Search Submissions 🔎

Results for "fire mri": 52 found

A Combination of Radiomics and Dosiomics for Gross Tumor Volume Regression in Personalized Ultra-Fractionated Stereotactic Adaptive Radiotherapy (PULSAR)

Authors: Hao Peng, Yajun Yu

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: Personalized ultra-fractionated stereotactic adaptive radiotherapy (PULSAR) is a novel ablative radiation dosing scheme developed by our institution. This study aims to establish a regression...

A SAM-Guided and Match-Based Semi-Supervised Segmentation Framework for Medical Imaging

Authors: Weiguo Lu, Jax Luo, Xiaoxue Qian, Hua-Chieh Shao, Guoping Xu, 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, Harvard Medical School

Abstract Preview: Purpose:
Semi-supervised segmentation leverages sparse annotation information to learn rich representations from combined labeled and label-less data for segmentation tasks. This study leverages th...

A Semi-Automated Landmark Identification Framework for Liver MR-CT Image Pairs: Towards a Multi-Modality DIR Benchmark Dataset

Authors: Deshan Yang, Zhendong Zhang

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

Abstract Preview: Purpose:
The evaluation of deformable image registration (DIR) algorithms is crucial for improving accuracy and clinical adoption. However, reliable benchmarks, especially for inter-modality regist...

A Study of Large Model Alignment Techniques for MRI Images of Small Sample Meningioma

Authors: Xiangli Cui, Man Hu, Wanli Huo, Da Yao, Jianguang Zhang, Yingying Zhang, Shanyang Zhao

Affiliation: Institute of Health and Medical Technology, Hefei Institutes of Physical Science, Chinese Academy of Sciences, Hefei, the Zhejiang-New Zealand Joint Vision-Based Intelligent Metrology Laboratory, College of Information Engineering, China Jiliang University, Departments of Radiation Oncology, Zibo Wanjie Cancer Hospital, Department of Oncology, Xiangya Hospital, Central South University, Department of Radiation Oncology, Shandong Cancer Hospital and Institute, Shandong First Medical University, Shandong Academy of Medical Sciences

Abstract Preview: Purpose:
To study the fine-tuning strategy of pre-trained AI image generation model to adapt to the generation of small sample meningioma MRI images, explore its impact on observer performance, and...

A Tool to Quantitatively Assess Dose after Patient Motion

Authors: Asma Amjad, Renae Conlin, Beth A. Erickson, William Hall, Eric S. Paulson, Christina M. Sarosiek

Affiliation: Department of Radiation Oncology, Medical College of Wisconsin

Abstract Preview: Purpose: The adapt-to-shape (ATS) workflow on the MR-Linac involves manual contour edits followed by treatment plan reoptimization on daily pre-beam MRIs. A verification image is acquired after plan o...

Advancing Post-Radiotherapy Toxicity Extraction: A Novel Privacy-Preserving, Parameter-Efficient Language Model Fine-Tuning

Authors: Hassan Bagher-Ebadian, Indrin J. Chetty, Mohamed Elshaikh, Ahmed I Ghanem, Mohammad M. Ghassemi, Reza Khanmohammadi, Benjamin Movsas, Shayan Siddiqui, Kundan S Thind, Jawad Turfa

Affiliation: Michigan State University, Department of Radiation Oncology,Cedars-Sinai Medical Center, Department of Radiation Oncology, Henry Ford Health-Cancer, Detroit, MI and Alexandria Department of Clinical Oncology, Faculty of Medicine, Alexandria University, Henry Ford Health

Abstract Preview: Purpose: Extracting late radiotherapy-induced toxicities from free-text notes using natural language processing is complicated by negative symptom identification, computational demands, and data priva...

An Efficient Deep Learning Model with Multi-Scale Integration for Automated Pancreas Segmentation on MR Images

Authors: Jingyun Chen, Yading Yuan

Affiliation: Columbia University Irving Medical Center, Department of Radiation Oncology

Abstract Preview: Purpose: To develop and evaluate the Scale-attention network (SANet) for automated pancreas segmentation on MR images.
Methods: To develop SANet, we extended the classic U-Net design with a dynamic...

