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Results for "dlg value": 18 found

Advancing Deep Segmentation Accuracy in CBCT for Radiotherapy Via Robust Scatter Mitigation: First Results from a Pilot Trial

Authors: Cem Altunbas, Farhang Bayat, Roy Bliley, Rupesh Dotel, Brian Kavanagh, Uttam Pyakurel, Tyler Robin, Ryan Sabounchi

Affiliation: Department of Radiation Oncology, University of Colorado School of Medicine, Taussig Cancer Center, Cleveland Clinic, University of Colorado Anschutz Medical Campus

Abstract Preview: Purpose: Automatic segmentation of anatomical structures in CBCT images is key to enabling dose delivery monitoring and online plan modifications in radiotherapy. However, poor image quality can degra...

An International Multi-Institutional Espresso Study of Developing the Specialized-Equipment-Free Remote Audit for Single-Isocenter Multi-Target Stereotactic Radiosurgery

Authors: Juan-Francisco Calvo-Ortega, Andrew Cousins, Ashley Cullen, Andrew Dipulia, Peter B. Greer, Seng Boh Gary Lim, Shih-Chi Lin, D. Michael Lovelock, Conor McGarry, Victoria Robinson, Cameron Stanton, Baozhou Sun, Ching-Ling Teng, Gemma Warner, Benjamin J. Zwan

Affiliation: Northern Ireland Cancer Centre, Baylor College of Medicine, Department of Medical Physics, Memorial Sloan Kettering Cancer Center, Christchurch Hospital, Northwell, Central Coast Cancer Centre, Calvary Mater Hospital, Hospital Quironsalud Barcelona, Icahn School of Medicine at Mount Sinai, Chris O'Brien Lifehouse, University of Newcastle

Abstract Preview: Purpose: This multi-institution Electronic Silicon-based Remote Survey of Small-field Output (ESPRESSO) study aims to develop the remote audit process to evaluate the safety of single-isocenter multi-...

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...

CT-Free PET Imaging: Synthetic CT Generation for Efficient and Accurate PET-Based Planning

Authors: Mingli Chen, Xuejun Gu, Hao Jiang, Mahdieh Kazemimoghadam, Weiguo Lu, Qingying Wang, Kangning Zhang

Affiliation: 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:
PET is used in radiotherapy workflows for accurate target delineation. However, a separate CT scan is typically required for attenuation correction in PET imaging and for registering PET-d...

Deep Learning–Based Dose Prediction for Automated Proton Radiation Therapy Planning of Breast Cancer

Authors: Ahssan Balawi, Peter Jermain, Timothy Kearney, Sonali Rudra, Michael H. Shang, Markus Wells, Mohammad Zarenia

Affiliation: Department of Radiation Medicine, MedStar Georgetown University Hospital

Abstract Preview: Purpose: To investigate the applicability and accuracy of a deep learning (DL) model in predicting radiation dose distribution for breast cancer patients treated with pencil-beam-scanning proton radio...

Evaluating the Impact of Contour Variability on the Effectiveness of Deep Learning Features in Head and Neck Imaging

Authors: Hania A. Al-Hallaq, Xuxin Chen, Anees H. Dhabaan, Elahheh (Ella) Salari, Xiaofeng Yang

Affiliation: Emory University, Department of Radiation Oncology and Winship Cancer Institute, Emory University

Abstract Preview: Purpose:
Radiomics image analysis could lead to the development of predictive signatures and personalized radiotherapy treatments. However, variations in delineation are known to affect hand-crafte...

Evaluating the Impact of an Average Versus Machine-Specific Dosimetric Leaf Gap on Dose Calculation

Authors: Michael Ashenafi, Nicholas Becerra Espinosa, Mario Ramos Gallardo, Matthew Pacella, Sean M. Tanny

Affiliation: Department of Radiation Oncology, University of Rochester

Abstract Preview: Purpose: The newest version of a large commercial treatment planning system (TPS) has introduced a new physical MLC model. We compare the impact of using an averaged dosimetric leaf gap (DLG) value ve...

Evaluation of Nodule Volume Accuracy with Deep Learning-Based Reconstructions on Cdznte Photon-Counting and Energy-Integrating CT

Authors: Gisell Ruiz Boiset, Paulo ROBERTO Costa, Luuk J Oostveen, Elsa Bifano Pimenta, Ioannis Sechopoulos, Alessandra Tomal

Affiliation: Radboud University Medical Center, University of São Paulo (USP), Institute of Physics, Universidade Estadual de Campinas. Instituto de Física Gleb Wataghin

Abstract Preview: Purpose: This study aimed to evaluate the precision and accuracy of volume measurements for solid nodules (SNs) and ground-glass opacities (GGOs) in lung images acquired using energy-integrating CT (E...

Impact of Ion Chamber Selection on Enhanced Leaf Modeling Predictions of Dosimetric Leaf Gap and Leaf Transmission Factors

Authors: Michael Ashenafi, Nicholas Becerra Espinosa, Mario Ramos Gallardo, Matthew Pacella, Sean M. Tanny

Affiliation: Department of Radiation Oncology, University of Rochester

Abstract Preview: Purpose: A new multileaf collimator (MLC) model has been introduced in Varian Eclipse v18.0, with the treatment planning system (TPS) explicitly modeling the leaf end effects. The vendor recommends a ...

