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Taxonomy: TH- External Beam- Photons: Treatment planning using machine learning/Knowledge Based Planning/automation
| MO-A-BRC-1 | An Automated Evaluation Tool for Quantitative Assessment of Knowledge-Based Planning Models J Harms*, D Stanley, R Popple, University of Alabama at Birmingham, Birmingham, AL |
| MO-A-BRC-2 | Development and Maintenance of a Knowledge-Based Planning Quality Assurance Tool for a Statewide Radiation Oncology Quality Consortium C Matrosic1*, K Dess1, K Torolski1, R Marsh1, M Grubb1, D Dryden2, D Jarema1, C Fraser3, P Paximadis4, M Dominello5, J Hayman1, S Jolly1, M Matuszak1, (1) University of Michigan, Ann Arbor, MI, (2) Covenant HealthCare, Boyne City, MI, (3) Henry Ford Health System, Detroit, MI, (4) Spectrum Health Lakeland, St. Joseph, MI, (5) Wayne State University School Of Medicine, Detroit, MI |
| MO-C930-IePD-F4-3 | Hazard Testing to Probe Points of Weakness in Automated Planning Tools K Nealon1,2*, R Douglas2, E Han1,2, S Kry1,2, V Reed2, S Simiele1,2, L Zhang2, L Court1,2 (1) University of Texas MD Anderson UTHealth Graduate School of Biomedical Sciences, (2) University of Texas MD Anderson Cancer Center, Houston, TX |
| MO-C930-IePD-F4-4 | Automated Clinical-Criteria-Driven Optimal Planning: Clinical Experience with 5000 Patients Q Huang, G Jhanwar*, J Yang, H Pham, L Cervino, J Deasy, M Zarepisheh, L Hong, Memorial Sloan Kettering Cancer Center, New York, NY |
| MO-E115-IePD-F3-2 | Hippocampal Sparing Whole Brain:RapidPlan Model V2.0 Training Process R Foster1*, A Magliari2, R Clark3, (1) Northwestern Medicine Chicago Proton Center, Warrenville, IL, (2) Varian Medical Systems Inc, (3) Varian Medical Systems Inc, |
| MO-H345-IePD-F7-1 | Automating Contouring and Treatment Planning for Pediatric 3D-Craniospinal Irradiation Therapy S Hernandez1,2*, J Parkes3, H Burger3, C Nguyen2, D Rhee2, A Paulino2, T Netherton1,2, R Mumme2, J Guma-de La Vega2, J Duryea2, C Cardenas4, R Howell1,2, D Fuentes1,2, J Pollard-Larkin1,2, L Court1,2, (1) UT MD Anderson Cancer Center UTHealth Graduate School of Biomedical Sciences, Houston, TX (2) The University of Texas MD Anderson Cancer Center, Houston, TX (3)Department of Radiation Oncology, Groote Schuur Hospital and University of Cape Town, Cape Town, South Africa (SA) (4) Department of Radiation Oncology, University of Alabama at Birmingham, Birmingham, AL |
| MO-H345-IePD-F7-3 | A Comparison of In-House and Shared Knowledge-Based Planning (KBP) Models for Bilateral Head and Neck Treatment Planning O Trejo*, H Li, K Guida, The University of Kansas Cancer Center, Kansas City, KS |
| MO-H345-IePD-F7-5 | The Impact of Advanced ESAPI-Based Automated Total Body Irradiation Treatment Planning On Plan Standardization R Frederick1,2*, L Van Dyke2, J Lovis2, A Hudson1,2, G Pierce1,2, (1) University of Calgary, Calgary, AB, CA, (2) Tom Baker Cancer Centre, Calgary, AB, CA |
| MO-H345-IePD-F7-6 | Development and Implementation of An Automated Planning Algorithm for Multi-Metastatic Stereotactic Radiosurgery Using Eclipse Scripting T Mann1,2*, N Ploquin1,2, K Thind1,3, (1) University of Calgary, Calgary, Alberta, CA, (2) Tom Baker Cancer Centre, Calgary, AB, CA, (3) Henry Ford Health Systems, Detroit, Michigan |
| MO-I430-BReP-F3-4 | Robust Multi-Site Deep Learning-Based Dose Predictions for Volumetric Modulated Arc Therapy Using the MR-Linac G Tsekas*, G Bol, B Raaymakers, University Medical Center Utrecht, Utrecht, UtrechtNL, |
