Abstract
BACKGROUND AND PURPOSE: Recurrent middle ear cholesteatomas are commonly preoperatively assessed using MR imaging (non-EPI-DWI) and CT. Both modalities are used with the aim of distinguishing scar tissue from cholesteatoma and determining the extent of bone erosions. Inflammation and scar tissue associated with the lesions might hamper a proper delineation of the corresponding extensions on CT images. Using surgical findings as the criterion standard, we assessed the recurrent middle ear cholesteatoma extent using either uncoregistered or fused CT–MR imaging datasets and determined the corresponding accuracy and repeatability.
MATERIALS AND METHODS: Twenty consecutive patients with suspected recurrent middle ear cholesteatoma and preoperative CT–MR imaging datasets were prospectively included. A double-blind assessment and coregistration of the recurrent middle ear cholesteatoma extent and manual delineation of 18 presumed recurrent middle ear cholesteatomas were performed by 2 radiologists and compared with the criterion standard. “Reliability score” was defined to qualify radiologists' confidence. For each volume, segmentation repeatability was assessed on the basis of intraclass correlation coefficient and overlap indices.
RESULTS: For the whole set of patients, recurrent middle ear cholesteatoma was further supported by surgical results. Two lesions were excluded from the analysis, given that MR imaging did not show a restricted diffusion. Lesions were accurately localized using the fused datasets, whereas significantly fewer lesions (85%) were correctly localized using uncoregistered images. Reliability scores were larger for fused datasets. Segmentation repeatability showed an almost perfect intraclass correlation coefficient regarding volumes, while overlaps were significantly lower in uncoregistered (52%) compared with fused (60%, P < .001) datasets.
CONCLUSIONS: The use of coregistered CT–MR images significantly improved the assessment of recurrent middle ear cholesteatoma with a greater accuracy and better reliability and repeatability.
ABBREVIATIONS:
- FD
- fused dataset
- ICC
- intraclass correlation coefficient
- JI
- Jaccard index
- MEC
- middle ear cholesteatoma
- rMEC
- recurrent MEC
- ROC
- receiver operating characteristic
- UD
- uncoregistered dataset
- VIBE
- volumetric interpolated brain examination
- © 2019 by American Journal of Neuroradiology