Analysis of Noise Power Spectra in MR Parallel Imaging

Authors: Sulaiman D. Aldoohan, Gerardo Garcia

Affiliation: University of Toledo Medical Center

Abstract Preview: Purpose: To evaluate the noise power spectra (NPS) of images acquired using parallel imaging with varying acceleration factors in 1-D and 3-D spaces and to compare the level of the power of the noise ...

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...

Automated Framework for Predicting Tumour Growth in Vestibular Schwannomas Using Contrast-Enhanced T1-Weighted MRI

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...

Box-Prompt Zero-Shot Smart Segmentation in Radiation Oncology Using a SAM-Based Model: Smartsam

Authors: Kristen A. Duke, Samer Jabor, Neil A. Kirby, Parker New, Niko Papanikolaou, Arkajyoti Roy, Yuqing Xia

Affiliation: St. Mary's University, The University of Texas San Antonio, UT Health San Antonio

Abstract Preview: Purpose:
The Segment Anything Model (SAM) is a foundational box-prompt-based model for natural image segmentation. However, its applicability to zero-shot 3D medical image segmentation, particularl...

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....

Clinical Application of Biology-Guided Radiotherapy (BgRT) to Patient Having a Cardiac Implantable Electronic Device (CIED)

Authors: Girish Bal, Thomas I. Banks, Bin Cai, Yesenia Gonzalez, Zohaib Iqbal, Paul M. Medin, Rameshwar Prasad, Chenyang Shen, Robert Timmerman, Yuanyuan Zhang

Affiliation: Department of Radiation Oncology, UT Southwestern Medical Center, University of Texas Southwestern Medical Center, UT Southwestern Medical Center, RefleXion Medical

Abstract Preview: Purpose: Each year more than one million pacemakers and 200k cardioverter-defibrillators are implanted in patients worldwide. The presence of a CIED introduces challenges to the delivery of radiation ...

Clinical Assessment of Synthetic CT in MR-Only Brain Radiotherapy

Authors: Ergun E. Ahunbay, Colette Gage, Abdul Kareem Parchur, Eric S. Paulson

Affiliation: Department of Radiation Oncology, Medical College of Wisconsin

Abstract Preview: Purpose: AI-generated synthetic CT (sCT) images address challenges with prior sCT approaches, including atlas- and threshold-based methods. Commercial AI-based sCT tools have been introduced. This wor...

Clinical I-131 Dosimetry: Audit, Review, and Evaluation

Authors: Colin Adam Doyle, Celeste Winters

Affiliation: Department of Diagnostic Radiology, Oregon Health & Science University, School of Medicine, Oregon Health & Science University

Abstract Preview: Purpose: To audit our radioactive iodine (I-131) dosimetry protocol, review dosimetry methods used at other facilities, investigate the clinical impact of I-131 dosimetry at our facility, and test the...

Clinical Implementation of a Film Based Psqa System for SBRT on a 1.5T MR-Linac

Authors: Dylan Yamabe Breitkreutz, Lee Chin, Brige P. Chugh, Mark D'Souza, Brian M. Keller, Anthony Kim, Michelle K. Nielsen, Arjun Sahgal

Affiliation: Sunnybrook Health Sciences Centre

Abstract Preview: Purpose: The Elekta Unity MR-linac delivers highly conformal SBRT treatments using IMRT. These treatment plans require patient-specific quality assurance (PSQA) measurements to detect discrepancies be...

Comparison of Respiratory Motion between 4D-MR and 4D-CT in Compression Belt Patients

Authors: Morgan Aire, Krystal M. Kirby, Olivia Magneson, David E. Solis, Hamlet Spears

Affiliation: Louisiana State University, Mary Bird Perkins Cancer Center

Abstract Preview: Purpose: This study evaluates the range of motion of abdominal organs using 4D stack-of-stars magnetic resonance (MR) imaging and 4D computed tomography (CT), the current clinical standard. Accurate o...