| PO-GePV-M-310 | Dose Mimicking of Carcinoma Cervix Treatment Plans Using a Novel Convolutional Deep Neural Network G Singh1*, H Himani2, A Oinam1, D Thaper3, R Kamal3, B Rai1, V Kumar4, (1) PGIMER, Chandigarh, Chandigarh, IN, (2) HOMI BHABHA CANCER HOSPITAL, SANGRUR, Rupnagar, PB, IN, (3) ILBS, Delhi, IN, (4) Centre for Medical Physics, Chandigarh, CH, IN |
| PO-GePV-T-92 | Feasibility Study of a Deep Learning-Based Model Trained On Adults for Auto-Segmentation of Head-And-Neck OARs in Pediatric CT Images Z Shen1*, A Olch2, N Bai3, K Wong2, E Chang1, W Yang1, (1) University of Southern California, Los Angeles, CA, (2) Children's Hospital of LA, Los Angeles, CA, (3) DeepVoxel Inc., Riverside, CA |
| PO-GePV-T-101 | The Effect of AI Contouring On Head and Neck Patient Treatment Plan Optimization M Jones1*, P Mavroidis2, T Wagner1, S Stathakis1, (1)Mays Cancer Center - MD Anderson Cancer Center, San Antonio, TX, (2)University of North Carolina, Chapel Hill, NC |
| PO-GePV-T-203 | Improving Quality and Consistency in HARVEST Clinical Trial for Breast Cancer Patients Receiving Hypofractionated Intensity-Modulated Radiotherapy Via Knowledge-Based Planning M Chen*, L Cao, C Xu, J Chen, Department of Radiation Oncology, Ruijin Hospital, Shanghai, 31CN, |
| PO-GePV-T-251 | Exploration of One-Step Auto Planning: Tomotherapy MLC Sequence Prediction Yaoying Liu1,2, Xuying Shang1,2, Gaolong Zhang1, Xiaoyun Le1, Wei Zhao1, Chuanbin Xie2, Baolin Qu2, Shouping Xu3,* (1) Beihang University, School of Physics, Beijing, China. (2) The First Medical Center of PLA General Hospital, Department of Radiation Oncology, Beijing, China. (3) National Cancer Center/Cancer Hospital- Chinese Academy of Medical Sciences and Peking Union Medical College, Department of Radiation Oncology, Beijing, China. |
| PO-GePV-T-252 | Reinforcement Learning to Speed Up Conjugate Gradient Optimization in IMRT M Hakala1, S Basiri1, E Kuusela1, K Bush2*, (1) Varian Medical Systems Finland, Helsinki,FI, (2) Stanford University, Stanford, CA |
| PO-GePV-T-253 | Hippocampal Sparing Whole Brain: RapidPlan Model V2.0 Validation Process R Foster1*, R Clark2, A Magliari3, (1) Northwestern Medicine Chicago Proton Center, Warrenville, IL, (2) Varian Medical Systems Inc,(3) Varian Medical Systems Inc, |
| PO-GePV-T-254 | Transformer Network Assisted VMAT Optimization P Dong*, L Xing, Stanford University School of Medicine, Stanford, CA |
| PO-GePV-T-257 | Dose Predictions Facilitate Efficient Optimization of High-Quality Prostate Treatment Plans S Robertson*, D Lasher, B Kassas, Wellspan Health, York, PA |
| PO-GePV-T-276 | Assessment of Varian Ethos Intelligent Optimization Engine (IOE) for Stereotactic Body Radiation Therapy (SBRT) Treatment Plans for Lung Metastases A Pacheco1*, S Pokharel2, C Cross3, (1) GenesisCare USA, Naples, FL, (2) Boca Raton Regional Hospital, Estero, FL, (3) GenesisCare USA, Naples, FL |
| PO-GePV-T-292 | Can AI Auto-Segmentation Affect Treatment Plan Approval Decisions? M Jones1*, K Mcghee1, P Mavroidis2, S Stathakis4, (1) Mays Cancer Center - MD Anderson Cancer Center, San Antonio, TX, (2) University of North Carolina, Chapel Hill, NC |
| PO-GePV-T-299 | Title:Automated Testing Platform Within a Software Development Governance Framework for Treatment Planning System User Scripts J Lucido*, S Seetamsetty, D Ellerbusch, S Shiraishi, J Antolak, D Moseley, Mayo Clinic, Rochester, MN |
| PO-GePV-T-304 | Determination of Optimal Indicators for Anatomy-Based Automated Beam Setup in Breast Cancer E Costa1, A Gobert1, D Dagot1, Y Jiang1, J Vu-Bezin1*, (1) Institut Curie, Paris,FR |
| PO-GePV-T-313 | Limited Dataset Transfer Learning for Deep Learning Dose Prediction On Head and Neck Cancer Patients Treated with Involved Nodal Radiation Therapy Using Artificial Intelligence-Based Radiomics (INRT-AIR) H Wang*, M Lin, D Sher, S Jiang, D Nguyen, UT Southwestern Medical Center, Dallas, TX |
