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Construction of an MRI-based decision tree to differentiate autoimmune and autoinflammatory inner ear disease from chronic otitis media with sensorineural hearing loss
- Title
- Construction of an MRI-based decision tree to differentiate autoimmune and autoinflammatory inner ear disease from chronic otitis media with sensorineural hearing loss
- Authors
- Lee, Boeun; Bae, Yun Jung; Choi, Byung Yoon; Kim, Young Seok; Han, Jin Hee; Kim, Hyojin; Choi, Byung Se; Kim, Jae Hyoung
- Ewha Authors
- 이보은
- SCOPUS Author ID
- 이보은
- Issue Date
- 2021
- Journal Title
- SCIENTIFIC REPORTS
- ISSN
- 2045-2322
- Citation
- SCIENTIFIC REPORTS vol. 11, no. 1
- Publisher
- NATURE PORTFOLIO
- Indexed
- SCIE; SCOPUS
- Document Type
- Article
- Abstract
- Autoimmune and autoinflammatory inner ear diseases (AIED/AID) are characterized by the symptom of sensorineural hearing loss (SNHL). To date, standardized diagnostic tools for AIED/AID are lacking, and clinically differentiating AIED/AID from chronic otitis media (COM) with SNHL is challenging. This retrospective study aimed to construct a magnetic resonance imaging (MRI)-based decision tree using classification and regression tree (CART) analysis to distinguish AIED/AID from COM. In total, 67 patients were enrolled between January 2004 and October 2019, comprising AIED/AID (n = 18), COM (n = 24), and control groups (n = 25). All patients underwent 3 T temporal bone MRI, including post-contrast T1-weighted images (postT1WI) and post-contrast FLAIR images (postFLAIR). Two radiologists evaluated the presence of otomastoid effusion and inner ear contrast-enhancement on MRI. A CART decision tree model was constructed using MRI features to differentiate AIED/AID from COM and control groups, and diagnostic performance was analyzed. High-intensity bilateral effusion (61.1%) and inner ear enhancement (postFLAIR, 93.8%; postT1WI, 61.1%) were the most common findings in the AIED/AID group. We constructed two CART decision tree models; the first used effusion amount as the first partitioning node and postT1WI-inner ear enhancement as the second node, whereas the second comprised two partitioning nodes with the degree of postFLAIR-enhancement of the inner ear. The first and second models enabled distinction of AIED/AID from COM with high specificity (100% and 94.3%, respectively). The amount of effusion and the degree of inner ear enhancement on MRI may facilitate the distinction between AIED/AID and COM with SNHL using decision tree models, thereby contributing to early diagnosis and intervention.
- DOI
- 10.1038/s41598-021-98557-w
- Appears in Collections:
- 의과대학 > 의학과 > Journal papers
- Files in This Item:
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s41598-021-98557-w.pdf(1.88 MB)
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