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Results for "linac adaptive": 36 found

A Deep Learning-Based Approach for Rapid Prediction of IMRT/VMAT Patient-Specific Quality Assurance for Online Adaptive Plans Generated with a 0.35T MR-Linac

Authors: Suman Gautam, Tianjun Ma, William Song

Affiliation: Virginia Commonwealth University

Abstract Preview: Purpose: We propose an artificial intelligence (AI)-based method to rapidly predict the patient-specific quality assurance (PSQA) results for magnetic resonance (MR)-guided online adaptive radiation th...

A Pilot Survey on Medical Physics Residency Education in External Beam Special Procedures

Authors: Courtney R. Buckey, Jay W. Burmeister, Minsong Cao, Grace Chang, Yu Kuang, Yixiang Liao, Yi Rong, Dandan Zheng

Affiliation: Mayo Clinic, Mayo Clinic Arizona, Karmanos Cancer Center, Gershenson ROC, Wayne State University School of Medicine, Department of Radiation Oncology, University of California, Los Angeles, Medical Physics Program, University of Nevada, Rush University Medical Center, University of Rochester

Abstract Preview: Purpose: Investigate the adequacy of training for therapeutic medical physics residents in select special procedures.
Methods: After a review of existing literature, a multi-institutional group dev...

AI-Based Registration-Free 3T T2-Weighted MRI Synthesis Using Truefisp MRI Acquired on a 0.35T MR-Linac System

Authors: Hilary P Bagshaw, Mark K Buyyounouski, Cynthia Fu-Yu Chuang, Yu Gao, Dimitre Hristov, Lianli Liu, Lawrie Skinner, Lei Xing

Affiliation: Department of Radiation Oncology, Department of Radiation Oncology, Stanford University

Abstract Preview: Purpose:
MR-guided radiation therapy has introduced a significant leap in cancer treatment by allowing adaptive treatment. The low-field MR-guided system predominantly uses the TrueFISP sequence, w...

Advancing MR-guided online adaptive radiotherapy using a 1.5T MR-Linac system

Authors: Neelam Tyagi

Affiliation: Memorial Sloan Kettering Cancer Center

Abstract Preview: N/A...

Advancing Thoracic Synthetic CT Images with Enhanced Cyclegan for Adaptive Radiotherapy Applications

Authors: Silambarasan Anbumani, Nicolette O'Connell, Eenas A. Omari, Amanda Pan, Eric S. Paulson, Lindsay Puckett, Monica E. Shukla, Dan Thill, Jiaofeng Xu

Affiliation: Elekta Inc, Elekta Limited, Linac House, Department of Radiation Oncology, Medical College of Wisconsin

Abstract Preview: Purpose: Accurate electron density information from on-board imaging is essential for direct dose calculations in adaptive radiotherapy (ART). This study evaluates a deep learning model for thoracic s...

An Efficient Workflow for X-Ray Imaging-Based IGRT/ART

Authors: Lili Chen, Ahmed A. Eldib, Chang Ming Charlie Ma

Affiliation: Fox Chase Cancer Center

Abstract Preview: Purpose: Specialized adaptive radiotherapy (ART) systems have been developed and clinically implemented, which are either cost-ineffective such as MR-linacs or inflexible in workflow such as the Ethos...

Application of a Conditional Diffusion Model to Improve Real-Time MR Imaging in Online Adaptive MR-Guided Radiotherapy

Authors: Hideaki Hirashima, Haruo Inokuchi, Nobutaka Mukumoto, Naruki Murahashi, Mitsuhiro Nakamura, Megumi Nakao, Keiko Shibuya, Linna Zhang

Affiliation: Kyoto University, Osaka Metropolitan University

Abstract Preview: Purpose:
To transform the quality of 2D cine MR images acquired during online adaptive MR-guided radiotherapy (OA-MRgRT) by utilizing a conditional diffusion model to achieve image quality comparab...

Assessing the Need for Online Adaptive Prostate SBRT Using the MR-Linac

Authors: Awens Alphonse, Nebi Demez, Michael Kasper, Noufal Manthala Padannayil, Shyam Pokharel, Suresh Rana, Samuel Richter, Lauren A. Rigsby, Tino Romaguera, Hina Saeed, Nishan Shrestha, Somol Sunny

Affiliation: Lynn Cancer Institute, Boca Raton Regional Hospital, Baptist Health South Florida

Abstract Preview: Purpose: This study evaluates the necessity and potential benefits of online adaptive stereotactic body radiotherapy (SBRT) for prostate cancer using the ViewRay MR-Linac system. By leveraging real-ti...