| PO-GePV-T-314 | Development and Validation of Knowledge Based Planning Model for Prostate Node Positive Stereotactic Body Radiation Therapy R Phurailatpam1*, D Patil2, V Raveendran3, K Joshi4, J Pk5, P Maitre6, V Murthy7, (1) Actrec, Tata Memorial Centre, Maharastra, ,IN, (2) ACTREC, Ratnagiri, ,IN, (3) Advanced Center for Treatment, Research and Education in Cancer (ACTREC), Tata Memorial Center, Navi Mumbai, MH, IN, (4) TATA MEMORIAL CENTRE, ACTREC, NAVI MUMBAI, Navi Mumbai, ,IN, (5) Actrec,tmc, ,,(6) Actrec,tmc, ,,(7) Actrec,tmc, |
| PO-GePV-T-402 | Validation of Automatic Planning Scripts for Prostate SBRT with and Without Lymph Nodes C Venencia*, M Almada, O Apaza Blanco, I Marquez, O Muriano, P Murina, Instituto Zunino -Fundacion Marie Curie, Cordoba, ARGENTINA |
| PO-GePV-T-404 | Genetic Algorithm and Neural Networks in Radiosurgery for Multiple Metastases JA Rojas-Lopez1*, CD Venencia2, MA Chesta1, F Tamarit1, (1) Universidad Nacional de Cordoba, Cordoba, ,AR, (2) Instituto Zunino, Cordoba, X, AR |
| SU-E-206-7 | Cardiac Substructures Specific Knowledge-Based Treatment Planning for Lung Radiotherapy S Momin1*, J Wolf1, J Roper1, Y Lei1, M Lloyd2, T Liu1, J Bradley1, K Higgins1, X Yang1, J Zhang1, (1) Department of Radiation Oncology and Winship Cancer Institute, Emory University, Atlanta, GA, 30322 (2) Department of Medicine, Division of Cardiology, Emory University, Atlanta, GA |
| SU-E-BRB-1 | Adaptation of Dose Prediction DenseNet for Prostate Cancer Patients Treated with Different Beam Modes Using Transfer Learning J Fu1*, Z Wang2, J Lewis3, X Qi2, (1) Stanford Radiation Oncology, Stanford, CA, (2) UCLA School of Medicine, Los Angeles, CA (3) Cedars-Sinai Medical Center, Pacific Palisades, CA |
| SU-E-BRB-4 | Clinical Commissioning and Implementation of An In-House Artificial Intelligence (AI) Tool for Automated Head and Neck Intensity Modulated Radiation Therapy (IMRT) Treatment Planning X Li1*, Y Sheng1, QJ Wu1, Y Ge2, C Wang1, D Brizel1, Y Mowery1, J Lee1, W Wang1, H Stephens1, D Yang1, F Yin1, Q Wu1, (1) Duke University Medical Center, Durham, NC, (2) University of North Carolina at Charlotte, Charlotte, NC |
| SU-F-BRB-2 | Automated Pipeline for Prostate Auto-Contouring and VMAT Planning M El Basha1,2*, Q Nguyen2, D Fuentes1,2, J Pollard-Larkin1,2, F Poenisch2, Z Yu1,2, S Frank2, C Cardenas3, C Nguyen2, A Olanrewaju2, C Tang2, S Shah2, A Aggarwal4, L Court1,2, (1) University of Texas MD Anderson Cancer Center UTHealth Graduate School of Biomedical Sciences, Houston, TX, (2) MD Anderson Cancer Center, Houston, TX, (3) The University of Alabama at Birmingham, Birmingham, AL, (4) Guy's and St. Thomas' NHS Foundation Trust, London, UK |
| SU-H300-IePD-F4-3 | Learned Iterative Shrinkage-Thresholding Algorithm (LISTA) for Sparse Rectangular Aperture Optimization Q Lyu*, M Cao, K Sheng, UCLA School of Medicine, Los Angeles, CA |
| SU-H300-IePD-F4-5 | Aperture and Control Point Weight Prediction for Breast VMAT Using Deep Learning L Vandewinckele1*, T Reynders2, S Petillion2, C Weltens1,2, F Maes3,4, W Crijns1,2, (1) Department of Oncology, Laboratory of Experimental Radiotherapy, KU Leuven, BE-Belgium, (2) Department of Radiation Oncology, UZ Leuven, BE-Belgium, (3) Department ESAT/PSI, KU Leuven, BE-Belgium,(4) Medical Imaging Research Center, UZ Leuven, BE-Belgium, |
