ArticleLife (Basel, Switzerland)2022
Transmastoid Ultrasound Detection of Middle Ear Effusion and Its Association with Clinical Audiometric Tests.
Article in Life (Basel, Switzerland), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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1 citing paper in PubMed, 3 citations in OpenAlex.
- Quantitative assessment of pneumothorax by using Shannon entropy of lung ultrasound M-mode image and diaphragmatic excursion based on automated measurement.Quantitative imaging in medicine and surgery · 2024Article
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4 authors at 3 institutions in 1 country.
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Abstract
Medical history taking, otoscopy, tympanometry, and audiometry are clinical methods to diagnose middle ear effusion (MEE); however, these procedures are experience-dependent and result in misdiagnosis under unfavorable conditions of the external auditory canal in non-cooperative young children. This study aimed to explore the use of transmastoid ultrasound combined with the Nakagami parameter analysis to detect MEE in children aged 3−5 years and to compare the proposed method with clinical evaluation methods. A total of forty subjects were enrolled; for each subject, a single-element ultrasound transducer of 2.25 MHz was used to measure backscattered signals returned from the mastoid for estimating the Nakagami parameter, which is a measure of the echo amplitude distribution. Tympanogram and hearing loss were also measured for comparisons. The results showed that the Nakagami parameter in the patients with MEE was significantly larger than that of the normal group (p < 0.05). The area under the receiver operating characteristic curve (AUROC) for using the Nakagami parameter to detect MEE was 0.90, and the sensitivity, specificity, and accuracy were 82.5%, 97.5%, and 79.6%, respectively. The Nakagami parameter for tympanogram types B/C was higher than that for tympanogram type A (p < 0.05); it was also higher in the subjects with hearing loss (p < 0.05). Quantitative transmastoid ultrasound based on the Nakagami parameter analysis has the potential to detect MEE and evaluate hearing loss.
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