Deep Learning Based Automatic Cerebrovascular Segmentation in Multi-Center TOF-MRA Datasets

Authors: Gayoung Kim, Junghoon Lee

Affiliation: Department of Radiation Oncology and Molecular Radiation Sciences, Johns Hopkins University

Abstract Preview: Purpose: 3D time-of-flight magnetic resonance angiography (TOF-MRA) is widely used for visualizing cerebrovascular structures. Accurate segmentation of cerebrovascular structures is critical for relia...

Demystifying Magnetic Resonance Imaging: Targeted Educational Initiatives for Medical Physicists in Türkiye and Preclinical Medical Students in the United States

Authors: Samuel A. Einstein, Jesutofunmi Fajemisin, Evren O. Göksel, Görkem O. Güngör, Marthony Robins, Travis C. Salzillo, Charles R. Thomas, Turgay Toksay, Joseph Weygand, Yue Yan

Affiliation: Acibadem MAA University, Department of Radiation Oncology and Applied Science, Dartmouth Health, Dartmouth College, Moffitt Cancer Center, Department of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Penn State College of Medicine, Bursa Ali Osman Sönmez Oncology Hospital

Abstract Preview: Purpose: Magnetic resonance imaging (MRI) is an indispensable clinical tool, offering unparalleled soft tissue contrast critical for diagnosing and managing a wide range of conditions. However, its co...

Direct-to-Unit Dose Calculations for Stereotactic Radiosurgery on a C-Arm Linac with Modern on-Board Imaging Solutions

Authors: Theodore Higgins Arsenault, Kenneth W. Gregg, Lauren E Henke, Rojano Kashani, Haley K Perlow, Alex T. Price, Atefeh Rezaei, Prashant Vempati, Runyon C. Woods

Affiliation: University Hospitals Seidman Cancer Center

Abstract Preview: Purpose: The HyperSight imaging feature on C-arm linacs(HS-CBCT) offers increased CT number accuracy over conventional on-board imaging. The C-arm geometry allows for noncoplanar treatments common to ...

Dose Dependent White Matter Injuries Quantified By Axial and Radial Diffusivity of Diffusion Tensor Imaging Significantly Correlate with Radiation-Induced Neurocognitive Decline in Diffuse Glioma Patients Underwent Chemoradiation Therapy

Authors: Robert Fucetola, Jiayi Huang, Zhihua Liu, Chongliang Luo, Tong Zhu

Affiliation: Washington University School of Medicine, Washington University in St. Louis, School of Medicine

Abstract Preview: Purpose:
This prospective observational study investigates radiation-induced white matter (WM) injuries using longitudinal diffusion tensor imaging (DTI) in patients with diffuse glioma following r...

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...

Enhancing Urethral Visualization for Prostate SBRT Using Post-Void T2-Weighted Imaging on a Low-Field 0.35T MR-Linac System

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

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

Abstract Preview: Purpose: Accurate delineation of the urethra is critical for optimizing tumor control and minimizing urethral toxicity in prostate stereotactic body radiation therapy (SBRT). The purpose of this study...

Evaluating Dose Variability in Bladder Contouring for MR-Guided Prostate Cancer Radiotherapy

Authors: Emily Helen Hayes, Chihray Liu

Affiliation: University of Florida

Abstract Preview: Purpose: To evaluate dosimetric discrepancies in bladder dose calculations among rigid, deformed, and manual contouring methods in prostate cancer patients and assess dose variations resulting from bl...

