Samuel Luk, PhD

Assistant Professor, Boston University Chobanian & Avedisian School of Medicine

Biography

Samuel Luk, Ph.D. is an Assistant Professor of Radiation Oncology at Chobanian and Avedisian School of Medicine, Boston, MA, USA and a Medical Physicist at the Department of Radiation Oncology at Boston Medical Center.

Sam received his Ph.D. from the University of Arizona under the supervision of Professor Rolf Binder and was a postdoctoral fellow at the University of Washington with Professor Alan Kalet. He completed his medical physics residency training at the University of Washington and is board certified at American Board of Radiology – Therapeutic Medical Physics.

Sam’s research focus is on using artificial intelligence (AI) and Bayesian approach to detect potential errors in radiation oncology to ensure a safe and efficient delivery of radiotherapy treatments to cancer patients. One of the projects he has worked on is a Bayesian network-based error detection (EDBN) model to detect potential erroneous treatment plan parameters in radiotherapy during physics plan review. The core concept of the EDBN project is to build an AI model to detect potential errors in radiotherapy treatment plans, which is rare but could lead to reduction of therapeutic effects and increase normal tissue toxicity. He is also interested in data science in health care and currently working on a collaborative project to compare radiation oncology clinical practices among clinics from different countries.

Sam has published 17 peer-reviewed original research and review articles in condensed matter and medical physics and has been invited to multiple conferences to discuss AI and quality assurance. He is a member of American Association of Physicists in Medicine (AAPM) and volunteering in the work group of prevention of error in radiation oncology and machine intelligence subcommittee. He is also a member of the American Society of Radiation Oncology.

Publications

  • Published 4/8/2024

    Johnson PB, Schubert L, Kim GG, Faught J, Buckey C, Conroy L, Luk SMH, Schofield D, Parker S. AAPM WGPE report 394: Simulated error training for the physics plan and chart review. Med Phys. 2024 May; 51(5):3165-3172. PMID: 38588484.

    Read at: PubMed

  • Published 2/28/2023

    Kalendralis P, Luk SMH, Canters R, Eyssen D, Vaniqui A, Wolfs C, Murrer L, van Elmpt W, Kalet AM, Dekker A, van Soest J, Fijten R, Zegers CML, Bermejo I. Automatic quality assurance of radiotherapy treatment plans using Bayesian networks: A multi-institutional study. Front Oncol. 2023; 13:1099994. PMID: 36925935.

    Read at: PubMed

  • Published 2/10/2022

    Glenn MC, Wallner K, Luk SMH, Ermoian R, Tseng YD, Phillips M, Kim M. Impact of lung block shape on cardiac dose for total body irradiation. Phys Imaging Radiat Oncol. 2022 Jan; 21:30-34. PMID: 35243029.

    Read at: PubMed

  • Published 2/1/2022

    Petros Kalendralis , Denis Eyssen, Richard Canters, Samuel M. H. Luk ,AlanM.Kalet,Wouter vanElmpt, Rianne Fijten, Andre Dekker, Catharina M. L. Zegers, and Inigo Bermejo. External Validation of a Bayesian Network for Error Detection in Radiotherapy Plans. IEEE Transactions on Radiation and Plasma Medical Sciences. 2022; 6(2):200.

  • Published 1/5/2022

    Luk SMH, Wallner K, Glenn MC, Ermoian R, Phillips MH, Tseng YD, Kim M. Effect of total body irradiation lung block parameters on lung doses using three-dimensional dosimetry. J Appl Clin Med Phys. 2022 Apr; 23(4):e13513. PMID: 34985180.

    Read at: PubMed