Assessment of Deep Learning Models for 3D Dose Prediction in Prostate Cancer SIB-IMRT Using MR-Linac

Authors: Hao-Wen Cheng, Jonathan G. Li, Chihray Liu, Wen-Chih Tseng, Guanghua Yan

Affiliation: University of Florida

Abstract Preview: Purpose: This study develops and evaluates deep learning (DL) models for predicting 3D dose distributions in simultaneous integrated boost (SIB) prostate cancer treatment using the Elekta Unity MR-Lin...

Automated MR Segmentation for Online Adaptive MR-Linac Therapy Using an in-House Model

Authors: David L. Barbee, David Byun, Matt Long, Jose R. Teruel Antolin, Michael J Zelefsky

Affiliation: NYU Langone Health

Abstract Preview: Purpose:
Online adaptive MR-Linac therapy requires contour adaptation, often adding 20 minutes to treatment time and reducing machine throughput. This study introduces a fully automated MR contour ...

BEST IN PHYSICS MULTI-DISCIPLINARY: Quantitative MRI Oximetry: Combining EPR and OE-MRI for Volumetric Mapping of Hypoxia in Tumors

Authors: Victor B. Kassey, Maciej M. Kmiec, Periannan Kuppusamy, Sergey V. Petryakov, Conner Ubert

Affiliation: Dartmouth College

Abstract Preview: Purpose: Tumor hypoxia—a state of reduced oxygen supply—is well known to affect treatment response, particularly in radiotherapy and chemotherapy. Oxygen-enhanced magnetic resonance imaging (OE-MRI) u...

Can AI Agent be a Good Judge for Online Adaptive Radiotherapy Plan Evaluation?

Authors: Steve B. Jiang, Mu-Han Lin, Dan Nguyen, Beiqian Qi, Daniel Yang, Ying Zhang

Affiliation: Department of Radiation Oncology, UT Southwestern Medical Center, Medical Artificial Intelligence and Automation (MAIA) Lab & Department of Radiation Oncology, UT Southwestern Medical Center

Abstract Preview: Purpose:
Online adaptive radiotherapy (oART) is a resource-intensive workflow requiring significant time and effort required from clinicians, particularly for the online evaluation of plan quality....

Comparison of CBCT Dose Calculation Accuracy between Truebeam Hypersight Image Reconstruction Algorithms

Authors: Sarah Aubert, Harald Keller, Jeff D. Winter

Affiliation: Princess Margaret Cancer Centre

Abstract Preview: Purpose: Support for treatment planning directly on CBCT imaging on C-arm linacs will enable adaptive radiation therapy (ART) capacity with increased treatment technique flexibility. The HyperSight im...

Comprehensive Evaluation of High-Performance Cone-Beam Computed Tomography on C-Arm and Ring-Gantry Linacs for Adaptive Radiation Therapy

Authors: Laura I. Cervino, Karen Episcopia, Hsiang-Chi Kuo, Sangkyu Lee, Seng Boh Gary Lim, Shih-Chi Lin, Grace Tang

Affiliation: Department of Medical Physics, Memorial Sloan Kettering Cancer Center

Abstract Preview: Purpose: This study evaluated the performance of the HyperSight Cone-Beam Computed Tomography (CBCT) system on a TrueBeam C-arm LINAC (TB) and two Ethos ring-gantry LINACs (ES) for adaptive radiation ...

Development and Validation of an MR-Compatible Anthropomorphic Motion Phantom for Liver Motion Assessment and MR-Linac Gating System Optimization

Authors: Tsuicheng D. Chiu, Weiguo Lu, Aaron Thomlinson, You Zhang

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

Abstract Preview: Purpose: To develop and validate an MR-compatible anthropomorphic motion phantom to assess liver motion, real-time dosimetry, and gating system performance under controlled and reproducible respirator...

Dosimetric Comparison of MR-Linac Vs. Cyberknife for Prostate Stereotactic Body Radiation Therapy

Authors: Awens Alphonse, Nebi Demez, Michael Kasper, Noufal Manthala Padannayil, Shyam Pokharel, Suresh Rana, Lauren A. Rigsby, Tino Romaguera, Hina Saeed, Nishan Shrestha, Somol Sunny

Affiliation: Lynn Cancer Institute, Boca Raton Regional Hospital, Baptist Health South Florida

Abstract Preview: Purpose: Prostate stereotactic body radiation therapy (SBRT) requires precise dose delivery to the target volume and organ-at-risk (OAR) sparing. This study compares MR-Linac (MRL) and CyberKnife (CK)...

