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Keywords: lung
| MO-B-TRACK 6-3 | Predicting PD-L1 Expression Level in Non-Small Cell Lung Cancer On Computed tomography Using Machine Learning T Shiinoki*, K Fujimoto, Y Kawazoe, Y Yuasa, M Kajima, Y Manabe, T Hirano, K Matsunaga, H Tanaka, Yamaguchi University |
| MO-B-TRACK 6-4 | Principal Component Analysis of Quantitative Computed Tomography Features and Visual Emphysema Scores: Association with Lung Function Decline M Koo1*, W Tan2, J Hogg2, J Bourbeau3, C Hague2, J Leipsic2, and M Kirby1,2 for the CanCOLD Collaborative Research Group and The Canadian Respiratory Research Network, (1) Ryerson University, Toronto, ON, CA, (2) Centre For Heart Lung Innovation, St. Paul's Hospital, Vancouver, BC, CA, (3) McGill University Health Centre Research Institute, McGill University, Montreal, QC, CA |
| MO-IePD-TRACK 4-7 | Can Unified Data Improve the Performance of Radiomics-Based Prognostic Prediction in Lung Cancer Patients? Y Sugai*, N Kadoya, S Tanaka, S Tanabe, M Umeda, T Yamamoto, K Takeda, S Dobashi, H Ohashi, K Takeda, K Jingu, Tohoku University, Sendai, 04JP, |
| MO-IePD-TRACK 6-5 | Survival Prediction of Locally Advanced Non-Small Cell Lung Cancer Via Machine Learning Techniques Based On Multi-Region Radiomics Features and Clinical Risk Factors R Nishioka1, D Kawahara2, N Imano2, Y Nagata1,3(1)Medical and Dental Sciences Course, Graduate School of Biomedical & Health Sciences, Hiroshima University, Hirohima, JP(2)Department of Radiation Oncology, Graduate School of Biomedical Health Sciences, Hiroshima University Hirohima, JP(3)Hiroshima High-Precision Radiotherapy Cancer Center Hirohima, JP |
| PO-GePV-M-5 | Radiation Induced Lung Damage Tissue Segmentation and Classification Framework A Szmul1*, E Chandy1,4, C Veiga1, A Stavropoulou1, J Jacob1,2, D Landau3, C Hiley4, J McClelland1, (1) Centre for Medical Image Computing, University College London, London, UK, (2) Department of Respiratory Medicine, University College London, London, UK, (3) Guys & St Thomas NHS Foundation Trust, London, UK, (4) Cancer Institute, UCL, London, UK |
| PO-GePV-M-8 | A 3D Multi-Modality Lung Tumor Segmentation Method Based On Deep Learning S Wang1*, L Yuan2, E Weiss3, R Mahon4, (1) Virginia Commonwealth University, Richmond, VA, (2) Virginia Commonwealth University Medical Center, Richmond, VA, (3) Virginia Commonwealth University, Richmond, VA, (4) Washington University in St. Louis, St. Louis, MO |
| PO-GePV-M-22 | Deep Learning–based COVID-19 Pneumonia Classification Using Chest CT Images: Model Generalizability D Nguyen1,2,a*, F Kay3, J Tan2, Y Yan2, Y Ng3, P Iyengar2, R Peshock3, S Jiang1,2,a, (1) Medical Artificial Intelligence and Automation (MAIA) Laboratory, UT Southwestern Medical Center, Dallas, TX, USA, (2) Department of Radiation Oncology, UT Southwestern Medical Center, Dallas, TX, USA, (3) Department of Radiology, UT Southwestern Medical Center, Dallas, TX, USA, (a) Co-correspondence authors: {Dan.Nguyen, Steve.Jiang}@UTSouthwestern.edu |
| PO-GePV-M-40 | Radiomics Analysis Improves Machine Learning Models Assessing Chronic Obstructive Pulmonary Disease R Au1*, K Makimoto1, W Tan2, J Bourbeau3, J Hogg2, M Kirby1, (1) Ryerson University, Toronto, ON, CA, (2) Centre For Heart Lung Innovation, University Of British Columbia, Vancouver, BC, CA, (3) McGill University, Montreal, QC, CA |
