ArticleMagma (New York, N.Y.)2017
What are the true volumes of SEGA tumors? Reliability of planimetric and popular semi-automated image segmentation methods.
Article in Magma (New York, N.Y.), 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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Who cites it
6 citing papers in PubMed.
- Review
- Subependymal Giant Cell Astrocytomas in Tuberous Sclerosis Complex-Current Views on Their Pathogenesis and Management.Journal of clinical medicine · 2023Review
- Three-dimensional printing and 3D slicer powerful tools in understanding and treating neurosurgical diseases.Frontiers in surgery · 2022Review
- Growth Curves of Subependymal Giant Cell Tumors in Tuberous Sclerosis Complex.AJNR. American journal of neuroradiology · 2021Article
- Congenital subpendymal giant cell astrocytoma in children with tuberous sclerosis complex: growth patterns and neurological outcome.Pediatric research · 2021Article
- Maintenance Therapy With Everolimus for Subependymal Giant Cell Astrocytoma in Patients With Tuberous Sclerosis - Final Results From the EMINENTS Study.Frontiers in neurology · 2021Article
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Authors and funding
8 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectiveTo evaluate the reliability of the standard planimetric methodology of volumetric analysis and three different open-source semi-automated approaches of brain tumor segmentation. MATERIALS AND
methodsThe volumes of subependymal giant cell astrocytomas (SEGA) examined by 30 MRI studies of 10 patients from a previous everolimus-related trial (EMINENTS study) were estimated using four methods: planimetric method (modified MacDonald ellipsoid method), ITK-Snap (pixel clustering, geodesic active contours, region competition methods), 3D Slicer (level-set thresholding), and NIRFast (k-means clustering, Markov random fields). The methods were compared, and a trial simulation was performed to determine how the choice of approach could influence the final decision about progression or response.
resultsIntraclass correlation coefficient was high (0.95; 95% CI 0.91-0.98). The planimetric method always overestimated the size of the tumor, while virtually no mean difference was found between ITK-Snap and 3D Slicer (P = 0.99). NIRFast underestimated the volume and presented a proportional bias. During the trial simulation, a moderate level of agreement between all the methods (kappa 0.57-0.71, P < 0.002) was noted.
conclusionSemi-automated segmentation can ease oncological follow-up but the moderate level of agreement between segmentation methods suggests that the reference standard volumetric method for SEGA tumors should be revised and chosen carefully, as the selection of volumetry tool may influence the conclusion about tumor progression or response.
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