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Lei Ren, PhD

Academic Title:

Professor

Primary Appointment:

Radiation Oncology

Administrative Title:

Associate Chief of Physics Research in the Department of Radiation Oncology

Email:

lren@som.umaryland.edu

Download CV

Education and Training

  • Tsinghua University, Beijing, China                                                1999- 2003
    Academic Talent Program, School of Science
    B.S. in Physics and Mathematics

  • Duke University, Durham, NC                                                        2005- 2009
    Ph.D. in Medical Physics

Biosketch

Dr. Ren is a clinical medical physicist certified by ABR and a leading scientist in medical imaging and radiation therapy. His seminal research focuses on the image-guided radiation therapy (IGRT) and development and application of AI in radiation therapy.

Dr. Ren conducted some of the first studies on developing digital tomosynthesis (DTS) for fast, low-dose target localization in radiation therapy, which led to the development of the limited-angle intrafraction verification (LIVE) system for intrafraction verification in radiotherapy. His group also developed novel cone-beam CT (CBCT) scatter reduction and correction methods, DTS/CBCT/MRI image reconstruction methods using prior information and motion modeling, and 4D-CBCT sorting and reconstruction algorithms.

In recent years, Dr. Ren's group has focused on developing and implementing AI for radiation therapy applications. His research areas include developing novel AI, especially deep learning, techniques for deformable image registration, image synthesis, image reconstruction, image augmentation, 4D imaging, radiomics, clinical decision making, and digital phantom generation. They have been developing techniques to use deep learning and biomechanical modeling to generate on-board hybrid virtual-MRI/CBCT images to substantially improve the soft tissue contrast in CBCT for target localization in liver radiotherapy. In addition, his group is actively developing AI technologies for synthesizing highly realistic eXtended Modular ANthropomorphic (XMAN) phantoms for motion management and virtual clinical trials in radiation therapy. Recently, his group has been developing image reconstruction and processing techniques for novel imaging modalities such as prompt gamma imaging and protoaoustic imaging for proton dose verification.

The overall goal of Dr. Ren's research is to develop novel imaging and therapy technologies to improve the precision and outcome of radiation therapy treatments with high efficiency and minimal imaging dose. 

Dr. Ren's lab is actively seeking postdoc fellows. Please feel free to reach out if interested.

Research/Clinical Keywords

Image-guided radiation therapy (IGRT), AI, Deep learning, digital tomosynthesis, dose reduction, CBCT, scatter correction, 4D imaging, prior information, motion modeling, biomechanical modeling, deformable image registration, image synthesis, image reconstruction, image augmentation, radiomics, clinical decision making, digital phantom generation.

Highlighted Publications

Y. Cao, P. Sutera, ... & L. Ren, “Machine learning predicts conventional imaging metastasis-free survival (MFS) for oligometastatic castration-sensitive prostate cancer (omCSPC) using prostate-specific membrane antigen (PSMA) PET Radiomics”, Radiotherapy and Oncology, 110443, 2024

Y. Zhang, Z. Jiang, Y. Zhang, L. Ren, “A review on 4D cone-beam CT (4D-CBCT) in radiation therapy: technical advances and clinical applications”, Medical Physics (Journal cover paper), 51(8), 5164-5180, 2024

Y. Lang, Z. Jiang, L. Sun, P. Tran, S. Mossashebi, L. Xiang, L. Ren, “Patient Specific Deep Learning for 3D Protoacoustic Image Reconstruction and Dose Verification in Proton Therapy”, Medical Physics, 51(7), 7425-7438, 2024 

X. Ling, G. Alexander, J. Molitoris, J. Choi, L. Schumaker, P. Tran, R. Mehra, D. Gaykalova, L. Ren, “Radiomic Biomarkers of Locoregional Recurrence: Prognostic Insights from Oral Cavity Squamous Cell Carcinoma preoperative CT scans”, Frontiers in Oncology, 14, 2024

