ABSTRACT
A large-scale outbreak of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) occurred in Shanghai, China, in early December 2022. To study the incidence and characteristics of otitis media with effusion (OME) complicating SARS-CoV-2, we collected 267 middle ear effusion (MEE) samples and 172 nasopharyngeal (NP) swabs from patients. The SARS-CoV-2 virus was detected by RT-PCR targeting. The SARS-CoV-2 virus, angiotensin-converting enzyme 2 (ACE2), and transmembrane serine protease 2 (TMPRSS2) expression in human samples was examined via immunofluorescence. During the COVID-19 epidemic in 2022, the incidence of OME (3%) significantly increased compared to the same period from 2020 to 2022. Ear symptoms in patients with SARS-CoV-2 complicated by OME generally appeared late, even after a negative NP swab, an average of 9.33 ± 6.272 days after COVID-19 infection. The SARS-CoV-2 virus was detected in MEE, which had a higher viral load than NP swabs. The insertion rate of tympanostomy tubes was not significantly higher than in OME patients in 2019-2022. Virus migration led to high viral loads in MEE despite negative NP swabs, indicating that OME lagged behind respiratory infections but had a favorable prognosis. Furthermore, middle ear tissue from adult humans coexpressed the ACE2 receptor for the SARS-CoV-2 virus and the TMPRSS2 cofactors required for virus entry.
Subject(s)
COVID-19 , Otitis Media with Effusion , Adult , Humans , SARS-CoV-2 , COVID-19/complications , Angiotensin-Converting Enzyme 2 , China/epidemiologyABSTRACT
BACKGROUND: Temporal bone computed tomography (CT) helps diagnose chronic otitis media (COM). However, its interpretation requires training and expertise. Artificial intelligence (AI) can help clinicians evaluate COM through CT scans, but existing models lack transparency and may not fully leverage multidimensional diagnostic information. OBJECTIVE: We aimed to develop an explainable AI system based on 3D convolutional neural networks (CNNs) for automatic CT-based evaluation of COM. METHODS: Temporal bone CT scans were retrospectively obtained from patients operated for COM between December 2015 and July 2021 at 2 independent institutes. A region of interest encompassing the middle ear was automatically segmented, and 3D CNNs were subsequently trained to identify pathological ears and cholesteatoma. An ablation study was performed to refine model architecture. Benchmark tests were conducted against a baseline 2D model and 7 clinical experts. Model performance was measured through cross-validation and external validation. Heat maps, generated using Gradient-Weighted Class Activation Mapping, were used to highlight critical decision-making regions. Finally, the AI system was assessed with a prospective cohort to aid clinicians in preoperative COM assessment. RESULTS: Internal and external data sets contained 1661 and 108 patients (3153 and 211 eligible ears), respectively. The 3D model exhibited decent performance with mean areas under the receiver operating characteristic curves of 0.96 (SD 0.01) and 0.93 (SD 0.01), and mean accuracies of 0.878 (SD 0.017) and 0.843 (SD 0.015), respectively, for detecting pathological ears on the 2 data sets. Similar outcomes were observed for cholesteatoma identification (mean area under the receiver operating characteristic curve 0.85, SD 0.03 and 0.83, SD 0.05; mean accuracies 0.783, SD 0.04 and 0.813, SD 0.033, respectively). The proposed 3D model achieved a commendable balance between performance and network size relative to alternative models. It significantly outperformed the 2D approach in detecting COM (P≤.05) and exhibited a substantial gain in identifying cholesteatoma (P<.001). The model also demonstrated superior diagnostic capabilities over resident fellows and the attending otologist (P<.05), rivaling all senior clinicians in both tasks. The generated heat maps properly highlighted the middle ear and mastoid regions, aligning with human knowledge in interpreting temporal bone CT. The resulting AI system achieved an accuracy of 81.8% in generating preoperative diagnoses for 121 patients and contributed to clinical decision-making in 90.1% cases. CONCLUSIONS: We present a 3D CNN model trained to detect pathological changes and identify cholesteatoma via temporal bone CT scans. In both tasks, this model significantly outperforms the baseline 2D approach, achieving levels comparable with or surpassing those of human experts. The model also exhibits decent generalizability and enhanced comprehensibility. This AI system facilitates automatic COM assessment and shows promising viability in real-world clinical settings. These findings underscore AI's potential as a valuable aid for clinicians in COM evaluation. TRIAL REGISTRATION: Chinese Clinical Trial Registry ChiCTR2000036300; https://www.chictr.org.cn/showprojEN.html?proj=58685.
