Insert INTO PMID_Summary(PMID,summaryText,IPAddress,dtCreated) VALUES (37089906, '** Intra-fraction motion management is crucial for the accuracy of Stereotactic Ablative Radiotherapy (SABR), and this study evaluated the effectiveness of automatic tumor segmentation in MR-guided radiotherapy compared to manual delineation. ** Twenty patients with either thoracic or abdominal tumors were analyzed using a combination of experienced observers\' manual delineations and four different algorithms for automatic tumor contouring, assessing accuracy through various geometrical analysis metrics. ** Results showed that the automatic segmentation algorithms achieved excellent agreement with manual contours, demonstrating high reliability and accuracy, thereby supporting the use of DIR-based auto-contouring in MRgRT for precise treatment delivery. **','18.223.209.114',now()) Accuracy of deformable image registration-based intra-fraction motion management in Magnetic Resonance-guided radiotherapy. | LitMetric

AI Article Synopsis

  • Intra-fraction motion management is crucial for the accuracy of Stereotactic Ablative Radiotherapy (SABR), and this study evaluated the effectiveness of automatic tumor segmentation in MR-guided radiotherapy compared to manual delineation.
  • Twenty patients with either thoracic or abdominal tumors were analyzed using a combination of experienced observers' manual delineations and four different algorithms for automatic tumor contouring, assessing accuracy through various geometrical analysis metrics.
  • Results showed that the automatic segmentation algorithms achieved excellent agreement with manual contours, demonstrating high reliability and accuracy, thereby supporting the use of DIR-based auto-contouring in MRgRT for precise treatment delivery.

Article Abstract

Background And Purpose: Intra-fraction motion management is key in Stereotactic Ablative Radiotherapy (SABR) gated delivery. This study assessed the accuracy of automatic tumor segmentation in the delivery of MR-guided radiotherapy (MRgRT) by comparing it to manual delineations performed by experienced observers.

Materials And Methods: Twenty patients previously treated with MR-guided SABR for thoracic and abdominal tumors were included. Five observers with at least two years of experience in MRgRT manually delineated the gross tumor volume (GTV) for 20 patients on 240 frames of a cine MRI on a sagittal plane. Deformable Image Registration (DIR) based GTV contours were propagated using four different algorithms from a reference frame to subsequent frames.Geometrical analysis based on the Dice Similarity Coefficient (DSC), centroid distance and Hausdorff Distance (HDD) were performed to assess the inter-observer variability and the accuracy of automatic segmentation. A Confidence Value (CV) metric for the reliability of the tumor auto-contouring was also calculated.

Results: Inter-observer delineation variability resulted in mean DSC of 0.89, HDD of 5.8 mm and centroid distance of 1.7 mm. Tumor auto-contouring by the four DIR algorithms resulted in an excellent agreement with the manual delineations by the experienced observers. Mean DSC for each algorithm across all patients was greater than 0.90, whereas the HDD and centroid distances were below 4.0 mm and 1.5 mm, respectively. The CV showed a strong correlation with the DSC.

Conclusions: DIR-based auto-contouring in MRgRT exhibited a high level of agreement with the manual contouring performed by experts, allowing accurate gated delivery.

Download full-text PDF

Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC10113900PMC
http://dx.doi.org/10.1016/j.phro.2023.100437DOI Listing

Publication Analysis

Top Keywords

deformable image
8
intra-fraction motion
8
motion management
8
gated delivery
8
accuracy automatic
8
manual delineations
8
centroid distance
8
tumor auto-contouring
8
agreement manual
8
accuracy deformable
4

Similar Publications

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!