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[1] EDH Gates, JS Weinberg, SS Prabhu, JS Lin, J Hamilton, JD Hazle, GN Fuller, V Baladandayuthapani, D. Fuentes, and D Schellingerhout. Estimating local cellular density in glioma using mr imaging data. American Journal of Neuroradiology, 2020. [ bib ]
[2] D. Fuentes, Emily Thompson, Megan Jacobsen, Anna Crouch, Rick R Layman, Beatrice Rivière, and Erik Cressman. Imaging-based characterization of convective tissue properties. International Journal of Hyperthermia, accepted, 2020. [ bib ]
[3] D. Fuentes, Samuel J Fahrenholtz, Chunxiao Guo, Christopher J MacLellan, Rick R Layman, Beatrice Rivière, R Jason Stafford, and Erik Cressman. Mathematical modeling of mass and energy transport for thermoembolization. International Journal of Hyperthermia, 37(1):356--365, 2020. [ bib ]
[4] Ahmed W Moawad, D. Fuentes, Ahmed M Khalaf, Katherine J Blair, Janio Szklaruk, Aliya Qayyum, John D Hazle, and Khaled M Elsayes. Feasibility of Automated Volumetric Assessment of Large Hepatocellular Carcinomas' Responses to Transarterial Chemoembolization. Frontiers in Oncology, 10:572, 2020. [ bib ]
[5] Drew Mitchell, Ken-Pin Hwang, James A Bankson, R Jason Stafford, Suchandrima Banerjee, Naoyuki Takei, and D. Fuentes. An information theory model for optimizing quantitative magnetic resonance imaging acquisitions. Physics in Medicine & Biology, 2020. [ bib ]
[6] Tracy W Liu, Seth T Gammon, Ping Yang, D. Fuentes, and David Piwnica-Worms. Myeloperoxidase-produced HOCl is a paracrine effector linking myeloid cells to NF-κB signaling in melanoma, mediating anti-tumor responses during early melanoma progression, 2020. [ bib ]
[7] Dhiego Chaves de Almeida Bastos, D. Fuentes, Jeffrey Traylor, Jeffrey Weinberg, Vinodh A Kumar, Jason Stafford, Jing Li, Ganesh Rao, and Sujit S Prabhu. The use of laser interstitial thermal therapy in the treatment of brain metastases: a literature review. International Journal of Hyperthermia, 37(2):53--60, 2020. [ bib ]
[8] Dhiego Chaves de Almeida Bastos, Jeffrey Weinberg, Vinodh A Kumar, D. Fuentes, Jason Stafford, Jing Li, Ganesh Rao, and Sujit S Prabhu. Laser Interstitial Thermal Therapy in the treatment of brain metastases and radiation necrosis. Cancer Letters, 2020. [ bib ]
[9] Dhiego Chaves de Almeida Bastos, Ganesh Rao, Isabella Claudia Glitza Oliva, Jonathan M Loree, D. Fuentes, R Jason Stafford, Vivek B Beechar, Jeffrey S Weinberg, Komal Shah, Vinodh A Kumar, et al. Predictors of local control of brain metastasis treated with laser interstitial thermal therapy. Neurosurgery, 87(1):112--122, 2020. [ bib ]
[10] Costas Papadopoulos, Eleni K Efthimiadou, Michael Pissas, D. Fuentes, Nikolaos Boukos, Vassilis Psycharis, George Kordas, Vassilios C Loukopoulos, and George C Kagadis. Magnetic fluid hyperthermia simulations in evaluation of SAR calculation methods. Physica Medica, 71:39--52, 2020. [ bib ]
[11] Rajarajeswari Muthusivarajan, William J Allen, Ashok D Pehere, Konstantin V Sokolov, and D. Fuentes. Role of alkylated residues in the tetrapeptide self-assembly—A molecular dynamics study. Journal of Computational Chemistry, 41(31):2634--2640, 2020. [ bib ]
[12] EDH Gates, JS Lin, JS Weinberg, SS Prabhu, J Hamilton, JD Hazle, GN Fuller, V Baladandayuthapani, D. Fuentes, and D Schellingerhout. Imaging-Based Algorithm for the Local Grading of Glioma. American Journal of Neuroradiology, 41(3):400--407, 2020. [ bib ]
