ArticleJournal of otolaryngology - head & neck surgery = Le Journal d'oto-rhino-laryngologie et de chirurgie cervico-faciale
Deep Learning-Assisted Prediction of Hearing Outcomes After Anatomically Successful Type I Tympanoplasty.
Article in Journal of otolaryngology - head & neck surgery = Le Journal d'oto-rhino-laryngologie et de chirurgie cervico-faciale. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
importanceType I tympanoplasty restores hearing in patients with simple tympanic membrane (TM) perforations, but reliable tools to predict postoperative outcomes remain limited.
objectiveTo develop and evaluate a deep learning-assisted model integrating automated TM image features and clinical data to predict postoperative air-bone gap (ABG) closure and residual ABG.
designDiagnostic and prognostic model development and validation study.
settingA tertiary referral medical center in northern Taiwan.
participantsA total of 1285 otoendoscopic images were collected, of which 1014 intact and 150 perforated TMs were used to train the mask region-based convolutional neural network (Mask R-CNN) segmentation model. Prognostic analysis included 121 patients with simple perforations and anatomically successful type I tympanoplasty (complete TM closure), with 83 preoperative images for training and 38 for independent internal testing. Demographic, clinical, and audiometric data were recorded.Intervention or Exposures:Automated image features extracted by Mask R-CNN, combined with clinical and audiometric variables, were used to develop prognostic models.
main outcome measuresSegmentation performance was evaluated using class pixel accuracy (CPA). Prognostic model performance was assessed using the coefficient of determination (R
resultsThe segmentation model achieved a CPA of 0.884 for TM detection and 0.901 for perforation detection. The prognostic models yielded R
conclusionsDeep learning-assisted analysis of TM images showed modest predictive ability for hearing outcomes after anatomically successful type I tympanoplasty. RELEVANCE: This image-based approach may modestly assist preoperative counseling in otologic practice.
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