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Results for "logistic regression": 24 found

18F-FDG PET/CT-Based Deep Radiomic Models for Enhancing Chemotherapy Response Prediction in Breast Cancer

Authors: Ke Colin Huang, Zirui Jiang, Joshua Low, Christopher F. Njeh, Oluwaseyi Oderinde, Yong Yue

Affiliation: Purdue University, Indiana University School of Medicine, Department of Radiation Oncology

Abstract Preview: Purpose: Enhancing the accuracy of tumor response predictions enables the development of tailored therapeutic strategies for patients with breast cancer (BCa). In this study, we developed deep-radiomi...

A Multi-Agent Approach for Fully Automated Nephrometry Feature Extraction in CT

Authors: Matthew S Brown, Joshua Genender, John M. Hoffman, Gabriel Melendez-Corres, Muhammad W. Wahi-Anwar

Affiliation: David Geffen School of Medicine at UCLA, UCLA Department of Radiology

Abstract Preview: Purpose: Renal lesions are evaluated using scoring systems based on visual assessments and manual measurements. The purpose of this work is to develop a multi-agent system for automated anatomic landm...

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...

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...

Automatic Contour Quality Assurance Using Deep-Learning Based Contours

Authors: Laurence Edward Court, Raphael Douglas, David Fuentes, Anuja Jhingran, Barbara Marquez, Raymond Mumme, Christine Peterson, Julianne M. Pollard-Larkin, Surendra Prajapati, Dong Joo Rhee, Thomas J. Whitaker

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

Abstract Preview: Purpose: Safe deployment of auto-contouring models requires the inclusion of automated quality assurance (QA). One approach is to use an independent auto-contouring model and compare the contours geom...

CBCT-Based Radiomics of Head and Neck Cancer for Predicting Patient Toxicity to Radiotherapy

Authors: Rodrigo Delgadillo, Nesrin Dogan, Benjamin J. Rich, Stuart E Samuels, Levent Sensoy

Affiliation: University of Miami Sylvester Comprehensive Cancer Center

Abstract Preview: Purpose: Daily Cone beam CT (CBCT) images may be useful in detecting early morphological changes during head and neck cancer radiotherapy. The aim of this study was to evaluate the performance of CBCT...

Characterization of HCC Tumor Response in 90Y-Radioembolization Clinical Trial RAPY90D Using Prospective Voxel Dosimetry

Authors: E Courtney Henry, Srinivas Cheenu Kappadath, Armeen Mahvash

Affiliation: UT MD Anderson Cancer Center

Abstract Preview: Purpose:
Characterization of hepatocellular carcinoma (HCC) tumor responses for single-arm single-center prospective 90Y-radioembolization clinical trial (n=40) that used patient-specific voxel-dos...

Clinical Factors Associated with Urinary Morbidity in Men Undergoing Combination Prostate Radiation Therapy

Authors: James Benton, Andrew Dewar, Benjamin C Lee, Ryan Y Lee

Affiliation: Radiotherapy Clinics of Georgia, Urology of Greater Atlanta

Abstract Preview: Purpose:
The purpose of our investigation was to determine if pre-treatment factors could predict urinary morbidity after combination radiation treatment for localized prostate cancer.
Methods:<...

Comparing Planned Vs. Delivered Bladder Dose-Toxicity Associations in Prostate Cancer Radiotherapy: Insights from the Mirage Trial

Authors: Minsong Cao, Amar Kishan, Yi Lao, An Liu, Beth Neilsen, X. Sharon Qi, Kun Qing, Ke Sheng, Michael Steinberg, Luca F Valle, Terence Williams

Affiliation: Department of Radiation Oncology, University of California, Los Angeles, Department of Radiation Oncology, City of Hope Medical Center, Department of Radiation Oncology, University of California, San Francisco, Department of Radiation Oncology, City of Hope National Medical Center

Abstract Preview: Purpose: To investigate the clinical relevance of planned versus delivered doses in toxicity associations utilizing localized assessment of genitourinary (GU) toxicity in bladder subregions among pros...

Development of Foundation Model for Analysis of Prostate Cancer with Mpmri

Authors: Ahmad Algohary, Adrian Breto, Quadre Emery, Radka Stoyanova

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

Abstract Preview: Purpose:
To develop a foundation model (U-Found) for multiparametric MRI (mpMRI) of the prostate by using self-supervised learning to prove the feasibility of a prostate-oriented foundation model u...