Y. Lang, Z. Jiang, L. Sun, L. Xiang, L. Ren, “Hybrid-Supervised Deep Learning for Domain Transfer 3D Protoacoustic Image Reconstruction”, Physics in Medicine and Biology, 69(8), 085007, 2024

X. Ling, G. Alexander, J. Molitoris, J. Choi, L. Schumaker, R. Mehra, D. Gaykalova, L. Ren, “Identification of CT-based non-invasive Radiographic Biomarkers for Overall Survival Stratification in Oral Cavity Squamous Cell Carcinoma”, Nature Scientific Report, 13, 21774, 2023

Z. Jiang, S. Wang, Y. Xu, L. Sun, G. Gonzalez, Y. Chen, J. Wu, L. Xiang, L. Ren, “Radiation-induced Acoustic Signal Denoising using a Supervised Deep Learning Framework for Imaging and Therapy Monitoring”, Physics in Medicine and Biology, 68, 235010, 2023

Z. Jiang, J. Polf, C. Barajas, M. Gobbert, L. Ren, “A Feasibility Study of Enhanced Prompt Gamma Imaging for Range Verification in Proton Therapy using Deep Learning”, Physics in Medicine and Biology, 68(7), 075001, 2023

Y. Cao, D. Kunaprayoon, L. Ren, “Interpretable AI-assisted Clinical Decision Making (CDM) for dose prescription in radiosurgery of brain metastases”, Radiotherapy and Oncology, 187, 109842, 2023

Y. Cao, D. Kunaprayoon, J. Xu, L. Ren, “AI-assisted Clinical Decision Making (CDM) for dose prescription in radiosurgery of brain metastases using three-path three-dimensional CNN”, Clinical and Translational Radiation Oncology, 39, 100565, 2023

Z. Jiang, L. Sun, W. Yao, J. Wu, L. Xiang, L. Ren, “3D in vivo dose verification in prostate proton therapy with deep learning-based proton-acoustic imaging”, Physics in Medicine and Biology, 67(21), 215012, 2022

Z. Jiang, Y. Chang, Z. Zhang, F. Yin, L. Ren, “Fast Four-dimensional Cone-beam Computed Tomography Reconstruction using Deformable Convolutional Networks”, Medical Physics, 49(10), 6461-6476, 2022

Z. Zhang, Z. Jiang, H. Zhong, K. Lu, F. Yin, L. Ren, “Patient-specific Synthetic MRI Generation from CBCT for image guidance in liver SBRT”, Precision Radiation Oncology, 6, 110-118, 2022

Z. Zhang, M. Huang, Z. Jiang, Y. Chang, K. Lu, F. Yin, P. Tran, D. Wu, C. Beltran, L. Ren, “Patient-specific deep learning model to enhance 4D-CBCT Image for radiomics analysis”, Physics in Medicine and Biology, 67(8), 085003, 2022

Z. Zhang, M. Huang, Z. Jiang, Y. Chang, J. Torok, F. Yin, L. Ren, “4D Radiomics: Impact of 4D-CBCT Image Quality on Radiomic Analysis”, Physics in Medicine and Biology, 66(4), 045023, 2021.

Z. Jiang, F. Yin, Y. Ge, L. Ren, “Enhancing Digital Tomosynthesis (DTS) for Lung Radiotherapy Guidance using Patient-Specific Deep Learning Model”, Physics in Medicine and Biology, 66(3), 035009, 2021.

