The human otitis media with effusion: a numerical-based study

A comprehensive finite-element human ear model to estimate noise-induced hearing loss associated with occupational noise exposure

BACKGROUND AND OBJECTIVE

Noise is a common occupational and environmental hazard; however, little is known about the use of computational tools to quantitively analyze data on basilar membrane (BM) damage in noise-induced hearing loss (NIHL). Here, we established a comprehensive three-dimensional finite-element human ear model to quantify the impact of noise exposure on BM and perilymph fluid.

METHODS

We used auditory risk units (ARUs) to evaluate the BM damage for subjects (3 men and 5 women; mean age, 32.75 ± 8.86 years; age range, 24-44 years). A 90-dB sound pressure level (SPL) was normally applied at the external auditory canal (EAC) entrance to simulate sound transmission from the EAC to the cochlea at frequencies of 0.2-10.0 kHz.

RESULTS

The pressure distribution of perilymph fluid is totally different on frequency responses under low and high sound-evoked (0.013-10.0 kHz). The highest ARUs were 18.479% at the distance of 1 mm from the base, and the second-highest to fourth-highest ARUs occurred at distances of 5-7 mm from the base, where their ARUs were 9.749%, 9.176%, and 11.231%. The total of the ARUs reached 81.956% at external frequencies' sounds of 3.2-5.0 kHz. Among these, the 3.8-kHz and 3.6-kHz frequencies yielded the highest and second-highest ARUs of 20.325% and 19.873%, respectively.

CONCLUSIONS

This study would inform our understanding of NIHL associated with occupational noise exposure. We present a FE modelling and describe how it might provide a unique way to unravel mechanisms that drive NIHL due to loud noises.

A Deep Learning Approach to Predict Conductive Hearing Loss in Patients With Otitis Media With Effusion Using Otoscopic Images

Importance

Otitis media with effusion (OME) is one of the most common causes of acquired conductive hearing loss (CHL). Persistent hearing loss is associated with poor childhood speech and language development and other adverse consequence. However, to obtain accurate and reliable hearing thresholds largely requires a high degree of cooperation from the patients.

Objective

To predict CHL from otoscopic images using deep learning (DL) techniques and a logistic regression model based on tympanic membrane features.

Design, Setting, and Participants

A retrospective diagnostic/prognostic study was conducted using 2790 otoscopic images obtained from multiple centers between January 2015 and November 2020. Participants were aged between 4 and 89 years. Of 1239 participants, there were 209 ears from children and adolescents (aged 4-18 years [16.87%]), 804 ears from adults (aged 18-60 years [64.89%]), and 226 ears from older people (aged >60 years, [18.24%]). Overall, 679 ears (54.8%) were from men. The 2790 otoscopic images were randomly assigned into a training set (2232 [80%]), and validation set (558 [20%]). The DL model was developed to predict an average air-bone gap greater than 10 dB. A logistic regression model was also developed based on otoscopic features.

Main Outcomes and Measures

The performance of the DL model in predicting CHL was measured using the area under the receiver operating curve (AUC), accuracy, and F1 score (a measure of the quality of a classifier, which is the harmonic mean of precision and recall; a higher F1 score means better performance). In addition, these evaluation parameters were compared to results obtained from the logistic regression model and predictions made by three otologists.

Results

The performance of the DL model in predicting CHL showed the AUC of 0.74, accuracy of 81%, and F1 score of 0.89. This was better than the results from the logistic regression model (ie, AUC of 0.60, accuracy of 76%, and F1 score of 0.82), and much improved on the performance of the 3 otologists; accuracy of 16%, 30%, 39%, and F1 scores of 0.09, 0.18, and 0.25, respectively. Furthermore, the DL model took 2.5 seconds to predict from 205 otoscopic images, whereas the 3 otologists spent 633 seconds, 645 seconds, and 692 seconds, respectively.

Conclusions and Relevance

The model in this diagnostic/prognostic study provided greater accuracy in prediction of CHL in ears with OME than those obtained from the logistic regression model and otologists. This indicates great potential for the use of artificial intelligence tools to facilitate CHL evaluation when CHL is unable to be measured.

Effects of age-related tympanic-membrane material properties on sound transmission in the middle ear in a three-dimensional finite-element model

BACKGROUND AND OBJECTIVES

The Young's modulus of the tympanic membrane (TM) is an important modeling parameter in computer simulations of the sound transmission in the ear. Understanding the material mechanics of the TM is essential to improve the coupling between the tympanic membrane and the auditory ossicles. However, the impact of the age-related Young's modulus of the TM on sound transmission is not well known. The objective of this study was to use a comprehensive finite element (FE) model to assess the impact of Young's modulus on sound transmission from the ear canal to the stapes footplate over acoustic frequencies.

METHODS

The FE model of the ear canal, the middle ear, and the inner ear, was constructed. The model was constructed with identical geometries and boundary conditions, but with three different Young's moduli for the TMs. The auditory ossicles, suspensory ligaments and tendons, and manubrium were also modeled as isotropic elastic materials. Beside, we evaluated the age-related Young's moduli of the TMs on sound transmission with the FE element fluid-structural interaction (FSI) model under acoustic loading conditions.

RESULTS

The impact of the age-related Young's moduli on the sound pressure distributions in the ear canal was significant over two frequency ranges of 1.4-3.2 and 8.6-10 kHz. Meanwhile, the significant differences of the displacement of the stapes occurred at around 1.6 kHz, where the displacement of the stapes decreased from 0.352 nm to 0.287 nm.

