Multi-modal screening system and method for senile deaf worker cochlea implantation candidate patients

Abstract

The invention provides a multi-modal screening system and method for candidate patients for cochlear implantation of senile deaf patients. The method comprises the steps that the relative telomere length of leukocyte DNA in peripheral blood sample data of the senile deaf patients and a temporal bone three-dimensional image of the senile deaf patients are obtained; analyzing the temporal bone three-dimensional image to obtain an oval window width and an included angle between a facial nerve level segment and a projia; obtaining an electric evoked compound action potential signal of the auditory nerve of the senile deafness patient under the electric stimulation effect of the preset parameters, and obtaining a filtered electric evoked compound action potential signal; based on the telomere relative length, the oval window width, the included angle and the filtered electric evoked composite action potential signal, candidate patients suitable for cochlear implant implantation are judged; according to the technical scheme provided by the invention, the construction of a comprehensive evaluation system is realized, so that the artificial cochlea implantation fitness of the patient is evaluated more accurately, and the scientificity and reliability of candidate patient screening are improved.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of biomedical engineering, in particular to a multi-modal screening system and method for a presbycusis cochlear implant candidate. BACKGROUND

[0002] With the aggravation of population aging, the number of presbycusis patients continues to grow. Cochlear implantation as an effective means to restore hearing, its preoperative precise screening has become the focus of clinical attention. Therefore, there is an urgent need for a multi-modal assessment technology that can comprehensively reflect the biological aging state of patients, the operability of middle ear anatomy, and the integrity of the auditory pathway function, to achieve scientific stratification of the candidate patients, and to improve the predictability and stability of postoperative auditory rehabilitation effect.

[0003] Currently, the existing mainstream scheme has tried to evaluate the implantation potential of presbycusis patients by high-resolution temporal bone CT images combined with preoperative electrophysiological detection. This scheme mainly relies on imaging measurements such as cochlear ossification degree, facial nerve running position and other structural features to judge the feasibility of surgical approach, and combines with intraoperative or preoperative detection of auditory brainstem response threshold or cochlear microphonics potential and other indicators to indirectly assess the residual function state of the auditory nerve. However, the existing scheme has certain defects, for example, it fails to fully incorporate molecular indicators reflecting the systematic biological aging process of patients, and lacks the ability to predict the differences in postoperative neural plasticity and auditory adaptation ability caused by aging differences between individuals; conventional electrophysiological indicators are easily affected by central compensation or test environment interference, and it is difficult to capture the instantaneous response characteristics of the auditory nerve terminal segment to electrical stimulation. SUMMARY

[0004] The present application provides a multi-modal screening system and method for a presbycusis cochlear implant candidate, to solve the problems in the prior art that molecular indicators of patients are not fully incorporated, and the ability to predict differences in postoperative neural plasticity and auditory adaptation ability of patients is lacking; it is difficult to capture the instantaneous response characteristics of the auditory nerve terminal segment to electrical stimulation.

[0005] In a first aspect, the present application provides a multi-modal screening method for a presbycusis cochlear implant candidate, comprising: obtaining the telomere relative length of leukocyte DNA in a peripheral blood sample data of a presbycusis patient, and a temporal bone three-dimensional image of the presbycusis patient; analyzing the temporal bone three-dimensional image to obtain the width of the oval window and the angle between the horizontal segment of the facial nerve and the promontory; obtaining an electrically evoked compound action potential signal of the auditory nerve of the presbycusis patient under the action of electrical stimulation of a preset parameter, and performing band-pass filtering processing on the electrically evoked compound action potential signal to obtain a filtered electrically evoked compound action potential signal; Based on the relative length of the telomere, the width of the oval window, the included angle and the filtered electrically induced compound action potential signal, the artificial cochlea implant adaptability score of the presbycusis patient is calculated, and when the artificial cochlea implant adaptability score exceeds the adaptability threshold, the presbycusis patient is determined as a candidate patient suitable for artificial cochlea implantation.