Y. Chang, K. Lafata, P. Segars, F. Yin, L. Ren, “Development of realistic Multi-contrast Textured XCAT (MT-XCAT) phantoms using a dual-discriminator conditional-generative adversarial network (D-CGAN)”, Physics in Medicine and Biology, 65(6), 065009, 2020

Z. Jiang, F. Yin, Y. Ge, L. Ren, “A multi-scale framework with unsupervised joint training of convolutional neural networks for pulmonary deformable image registration”, Physics in Medicine and Biology, 65(1), 015011, 2020

X. Jia, L. Ren, J. Cai, “Point/Counterpoint: Clinical implementation of AI technologies will require interpretable AI models”, Medical Physics, 47(1), 1-4, 2020

Z. Jiang, Y. Chen, Y. Zhang, Y. Ge, F. Yin, L. Ren, “Augmentation of CBCT Reconstructed from Under-sampled Projections using Deep Learning”, IEEE Transactions on Medical Imaging, 38(11), 2705-2715, 2019

J. Pham, W. Harris, W. Sun, Z. Yang, F. Yin, L. Ren, “Predicting Real-Time 3D Deformation Field Maps (DFM) based on Volumetric Cine MRI (VC-MRI) and Artificial Neural Networks for On-board 4D Target Tracking: A feasibility study”, Physics in Medicine and Biology, 64(16), 165016, 2019

C. Shieh, Y. Gonzalez, B. Li, X. Jia, S. Rit, C. Mory, M. Riblett, G. Hugo, Y. Zhang, L. Ren, P. Keall, “SPARE: SPArse-view REconstruction challenge for 4D cone-beam CT from a one-minute scan”, Medical Physics, 46(9), 3799-3811, 2019

G. Ding, Y. Zhang, L. Ren, “Imaging dose resulting from optimized procedures with Limited-angle Intra-fractional Verification (LIVE) system during SBRT lung treatment”, Medical Physics, 46(6), 2709-2715, 2019

W. Harris, C. Wang, F.F. Yin, J. Cai, L. Ren, “A Novel Method to Generate On-board 4D MRI Using Prior 4D MRI and On-board kV Projections From a Conventional LINAC for Target Localization in Liver SBRT”, Medical Physics, 45(7), 3238-3245, 2018. (Medical Physics Letter)

Y. Chen, F.F. Yin, Y. Zhang, Y. Zhang, L. Ren, “Low dose CBCT reconstruction via prior contour based total variation regularization (PCTV): a feasibility study”, Physics in Medicine and Biology, 63(8), 085014, 2018

A. Dubey, A. Iliopoulos, X. Sun, F.F. Yin, L. Ren, “Iterative Inversion of Deformation Vector Fields with Feedback Control”, Medical Physics, 45(7), 3147-3160, 2018

Y. Zhang, X. Deng, F.F. Yin, L. Ren, “Image Acquisition Optimization of a Limited-Angle Intrafraction Verification (LIVE) System for Lung Radiotherapy”, Medical Physics, 45(1), 340-351, 2018  (Editor’s Pick)

Y. Zhang, F.F. Yin, Y. Zhang, L. Ren, “Reducing scan angle using adaptive prior knowledge for a limited-angle intrafraction verification (LIVE) system for conformal arc radiotherapy,” Physics in Medicine and Biology, 62(9), 3859-3882, 2017

C. Wang, F. Yin, W. Segars, Z. Chang, L. Ren, “Development of a Computerized 4D MRI Phantom for Liver Motion Study”, Technology in Cancer Research & Treatment, 16(6), 1051-1059, 2017

Y. Zhang, F.F. Yin, T. Pan, I. Vergalasova, and L. Ren, “Preliminary clinical evaluation of a 4D-CBCT estimation technique using prior information and limited-angle projections,” Radiotherapy and Oncology, 115(1), 22-29, 2015

L. Ren, Y. Zhang, and F.F. Yin, “Medical Physics Letter: A limited-angle intrafraction verification (LIVE) system for radiation therapy,” Med. Phys., 41(2), 020701, 2014. (Medical Physics Letter)

Y. Zhang, F.F. Yin, W.P. Segars, and L. Ren, “A technique for estimating 4D-CBCT using prior knowledge and limited-angle projections,” Med. Phys., 40(12), 121701, 2013

L. Ren, I. Chetty, J. Zhang, J. Jin, Q.J. Wu, H. Yan, D. Brizel, W.R. Lee, C. Willett, B. Movsas, and F.F. Yin, “Development and clinical evaluation of a three-dimensional cone-beam computed tomography estimation method using a deformation field map,” Int. J. Radiat. Oncol. Biol. Phys., 82(5), 1584-93, 2012

