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Items: 1 to 50 of 168

1.

Measuring DNA hybridization kinetics in live cells using a time-resolved 3D single-molecule tracking method.

Chen YI, Chang YJ, Nguyen TD, Liu C, Phillion S, Kuo YA, Vu HT, Liu A, Liu YL, Hong S, Ren P, Yankeelov TE, Yeh HC.

J Am Chem Soc. 2019 Sep 11. doi: 10.1021/jacs.9b08036. [Epub ahead of print]

PMID:
31509386
2.

Experimentally-driven mathematical modeling to improve combination targeted and cytotoxic therapy for HER2+ breast cancer.

Jarrett AM, Shah A, Bloom MJ, McKenna MT, Hormuth DA 2nd, Yankeelov TE, Sorace AG.

Sci Rep. 2019 Sep 6;9(1):12830. doi: 10.1038/s41598-019-49073-5.

3.

Recent trends in the age at diagnosis of colorectal cancer in the US National Cancer Data Base, 2004-2015.

Virostko J, Capasso A, Yankeelov TE, Goodgame B.

Cancer. 2019 Jul 22. doi: 10.1002/cncr.32347. [Epub ahead of print]

PMID:
31328273
4.

Leveraging Mathematical Modeling to Quantify Pharmacokinetic and Pharmacodynamic Pathways: Equivalent Dose Metric.

McKenna MT, Weis JA, Quaranta V, Yankeelov TE.

Front Physiol. 2019 May 22;10:616. doi: 10.3389/fphys.2019.00616. eCollection 2019.

5.

The 2019 mathematical oncology roadmap.

Rockne RC, Hawkins-Daarud A, Swanson KR, Sluka JP, Glazier JA, Macklin P, Hormuth DA, Jarrett AM, Lima EABF, Tinsley Oden J, Biros G, Yankeelov TE, Curtius K, Al Bakir I, Wodarz D, Komarova N, Aparicio L, Bordyuh M, Rabadan R, Finley SD, Enderling H, Caudell J, Moros EG, Anderson ARA, Gatenby RA, Kaznatcheev A, Jeavons P, Krishnan N, Pelesko J, Wadhwa RR, Yoon N, Nichol D, Marusyk A, Hinczewski M, Scott JG.

Phys Biol. 2019 Jun 19;16(4):041005. doi: 10.1088/1478-3975/ab1a09.

6.

Calibrating a Predictive Model of Tumor Growth and Angiogenesis with Quantitative MRI.

Hormuth DA 2nd, Jarrett AM, Feng X, Yankeelov TE.

Ann Biomed Eng. 2019 Jul;47(7):1539-1551. doi: 10.1007/s10439-019-02262-9. Epub 2019 Apr 8.

PMID:
30963385
7.

Translating preclinical MRI methods to clinical oncology.

Hormuth DA 2nd, Sorace AG, Virostko J, Abramson RG, Bhujwalla ZM, Enriquez-Navas P, Gillies R, Hazle JD, Mason RP, Quarles CC, Weis JA, Whisenant JG, Xu J, Yankeelov TE.

J Magn Reson Imaging. 2019 Mar 29. doi: 10.1002/jmri.26731. [Epub ahead of print] Review.

PMID:
30925001
8.
9.

The Quantitative Imaging Network: A Decade of Achievement.

Yankeelov TE.

Tomography. 2019 Mar;5(1):A8. doi: 10.18383/j.tom.2019.00999. No abstract available.

10.

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).

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.

Tomography. 2019 Mar;5(1):110-117. doi: 10.18383/j.tom.2018.00041.

11.

The Impact of Arterial Input Function Determination Variations on Prostate Dynamic Contrast-Enhanced Magnetic Resonance Imaging Pharmacokinetic Modeling: A Multicenter Data Analysis Challenge, Part II.

Huang W, Chen Y, Fedorov A, Li X, Jajamovich GH, Malyarenko DI, Aryal MP, LaViolette PS, Oborski MJ, O'Sullivan F, Abramson RG, Jafari-Khouzani K, Afzal A, Tudorica A, Moloney B, Gupta SN, Besa C, Kalpathy-Cramer J, Mountz JM, Laymon CM, Muzi M, Kinahan PE, Schmainda K, Cao Y, Chenevert TL, Taouli B, Yankeelov TE, Fennessy F, Li X.