[13] Joseph D Butner, D. Fuentes, Bulent Ozpolat, George A Calin, Xiaobo Zhou, John Lowengrub, Vittorio Cristini, and Zhihui Wang. A multiscale agent-based model of ductal carcinoma in situ. IEEE Transactions on Biomedical Engineering, 2019. [ bib ]
[14] SL Thrower, SK Kandala, D. Fuentes, W Stefan, N Sowko, MX Huang, K Mathieu, and JD Hazle. A compressed sensing approach to immobilized nanoparticle localization for superparamagnetic relaxometry. Physics in Medicine & Biology, 64(19):194001, 2019. [ bib ]
[15] Evan DH Gates, Jie Yang, Kazutaka Fukumura, Jonathan S Lin, Jeffrey S Weinberg, Sujit S Prabhu, Lihong Long, D. Fuentes, Erik P Sulman, Jason T Huse, et al. Spatial distance correlates with genetic distance in diffuse glioma. Frontiers in oncology, 9, 2019. [ bib ]
[16] A. Morshid, K. Elsayes A.M. Khalaf, J. Yu, A. Kaseb, M. Hassan, A. Mahvash, Z. Wang, J.D. Hazle, and D. Fuentes. A machine learning model to predict hepatocellular carcinoma response to transcatheter arterial chemoembolization. Radiology: Artificial Intelligence, 1(5), 2019. Cover Page. [ bib ]
[17] J. Traylor, D. Bastos, D. Fuentes, M. Muir, R. Patel, VA. Kumar, RJ. Stafford, G. Rao, and SS Prabhu. Dynamic contrast-enhanced MRI in patients with brain metastases receiving laser interstitial thermal therapy. American Journal of Neuroradiology, 40(9):1451--1457, 2019. [ bib ]
[18] Dhiego Bastos, Ganesh Rao, Isabella Claudia Glitza, D. Fuentes, Jason Stafford, Jeffrey Weinberg, Komal Shah, Vinodh A Kumar, and Sujit S Prabhu. Predictors of Local Control of Brain Metastasis Treated with Laser Interstitial Thermal Therapy. J. of Neurosurgery, 2019. [ bib ]
[19] M. Elmohr, D. Fuentes, A. Morshid, A. Kaseb, M. Hassan, E Gates, J. Szklaruk, J.D. Hazle, and K. Elsayes. Machine learning-based texture analysis for differentiation of large adrenal cortical tumors on computed tomography. Clinical radiology, 74(10):818, 2019. [ bib ]
[20] A. Khalaf, D. Fuentes, A. Morshid, M. Elmohr, A. Kaseb, M. Hassan, J. Szklaruk, J.D. Hazle, and K. Elsayes. Hepatocellular Carcinoma (HCC) Response to Transcatheter Arterial Chemoembolization (TACE) Using Automatically Generated Pre-Therapeutic Tumor Volumes by a Random Forest-Based Segmentation Protocol. Clinical radiology, 74(12):974--e13, 2019. [ bib ]
[21] C Walker, D. Fuentes, Peder Larson, Vikas Kundra, Daniel Vigneron, and James Bankson. Effects of Excitation Angle Strategy on Quantitative Analysis of Hyperpolarized Pyruvate. Magnetic resonance in medicine, 2019. [ bib ]
[22] Evan DH Gates, Jonathan S Lin, Jeffrey S Weinberg, Jackson Hamilton, Sujit S Prabhu, John D Hazle, Gregory N Fuller, Veera Baladandayuthapani, D. Fuentes, and Dawid Schellingerhout. Guiding the first biopsy in glioma patients using estimated Ki-67 maps derived from MRI: conventional versus advanced imaging. Neuro-Oncology, 21(4):527--536, 2019. [ bib ]
[23] D. Fuentes, K. Ahmed, J.S. Lin, R. Ali, A. Kaseb, M. Hassan, J. Szklaruk, J.D. Hazle, A. Qayyum, and K. Elsayes. Automated Volumetric Assessment of Hepatocellular Carcinoma Response to Sorafenib: A pilot study. J. of Computer Assisted Tomography, 43(3):499--506, 2019. [ bib ]
[24] D. Hormuth, A. Jarrett, E. ABF Lima, M. .T. McKenna, D. Fuentes, and T. Yankeelov. Mechanism based modeling of tumor growth and treatment response constrained by multiparametric imaging data. JCO Clinical Cancer Informatics, 3:1--10, 2019. [ bib ]
