Kareem A. Wahid
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View article: Computed Tomography Orodental Sub-volume Imaging Annotation Dataset of Head and Neck Cancer Radiation Therapy Patients
Computed Tomography Orodental Sub-volume Imaging Annotation Dataset of Head and Neck Cancer Radiation Therapy Patients Open
Accurate delineation of orodental structures on computed tomography (CT) is critical for image-guided assessments of radiation-associated bone injury. This dataset comprises curated CT imaging and expert-defined segmentation masks for 60 p…
View article: A Multimodal and Multi-centric Head and Neck Cancer Dataset for Segmentation, Diagnosis and Outcome Prediction
A Multimodal and Multi-centric Head and Neck Cancer Dataset for Segmentation, Diagnosis and Outcome Prediction Open
We present a publicly available multimodal dataset for head and neck cancer research, comprising 1123 annotated Positron Emission Tomography/Computed Tomography (PET/CT) studies from patients with histologically confirmed disease, acquired…
View article: Clinical and dosimetric dataset of time-to-event normal tissue complication probability for osteoradionecrosis
Clinical and dosimetric dataset of time-to-event normal tissue complication probability for osteoradionecrosis Open
Osteoradionecrosis of the jaw (ORNJ) is a radiation-induced late toxicity that can dramatically decrease patients’ quality of life. Recent increases in survival rates of head and neck cancers associated with human papillomavirus (HPV) infe…
View article: Optimizing Atlas Counts for MRI-Guided Atlas-Based Autosegmentation of Swallowing Muscles in Head and Neck Radiotherapy
Optimizing Atlas Counts for MRI-Guided Atlas-Based Autosegmentation of Swallowing Muscles in Head and Neck Radiotherapy Open
Purpose Radiotherapy-induced dysphagia can significantly impair head and neck (H&N) cancer patients’ quality of life. Despite the dose-dependent relationship between radiotherapy and dysphagia, swallowing structures are not routinely conto…
View article: Image-based mandibular and maxillary parcellation and annotation using computed tomography (IMPACT): a deep learning-based clinical tool for orodental dose estimation and osteoradionecrosis assessment
Image-based mandibular and maxillary parcellation and annotation using computed tomography (IMPACT): a deep learning-based clinical tool for orodental dose estimation and osteoradionecrosis assessment Open
View article: Computed tomography radiomics-based cross-sectional detection of mandibular osteoradionecrosis in head and neck cancer survivors
Computed tomography radiomics-based cross-sectional detection of mandibular osteoradionecrosis in head and neck cancer survivors Open
View article: A method for sensitivity analysis of automatic contouring algorithms across different contrast weightings using synthetic magnetic resonance imaging
A method for sensitivity analysis of automatic contouring algorithms across different contrast weightings using synthetic magnetic resonance imaging Open
View article: Externally validated digital decision support tool for time-to-osteoradionecrosis risk-stratification using right-censored multi-institutional observational cohorts
Externally validated digital decision support tool for time-to-osteoradionecrosis risk-stratification using right-censored multi-institutional observational cohorts Open
View article: Machine learning predicting acute pain and opioid dose in radiation treated oropharyngeal cancer patients
Machine learning predicting acute pain and opioid dose in radiation treated oropharyngeal cancer patients Open
Introduction Acute pain is common among oral cavity/oropharyngeal cancer (OCC/OPC) patients undergoing radiation therapy (RT). This study aimed to predict acute pain severity and opioid doses during RT using machine learning (ML), facilita…
View article: International multispecialty expert physician preoperative identification of extranodal extension in patients with oropharyngeal cancer using computed tomography: Prospective blinded human inter‐observer performance evaluation