| SU-H430-IePD-F5-1 | An Integrated Reporting Dataset for Investigating Programmatic Modifications of Radiotherapy Treatment Planning Data M Schmidt1*, P Szentivanyi2, F Reynoso1, N Knutson1, G Hugo1, E Sajo3, J Labrash1, B Sun1, P Zygmanski4, M Jandel3, A Price1, (1) Washington University School of Medicine in St. Louis, Saint Louis, MO, (2) Varian Medical Systems, (3) University of Massachusetts Lowell, Lowell, MA,(4) Brigham & Women's Hospital, Boston, MA |
| SU-J-BRC-4 | An Investigation of the Transferability of Deep-Learning Based Head and Neck Dose Prediction Model Among Different Institutions Y Chang*, B Teo, T Li, R McBeth, University of Pennsylvania, Philadelphia, PA |
| TH-F-BRC-6 | Understanding and Modeling Human-Robot Interaction of Artificial Intelligence (AI) Tool in Real Radiation Oncology Clinic Using Deep Neural Network: A Feasibility Study Based On Three Year Prospective Clinical Data D Yang*, C Murr, S Yoo, F Yin, QJ Wu, Y Sheng, Duke University Medical Center, Durham, NC |
| TU-D1000-IePD-F4-2 | An IMRT Auto-Planning Agent for Dose Gradient Control in Regions with Conflicting Constraints H Stephens1*, J Zhang2, Y Ge3, Q Wu1, Q Wu1, (1) Duke University, Durham, NC, (2) Emory University, Atlanta, GA, (3) University of North Carolina at Charlotte, Charlotte, NC, |
| TU-GH-BRB-10 | Intelligent Automatic Treatment Planning for Prostate Cancer Stereotactic Body Radiation Therapy Y Gao*, C Shen, Y Gonzalez, X Jia, Y Park, University of Texas Southwestern Medical Center, Dallas, TX |
| TU-H-BRA-2 | A User-Specific Automatic Contouring, Planning, and QA Solution for Cervical Cancer Radiotherapy D Rhee1*, A Jhingran1, B Rigaud1, K Huang1, C Anakwenze1, K Kisling2, B Beadle3, C Cardenas4, S Kry1, S Prajapati1, L Zhang1, K Brock1, W Shaw5, H Simonds6, L Court1, (1) MD Anderson Cancer Center, Houston, TX, (2) UC San Diego, La Jolla, CA, (3) Stanford University, Stanford, CA, (4) The University of Alabama at Birmingham, Birmingham, AL, (5) University of the Free State, Bloemfontein, ZA, (6) Stellenbosch University, Stellenbosch, Cape Town, ZA |
| TU-I345-IePD-F2-3 | Using Deep Neural Network for Beam Angle Selection in 4π IMRT Planning of Patients with Lung Cancer A Sadeghnejad Barkousaraie*, M Lin, S Jiang, D Nguyen, The University of Texas Southwestern Medical Center, Dallas, TX |
| TU-I345-IePD-F2-5 | Input Feature Design and Their Impact On the Artificial Intelligence Planning Agent’s Performance X Li1*, Y Ge2, Q Wu1, C Wang1, Y Sheng1, W Wang1, H Stephens1, F Yin1, QJ Wu1, (1) Duke University Medical Center, Durham, NC, (2) University of North Carolina at Charlotte, Charlotte, NC |
| WE-C1030-IePD-F3-4 | Development of Automated Sphere Placement Script for Lattice SBRT Using the Eclipse Scripting Application Programming Interface (ESAPI) W Tucker*, M Schmidt, T Mazur, J Hilliard, M Spraker, J Kavanaugh, Washington University School of Medicine in St. Louis, St. Louis, MO |
| WE-C1030-IePD-F4-3 | Stanford VMAT TBI Technique N Kovalchuk1*, E Simiele2, L Skinner1, Y Yang1, N Howell1, J Lewis1, C Hui1, E Blomain1, R Hoppe1, S Hiniker1, (1) Stanford University Cancer Center, Stanford, CA, (2) Rutgers University, New Brunswick, NJ |
| WE-FG-BRA-0 | Enhancing a Physicist's Role in Radiation Therapy Treatment Plan Assessment D Jacqmin1*, M Kim2*, S Parker3*, B Juneja4*, G Kim5*, L Rankine6*, (1) University of Wisconsin-Madison, Madison, WI, (2) University of Washington, Seattle, WA, (3) Wake Forest Baptist Health High Point Medical Center, Winston-Salem, NC, (4) MD Anderson Cancer Center at Cooper, Media, PA, (5) UC San Diego, La Jolla, CA, (6) The University of North Carolina at Chapel Hill, Chapel Hill, NC |
| WE-G-BRC-5 | Performing Fully Automated Treatment Planning Using Meta-Optimization C Huang*, Y Nomura, Y Yang, L Xing, Stanford University School of Medicine, Stanford, CA |