ArticleJournal of applied clinical medical physics2022
Comparison of Eclipse Smart Segmentation and MIM Atlas Segment for liver delineation for yttrium-90 selective internal radiation therapy.
Article in Journal of applied clinical medical physics, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
10 citing papers in PubMed.
- Impact of deep learning on CT-based organ-at-risk delineation for flank irradiation in paediatric renal tumours: a SIOP-RTSG radiotherapy committee study.Clinical and translational radiation oncology · 2026Article
- Dosimetric study on radioembolization with 166Ho poly L-lactic acid microspheres: dead time effects on prediction power.EJNMMI physics · 2025Article
- Comparison of commercial atlas-based automatic segmentation software for prostate radiotherapy treatment planning.Physical and engineering sciences in medicine · 2024Article
- Oncologic Applications of Artificial Intelligence and Deep Learning Methods in CT Spine Imaging-A Systematic Review.Cancers · 2024Review
- Evaluation of manual and automated approaches for segmentation and extraction of quantitative indices from [Biomedical physics & engineering express · 2024Article
- A deep learning segmentation method to assess dose to organs at risk during breast radiotherapy.Physics and imaging in radiation oncology · 2023Article
- 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
- Prospective deployment of an automated implementation solution for artificial intelligence translation to clinical radiation oncology.Frontiers in oncology · 2023Article
- Comparison of Eclipse Smart Segmentation and MIM Atlas Segment for liver delineation for yttrium-90 selective internal radiation therapy.Journal of applied clinical medical physics · 2022Article
- Deep Learning-Based Auto-Segmentation for Liver Yttrium-90 Selective Internal Radiation Therapy.Technology in cancer research & treatmentArticle
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
purposeThe aim was to compare Smart Segmentation of Eclipse treatment planning system and Atlas Segment of MIM software for liver delineation for resin yttrium-90 (Y-90) procedures. MATERIALS AND
methodsCT images of 20 patients treated with resin Y-90 selective internal radiation therapy (SIRT) were tested. Liver contours generated with Smart Segmentation and Atlas Segment were compared with physician manually delineated contours. Dice similarity coefficient (DSC), mean distance to agreement (MDA), and ratio of volume (RV) were calculated. The contours were evaluated with activity calculations and ratio of activity (RA) was calculated.
resultsMean DSCs were 0.77 and 0.83, MDAs were 0.88 and 0.71 cm, mean RVs were 0.95 and 1.02, and mean RAs were 1.00 and 1.00, for Eclipse and MIM results, respectively.
conclusionMIM outperformed Eclipse in both DSC and MDA, whereas the differences in liver volumes and calculated activities were statistically insignificant between the Eclipse and MIM results. Both auto-segmentation tools can be used to generate initial liver contours for resin Y-90 SIRT, which need to be reviewed and edited by physicians.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.