L. Ren, F. Yin, I. Chetty, D. Jaffray, and J. Jin, “Feasibility study of a synchronized-moving-grid (SMOG) system to improve image quality in Cone-Beam Computed Tomography (CBCT)”, Med. Phys., 39(8), 5099-5110, 2012

L. Ren, D.J. Godfrey, H. Yan, Q.J. Wu, and F.F. Yin, “Automatic registration between reference and on-board digital tomosynthesis images for positioning verification,” Med. Phys. 35, 664-672, 2008

L. Ren, J. Zhang, D. Thongphiew, D.J. Godfrey, Q.J. Wu, S. Zhou, and F.F. Yin, “A novel digital tomosynthesis (DTS) reconstruction method using a deformation field map,” Med. Phys. 35, 3110-3115, 2008. (Medical Physics Letter)

Additional Publication Citations

BOOK CHAPTERS:
D. Godfrey, Z. Jiang, L. Ren, J. Wu, F. Yin, Chapter “Tomosynthesis applications in Radiation Oncology” in the book “Tomosynthesis Imaging”, to be published in 2023

Y. Zhang, W. Harris, J. Wang, L. Ren, Chapter “Virtual imaging for abdominal IGRT” in the book “Principles and Practice of Image-Guided Abdominal Radiation Therapy”, by IOP Publishing, 2021

L. Ren, Y. Zhang, Chapter “Combined kV/MV imaging and tomosynthesis” in the book “Image Guidance in Radiation Therapy: Techniques, Accuracy, and Limitations”, by Medical Physics Publishing, 2018

L. Ren, Fang-Fang Yin, Chapter “Advances in Patient Setup and Target Localization” in the book “Advanced and Emerging Technologies in Radiation Oncology Physics”, by Taylor & Francis, 2018.

N. Wen, C. Glide-Hurst, K. Snyder, M. Hoogeman, M. Descovich, L. Ren, I. Chetty, “Treatment Verification and Delivery” in the book “Principles and Practice of Image-Guided Radiation Therapy of Lung Cancer”, by Taylor & Francis, 2017

L. Ren, Martina Descovich, and Jing Wang, Chapter “Advances in Verification and Delivery Techniques” in the book “Principles and Practice of Image-Guided Radiation Therapy of Lung Cancer”, by Taylor & Francis, 2017

D. Godfrey, L. Ren, J. Wu, F.F. Yin, Chapter “Tomosynthesis Applications in Radiation Oncology” in the book “Tomosynthesis Imaging”, published by Taylor & Francis, 2014.

L. Ren, Samuel Ryu, Chapter “Radiation Therapy: IMRT, Cyberknife, Gamma Knife, Proton Beam” in the book “Image-guided Cancer Therapy: A Multiple-disciplinary Approach”, published by Springer, 2013.

Q.J. Wu, D. Godfrey, L. Ren, S. Yoo, F.F. Yin, Chapter “On-board Digital Tomosynthesis: An Emerging New Technology for Image-Guided Radiation Therapy” in the book “Image-guided Radiation Therapy”, published by Taylor & Francis, 2012.

Clinical Specialty Details

Dr. Ren's clinical expertise focuses on stereotactic radiosurgery (SRS) and stereotactic body radiation therapy (SBRT) of brain, spine, lung and liver cancer patients as well as motion management strategies.

