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Results for "locally advanced": 27 found

A Multi-Omics Approach for Predicting Acute Hematologic Toxicity in Patients with Cervical Cancer Undergoing External-Beam Radiotherapy

Authors: Sijuan Huang, Yongbao Li

Affiliation: Sun Yat-sen University Cancer Center; State Key Laboratory of Oncology in South China; Collaborative Innovation Center for Cancer Medicine; Guangdong Key Laboratory of Nasopharyngeal Carcinoma Diagnosis and Therapy, Guangzhou, Guangdong, 510060, China, Sun-Yat sen University Cancer Center

Abstract Preview: Purpose: Hematologic toxicity (HT) is one of the most prevalent treatment-related toxicities experienced by locally advanced cervical cancer (LACC) patients receiving radiotherapy (RT). This study aim...

A Multi-Regional and Multi-Omics Approach to Predict Penumonitis in Patients with Locally Advanced Non-Small Cell Lung Cancer in Nrg Oncology Trial RTOG 0617

Authors: Katelyn M. Atkins, Indrin J. Chetty, Elizabeth M. McKenzie, Taman Upadhaya, Samuel C. Zhang

Affiliation: Department of Radiation Oncology,Cedars-Sinai Medical Center, Cedars-Sinai Medical Center

Abstract Preview: Purpose:
We explored a multi-regional and multi-omics approach to extract CT-based radiomics and 3D dosiomics features to predict radiation pneumonitis (RP) in patients with locally advanced Non-Sm...

A Two-Layer, Two-Task Prediction Model Based on 3D Imaging and Residual Networks for Mid-Chemoradiation Tumor Response Prediction on FDG PET for La-NSCLC

Authors: Stephen R. Bowen, Chunyan Duan, Daniel S. Hippe, Qiantuo Liu, Jing Sun, Jiajie Wang, Shouyi Wang, Faisal Yaseen, Xiaojing Zhu

Affiliation: Tongji University, University of Washington, Department of Radiation Oncology, Fred Hutchinson Cancer Center, University of Washington, Shanghai University of Electric Power, Fred Hutchinson Cancer Center, University of Texas at Arlington

Abstract Preview: Purpose: Accurate prediction of patient response to radiotherapy plays a crucial role in monitoring disease progression and assessing treatment efficacy, enabling clinicians to develop personalized th...

An Image Representation of Radiomics Data for Enhanced Deep Radiomics Analysis with Consideration of Feature Interactions

Authors: Xiaolong Fu, Runping Hou, Md Tauhidul Islam, Lei Xing

Affiliation: Department of Radiation Oncology, Stanford University, Department of Radiation Oncology, Shanghai Chest Hospital, Shanghai Jiao Tong University School of Medicine

Abstract Preview: Purpose: To introduce a novel schematic image representation of radiomics data, called OmicsMap, for high-performance deep radiomics analysis. OmicsMap transforms tabular radiomics data into an image ...

Automated Case Prioritization in Breast Radiation Therapy Peer Review Rounds

Authors: Leigh A. Conroy, Thomas G Purdie, Christy Wong

Affiliation: Department of Medical Biophysics, University of Toronto, Princess Margaret Cancer Centre

Abstract Preview: Purpose: To develop a novel machine learning (ML) algorithm to evaluate and rank breast radiation therapy (RT) treatment plans based on treatment complexity for prioritization in multidisciplinary pee...

Beam Orientation Optimization in IMRT Using Sparse Mixed Integer Programming and Non-Convex IMRT Fluence Map Optimization

Authors: Yabo Fu, Yang Lei, Yu Lei, Haibo Lin, Ruirui Liu, Tian Liu, Kenneth Rosenzweig, Charles B. Simone, Shouyi Wei, Jiahan Zhang

Affiliation: Icahn School of Medicine at Mount Sinai, University of Nebraska Medical Center, Department of Medical Physics, Memorial Sloan Kettering Cancer Center, New York Proton Center

Abstract Preview: Purpose: Beam orientation optimization (BOO) in intensity-modulated radiation therapy (IMRT) is traditionally a complex, non-convex problem tackled with heuristic methods. This study benchmarks global...

Comprehensive Evaluation of Federated Learning Strategies for Head and Neck Tumor Segmentation on PET/CT Images

Authors: Jingyun Chen, Yading Yuan

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

Abstract Preview: Purpose: To evaluate centralized and decentralized strategies for federated head and neck tumor segmentation on PET/CT.
Methods: We utilized training data from the HEad and neCK TumOR segmentation ...

