ArticleJournal of applied clinical medical physics2023
Evaluation of Atlas-based auto-segmentation of liver in MR images for Yttrium-90 selective internal radiation therapy.
Article in Journal of applied clinical medical physics, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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Who cites it
3 citing papers in PubMed.
- Assessing the suitability of automated registration and segmentation for dosimetry calculations in SIRT treatment planning.EJNMMI physics · 2026Article
- Evaluation of Atlas-based auto-segmentation of liver in MR images for Yttrium-90 selective internal radiation therapy.Journal of applied clinical medical physics · 2023Article
- Deep Learning-Based Auto-Segmentation for Liver Yttrium-90 Selective Internal Radiation Therapy.Technology in cancer research & treatmentArticle
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2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
purposeThe aim was to explore the feasibility of applying an atlas-based auto-segmentation tool, MIM Atlas Segment, for liver delineation in MR images in Y-90 selective internal radiation therapy (SIRT). MATERIALS AND
methodsMR images of 41 liver patients treated with resin Y-90 SIRT were included: 20 patients' images were used to create an atlas, and the other 21 patients' images were used for testing. Auto-segmentation of liver in the MR images was performed with MIM Atlas Segment, and various settings for the auto-segmentation (i.e., with and without normalized deformable registration, single atlas-match and multi-atlas match, and multi-atlas match using different finalization methods) were tested. Auto-segmented liver contours were compared with physician manually-delineated contours, using Dice similarity coefficient (DSC) and mean distance to agreement (MDA). Ratio of volume (RV) and ratio of activity (RA) were calculated to further evaluate the auto-segmentation results.
resultsAuto-segmentations with normalized deformable registration generated better contours than those without normalized deformable registration. With normalized deformable registration, 3-atlas match using Majority Vote (MV) method generated better results than single-atlas match and 3-atlas match using STAPLE method, and generated similar results as 5-atlas match using MV method or STAPLE method. The average DSC, MDA, and RV of the contours generated with normalized deformable registration are 0.80-0.83, 0.60-0.67, and 0.91-1.00 cm, respectively. The average RA are 1.00-1.01, which indicate that the activities calculated using the auto-segmented liver contours are close to the accurate activities.
conclusionThe atlas-based auto-segmentation can be applied to generate initial liver contours in MR images for resin Y-90 SIRT, which can be used for activity calculations after physicians review.
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