Subject(s)
Artificial Intelligence , Otitis Media , Temporal Bone , Tomography, X-Ray Computed , Humans , Otitis Media/diagnostic imaging , Temporal Bone/diagnostic imaging , Tomography, X-Ray Computed/methods , Chronic Disease , Retrospective Studies , Female , Male , Middle Aged , Imaging, Three-Dimensional/methods , Adult , Neural Networks, ComputerABSTRACT
BACKGROUND: Treacher Collins syndrome (TCS; OMIM 154500) is a craniofacial developmental disorder. METHODS: To investigate the genetic features of a four-generation Chinese family with TCS, clinical examinations, hearing tests, computed tomography, whole-exome sequencing (WES), Sanger sequencing, reverse transcription (RT)-PCR, and the Minigene assay were performed. RESULTS: The probands, an 11-year-old male and his cousin exhibited typical clinical manifestations of TCS including conductive hearing loss, downward slanting palpebral fissures, and mandibular hypoplasia. Computed tomography revealed bilateral fusion of the anterior and posterior stapedial crura and malformation of the long crura of the incus. WES of both patients revealed a novel heterozygous intronic variant, i.e., c.4342 + 5_4342 + 8delGTGA (NM_001371623.1) in TCOF1. Minigene expression analysis revealed that the c.4342 + 5_4342 + 8delGTGA variant in TCOF1 caused a partial deletion of exon 24 (c.4115_4342del: p.Gly1373_Arg1448del), which was predicted to yield a truncated protein. The deletion was further confirmed via RT-PCR and sequencing of DNA from proband blood cells. A heterozygous variant in the POLR1C gene (NM_203290; exon6; c.525delG) was found almost co-segregated with the TCOF1 pathogenic variant. CONCLUSIONS: In conclusion, we identified a heterozygous TCOF1 splicing variant c.4342 + 5_4342 + 8delGTGA (splicing) in a Chinese TSC family with ossicular chain malformations and facial anomalies. Our findings broadened the spectrum of TCS variants and will facilitate diagnostics and prognostic predictions.
Subject(s)
Mandibulofacial Dysostosis , Male , Humans , Child , Mandibulofacial Dysostosis/genetics , Mutation , Exons , Introns , China , Nuclear Proteins/genetics , Phosphoproteins/geneticsABSTRACT
Purpose: Glomus tympanicum tumors are benign primary tumors of the middle ear that can be completely removed using modern surgery. We compared endoscopic ear surgery (EES) to traditional microscopic ear surgery (MES) in terms of the removal of early-stage glomus tympanicum tumors. Methods: We retrospectively reviewed 25 cases treated from 2003 to 2021 that were of Grade I or II based on the Glasscock-Jackson classification system. Overall, 18 cases underwent MES: 8 via trans-tympanic bone and 10 via canal-wall-down or canal-wall-up tympanomastoidectomy (CWDT or CWUT) and 7 underwent EES. We compared surgery durations, the lengths and costs of hospitalization, postoperative complications, and relapse rates between the two groups and among the three specific operation ways. Results: The postoperative follow-up period ranged from 1 to 19 years. There was no between-group difference in operative time or the length or cost of hospitalization. Operative time and cost of hospitalization did not show a statistically significant correlation to the three surgical procedures, whereas it was found that the group of MES via the trans-tympanic bone had shorter length of hospitalization when compared with CWUT or CWDT group. All tumors were completely resected; pulsatile tinnitus improved in all patients, and there was no major complication. Two patients who underwent CWUT or CWDT (one each) relapsed; no patient relapsed in the EES group. Conclusion: MES via the trans-tympanic bone and EES via the ear canal safely and reliably remove early-stage tumors without excessive patient discomfort.
ABSTRACT
OBJECTIVES: Planar cell polarity (PCP) signaling, essential for uniform alignment and directional beating of motile cilia, has been investigated in multiciliated epithelia. As a complex structure connecting the middle ear to the nasopharynx, the eustachian tube (ET) is important in the onset of ear-nose-throat diseases. However, PCP signaling, including the orientation that is important for ciliary motility and clearance function in the ET, has not been studied. We evaluated PCP in the ET epithelium. STUDY DESIGN: Morphometric examination of the mouse ET. METHODS: We performed electron microscopy to assess ciliary polarity in the mouse ET, along with immunohistochemical analysis of PCP protein localization in the ET epithelium. RESULTS: We discovered PCP in the ET epithelium. Motile cilia were aligned in the same direction in individual and neighboring cells; this alignment manifested as ciliary polarity in multiciliated cells. Additionally, PCP proteins were asymmetrically localized between adjacent cells in the plane of the ET. CONCLUSIONS: The multiciliated ET epithelium exhibits polarization, suggesting novel structural features that may be critical for ET function. LEVEL OF EVIDENCE: NA Laryngoscope, 134:3795-3801, 2024.