Development and Validation of a Deep Learning Predictive Model Combining Clinical and Radiomic Features for Short-Term Postoperative Facial Nerve Function in Acoustic Neuroma Patients

Objective This study aims to construct and validate a predictable deep learning model associated with clinical data and multi-sequence magnetic resonance imaging(MRI)for short-term postoperative facial nerve function in patients with acoustic neuroma.Methods A total of 110 patients with acoustic neuroma who underwent surgery through the retrosigmoid sinus approach were included.Clinical data and raw features from four MRI sequences(T1-weighted,T2-weighted,T1-weighted contrast enhancement,and T2-weighted-Flair images)were analyzed.Spearman correlation analysis along with least absolute shrinkage and selection operator regression were used to screen combined clinical and radiomic features.Nomogram,machine learning,and convolutional neural network(CNN)models were constructed to predict the prognosis of facial nerve function on the seventh day after surgery.Receiver operating characteristic(ROC)curve and decision curve analysis(DCA)were used to evaluate model performance.A total of 1050 radiomic parameters were extracted,from which 13 radiomic and 3 clinical features were selected.Results The CNN model performed best among all prediction models in the test set with an area under the curve(AUC)of 0.89(95%CI,0.84–0.91).Conclusion CNN modeling that combines clinical and multi-sequence MRI radiomic features provides excellent performance for predicting short-term facial nerve function after surgery in patients with acoustic neuroma.As such,CNN modeling may serve as a potential decision-making tool for neurosurgery.

Hearing Preservation in Acoustic Neuroma Surgery

Objective To report the authors' experiences in hearing preservation during acoustic neuroma (AN) resection procedures. Methods Two cases of AN removal via retrosigmoid approach were reviewed. Hearing preservation was attempted in the aid of endoscopic technique along with continuous monitoring of the compound action potential (CAP) and auditory brainstem response(ABR) during the surgery. Results The tumor in Case 1 was 1.5 cm in diameter. The average pure-tone hearing threshold was 30 dB HL and ABR was normal. Waves I, III and V of ABR were present following tumor removal. At 7th month follow-up, audiometric thresholds and ABR inter-peak intervals had recovered to pre-operative levels, with normal facial nerve function. The patient in Case 2 had bilateral AN. The tumors measured 4.0 cm(left) and 5.0 cm (right) on MRI scans. The AN on the right side was removed first, followed by removal of the left AN four months later. Intraoperative CAP monitoring was employed during removal of the left AN. While efforts to preserve the cochlear nerve were not successful, CAPs were still present after tumor removal. Conclusions Intraoperatively recorded CAPs are not reliable in predicting postoperative hearing outcomes. In contrast, ABRs are an indicator of function of the peripheral auditory pathway. Presence of waves I, III and V following tumor removal may represent preservation of useful hearing.

ADVANCES IN SURGICAL TREATMENT OF ACOUSTIC NEUROMA

Acoustic Neuroma (AN) arises from the eighth cranial nerve. It primarily involves the vestibular branch of the nerve and is therefore also called vestibular schwannoma(VS). To the date, diagnosis and surgical treatment of AN have advanced significantly. Along with advances in audiology and imaging technologies, cases of diagnosed AN have been increasing, making it a common

Facial nerve preservation following microsurgical removal of large and huge acoustic neuroma

Objective To evaluate the long-term facial nerve funtion of patients following microsurgical removal of large and huge acoustic neuroma,and to indentify the factors that influence these outcomes. Methods A retrospective review was performed,which included 176 consecutive patients with a

The viscous strip approach to simplify the calculation of the surface acoustic wave generated streaming

In recent decades,the importance of surface acoustic waves,as a biocompatible tool to integrate with microfluidics,has been proven in various medical and biological applications.The numerical modeling of acoustic streaming caused by surface acoustic waves in microchannels requires the effect of viscosity to be considered in the equations which complicates the solution.In this paper,it is shown that the major contribution of viscosity and the horizontal component of actuation is concentrated in a narrow region alongside the actuation boundary.Since the inviscid equations are considerably easier to solve,a division into the viscous and inviscid domains would alleviate the computational load significantly.The particles'traces calculated by this approximation are excellently alongside their counterparts from the completely viscous model.It is also shown that the optimum thickness for the viscous strip is about 9-fold the acoustic boundary layer thickness for various flow patterns and amplitudes of actuation.