[0006] Optionally, the temporal bone three-dimensional image is analyzed to obtain the width of the oval window, the included angle between the horizontal segment of the facial nerve and the promontorium, and the width of the oval window, including: The bony edges on both sides of the oval window are identified from the axial view of the temporal bone three-dimensional image, and the vertical distance between the narrowest edges of the two bony edges is calculated as the width of the oval window; According to the oblique sagittal view of the temporal bone three-dimensional image, an initial reference line is fitted, and based on the initial reference line, a first reference line is optimized and fitted; In the oblique sagittal view, the bony protuberance highest point of the promontorium is identified, and a straight line passing through the bony protuberance highest point and parallel to the skull base plane is generated as a second reference line; The reference line included angle of the first reference line and the second reference line in the plane of the oblique sagittal view is calculated, and the reference line included angle is taken as the included angle between the horizontal segment of the facial nerve and the promontorium.

[0007] Optionally, according to the oblique sagittal view of the temporal bone three-dimensional image, an initial reference line is fitted, and based on the initial reference line, a first reference line is optimized and fitted, including: The anatomical positioning points of the bony boundary of the facial nerve canal in the oblique sagittal view of the temporal bone three-dimensional image are identified, and the anatomical positioning points include the posterior margin point of the vestibular window, the midpoint of the horizontal segment of the facial nerve, and the conical protuberance point; All the anatomical positioning points are linearly fitted to obtain an initial reference line; Based on the initial reference line, the vertical deviation value of each anatomical positioning point is calculated, and the median value of all the vertical deviation values is determined; Anatomical positioning points with a vertical deviation value more than three times the median value are marked as outliers, and all the outliers and non-outliers are assigned weights to form a weighted positioning point set; The weighted positioning point set is weighted and fitted to generate a first reference line.

[0008] Optionally, in the oblique sagittal view, the bony protuberance highest point of the promontorium is identified, and a straight line passing through the bony protuberance highest point and parallel to the skull base plane is generated as a second reference line, including: The bony eminence of the tympanic prominence is calibrated in the oblique sagittal view, and the highest pixel point corresponding to each longitudinal coordinate position in the bony eminence of the tympanic prominence is recorded, and the highest pixel point with the largest longitudinal coordinate value is selected as the highest point of the bony eminence of the tympanic prominence; In the axial view, a feature position point of the skull base bone structure is located, and the feature position point includes a central most concave point of the anterior cranial fossa and bilateral highest points of the middle cranial fossa; The central most concave point of the anterior cranial fossa and the bilateral highest points of the middle cranial fossa are connected to form a skull base reference surface; In the oblique sagittal view, an initial straight line passing through the highest point of the bony eminence of the tympanic prominence is generated based on the image horizontal axis, and the angle of the initial straight line is adjusted until the extension direction of the skull base reference surface in the three-dimensional space is consistent, so as to obtain an adjusted straight line, and the adjusted straight line is taken as a second reference line.

[0009] Optionally, the electrically evoked compound action potential signal is subjected to band-pass filtering processing to obtain a filtered electrically evoked compound action potential signal, including: The electrically evoked compound action potential signal is subjected to signal amplification and analog-to-digital conversion processing to generate a digital signal; According to a common frequency range of the electrically evoked compound action potential signal, a band-pass filtering frequency range is set, and the digital signal is subjected to filtering processing according to the band-pass filtering frequency range to obtain a filtered signal; The filtered signal is subjected to superposition averaging processing to obtain a filtered electrically evoked compound action potential signal.

[0010] Optionally, the electrically evoked compound action potential signal is subjected to signal amplification and analog-to-digital conversion processing to generate a digital signal, including: The waveform amplitude distribution of the electrically evoked compound action potential signal is analyzed to determine a peak amplitude range; According to the relative position relationship between the peak amplitude range and a preset amplitude interval, a signal amplification gain coefficient is selected; The electrically evoked compound action potential signal is subjected to amplification processing by using the signal amplification gain coefficient to obtain an amplified analog signal; The amplified analog signal is subjected to equal-interval sampling to obtain a plurality of sampling points, and a digital code of each sampling point is determined according to an analog amplitude value of each sampling point and in combination with a preset digital code interval; All digital codes are arranged according to time sequence to generate a digital signal.

