AIMC Topic: Radiotherapy Dosage

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Aleatoric and epistemic uncertainty extraction of patient-specific deep learning-based dose predictions in LDR prostate brachytherapy.

Physics in medicine and biology Apr 9, 2024
In brachytherapy, deep learning (DL) algorithms have shown the capability of predicting 3D dose volumes. The reliability and accuracy of such methodologies remain under scrutiny for prospective clinical applications. This study aims to establish fast...
Humans Prospective Studies Reproducibility of Results Brachytherapy Radiotherapy Dosage Monte Carlo Method Uncertainty Male Deep Learning Prostate Radiotherapy Planning, Computer-Assisted
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Deep-Learning for Rapid Estimation of the Out-of-Field Dose in External Beam Photon Radiation Therapy - A Proof of Concept.

International journal of radiation oncology, biology, physics Mar 28, 2024
PURPOSE: The dose deposited outside of the treatment field during external photon beam radiation therapy treatment, also known as out-of-field dose, is the subject of extensive study as it may be associated with a higher risk of developing a second c...
Photons Humans Deep Learning Child Proof of Concept Study Radiotherapy Planning, Computer-Assisted Radiotherapy Dosage Monte Carlo Method
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Multi-center Dose Prediction Using Attention-aware Deep learning Algorithm Based on Transformers for Cervical Cancer Radiotherapy.

Clinical oncology (Royal College of Radiologists (Great Britain)) Mar 26, 2024
AIMS: Accurate dose delivery is crucial for cervical cancer volumetric modulated arc therapy (VMAT). We aimed to develop a robust deep-learning (DL) algorithm for fast and accurate dose prediction of cervical cancer VMAT in multicenter datasets and t...
Endometrial Neoplasms Humans Algorithms Adult Radiotherapy Planning, Computer-Assisted Female Uterine Cervical Neoplasms Radiotherapy Dosage Aged Middle Aged Radiotherapy, Intensity-Modulated Deep Learning
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Prospective validation of a machine learning model for applicator and hybrid interstitial needle selection in high-dose-rate (HDR) cervical brachytherapy.

Brachytherapy Mar 26, 2024
PURPOSE: To Demonstrate the clinical validation of a machine learning (ML) model for applicator and interstitial needle prediction in gynecologic brachytherapy through a prospective clinical study in a single institution.
Female Aged Uterine Cervical Neoplasms Middle Aged Organs at Risk Radiotherapy Planning, Computer-Assisted Needles Brachytherapy Radiotherapy Dosage Humans Machine Learning Prospective Studies
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Enhancing the prediction of symptomatic radiation pneumonitis for locally advanced non-small-cell lung cancer by combining 3D deep learning-derived imaging features with dose-volume metrics: a two-center study.

Strahlentherapie und Onkologie : Organ der Deutschen Rontgengesellschaft ... [et al] Mar 18, 2024
OBJECTIVE: This study aims to examine the ability of deep learning (DL)-derived imaging features for the prediction of radiation pneumonitis (RP) in locally advanced non-small-cell lung cancer (LA-NSCLC) patients.
Radiation Pneumonitis Middle Aged Deep Learning Cohort Studies Imaging, Three-Dimensional Lung Neoplasms Carcinoma, Non-Small-Cell Lung Radiotherapy Planning, Computer-Assisted Radiotherapy Dosage Female Aged Adult Humans Male Tomography, X-Ray Computed
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High-dose-rate Brachytherapy Monotherapy in Patients With Localised Prostate Cancer: Dose Modelling and Optimisation Using Computer Algorithms.

Clinical oncology (Royal College of Radiologists (Great Britain)) Mar 14, 2024
AIMS: Interstitial high-dose-rate brachytherapy (HDR-BT) is an effective therapy modality for patients with localized prostate carcinoma. The objectives of the study were to optimise the therapy regime variables using two models: response surface met...
Humans Neural Networks, Computer Algorithms Male Prostatic Neoplasms Brachytherapy Radiotherapy Dosage
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Cluster-Based Toxicity Estimation of Osteoradionecrosis Via Unsupervised Machine Learning: Moving Beyond Single Dose-Parameter Normal Tissue Complication Probability by Using Whole Dose-Volume Histograms for Cohort Risk Stratification.

International journal of radiation oncology, biology, physics Mar 10, 2024
PURPOSE: Given the limitations of extant models for normal tissue complication probability estimation for osteoradionecrosis (ORN) of the mandible, the purpose of this study was to enrich statistical inference by exploiting structural properties of d...
Mandibular Diseases Probability Radiotherapy Dosage Osteoradionecrosis Middle Aged Risk Assessment Mandible Head and Neck Neoplasms Support Vector Machine Cluster Analysis Unsupervised Machine Learning Organs at Risk Female Aged Adult Male Humans Retrospective Studies
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"sCT-Feasibility" - a feasibility study for deep learning-based MRI-only brain radiotherapy.

Radiation oncology (London, England) Mar 8, 2024
BACKGROUND: Radiotherapy (RT) is an important treatment modality for patients with brain malignancies. Traditionally, computed tomography (CT) images are used for RT treatment planning whereas magnetic resonance imaging (MRI) images are used for tumo...
Humans Brain Retrospective Studies Radiotherapy Planning, Computer-Assisted Radiotherapy Dosage Radiotherapy, Intensity-Modulated Brain Neoplasms Deep Learning Magnetic Resonance Imaging Feasibility Studies
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Assessment of lymph node area coverage with total marrow irradiation and implementation of total marrow and lymphoid irradiation using automated deep learning-based segmentation.

PloS one Mar 8, 2024
BACKGROUND: Total marrow irradiation (TMI) and total marrow and lymphoid irradiation (TMLI) have the advantages. However, delineating target lesions according to TMI and TMLI plans is labor-intensive and time-consuming. In addition, although the deli...
Bone Marrow Humans Radiotherapy Dosage Deep Learning Radiotherapy, Intensity-Modulated Lymph Nodes Lymphatic Irradiation
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Evaluation of the performance of both machine learning models using PET and CT radiomics for predicting recurrence following lung stereotactic body radiation therapy: A single-institutional study.

Journal of applied clinical medical physics Mar 4, 2024
PURPOSE: Predicting recurrence following stereotactic body radiotherapy (SBRT) for non-small cell lung cancer provides important information for the feasibility of the individualized radiotherapy and allows to select the appropriate treatment strateg...
Humans Radiosurgery Radiotherapy Planning, Computer-Assisted Radiotherapy Dosage Radiotherapy, Intensity-Modulated Radiomics Male Middle Aged Image Processing, Computer-Assisted Lung Neoplasms Carcinoma, Non-Small-Cell Lung Retrospective Studies Positron Emission Tomography Computed Tomography Female Neoplasm Recurrence, Local Aged Aged, 80 and over Machine Learning Algorithms Prognosis
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