Development of a Knowledge-Based Planning Model for Optimal Trade-Off Guidance in Locally Advanced Non-Small Cell Lung Cancer

Authors: Ming Chao, Hao Guo, Tenzin Kunkyab, Yang Lei, Tian Liu, Kenneth Rosenzweig, Robert Samstein, James Tam, Junyi Xia, Jiahan Zhang

Affiliation: Icahn School of Medicine at Mount Sinai

Abstract Preview: Purpose:
The aim of the study is to develop a trade-off prediction model to efficiently guide the treatment planning process for patients with stage III non-small cell lung cancer (NSCLC).
Metho...

Diffusion-Weighted MRI: An Early Biomarker for Treatment Response in MR-Guided Treatment of Rectal Cancer

Authors: Huiming Dong, Jonathan Pham, X. Sharon Qi, Ann Raldow

Affiliation: Department of Radiation Oncology, University of California, Los Angeles

Abstract Preview: Purpose: The study aimed to investigate longitudinal apparent diffusion coefficient (ADC) as an early biomarker of treatment response in patients with locally advanced rectal cancer (LARC) undergoing ...

Dual-Energy CT Derived Perfusion Blood Volume and 4D-CT Derived Ventilation Changes in Lung Cancer Patients 6-Months Post Radiation Therapy

Authors: Daniel A. Alexander, Jeffrey D. Bradley, Steven J. Feigenberg, Cole Friedes, Casey Hollawell, William Levin, Maksym Sharma, Boon-Keng Kevin Teo, Ying Xiao, Nikhil Yegya-Raman, Jennifer Wei Zou

Affiliation: Department of Radiation Oncology and Applied Sciences, Department of Radiation Oncology, University of Pennsylvania, University of Pennsylvania

Abstract Preview: Purpose: To investigate lung function changes following definitive chemoradiation dose using CT-derived measurements in patients with locally advanced NSCLC at 6-months post-treatment compared to pre-...

Empowering Knowledge Transfer in Global Radiotherapy Planning: An Educational Case Study of Knowledge-Based Models in Nepal

Authors: Rita Buono, Elisabetta Cagni, Roberta Castriconi, Surendra Bahadur Chand, Marco Esposito, Claudio Fiorino, Valeria Landoni, Aldo Mazzilli, Eugenia Moretti, Lorenzo Placidi, Giulia Rambaldi Guidasci, Alessia Tudda

Affiliation: IRCCS San Raffaele Scientific Institute, Department of Advanced Technology, IRCCS Regina Elena National Cancer Institute, ASU FC Medical Physics, University Hospital of Parma AOUP, ICTP, B.P. Koirala Memorial Cancer Hospital, Fondazione Policlinico Universitario Agostino Gemelli IRCCS, Fatebenefratelli Isola Tiberina – Gemelli Isola

Abstract Preview: Purpose: To explore the feasibility and educational impact of transferring knowledge-based planning (KBP) models—developed using Italian breast radiotherapy data—to a Nepalese hospital, thereby demons...

Equivalent Uniform Dose and Duodenal Toxicity Correlation in Pancreatic Cancer Irradiation

Authors: Samira Dabaghmanesh, Beth A. Erickson, William Hall, Jason Hirshberg, An Tai

Affiliation: Department of Radiation Oncology, Medical College of Wisconsin

Abstract Preview: Purpose: Treatment plan evaluation for minimizing duodenal toxicity often involves multiple dose-volume constraints that vary based on fractionation. The Equivalent Uniform Dose (EUD) has emerged as a...

Feasibility Study of Deep Learning-Based MRI-to-PET Generation for Rectal Cancer: Overall Survival Prediction and Pathological Complete Response Assessment

Authors: Weigang Hu, Zhenhao Li, Jiazhou Wang, Xiaojie Yin, Zhen Zhang

Affiliation: Fudan University Shanghai Cancer Center

Abstract Preview: Purpose:
This study aims to develop and validate a novel deep learning method to generate synthetic PET images for rectal cancer from MRI data. By incorporating metabolic information from the synth...