[0011] Optionally, based on the telomere relative length, the oval window width, the included angle, and the filtered electrically evoked compound action potential signal, a cochlear implant suitability score of the presbycusis patient is calculated, and when the cochlear implant suitability score exceeds a suitability threshold, the presbycusis patient is determined as a candidate patient suitable for cochlear implantation, comprising: A feature amplitude value is extracted from the filtered electrically evoked compound action potential signal. According to a preset correlation degree, weight coefficients corresponding to the telomere relative length, the oval window width, the included angle, and the feature amplitude value are set, so as to calculate the cochlear implant suitability score of the presbycusis patient according to the weight coefficients. According to historical presbycusis patient data and clinical specific needs, a suitability threshold is set, and when the cochlear implant suitability score exceeds the suitability threshold, the presbycusis patient is determined as a candidate patient suitable for cochlear implantation.

[0012] In a second aspect, the present application provides a presbycusis cochlear implant candidate patient multi-modal screening system, comprising: A obtaining module is configured to obtain a telomere relative length of white blood cell DNA in a peripheral blood sample of a presbycusis patient, and a temporal bone three-dimensional image of the presbycusis patient. An analyzing module is configured to analyze the temporal bone three-dimensional image to obtain an oval window width and an included angle between a horizontal segment of a facial nerve and a tympanic eminence. A processing module is configured to obtain an electrically evoked compound action potential signal of an auditory nerve of the presbycusis patient under the action of a preset parameter electric stimulation, and perform a band-pass filtering processing on the electrically evoked compound action potential signal to obtain a filtered electrically evoked compound action potential signal. A calculating module is configured to calculate a cochlear implant suitability score of the presbycusis patient based on the telomere relative length, the oval window width, the included angle, and the filtered electrically evoked compound action potential signal, and determine the presbycusis patient as a candidate patient suitable for cochlear implantation when the cochlear implant suitability score exceeds a suitability threshold.

[0013] In a third aspect, the present application provides a computing device comprising a processing component and a storage component; the storage component stores one or more computer instructions; the one or more computer instructions are used to be called and executed by the processing component to implement a presbycusis cochlear implant candidate patient multi-modal screening method as described in the first aspect above.

[0014] In a fourth aspect, the present application provides a computer storage medium storing a computer program, which, when executed by a computer, implements the multi-modal screening method for a presbycusis cochlear implant candidate patient according to the first aspect.

[0015] In the present application, the relative length of telomeres of white blood cell DNA in a peripheral blood sample of a presbycusis patient and a temporal bone three-dimensional image of the presbycusis patient are obtained; the temporal bone three-dimensional image is analyzed to obtain the width of the oval window and the angle between the horizontal segment of the facial nerve and the promontorium; the electrically evoked compound action potential signal of the auditory nerve of the presbycusis patient under the action of electrical stimulation of a preset parameter is obtained, the electrically evoked compound action potential signal is subjected to band-pass filtering processing to obtain a filtered electrically evoked compound action potential signal; based on the relative length of telomeres, the width of the oval window, the angle, and the filtered electrically evoked compound action potential signal, the presbycusis patient's cochlear implant adaptability score is calculated, and when the cochlear implant adaptability score exceeds the adaptability threshold, the presbycusis patient is determined to be a candidate patient suitable for cochlear implantation. The technical solution provided in the present application obtains the relative length of telomeres of white blood cell DNA in the peripheral blood sample of the presbycusis patient, provides an objective basis at the molecular level for evaluating the degree of degeneration of the auditory system and the potential of neural plasticity after surgery; at the same time, the temporal bone three-dimensional image is obtained, which provides a spatial data basis for subsequent fine analysis of key anatomical structures, and the width of the oval window and the angle between the horizontal segment of the facial nerve and the promontorium are extracted, realizing quantitative description of the anatomical relationship of the key operation area and improving the accuracy of the feasibility judgment of the operation. At the same time, the signal-to-noise ratio of the target neural response signal is enhanced, and non-specific electrophysiological interference is excluded, so that the real-time functional response capability of the auditory nerve terminal to electrical stimulation is more truly reflected. The whole-chain comprehensive evaluation from the molecular aging state, local anatomical features to neural function response is realized, and the scientificity and individualization level of the candidate patient screening are improved.