Early GU Toxicity Prediction in Prostate SBRT Using Delivered Dosimetry Via Long Short-Term Memory Model

Authors: Amar Kishan, Jun Lian, Yunkui Pang, Jonathan Pham, X. Sharon Qi, Michael Steinberg, Luca F Valle, Pew-Thian Yap

Affiliation: Department of Radiation Oncology, University of California, Los Angeles, University of North Carolina at Chapel Hill

Abstract Preview: Purpose: Stereotactic body radiotherapy (SBRT) is a highly effective treatment for prostate cancer, yet predicting genitourinary (GU) toxicity has primarily relied on planned dosimetry. This study inv...

Evaluating Necessity of Patient-Specific Deep Learning-Based Auto-Segmentation for Improved Adaptation for Abdominal Tumors

Authors: Asma Amjad, Renae Conlin, Eric S. Paulson, Christina M. Sarosiek

Affiliation: Department of Radiation Oncology, Medical College of Wisconsin

Abstract Preview: Purpose: In an effort to improve contouring accuracy for abdominal MR guided online adaptive radiotherapy (MRgOART), patient-specific deep learning-based auto-segmentation (PS-DLAS) has been proposed....

Evaluation of Thoracic Direct Dose Calculation Using Truebeam Linac with Hypersight Imaging CBCT Solution

Authors: Theodore Higgins Arsenault, Kenneth W. Gregg, Lauren E Henke, Rojano Kashani, Alex T. Price, Sagar Regmi, Atefeh Rezaei, Runyon C. Woods

Affiliation: University Hospitals Seidman Cancer Center

Abstract Preview: Purpose: To investigate the feasibility and accuracy of using a Hounsfield Unit(HU) calibrated cone-beam computed tomography(CBCT) for direct dose calculation in thoracic treatment settings. In combin...

Evaluation of a Novel Multimodal Deformable Image Registration Algorithm for Pelvic MRI-CT Fusion in Radiotherapy

Authors: Christian Fiandra, Marco Fusella, Gianfranco Loi, Silvia Pesente, Lorenzo Placidi, Claudio Vecchi, Orlando Zaccaria, Stefania Zara

Affiliation: Abano Terme Hospital, University of Turin, Maggiore della Carità, Tecnologie Avanzate Srl, Fondazione Policlinico Universitario Agostino Gemelli IRCCS

Abstract Preview: Purpose: Deformable-image-registration (DIR) is essential in modern radiotherapy for adaptive RT, re-irradiation, and other clinical applications. Multimodal DIR is especially important in MRI-only wo...

Fast Synthetic-CT-Free Dose Calculation in MR Guided RT

Authors: Claus Belka, Stefanie Corradini, George Dedes, Nikolaos Delopoulos, Christopher Kurz, Guillaume Landry, Ahmad Neishabouri, Domagoj Radonic, Adrian Thummerer, Niklas Wahl, Fan Xiao

Affiliation: Department of Radiation Oncology, LMU University Hospital, LMU Munich, Department of Medical Physics, LMU Munich, Department of Medical Physics in Radiation Oncology, German Cancer Research Center (DKFZ), National Center for Radiation Oncology (NCRO), Heidelberg Institute for Radiation Oncology (HIRO)

Abstract Preview: Purpose: In MR-guided online adaptive radiotherapy, MRI lacks tissue attenuation information necessary for accurate dose calculations. Instead of using deep learning methods to generate synthetic CT i...

Feasibility of Efficient Offline Adaptive Replanning with Hypersight High-Performance Cone-Beam CT on Truebeam for Pelvis RT

Authors: Jochen Cammin, Shifeng Chen, Arun Gopal, Kai Huang, Jason K Molitoris, Amit Sawant, Kai Wang

Affiliation: University of Maryland, Department of Radiation Oncology, University of Maryland School of Medicine, Maryland University Baltimore, Department of Radiation Oncology, University of Maryland Medical Center

Abstract Preview: Purpose: The HyperSight CBCT optional feature on Varian TrueBeam linacs offers a larger field-of-view, improved Hounsfield units (HU) accuracy, and overall improved image quality, including metal arti...

Implementation of a Virtual Quality Assurance System Using Raystation for Online MR-Linac Adaptive Radiotherapy

Authors: Min-Sig Hwang, Danny K. Lee, Daniel C. Pavord, Kyung Lim Yun

Affiliation: Allegheny Health Network

Abstract Preview: Purpose: Ensuring the quality of treatment plans through patient-specific pre-treatment quality assurance (QA) is essential. However, the use of physical phantom-based QA devices is not feasible for o...