[25] Constance Owens, Christine Peterson, Chad Tang, Eugene Koay, Wen Yu, Dennis Mackin, Jing Li, Mohammad Salehpour, D. Fuentes, Laurence Court, and Jinzhong Yang. Lung tumor segmentation methods: Impact on the uncertainty of radiomics features for non-small cell lung cancer. PloS one, 13(10):e0205003, 2018. [ bib ]
[26] Ahmed M Khalaf, D. Fuentes, Ali I Morshid, Mata R Burke, Ahmed O Kaseb, Manal Hassan, John D Hazle, and Khaled M Elsayes. Role of wnt/β-catenin signaling in hepatocellular carcinoma, pathogenesis, and clinical significance. Journal of hepatocellular carcinoma, 5:61, 2018. [ bib ]
[27] D. Fuentes, Nina M Muñoz, Chunxiao Guo, Urzsula Polak, Adeeb A Minhaj, William J Allen, Michael C Gustin, and Erik NK Cressman. A molecular dynamics approach towards evaluating osmotic and thermal stress in the extracellular environment. International Journal of Hyperthermia, pages 1--9, 2018. [ bib ]
[28] D. Mitchell, S. Fahrenholtz, CJ MacLellan, D. Bastos, G. Rao, S. Prabhu, J. Weinberg, JD Hazle, RJ Stafford, and D. Fuentes. A heterogeneous tissue model for treatment planning for magnetic resonance-guided laser interstitial thermal therapy. International Journal of Hyperthermia, 34(7):943--952, 2018. [ bib ]
[29] V. Beechar, S. Prabhu, D. Bastos, J. Weinberg, RJ Stafford, D. Fuentes, K. Hess, and G. Rao. Volumetric Response of Progressing Post-SRS Lesions Treated with Laser Interstitial Thermal Therapy. Journal of Neuro-Oncology, 137(1):57--65, 2018. [ bib ]
[30] Samuel John Fahrenholtz, Reza Madankan, Shabbar Danish, John D Hazle, R Jason Stafford, and D. Fuentes. Theoretical model for laser ablation outcome predictions in brain: calibration and validation on clinical MR thermometry images. International Journal of Hyperthermia, pages 1--11, 2017. [ bib ]
[31] Marites P Melancon, Tomas Appleton Figueira, D. Fuentes, Li Tian, Yang Qiao, Jianhua Gu, Mihai Gagea, Joe E Ensor, Nina M Muñoz, Kiersten L Maldonado, and A. Tam. Development of an Electroporation and Nanoparticle-based Therapeutic Platform for Bone Metastases. Radiology, page 161721, 2017. [ bib ]
[32] J. Yung, D. Fuentes, C. J. MacLellan, F. Maier, J. D. Hazle, and R. J. Stafford. Referenceless Magnetic Resonance Temperature Imaging using Gaussian Process Modeling. Medical Physics, 44(7):3545--3555, 2017. [ bib ]
[33] Javad Sovizi, Kelsey B Mathieu, Sara L Thrower, Wolfgang Stefan, John D Hazle, and D. Fuentes. Gaussian Process Classification of Superparamagnetic Relaxometry Data: Phantom Study. Artificial Intelligence in Medicine, 82:47--59, 2017. [ bib ]
[34] C. J. MacLellan, D. Fuentes, S. Prabhu, G. Rao, J. Weinberg, J. D. Hazle, and R. J. Stafford. A methodology for thermal dose model parameter development using perioperative MRI. International Journal of Hyperthermia, pages 1--10, 2017. [ bib ]
[35] Trevor Mitcham, Houra Taghavi, James Long, Cayla Wood, D. Fuentes, Wolfgang Stefan, John Ward, and Richard Bouchard. Photoacoustic-based so2 estimation through excised bovine prostate tissue with interstitial light delivery. Photoacoustics, 7:47--56, 2017. [ bib ]
[36] J. Lin, D. Fuentes, J. Weinberg, S. Prabhu, V. Baladandayuthapani, J. D. Hazle, and D. Schellingerhout. Performance Assessment for Brain Magnetic Resonance Imaging Registration Methods. American Journal of Neuroradiology, 38(5):973--980, 2017. [ bib ]