Improve the Risk Prediction of Radiation-Induced Esophagitis in Lung IMRT By an Anisotropic Dose Convolution Neural Network

Authors: Ibtisam Almajnooni, Elisabeth Weiss, Lulin Yuan

Affiliation: Virginia Commonwealth University

Abstract Preview: Purpose: We developed a deep learning neural network (DLNN) to predict the risk of radiation-induced esophagitis (RE) during lung cancer radiation therapy based on the spatial dose distribution, for t...

In-Silico Clinical Trials Enabled By Digital Twin Approach Can Accurately and Prospectively Predict Outcomes of Clinical Trials Combining Radiation and Systemic Therapy

Authors: Clemens Grassberger, David (Bo) McClatchy, Harald Paganetti

Affiliation: Department of Radiation Oncology, University of Washington and Fred Hutchinson Cancer Center, Massachusetts General Hospital

Abstract Preview: Purpose: While randomized controlled trials (RCTs) are the gold standard for demonstrating efficacy, nearly 50% of late-stage clinical trials fail to meet their endpoint. Tools to study the design of ...

Leveraging Codex-Based Spatial Profiling of the Tumor Microenvironment in Concurrent Radiation Therapy and Immunotherapy

Authors: Todd A Aguilera, Bassel Dawod, Sebastian Diegeler, Eslam Elghonaimy, Purva Gopal, Jiaqi Liu, Hao Peng, Arely Perez Rodriguez, Nina N. Sanford, Robert Timmerman, Megan B Wachsmann, Haozhao 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, UT Southwestern Medical Center

Abstract Preview: Purpose: This study pioneers the integration of CODEX (co-detection by indexing)-based spatial profiling and advanced computational techniques to investigate the tumor immune microenvironment (TIME) i...

Lymph Node Dose Is Associated with Immune Suppression and Poor Overall Survival in Locally Advanced Non-Small Cell Lung Cancer (NSCLC)

Authors: Ryan Gentzler, Xin He, James Larner, J.T. Morgan, Cam Nguyen, Wendy Stewart, Krishni Wijesooriya, Grant Williams

Affiliation: Department of Physics, University of Virginia, Department of Radiation Oncology, University of Virginia, Division of Hematology & Oncology, Department of Medicine, University of Virginia

Abstract Preview: Purpose: Some recent studies have shown Overall Survival (OS) of advanced-stage lung cancer patients treated with chemo-radiation therapy (CRT) is correlated with heart dose [1-5], while in other stud...

Medical Physics Training Program, Staff Retention, and Service Improvement Strategy in a Regional Radiotherapy Centre

Authors: Dilli Banjade, Ajeet Mishra, Shiaw Juen (Eugene) Tan

Affiliation: District Radiation Oncology Service WNW Health

Abstract Preview: Purpose: A shortage of qualified Radiation Oncology Medical Physicists (ROMPs) poses a critical challenge to providing advanced treatments in regional Australia. Training and retaining medical physici...

Muilt-Instance Learning Model with 2D and 3D Features Representation and Transformer-Based Prediction for FDG PET Tumor Chemoradiation Response of La-NSCLC

Authors: Stephen R. Bowen, Chunyan Duan, Daniel S. Hippe, Qiantuo Liu, Jiajie Wang, Shouyi Wang, Faisal Yaseen, Han Zhou

Affiliation: Tongji University, University of Washington, Department of Radiation Oncology, Fred Hutchinson Cancer Center, University of Washington, Fred Hutchinson Cancer Center, University of Texas at Arlington

Abstract Preview: Purpose: Predicting the effects of the spatial-temporal tumor response to chemoradiation can assist in adjusting radiation dose and support clinical decision-making in radiotherapy. A multi-instance l...

Multi-Omics-Based Prognostic Prediction for Locally Advanced Hypopharyngeal Cancer Treated with Postoperative Chemoradiotherapy: A Dual-Center Study

Authors: Sixue Dong, Chaosu Hu, Weigang Hu, Xiaomin Ou, Jiazhou Wang, Zhen Zhang

Affiliation: Fudan University Shanghai Cancer Center

Abstract Preview: Purpose:
This study aimed to predict the PFS of the patients who were diagnosed with hypopharyngeal cancer and received postoperative chemoradiotherapy by using multi-omics which integrating clinic...