International multispecialty expert physician preoperative identification of extranodal extension in patients with oropharyngeal cancer using computed tomography: Prospective blinded human inter‐observer performance evaluation Open
Background Pathologic extranodal extension (pENE) is a crucial prognostic factor in oropharyngeal cancer (OPC), but determining pENE from imaging has high inter‐observer variability. The role of clinician specialty in the accuracy of imagi…
View article: Image-based Mandibular and Maxillary Parcellation and Annotation using Computer Tomography (IMPACT): A Deep Learning-based Clinical Tool for Orodental Dose Estimation and Osteoradionecrosis Assessment
Image-based Mandibular and Maxillary Parcellation and Annotation using Computer Tomography (IMPACT): A Deep Learning-based Clinical Tool for Orodental Dose Estimation and Osteoradionecrosis Assessment Open
Background Accurate delineation of orodental structures on radiotherapy CT images is essential for dosimetric assessments and dental decisions. We propose a deep-learning auto-segmentation framework for individual teeth and mandible/maxill…
View article: Radiographic classification of mandibular osteoradionecrosis: A blinded prospective multi-disciplinary interobserver diagnostic performance study
Radiographic classification of mandibular osteoradionecrosis: A blinded prospective multi-disciplinary interobserver diagnostic performance study Open
Background Osteoradionecrosis of the jaw (ORNJ) is a debilitating complication that affects up to 15% of head and neck cancer patients who undergo radiotherapy. The ASCO/ISOO/MASCC-endorsed ClinRad severity classification system was recent…
View article: A Method for Sensitivity Analysis of Automatic Contouring Algorithms Across Different MRI Contrast Weightings Using SyntheticMR
A Method for Sensitivity Analysis of Automatic Contouring Algorithms Across Different MRI Contrast Weightings Using SyntheticMR Open
Background Currently, a majority of institution-specific automatic MRI-based contouring algorithms are trained, tested, and validated on one contrast weighting (i.e., T2-weighted), however their actual performance within this contrast weig…
View article: Overview of the Head and Neck Tumor Segmentation for Magnetic Resonance Guided Applications (HNTS-MRG) 2024 Challenge
Overview of the Head and Neck Tumor Segmentation for Magnetic Resonance Guided Applications (HNTS-MRG) 2024 Challenge Open
View article: Image-Based Mandibular and Maxillary Parcellation and Annotation Using Computer Tomography (Impact): A Deep Learning-Based Clinical Tool for Orodental Dose Estimation and Osteoradionecrosis Assessment
Image-Based Mandibular and Maxillary Parcellation and Annotation Using Computer Tomography (Impact): A Deep Learning-Based Clinical Tool for Orodental Dose Estimation and Osteoradionecrosis Assessment Open
View article: Image-Based Mandibular and Maxillary Parcellation and Annotation Using Computer Tomography (Impact): A Deep Learning-Based Clinical Tool for Orodental Dose Estimation and Osteoradionecrosis Assessment
Image-Based Mandibular and Maxillary Parcellation and Annotation Using Computer Tomography (Impact): A Deep Learning-Based Clinical Tool for Orodental Dose Estimation and Osteoradionecrosis Assessment Open
View article: Radiographic Classification of Mandibular Osteoradionecrosis: A Blinded Prospective Multi-Disciplinary Interobserver Diagnostic Performance Study
Radiographic Classification of Mandibular Osteoradionecrosis: A Blinded Prospective Multi-Disciplinary Interobserver Diagnostic Performance Study Open
View article: Optimal timing of organs-at-risk-sparing adaptive radiation therapy for head-and-neck cancer under re-planning resource constraints
Optimal timing of organs-at-risk-sparing adaptive radiation therapy for head-and-neck cancer under re-planning resource constraints Open
In limited-resource settings that impeded high-frequency adaptations, ΔNTCP thresholds obtained from an MDP model could derive optimal timing of re-planning to minimize the likelihood of treatment toxicities.