| PO-GePV-M-51 | A Multichannel Feature-Based Approach for Longitudinal Lung CT Registration in the Presence of Radiation Induced Lung Damage A Stavropoulou1*, A Szmul1, E Chandy1,2, C Veiga1, D Landau2,3, J McClelland1, (1) University College London, UK, (2) University College Hospital London, UK, (3) Guys & St Thomas NHS Foundation Trust, UK |
| PO-GePV-M-66 | Impact of 4DCT Artifacts On Local Control for Lung SBRT L Rakotondravohitra*, J Adamson, Duke University Medical Center, Durham, NC |
| PO-GePV-M-92 | Evaluation of Online Planning Strategies for CBCT-Based Adaptive Radiotherapy for Locally Advanced Lung Cancer J Kim*, W Mao, I Gallagher, J Riess, S Vance, B Movsas, IJ Chetty, A Kretzler, Henry Ford Health System, Detroit, MI |
| PO-GePV-M-94 | AI-Based Online Adaptive Radiation Therapy for Lung Cancer Treatment W Mao*, J Riess, J Kim, S Vance, P Parikh, H Li, B Zhao, B Movsas, I Chetty, A Kretzker, Henry Ford Health System, Detroit, MI |
| PO-GePV-M-136 | Feasibility of Diagnostic Dose Fast-Helical Free Breathing CT Scan Protocol for Ventilation Measurement M Lauria*, B Stiehl, L Naumann, A Santhanam, D O'Connell, K Singhrao, J Goldin, I Barjaktarevic, D Low, University of California, Los Angeles, Los Angeles, CA |
| PO-GePV-M-141 | Using Previously Registered CBCT Image to Facilitate Online HCT to CBCT Image Registration in Lung Stereotactic Body Radiation Therapy J Liang*, D Yan, J Wloch, J Sliwinski, I Grills, C Stevens, T Guerrero, Q Liu, William Beaumont Hospital, Royal Oak, MI |
| PO-GePV-M-233 | A Knowledge-Based Automatic Lung IMRT Planning Method for Partial Heart Sparing L Yuan*, J Sohn, R Singh, E Weiss, S Kim, Virginia Commonwealth University, Richmond, VA |
| PO-GePV-T-69 | 4D Treatment Planning for Lung Proton Therapy: Treatment Design and Evaluation V T Taasti*, D Hattu, F Vaassen, R Canters, M Velders, J Mannens, J van Loon, I Rinaldi, M Unipan, W van Elmpt, Department of Radiation Oncology (MAASTRO), GROW - School for Oncology, Maastricht University Medical Centre+, Maastricht, The Netherlands. |
| PO-GePV-T-192 | Design of a Respiratory Motion Quality Assurance System with Portal Dosimetry and Customizable Tumor Phantom H Tan*, L Tan, C Koh, K Ang, S Park, National Cancer Centre Singapore, Singapore, 01 |
| PO-GePV-T-201 | Automated and Clinical-Criteria-Driven Planning for Locally Advanced Non-Small-Cell Lung Cancer Using the Expedited Constrained Hierarchical Optimization (ECHO) System Q Huang, L Hong, Y Zhou*, G Jhanwar, J Yang, H Pham, E Yorke, L Cervino, J Deasy, M Zarepisheh, Memorial Sloan Kettering Cancer Center, New York, NY |
| PO-GePV-T-262 | A Retrospective Study to Establish Recommendations for Plan Quality Metrics in Linac Lung SBRT S Taghizadehghahremanloo, F Akbari*, D Pearson, University of Toledo, Toledo, OH |
| PO-GePV-T-317 | The Impact of Flattening Filter Free On Remaining Volume at Risk in Lung Cases for VMAT and IMRT Techniques M Alfishawy1*, (1) International Medical Center, Cairo, EG |
| PO-GePV-T-334 | Pre-Treatment 4DCT Fiducial Marker Combination Selection for Robotic Lung SBRT W Belcher*, A Ju, J Jung, East Carolina Univ, Greenville, NC |
| PO-GePV-T-335 | Prediction of Fiducial Marker Positions in Robotic SBRT Using 4D-CTs at Different Treatment Dates J Jung1*, W Belcher1, K Patel1, E Patel1, K Yang2, S Sharma2, A Ju2, (1) East Carolina Univ, Greenville, NC, (2) Medical School of East Carolina Univ, Greenville, NC |