Tomography. 2019 Mar;5(1):99-109. doi: 10.18383/j.tom.2018.00027.

12.

Magnetization Transfer MRI of Breast Cancer in the Community Setting: Reproducibility and Preliminary Results in Neoadjuvant Therapy.

Virostko J, Sorace AG, Wu C, Ekrut D, Jarrett AM, Upadhyaya RM, Avery S, Patt D, Goodgame B, Yankeelov TE.

Tomography. 2019 Mar;5(1):44-52. doi: 10.18383/j.tom.2018.00019.

13.

Assessing metastatic potential of breast cancer cells based on EGFR dynamics.

Liu YL, Chou CK, Kim M, Vasisht R, Kuo YA, Ang P, Liu C, Perillo EP, Chen YA, Blocher K, Horng H, Chen YI, Nguyen DT, Yankeelov TE, Hung MC, Dunn AK, Yeh HC.

Sci Rep. 2019 Mar 4;9(1):3395. doi: 10.1038/s41598-018-37625-0.

14.

Mechanism-Based Modeling of Tumor Growth and Treatment Response Constrained by Multiparametric Imaging Data.

Hormuth DA 2nd, Jarrett AM, Lima EABF, McKenna MT, Fuentes DT, Yankeelov TE.

JCO Clin Cancer Inform. 2019 Feb;3:1-10. doi: 10.1200/CCI.18.00055.

15.

In vitro vascularized liver and tumor tissue microenvironments on a chip for dynamic determination of nanoparticle transport and toxicity.

Ozkan A, Ghousifam N, Hoopes PJ, Yankeelov TE, Rylander MN.

Biotechnol Bioeng. 2019 May;116(5):1201-1219. doi: 10.1002/bit.26919. Epub 2019 Feb 13.

PMID:
30636289
16.

The effects of IKK-beta inhibition on early NF-kappa-B activation and transcription of downstream genes.

Bloom MJ, Saksena SD, Swain GP, Behar MS, Yankeelov TE, Sorace AG.

Cell Signal. 2019 Mar;55:17-25. doi: 10.1016/j.cellsig.2018.12.004. Epub 2018 Dec 10.

PMID:
30543861
17.

Characterizing Trastuzumab-Induced Alterations in Intratumoral Heterogeneity with Quantitative Imaging and Immunohistochemistry in HER2+ Breast Cancer.

Syed AK, Woodall R, Whisenant JG, Yankeelov TE, Sorace AG.

Neoplasia. 2019 Jan;21(1):17-29. doi: 10.1016/j.neo.2018.10.008. Epub 2018 Nov 23.

18.

Quantitative analysis of vascular properties derived from ultrafast DCE-MRI to discriminate malignant and benign breast tumors.

Wu C, Pineda F, Hormuth DA 2nd, Karczmar GS, Yankeelov TE.

Magn Reson Med. 2019 Mar;81(3):2147-2160. doi: 10.1002/mrm.27529. Epub 2018 Oct 28.

PMID:
30368906
19.

Calibration of Multi-Parameter Models of Avascular Tumor Growth Using Time Resolved Microscopy Data.

Lima EABF, Ghousifam N, Ozkan A, Oden JT, Shahmoradi A, Rylander MN, Wohlmuth B, Yankeelov TE.

Sci Rep. 2018 Sep 28;8(1):14558. doi: 10.1038/s41598-018-32347-9.

20.

Mathematical models of tumor cell proliferation: A review of the literature.

Jarrett AM, Lima EABF, Hormuth DA 2nd, McKenna MT, Feng X, Ekrut DA, Resende ACM, Brock A, Yankeelov TE.

Expert Rev Anticancer Ther. 2018 Dec;18(12):1271-1286. doi: 10.1080/14737140.2018.1527689. Epub 2018 Oct 22. Review.

PMID:
30252552
21.

Mathematical modelling of trastuzumab-induced immune response in an in vivo murine model of HER2+ breast cancer.