CONCLUSIONS

The FSI model could demonstrate the influence of Young's modulus of the TM on the transfer of sound-induced vibrations form the ear canal to the stapes footplate. The FE model may provide appropriate information to the medical device development of artificial ossicles and hearing aids.

Intracochlear Pressures in Simulated Otitis Media With Effusion: A Temporal Bone Study

HYPOTHESIS

Simulated otitis media with effusion reduces intracochlear pressures comparable to umbo velocity.

BACKGROUND

Otitis media with effusion is a common cause of temporary hearing loss, particularly in children, producing deficits of 30 to 40 dB. Previous studies measured the effects of simulated effusion on ossicular mechanics; however, no studies have measured cochlear stimulation directly. Here, we compare pressures in the scala vestibuli and tympani to umbo velocity, before and after induction of simulated effusion in cadaveric human specimens.

METHODS

Eight cadaveric, hemi-cephalic human heads were prepared with complete mastoidectomies. Intracochlear pressures were measured with fiber optic pressure probes, and umbo velocity measured via laser Doppler vibrometry (LDV). Stimuli were pure tones (0.1-14 kHz) presented in the ear canal via a custom speculum sealed with a glass cover slip. Effusion was simulated by filling the mastoid cavity and middle ear space with water.

RESULTS

Acoustic stimulation with middle ear effusion resulted in decreased umbo velocity up to ∼26 dB, whereas differential pressure (PDiff) at the base of the cochlea decreased by only ∼16 dB.

CONCLUSION

Simulating effusion leads to a frequency-dependent reduction in intracochlear sound pressure levels consistent with audiological presentation and prior reports. Results reveal that intracochlear pressure measurements (PSV and PST) decrease less than expected, and less than the decrease in PDiff. The observed decrease in umbo velocity is greater than in the differential intracochlear pressures, suggesting that umbo velocity overestimates the induced conductive hearing loss. These results suggest that an alternate sound conduction pathway transmits sound to the inner ear during effusion.

Influence of ossicular chain malformation on the performance of round-window stimulation: A finite element approach

As a novel application of implantable middle ear hearing device, round-window stimulation is widely used to treat hearing loss with middle ear disease, such as ossicular chain malformation. To evaluate the influence of ossicular chain malformations on the efficiency of the round-window stimulation, a human ear finite element model, which incorporates cochlear asymmetric structure, was constructed. Five groups of comparison with experimental data confirmed the model’s validity. Based on this model, we investigated the influence of three categories of ossicular chain malformations, that is, incudostapedial disconnection, incus and malleus fixation, and fixation of the stapes. These malformations’ effects were evaluated by comparing the equivalent sound pressures derived from the basilar membrane displacement. Results show that the studied ossicular chain malformations mainly affected the round-window simulation’s performance at low frequencies. In contrast to the fixation of the ossicles, which mainly deteriorates round-window simulation’s low-frequency performance, incudostapedial disconnection increases this performance, especially in the absence of incus process and stapes superstructure. Among the studied ossicular chain malformations, the stapes fixation has a much more severe impact on the round-window stimulation’s efficiency. Thus, the influence of the patients’ ossicular chain malformations should be considered in the design of the round-window stimulation’s actuator. The low-frequency output of the round-window simulation’s actuator should be enhanced, especially for treating the patients with stapes fixation.

Numerical Study and Optimization of a Novel Piezoelectric Transducer for a Round-Window Stimulating Type Middle-Ear Implant

Round window (RW) stimulation is a new application of middle ear implants for treating hearing loss, especially for those with middle ear disease. However, most reports on it are based on the use of the floating mass transducer (FMT), which was not originally designed for round window stimulation. The mismatch of the FMT's diameter and the round window membrane's diameter and the uncontrollable preload of the transducer, leads to a high variability in its clinical outcomes. Accordingly, a new piezoelectric transducer for the round-window-stimulating-type middle ear implant is proposed in this paper. The transducer consists of a piezoelectric stack, a flextensional amplifier, a coupling rod, a salver, a plate, a titanium housing and a supporting spring. Based on a constructed coupling finite element model of the human ear and the transducer, the influences of the transducer design parameters on its performance were analyzed. The optimal structure of the supporting spring, which determines the transducer's resonance frequency, was ascertained. The results demonstrate that our designed transducer generates better output than the FMT, especially at low frequency. Besides this, the power consumption of the transducer was significantly decreased compared with a recently reported RW-stimulating piezoelectric transducer.

Transient response of the human ear to impulsive stimuli: A finite element analysis

Nowadays, the steady-state responses of human ear to pure tone stimuli have been widely studied. However, the temporal responses to transient stimuli have not been investigated systematically to date. In this study, a comprehensive finite element (FE) model of the human ear is used to investigate the transient characteristics of the human ear in response to impulsive stimuli. There are two types of idealized impulses applied in the FE analysis: the square wave impulse (a single positive pressure waveform) and the A-duration wave impulse (both of positive and negative pressure waveforms). The time-domain responses such as the displacements of the tympanic membrane (TM), the stapes footplate (SF), the basilar membrane (BM), the TM stress distribution, and the cochlea input pressure are derived. The results demonstrate that the TM motion has the characteristic of spatial differences, and the umbo displacement is smaller than other locations. The cochlea input pressure response is synchronized with the SF acceleration response while the SF displacement response appears with some time delay. The BM displacement envelope is relatively higher in the middle cochlea and every portion of BM vibrates at its best frequency approximately. The present results provide a good understanding of the transient response of the human ear.