[0016] Further, the present application proposes a set of standardized, visualized quantitative analysis procedures for the analysis process of the temporal bone three-dimensional image: the bony edges on both sides of the oval window are identified through the axial view and the vertical distance at the narrowest part is measured to determine the width of the oval window; in the oblique sagittal view, the first reference line representing the direction of the horizontal segment of the facial nerve is obtained by fitting the initial reference line and optimization, and the second reference line parallel to the skull base is constructed with the highest point of the promontorium, and finally the angle between the two reference lines is calculated as the spatial relationship index of the horizontal segment of the facial nerve and the promontorium. The problem of relying on subjective experience judgment and lacking unified quantitative standard in traditional image evaluation is solved, and the objectivity and spatial accuracy of the evaluation of the local anatomical structure of the middle ear are improved, providing more reliable technical support for predicting the difficulty of surgical operation and individualized anatomical risk.

[0017] These and other aspects of the present application will become more apparent from the following description. BRIEF DESCRIPTION OF DRAWINGS

[0018] In order to more clearly illustrate the technical solutions of the embodiments of the present application or the prior art, the following will briefly introduce the drawings needed to be used in the description of the embodiments or the prior art. Obviously, the drawings described below are only some of the embodiments of the present application, and the drawings can be obtained by those skilled in the art without creative labor.

[0019] Figure 1 A flow chart of a multi-modal screening method for senile deafness artificial cochlea implantation candidate patients provided by the present application; Figure 2 A structural schematic diagram of a multi-modal screening system for senile deafness artificial cochlea implantation candidate patients provided by the present application; Figure 3 A structural schematic diagram of a computing device provided by the present application. DETAILED DESCRIPTION

[0020] In order to make the person skilled in the art better understand the present application, the technical solutions in the embodiments of the present application will be described clearly and completely below in conjunction with the drawings in the embodiments of the present application.

[0021] In some of the processes described in the specification and the claims of the present application and the above-mentioned drawings, a plurality of operations appearing in a specific order, but it should be clearly understood that these operations can be executed or in parallel without the order appearing in the text, the serial numbers of the operations such as 101, 102, etc. are only used to distinguish different operations, and the serial numbers themselves do not represent any execution order. In addition, these processes can include more or less operations, and these operations can be executed in sequence or in parallel. It should be noted that the "first", "second" and the like in the text are used to distinguish different messages, devices, modules, etc., and do not represent the order of sequence, nor do the "first" and "second" represent different types.

[0022] The technical solutions in the embodiments of the present application will be described clearly and completely below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are only some of the embodiments of the present application, not all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative labor are within the scope of protection of the present application.

[0023] The application provides a multi-modal evaluation method, aiming to overcome the problem of single evaluation dimension and insufficient prediction ability caused by the fact that the prior art only relies on image anatomical features and indirect electrophysiological indicators. Although the prior scheme can preliminarily judge the feasibility of the surgical structure and the residual hearing state, it lacks quantitative characterization of the systematic biological aging process of the patient, and it is difficult to predict the differentiation of postoperative neural plasticity and hearing rehabilitation potential caused by aging differences between individuals. Therefore, the application combines the relative length of the telomere of white blood cell DNA in peripheral blood as a molecular marker of biological aging, and combines the fine analysis of key surgical anatomical parameters such as the width of the oval window and the angle between the horizontal segment of the facial nerve and the promontorium of the ear in the temporal bone three-dimensional image, to realize comprehensive and objective evaluation of the implantation adaptability of the patient, and improve the scientificity of candidate patient screening and the predictability of postoperative effect.