| PO-GePV-T-336 | The 4D Composite Dose Study of the Breath Motion Effect During the Lung Stereotactic Body Radiotherapy (SBRT) Z Xia*, F Wang, Y Xu, J Xu, Kansas University Medical Center, Kansas City, KS |
| PO-GePV-T-397 | New Dosimetric Guidelines for Acuros Through Comparative Evaluation of SBRT Lung Treatment Plans Against AAA M Pacella*, M Webster, S Tanny, N Joyce, L Constine, M Milano, I Yeo, University of Rochester, Rochester, NY |
| PO-GePV-T-407 | Dosimetric Case Study of Lung SBRT with Two Adjacent Targets: One ISO Vs Two ISOs J Zhang1*, B Lee2, W Inouye3, R Kwon3, W Lien1, (1) Southern California Permanente Medical Group, Los Angeles, CA (2) Loma Linda University Medical Center, Loma Linda, CA, (3) VA Long Beach Healthcare System, Long Beach, CA |
| PO-GePV-T-410 | Predictive Model of Lung Tumor Intrafraction Motion Variability L Knybel1*, J Cvek1, M Penhaker2, (1) University Hospital Ostrava, Ostrava,CZ, (2) VSB- Technical University Of Ostrava,CZ |
| PO-GePV-T-417 | Appropriate Modality for Salvage Radiation Therapy for Local Failure After Primary Lung SBRT T Arsenault*, K Lyons, A Gross, T Biswas, M Yao, N Azar, C Towe, T Podder, University Hospitals Cleveland Medical Center, Cleveland, OH |
| PO-GePV-T-420 | Dosimetric Comparison of Coplanar and Noncoplanar Beam Arrangements for Radiotherapy of Patients with Lung Cancer: A Meta-Analysis M Ma*, J Dai, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, China, BeijingCN, |
| PO-GePV-T-445 | Relative Response of Murine Lung Tumors From Conventional Radiotherapy (CRT) Versus Pulsed Low-Dose-Rate (PLDR) Radiotherapy T Dos Santos*, D Cvetkovic, L Chen, C Ma, Fox Chase Cancer Center, Philadelphia, PA |
| SU-D-TRACK 4-2 | Automated Predictive Models for Lung ART J Kavanaugh1*, G Hugo1, Z Ji1, J Fontenot4, (1) Washington University School of Medicine, St. Louis, MO, (2) Mary Bird Perkins Cancer Center, Baton Rouge, LA |
| SU-D-TRACK 4-3 | Biomechanical Simulation of Lung Motion for Tumor Position Estimation During Radiation Therapy M Ranjbar1*, P Sabouri2, S Mossahebi3, A Sawant3, P Mohindra3, G Lasio3, L Topoleski1, (1) University Of Maryland, Baltimore County, Baltimore, MD, (2) Miami Cancer Institute, Miami, FL, (3) University of Maryland School of Medicine, Baltimore, MD. |
| SU-E-TRACK 5-7 | Prediction of Organ-At-Risk Doses Using An Artificial Intelligence Algorithm: Clinical Validation and Estimated Benefit to Treatment Planning for Lung SBRT P Brodin1*, L Schulte2, D Pappas2, W Martin3, X Shen3, A Basavatia3, N Ohri1, M Garg1, S Kalnicki3, C Carpenter2, W Tome1, (1) Albert Einstein College of Medicine and Montefiore Medical Center, Bronx, NY, (2) Siris Medical, Newburyport, MA, (3) Montefiore Medical Center, New York, NY |
| SU-E-TRACK 6-1 | A Multi-Modality Radiomics-Based Model for Recurrence Risk Stratification in Non-Small Cell Lung Cancer J Christie1*, O Daher1, M Abdelrazek1, P Lang1, V Nair2, S Mattonen1, (1) Western University, London, ON, CA, (2) University of Washington School of Medicine, Seattle, WA |
