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Otol Neurotol ; 45(3): e137-e141, 2024 Mar 01.
Artículo en Inglés | MEDLINE | ID: mdl-38361290

RESUMEN

PURPOSE: Manual segmentation of anatomical structures is the accepted "gold standard" for labeling structures in clinical images. However, the variability in manual segmentation of temporal bone structures in CBCT images of the temporal bone has not been systematically evaluated using multiple reviewers. Therefore, we evaluated the intravariability and intervariability of manual segmentation of inner ear structures in CBCT images of the temporal bone. METHODS: Preoperative CBCTs scans of the inner ear were obtained from 10 patients who had undergone cochlear implant surgery. The cochlea, facial nerve, chorda tympani, mid-modiolar (MM) axis, and round window (RW) were manually segmented by five reviewers in two separate sessions that were at least 1 month apart. Interreviewer and intrareviewer variabilities were assessed using the Dice coefficient (DICE), volume similarity, mean Hausdorff Distance metrics, and visual review. RESULTS: Manual segmentation of the cochlea was the most consistent within and across reviewers with a mean DICE of 0.91 (SD = 0.02) and 0.89 (SD = 0.01) respectively, followed by the facial nerve with a mean DICE of 0.83 (SD = 0.02) and 0.80 (SD = 0.03), respectively. The chorda tympani had the greatest amount of reviewer variability due to its thin size, and the location of the centroid of the RW and the MM axis were also quite variable between and within reviewers. CONCLUSIONS: We observed significant variability in manual segmentation of some of the temporal bone structures across reviewers. This variability needs to be considered when interpreting the results in studies using one manual reviewer.


Asunto(s)
Implantación Coclear , Oído Interno , Humanos , Cóclea/diagnóstico por imagen , Cóclea/cirugía , Tomografía Computarizada de Haz Cónico/métodos , Oído Interno/cirugía , Implantación Coclear/métodos , Hueso Temporal/diagnóstico por imagen , Hueso Temporal/cirugía , Procesamiento de Imagen Asistido por Computador/métodos
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