Development of a Comprehensive Thoracic Re-Irradiation Database and Investigation of Time-Dependent Dose-Recovery Dynamics for Toxicity Modeling

Authors: Victoria Doss, Tsion Gebre, Rachel B. Ger, Esi A Hagan, Elaina Hales, Russell K Hales, Xun Jia, Heng Li, Dezhi Liu, Todd R. McNutt, Meti Negassa, Anas Obaideen, Tinker Trent, K. Ranh Voong, Cecilia FPM de Sousa

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

Abstract Preview: Purpose: As cancer care advances, more patients require re-irradiation, yet evidence-based data is lacking. This study aimed to develop a thoracic re-irradiation database and explore time-dependent re...

Evaluating Supervised Learning Models for Binary Classification of Radiomic Data in Predicting Head and Neck Cancer Treatment Outcomes

Authors: Theodore Higgins Arsenault, Kyle O'Carroll, Christian Erik Petersen, Alex T. Price, Meiying Xing

Affiliation: University Hospitals Seidman Cancer Center

Abstract Preview: Purpose: To assess the performance of various supervised learning models’ ability to predict binary classification of radiomic data for head and neck (H&N) cancer treatment outcomes.
Methods: Using...

MRI Radiomics-Based Machine Learning Model for Predicting BNCT Treatment Response in Glioblastoma

Authors: Huang Chi-Shiuan, Wu Chih-Chun, Hui-Yu Cathy Tsai, Chen Yan-Han, Chen Yi-Wei, Pan Yi-Ying

Affiliation: Institute of Nuclear Engineering and Science, National Tsing Hua University, Taipei Veterans General Hospital, Tri-Service General Hospital

Abstract Preview: Purpose:
This study aims to develop and validate a machine learning (ML) model based on MRI-derived radiomic features to predict progressive disease (PD) in glioblastoma (GBM) patients four months ...

Machine Learning Model for Early Prediction of Chemoradiotherapy Response in Oropharyngeal Cancer Patients

Authors: Waleed Mutlaq Almutairi, Ke Colin Huang, Vishwas Mukundan, Christopher F. Njeh, Oluwaseyi Oderinde, Yong Yue

Affiliation: Purdue University, Indiana University School of Medicine, Department of Radiation Oncology, Advanced Molecular Imaging in Radiotherapy (AdMIRe) Research Laboratory, Purdue University, West Lafayette, Indiana, USA

Abstract Preview: Purpose:
This study aimed to develop a machine learning (ML) model for early prediction of chemoradiotherapy (CRT) response in order to enhance personalized treatment selection for oral or orophary...

Mechanistical Modeling of Radiation Response of Parotid in Head and Neck Cancer Radiotherapy

Authors: Rachel B. Ger, Xun Jia, Youfang Lai, Todd R. McNutt, Xingyi Zhao

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

Abstract Preview: Purpose: Radiotherapy (RT) plays an essential role for head and neck (HN) cancer treatment but often results in xerostomia due to salivary gland damage. It is important to mechanistically model the ra...

Mitigating Data-Driven Uncertainty in Machine Learning-Based Radiotherapy Outcome Prediction

Authors: Ali Ajdari, Alice Bondi, Thomas R. Bortfeld, Gregory Buti, Xinru Chen, Zhongxing Liao, Antony John Lomax, Ting Xu

Affiliation: The University of Texas MD Anderson Cancer Center, Department Of Radiation Oncology, Massachusetts General Hospital (MGH), Massachusetts General Hospital & Harvard Medical School, Paul Scherrer Institut, ETH Zurich

Abstract Preview: Title: Addressing Imaging and Biomarker-driven Uncertainty in Machine Learning-based Radiotherapy Outcome Prediction
Alice Bondi, Gregory Buti, Antony Lomax, Thomas Bortfeld, Xinru Chen, Ting Xu, Z...