Evaluating the Radiological Safety of 64Cu-Macrin in PET/MRI Studies through Radiopharmaceutical Dosimetry

Authors: Alejandro Bertolet, Mislav Bobić, Carlos Huesa-Berral, Aileen O'Shea, Ralph Weissleder

Affiliation: Department of Radiation Oncology, Massachusetts General Hospital and Harvard Medical School, Department of Radiology, Massachusetts General Hospital and Harvard Medical School, Massachusetts General Hospital and Harvard Medical School

Abstract Preview: Purpose: To develop a pipeline for estimating the absorbed dose to various organs from positron emission tomography (PET) combined with magnetic resonance imaging (MRI). We use this pipeline to evalua...

Evaluation of AI-Generated Synthetic 4DCT from 3DCT for Radiotherapy Planning

Authors: Shinichiro Mori, Isabella Pfeiffer, Chester R. Ramsey, Alexander Usynin

Affiliation: Thompson Proton Center, National Institutes for Quantum Science and Technology, Thompson Cancer Survival Center

Abstract Preview: Purpose: Four-dimensional CT imaging (4DCT) has become a standard tool for managing respiratory motion in radiation therapy. However, many treatment delivery systems and most diagnostic CT scanners la...

Evaluation of Deformable Image Registration Accuracy Used in MR-Only Ventilation Mapping

Authors: Fei Han, James M. Lamb, Michael Vincent Lauria, Daniel A. Low, Tessa Elizabeth Maurer, Danilo Maziero, Claudia R. Miller, Drew Moghanaki, Louise Naumann, Nicolas Viot

Affiliation: Department of Radiation Oncology, University of California, Los Angeles, Siemens Healthineers, UCLA, University of California Los Angeles

Abstract Preview: Purpose: Patients with lung disease outside radiotherapy are barred from high dose protocols used for motion modeling, but MRI could offer no-dose alternatives. Image-based ventilation is a promising ...

Evaluation of Fractional Variability in High-Risk Clinical Target Volume (HR-CTV) during High-Dose-Rate Brachytherapy for Cervical Cancer: A Retrospective Analysis for Adaptive Treatment Planning.

Authors: Olubunmi Odunola Aregbe, Clara Ferreira, Margaret Reynolds, David A. Sterling, Jianling Yuan

Affiliation: University of Minnesota, University of Minnesota Physicians, Department of Radiation Oncology, University of Minnesota, Minneapolis

Abstract Preview: Purpose: To analyze volume changes in the high-risk clinical target volume (HR-CTV) during high-dose rate (HDR) brachytherapy for cervical cancer patients. The study aims to evaluate the trend and cor...

Exploiting the Glycerol CH2 Resonances for Estimating Relative Free Fatty Acid to Triglyceride Concentration Ratios

Authors: José Antonio Klautau Toffoli, Anthony G. Tessier, Atiyah Yahya

Affiliation: Department of Oncology, University of Alberta

Abstract Preview: Purpose: To demonstrate that magnetic resonance spectroscopy (MRS) methyl (≈0.9 ppm) to glycerol (≈4.1-4.3 ppm) resonance area ratios correlate with relative concentrations of free fatty acids to trig...

Fine-Tuning AI-Based Generative Models for Small-Sample Glioma MRI Generation.

Authors: Xiangli Cui, Chunyan Fu, Man Hu, Wanli Huo, Jingyu Liu, Jianguang Zhang, Yingying Zhang, Shanyang Zhao

Affiliation: Institute of Health and Medical Technology, Hefei Institutes of Physical Science, Chinese Academy of Sciences, Hefei, the Zhejiang-New Zealand Joint Vision-Based Intelligent Metrology Laboratory, College of Information Engineering, China Jiliang University, Departments of Radiation Oncology, Zibo Wanjie Cancer Hospital, Key Laboratory of Electromagnetic Wave Information Technology and Metrology of Zhejiang Province, College of Information Engineering, China Jiliang University, Department of Oncology, Xiangya Hospital, Central South University, College of Information Engineering, China Jiliang University, Department of Radiation Oncology, Shandong Cancer Hospital and Institute, Shandong First Medical University, Shandong Academy of Medical Sciences

Abstract Preview: Purpose: To quantify the impact of fine-tuning strategies for pre-trained AI image generation models on glioma MRI image quality and observer performance, and to determine the optimal fine-tuning conf...