[0024] Figure 1 A flow chart of a multi-modal screening method for a candidate patient for cochlear implantation of presbycusis is provided for the embodiments of the application, as shown in Figure 1 The method comprises the following steps. Step 101: obtaining the relative length of the telomere of white blood cell DNA in the peripheral blood sample data of a presbycusis patient, and the three-dimensional image of the temporal bone of the presbycusis patient.

[0025] In this step, the presbycusis patient refers to an age-related hearing loss patient. The peripheral blood sample data refers to various types of information contained in the sample collected from the peripheral blood of the presbycusis patient. The relative length of the telomere refers to the relative ratio of the length of the telomere region in the white blood cell DNA to the length of the reference gene region. The three-dimensional image of the temporal bone refers to the image data obtained by three-dimensional scanning of the temporal bone of the patient through medical imaging technology.

[0026] In the embodiments of the application, the white blood cell DNA is extracted from the peripheral blood sample data of the presbycusis patient by molecular biology technology, and the relative length of the telomere is calculated by nucleic acid amplification and fluorescence detection technology, and the three-dimensional image of the temporal bone is generated by scanning the temporal bone of the patient through a medical imaging device.

[0027] Step 102: analyzing the three-dimensional image of the temporal bone to obtain the width of the oval window and the angle between the horizontal segment of the facial nerve and the promontorium of the ear.

[0028] In this step, the width of the oval window refers to the vertical distance of the narrowest part of the bony edge on both sides of the oval window in the temporal bone. The horizontal segment of the facial nerve refers to the part of the facial nerve that runs horizontally in the temporal bone. The angle refers to the angle formed between the reference line corresponding to the horizontal segment of the facial nerve and the reference line corresponding to the promontorium of the ear.

[0029] Step 103: obtaining the electrically evoked compound action potential signal of the auditory nerve of the presbycusis patient under the electrical stimulation of the preset parameter, and performing band-pass filtering processing on the electrically evoked compound action potential signal to obtain the filtered electrically evoked compound action potential signal.

[0030] In this step, the preset parameter refers to a stimulation-related parameter set before electrical stimulation of the auditory nerve. The electrically evoked compound action potential signal refers to a compound potential signal generated by the auditory nerve under the action of electrical stimulation. The filtered electrically evoked compound action potential signal refers to a signal obtained after band-pass filtering processing of the original electrically evoked compound action potential signal.

[0031] Step 104: Based on the relative length of the telomere, the width of the oval window, the included angle, and the filtered electrically evoked compound action potential signal, the cochlear implant adaptability score of the presbycusis patient is calculated. When the cochlear implant adaptability score exceeds the adaptability threshold, the presbycusis patient is determined as a candidate patient suitable for cochlear implantation.

[0032] In this step, the cochlear implant adaptability score refers to a comprehensive score calculated based on the relative length of the telomere, the width of the oval window, the included angle, and the filtered electrically evoked compound action potential signal. The adaptability threshold refers to a critical value for determining whether the cochlear implant adaptability score meets the standard. The candidate patient refers to a presbycusis patient determined to be suitable for cochlear implantation.

[0033] The embodiments of the present application realize the evaluation of the cochlear implant adaptability of the presbycusis patient by acquiring multi-modal data and performing comprehensive analysis, improve the accuracy and comprehensiveness of the screening, and provide a reliable basis for clinical surgical decision-making.

[0034] The present application provides a specific embodiment, step 102, the temporal bone three-dimensional image is analyzed to obtain the width of the oval window, the included angle between the horizontal segment of the facial nerve and the promontorium, and specifically includes the following steps: Step 201: Identify the bony edges on both sides of the oval window from the axial view of the temporal bone three-dimensional image, and calculate the vertical distance between the narrowest edges of the two bony edges, taking the vertical distance as the width of the oval window.

[0035] In this step, the axial view refers to a cross-sectional view obtained along the long axis direction of the human body in the temporal bone three-dimensional image. The bony edges on both sides of the oval window refer to the edge parts of the bony structures formed around the oval window, which are used to determine the anatomical boundaries of the width of the oval window.