Jarrett AM, Bloom MJ, Godfrey W, Syed AK, Ekrut DA, Ehrlich LI, Yankeelov TE, Sorace AG.

Math Med Biol. 2019 Sep 2;36(3):381-410. doi: 10.1093/imammb/dqy014.

PMID:
30239754
22.

A multi-state model of chemoresistance to characterize phenotypic dynamics in breast cancer.

Howard GR, Johnson KE, Rodriguez Ayala A, Yankeelov TE, Brock A.

Sci Rep. 2018 Aug 13;8(1):12058. doi: 10.1038/s41598-018-30467-w.

23.
24.

Precision Medicine with Imprecise Therapy: Computational Modeling for Chemotherapy in Breast Cancer.

McKenna MT, Weis JA, Brock A, Quaranta V, Yankeelov TE.

Transl Oncol. 2018 Jun;11(3):732-742. doi: 10.1016/j.tranon.2018.03.009. Epub 2018 Apr 16. Review.

25.

Repeatability, reproducibility, and accuracy of quantitative mri of the breast in the community radiology setting.

Sorace AG, Wu C, Barnes SL, Jarrett AM, Avery S, Patt D, Goodgame B, Luci JJ, Kang H, Abramson RG, Yankeelov TE, Virostko J.

J Magn Reson Imaging. 2018 Mar 23. doi: 10.1002/jmri.26011. [Epub ahead of print]

PMID:
29570895
26.

Variable Cell Line Pharmacokinetics Contribute to Non-Linear Treatment Response in Heterogeneous Cell Populations.

McKenna MT, Weis JA, Quaranta V, Yankeelov TE.

Ann Biomed Eng. 2018 Jun;46(6):899-911. doi: 10.1007/s10439-018-2001-2. Epub 2018 Feb 26.

27.

Biophysical Modeling of In Vivo Glioma Response After Whole-Brain Radiation Therapy in a Murine Model of Brain Cancer.

Hormuth DA 2nd, Weis JA, Barnes SL, Miga MI, Quaranta V, Yankeelov TE.

Int J Radiat Oncol Biol Phys. 2018 Apr 1;100(5):1270-1279. doi: 10.1016/j.ijrobp.2017.12.004. Epub 2017 Dec 13.

28.

Distinguishing benign and malignant breast tumors: preliminary comparison of kinetic modeling approaches using multi-institutional dynamic contrast-enhanced MRI data from the International Breast MR Consortium 6883 trial.

Sorace AG, Partridge SC, Li X, Virostko J, Barnes SL, Hippe DS, Huang W, Yankeelov TE.

J Med Imaging (Bellingham). 2018 Jan;5(1):011019. doi: 10.1117/1.JMI.5.1.011019. Epub 2018 Jan 22.

29.

A HYBRID THREE-SCALE MODEL OF TUMOR GROWTH.

Rocha HL, Almeida RC, Lima EABF, Resende ACM, Oden JT, Yankeelov TE.

Math Models Methods Appl Sci. 2018 Jan;28(1):61-93. doi: 10.1142/S0218202518500021. Epub 2017 Nov 24.

30.

Mechanically Coupled Reaction-Diffusion Model to Predict Glioma Growth: Methodological Details.

Hormuth DA 2nd, Eldridge SL, Weis JA, Miga MI, Yankeelov TE.

Methods Mol Biol. 2018;1711:225-241. doi: 10.1007/978-1-4939-7493-1_11.

31.

Combining multiparametric MRI with receptor information to optimize prediction of pathologic response to neoadjuvant therapy in breast cancer: preliminary results.

Kang H, Hainline A, Arlinghaus LR, Elderidge S, Li X, Abramson VG, Chakravarthy AB, Abramson RG, Bingham B, Fakhoury K, Yankeelov TE.

J Med Imaging (Bellingham). 2018 Jan;5(1):011015. doi: 10.1117/1.JMI.5.1.011015. Epub 2017 Dec 29.

32.

Selection and Validation of Predictive Models of Radiation Effects on Tumor Growth Based on Noninvasive Imaging Data.

Lima EABF, Oden JT, Wohlmuth B, Shahmoradi A, Hormuth DA 2nd, Yankeelov TE, Scarabosio L, Horger T.

