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Results for "investigate utility": 11 found

A Novel Linac Onboard Dual-Layer Kv Imager Provides Increased Clinical CBCT Contrast and Metal Artifact Reduction Using Virtual Monoenergetic Images

Authors: Ross I. Berbeco, Vera Birrer, Raphael Bruegger, Pablo Corral Arroyo, Roshanak Etemadpour, Dianne M. Ferguson, Rony Fueglistaller, Thomas C. Harris, Yue-Houng Hu, Matthew W. Jacobson, Mathias Lehmann, Marios Myronakis

Affiliation: Brigham and Women's Hospital, Harvard Medial School, Dana-Farber Cancer Institute, Department of Radiation Oncology, Dana Farber/Brigham and Women's Cancer Center, Department of Radiation Oncology, Brigham and Women’s Hospital, Dana-Farber Cancer Institute, Harvard Medical School, Brigham and Women's Hospital, Varian Imaging Laboratory, Dana-Farber Cancer Institute

Abstract Preview: Purpose: Dual-energy imaging offers benefits, including metal artifact reductions (MAR) and improved contrast, that enhance visualization. Currently, dual-energy imaging is largely limited to CT scann...

Advancing Magnetic Resonance Imaging (MRI) Safety Clearance: Utilizing Dual-Energy CT (DECT) Material Decomposition for Foreign Object Assessment

Authors: Anzi Zhao

Affiliation: Northwestern Medicine

Abstract Preview: Purpose: This study investigates the utility of Dual-Energy Computed Tomography (DECT) material decomposition in resolving Magnetic Resonance Imaging (MRI) safety concerns for patients with unidentifi...

Deep Learning-Based Ventricular Auto-Segmentation for Dosimetric Analysis in Intraventricular Tumor SRS

Authors: John Byun, Juan J Cardona, Steven D Chang, Cynthia Fu-Yu Chuang, Xuejun Gu, Yusuke Hori, Hao Jiang, Fred Lam, Lianli Liu, Weiguo Lu, David Park, Erqi Pollom, Elham Rahimy, Deyaaldeen Abu Reesh, Scott Soltys, Gregory Szalkowski, Lei Wang

Affiliation: Department of Radiation Oncology, Stanford University, Department of Neurosurgery, Stanford School of Medicine, Department of Neurosurgery, Stanford University, Medical Artificial Intelligence and Automation (MAIA) Lab, Department of Radiation Oncology, UT Southwestern Medical Center, UT Southwestern Medical Center, Department of Radiation Oncology, Stanford University School of Medicine

Abstract Preview: Purpose:
Intraventricular tumors pose significant challenges in neurosurgery due to their complex location. Therefore, brain SRS could be a better treatment option. At our institution, some patient...

Detector Physics-Incorporated Diffusion Denoising Models for Digital Breast Tomosynthesis with Dual-Layer Flat Panel Detectors

Authors: Alexander Bookbinder, Matthew Tivnan, Xiangyi Wu, Wei Zhao

Affiliation: Stony Brook Medicine, Massachusetts General Hospital

Abstract Preview: Purpose: To investigate and benchmark a system-adaptive diffusion-based digital breast tomosynthesis (DBT) denoising model for a direct-indirect dual-layer flat panel detector (DI-DLFPD) with a k-edge...

Emulating Human Perception of Low-Dose CT Image Quality Via Deep Generative Models

Authors: Jongduk Baek, Jooho Lee, Adam S. Wang

Affiliation: Stanford University, Yonsei University

Abstract Preview: Purpose: Optimizing the balance between radiation dose and image quality in computed tomography (CT) is important for minimizing patient X-ray exposure while maintaining diagnostic accuracy. While rad...

Hypersight-Archer Study: Improved Target Coverage and Organ-at-Risk Sparing Via Adaptive Radiotherapy of Head and Neck Cancer Using Direct-Dose Calculation on Cone Beam CT

Authors: Cheryl Anderson, Lara Best, Amanda Cherpak, Jennifer DeGiobbi, Marc C. LeBlanc, R. Lee MacDonald, Peter R. Martin, Natasha McMaster, Murali Rajaraman, James L. Robar, Lucy Ward, Derek Wilke, Kenny Zhan

Affiliation: Department of Radiation Oncology, QE2 Cancer Centre, Nova Scotia Health

Abstract Preview: Purpose: This work investigates the potential benefit of adaptive planning using the Ethos radiotherapy system (Varian Medical Systems) with direct-dose calculation on HyperSight cone beam CT (CBCT) f...

Improving TG-263 Target Name Compliance Using Locally-Hosted Large Language Models

Authors: Rex A. Cardan, Carlos E. Cardenas, Udbhav S. Ram

Affiliation: The University of Alabama at Birmingham, University of Alabama at Birmingham

Abstract Preview: Purpose: The AAPM TG-263 report provides nomenclature guidelines for target and normal tissue structures used in radiation oncology. Adherence to these guidelines is challenging for targets, as there ...

Investigation of the Diagnostic Quality of Chest X-Rays Simulated from CT

Authors: Matthew R. Hoerner, Allison Shields

Affiliation: Yale University School of Medicine, Yale University

Abstract Preview: Purpose: To investigate the quality and clinical utility of chest x-rays synthesized from CT scans (sCXR).
Methods: Five helical chest CT exams were chosen for evaluation: this cohort represented a...

Mitigating Discrepancies in Radiology Reports: A Robust LLM Approach for Generating Consistent Impressions

Authors: Junwen Liu, Mengzhen Wang, Ning Wen, Jifeng Xiao, Fuhua Yan, Yanzhao Yang, Xuekun Zhang, Zheyu Zhang

Affiliation: Department of Radiology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Department of Radiology, Ruijin Hospital Shanghai Jiaotong University School of Medicine, Shanghai Jiaotong University, The SJTU-Ruijin-UIH Institute for Medical Imaging Technology, Shanghai Jiaotong University Schoo of Medicine

Abstract Preview: Purpose:This study aims to develop and evaluate a large language model (LLM) fine-tuned to generate consistent and accurate impressions from imaging findings. Additionally, the study investigates the ...

Multi-Region Multiomic Features Improve Random Forest Toxicity Modeling of Radiation Pneumonitis

Authors: Laurence Edward Court, Alexandra Olivia Leone, Zhongxing Liao, Saurabh Shashikumar Nair, Joshua S. Niedzielski, Ramon Maurilio Salazar, Ting Xu

Affiliation: The University of Texas MD Anderson Cancer Center, Department of Radiation Physics, The University of Texas MD Anderson Cancer Center

Abstract Preview: Purpose: Radiation Pneumonitis (RP) predictive models often rely on clinical and DVH parameters, but multiomic features from CT imaging and 3D dose distributions from various regions could provide add...

To Investigate the Utility of Magnetic Resonance Imaging (MRI)-Based Radiomics for Predicting Tumor Response and Adverse Effects, Specifically Gastrointestinal (GI) Toxicity, in Cervical Cancer Patients Undergone Radiotherapy.

Authors: Issam M. El Naqa, Kurukulasuriya Ruwani Fernando, Himani Himani, Vivek Kumar, Arun Oinam, Manju Sharma

Affiliation: Panjab University, Moffitt Cancer Center, H. Lee Moffitt Cancer Center, Post Graduate Institute of Medical Sciences, University of California San Francisco

Abstract Preview: Purpose: To investigate the utility of Magnetic Resonance Imaging (MRI)-based radiomics for predicting tumor response and adverse effects, specifically gastrointestinal (GI) toxicity, in cervical canc...