| SU-E-TRACK 6-3 | JACK KROHMER EARLY-CAREER INVESTIGATOR COMPETITION WINNER: Multi-Group Multi-Block Data Integration for Harmonizing 18F-FDG-PET/CT Radiomics Associated with Circulating Tumor Cells and Predicting Recurrence-Free Survival Across Independent Lung Cancer Radiotherapy Studies S Lee*, G Kao, S Feigenberg, Y Fan, Y Xiao, University of Pennsylvania, Philadelphia, PA |
| SU-IePD-TRACK 2-2 | Prediction of EGFR Mutations, Subtypes, and Uncommon Mutations in Lung Adenocarcinoma Based On Machine Learning Y Kawazoe*, T Shiinoki, K Fujimoto, Y Yuasa, T Hirano, K Matsunaga, H Tanaka, Yamaguchi University |
| SU-IePD-TRACK 2-5 | Evaluation of Computer-Aided Nodule Assessment and Risk Yield (CANARY) in Korean Patients for Prediction of Invasiveness of Early Lung Adenocarcinoma Juyoung Lee1,2*, Seong Yong Park, M.D., Ph.D.3, Jin Sung Kim, Ph.D.1, (1) Department of Radiation Oncology, Yonsei University College of Medicine, Seodaemun-gu, Seoul, KR, (2) Department of Integrative Medicine, Yonsei University College of Medicine, Seoul, KR, (3) Department of Thoracic and Cardiovascular Surgery, Yonsei University College of Medicine, Seoul, KR |
| SU-IePD-TRACK 2-6 | Development of Machine Learning Based Algorithm for Prediction of Invasiveness of Early-Lung Adenocarcinoma by Using Chest Computed Tomography Juyoung Lee1,2*, Seong Yong Park, M.D., Ph.D.3, Jin Sung Kim, Ph.D.1, (1) Department of Radiation Oncology, Yonsei University College of Medicine, Seodaemun-gu, Seoul, KR, (2) Department of Integrative Medicine, Yonsei University College of Medicine, Seoul, KR, (3) Department of Thoracic and Cardiovascular Surgery, Yonsei University College of Medicine, Seoul, KR |
| TH-B-TRACK 6-3 | Prediction of Lung Tumor Position Using 0.35 T Cine MRgRT in Retrospective Study J Shin1,2*, Z Ji1, Y Huang1, B Lewis1, A Guta1, S Oh3, J Kim2, T Kim1, (1) Washington University in St. Louis, Saint Louis, MO, (2) Yonsei University College of Medicine, Seoul, ,KR, (3) Allegheny General Hospital, Wexford, PA |
| TH-B-TRACK 6-6 | Markerless Tracking of Lung Tumor Motion Using Simulated Coded Aperture Scatter Imaging A Mahl*, B Miller, C Altunbas, B Kavanagh, M Miften, B Jones, University of Colorado Anschutz Medical Campus, Aurora, CO |
| TH-E-TRACK 6-5 | Demonstrating the Practical Limitation of a Previously Validated Knowledge-Based Planning Model for SIB Lung SBRT of Large (> 5 Cm) Tumors J Visak*, A Webster, M Kudrimoti, R McGarry, M Randall, D Pokhrel, University of Kentucky, Lexington, KY |
| TH-F-TRACK 4-6 | Quantifying Radiation-Induced Lung Injury as a Function of Regional Radiation Therapy Dose Using Hyperpolarized-129Xe MRI L Rankine1,2*, Z Wang2, E Bier2, C Kelsey2, S Das1, L Marks1, B Driehuys2, (1) The University of North Carolina at Chapel Hill, Chapel Hill, NC, (2) Duke University, Durham, NC |
| TH-F-TRACK 6-1 | Development and Evaluation of a Bi-Polar Gated Respiratory Motion Management Strategy for Lung SBRT Z Li1*, L Zhang2, J Qiu2, S Zhang3, X Zheng2, Q Wu4, (1) Department of Radiation Oncology, Shanghai Sixth People's Hospital (2) Department of Radiation Oncology, Fudan University Huadong Hospital, (3) Fudan University, (4) Duke University Medical Center, Durham, NC |
| TU-C-TRACK 4-3 | BEST IN PHYSICS (MULTI-DISCIPLINARY): Lung Treatment Planning with Parametric Response Mapping Function Guidance C K Matrosic*, D R Owen, D Polan, Y Sun, S Jolly, C Schonewolf, M Schipper, R Ten Haken, C Galban, M Matuszak, University of Michigan, Ann Arbor, MI |
