| Literature DB >> 30210975 |
Karl Lindberg1,2, Angelica Kouti2, Doerthe Ziegelitz2, Tobias Hallén1, Thomas Skoglund1,3, Dan Farahmand1,3.
Abstract
Background The assessment of pituitary tumor (PT) volume is important in the treatment and follow-up of patients with PT. Previously, PT volume estimation has been performed by conventional geometric equations (CGE) such as abc/2 (simplified ellipsoid volume equation) and 4πr 3 /3 (sphere), both presuming a symmetric tumor shape, which occurs uncommonly in patients with PT. In contrast, three-dimensional (3D) voxel-based software segmentation takes the irregular and asymmetric shapes that PTs often possess into account and might be a more accurate method for PT volume segmentation. The purpose of this study is twofold. (1) To compare 3D segmentation with CGE for PT volume estimation. (2) To assess inter-rater reliability in 3D segmentation of PTs. Methods Nineteen high-resolution (1mm slice thickness) T1-weighted MRI examinations of patients with PT were independently analyzed and manually segmented, using the software ITK-SNAP, by two certified neuroradiologists. Concurrently, the volumes of the PTs were estimated with abc/2 and 4πr 3 /3 by a clinician, and the results were compared with the corresponding segmented volumes. Results There was a significant decrease in PT volume attained from the segmentations compared with the calculations made with abc/2 ( p < 0.001, mean volume 18% higher than segmentation) and 4πr 3 /3 ( p < 0.001, mean volume 28% higher than segmentation). The intraclass correlation coefficient (ICC) for the two sets of segmented PTs was 0.99. Conclusion CGE ( abc/2 and 4πr 3 /3 ) significantly overestimates PT volume compared with 3D volumetric segmentation. The inter-rater agreement on manual 3D volumetric software segmentation is excellent.Entities:
Keywords: abc/2; pituitary tumor volume; segmentation; volumetric analysis
Year: 2018 PMID: 30210975 PMCID: PMC6133660 DOI: 10.1055/s-0037-1618577
Source DB: PubMed Journal: J Neurol Surg B Skull Base ISSN: 2193-634X