New ultra-fast algorithm for cochlear implant misalignment detection.
Artificial intelligence
Automatic cochlear image registration
Cochlea
Cochlea implant
Electrode misalignment
Journal
European journal of radiology
ISSN: 1872-7727
Titre abrégé: Eur J Radiol
Pays: Ireland
ID NLM: 8106411
Informations de publication
Date de publication:
Jun 2022
Jun 2022
Historique:
received:
01
10
2021
revised:
07
03
2022
accepted:
30
03
2022
pubmed:
8
4
2022
medline:
18
5
2022
entrez:
7
4
2022
Statut:
ppublish
Résumé
Postoperative imaging following cochlear implant (CI) placement is currently the only means of diagnosing proper electrode position. Manual multiplanar reconstruction (MPR) analysis of CT and CBCT is time-consuming and requires extensive training. This study aims to evaluate the rate of CI misalignment and to determine the amount of time necessary to reach a diagnosis of correct versus incorrect CI placement for readers of different experience levels, using a novel algorithm for image analysis (ACIR) compared to MPR analysis. The retrospective single centre study included 333 patients with cochlear implant surgery between May 2002 and May 2021. Postoperative CT and CBCT images were evaluated in three subgroups and the time to diagnosis was documented. Group 1: image evaluation using conventional MPR analysis; group 2: image evaluation by an experienced neuroradiologist via a novel ultra-fast algorithm; group 3: image evaluation by a young specialist via novel ultra-fast algorithm. T-test and Pearson's chi-squared test were used for inter-group comparisons. 333 patients (63.3 ± 15.9 years; 188 men) with 335 CIs were evaluated. The rate of CI misalignment diagnosed from 3D imaging was 14.3% (n = 48). MPR analysis required 255.7 ± 70.4 s per temporal bone, whereas Slicer plugin reduced analysis time to 83.3 ± 7.7 s (p < 0.001) for the experienced reader and 89.6 ± 8.7 s for the young specialist (p < 0.001). 3D postoperative imaging reveals high incidences of CI misalignment. Application of a novel ultra-fast algorithm significantly reduces the time for diagnosis compared to MPR analysis for readers of varying experience levels.
Identifiants
pubmed: 35390602
pii: S0720-048X(22)00133-4
doi: 10.1016/j.ejrad.2022.110283
pii:
doi:
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
110283Informations de copyright
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