[0036] In the embodiments of the present application, the axial view of the temporal bone three-dimensional image is processed by image segmentation technology to identify the bony edges on both sides of the oval window, and then the vertical distance between the narrowest edges of the two edges is measured by using a distance calculation tool, and the vertical distance is taken as the width of the oval window.

[0037] Step 202: According to the oblique sagittal view of the temporal bone three-dimensional image, an initial reference line is fitted, and based on the initial reference line, a first reference line is optimized and fitted.

[0038] In this step, the oblique sagittal view refers to a view obtained along an oblique sagittal plane in the three-dimensional image of the temporal bone. The initial reference line refers to a straight line preliminarily fitted based on the anatomical feature points of the horizontal segment of the facial nerve in the oblique sagittal view. The first reference line refers to a straight line obtained after optimizing and adjusting the initial reference line.

[0039] In the embodiments of the present application, the anatomical feature points of the horizontal segment of the facial nerve are extracted from the oblique sagittal view of the three-dimensional image of the temporal bone through feature extraction technology, the initial reference line is obtained by connecting the feature points using a straight line fitting method, and the first reference line is optimized and fitted by adjusting the angle and position of the initial reference line to make the reference line more consistent with the running trend of the horizontal segment of the facial nerve.

[0040] Step 203: identifying the highest bone protuberance of the promontory in the oblique sagittal view, and generating a straight line passing through the highest bone protuberance and parallel to the skull base plane as the second reference line.

[0041] In this step, the highest bone protuberance of the promontory refers to the point with the highest degree of protuberance in the bony structure of the promontory, which is a feature point for positioning the key position of the promontory. The second reference line refers to a straight line passing through the highest bone protuberance of the promontory and parallel to the skull base plane.

[0042] In the embodiments of the present application, the gray scale analysis technology is used to locate the promontory region in the oblique sagittal view, and the highest bone protuberance point in the vertical direction in the promontory region is selected as the highest bone protuberance point. The skull base plane is determined by plane fitting technology, and a straight line passing through the highest point and parallel to the skull base plane is generated as the second reference line.

[0043] Step 204: calculating the reference line included angle of the first reference line and the second reference line in the plane of the oblique sagittal view, and taking the reference line included angle as the included angle between the horizontal segment of the facial nerve and the promontory.

[0044] In this step, the reference line included angle refers to the angle formed by the first reference line and the second reference line in the plane of the oblique sagittal view, which is used to reflect the angle value of the spatial positional relationship between the horizontal segment of the facial nerve and the promontory.

[0045] In the embodiments of the present application, the angle calculation tool is used to measure the angle formed between the first reference line and the second reference line in the plane of the oblique sagittal view, and the angle is determined as the reference line included angle, which is taken as the included angle between the horizontal segment of the facial nerve and the promontory.

[0046] The embodiments of the present application extract the oval window width and the reference line included angle by analyzing the three-dimensional image of the temporal bone in multiple views, provide accurate anatomical parameters for evaluating the anatomical feasibility of cochlear implantation, and improve the reliability of anatomical data in the screening process.

[0047] The application provides an embodiment, step 202, fitting an initial reference line according to the oblique sagittal view of the temporal bone three-dimensional image, and optimizing fitting a first reference line based on the initial reference line, specifically comprising the following steps: Step 211: identifying the anatomical positioning points of the facial nerve canal bony boundary in the oblique sagittal view of the temporal bone three-dimensional image, wherein the anatomical positioning points comprise a posterior semicircular canal posterior edge point, a facial nerve horizontal segment midpoint and a pyramid protuberance point.

[0048] In this step, the anatomical positioning points of the facial nerve canal bony boundary refer to the position points with marks on the facial nerve canal bony boundary in the oblique sagittal view of the temporal bone three-dimensional image. The posterior semicircular canal posterior edge point refers to the edge position point of the posterior semicircular canal, which is an anatomical point for fitting the initial reference line. The facial nerve horizontal segment midpoint refers to the middle position point of the facial nerve horizontal segment. The pyramid protuberance point refers to the starting position point of the pyramid protuberance.

