Authors: Ishika Bhaumik, John M. Boone, Michael T Corwin, Eric S Diaz, Ahmadreza Ghasemiesfe, Andrew M. Hernandez, Sarah E. McKenney, Misagh Piran, Ali Uneri, Eric L White
Affiliation: UC Davis, UC Davis Health, University of California, Johns Hopkins Univ
Abstract Preview: Purpose: A new model CT scanner (Canon Aquilion One Insight) was recently installed at our institution, and it included a 3D Landmark (3DLM) scan for automatic scan planning, a new deep learning recon...
Authors: Huay Din, Grace Jianan Gang, Grace Hyun Kim, Michael F. McNitt-Gray, Joseph W. Stayman, Yijie Yuan
Affiliation: Johns Hopkins University, John Hopkins University, University of Pennsylvania, David Geffen School of Medicine at UCLA
Abstract Preview: Purpose:
Radiomics rely on quantitative features to discern underlying biological signatures. However, feature dependence on the imaging systems themselves hampers the creation of reproducible and ...
Authors: Christos Ilioudis, Marios Myronakis, Sotirios Raptis, Kyriaki Theodorou
Affiliation: Medical Physics Department, Medical School, University of Thessaly, Department of Information and Electronic Engineering, International Hellenic University (IHU)
Abstract Preview: Purpose: This study presents a radiomics-driven, machine learning framework developed to predict the possibility of Radiation Pneumonitis (RP), as a side effect of radiation therapy in lung cancer pat...
Authors: Wenfeng He, Tian Liu, Pretesh Patel, Richard L.J. Qiu, Keyur Shah, Tonghe Wang, Xiaofeng Yang, Chulong Zhang
Affiliation: Icahn School of Medicine at Mount Sinai, Emory University, Medical Physics Graduate Program, Duke Kunshan University, Memorial Sloan Kettering Cancer Center, Department of Radiation Oncology and Winship Cancer Institute, Emory University
Abstract Preview: Purpose: This study introduces a tracking-free approach to reconstruct 3D ultrasound (US) volumes from 2D freehand US scans. By eliminating the reliance on external tracking systems, this method aims ...
Authors: Yuli Lu, Chendong Ni, Cheng Qian, Kun Qian, Weiwei Sang, Chunhao Wang, Fan Xia, Zhenyu Yang, Fang-Fang Yin, Rihui Zhang, Haiming Zhu
Affiliation: Jiahui International Hospital, Radiation Oncology, Duke University, Medical Physics Graduate Program, Duke Kunshan University, Duke Kunshan University, The First People's Hospital of Kunshan
Abstract Preview: Purpose: To develop a radiomic quantification framework to evaluate the effects of radiomic image preprocessing hyperparameters (i.e., image resampling and discretization) on texture characterization ...
Authors: David Brizel, Kyle J. Lafata, Jian-Guo Liu, Yvonne M Mowery, Yvonne M Mowery, William Paul Segars, Jack B Stevens
Affiliation: Department of Physics, Duke University, Carl E. Ravin Advanced Imaging Laboratories and Center for Virtual Imaging Trials, Duke University Medical Center, Duke University, Department of Radiation Oncology, Duke University, University of Pittsburgh
Abstract Preview: Purpose: To develop a technique to quantify tumor topology using a unifying mathematical framework that integrates texture and morphology and to evaluate its feasibility as a prognostic biomarker for ...
Authors: Himanshu Joshi, Tian Liu, Deborah C Marshall, Joseph Shelton, Jing Wang, Xiaofeng Yang, Emi Yoshida, Boran Zhou
Affiliation: Department of Radiation Oncology, Baylor College of Medicine, Icahn School of Medicine at Mount Sinai, Emory University, Department of Population Health Science and Policy, Icahn School of Medicine at Mount Sinai, Department of Radiation Oncology, University of California, Department of Radiation Oncology and Winship Cancer Institute, Emory University
Abstract Preview: Purpose: Radiation-induced long-term toxicities, such as vaginal stenosis, significantly impact the quality of life for patients undergoing pelvic radiotherapy (RT) for gynecologic (GYN) malignancies....
Authors: Beth Bradshaw Ghavidel, Benyamin Khajetash, Yang Lei, Meysam Tavakoli
Affiliation: Icahn School of Medicine at Mount Sinai, Department of Medical Physics, School of Medicine, Iran University of Medical Sciences, Emory University, Department of Radiation Oncology, Emory University
Abstract Preview: Purpose: Pancreatic cancer is among the most aggressive types of cancer, with a five-year survival rate of approximately 10%. Recent studies show that radiomics and deep learning (DL)-based methods ar...
Authors: Mehdi Amini, Minerva Becker, Simina Chiriac, Alexandre Cusin, Dimitrios Daskalou, Ghasem Hajianfar, Sophie Neveu, Marcella Pucci, Yazdan Salimi, Pascal Senn, Habib Zaidi
Affiliation: Geneva University Hospital, Division of Radiology, Diagnostic Department, Geneva University Hospitals, Service of Otorhinolaryngology-Head and Neck Surgery, Department of Clinical Neurosciences, Geneva University Hospitals
Abstract Preview: Purpose: Personalized prediction of vestibular schwannoma (VS) tumour growth is crucial for guiding patient management decisions toward observation versus intervention. This study proposes an automate...
