Thompson Lab

Dr. Reid Thompson

Reid Thompson, M.D., Ph.D. is an assistant professor of radiation medicine and a member of the Knight Cancer Institute’s Computational Biology Program.  He received his medical and doctorate degrees from the Albert Einstein College of Medicine and trained at the University of Pennsylvania. He also holds degrees in genetics and biophysical chemistry.

Research interests

Immunotherapy has opened a new frontier in cancer treatment and has improved survival for many patients with metastatic melanoma and other aggressive cancers. The field of immunotherapy is exciting and fast-evolving, however there remain a number of critical questions regarding predictors of immunotherapy response and treatment-related toxicity.  The Thompson Lab is actively engaged in this field broadly, and focused specifically on cancer neoepitope prediction and genomic correlates of immunotherapy response and toxicity. The lab has multiple active projects ongoing, from development of novel software tools and algorithms to analysis of large immunotherapy datasets to clinical informatics based investigations of cancer outcomes.

Lung cancer screening of high-risk individuals has been shown to improve survival in the population, and can lead to earlier diagnosis, earlier stage migration, and more effective treatment for the disease.  However, there are many outstanding issues and opportunities for improving lung cancer outcomes.  In conjunction with The Knight Cancer Institute's, Center for Cancer Early Detection Advanced Research (CEDAR), the Thompson Lab is investigating biomarkers for early detection of lung cancer and lung cancer outcomes prediction.

 Dr. Thompson serves as a co-leader of the Portland VA's Clinical Data Science Research Group (CDSRG).  Within the scope of the CDSRG, the Thompson Lab is actively investigating patterns of cancer care and long-term patient outcomes within the VA, particularly as related to radiotherapy.

The Thompson Lab also performs comparative radiation dosimetric analyses and has developed and maintains tools (e.g. RadOnc software package, available on CRAN) to facilitate this work for the broader scientific community.

About Thompson Lab

Julianne David, Ph.D. student

Mary Wood, Research Associate

April 13, 2018

Reid Thompson, M.D., Ph.D., assistant professor, presented webinar on Artificial Intelligence in Radiation Oncology

April 12, 2018

Artificial Intelligence in Radiation Oncology, ACR Data Science Institute podcast featuring Dr. Reid Thompson

March 7, 2018

Reid Thompson, M.D., Ph.D. participated in 60th Annual ASTRO panel, "Current Applications & Future Directions"

May 6, 2017

Reid Thompson, M.D., Ph.D., is recipient of a grant by the Sunlin & Priscilla Chou Foundation

December 1, 2019

Artificial Intelligence in Radiation Oncology.

Deig CR, Kanwar A, Thompson RF. Hematol Oncol Clin North Am. 2019 Dec;33(6):1095-1104. doi: 10.1016/j.hoc.2019.08.003. Epub 2019 Sep 11

November 7, 2019

Validity of Veterans Health Administration structured data to determine accurate smoking status. Golden SE, Hooker ER, Shull S, Howard M, Crothers K, Thompson RF, Slatore CG. Health Informatics J. 2019 Nov 7:1460458219882259. doi: 10.1177/1460458219882259.

October 24, 2019

Tumor Mutation Burden-From Doubts to Concerns. Wood MA, Nellore A, Thompson RF. JAMA Oncol. 2019 Oct 24. doi: 10.1001/jamaoncol.2019.4138.

September 16, 2019

Clinical Documentation and Patient Care Using Artificial Intelligence in Radiation Oncology. Luh JY, Thompson RF, Lin S. J Am Coll Radiol. 2019 Sep;16(9 Pt B):1343-1346. doi: 10.1016/j.jacr.2019.05.044

September 1, 2019

Using Artificial Intelligence to Improve the Quality and Safety of Radiation Therapy. Pillai M, Adapa K, Das SK, Mazur L, Dooley J, Marks LB, Thompson RF, Chera BS. J Am Coll Radiol. 2019 Sep;16(9 Pt B):1267-1272. doi: 10.1016/j.jacr.2019.06.001.

September 1, 2019

Enhancing Career Paths for Tomorrow's Radiation Oncologists. Vapiwala N, Thomas CR Jr, Grover S, Yap ML, Mitin T, Shulman LN, Gospodarowicz MK, Longo J, Petereit DG, Ennis RD, Hayman JA, Rodin D, Buchsbaum JC, Vikram B, Abdel-Wahab M, Epstein AH, Okunieff P, Goldwein J, Kupelian P, Weidhaas JB, Tucker MA, Boice JD Jr, Fuller CD, Thompson RF, Trister AD, Formenti SC,

May 1, 2019

The Potential and Pitfalls of Crowdsourced Algorithm Development in Radiation Oncology. Elhalawani H, Fuller CD, Thompson RF. JAMA Oncol. 2019 May 1;5(5):662-663. doi: 10.1001/jamaoncol.2019.0157.

December 1, 2018

Artificial intelligence in radiation oncology: A specialty-wide disruptive transformation? Thompson RF, Valdes G, Fuller CD, Carpenter CM, Morin O, Aneja S, Lindsay WD, Aerts HJWL, Agrimson B, Deville C Jr, Rosenthal SA, Yu JB, Thomas CR Jr. Radiother Oncol. 2018 Dec;129(3):421-426. doi: 10.1016/j.radonc.2018.05.030.