[0049] In the embodiment of the application, the facial nerve canal bony boundary in the oblique sagittal view is scanned, the edge position of the posterior semicircular canal is located as the posterior semicircular canal posterior edge point, the midpoint position of the facial nerve horizontal segment is located as the facial nerve horizontal segment midpoint, and the starting position of the pyramid protuberance is located as the pyramid protuberance point, thereby obtaining three anatomical positioning points.

[0050] Step 212: linear fitting all the anatomical positioning points to obtain the initial reference line.

[0051] In the embodiment of the application, the posterior semicircular canal posterior edge point, the facial nerve horizontal segment midpoint and the pyramid protuberance point are connected to generate a straight line passing through the three points, and the straight line is taken as the initial reference line.

[0052] Step 213: calculating the vertical deviation value of each anatomical positioning point based on the initial reference line, and determining the median value of all the vertical deviation values.

[0053] In this step, the vertical deviation value refers to the vertical distance of each anatomical positioning point to the initial reference line. The median value refers to the value at the middle position after all the vertical deviation values are sorted by size.

[0054] In the embodiment of the application, the vertical distance of each anatomical positioning point to the initial reference line is measured respectively, the distance is taken as the vertical deviation value, and the value at the middle position is taken as the median value after all the vertical deviation values are sorted.

[0055] Step 214: marking the anatomical positioning points with the vertical deviation value more than three times of the median value as outlier points, and assigning weights to all the outlier points and non-outlier points to form a weighted positioning point set.

[0056] In this step, outliers refer to anatomical positioning points whose vertical deviation values exceed three times the median value. Non-outliers refer to anatomical positioning points whose vertical deviation values do not exceed three times the median value. The weighted positioning point set refers to the combination of positioning points after assigning different weights to outliers and non-outliers.

[0057] In the embodiments of the present application, the size of each vertical deviation value is compared with the median value, and points exceeding three times the median value are marked as outliers. Different weights are assigned to outliers and non-outliers, respectively, and the weights of outliers are required to be lower than the weights of non-outliers. The combination forms a weighted positioning point set.

[0058] Step 215: Weighted fitting is performed on the weighted positioning point set to generate a first reference line.

[0059] In the embodiments of the present application, linear fitting is performed on the weighted positioning point set, and non-outliers occupy a greater influence weight in the fitting process to generate a new straight line. The straight line is taken as the first reference line.

[0060] The embodiments of the present application reduce the influence of outliers on the reference line by weighted fitting of the anatomical positioning points, improve the fitting degree of the first reference line with the horizontal segment of the facial nerve, provide a more accurate reference benchmark for subsequent angle calculation, and improve the reliability of anatomical parameter extraction.

[0061] The present application provides a specific embodiment, step 203, identifying the highest bony protuberance point of the promontorium in the oblique sagittal view, and generating a straight line passing through the highest bony protuberance point of the promontorium and parallel to the skull base plane as a second reference line, specifically comprising the following steps: Step 221: Marking the bony region of the promontorium in the oblique sagittal view and recording the highest pixel point corresponding to each longitudinal coordinate position in the bony region of the promontorium, and selecting the highest pixel point with the largest longitudinal coordinate value as the highest bony protuberance point of the promontorium.

[0062] In this step, the bony region of the promontorium refers to the bony structure region where the promontorium is located in the oblique sagittal view, and is a specific region for positioning the highest bony protuberance point. The highest pixel point refers to the point with the highest pixel position at each longitudinal coordinate position in the bony region of the promontorium.

[0063] In the embodiments of the present application, the boundaries of the bony region of the promontorium are delineated in the oblique sagittal view by image segmentation technology, and the region is scanned row by row to record the point with the highest pixel position at each longitudinal coordinate. The longitudinal coordinate values of all highest pixel points are compared, and the point with the largest value is determined as the highest bony protuberance point of the promontorium.

[0064] Step 222: Positioning the feature position points of the skull base bone structure in the axial view, the feature position points including the central most concave point of the cranial fossa, and the bilateral highest points of the middle cranial fossa.