Comput Methods Appl Mech Eng. 2017 Dec 1;327:277-305. doi: 10.1016/j.cma.2017.08.009. Epub 2017 Aug 18.

33.

Dynamic contrast-enhanced magnetic resonance imaging and diffusion-weighted magnetic resonance imaging for predicting the response of locally advanced breast cancer to neoadjuvant therapy: a meta-analysis.

Virostko J, Hainline A, Kang H, Arlinghaus LR, Abramson RG, Barnes SL, Blume JD, Avery S, Patt D, Goodgame B, Yankeelov TE, Sorace AG.

J Med Imaging (Bellingham). 2018 Jan;5(1):011011. doi: 10.1117/1.JMI.5.1.011011. Epub 2017 Nov 24.

34.

A fully coupled space-time multiscale modeling framework for predicting tumor growth.

Rahman MM, Feng Y, Yankeelov TE, Oden JT.

Comput Methods Appl Mech Eng. 2017 Jun 15;320:261-286. doi: 10.1016/j.cma.2017.03.021. Epub 2017 Mar 21.

35.

Toward uniform implementation of parametric map Digital Imaging and Communication in Medicine standard in multisite quantitative diffusion imaging studies.

Malyarenko D, Fedorov A, Bell L, Prah M, Hectors S, Arlinghaus L, Muzi M, Solaiyappan M, Jacobs M, Fung M, Shukla-Dave A, McManus K, Boss M, Taouli B, Yankeelov TE, Quarles CC, Schmainda K, Chenevert TL, Newitt DC.

J Med Imaging (Bellingham). 2018 Jan;5(1):011006. doi: 10.1117/1.JMI.5.1.011006. Epub 2017 Oct 30.

36.

The effects of intravoxel contrast agent diffusion on the analysis of DCE-MRI data in realistic tissue domains.

Woodall RT, Barnes SL, Hormuth DA 2nd, Sorace AG, Quarles CC, Yankeelov TE.

Magn Reson Med. 2018 Jul;80(1):330-340. doi: 10.1002/mrm.26995. Epub 2017 Nov 8.

37.

Multisite concordance of apparent diffusion coefficient measurements across the NCI Quantitative Imaging Network.

Newitt DC, Malyarenko D, Chenevert TL, Quarles CC, Bell L, Fedorov A, Fennessy F, Jacobs MA, Solaiyappan M, Hectors S, Taouli B, Muzi M, Kinahan PE, Schmainda KM, Prah MA, Taber EN, Kroenke C, Huang W, Arlinghaus LR, Yankeelov TE, Cao Y, Aryal M, Yen YF, Kalpathy-Cramer J, Shukla-Dave A, Fung M, Liang J, Boss M, Hylton N.

J Med Imaging (Bellingham). 2018 Jan;5(1):011003. doi: 10.1117/1.JMI.5.1.011003. Epub 2017 Oct 10.

38.

Dual Src and EGFR inhibition in combination with gemcitabine in advanced pancreatic cancer: phase I results : A phase I clinical trial.

Cardin DB, Goff LW, Chan E, Whisenant JG, Dan Ayers G, Takebe N, Arlinghaus LR, Yankeelov TE, Berlin J, Merchant N.

Invest New Drugs. 2018 Jun;36(3):442-450. doi: 10.1007/s10637-017-0519-z. Epub 2017 Oct 9.

39.

CCR7 Modulates the Generation of Thymic Regulatory T Cells by Altering the Composition of the Thymic Dendritic Cell Compartment.

Hu Z, Li Y, Van Nieuwenhuijze A, Selden HJ, Jarrett AM, Sorace AG, Yankeelov TE, Liston A, Ehrlich LIR.

Cell Rep. 2017 Oct 3;21(1):168-180. doi: 10.1016/j.celrep.2017.09.016.

40.

Quantitative Evaluation of Temporal Regularizers in Compressed Sensing Dynamic Contrast Enhanced MRI of the Breast.

Wang D, Arlinghaus LR, Yankeelov TE, Yang X, Smith DS.

Int J Biomed Imaging. 2017;2017:7835749. doi: 10.1155/2017/7835749. Epub 2017 Aug 28.

41.