Scheme of negative acoustic radiation force based on a multiple-layered spherical structure

Acoustic radiation force(ARF), as an important particle manipulation method, has been extensively studied in recent years. With the introduction of the concept of “acoustic tweezers”, negative acoustic radiation has become a research hotspot. In this paper, a scheme of realizing negative ARF based on the multiple-layered spherical structure design is proposed. The specific structure and design idea are presented. Detailed theoretical calculation analysis is carried out.Numerical simulations have been performed to verify the correctness of this prediction. The conjecture that the suppression of backscattering can achieve negative ARF is verified concretely, which greatly expands the application prospect and design ideas of the ARF. This work has laid a theoretical foundation for realizing precise control of the structure.

Clinical associations of corneal neuromas with ocular surface diseases

Corneal neuromas,also termed microneuromas,refer to microscopic,irregula rly-shaped enlargements of terminal subbasal nerve endings at sites of nerve damage or injury.The formation of corneal neuromas results from damage to corneal nerves,such as following corneal pathology or corneal or intraocular surge ries.Initially,denervated areas of sensory nerve fibers become invaded by sprouts of intact sensory nerve fibers,and later injured axons regenerate and new sprouts called neuromas develop.In recent years,analysis of corneal nerve abnormalities including corneal neuromas which can be identified using in vivo confocal microscopy,a non-invasive imaging technique with microscopic resolution,has been used to evaluate corneal neuropathy and ocular surface dysfunction.Corneal neuromas have been shown to be associated with clinical symptoms of discomfort and dryness of eyes,and are a promising surrogate biomarker for ocular surface diseases,such as neuropathic corneal pain,dry eye disease,diabetic corneal neuropathy,neurotrophic keratopathy,Sjogren's syndrome,bullous keratopathy,post-refra ctive surgery,and others.In this review,we have summarized the current literature on the association between these ocular surface diseases and the presentation of corneal microneuromas,as well as elaborated on their pathogenesis,visualization via in vivo confocal microscopy,and utility in monitoring treatment efficacy.As current quantitative analysis on neuromas mainly relies on manual annotation and quantification,which is user-dependent and labor-intensive,future direction includes the development of artificial intelligence software to identify and quantify these potential imaging biomarkers in a more automated and sensitive manner,allowing it to be applied in clinical settings more efficiently.Combining imaging and molecular biomarkers may also help elucidate the associations between corneal neuromas and ocular surface diseases.

A Self-Healing Optoacoustic Patch with High Damage Threshold and Conversion Efficiency for Biomedical Applications

Compared with traditional piezoelectric ultrasonic devices,optoacoustic devices have unique advantages such as a simple preparation process,anti-electromagnetic interference,and wireless long-distance power supply.However,current optoacoustic devices remain limited due to a low damage threshold and energy conversion efficiency,which seriously hinder their widespread applications.In this study,using a self-healing polydimethylsiloxane(PDMS,Fe-Hpdca-PDMS)and carbon nanotube composite,a flexible optoacoustic patch is developed,which possesses the self-healing capability at room temperature,and can even recover from damage induced by cutting or laser irradiation.Moreover,this patch can generate high-intensity ultrasound(>25 MPa)without the focusing structure.The laser damage threshold is greater than 183.44 mJ cm^(-2),and the optoacoustic energy conversion efficiency reaches a major achievement at 10.66×10^(-3),compared with other carbon-based nanomaterials and PDMS composites.This patch is also been successfully examined in the application of acoustic flow,thrombolysis,and wireless energy harvesting.All findings in this study provides new insight into designing and fabricating of novel ultrasound devices for biomedical applications.

Predicting microseismic,acoustic emission and electromagnetic radiation data using neural networks

Microseism,acoustic emission and electromagnetic radiation(M-A-E)data are usually used for predicting rockburst hazards.However,it is a great challenge to realize the prediction of M-A-E data.In this study,with the aid of a deep learning algorithm,a new method for the prediction of M-A-E data is proposed.In this method,an M-A-E data prediction model is built based on a variety of neural networks after analyzing numerous M-A-E data,and then the M-A-E data can be predicted.The predicted results are highly correlated with the real data collected in the field.Through field verification,the deep learning-based prediction method of M-A-E data provides quantitative prediction data for rockburst monitoring.