Awards and Affiliations

  • Selected for the John R. Cameron Young Investigator Symposium in the AAPM 63rd Annual Meeting, Virtual, 2021 (Advisor and Senior author)
  • Distinguished Associate Editor, Medical Physics journal, 2020
  • Fellow of AAPM, 2020
  • Selected for the John R. Cameron Young Investigator Symposium in the AAPM 62nd Annual Meeting, Virtual, 2020 (Advisor and Senior author)
  • Thomas Gorrie Clinical Leadership Impact Award from the Duke Clinical Leadership Program (DCLP), 2019 
  • “Director’s Award for Exemplary Service” from Duke Medical Physics Program, 2019
  • Top 5 team of the AAPM Grand Challenge for 4D-CBCT reconstruction, AAPM, 2018
  • Selected for the John R. Cameron Young Investigator Symposium in the AAPM 59th Annual Meeting, Denver, CO, 2017 (Advisor and Senior author)
  • Science Council Junior Investigator Award in the AAPM 58th Annual Meeting, Washington, DC, 2016 (Advisor and Senior author)
  • Merit Award from ISMRM Annual Meeting, Singapore, 2016 (Advisor and Senior author)
  • “Excellence in Mentorship” Award from Duke Medical Physics Program, 2015
  • ASTRO 2010 Annual Meeting Basic Science Abstract Award, 2010 
  • “Excellence in Research” Award from Duke Medical Physics Program, 2008
  • Selected for the John R. Cameron Young Investigator Symposium in the AAPM 48th Annual Meeting, Orlando, FL, 2006
  • “Excellence in Research” Award from Duke Medical Physics Program, 2006
  • Fellowship from Duke Medical Physics Program, 2005
  • Distinguished Graduate Award from Tsinghua University, 2003
  • Member of American Association of Physicists in Medicine (AAPM), 2007-present
  • Member of American Society of Therapeutic Radiology and Oncology (ASTRO), 2009-present
  • Member of the Duke Cancer Institute (DCI), 2017-present
  • Member of IEEE, 2018-present  

Grants and Contracts

  • 3-dimensional prompt gamma imaging for online proton beam dose verification
    NIH/NCI, R01CA279013, 2023-2027
    Role: PI

  • eXtended Modular ANthropomorphic (XMAN) phantom for Imaging and Treatment Optimization in Radiotherapy
    NIH/NIBIB, R01EB032680, 2022-2026
    Role: PI

  • Study of Biological and Radiographic Biomarkers and Association with Ancestry and Survival Disparities in Oral Cavity Squamous Cell Carcinoma Using AI Approaches
    NIH/NIDCR, R01DE033426, 2024-2029
    Role: Multi-PI

  • 3D in vivo dosimetry for FLASH proton therapy
    NIH/NCI, U01CA288351, 2024-2029
    Role: Multi-PI

  • Radiation modulation of cell plasticity programs determine prostate cancer oligometastatic potential
    NIH/NCI, U54 ROBIN, 2022-2027
    Role: Multi-PI of Project 1 and Resource sharing core.

  • Hybrid virtual-MRI/CBCT: A new paradigm for image guidance in liver SBRT
    NIH/NIBIB, R01EB028324, 2019-2025
    Role: PI          

  • A Limited-angle Intra-fractional Verification (LIVE) System for SBRT Treatments
    NIH/NCI, R01CA184173, 2014-2020
    Role: PI      

  • Simulation tools for 3D and 4D CT and Dosimetry
    NIH/NIBIB, 2R01EB001838, 2020-2024
    Role: Co-investigator
  • Center for Virtual Imaging Trials: Development of Virtual Patient Population for CT Research
    NIH/NIBIB, P41EB028744, 2021-2025
    Role: Co-investigator
  • A Synchronized Moving Grid (SMOG) System to Improve CBCT for IGRT and ART
    NIH/NCI, 1R01CA166948, 2012-2018
    Role: Co-investigator

  • Developing a workflow for clinical evaluation of a hybrid virtual-MRI/CBCT system for precision image guidance in radiation therapy
    Varian Medical System, 2020-2022
    Role: PI 

  • Duke Bridge Fund, 2019-2021
    Role: PI
  • Prospective Clinical Trial of Digital Tomosynthesis (DTS) for On-line Target Localization and Verification in Lung and Breast Radiotherapy
    Varian Medical System, 2016-2017
    Role: co-PI
  • Clinical Implementation and Evaluation of DTS for Ultra-low Dose Inter and Intrafraction Imaging in Image Guided Radiation Therapy
    Varian Medical System, 2013-2016
    Role: co-PI

