AI Medical Compendium Journal:
Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology

Showing 1 to 10 of 120 articles

Deep learning-based auto-contouring of organs/structures-at-risk for pediatric upper abdominal radiotherapy.

Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology May 4, 2025
PURPOSES: This study aimed to develop a computed tomography (CT)-based multi-organ segmentation model for delineating organs-at-risk (OARs) in pediatric upper abdominal tumors and evaluate its robustness across multiple datasets.
View on PubMed DOI

Radiation oncology patients' perceptions of artificial intelligence and machine learning in cancer care: A multi-centre cross-sectional study.

Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology Apr 13, 2025
AIM: The use of artificial intelligence (AI) and machine learning (ML) is increasingly widespread in radiation oncology. However, patient engagement to date has been poor. Respect for persons in the healthcare setting and the principle of informed co...
Aged Adult Cross-Sectional Studies Artificial Intelligence Machine Learning Female Humans Surveys and Questionnaires Male Australia Middle Aged Radiation Oncology Neoplasms
View on PubMed DOI

Evaluating the prognostic significance of artificial intelligence-delineated gross tumor volume and prostate volume measurements for prostate radiotherapy.

Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology Mar 22, 2025
BACKGROUND AND PURPOSE: Artificial intelligence (AI) may extract prognostic information from MRI for localized prostate cancer. We evaluate whether AI-derived prostate and gross tumor volume (GTV) are associated with toxicity and oncologic outcomes a...
Brachytherapy Prostatic Neoplasms Radiotherapy Planning, Computer-Assisted Tumor Burden Retrospective Studies Aged Aged, 80 and over Male Middle Aged Magnetic Resonance Imaging Humans Artificial Intelligence Prognosis
View on PubMed DOI

PET and CT based DenseNet outperforms advanced deep learning models for outcome prediction of oropharyngeal cancer.

Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology Mar 19, 2025
BACKGROUND: In the HECKTOR 2022 challenge set [1], several state-of-the-art (SOTA, achieving best performance) deep learning models were introduced for predicting recurrence-free period (RFP) in head and neck cancer patients using PET and CT images.
Humans Tomography, X-Ray Computed Middle Aged Deep Learning Convolutional Neural Networks Female Aged Male Positron Emission Tomography Computed Tomography Datasets as Topic Oropharyngeal Neoplasms
View on PubMed DOI

Optimizing fractionation schedules for de-escalation radiotherapy in head and neck cancers using deep reinforcement learning.

Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology Mar 14, 2025
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 suffer significant toxicities from standard che...
Head and Neck Neoplasms Dose Fractionation, Radiation Humans Support Vector Machine Reinforcement Machine Learning Deep Learning Radiotherapy Planning, Computer-Assisted Squamous Cell Carcinoma of Head and Neck
View on PubMed DOI

Incorporating indirect MRI information in a CT-based deep learning model for prostate auto-segmentation.

Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology Feb 21, 2025
BACKGROUND AND PURPOSE: Computed tomography (CT) imaging poses challenges for delineation of soft tissue structures for prostate cancer external beam radiotherapy. Guidelines require the input of magnetic resonance imaging (MRI) information. We devel...
Humans Prostatic Neoplasms Tomography, X-Ray Computed Male Prostate Deep Learning Radiotherapy Planning, Computer-Assisted Magnetic Resonance Imaging
View on PubMed DOI

Assessing multiple MRI sequences in deep learning-based synthetic CT generation for MR-only radiation therapy of head and neck cancers.

Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology Feb 8, 2025
PURPOSE: This study investigated the effect of multiple magnetic resonance (MR) sequences on the quality of deep-learning-based synthetic computed tomography (sCT) generation in the head and neck region.
Humans Tomography, X-Ray Computed Female Aged Male Radiotherapy Planning, Computer-Assisted Middle Aged Deep Learning Head and Neck Neoplasms Magnetic Resonance Imaging
View on PubMed DOI

Personalized auto-segmentation for magnetic resonance imaging-guided adaptive radiotherapy of large brain metastases.

Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology Feb 4, 2025
BACKGROUND AND PURPOSE: Magnetic resonance-guided adaptive radiotherapy (MRgART) may improve the efficacy of large brain metastases (BMs)(≥2 cm), whereas the workflow requires optimized. This study develops a two-stage, personalized deep learning aut...
Magnetic Resonance Imaging Female Radiotherapy Planning, Computer-Assisted Aged Humans Radiotherapy, Image-Guided Male Brain Neoplasms Prospective Studies Middle Aged Deep Learning
View on PubMed DOI

Machine learning model for predicting DIBH non-eligibility in left-sided breast cancer radiotherapy: Development, validation and clinical impact analysis.

Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology Jan 31, 2025
OBJECTIVE: Multi-day assessments accurately identify patients with left-sided breast cancer who are ineligible for irradiation in Deep Inspiration Breath Hold (DIBH) and minimise on-couch treatment time in those who are eligible. The challenge of imp...
Breast Neoplasms Middle Aged Unilateral Breast Neoplasms Breath Holding Prospective Studies Humans Female Machine Learning Aged Algorithms
View on PubMed DOI

Multiscale deep learning radiomics for predicting recurrence-free survival in pancreatic cancer: A multicenter study.

Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology Jan 31, 2025
PURPOSE: This multicenter study aimed to develop and validate a multiscale deep learning radiomics nomogram for predicting recurrence-free survival (RFS) in patients with pancreatic ductal adenocarcinoma (PDAC).
Middle Aged Disease-Free Survival Aged Deep Learning Humans Radiomics Pancreatic Neoplasms Nomograms Female Male Neoplasm Recurrence, Local Carcinoma, Pancreatic Ductal
View on PubMed DOI
Popular Topics
Popular Journals