2D DOA Estimation of Coherent Signals with a Separated Linear Acoustic Vector-Sensor Array

In this paper, a two-dimensional(2D) DOA estimation algorithm of coherent signals with a separated linear acoustic vector-sensor(AVS) array consisting of two sparse AVS arrays is proposed. Firstly,the partitioned spatial smoothing(PSS) technique is used to construct a block covariance matrix, so as to decorrelate the coherency of signals. Then a signal subspace can be obtained by singular value decomposition(SVD) of the covariance matrix. Using the signal subspace, two extended signal subspaces are constructed to compensate aperture loss caused by PSS.The elevation angles can be estimated by estimation of signal parameter via rotational invariance techniques(ESPRIT) algorithm. At last, the estimated elevation angles can be used to estimate automatically paired azimuth angles. Compared with some other ESPRIT algorithms, the proposed algorithm shows higher estimation accuracy, which can be proved through the simulation results.

Microstructure Features and the Macroscopic Acoustic Behavior of Gassy Silt in the Yellow River Delta

The morphological changes in isolated bubbles in gassy silt play a critical role in the microscopic structures between soil particles and bubbles and macroscopic physical properties.Based on X-ray CT scanning experiments under various vertical loads(four levels),self-designed acoustic macro experiments,and a series of formula revisions to the macro-air-bearing silt sound-velocity prediction model,this paper discusses the macro-and micro-scale features of gassy silts from the Yellow River Delta.The samples consisted of different proportions of silt from the Yellow River Delta and porous media,and they were used to form two types of aerosol silts with initial gas contents of 4.23%and 7.67%.The results show that the air bubble content and external load considerably affect the microstructural parameters and acoustic behavior of gassy silt in the Yellow River Delta.The macroscopic sound velocity showed a linear positive correlation with vertical load and relation to microstructural parameters in varying manners and degrees.Based on the traditional Biot-Stoll acoustic model,the gas-phase medium coefficient was introduced for the proper calculation and prediction of the sound velocity of air-bearing silt.The errors of the overall prediction varied between 5.6%and 9.6%.

Simplified prediction models for acoustic installation effects of train-mounted equipment

Acoustic models of railway vehicles in standstill and pass-by conditions can be used as part of a virtual certification process for new trains.For each piece of auxiliary equipment,the sound power measured on a test bench is combined with meas-ured or predicted transfer functions.It is important,however,to allow for installation effects due to shielding by fairings or the train body.In the current work,fast-running analytical models are developed to determine these installation effects.The model for roof-mounted sources takes account of diffraction at the corner of the train body or fairing,using a barrier model.For equipment mounted under the train,the acoustic propagation from the sides of the source is based on free-field Green’s functions.The bottom surfaces are assumed to radiate initially into a cavity under the train,which is modelled with a simple diffuse field approach.The sound emitted from the gaps at the side of the cavity is then assumed to propagate to the receivers according to free-field Green’s functions.Results show good agreement with a 2.5D boundary element model and with measurements.Modelling uncertainty and parametric uncertainty are evaluated.The largest variability occurs due to the height and impedance of the ground,especially for a low receiver.This leads to standard deviations of up to 4 dB at low frequencies.For the roof-mounted sources,uncertainty over the location of the corner used in the equivalent barrier model can also lead to large standard deviations.

Enriched Constant Elements in the Boundary Element Method for Solving 2D Acoustic Problems at Higher Frequencies

The boundary element method(BEM)is a popular method for solving acoustic wave propagation problems,especially those in exterior domains,owing to its ease in handling radiation conditions at infinity.However,BEM models must meet the requirement of 6–10 elements per wavelength,using the conventional constant,linear,or quadratic elements.Therefore,a large storage size of memory and long solution time are often needed in solving higher-frequency problems.In this work,we propose two new types of enriched elements based on conventional constant boundary elements to improve the computational efficiency of the 2D acoustic BEM.The first one uses a plane wave expansion,which can be used to model scattering problems.The second one uses a special plane wave expansion,which can be used tomodel radiation problems.Five examples are investigated to showthe advantages of the enriched elements.Compared with the conventional constant elements,the new enriched elements can deliver results with the same accuracy and in less computational time.This improvement in the computational efficiency is more evident at higher frequencies(with the nondimensional wave numbers exceeding 100).The paper concludes with the potential of our proposed enriched elements and plans for their further improvement.