  • Clinical implementation and evaluation of a 3D QA device
    ScandiDos AB, 2011-2014
    Role: co-investigator

Community Service

Invited talks:

  • “Interpretable/Explainable AI in Radiation Therapy”
    L. Ren
    Invited talk to AAPM Annual Meeting, July 2024
  • “Interpretable AI: Advancements, Challenges and Paths Ahead”
    L. Ren
    Invited talk to ASTRO Annual Meeting, 2024
  • “The Quantum Leap: Bridging AI, Physics, and Medicine for Revolutionary Innovations in Radiation Therapy”
    L. Ren
    Invited talk to GWU Barry Berman Memorial Lecture Series, April 11, 2024
  • “AI in medical imaging for proton therapy”
    L. Ren
    Invited talk to Mayo Clinic proton research workshop, April 2024
  • “AI for Imaging and Image Guidance in Radiation Oncology”
    L. Ren
    Invited talk to Stanford Symposium on Emerging Technologies and AI for Modern Radiation Oncology, 2023
  • “Emerging Role of Medical Physicists in Virtual Clinical Trials”
    L. Ren
    Invited talk at ASTRO Annual Meeting, October 2023
  • “AI for clinical decision support: Current and Future”
    L. Ren
    Invited talk at AAPM Annual Meeting, July 2023
  • “AI-Assisted Image Guidance and Clinical Decision Making in Radiation Therapy”
    L. Ren
    Invited talk to Stanford Physics Seminar Series, September 2023
  • “Clinical translation of AI in IGRT”
    L. Ren
    Invited talk to the ASTRO Annual Meeting Education Session: Clinical implementation and translation of AI in Radiation Oncology: challenges, pitfalls, and promises, 2022
  • “The Emerging Use of AI in Image-Guided Radiation Therapy”
    L. Ren
    Invited talk to the Conference on Machine Intelligence in Medical Imaging (CMIMI), 2022
  • “Virtual Clinical Trials in Radiation Therapy”
    L. Ren
    Invited talk to the Virtual Clinical Trials Symposium at AAPM annual meeting in 2022
  • “The Emerging Use of AI in Image-Guided Radiation Therapy”
    L. Ren
    Invited talk to the SIIM-AAPM Joint Symposium: Machine Intelligence in Medical Imaging at AAPM annual meeting in 2022
  • “Advances and Applications of AI in IGRT”
    L. Ren
    DKU summer school lecture, 2022
  • “Developments and Advances in AI for Image Guided Radiation Therapy”
    L. Ren
    Invited talk to Hongkong Polytechnic University, Hongkong, 2022
  • “AI in IGRT: Advances and Applications”
    L. Ren
    Invited talk to Annual Radiation Oncology Meeting in Hebei, China, 2022
  • “Advances of AI in Image-Guided Radiation Therapy”
    L. Ren
    Invited talk to the Practical AI in Radiation Oncology Symposium, University of Maryland, 2022
  • “Clinical Applications of AI in Radiotherapy”
    L. Ren
    Invited talk to the Radiobiology and physics course, University of Maryland, 2022
  • “The Emerging Use of AI in Image-Guided Radiation Therapy”
    L. Ren
    Invited talk to the Conference on Machine Intelligence in Medical Imaging (CMIMI), 2022
  • “Artificial Intelligence (AI) for Image-guided radiotherapy (IGRT)”
    L. Ren
    Invited talk by Henry Ford Cancer Institute-Cancer Research Grand Rounds, 2021
