Igor Shuryak, MD, PhD

  • Associate Professor of Radiation Oncology (in the Center for Radiological Research) at CUMC

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Overview

Igor Shuryak, MD, PhD, is an Associate Professor of Radiation Oncology (in the Center for Radiological Research) at CUMC. He earned a BA in Biology from Columbia University and an MD from SUNY Downstate College of Medicine with distinction in research. He then completed the intensive Cancer Training Program at Columbia University’s Mailman School of Public Health, where he honed his skills in cancer epidemiology and biostatistics. In 2006, he received his PhD with distinction from the Department of Environmental Health Sciences at Columbia University’s Mailman School of Public Health.

Academic Appointments

  • Associate Professor of Radiation Oncology (in the Center for Radiological Research) at CUMC

Languages

  • English
  • Russian

Credentials & Experience

Education & Training

  • BA, 1997 Biology and Environmental Sciences, Columbia College-Columbia University
  • MD, 2001 Medicine, SUNY - Downstate Medical Center
  • PhD, 2006 Environmental Health Sciences, Columbia University, Mailman School of Public Health

Committees, Societies, Councils

  • 2018 - Present: Member, National Council on Radiation Protection & Measurements (NCRP)
  • 2006 - Present: Member, Radiation Research Society

Honors & Awards

  • 2020: Michael Fry Award, Radiation Research Society
  • 2014: Radiation Research Jack Fowler Award, Radiation Research Society
  • 2011: Radiation Research Editor's Award, Radiation Research Society

Research

Dr. Shuryak's research is interdisciplinary, situated at the intersection of radiation biology, oncology, data science, and mathematical modeling. He focuses on quantitatively modeling radiation effects, including radiation carcinogenesis, tumor control and repopulation, normal tissue complications, radioresistance, and non-targeted effects. This work relies on implementation of applied mathematics, programming, statistics, and machine learning, using languages such as R, Python and Maple.

He is also a practitioner of machine learning, including causal inference methodologies, which he applies to better understand and model biological responses to ionizing radiation. He is interested in combining concepts from mechanistic models of radiation effects with modern machine learning techniques.

Throughout his career, his work has resulted in over 140 peer-reviewed publications, and he continues to integrate cutting-edge data science techniques to advance understanding in this field.

Selected Publications

  1. Shuryak I, Wang E, Brenner DJ. Understanding the impact of radiotherapy fractionation on overall survival in a large head and neck squamous cell carcinoma dataset: a comprehensive approach combining mechanistic and machine learning models. Front Oncol. 2024 Aug 13;14:1422211. doi: 10.3389/fonc.2024.1422211. PMID: 39193391; PMCID: PMC11347346.
  2. Wang E, Shuryak I, Brenner DJ. A competing risks machine learning study of neutron dose, fractionation, age, and sex effects on mortality in 21,000 mice. Sci Rep. 2024 Aug 2;14(1):17974. doi: 10.1038/s41598-024-68717-9. PMID: 39095647; PMCID: PMC11297256.
  3. Shuryak I, Royba E, Repin M, Turner HC, Garty G, Deoli N, Brenner DJ. A machine learning method for improving the accuracy of radiation biodosimetry by combining data from the dicentric chromosomes and micronucleus assays. Sci Rep. 2022 Dec 6;12(1):21077. doi: 10.1038/s41598-022-25453-2. PMID: 36473912; PMCID: PMC9726929.
  4. Shuryak I, Hall EJ, Brenner DJ. Dose dependence of accelerated repopulation in head and neck cancer: Supporting evidence and clinical implications. Radiother Oncol. 2018 Apr;127(1):20-26. doi: 10.1016/j.radonc.2018.02.015. Epub 2018 Mar 10. PMID: 29534828.
  5. Shuryak I, Loucas BD, Cornforth MN. Straightening Beta: Overdispersion of Lethal Chromosome Aberrations following Radiotherapeutic Doses Leads to Terminal Linearity in the Alpha-Beta Model. Front Oncol. 2017 Dec 21;7:318. doi: 10.3389/fonc.2017.00318. PMID: 29312888; PMCID: PMC5742594.
  6. Shuryak I, Fornace AJ Jr, Datta K, Suman S, Kumar S, Sachs RK, Brenner DJ. Scaling Human Cancer Risks from Low LET to High LET when Dose-Effect Relationships are Complex. Radiat Res. 2017 Apr;187(4):476-482. doi: 10.1667/RR009CC.1. Epub 2017 Feb 20. PMID: 28218889.
  7. Shuryak I, Carlson DJ, Brown JM, Brenner DJ. High-dose and fractionation effects in stereotactic radiation therapy: Analysis of tumor control data from 2965 patients. Radiother Oncol. 2015 Jun;115(3):327-34. doi: 10.1016/j.radonc.2015.05.013. Epub 2015 Jun 6. PMID: 26058991.
  8. Ng J, Shuryak I, Xu Y, Clifford Chao KS, Brenner DJ, Burri RJ. Predicting the risk of secondary lung malignancies associated with whole-breast radiation therapy. Int J Radiat Oncol Biol Phys. 2012 Jul 15;83(4):1101-6. doi: 10.1016/j.ijrobp.2011.09.052. Epub 2012 Jan 13. PMID: 22245205; PMCID: PMC4005006.
  9. Brenner DJ, Shuryak I, Einstein AJ. Impact of reduced patient life expectancy on potential cancer risks from radiologic imaging. Radiology. 2011 Oct;261(1):193-8. doi: 10.1148/radiol.11102452. Epub 2011 Jul 19. PMID: 21771956.
  10. Shuryak I, Brenner DJ. Effects of radiation quality on interactions between oxidative stress, protein and DNA damage in Deinococcus radiodurans. Radiat Environ Biophys. 2010 Nov;49(4):693-703. doi: 10.1007/s00411-010-0305-1. Epub 2010 Jun 24. PMID: 20574841.
  11. Shuryak I, Hahnfeldt P, Hlatky L, Sachs RK, Brenner DJ. A new view of radiation-induced cancer: integrating short- and long-term processes. Part I: approach. Radiat Environ Biophys. 2009 Aug;48(3):263-74. doi: 10.1007/s00411-009-0230-3. Epub 2009 Jun 18. Erratum in: Radiat Environ Biophys. 2011 Nov;50(4):607-8. PMID: 19536557; PMCID: PMC2714893.
  12. Shuryak I, Sachs RK, Hlatky L, Little MP, Hahnfeldt P, Brenner DJ. Radiation-induced leukemia at doses relevant to radiation therapy: modeling mechanisms and estimating risks. J Natl Cancer Inst. 2006 Dec 20;98(24):1794-806. doi: 10.1093/jnci/djj497. PMID: 17179481.

For a complete list of publications, please visit PubMed.gov