View article: Precision in the Face of Noise -- Lessons from Kahneman, Siboney, and Sunstein for Radiation Oncology
Precision in the Face of Noise -- Lessons from Kahneman, Siboney, and Sunstein for Radiation Oncology Open
In this manuscript, we draw on the insights from Kahneman, Sibony, and Sunsteins influential nonfiction book Noise: A Flaw in Human Judgment to explore the concept of unwanted variability in judgment (i.e., noise). We introduce key terms a…
View article: OAR-Weighted Dice Score: A spatially aware, radiosensitivity aware metric for target structure contour quality assessment
OAR-Weighted Dice Score: A spatially aware, radiosensitivity aware metric for target structure contour quality assessment Open
The Dice Similarity Coefficient (DSC) is the current de facto standard to determine agreement between a reference segmentation and one generated by manual / auto-contouring approaches. This metric is useful for non-spatially important imag…
View article: Artificial intelligence uncertainty quantification in radiotherapy applications − A scoping review
Artificial intelligence uncertainty quantification in radiotherapy applications − A scoping review Open
View article: Computed tomography radiomics-based cross-sectional detection of mandibular osteoradionecrosis in head and neck cancer survivors
Computed tomography radiomics-based cross-sectional detection of mandibular osteoradionecrosis in head and neck cancer survivors Open
Purpose This study aims to identify radiomic features extracted from contrast-enhanced CT scans that differentiate osteoradionecrosis (ORN) from normal mandibular bone in patients with head and neck cancer (HNC) treated with radiotherapy (…
View article: Mandibular dose-volume predicts time-to-osteoradionecrosis in an actuarial normal-tissue complication probability (NTCP) model: External validation of right-censored clinico-dosimetric and competing risk application across international multi-institutional observational cohorts and online graphical user interface clinical support tool assessment
Mandibular dose-volume predicts time-to-osteoradionecrosis in an actuarial normal-tissue complication probability (NTCP) model: External validation of right-censored clinico-dosimetric and competing risk application across international multi-institutional observational cohorts and online graphical user interface clinical support tool assessment Open
Background Existing studies on osteoradionecrosis of the jaw (ORNJ) have primarily used cross-sectional data, assessing risk factors at a single time point. Determining the time-to-event profile of ORNJ has important implications to monito…
View article: Artificial Intelligence and Machine Learning in Cancer Pain: A Systematic Review
Artificial Intelligence and Machine Learning in Cancer Pain: A Systematic Review Open
Implementation of AI/ML tools promises significant advances in the classification, risk stratification, and management decisions for cancer pain. Further research focusing on quality improvement, model calibration, rigorous external clinic…
View article: Exploring quantitative MRI biomarkers of head and neck post-radiation lymphedema and fibrosis: Post hoc analysis of a prospective trial
Exploring quantitative MRI biomarkers of head and neck post-radiation lymphedema and fibrosis: Post hoc analysis of a prospective trial Open
Importance Quantifying Head and Neck Lymphedema and Fibrosis (HN-LEF) is crucial in the investigation and management of this highly prevalent treatment sequelae in head and neck cancer (HNC). The HN-LEF grading system classifies physically…
View article: Application of simultaneous uncertainty quantification and segmentation for oropharyngeal cancer use-case with Bayesian deep learning
Application of simultaneous uncertainty quantification and segmentation for oropharyngeal cancer use-case with Bayesian deep learning Open
View article: Associations Between Radiation Oncologist Demographic Factors and Segmentation Similarity Benchmarks: Insights From a Crowd-Sourced Challenge Using Bayesian Estimation
Associations Between Radiation Oncologist Demographic Factors and Segmentation Similarity Benchmarks: Insights From a Crowd-Sourced Challenge Using Bayesian Estimation Open
PURPOSE The quality of radiotherapy auto-segmentation training data, primarily derived from clinician observers, is of utmost importance. However, the factors influencing the quality of clinician-derived segmentations are poorly understood…
View article: Artificial Intelligence Uncertainty Quantification in Radiotherapy Applications - A Scoping Review
Artificial Intelligence Uncertainty Quantification in Radiotherapy Applications - A Scoping Review Open
Background/purpose The use of artificial intelligence (AI) in radiotherapy (RT) is expanding rapidly. However, there exists a notable lack of clinician trust in AI models, underscoring the need for effective uncertainty quantification (UQ)…
View article: Dataset of weekly intra-treatment diffusion weighted imaging in head and neck cancer patients treated with MR-Linac
Dataset of weekly intra-treatment diffusion weighted imaging in head and neck cancer patients treated with MR-Linac Open
Radiation therapy (RT) is a crucial treatment for head and neck squamous cell carcinoma (HNSCC); however, it can have adverse effects on patients’ long-term function and quality of life. Biomarkers that can predict tumor response to RT are…
View article: Evolving Horizons in Radiation Therapy Auto-Contouring: Distilling Insights, Embracing Data-Centric Frameworks, and Moving Beyond Geometric Quantification
Evolving Horizons in Radiation Therapy Auto-Contouring: Distilling Insights, Embracing Data-Centric Frameworks, and Moving Beyond Geometric Quantification Open