Authors: Jean Bourbeau, Jim Hogg, Miranda Kirby, Meghan Koo, Kalysta Makimoto, Wan Tan
Affiliation: Montreal Chest Institute of the Royal Victoria Hospital, McGill University Health Centre, Toronto Metropolitan University, Centre for Heart Lung Innovation, University of British Columbia
Abstract Preview: Purpose: Chronic obstructive pulmonary disease (COPD) exacerbations are burdensome to patients and healthcare systems. CT imaging-derived measures of emphysema and airway remodeling have been shown to...
Authors: David J. Carlson, Ming Chao, Tian Liu, Yong Hum Na, Kenneth E Rosenzweig, Robert Samstein, Lewis Tomalin
Affiliation: Icahn School of Medicine at Mount Sinai, Yale University School of Medicine, Department of Therapeutic Radiology, Yale University School of Medicine
Abstract Preview: Purpose: To investigate the potential of regional radiomic features extracted from five lung sub-lobes on pre-treatment CT as biomarkers for predicting radiation pneumonitis (RP) using machine learnin...
Authors: Morgan A. Daly, David J. Goodenough, Andrew M. Hernandez, John M. Hoffman, Joshua Levy, Michael F. McNitt-Gray, Ali Uneri, Bino Varghese
Affiliation: University of California, George Washington University, David Geffen School of Medicine at UCLA, Johns Hopkins Univ, University of Southern California, The Phantom Laboratory
Abstract Preview: Purpose: Quantitative imaging is affected by CT acquisition and reconstruction conditions, limiting robustness in multi-site or -scanner studies. This work aimed to develop a dataset that will enable ...
Authors: Cem Altunbas, Farhang Bayat, Roy Bliley, Brian Kavanagh, Uttam Pyakurel, Tyler Robin, Ryan Sabounchi
Affiliation: Department of Radiation Oncology, University of Colorado School of Medicine, Taussig Cancer Center, Cleveland Clinic
Abstract Preview: Purpose: The use of image features extracted from serial CBCT images to assess radiotherapy response and toxicity is an active research area. However, poor image quality often compromises reliability ...
Authors: Ryan Alden, Tithi Biswas, Kaushik Halder, Felix Maria-Joseph, Michael Mix, Rihan Podder, Tarun Kanti Podder
Affiliation: SUNY Upstate Medical University, IIT-Roorkee, University of Florida
Abstract Preview: Purpose: Radiomics feature-based model for predicting distant recurrence can potentially provide critical insight for clinical decision-making and assistance in treatment strategies. This study focuse...
Authors: Giavanna Luisa Jadick, Patrick J La Riviere
Affiliation: University of Chicago
Abstract Preview: Purpose: We assess two multi-measurement acquisition schemes for material decomposition with x-ray phase-contrast imaging (XPCI); demonstrating for the first time that multi-distance imaging can match...
Authors: Wookjin Choi, Michael Dichmann, Adam Dicker, Nilanjan Haldar, Yingcui Jia, Nicole L Simone, Eugene Storozynsky, Yevgeniy Vinogradskiy, Maria Werner-Wasik
Affiliation: Thomas Jefferson University, 9Department of Radiation Oncology, Thomas Jefferson University
Abstract Preview: Purpose: Cardiotoxicity remains a significant limitation for lung cancer patients treated with radiotherapy. Pre-radiotherapy cardiac conditions increase the probability of patients developing cardiot...
Authors: Rico Castillo, Katherine Gonzalez, Casey C. Heirman, Kyle J. Lafata, Xiang Li, Yvonne M Mowery, Yvonne M Mowery, Allison Pittman, Ashlyn G. Rickard, Breylon Riley
Affiliation: Duke University, Department of Radiation Oncology, Duke University, University of Pittsburgh
Abstract Preview: Purpose: To evaluate the relationships between quantitative imaging biomarkers and chemoradiation resistance in head and neck squamous cell carcinoma (HNSCC) using preclinical mouse models.
Met...
Authors: Liyuan Chen, Sepeadeh Radpour, David Sher, Jing Wang
Affiliation: Medical Artificial Intelligence and Automation (MAIA) Lab, Department of Radiation Oncology, UT Southwestern Medical Center, UT Southwestern Medical Center
Abstract Preview: Purpose: Accurate lymph node malignancy prediction is pivotal in optimizing radiation treatment strategies for head and neck (HN) cancer patients. While conventional radiomics models leverage intensit...
Authors: Aditya P. Apte, Joseph O. Deasy, Yusuf Emre Erdi, Anqi Fu, Johannes Hertrich, Andrew Jackson, Usman Mahmood, Jason Ocana, Trahan Sean, Amita Shukla-Dave
Affiliation: Department of Medical Physics, Memorial Sloan Kettering Cancer Center
Abstract Preview: Purpose: Automated AI-based quantitative CT tools hold immense promise for advancing clinical decision-making, yet their reproducibility and generalizability remain vulnerable to variability in imagin...