  • “4D-CBCT: Where Are We and What's Next?”
    L. Ren
    Invited talk to the SAM session at AAPM annual meeting in 2021
  • “International Mentoring for Medical Physics Scholars and Students”
    L. Ren
    Invited talk to International Medical Physics Education Conference, Hongkong, 2021
  • “AI Based Image Augmentation: Advances and Clinical Implications”
    L. Ren
    Invited talk to the SAM session at AAPM annual meeting in 2021
  • “NIH R01, Hybrid Virtual-MRI/CBCT: A New Paradigm for Image Guidance in Liver SBRT”
    L. Ren
    Invited talk to the Principal Investigator Scientific Highlights Symposium at AAPM annual meeting in 2021
  • “Advances in AI for Image Guided Radiation Therapy”
    L. Ren
    Invited talk to Bioengineering department at UMD, 2021
  • “AI for image augmentation, registration, and digital simulation”
    L. Ren
    Invited talk to SEAAPM, 2021
  • “Medical image synthesis for digital simulation and image augmentation”
    L. Ren
    Invited talk to the SAM session at AAPM annual meeting in 2020
  • “Fast low-dose intelligent imaging for image-guided radiation therapy (IGRT)”
    L. Ren
    Invited talk by the University of Texas at Southwest, 2020
  • “AI for image-guided radiation therapy (IGRT)”
    L. Ren
    Invited talk by Mayo Clinic, 2020
  • “AI for image-guided radiation therapy (IGRT)”
    L. Ren
    Invited talk by Stanford, 2020
  • “Advances and applications of deep learning in image-guided radiation therapy”
    L. Ren
    Invited talk to Duke Computing Symposium, 2020
  • “Advancements and Clinical Applications of 4D-CT/CBCT”
    L. Ren
    Invited talk to the Education Session, ASTRO annual meeting, 2018
  • “4D-CBCT reconstruction using prior knowledge and deformation models”
    Y. Zhang, Z. Jiang, X. Liu, L. Ren (Senior and Corresponding Author)
    Invited talk as Top 5 Teams for AAPM Grand Challenges Symposium: Image Reconstruction for 4D-CBCT, AAPM annual meeting, 2018
  • “Minimizing effects of respiratory motion: principles, strategies and clinical implications”
    L. Ren
    Invited talk and Chair of the SAM session at AAPM annual meeting in 2018
  • “Combined kV/MV imaging and tomosynthesis”
    L. Ren
    Invited talk to the AAPM summer school, Nashville, TN, July 26-28, 2018
  • “4D Cone-beam CT: Developments and Applications”
    L. Ren
    Invited talk and Chair of the Education Course at AAPM Annual Meeting in 2017
  • “Emerging Technology in Robotic Stereotactic Radiosurgery and Stereotactic Body Radiotherapy (SRS/SBRT)”
    L. Ren
    Invited talk and Chair of the SAM session at AAPM Annual Meeting in 2016
  • “Real time imaging verification and tracking for moving targets”
    L. Ren
    Invited talk and Chair of the Education Course at AAPM Annual Meeting in 2015
  • “3D/4D Imaging Verification Using Digital Tomosynthesis (DTS)”
    L. Ren
    Invited talk to the Society for Industrial and Applied Mathematics (SIAM) Conference on Imaging Science, Hong Kong, May 12-14, 2014