[37] Reza Madankan, Wolfgang Stefan, SJ Fahrenholtz, CJ MacLellan, JD Hazle, RJ Stafford, Jeffrey S Weinberg, Ganesh Rao, and D. Fuentes. Accelerated Model-based Signal Reconstruction for Magnetic Resonance Imaging in Presence of Uncertainties. Physics in medicine and biology, 62(1):214, 2016. [ bib ]
[38] Alda L Tam, Tomas A Figueira, Mihai Gagea, Joe E Ensor, Katherine Dixon, Amanda McWatters, Sanjay Gupta, and D. Fuentes. Irreversible Electroporation in the Epidural Space of the Porcine Spine: Effects on Adjacent Structures. Radiology, page 152688, 2016. [ bib ]
[39] J Tinsley Oden, Ernesto ABF Lima, Regina C Almeida, Yusheng Feng, Marissa Nichole Rylander, D. Fuentes, Danial Faghihi, Mohammad M Rahman, Matthew DeWitt, and Manasa Gadde. Toward predictive multiscale modeling of vascular tumor growth. Archives of Computational Methods in Engineering, pages 1--45, 2015. [ bib ]
[40] James A Bankson, Christopher M Walker, Marc S Ramirez, Wolfgang Stefan, D. Fuentes, Matthew E Merritt, Jaehyuk Lee, Vlad C Sandulache, Yunyun Chen, Liem Phan, et al. Kinetic modeling and constrained reconstruction of hyperpolarized 1-13c-pyruvate offers improved metabolic imaging of tumors. Cancer research, pages canres--0171, 2015. [ bib ]
[41] S. Fahrenholtz, T. Moon, M. Franco, D. Medina, J. D. Hazle, R. J. Stafford, F. Maier, S. Danish, A. Gowda, A. Shetty, T. Warburton, and D. Fuentes. A Model Evaluation Study for Treatment Planning of Laser Induced Thermal Therapy. International Journal of Hyperthermia, 31(7):705--714, 2015. [ bib ]
[42] F. Maier, D. Fuentes, J. S. Weinberg, J. Hazle, and R. J. Stafford. Robust Phase Unwrapping using a Sorted List, Multi-clustering Algorithm. Magnetic Resonance in Medicine, 73(4):1662--1668, 2015. [ bib | DOI | http ]
[43] D. Fuentes, J. Contreras, J. Yu, R. He, E. Castillo, R. Castillo, and T. Guerrero. Morphometry-based measurements of the structural response to whole-brain radiation. International Journal of Computer Assisted Radiology and Surgery, 10:393--401, 2014. [ bib | DOI | http ]
[44] Edward Castillo, Richard Castillo, D. Fuentes, and Thomas Guerrero. Computing global minimizers to a constrained b-spline image registration problem from optimal l1 perturbations to block match data. Medical physics, 41(4):041904, 2014. [ bib ]
[45] Christopher J MacLellan, D. Fuentes, Andrew M Elliott, Jon Schwartz, John D Hazle, and R Jason Stafford. Estimating nanoparticle optical absorption with magnetic resonance temperature imaging and bioheat transfer simulation. International Journal of Hyperthermia, 30(1):47--55, 2013. [ bib ]
[46] E. Yeniaras, D. Fuentes, S.J. Fahrenholtz, J.S. Weinberg, F. Maier, J.D. Hazle, and R.J. Stafford. Design and initial evaluation of a treatment planning software system for MRI-guided laser ablation in the brain. International Journal of Computer Assisted Radiology and Surgery, pages 1--9, 2013. [ bib | DOI | http ]
[47] S. Fahrenholtz, R. J. Stafford, J. Hazle, and D. Fuentes. Generalised polynomial chaos-based uncertainty quantification for planning MRgLITT procedures. International Journal of Hyperthermia, 29(4):324--335, 2013. PMC3924420. [ bib | http ]
[48] R. Castillo, E. Castillo, D. Fuentes, M. Ahmad, A. M Wood, M. S. Ludwig, and T. Guerrero. A Reference Dataset for Deformable Image Registration Spatial Accuracy Evaluation using the COPDgene Study Archive. Physics in Medicine and Biology, 58(9):2861, 2013. PMC3677192. [ bib ]