Initial Phantom Studies Towards Implementation of Sequential Dual Energy CBCT on an Adaptive Radiotherapy Linac Platform

Authors: James M. Balter, Alexander Moncion, Ikechi S Ozoemelam

Affiliation: University of Michigan

Abstract Preview: Purpose: Sequential dual-energy cone beam computed tomography (DE-CBCT) integrated with an online adaptive platform could potentially improve soft tissue visualization for more accurate anatomical del...

Insights into Deep Learning Auto-Segmentation for Abdominal Organs in MR-Guided Adaptive Radiation Therapy: A Single-Institution CT-MR Comparison

Authors: Asma Amjad, Renae Conlin, Eric S. Paulson, Christina M. Sarosiek

Affiliation: Department of Radiation Oncology, Medical College of Wisconsin

Abstract Preview: Purpose:
MR-guided adaptive radiation therapy (MRgART) is transforming clinical workflows, requiring fast, accurate organs-at-risk (OARs) contouring. While deep learning auto-segmentation (DLAS) of...

Inter-Fraction Monitoring of Brain Metastases Resection Cavities during Fractionated Stereotactic Radiosurgery on the 0.35 T MRI-Linac

Authors: Eyub Y. Akdemir, Gregory A Azzam, Rupesh Kotecha, Gregory J. Kubicek, Natalia Lutsik, Eric Mellon, Siamak P. Nejad-Davarani, Parag Parikh, Karen C. Snyder

Affiliation: Miami Cancer Institute, Baptist Health South Florida, Department of Radiation Oncology, University of Miami, Henry Ford Health

Abstract Preview: Purpose: Resection cavity volumes shrink gradually over time after surgical resection of brain metastases. Fractionated stereotactic radiosurgery (fSRS) is often delivered to the cavity to prevent rec...

Liver Tumor Auto-Contouring Using Recurrent Neural Networks on MRI-Linac for Adaptive Radiation Therapy

Authors: Yan Dai, Jie Deng, Christopher Kabat, Weiguo Lu, Ying Zhang, Hengrui Zhao

Affiliation: Medical Artificial Intelligence and Automation (MAIA) Lab, Department of Radiation Oncology, UT Southwestern Medical Center, Medical Artificial Intelligence and Automation (MAIA) Laboratory, Department of Radiation Oncology, UT Southwestern Medical Center, Medical Artificial Intelligence and Automation (MAIA) Lab & Department of Radiation Oncology, UT Southwestern Medical Center

Abstract Preview: Purpose:
MRI-guided adaptive radiotherapy (MRgART) using MR-LINAC systems offers significant advantages for liver cancer, enabling superior tumor delineation and online plan adaptation. However, ma...

Multi-Center Diffusion-Weighted MRI Validation for 0.35T MR-Linac: A Repeatability and Reproducibility Study

Authors: Tess Armstrong, Nema Bassiri, Alonso N. Gutierrez, Michael Kasper, Natalia Lutsik, Eric Mellon, Kathryn E. Mittauer, Siamak P. Nejad-Davarani, Shyam Pokharel, Suresh Rana, Hui Wang, Joseph Weygand

Affiliation: Department of Radiation Oncology and Applied Science, Dartmouth Health, Miami Cancer Institute, Baptist Health South Florida, ViewRay, Inc., Miami Cancer Institute, Lynn Cancer Institute, Boca Raton Regional Hospital, Baptist Health South Florida, Department of Radiation Oncology, University of Miami

Abstract Preview: Purpose: Radiation treatments on the MR-linac (MRL) enable daily acquisition of anatomical and physiological images for adaptive treatment planning. The apparent diffusion coefficient (ADC) estimated ...

Multi-Vendor Validation of a Deep Learning-Based Synthetic CT Generation Model for MR-Only Radiotherapy Planning in the Pelvis

Authors: Gregory Bolard, Rabten Datsang, Sarah Ghandour, Timo Kiljunen, Pauliina Paavilainen, Sami Suilamo, Katlin Tiigi

Affiliation: Turku University Hospital, Virginia Commonwealth University, MVision AI, North Estonia Medical Centre, Docrates Cancer Center, Hopital Riviera-Chablais

Abstract Preview: Purpose: To verify the performance of a vendor-neutral deep learning model for synthetic CT generation from T2-weighted and balanced steady-state MR sequences to support both MR-only simulation and MR...

Preliminary Clinical Experience with MRI-Guided Online Adaptive Radiotherapy for Esophageal Cancer Patients

Authors: Ali Hosni, Oleksii Semeniuk, Andrea Shessel, Teo Stanescu

Affiliation: Princess Margaret Hospital, Princess Margaret Cancer Centre, Brown University Health

Abstract Preview: Purpose: To report on early clinical experience with a two-phase radiotherapy approach for esophageal cancer patients, utilizing CBCT-based conventional C-arm linear accelerator radiotherapy and MR-gu...