Free Radical Irradiation Emergent (FIRE) MRI: Real-Time MR-Based Quantification of Radiation-Produced Free Radical Generation on a Clinical MR-Linac

Authors: Claire Keun Sun Park, Atchar Sudhyadhom, Veena Venkatachalam, Noah Warner

Affiliation: Harvard–MIT Program in Health Sciences and Technology, Massachusetts Institute of Technology, Brigham and Women’s Hospital and Dana Farber Cancer Institute, Harvard Medical School,, Brigham and Women’s Hospital and Dana Farber Cancer Institute, Harvard Medical School

Abstract Preview: Purpose: Modern radiotherapy achieves sub-millimeter spatial accuracy but fails to account for patient- and spatially-specific variations in biological response. Free radical generation (FRG), particu...

Fully Automated Zero-Shot Organ Segmentation in Male Pelvic MR Images for MR-Guided Radiation Therapy

Authors: Jihun Kim, Jin Sung Kim, Jun Won Kim, Yong Tae Kim, Chanwoong Lee, Jihyn Pyo, Young Hun Yoon

Affiliation: Department of Radiation Oncology, Yonsei Cancer Center, Heavy Ion Therapy Research Institute, Yonsei University College of Medicine, Department of Radiation Oncology, Gangnam Severance Hospital, Yonsei University College of Medicine

Abstract Preview: Purpose: Although segmentation foundation models have recently demonstrated promising zero-shot performance on natural images, its clinical application to magnetic resonance (MR) images still requires...

Generalized 2D Cine Multi-Modal MRI-Based Dynamic Volumetric Reconstruction Using Motion-Aligned Implicit Neural Network with Spatial Prior Embedding

Authors: Ming Chao, Karyn A Goodman, Yang Lei, Tian Liu, Jing Wang, Jiahan Zhang

Affiliation: Icahn School of Medicine at Mount Sinai

Abstract Preview: Purpose: Real-time volumetric MRI is essential for motion management in MRI-guided radiotherapy (MRIgRT), yet acquiring high-quality 3D images remains challenging due to time constraints and motion ar...

Improving 4D-MRI Parameters for Abdominal Tumor Motion Management: A Phantom Study

Authors: Morgan Aire, Krystal M. Kirby, Olivia Magneson, David E. Solis

Affiliation: Louisiana State University, Mary Bird Perkins Cancer Center

Abstract Preview: Purpose: For soft-tissue abdominal tumors, a 4D-MR may provide improved tumor tracking over the clinical standard 4D-CT. This project aims to optimize a clinically available 4D-MR pulse sequence to ac...

Initial Comparison of 3D CBCT Performance: New Mobile C-Arm Vs. O-Arm Unit

Authors: Wendy Siman, Wei Zhou

Affiliation: University of Colorado Anschutz Medical Campus, School of Medicine

Abstract Preview: Purpose:
To compare the image quality and radiation dose of 3D cone-beam CT modes of a mobile C-arm and an O-arm unit for intraoperative imaging.
Methods:
A 50-µm tungsten wire was imaged at ...

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...

Integrating Foundation Model with Self-Supervised Learning for Brain Lesion Segmentation with Multimodal and Diverse MRI Datasets

Authors: Zong Fan, Fan Lam, Hua Li, Rita Huan-Ting Peng, Yuan Yang

Affiliation: University of Illinois at Urbana Champaign, University of Illinois at Urbana-Champaign, Washington University School of Medicine, University of Illinois Urbana-Champaign

Abstract Preview: Purpose: Accurate lesion segmentation in MRI is critical for early diagnosis, treatment planning, and monitoring disease progression in various neurological disorders. Cross-site MRI data can alleviat...

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...