[49] D. Fuentes, A. Elliott, J. S. Weinberg, A. Shetty, J. D. Hazle, and R. J. Stafford. An Inverse Problem Approach to Recovery of In-Vivo Nanoparticle Concentrations from Thermal Image Monitoring of MR-Guided Laser Induced Thermal Therapy. Ann. BME., 41(1):100--111, 2013. PMC3524364. [ bib | http ]
[50] D. Fuentes, J. Yung, J. D. Hazle, J. S. Weinberg, and R. J. Stafford. Kalman Filtered MR Temperature Imaging for Laser Induced Thermal Therapies. Trans. Medical Imaging, 31(4):984--994, 2012. Special Issue on Interventional Imaging, PMC3873725. [ bib | http ]
[51] Y. Feng and D. Fuentes. Real-Time Predictive Surgical Control for Cancer Treatment Using Laser Ablation [Life Science]. Signal Processing Magazine, IEEE, 28(3):134 --138, May 2011. [ bib ]
[52] Y. Feng and D. Fuentes. Model-Based Planning and Real-Time Predictive Control for Laser-Induced Thermal Therapy. Inter. Journal Hyperthermia, 27(8):751--761, 2011. invited review. PMC3930104. [ bib ]
[53] D. Fuentes, C. Walker, A. Elliott, A. Shetty, J. Hazle, and R. J. Stafford. MR Temperature Imaging Validation of a Bioheat Transfer Model for LITT. International Journal of Hyperthermia, 27(5):453--464, 2011. Cover Page, PMC3930085. [ bib | DOI ]
[54] R. J. Stafford, D. Fuentes, A. Elliott, and K. Ahrar. Laser Induced Thermal Therapy for Ablation. Crit. Rev. Biomed. Eng., 38(1):79--100, 2010. [ bib ]
[55] D. Fuentes, Y. Feng, A. Elliott, A. Shetty, R. J. McNichols, J. T. Oden, and R. J. Stafford. Adaptive Real-Time Bioheat Transfer Models for Computer Driven MR-guided Laser Induced Thermal Therapy. IEEE Trans. Biomed. Eng., 57(5), 2010. Cover Page, PMC3857613. [ bib | http ]
[56] D. Fuentes, R. Cardan, R. J. Stafford, J. Yung, G. D. Dodd-III, and Y. Feng. High Fidelity Computer Models for Prospective Treatment Planning of RF Ablation with in vitro Experimental Correlation. J. of Vascular and Interventional Radiology, 21(11):1725--1732, 2010. PMC2966506. [ bib | http ]
[57] D. Fuentes, J. T. Oden, K. R. Diller, J. Hazle, A. Elliott, A. Shetty, and R. J. Stafford. Computational Modeling and Real-Time Control of Patient-Specific Laser Treatment Cancer. Ann. BME., 37(4):763, 2009. PMC4064943. [ bib | http ]
[58] Y. Feng, D. Fuentes, A. Hawkins, J. Bass, and M. N. Rylander. Model-Based Optimization and Real-Time Control for Laser Treatment of Heterogeneous Soft Tissues. CMAME, 198(21-26):1742--1750, 2009. Advances in Simulation-Based Engineering Sciences Special Issue Honoring Prof. J. Tinsley Oden, PMC2871336. [ bib | http ]
[59] Y. Feng, D. Fuentes, A. Hawkins, J. Bass, M. N. Rylander, A. Elliott, A. Shetty, R. J. Stafford, and J. T. Oden. Nanoshell-Mediated Laser Surgery Simulation for Prostate Cancer Treatment. Engineering with Computers, 25(1):3--13, 2009. PMC2905827. [ bib | DOI ]
[60] J. T. Oden, K. R. Diller, C. Bajaj, J. C. Browne, J. Hazle, I. Babuška, J. Bass, L. Demkowicz, Y. Feng, D. Fuentes, S. Prudhomme, M. N. Rylander, R. J. Stafford, and Y. Zhang. Dynamic Data-Driven Finite Element Models for Laser Treatment of prostate cancer. Num. Meth. PDE, 23(4):904--922, 2007. PMC2850081. [ bib | http ]
[61] D. Fuentes, D. Littlefield, J.T. Oden, and S. Prudhomme. Extensions of goal-oriented error estimation methods to simulations of highly-nonlinear response of shock-loaded elastomer-reinforced structures. Comput. Methods Appl. Mech. Engrg., 195:4659--4680, 2006. [ bib | http ]
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