Real-Time 3D Dose Verification for MR-Guided Online Adaptive Radiotherapy (ART) Via Geometry-Encoded Deep Learning Framework

Authors: Steve B. Jiang, Dan Nguyen, Chenyang Shen, Fan-Chi F. Su, Jiacheng Xie, Shunyu Yan, Daniel Yang, Ying Zhang, You Zhang

Affiliation: Medical Artificial Intelligence and Automation (MAIA) Lab, Department of Radiation Oncology, UT Southwestern Medical Center, UT Southwestern Medical Center, Medical Artificial Intelligence and Automation (MAIA) Lab & Department of Radiation Oncology, UT Southwestern Medical Center, Medical Artificial Intelligence and Automation (MAIA) Laboratory, Department of Radiation Oncology, UT Southwestern Medical Center, The University of Texas at Dallas

Abstract Preview: Purpose: Fast dose verification is essential for the safety and efficiency of MR-guided adaptive radiotherapy (ART) as patients anxiously waiting on the treatment couch. Conventional tools often requi...

Segmentation Regularized Registration Training Improves Multi-Domain Generalization of Deformable Image Registration for MR-Guided Prostate Radiotherapy

Authors: Lando S. Bosma, Victoria Brennan, Nicolas Cote, ChengCheng Gui, Nima Hassan Rezaeian, Jue Jiang, Sudharsan Madhavan, Josiah Simeth, Neelam Tyagi, Harini Veeraraghavan, Michael J Zelefsky

Affiliation: Department of Medical Physics, Memorial Sloan Kettering Cancer Center, Department of Radiation Oncology, Memorial Sloan Kettering Cancer Center, NYU Langone Health, University Medical Center Utrecht, Memorial Sloan Kettering Cancer Center

Abstract Preview: Purpose: Deep learning-based deformable image registration (DIR) models often lack robustness when applied to datasets with differing imaging characteristics. We aimed to (1) improve registration netw...

The Development of Large Field MR Guided Radiotherapy for Pelvic Lymph Node SBRT and Its Dosimetry Improvement

Authors: David Byun, Ting Chen, Paulina E. Galavis, Allison McCarthy, Hesheng Wang, Michael J Zelefsky

Affiliation: NYU Langone Health

Abstract Preview: Purpose: To summarize a MR guided adaptive workflow developed for pelvic lymph nodes (PLN) stereotactic radiotherapy using large field size on Elekta Unity© MR Linac system, and to quantitatively anal...

Towards In Vivo Dosimetry for Adaptive MR-Guided Radiation Therapy: Initial Report on a Prototype Injectable Dosimeter

Authors: Daniel Ball, Alex Dresner, Geoffrey S. Ibbott, Leonard H. Kim, Christopher Tyerech, Sebastián Vega

Affiliation: MD Anderson Cancer Center at Cooper, Cooper Medical School of Rowan University, The American Board of Radiology, Department of Radiation Oncology, University of Pennsylvania, Rowan University, Philips Healthcare MR Oncology

Abstract Preview: Purpose:
In vivo dosimetry is valuable to radiation therapy for its ability to report the actual dose received by patients but is currently limited to surface and intracavitary measurements, leavin...

Universal Anatomical Mapping and Patient-Specific Prior Implicit Neural Representation for MRI Super-Resolution

Authors: Jie Deng, Yunxiang Li, You Zhang

Affiliation: Medical Artificial Intelligence and Automation (MAIA) Lab, Department of Radiation Oncology, UT Southwestern Medical Center, Medical Artificial Intelligence and Automation (MAIA) Laboratory, Department of Radiation Oncology, UT Southwestern Medical Center

Abstract Preview: Purpose: Magnetic Resonance Imaging (MRI) has exceptional soft tissue contrast and an essential role in radiotherapy. The introduction of clinical MR-LINACs has enabled adaptive radiotherapy (ART) usi...

Validation of an Ivim Tool for Liver Hypoxia Assessment for an Online Adaptive MR-Linac System

Authors: Jean-Pierre Bissonnette, Catherine Coolens, Laura Dawson, Ryan A Kuhn, Michael Maddalena, Teo Stanescu

Affiliation: Princess Margaret Hospital, The Princess Margaret Cancer Centre - UHN, University of Toronto, Princess Margaret Cancer Centre

Abstract Preview: Purpose: To investigate the generation and reproducibility of 3D hypoxia maps in liver hepatocellular carcinoma (HCC) patients using data derived from an Intravoxel Incoherent Motion (IVIM) MR sequenc...