Effects of confining pressure and pore pressure on multipole borehole acoustic field in fluid-saturated porous media

In-situ stress is a common stress in the exploration and development of oil reservoirs. Therefore, it is of great significance to study the propagation characteristics of borehole acoustic waves in fluid-saturated porous media under stress.Based on the acoustoelastic theory of fluid-saturated porous media, the field equation of fluid-saturated porous media under the conditions of confining pressure and pore pressure and the acoustic field formula of multipole source excitation in open hole are given. The influences of pore pressure and confining pressure on guided waves of multipole borehole acoustic field in fluid-saturated porous media are investigated. The numerical results show that the phase velocity and excitation intensity of guided wave increase significantly under the confining pressure. For a given confining pressure, the phase velocity of the guided wave decreases with pore pressure increasing. The excitation intensity of guided wave increases at low frequency and then decreases at high frequency with pore pressure increasing, except for that of Stoneley wave which decreases in the whole frequency range. These results will help us get an insight into the influences of confining pressure and pore pressure on the acoustic field of multipole source in borehole around fluid-saturated porous media.

High-order Bragg forward scattering and frequency shift of low-frequency underwater acoustic field by moving rough sea surface

Acoustic scattering modulation caused by an undulating sea surface on the space-time dimension seriously affects underwater detection and target recognition.Herein,underwater acoustic scattering modulation from a moving rough sea surface is studied based on integral equation and parabolic equation.And with the principles of grating and constructive interference,the mechanism of this acoustic scattering modulation is explained.The periodicity of the interference of moving rough sea surface will lead to the interference of the scattering field at a series of discrete angles,which will form comb-like and frequency-shift characteristics on the intensity and the frequency spectrum of the acoustic scattering field,respectively,which is a high-order Bragg scattering phenomenon.Unlike the conventional Doppler effect,the frequency shifts of the Bragg scattering phenomenon are multiples of the undulating sea surface frequency and are independent of the incident sound wave frequency.Therefore,even if a low-frequency underwater acoustic field is incident,it will produce obvious frequency shifts.Moreover,under the action of ideal sinusoidal waves,swells,fully grown wind waves,unsteady wind waves,or mixed waves,different moving rough sea surfaces create different acoustic scattering processes and possess different frequency shift characteristics.For the swell wave,which tends to be a single harmonic wave,the moving rough sea surface produces more obvious high-order scattering and frequency shifts.The same phenomena are observed on the sea surface under fully grown wind waves,however,the frequency shift slightly offsets the multiple peak frequencies of the wind wave spectrum.Comparing with the swell and fully-grown wind waves,the acoustic scattering and frequency shift are not obvious for the sea surface under unsteady wind waves.

Shear band evolution and acoustic emission characteristics of sandstone containing non-persistent flaws

Direct shear tests were conducted on sandstone specimens under different constant normal stresses to study the coalescence of cracks between non-persistent flaws and the shear sliding characteristics of the shear-formed fault.Digital image correlation and acoustic emission(AE)techniques were used to monitor the evolution of shear bands at the rock bridge area and microcracking behaviors.The experimental results revealed that the shear stresses corresponding to the peak and sub-peak in the stressdisplacement curve are significantly affected by the normal stress.Strain localization bands emerged at both the tip of joints and the rock bridge,and their extension and interaction near the peak stress caused a surge in the AE hit rate and a significant decrease in the AE b value.Short and curvilinear strain bands were detected at low normal stress,while high normal stress generally led to more microcracking events and longer coplanar cracks at the rock bridge area.Furthermore,an increase in normal stress resulted in a higher AE count rate and more energetic AE events during friction sliding along the shearformed fault.It was observed that the elastic energy released during the crack coalescence at the prepeak stage was much greater than that released during friction sliding at the post-peak stage.More than 75%of AE events were located in the low-frequency band(0e100 kHz),and this proportion continued to rise with increasing normal stress.Moreover,more AE events of low AF value and high RA value were observed in specimens subjected to high normal stress,indicating that greater normal stress led to more microcracks of shear nature.

Fine Sand and Clay Sediment Acoustic Properties of the Novel Sediment Sample from the Arabian Sea:Experimental Investigations and Biot−Stoll Model Validation

