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Automated Calculation of Cochlear Implant Electrode Insertion Parameters in Clinical Cone-Beam CT.
Andersen, Steven Arild Wuyts; Keith, Jason P; Hittle, Brad; Riggs, William J; Adunka, Oliver; Wiet, Gregory J; Powell, Kimerly A.
Afiliação
  • Andersen SAW; Department of Otolaryngology, Nationwide Children's Hospital, Columbus, Ohio.
  • Keith JP; Department of Otolaryngology-Head and Neck Surgery, The Ohio State University, Columbus, Ohio.
  • Hittle B; Department of Otorhinolaryngology-Head & Neck Surgery, Rigshospitalet, Copenhagen, Denmark.
  • Riggs WJ; Department of Biomedical Informatics, The Ohio State University, Columbus, Ohio.
  • Adunka O; Department of Biomedical Informatics, The Ohio State University, Columbus, Ohio.
  • Wiet GJ; Department of Otolaryngology-Head and Neck Surgery, The Ohio State University, Columbus, Ohio.
  • Powell KA; Department of Otolaryngology, Nationwide Children's Hospital, Columbus, Ohio.
Otol Neurotol ; 43(2): 199-205, 2022 02 01.
Article em En | MEDLINE | ID: mdl-34789695
HYPOTHESIS: Automated processing of postoperative clinical cone-beam CT (CBCT) of cochlear implant (CI) patients can be used to accurately determine electrode contacts and integrated with an atlas-based mapping of cochlear microstructures to calculate modiolar distance, angular insertion distance, and scalar location of electrode contacts. BACKGROUND: Hearing outcomes after CI surgery are dependent on electrode placement. CBCT is increasingly used for in-office temporal bone imaging and might be routinely used for pre- and post-surgical evaluation. METHODS: Thirty-six matched pairs of pre- and postimplant CBCT scans were obtained. These were registered with an atlas to model cochlear microstructures in each dataset. Electrode contact center points were automatically determined using thresholding and electrode insertion parameters were calculated. Automated localization and calculation were compared with manual segmentation of contact center points as well as manufacturer specifications. RESULTS: Automated electrode contact detection aligned with manufacturer specifications of spacing and our algorithms worked for both distantly- and closely spaced arrays. The average difference between the manual and the automated selection was 0.15 mm, corresponding to a 1.875 voxel difference in each plane at the scan resolution. For each case, we determined modiolar distance, angular insertion depth, and scalar location. These calculations also resulted in similar insertion values using manual and automated contact points as well as aligning with electrode properties. CONCLUSION: Automated processing of implanted high-resolution CBCT images can provide the clinician with key information on electrode placement. This is one step toward routine use of clinical CBCT after CI surgery to inform and guide postoperative treatment.
Assuntos

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Implantes Cocleares / Implante Coclear Tipo de estudo: Guideline Limite: Humans Idioma: En Ano de publicação: 2022 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Implantes Cocleares / Implante Coclear Tipo de estudo: Guideline Limite: Humans Idioma: En Ano de publicação: 2022 Tipo de documento: Article