Chief of Clinical Medical Physics
Director, Medical Dosimetry School
Education and Training
I received my PhD degree of Physics from Florida State University in 2006. I then pursued postdoctoral training in the Department of Radiation Oncology, at Duke University Medical Center, Durham, NC. I then joined the Faculty at the University of Nebraska Medical Center, Omaha, NE. In 2012 I came to the University of Maryland where I am currently an Assistant Professor in Radiation Oncology.
My research interests are in the areas of clinical data mining. With existing clinical database (patient data, radiation dose, and clinical outcomes), the treatment outcomes can be modeled and used to guide the treatment of future patients. I have devoted my efforts to model normal tissue complication probability (NTCP) using machine learning method. My clinical interests focus on development and implementation of innovative technologies in the clinical practice. While at the University of Maryland, I have implemented two programs into clinical practice: RayStation Treatment Planning System and thermal therapy program. I have contributed to non-measurement-based IMRT QA program, and TG-71 based electron dosimetry upgrade.
I am a member of American Association of Physicists in Medicine, and American Society for Therapeutic Radiology and Oncology. I am a member of the Board of Editors for Journal of Applied Clinical Medical Physics.
NTCP, IMRT/VMAT, SRS/SBRT, treatment planning system, and thermal therapy
H. Xu, M. Guerrero, S. Chen, X. Yang, K. Prado, C. Schinkel, "Clinical implementation of an electron monitor unit dosimetry system based on task group 71 report and a commercial calculation program", Accepted by Journal of Medical Physics
W. Choi , M. Xue , B. F Lane , M. K. Kang , K. Patel , P. Klahr , W. F. Regine , J. Wang , S. Chen , W. D'Souza , Wei Lu, “Individually optimized contrast-enhanced 4D-CT for radiotherapy simulation in pancreatic ductal adenocarcinoma”, Med. Phy. 43, 5659 (2016)
S. Chen, B. Yi, X. Yang, H. Xu, K. L. Prado and W. D. D’Souza, “Optimizing the MLC model parameters for IMRT in the RayStation treatment planning system”, Journal of Applied Clinical Medical Physics, Vol 16, No 5 (2015).
H. Boggs, M. Guerrero, K. Patel, S. Chen, F. Moeslein, P. Amin, Z. Vujaskovic, “Pelvic local recurrence in a patient with muscle-invasive bladder cancer treated with interstitial thermal therapy and interstitial brachytherapy”, Practical Radiation Oncology, Vol 5 (5), 2015, e483-e487.
J J Souchek, M J Baine, C Lin, S Rachagani, S Gupta, S Kaur, K Lester, D Zheng, S. Chen, L Smith, A Lazenby, S L Johansson, M Jain and S K Batra, “Unbiased analysis of pancreatic cancer radiation resistance reveals cholesterol biosynthesis as a novel target for radiosensitisation”, British Journal of Cancer (2014), 1-11.
S. Das, S. Chen, J. Deasy, S. Zhou, F. Yin, and L. Marks. “Combining multiple models to generate consensus: Application to radiation-induced pneumonitis prediction”, Med. Phys. 2008 Nov; 35(11): 5098-5109
S. Chen, S. Zhou, F. Yin, L. Marks and S. Das, “Using patient data similarities to predict radiation pneumonits via a self-organizing map”, Phys. Med. Biol. 2008; 53: 203
S. Chen, S. Zhou, F. Yin, L. Marks, S. Das, “Investigation of the Support Vector Machine Algorithm to Predict Lung Radiation-Induced Pneumonitis”, Med. Phys. 2007 Oct;34(10):3808-14
S. Chen, S. Zhou, J. Zhang, F. Yin, L. Marks, S. Das, “A Neural Network Model to Predict Lung Radiation-Induced Pneumonitis”, Med. Phys. 2007 Sep; 34(9):3420-7
S. Chen, H. Avakian,V. Burkert, P. Eugenio, et al (CLAS Collaboration), “Measurement of Deeply Virtual Compton Scattering with a Polarized Proton Target”, Phys. Rev. Lett. 2006; 97, 072002