Optimization of the U-Net Model for the Radiation Dose Prediction in Lung Cancer RT Plans and Its Uncertainty Quantification

Authors: Ibtisam Almajnooni, Victor Cobilean, Milos Manic, Harindra Sandun Mavikumbure, Elisabeth Weiss, Lulin Yuan

Affiliation: Virginia Commonwealth University

Abstract Preview: Purpose: This study aims to optimize the 3D U-Net architecture for dose prediction in lung cancer radiation therapy (RT) plans, particularly in scenarios with limited clinical data, as well as to quan...

Optimizing Fractionation Schedules for De-Escalation Radiotherapy in Head and Neck Cancers Using Deep Reinforcement Learning

Authors: Zhongjie Lu

Affiliation: Department of Radiation Oncology, The First Affiliated Hospital, Zhejiang University School of Medicine

Abstract Preview: Purpose: Patients with locally-advanced head and neck squamous cell carcinomas(HNSCCs), particularly those related to human papillomavirus(HPV), often achieve good locoregional control(LRC), yet they ...

Quantifying Cervical Cancer Radiotherapy Care Gap in Uganda: Baseline Assessment Prior to Implementation of a Custom Mobile Health App.

Authors: Eric C. Ford, Awusi Kavuma, Solomon Kibudde, Lilie Lin, Apollo Muramuzi, Nibedita Paul, Peniel T Twum, Afua A. Yorke

Affiliation: Uganda Cancer Institute, MD Anderson Cancer Center, University of Washington, Department of Radiation Oncology, Fred Hutchinson Cancer Center, University of Washington, University of Nebraska, Global Communities

Abstract Preview: Purpose: Sub-Saharan Africa accounts for over one-third of global cervical cancer deaths, despite representing only 14% of the world’s female population. At the only RT center in Uganda, prior studies...

Treatment Plan Evaluation of the Patient-Tailored Architect Applicator for Cervical Cancer Brachytherapy

Authors: Jenny Dankelman, Ben J. M. Heijmen, Inger-Karine K. Kolkman-Deurloo, Remi A. Nout, Linda Rossi, Robin Straathof, Linda Wauben, Henrike Westerveld, Nick J. van De Berg, Sharline M. van Vliet - Perez

Affiliation: Department of BioMechanical Engineering, Delft University of Technology, Department of Gynecological Oncology, Erasmus MC Cancer Institute, University Medical Center Rotterdam, Department of Radiotherapy, Erasmus MC Cancer Institute, University Medical Center Rotterdam

Abstract Preview: Purpose:
To quantify the dosimetric advantages of the 3D-printed patient-tailored ARCHITECT applicator with optimized needle channel configurations compared to clinically used intracavitary/interst...

Two-Stage Clustering and Auto Machine Learning to Predict Chemoradiation Response in Tumor Subregions on FDG PET for La-NSCLC

Authors: Stephen R. Bowen, Shijun Chen, Chunyan Duan, Daniel S. Hippe, Qiantuo Liu, Qianqian Tong, Jiajie Wang, Shouyi Wang, Faisal Yaseen

Affiliation: The University of Texas at Austin, Tongji University, University of Washington, Department of Radiation Oncology, Fred Hutchinson Cancer Center, University of Washington, Fred Hutchinson Cancer Center, University of Texas at Arlington

Abstract Preview: Purpose: Tumor subregion clustering and prediction of region-specific response can augment assessments and adaptive treatment decisions. A modeling framework was constructed to predict chemoradiation ...

Using Machine Learning to Predict Esophagitis Risk in Lung Cancer Radiotherapy Based on Clinical and Dosimetric Factors

Authors: Ibtisam Almajnooni, Siyong Kim, Nathaniel Miller, Elisabeth Weiss, Lulin Yuan

Affiliation: Virginia Commonwealth University

Abstract Preview: Purpose: Radiation-induced esophagitis (RE) is a common concern in lung cancer IMRT. Recent studies have indicated that the risk of radiation side effects varies greatly with patients’ baseline clinic...

Volumetric-Modulated Arc Therapy (VMAT) Is Associated with Improved Dose Homogeneity, but More Normal Tissue Irradiation Compared to Three-Dimensional Conformal Radiation Therapy (3DCRT) for Breast Cancer

Authors: Laura I. Cervino, Linda X. Hong, Jessica Pagan, Angelica A. Perez-Andujar, Maria Thor

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

Abstract Preview: Purpose: Three-dimensional conformal radiotherapy (3DCRT) and Volumetric-Modulated Arc Therapy (VMAT) are used to treat locally advanced breast cancer. The 3DCRT treatment plans use the treatment fiel...