Imaging Considerations and Interprofessional Opportunities in the Care of Breast Cancer Patients in the Neoadjuvant Setting.

Sorace AG, Harvey S, Syed A, Yankeelov TE.

Semin Oncol Nurs. 2017 Nov;33(4):425-439. doi: 10.1016/j.soncn.2017.08.008. Epub 2017 Sep 15. Review.

42.

DCE- and DW-MRI as early imaging biomarkers of treatment response in a preclinical model of triple negative breast cancer.

Barnes SL, Sorace AG, Whisenant JG, McIntyre JO, Kang H, Yankeelov TE.

NMR Biomed. 2017 Nov;30(11). doi: 10.1002/nbm.3799. Epub 2017 Sep 15.

PMID:
28915312
43.

Accuracy, repeatability, and interplatform reproducibility of T1 quantification methods used for DCE-MRI: Results from a multicenter phantom study.

Bane O, Hectors SJ, Wagner M, Arlinghaus LL, Aryal MP, Cao Y, Chenevert TL, Fennessy F, Huang W, Hylton NM, Kalpathy-Cramer J, Keenan KE, Malyarenko DI, Mulkern RV, Newitt DC, Russek SE, Stupic KF, Tudorica A, Wilmes LJ, Yankeelov TE, Yen YF, Boss MA, Taouli B.

Magn Reson Med. 2018 May;79(5):2564-2575. doi: 10.1002/mrm.26903. Epub 2017 Sep 14.

44.

Selection, calibration, and validation of models of tumor growth.

Lima EABF, Oden JT, Hormuth DA 2nd, Yankeelov TE, Almeida RC.

Math Models Methods Appl Sci. 2016 Nov;26(12):2341-2368. doi: 10.1142/S021820251650055X. Epub 2016 Oct 3.

45.

A Predictive Mathematical Modeling Approach for the Study of Doxorubicin Treatment in Triple Negative Breast Cancer.

McKenna MT, Weis JA, Barnes SL, Tyson DR, Miga MI, Quaranta V, Yankeelov TE.

Sci Rep. 2017 Jul 18;7(1):5725. doi: 10.1038/s41598-017-05902-z.

46.

A mechanically coupled reaction-diffusion model that incorporates intra-tumoural heterogeneity to predict in vivo glioma growth.

Hormuth DA 2nd, Weis JA, Barnes SL, Miga MI, Rericha EC, Quaranta V, Yankeelov TE.

J R Soc Interface. 2017 Mar;14(128). pii: 20161010. doi: 10.1098/rsif.2016.1010.

47.

Accrual Patterns for Clinical Studies Involving Quantitative Imaging: Results of an NCI Quantitative Imaging Network (QIN) Survey.

Kurland BF, Aggarwal S, Yankeelov TE, Gerstner ER, Mountz JM, Linden HM, Jones EF, Bodeker KL, Buatti JM.

Tomography. 2016 Dec;2(4):276-282. doi: 10.18383/j.tom.2016.00169.

48.

QIN DAWG Validation of Gradient Nonlinearity Bias Correction Workflow for Quantitative Diffusion-Weighted Imaging in Multicenter Trials.

Malyarenko DI, Wilmes LJ, Arlinghaus LR, Jacobs MA, Huang W, Helmer KG, Taouli B, Yankeelov TE, Newitt D, Chenevert TL.

Tomography. 2016 Dec;2(4):396-405. doi: 10.18383/j.tom.2016.00214.

49.

Quantitative Magnetization Transfer Imaging of the Breast at 3.0 T: Reproducibility in Healthy Volunteers.

Arlinghaus LR, Dortch RD, Whisenant JG, Kang H, Abramson RG, Yankeelov TE.

Tomography. 2016 Dec;2(4):260-266. doi: 10.18383/j.tom.2016.00142.

50.

Bloch-Siegert B1-Mapping Improves Accuracy and Precision of Longitudinal Relaxation Measurements in the Breast at 3 T.

Whisenant JG, Dortch RD, Grissom W, Kang H, Arlinghaus LR, Yankeelov TE.

Tomography. 2016 Dec;2(4):250-259. doi: 10.18383/j.tom.2016.00133.

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