Multi-Variat, Multi-Model, and Multi-Patient: From Pure Feasibility to Generalizability in Machine Learning Outcome Prediction Model-Based Treatment Plan Optimization

Authors: Martin Frank, Oliver Jäkel, Niklas Wahl

Affiliation: Department of Medical Physics in Radiation Oncology, German Cancer Research Center (DKFZ), Karlsruhe Institute of Technology (KIT)

Abstract Preview: Purpose: Machine learning (ML) models on normal tissue complication and tumor control probability ((N)TCP) exploiting e.g. dosiomic and radiomic features are playing an increasingly important role in ...

Personalized Radiotherapy: A Novel Approach to Multi-Criteria Optimization with Patient-Specific Risk Integration

Authors: Ali Ajdari, Thomas R. Bortfeld, Zhongxing Liao, Mara Schubert, Katrin Teichert

Affiliation: The University of Texas MD Anderson Cancer Center, Department Of Radiation Oncology, Massachusetts General Hospital (MGH), Massachusetts General Hospital & Harvard Medical School, Fraunhofer ITWM

Abstract Preview: Purpose: Radiotherapy (RT) treatment planning often involves solving a multi-criteria optimization (MCO) problem. Conventionally, MCO considers a set of generic (population-wide) dosimetric criteria, ...

Predicting Hormone Receptor Status in Breast Cancer Using Mammographic and Sonographic Data and Machine Learning Models

Authors: Zahra Bagherpour, Manijeh Beigi, Pedram Fadavi, Faraz Kalantari, Moghadaseh Khaleghibizaki, Hengameh Nazari, Mojtaba Safari, Sepideh Soltani

Affiliation: Department of Radiation Oncology, School of Medicine, Iran University of Medical Sciences, Department of Radiation Oncology, School of Medicine, Emory University and Winship Cancer Institute, Department of Radiation Oncology, Iran University of Medical Sciences, University of Arkansas for medical sciences, Department of Radiation physics, The University of Texas MD Anderson Cancer Center UTHealth Houston Graduate School of Biomedical Sciences

Abstract Preview: Purpose: This study aims to evaluate whether readily available mammographic and sonographic data, combined with machine learning (ML) models, can predict critical molecular factors (ER, PR, HER2) in b...

Prediction of Metastasis-Free Survival in Patients with Prostate Adenocarcinoma Using Primary Tumor and Lymph Node Radiomics from Pre-Treatment PSMA PET/CT Scans.

Authors: Ozan Cem Guler, William Silva Mendes, Sangbo Oh, Cem Onal, Lei Ren, Apurva Singh, Phuoc Tran

Affiliation: University of Maryland School of Medicine, Baskent University Faculty of Medicine, Department of Radiation Oncology, Department of Radiation Oncology, University of Maryland School of Medicine

Abstract Preview: Purpose: To predict metastasis-free survival (MFS) for patients with prostate adenocarcinoma treated with androgen deprivation therapy and external radiotherapy using clinical factors and radiomics ex...

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...

Using Bayesian Analysis to Quantify the Impact of Clinical and Dosimetric Features for Predicting Swallowing Dysfunction in Oropharyngeal Cancer after Radiotherapy

Authors: Matthew D Blackledge, Christopher M. Nutting, Anju Mohanan Kaimal, Justine Tyler, Konstantinos Zormpas-Petridis

Affiliation: Fondazione Policlinico Universitario Agostino Gemelli IRCCS, Institute of Cancer Research, The Royal Marsden NHS Foundation Trust, The Institute of Cancer Research

Abstract Preview: Purpose: Swallowing dysfunction (dysphagia) is a common side effect of radiotherapy for oropharyngeal cancer, significantly affecting patient's quality of life. This study aims to investigate the rela...

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...

Utilizing Multiple Modalities to Improve Models to Predict Changes in International Prostate Score for Prostate Cancer

Authors: Matthew C Abramowitz, Alan Dal Pra, Rodrigo Delgadillo, Nesrin Dogan, John C. Ford, Kyle R. Padgett, Levent Sensoy, Benjamin Spieler, Matthew T. Studenski, Jace Allen Walker

Affiliation: University of Miami, Department of Radiation Oncology, University of Miami, University of Miami Sylvester Comprehensive Cancer Center, University of Miami School of Medicine

Abstract Preview: Purpose:
Toxicities that affect a patient’s quality-of-life due to prostate cancer (pCa) radiation therapy (RT) are receiving more attention as RT has become increasingly successful in treating pCA...