Impact of a contouring atlas on radiographer inter-observer variation in male pelvis radiotherapy.

J Med Imaging Radiat Sci

The Christie NHS Foundation Trust, Manchester, United Kingdom; Division of Cancer Sciences, Faculty of Biology, Medicine and Health, The University of Manchester, Manchester, United Kingdom. Electronic address:

Published: June 2024

Purpose/objective: To determine the impact of a MR-based contouring atlas for male pelvis radiotherapy delineation on inter-observer variation to support radiographer led real-time magnetic resonance image guided adaptive radiotherapy (MRgART).

Material/methods: Eight RTTs contoured 25 MR images in the Monaco treatment planning system (Monaco 5.40.01), from 5 patients. The prostate, seminal vesicles, bladder, and rectum were delineated before and after the introduction of an atlas developed through multi-disciplinary consensus. Inter-observer contour variations (volume), time to contour and observer contouring confidence were determined at both time-points using a 5-point Likert scale. Descriptive statistics were used to analyse both continuous and categorical variables. Dice similarity coefficient (DSC), Dice-Jaccard coefficient (DJC) and Hausdorff distance were used to calculate similarity between observers.

Results: Although variation in volume definition decreased for all structures among all observers post intervention, the change was not statistically significant. DSC and DJC measurements remained consistent following the introduction of the atlas for all observers. The highest similarity was found in the bladder and prostate whilst the lowest was the seminal vesicles. The mean contouring time for all observers was reduced by 50% following the introduction of the atlas (53 to 27 minutes, p=0.01). For all structures across all observers, the mean contouring confidence increased significantly from 2.3 to 3.5 out of 5 (p=0.02).

Conclusion: Although no significant improvements were observed in contour variation amongst observers, the introduction of the consensus-based contouring atlas improved contouring confidence and speed; key factors for a real-time RTT-led MRgART.

Download full-text PDF

Source
http://dx.doi.org/10.1016/j.jmir.2024.03.004DOI Listing

Publication Analysis

Top Keywords

contouring atlas
12
introduction atlas
12
contouring confidence
12
inter-observer variation
8
male pelvis
8
pelvis radiotherapy
8
seminal vesicles
8
structures observers
8
atlas
6
contouring
6

Similar Publications

Radiotherapy Quality Assurance in the SCOPE2 Trial: What Lessons can be Learned for the Next UK Trial in Oesophageal Cancer?

Clin Oncol (R Coll Radiol)

December 2024

South West Wales Cancer Centre, Swansea, UK; National Radiotherapy Trials Quality Assurance (RTTQA) Group, National Institute for Health and Care Research, UK; Swansea University Medical School, Swansea, UK.

Aims: The SCOPE2 trial evaluates radiotherapy (RT) dose escalation for oesophageal cancer. We report findings from the accompanying RT quality assurance (RTQA) programme and identify recommendations for PROTIEUS, the next UK trial in oesophageal RT.

Maetrials And Methods: SCOPE2's RTQA programme consisted of a pre-accrual and on-trial component.

View Article and Find Full Text PDF

Predicting cancer content in tiles of lung squamous cell carcinoma tumours with validation against pathologist labels.

Comput Biol Med

December 2024

Baines Imaging Research Laboratory, London Regional Cancer Program, London Health Sciences Centre, London, Ontario, Canada; School of Biomedical Engineering, Western University, London, Ontario, Canada; Department of Oncology, Schulich School of Medicine and Dentistry, Western University, London, Ontario, Canada; Department of Medical Biophysics, Schulich School of Medicine and Dentistry, Western University, London, Ontario, Canada. Electronic address:

Background: A growing body of research is using deep learning to explore the relationship between treatment biomarkers for lung cancer patients and cancer tissue morphology on digitized whole slide images (WSIs) of tumour resections. However, these WSIs typically contain non-cancer tissue, introducing noise during model training. As digital pathology models typically start with splitting WSIs into tiles, we propose a model that can be used to exclude non-cancer tiles from the WSIs of lung squamous cell carcinoma (SqCC) tumours.

View Article and Find Full Text PDF

Increasing radiotherapy dose to select cardiac structures is associated with cardiac events and premature death. Previous studies have found a dose-response relationship for structures at the base of the heart. We have defined a new cardiac anatomical region at risk for radiotherapy by consensus opinion, based on image-based data-mining studies.

View Article and Find Full Text PDF

Purpose: Accurate target delineation is essential when using intensity modulated radiation therapy for intact cervical cancer. In 2011, the Radiation Therapy Oncology Group published a consensus guideline using magnetic resonance imaging (MRI). The current project expands on the previous atlas by including computed tomography (CT)-based contours, contours with MRI and positron emission tomography (PET) registrations, the addition of common and complex scenarios, and incorporating information on simulation and treatment planning techniques.

View Article and Find Full Text PDF
Article Synopsis
  • The study assessed the accuracy of different segmentation methods in adaptive radiotherapy for head-and-neck cancer, specifically focusing on atlas-based auto-segmentation (ABAS), deformable image registration (DIR), and deep learning auto-segmentation (DLAS).
  • Seventeen patients were examined, using various datasets for the segmentation methods, including an atlas of 30 patients for ABAS and a training set of 143 for DLAS.
  • Results showed that DIR provided the highest accuracy in delineating organs at risk, while mABAS slightly outperformed standard ABAS; no significant accuracy differences were found between ABAS and DLAS, indicating DIR as the best method overall.
View Article and Find Full Text PDF

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!