Motion Correction-Driven Patient-Specific 2D Cine MRI-Based Dynamic Volumetric Reconstruction for MRI-Guided Radiotherapy Intra-Fractional Motion Monitoring

Authors: Karyn A Goodman, Yang Lei, Tian Liu, D. Michael Lovelock, Charlotte Elizabeth Read, Jing Wang, Jiahan Zhang

Affiliation: Icahn School of Medicine at Mount Sinai

Abstract Preview: Purpose: Real-time volumetric MRI is essential for precise motion management in MRI-guided radiotherapy (MRIgRT). While 2D Cine MRI offers high temporal resolution for motion tracking, it inherently l...

Predicting and Monitoring Response to Head and Neck Cancer Radiotherapy Using Multi-Modality Imaging and Radiobiological Digital Twin Simulations

Authors: Eric Aliotta, Michalis Aristophanous, Joseph O. Deasy, Bill Diplas, Milan Grkovski, James Han, Vaios Hatzoglou, Jeho Jeong, Nancy Y Lee, Ramesh Paudyal, Nadeem Riaz, Heiko Schoder, Amita Shukla-Dave

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

Abstract Preview: Purpose: To forecast radiotherapy treatment response for head and neck cancer (HNC) using multimodality imaging and personalized radiobiological modeling.
Methods: Multi-modality imaging data from ...

Prediction of Vertebral Compression Fracture after Stereotactic Body Radiotherapy for Spinal Metastases Using Clinical, Radiomic and Dosiomic Features

Authors: Yukio Fujita, Syoma Ide, Kei Ito, Tomohiro Kajikawa, Satoshi Kito, Keiko Murofushi, Yujiro Nakajima, Yuhi Suda, Kentaro Taguchi, Naoki Tohyama, Fumiya Tsurumaki

Affiliation: Komazawa University Graduate School, Tokyo Metropolitan Cancer and Infectious Diseases Center Komagome Hospital, Department of Radiology, Kyoto Prefectural University of Medicine

Abstract Preview: Purpose: Stereotactic body radiotherapy (SBRT) for spine metastases is more effective for pain relief and local control than conventional radiotherapy. However, it is associated with vertebral compres...

Radiodynamic Therapy: Inhibiting Metastases of Small Cell Lung Cancer In Vivo

Authors: Lili Chen, Andy T. Clark, Dusica Cvetkovic, Chang Ming Charlie Ma, Dae-Myoung Yang

Affiliation: Fox Chase Cancer Center

Abstract Preview: Purpose: Radiodynamic therapy (RDT) shows promise as a strategy to inhibit the metastasis of premetastatic small cell lung cancer (SCLC). This study evaluates the therapeutic effect of RDT in inhibiti...

Small but Mighty: A Lightweight and Computationally Efficient Model for Deformable Image Registration

Authors: Hengjie Liu, Dan Ruan, Ke Sheng, DI Xu

Affiliation: Physics and Biology in Medicine, University of California, Los Angeles, Department of Radiation Oncology, University of California, San Francisco, Department of Radiation Oncology, University of California at San Francisco, Department of Radiation Oncology, University of California, Los Angeles

Abstract Preview: Purpose:
State-of-the-art deep learning-based deformable image registration often uses large, complex models directly adapted from computer vision tasks but achieves only comparable performance to ...

Standardized Immobilization and Setup Procedure Improves Accuracy of Multi-Time Point SPECT/CT Image Registration for Radiopharmaceutical Therapy (RPT) Dosimetry

Authors: Bryan Bednarz, Laura Bennett, Abby E. Besemer, Tyler J Bradshaw, Steve Y Cho, John M. Floberg, Joseph Grudzinski, Elissa Khoudary, Michael J. Lawless

Affiliation: Department of Radiology, University of Wisconsin, University of Wisconsin-Madison Department of Medical Physics, Department of Medical Physics, School of Medicine and Public Health, University of Wisconsin - Madison, Department of Human Oncology, University of Wisconsin School of Medicine and Public Health, Voximetry, Inc, University of Pennsylvania, Department of Radiology, University of Wisconsin - Madison, Department of Human Oncology, University of Wisconsin-Madison

Abstract Preview: Purpose: To assess the impact of using a standardized immobilization setup for multi-time-point SPECT/CT imaging on radiopharmaceutical therapy (RPT) dosimetry image registration.

