A Comparison of Repeatability and Usability of Semi-Automated Volume Segmentation Tools for Measurement of Vestibular Schwannomas. Issue 6 (July 2018)

• Record Type: Journal Article
• Authors: MacKeith, Samuel A. C.; Das, Tilak; Graves, Martin; Patterson, Andrew; Donnelly, Neil; Mannion, Richard; Axon, Patrick; Tysome, James
• Is Part Of: Otology & neurotology. Volume 39:Issue 6(2018)
• Publication Date: 2018-07
• Subjects: Acoustic neuroma -- Automated -- Measurement -- Repeatability -- Usability -- Vestibular schwannoma -- Volume segmentation -- Volumetric; Otology -- Periodicals; Ear -- Diseases -- Periodicals; Skull base -- Surgery -- Periodicals; 617.8005
• DOI: 10.1097/MAO.0000000000001796
• Languages: English
• ISSNs: 1531-7129

Abstract

Abstract : Objective: Semi-automated volume segmentation tools (SAVST) offer a less time consuming technique compared with manual volume segmentation method. No data exists to suggest which of the available applications are optimal for use with vestibular schwannomas (VS). This study aims to compare repeatability and usability of three different SAVST for measurement of VS. Study Design: Experimental comparison of three SAVST. Setting: Tertiary skull base unit. Patients: Twenty-four patients with a unilateral VS imaged with T1-weighted Gadolinium enhanced MRI. Intervention: Repeated measurements made to determine intra and inter-observer agreement. This was repeated using three different SAVST. Main Outcome Measures: 1) Intra- and inter-observer intraclass correlation coefficients (ICC), repeatability coefficients (RC), and relative smallest detectable differences (%SDD). 2) Usability as determined by the mean number of steps and time required per tumor measurement and the proportion of cases where manual editing was required. Results: Intra-observer ICCs were significantly better for SliceOmatic and OleaSphere than AW VolumeShare (0.998 versus 0.994, p < 0.05). Inter-observer ICCs were also better for SliceOmatic (0.994) and OleaSphere (0.989) compared with AW VolumeShare (0.976), however, this was only significant for SliceOmatic ( p = 0.012). SliceOmatic had a poorer usability profile requiring more manual editing, time, and individual steps per measurement but its "watershed segmentation" algorithm was better at measuring cystic or heterogenous tumors. Conclusions: This is the first study to compare three SAVST for measurement of VS. While SliceOmatic had the highest repeatability, Olea Sphere combined comparable repeatability with improved usability and a greater degree of automation and was, therefore, deemed optimal for use in routine clinical practice.