| TU-D-TRACK 3-5 | Synthesize 3D Realistic CT Textures and Anatomy in the XCAT Phantom Using Generative Adversarial Network (GAN) Y Yuan*, L Ren, Y Chang, Duke University Medical Center, Durham, NC |
| TU-IePD-TRACK 1-2 | Anatomically Realistic Simulation of Random Human Airway Trees J Whitehead*, L Torres, A Hahn, S Fain, M Speidel, M Wagner, University of Wisconsin, Madison, WI |
| TU-IePD-TRACK 3-1 | Deep Learning-Based Real-Time Volumetric Imaging Using Single CBCT Projections Y Lei*, Z Tian, T Wang, J Roper, A Kesarwala, E Schreibmann, K Higgins, J Bradley, T Liu, X Yang, Emory Univ, Atlanta, GA |
| WE-F-TRACK 6-3 | Changes in Post-Treatment Cardiac PET Avidity Predict Overall Survival in Lung Cancer Patients Treated with Chemoradiation T Santangelo1*, F Forghani1, C Rusthoven1, R Castillo2, E Castillo3, B Jones1, T Guerrero3, Y Vinogradskiy1, (1) University of Colorado, Denver, CO, (2) Emory Univ, Atlanta, GA, (3) Beaumont Health Research Institute, Houston, TX |
| WE-F-TRACK 6-7 | Computational Prediction of Symptomatic RP Based On Planning Computed Tomography Images Using Topologically Invariant Betti Numbers Prior to Stereotactic Body Radiation Therapy K Ninomiya1*, H Arimura1, T Yoshitake2, T Hirose2, Y Shioyama3, (1) Kyushu University, Fukuoka, JP (2) Kyushu University Hospital, Fukuoka, JP (3) SAGA HIMAT Foundation, Saga, JP |
| WE-IePD-TRACK 3-2 | Characterization of Lobe-Wise Ventilation and Elasticity in Patients with Chronic Obstructive Pulmonary Disease M Lauria*, B Stiehl, L Naumann, A Santhanam, D O'Connell, K Singhrao, J Goldin, I Barjaktarevic, D Low, University of California, Los Angeles, Los Angeles, CA |
| WE-IePD-TRACK 3-3 | Machine Learning Based Prediction of Big Inter-Fractional Changes in Lung Tumor Motion During Radiotherapy Course Using Robust Feature Selection Q Wang*, L Dong, B Teo, H Lin, S O'Reilly, University of Pennsylvania, Philadelphia, PA |
| WE-IePD-TRACK 3-4 | Powering Predictive Treatment Planning by a Seq2seq Deep Learning Predictor D Lee*, Y Hu, L KUO, S Alam, E Yorke, A Rimner, P Zhang, Memorial Sloan-Kettering Cancer Center, New York, NY |
| WE-IePD-TRACK 3-6 | Comparison of 3D Deep Convolutional Neural Networks and Training Strategies for Ventilated Lung Segmentation Using Multi-Nuclear Hyperpolarized Gas MRI J Astley*, A Biancardi, P Hughes, L Smith, H Marshall, J Eaden, N Weatherley, G Collier, J Wild, B Tahir, The University of Sheffield, Sheffield, United Kingdom |
| WE-IePD-TRACK 4-2 | Imaging Biomarkers for Radiation-Induced Airway Changes in a Swine Model E Wallat1*, A Wuschner1, M Flakus1, J Reinhardt2, G Christensen2, J Bayouth1, (1) University of Wisconsin, Madison, WI, (2) University of Iowa, Iowa City, IA |
| WE-IePD-TRACK 5-2 | Dosimetric Impact of Dose Calculation Algorithms On Lung SBRT Plan for COPD Patients S Jang*, S Lee, X Zhang, K Mak, A Hirsch, M Truong, Boston Medical Center and Boston University School of Medicine, Boston, MA |
| WE-IePD-TRACK 5-5 | Uncertainties in the Lung Heterogeneity Correction and Local Control for Lung SBRT B Erickson*, B Ackerson, C Kelsey, F Yin, W Giles, J Adamson, Duke University, Durham, NC |
| WE-IePD-TRACK 5-6 | Feasibility of Using 6MV-FFF Halcyon RDS for Single-Isocenter/Two-Lesion Lung SBRT A Webster*, J Visak, M Bernard, R McGarry, M Kudrimoti, D Pokhrel, University of Kentucky, Lexington, KY |