Methods: Ten ...

The Comparison of Radiation Uses in Common Procedures Amongst Didactic Pediatric Fluoroscopic Units

Authors: Janet Ching-Mei Feng, Jimmy Huynh

Affiliation: UTHealth McGovern Medical School

Abstract Preview: Purpose: The Image Gently Alliance had provided helpful information to optimize image protocols in pediatric patients since 2007, and our assumption was that newer units could use near-to-optimal prot...

The Role of 3D Vane MRI in Accurate Phase Matching with 4D-CT for Motion Representation in Liver Cancer Radiotherapy

Authors: Jiayun Chen, Shengqi Chen, Junchao Li, Fei Liu, Jianan Wu

Affiliation: Cancer Hospital Chinese Academy of Medical Sciences, Shenzhen Center, Tongji Medical College, Huazhong University of Science & Technology, School of Electronic Engineering, Beijing University of Posts and Telecommunications, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College

Abstract Preview: Purpose: To assess if 3D Vane MRI can accurately depict the motion of the target volume and OARs.
Methods: This retrospective study included 54 liver cancer patients who underwent both 3D Vane MRI ...

Towards Penile Small Vessel Imaging with Ferumoxytol-Enhanced MRI

Authors: Darren Fang, Amar Kishan, Justin McWilliams, Dan Ruan, Xiaodong Zhong

Affiliation: Department of Radiation Oncology, University of California, Los Angeles, Department of Radiology, University of California, Los Angeles, Department of Radiological Sciences, University of California, Los Angeles

Abstract Preview: Purpose: Prostate radiotherapy can malform penile vasculature, contributing to erectile dysfunction and compromising quality of life. To detect, quantify, and preferably avoid such occurrences, this p...

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...

Using Multiple Sequences MRI for Synthesizing CT Based on a Deep Learning Approach

Authors: Jie Hu, Nan Li, Chuanbin Xie, Shouping Xu, Xinlei Xu, Gaolong Zhang, Zhilei Zhang

Affiliation: School of Physics, Beihang University, National Cancer Center/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Department of Radiation Oncology, the First Medical Center of the People's Liberation Army General Hospital, National Cancer Center/ National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100021, Peopleʼs Republic of China, Department of Radiation Oncology, School of Physics, Beihang University, Beijing, 102206, Peopleʼs Republic of China

Abstract Preview: Purpose: This study aims to synthesize CT images for MRI-only radiation therapy using a deep learning approach that integrates information from the T1- and T2-weighted MRI sequence.
Methods: 97 hea...

VMAT Machine Parameter Optimization Using Policy Gradient Reinforcement Learning

Authors: Avinash Mudireddy, Nathan Shaffer, Joel J. St-Aubin

Affiliation: University of Iowa

Abstract Preview: Purpose: This work demonstrates preliminary results in training a reinforcement learning (RL) network to perform VMAT machine parameter optimization.
Methods: We implemented a policy gradient RL al...

Workflow for Same Day Linac-Based Stereotactic Radiosurgery

Authors: William Amestoy, Carolina Benjamin, Markus Bredel, Rodrigo Delgadillo, Nesrin Dogan, Michael E Ivan, Ricardo J Komotar, Gregory J. Kubicek, Eric Mellon, Ivaylo B. Mihaylov, Maria Irene Monterroso, Raymond A. Schulz, Ashish Shah, Robert M Starke

Affiliation: University of Miami, Department of Radiation Oncology, University of Miami, University of Miami Sylvester Comprehensive Cancer Center, Varian Medical Systems

Abstract Preview: Purpose: Stereotactic Radiosurgery (SRS) is a widely used treatment modality in radiation oncology, utilizing various technologies such as Gamma Knife (GK), Cyber Knife (CK) and Linac-based SRS with H...