Professional Activity

  • 2023-present Vice-Chair of AAPM Annual Meeting Subcomittee
  • 2023-present Deputy Editor of Medical Physics journal
  • 2022-2023    Member of the NIH Study Section on Radiation Therapeutics and Biology (RTB)
  • 2021             Member of the NIH Study Section on Radiation Therapy and Biology (RTB) SBIR/STTR - ZRG1 OTC1-R(11)
  • 2020-present Member of the NIH Study Section on Academic-Industrial Partnerships for Translation of Medical Technologies – SBIB Q57
  • 2019-2020     Member of the NIH Study Section on Small Business: Medical Imaging – SBIB (10)
  • 2020             Member of the NIH Study Section on Early Phase Clinical Trials in Imaging and Image-Guided Interventions – SBIB A(56) R
  • 2019             Member of the NIH Study Section on Imaging Guided Interventions and Surgery (IGIS)
  • 2022             Organizer and Director of Symposium on Practical AI in Radiation Oncology at the University of Maryland
  • 2020-present  ASTRO Annual Meeting Education Committee
  • 2017-present  ASTRO Research Grants Evaluation Subcommittee
  • 2022              ASTRO Radiation Oncology Institute (ROI) grant reviewer
  • 2022              ASTRO seed grant reviewer
  • 2022-2024      AAPM Research Committee (RSRCH)
  • 2021-2024      AAPM Specialty Meetings Oversight Subcommittee
  • 2022-present   AAPM Joint Working Group for Research Seed Funding Initiative
  • 2019-2021, 2023 AAPM Annual Meeting Therapy Scientific Program Co-Director in 2020 and Director in 2021 and 2023
  • 2019-present  Member of the AAPM Annual Meeting Scientific Program Working Group
  • 2018-2020     AAPM Working Group for Non-clinical Professionals
  • 2020             Mentor for AAPM Summer Undergraduate Fellowship Program
  • 2019-2020     Organizing Committee of the AAPM Grand Challenge: MArkerless lung target Tracking CHallenge (MATCH)
  • 2020-2021     Guest editor of the special issue on deep learning in radiotherapy for IEEE TRPMS.
  • 2019              Duke Clinical Leadership Program (DCLP) Fellow Review Committee
  • 2019              Selected as a Duke Clinical Leadership Program (DCLP) Fellow
  • 2018              Invited Ph.D. Thesis Examiner to University of Sydney
  • 2019              Invited Guest Editor of Special Issue on Quantitative Imaging for Radiation Oncology  in Quantitative Imaging in Medicine and Surgery journal
  • 2018              Invited speaker and Faculty for the AAPM summer school
  • 2016-present  Board of Associate Editors of Medical Physics journal (Senior Associate Editor)
  • 2016-present  Editorial board member of Cancer Translational Medicine journal
  • 2018-present   NACMPA best paper award selection committee
  • 2016-2017      Book proposal reviewer for Taylor & Francis
  • 2011-2016      Guest associate editor of Medical Physics journal
  • 2013-2014      Grant reviewer of Technology Evaluation in the Elderly Network (TVN) Catalyst Grant Program funded by the Government of Canada’s Networks of Centers of Excellence (NCE) program
  • 2009-present   Reviewer of Medical Physics Journal, Physics in Medicine and Biology, Radiotherapy and Oncology, International Journal of Radiation Oncology Biology Physics, TCRT, Journal of X-ray Science and Technology, PLOS ONE, IEEE TMI, etc.
  • 2010-present  Scientific abstract reviewer of AAPM annual meeting
  • 2013-present  Scientific abstract reviewer of ASTRO annual meeting
  • 2014-present  Session Chair and Moderator/Discussant of ASTRO annual meeting sessions
  • 2015-present  Session Chair and Moderator of AAPM annual meeting sessions
  • 2017-2019      Chair of the Qualify Exam Committee of the Duke Medical Physics Graduate Program
  • 2020-2021      Board Member at Large of the Medical Physics Academic Council (MPAC) of the Duke Medical Physics Graduate Program
  • 2020-2021      Chair of the Faculty Affairs Committee (FAC) of the Duke Medical Physics Graduate Program

Previous Positions

  • Henry Ford Health System, Dept. of Radiation Oncology                  2009- 2011
    Senior Associate Medical Physics Faculty           

  • Duke Univ. Medical Center, Dept. of Radiation Oncology                   2011- 2015     
    Assistant Professor

  • Duke Univ. Medical Center, Dept. of Radiation Oncology                   2015- 2020 
    Associate Professor

  • Duke Univ. Medical Center, Dept. of Radiation Oncology                   2020- 2021     
    Professor and Director of Physics Research

  • Duke Univ. Medical Center, Dept. of Radiation Oncology                   2021- present     
    Adjunct Professor                  

Board Certification

Certified by American Board of Radiology (ABR) in Therapeutic Radiological Physics, 2012

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