Outcomes of regenerative treatment for over 200 patients with tympanic membrane perforation.

OBJECTIVE: To evaluate outcomes of a regenerative treatment (RT) for over 200 patients with tympanic membrane perforation (TMP). The RT-TMP method involves a gelatin sponge, basic fibroblast growth factor (bFGF) and fibrin glue. METHODS: The study population included 216 patients and 234 ears (male: female =100:116; age 1-93 years). All enrolled patients were treated with RT-TMP in which TMP edges were disrupted mechanically and a gelatin sponge immersed in bFGF was inserted into the perforation. Fibrin glue was then dripped over the sponge. Patient outcomes including TMP closure rates, change in hearing level, and complications were obtained from retrospective medical chart reviews. The TMP was examined three or more weeks after surgery. The treatment was repeated up to 4 times until complete TMP closure was achieved. RESULTS: After mechanical disruption, the perforation size was Grade I, ≤1/3 of entire TM area in 22 ears (9.4 %), Grade II, 1/3-2/3 of entire TM in 77 ears (32.9 %) and Grade III, ≥2/3 of entire TM area in 135 ears (57.7 %). The overall TMP closure rates were 97.0 % (227/234). Complete TMP closure was achieved in 68.8 % (161/234), 22.6 % (53/234), 4.7 % (11/234) and 0.9 % (2/234) of ears after 1, 2, 3 and 4 treatments, respectively. In 7 of 234 ears (3.0 %), the TMPs were not closed completely after 4 treatments. There was no correlation between TMP size after mechanical disruption and number of treatments required to achieve complete closure (Fisher's exact test p = 0.70). The mean air-conduction hearing threshold at low frequency improved from 57.3 ± 16.7 dB before treatment to 37.3 ± 16.0 dB (p < 0.0001) after closure of TMPs. For middle and high frequencies, the improvement was 49.0 ± 19.3 dB to 36.9 ± 17.9 dB (p < 0.0001) and 57.7 ± 22.9 dB to 49.2 ± 23.3 dB (p < 0.0001), respectively. The mean air-bone gaps also improved significantly, and were within 10 dB at 250 Hz, 500 Hz and 1 kHz, and 11 dB at 2 kHz. One or more complications occurred in 32 patients (32/216; 14.8 %). The most common complication was formation of an epithelial pearl (16 ears; 6.8 %), followed by severe TM retraction (9 ears; 3.8 %) and otitis media with effusion (6 ears; 2.6 %). There were no serious complications that caused deterioration of the patient's general condition. CONCLUSION: Our results showed that RT-TMP had high success rates for TMP closure and good hearing improvement and produced no severe complications that could affect general health status. This novel therapy is simple, safe and minimally invasive, and could help improve the quality of life in patients with TMP.

Diagnosing Middle Ear Malformation by Pure-Tone Audiometry Using a Three-Dimensional Finite Element Model: A Case-Control Study.

BACKGROUND: Hearing loss caused by middle ear malformations is treated by tympanoplasty to reconstruct the acoustic conduction system. The mobility of the ossicles plays a crucial role in postoperative success. However, identifying the location of ossicular malformation based solely on preoperative audiograms is challenging due to the complex relationship between fixation location, deformity levels, and ossicular mobility. METHODS: Middle ear finite element models for simulating ossicular malformations were created, and the results were compared with the actual preoperative audiograms. RESULTS: This approach objectively diagnosed ossicular fixation and disarticulation, bypassing traditional criteria reliant on physician examination or imaging. CONCLUSION: This study suggests that future research should focus on developing a diagnostic framework utilizing large-scale data.

Predictive factors of acute sensorineural hearing loss in adult Japanese patients for clinical application by primary care doctors: a cross-sectional study.

BACKGROUND: Several methods are used for hearing loss screening; however, their benefits are uncertain. In this study, we aimed to determine the predictive factors of acute sensorineural hearing loss for clinical application by primary care doctors. METHODS: This retrospective, cross-sectional study included 365 patients with acute sensorineural hearing loss without prior therapy. The patients' clinical data, demographic information, and medical histories were obtained, and they were asked about comorbidities. In addition, we assessed lifestyle factors such as stress level, alcohol consumption, marital status, and socioeconomic level. Logistic regression analysis was performed to investigate the diagnostic predictive ability of the selected factors associated with acute sensorineural hearing loss. The hearing levels of all patients were evaluated using pure tone audiometry. RESULTS: We identified significant predictive factors for acute sensorineural hearing loss. The absence of hyperacusis was a predictive factor for sudden sensorineural hearing loss. Younger age, female sex, and marital status were predictive factors for acute low-tone hearing loss. High body mass index, high socioeconomic level, low alcohol consumption, high stress level, hyperacusis, and vertigo/dizziness were predictive factors for Ménière's disease. High body mass index and ear fullness were predictive factors for perilymph fistula. Low stress level was a predictive factor for acoustic tumours. CONCLUSIONS: Our findings can be used to distinguish between the types of acute sensorineural hearing loss. Symptoms, physical status, and lifestyle factors identified during this study are useful markers for predicting acute sensorineural hearing loss occurrence.

Application of artificial intelligence using a convolutional neural network for detecting cholesteatoma in endoscopic enhanced images.

OBJECTIVE: We examined whether artificial intelligence (AI) used with the novel digital image enhancement system modalities (CLARA+CHROMA, SPECTRA A, and SPECTRA B) could distinguish the cholesteatoma matrix, cholesteatoma debris, and normal middle ear mucosa, and observe the middle ear cavity during middle ear cholesteatoma surgery. METHODS: A convolutional neural network (CNN) was trained with a set of images chosen by an otologist. To evaluate the diagnostic accuracy of the constructed CNN, an independent test data set of middle ear images was collected from 14 consecutive patients with 26 cholesteatoma matrix lesions, who underwent transcanal endoscopic ear surgery at a single hospital from August 2018 to September 2019. The final test data set included 58 total images, with 1‒5 images from each modality for each case. RESULTS: The CNN required only 10 s to analyze more than 58 test images. Using SPECTRA A and SPECTRA B, the CNN correctly diagnosed 15 and 15 of 26 cholesteatoma matrix lesions, with a sensitivity of 34.6% and 42.3%, and with a specificity of 81.3% and 87.5%, respectively. CONCLUSION: Our preliminary study revealed that AI and novel imaging modalities are potentially useful tools for identifying and visualizing the cholesteatoma matrix during endoscopic ear surgery. The diagnostic ability of the CNN is not yet appropriate for implementation in daily clinical practice, based on our study findings. However, in the future, these techniques and AI tools could help to reduce the burden on surgeons and will facilitate telemedicine in remote and rural areas, as well as in developing countries where the number of surgeons is limited.