The present study explores the physical and acoustic characteristics of fine sand and clay in novel seabed marine sediments from of Pakistan coastline of the Arabian Sea.The measured physical parameters included mean grain size,mass density,bulk density,salinity,porosity,permeability,pore size and mineralogical composition.Acoustic properties,including sound speed and attenuation,in the high frequency range of 90-170 kHz were analyzed.A controlled laboratory setup with the acoustic transmission method and Fourier transform techniques was utilized to examine the sound propagation and absorption of novel seabed sediments.The standard deviation of mean sound speed in fresh water was 0.75 m/s,and attenuation was observed in the range of 0.43 to 0.61 dB/m.The mean sound velocity in sand and clay varied from 1706 to 1709 m/s and 1602 to 1608 m/s,respectively.Corresponding average attenuation was observed at 80 to 93 dB/m in sandy sediments and from 31.8 to 38.6 dB/m in clayey sediments.Sound velocity variation within sandy sediment is low,consistent with expected results,and smaller than the predicted uncertainty.However,clay sediment exhibited a positive linear correlation and low sound speed variation.Attenuation increased linearly with frequency for both sediments.Finally,the laboratory results were validated by using the Biot−Stoll model.The dispersion of sound speed in sandy and clayey sediments was consistent with the predictions of the Biot−Stoll model.Measured attenuation aligned more with Biot−Stoll model predictions due to improved permeability,tortuosity and pore size parameter fitting.

A stable staggered-grid finite-difference scheme for acoustic modeling beyond conventional stability limit

Staggered-grid finite-difference(SGFD)schemes have been widely used in acoustic wave modeling for geophysical problems.Many improved methods are proposed to enhance the accuracy of numerical modeling.However,these methods are inevitably limited by the maximum Courant-Friedrichs-Lewy(CFL)numbers,making them unstable when modeling with large time sampling intervals or small grid spacings.To solve this problem,we extend a stable SGFD scheme by controlling SGFD dispersion relations and maximizing the maximum CFL numbers.First,to improve modeling stability,we minimize the error between the FD dispersion relation and the exact relation in the given wave-number region,and make the FD dispersion approach a given function outside the given wave-number area,thus breaking the conventional limits of the maximum CFL number.Second,to obtain high modeling accuracy,we use the SGFD scheme based on the Remez algorithm to compute the FD coefficients.In addition,the hybrid absorbing boundary condition is adopted to suppress boundary reflections and we find a suitable weighting coefficient for the proposed scheme.Theoretical derivation and numerical modeling demonstrate that the proposed scheme can maintain high accuracy in the modeling process and the value of the maximum CFL number of the proposed scheme can exceed that of the conventional SGFD scheme when adopting a small maximum effective wavenumber,indicating that the proposed scheme improves stability during the modeling.

Acoustical properties of a 3D printed honeycomb structure filled with nanofillers:Experimental analysis and optimization for emerging applications

The novelty of this research lies in the successful fabrication of a 3D-printed honeycomb structure filled with nanofillers for acoustic properties,utilizing an impedance tube setup in accordance with ASTM standard E 1050-12.The Creality Ender-3,a 3D printer,was used for printing the honeycomb structures,and polylactic acid(PLA)material was employed for their construction.The organic,inorganic,and polymeric compounds within the composites were identified using fourier transformation infrared(FTIR)spectroscopy.The structure and homogeneity of the samples were examined using a field emission scanning electron microscope(FESEM).To determine the sound absorption coefficient of the 3D printed honeycomb structure,numerous samples were systematically developed using central composite design(CCD)and analysed using response surface methodology(RSM).The RSM mathematical model was established to predict the optimum values of each factor and noise reduction coefficient(NRC).The optimum values for an NRC of 0.377 were found to be 1.116 wt% carbon black,1.025 wt% aluminium powder,and 3.151 mm distance between parallel edges.Overall,the results demonstrate that a 3Dprinted honeycomb structure filled with nanofillers is an excellent material that can be utilized in various fields,including defence and aviation,where lightweight and acoustic properties are of great importance.

Acoustic emission signal identification of different rocks based on SE-1DCNN-BLSTM network model

In order to study fracture mechanism of rocks in different brittle mineral contents,this study pro-poses a method to identify the acoustic emission signal released by rock fracture under different brittle miner-al content(BMC),and then determine the content of brittle matter in rock.To understand related interference such as the noises in the acoustic emission signals released by the rock mass rupture,a 1DCNN-BLSTM network model with SE module is constructed in this study.The signal data is processed through the 1DCNN and BLSTM networks to fully extract the time-series correlation features of the signals,the non-correlated features of the local space and the weak periodicity law.Furthermore,the processed signals data is input into the fully connected layers.Finally,softmax function is used to accurately identify the acoustic emission signals released by different rocks,and then determine the content of brittle minerals contained in rocks.Through experimental comparison and analysis,1DCNN-BLSTM model embedded with SE module has good anti-noise performance,and the recognition accuracy can reach more than 90 percent,which is better than the traditional deep network models and provides a new way of thinking for rock acoustic emission re-search.