macro. ; 13: 167-183. doi: 10.1093/intbio/zyab010
PMID: 34060613
Characterizing Errors in Pharmacokinetic Parameters from Analyzing Quantitative Abbreviated DCE-MRI Data in Breast Cancer.
Slavkova KP, DiCarlo JC, Kazerouni AS, Virostko J, Sorace AG, Patt D, Goodgame B, Yankeelov TE
Tomography (Ann Arbor, Mich.). 2021 Jun 23; 7: 253-267. doi: 10.3390/tomography7030023
PMID: 34201654
Biologically-Based Mathematical Modeling of Tumor Vasculature and Angiogenesis via Time-Resolved Imaging Data.
Hormuth DA 2nd, Phillips CM, Wu C, Lima EABF, Lorenzo G, Jha PK, Jarrett AM, Oden JT, Yankeelov TE
Cancers. 2021 Jun 16; 13: . doi: 10.3390/cancers13123008
PMID: 34208448
Image-based personalization of computational models for predicting response of high-grade glioma to chemoradiation.
Hormuth DA 2nd, Al Feghali KA, Elliott AM, Yankeelov TE, Chung C
Scientific reports. 2021 Apr 19; 11: 8520. doi: 10.1038/s41598-021-87887-4
PMID: 33875739
Data valuation for medical imaging using Shapley value and application to a large-scale chest X-ray dataset.
Tang S, Ghorbani A, Yamashita R, Rehman S, Dunnmon JA, Zou J, Rubin DL
Scientific reports. 2021 Apr 16; 11: 8366. doi: 10.1038/s41598-021-87762-2
PMID: 33863957
Towards an Image-Informed Mathematical Model of In Vivo Response to Fractionated Radiation Therapy.
Hormuth DA 2nd, Jarrett AM, Davis T, Yankeelov TE
Cancers. 2021 Apr 7; 13: . doi: 10.3390/cancers13081765
PMID: 33917080
The rate of breast fibroglandular enhancement during dynamic contrast-enhanced MRI reflects response to neoadjuvant therapy.
Virostko J, Kuketz G, Higgins E, Wu C, Sorace AG, DiCarlo JC, Avery S, Patt D, Goodgame B, Yankeelov TE
European journal of radiology. 2021 Jan 9; 136: 109534. doi: 10.1016/j.ejrad.2021.109534
PMID: 33454460
Math, magnets, and medicine: enabling personalized oncology.
Hormuth DA 2nd, Jarrett AM, Lorenzo G, Lima EABF, Wu C, Chung C, Patt D, Yankeelov TE
Expert review of precision medicine and drug development. 2021 Jan 27; 6: 79-81. doi: 10.1080/23808993.2021.1878023
PMID: 34027102
Evaluating patient-specific neoadjuvant regimens for breast cancer via a mathematical model constrained by quantitative magnetic resonance imaging data.
Jarrett AM, Hormuth DA 2nd, Wu C, Kazerouni AS, Ekrut DA, Virostko J, Sorace AG, DiCarlo JC, Kowalski J, Patt D, Goodgame B, Avery S, Yankeelov TE
Neoplasia (New York, N.Y.). 2020 Nov 14; 22: 820-830. doi: 10.1016/j.neo.2020.10.011
PMID: 33197744
Towards integration of (64)Cu-DOTA-trastuzumab PET-CT and MRI with mathematical modeling to predict response to neoadjuvant therapy in HER2 + breast cancer.
Jarrett AM, Hormuth DA, Adhikarla V, Sahoo P, Abler D, Tumyan L, Schmolze D, Mortimer J, Rockne RC, Yankeelov TE
Scientific reports. 2020 Nov 25; 10: 20518. doi: 10.1038/s41598-020-77397-0
PMID: 33239688
Integrating transcriptomics and bulk time course data into a mathematical framework to describe and predict therapeutic resistance in cancer.
Johnson KE, Howard GR, Morgan D, Brenner EA, Gardner AL, Durrett RE, Mo W, Al'Khafaji A, Sontag ED, Jarrett AM, Yankeelov TE, Brock A
Physical biology. 2020 Nov 20; 18: 016001. doi: 10.1088/1478-3975/abb09c
PMID: 33215611
Imaging for Response Assessment in Cancer Clinical Trials.
Sorace AG, Elkassem AA, Galgano SJ, Lapi SE, Larimer BM, Partridge SC, Quarles CC, Reeves K, Napier TS, Song PN, Yankeelov TE, Woodard S, Smith AD
Seminars in nuclear medicine. 2020 Jun 10; 50: 488-504. doi: 10.1053/j.semnuclmed.2020.05.001
PMID: 33059819
Co-Clinical Imaging Resource Program (CIRP): Bridging the Translational Divide to Advance Precision Medicine.
Shoghi KI, Badea CT, Blocker SJ, Chenevert TL, Laforest R, Lewis MT, Luker GD, Manning HC, Marcus DS, Mowery YM, Pickup S, Richmond A, Ross BD, Vilgelm AE, Yankeelov TE, Zhou R
Tomography (Ann Arbor, Mich.). ; 6: 273-287. doi: 10.18383/j.tom.2020.00023
PMID: 32879897
Patient-Specific Characterization of Breast Cancer Hemodynamics Using Image-Guided Computational Fluid Dynamics.
Wu C, Hormuth DA, Oliver TA, Pineda F, Lorenzo G, Karczmar GS, Moser RD, Yankeelov TE
IEEE transactions on medical imaging. 2020 Feb 20; 39: 2760-2771. doi: 10.1109/TMI.2020.2975375
PMID: 32086203
Multiparametric Analysis of Longitudinal Quantitative MRI data to Identify Distinct Tumor Habitats in Preclinical Models of Breast Cancer.
Syed AK, Whisenant JG, Barnes SL, Sorace AG, Yankeelov TE
Cancers. 2020 Jun 24; 12: . doi: 10.3390/cancers12061682
PMID: 32599906
The Influence of Chronic Liver Diseases on Hepatic Vasculature: A Liver-on-a-chip Review.
Özkan A, Stolley D, Cressman ENK, McMillin M, DeMorrow S, Yankeelov TE, Rylander MN
Micromachines. 2020 May 9; 11: . doi: 10.3390/mi11050487
PMID: 32397454
Optimal Control Theory for Personalized Therapeutic Regimens in Oncology: Background, History, Challenges, and Opportunities.
Jarrett AM, Faghihi D, Ii DAH, Lima EABF, Virostko J, Biros G, Patt D, Yankeelov TE
Journal of clinical medicine. 2020 May 2; 9: . doi: 10.3390/jcm9051314
PMID: 32370195