Inconsistencies in Methods for CMS Size-Adjusted Dose Measure

Authors: Alexander Alsalihi, Gary Y. Ge, Charles Mike Weaver, Jie Zhang

Affiliation: University of Kentucky

Abstract Preview: Purpose: The upcoming CMS regulation, titled “Excessive Radiation Dose or Inadequate Image Quality for Diagnostic Computed Tomography (CT) in Adults”, employs two measures, size-adjusted DLP (SAD) and...

Inter-System and Inter-Layer Dlg Variations in Halcyon/Ethos Mlcs: Implications for Dosimetric Matching and User-Adjustable TPS Models

Authors: Evan Barber, Gloria P. Beyer, Matthew J. Daniels, Callum Hartley, Jordi Saez, Philip Wheeler

Affiliation: TrueNorth Medical Physics, Department of Radiotherapy Physics, Velindre University NHS Trust, Department of Radiation Oncology, Hospital Clinic de Barcelona, Medical Physics Services, LLC

Abstract Preview: Purpose: To quantify inter-system and inter-layer dosimetric leaf gap (DLG) variations in Halcyon/Ethos multileaf collimators (MLCs) using custom sweeping gap tests, and to evaluate implications for c...

Investigation of High Cumulative Doses and Dose Outliers in a Pediatric Hospital

Authors: Niki Fitousi, Stanley Thomas Fricke, Anna Romanyukha

Affiliation: Qaelum NV, Children's National Hospital

Abstract Preview: Purpose:
To identify opportunities for improvement through investigation of outliers in exam dose length product (DLP) and patients receiving high cumulative doses (CED), in the context of our “ped...

Investigation of the Impact of Dlg Changes on Plan Quality and Patient Specific QA

Authors: Nicole C. Detorie, Steven M. Kirsner, Remy Y. Manigold

Affiliation: Scripps Cancer Center

Abstract Preview: Purpose:
Dosimetric Leaf Gap (DLG) is an important factor in obtaining the proper beam model in the Eclipse treatment planning system. The purpose of this study was to investigate the dosimetric im...

Is Simplicity Even Better: Deep Learning Algorithms for Breath Motion Phase Prediction in Motion Management

Authors: Amanda J. Deisher, Andrew YK Foong, Witold Matysiak, Jing Qian, Xueyan Tang, Erik J. Tryggestad, Mi Zhou

Affiliation: Mayo Clinic

Abstract Preview: Purpose: Phase gating is commonly employed to mitigate the impact of tumor motion in radiotherapy. Due to the machine-specific time delay between triggering and radiation delivery, the triggering sign...

Simultaneous Synthesis of Lung Perfusion and Ventilation Images from CT Using a Dual-Decoder Residual Attention Network for Lung Disease Diagnosis

Authors: Li-Sheng Geng, David Huang, Haoze Li, Xi Liu, Meng Wang, Tianyu Xiong, Ruijie Yang, Weifang Zhang, Meixin Zhao

Affiliation: School of Physics, Beihang University, Department of Health Technology and Informatics, The Hong Kong Polytechnic University, Department of Radiation Oncology, Peking University Third Hospital, Department of Nuclear Medicine, Peking University Third Hospital, Medical Physics Graduate Program, Duke Kunshan University

Abstract Preview: Purpose: This study aimed to develop a deep learning-based framework for simultaneously generating lung perfusion and ventilation images from three-dimensional computed tomography (3D CT) images.
M...

Teaching an Old Dog New Tricks: Unlocking Hidden Potential in Existing Frameworks for Versatile Radiotherapy Applications

Authors: Mingli Chen, Xuejun Gu, Hao Jiang, Mahdieh Kazemimoghadam, Weiguo Lu, Qingying Wang, Kangning Zhang

Affiliation: 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:
This work demonstrates how existing software, when creatively adapted, can address a wide range of clinical challenges. By focusing on data exploration and application-specific modificatio...

Uncertainty Analysis for Effective Dose Conversion Factors in CT

Authors: Renxin Chu, Jelena Mihailovic, Kai Yang, Lifeng Yu, Da Zhang

Affiliation: Massachusetts General Hospital, Mayo Clinic, Boston Children's Hospital, UVA Health University Hospital, University of Missouri Health Care

Abstract Preview: Purpose:
A frequently used method to estimate effective dose (ED) in CT is by multiplying the dose length product (DLP) by a conversion factor, known as k-factor. The k-factor in this method is sus...

Validation of a Simulation Tool and in-Silico Assessment of Low Contrast Detectability for Super-Resolution Deep Learning Reconstruction

Authors: Naruomi Akino, Kirsten Lee Boedeker, Ilmar Hein, Akira Nishikori, Daniel W Shin

Affiliation: Canon Medical Systems Corporation, Canon Medical Research USA

Abstract Preview: Purpose: To validate a simulation tool using physics-based image quality metrics in both phantom and patient data, and to assess the low contrast detectability (LCD) of Super Resolution-Deep Learning ...