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Taxonomy: IM/TH- Image Analysis (Single modality or Multi-modality): Imaging biomarkers and radiomics
| MO-E115-GePD-F2-4 | Longitudinal Changes of Cone Beam Computed Tomography Based Radiomics Features During Chemoradiotherapy for Locally Advanced Lung Cancer L Shi1*, Y Rong1 , M Daly1 , B Dyer1 , S Benedict1 , P Wang2 , J Qiu2 , T Yamamoto1 , (1) University of California Davis Comprehensive Cancer Center, Sacramento, CA, (2) Taishan Medical University, Taian, Shandong |
| MO-E115-GePD-F2-5 | Radiomics Analysis of Contrast-Enhanced CT Images for Detection of Human Papilloma Virus in Patients with Oropharyngeal Cancers H Bagher-Ebadian*, C Liu , F Siddiqui , N Wen , B Movsas , I Chetty , Henry Ford Health System, Detroit, MI |
| SU-E-KDBRC-5 | An Investigation of Machine Learning Methods for Delta-Radiomic Feature Analysis Y Chang1*, F Yin2 , (1) Duke Kunshan University, Kunshan, ,(2) Duke University Medical Center, Durham, NC; Duke Kunshan University, Kunshan |
| SU-F-DBRB-5 | Exploring Feature Reliability On Multiple CT Image Acquisition Parameters for Abdominal Radiomic Studies - a Pilot Phantom Experiment L Lu , Y Liang*, B Zhao , Columbia University Medical Center, New York, NY |
| SU-F-DBRB-7 | Rectal Cancer Prognosis Prediction Using Radiomics From Pretreatment MRI X Zhong1*, N Li2 , K Sung1 , X Qi1 , (1) UCLA School of Medicine, Los Angeles, CA, (2) Cancer Hospital Chinese Academy of Medical Sciences, Beijing, China |
| SU-H300-GePD-F8-6 | Predicting Prognosis of Lung Cancer Patient Based On Radiomic Features From Slow CT Images S Sato1*, N Kadoya1 , K Takeda1 , T Kajikawa1 , T Yamamoto1 , K Takeda2 , K Jingu1 , (1) Department of Radiation Oncology, Tohoku University Graduate School of Medicine, Sendai, Japan (2) Department of Therapeutic Radiology, Tohoku University School of Medicine, Sendai, Japan |
| SU-H330-GePD-F6-6 | Cone-Beam CT Radiomics Features as Potential Predictors for Esophageal Cancer Response J Teruel*, K Du , P Galavis , NYU Langone Health, New York, NY |
| SU-I-GPD-J-54 | Efficient Multi-GPU Calculation of Local Radiomic Features From 2D and 3D Images R Neph*, K Sheng , UCLA Dept. of Radiation Oncology, Los Angeles, CA |
| TH-AB-DBRB-1 | Optimal Energy of Virtual Monoenergetic Imaging From Dual-Energy CT for Target Delineation and Radiation Response Assessment G Noid1*, D Schott1 , T Schmidt2 , A Tai1 , X Li1 , (1) Medical College of Wisconsin, Milwaukee, WI, (2) Marquette University, Milwaukee, WI, |
| TH-AB-DBRB-10 | Comparison of Single and Multi-Modality CT and MR Radiomics Models for Overall Survival and Local Control for Non-Small Cell Lung Cancer R N Mahon1*, G D Hugo2 , E Weiss1 , (1) Virginia Commonwealth University, Richmond, Virginia, (2) Washington University School of Medicine, St. Louis, MO |
| TU-AB-DBRB-7 | CT-Based Radiomic Analysis for Prediction of Liver Progression Risk in Hepatocellular Carcinoma Patients Treated with Stereotactic Body Radiation Therapy L Wei*, D Owen , M Mendiratta-Lala , B Rosen , K Cuneo , T Lawrence , R Ten Haken , I El Naqa , University of Michigan, Ann Arbor, MI |
| TU-AB-DBRB-8 | Radiomics Features Predict Tumor Volume Change During Head and Neck Cancer Radiotherapy M Surucu1*, I Mescioglu2 , F Cozzi1 , N Hurst1 , B Emami1 , J Roeske1 , (1) Loyola University Medical Center, Maywood, IL, (2) Lewis University, Romeoville, IL, |
| TU-C1030-GePD-F2-1 | CT/MRI-Based Radiomics Analysis to Predict Radiation Induced Xerostomia in Head and Neck Cancer Radiotherapy K Sheikh*, L Peng , S Lee , P Han , Z Cheng , P Lakshminarayanan , T McNutt , H Quon , J Lee , Department of Radiation Oncology and Molecular Radiation Sciences, Johns Hopkins University, Baltimore, MD |