[0065] In this step, the feature position point of the skull base bone structure refers to a position point on the skull base bone structure in the axial view that has a landmark. The central most concave point of the anterior cranial fossa refers to the lowest concave point of the central position of the anterior cranial fossa, reflecting a feature point of the anterior part of the skull base. The bilateral highest point of the middle cranial fossa refers to the highest position point on both sides of the middle cranial fossa.

[0066] In the embodiment of the present application, the contour of the skull base bone structure in the axial view is recognized by the edge detection technology, and the lowest concave point of the central position of the anterior cranial fossa is marked as the central most concave point of the anterior cranial fossa in the contour, and the highest position point on both sides of the middle cranial fossa is marked as the bilateral highest point of the middle cranial fossa.

[0067] Step 223: connecting the central most concave point of the anterior cranial fossa and the bilateral highest point of the middle cranial fossa to form a skull base reference plane.

[0068] In this step, the skull base reference plane refers to a plane formed by connecting the central most concave point of the anterior cranial fossa and the bilateral highest point of the middle cranial fossa.

[0069] In the embodiment of the present application, the central most concave point of the anterior cranial fossa and the bilateral highest point of the middle cranial fossa positioned in the axial view are connected in space, and a plane composed of three lines is formed, which is taken as the skull base reference plane.

[0070] Step 224: in the oblique sagittal view, an initial straight line passing through the highest point of the bony eminence of the tympanic prominence is generated based on the image horizontal axis, and the angle of the initial straight line is adjusted until it is consistent with the extension direction of the skull base reference plane in three-dimensional space, to obtain an adjusted straight line, which is taken as a second reference line.

[0071] In this step, the initial straight line refers to a straight line passing through the highest point of the bony eminence of the tympanic prominence in the oblique sagittal view and generated based on the image horizontal axis. The adjusted straight line refers to a straight line that is adjusted in angle and consistent with the extension direction of the skull base reference plane in three-dimensional space.

[0072] In the embodiment of the present application, the initial straight line passing through the highest point of the bony eminence of the tympanic prominence and parallel to the image horizontal axis is drawn in the oblique sagittal view, and the inclination angle of the initial straight line is adjusted by a spatial angle calculation tool, so that the extension direction of the straight line is consistent with the spatial trend of the skull base reference plane. The adjusted straight line is determined as the second reference line.

[0073] The embodiment of the present application provides a reliable spatial reference for the calculation of the angle between the horizontal segment of the facial nerve and the bony eminence of the tympanic prominence by positioning the highest point of the bony eminence of the tympanic prominence and generating a second reference line parallel to the skull base reference plane, thereby improving the accuracy and consistency of the extraction of anatomical parameters.

[0074] The application provides a specific embodiment, step 103, band-pass filtering the electrically induced compound action potential signal to obtain a filtered electrically induced compound action potential signal, specifically including the following steps: Step 301: Signal amplification and analog-digital conversion processing are performed on the electrically induced compound action potential signal to generate a digital signal.

[0075] In this step, the digital signal refers to a set of discrete digital quantities obtained after signal amplification and analog-digital conversion processing of the electrically induced compound action potential signal.

[0076] In the embodiment of the application, the signal amplifier is used to enhance the electrically induced compound action potential signal, and then the analog-digital conversion device is used to convert the amplified analog signal into discrete digital quantities to form the digital signal.

[0077] Step 302: According to the common frequency range of the electrically induced compound action potential signal, a band-pass filtering frequency range is set, and the digital signal is filtered according to the band-pass filtering frequency range to obtain a filtered signal.

[0078] In this step, the common frequency range refers to the frequency interval usually contained in the electrically induced compound action potential signal. The band-pass filtering frequency range refers to the filtering frequency interval set according to the common frequency range. The filtered signal refers to the signal obtained after the band-pass filtering processing of the digital signal.

[0079] In the embodiment of the application, the lower limit frequency and the upper limit frequency of the band-pass filtering are determined by analyzing the common frequency range of the electrically induced compound action potential signal, and the filter is used to process the digital signal to retain the signal components in the frequency range to obtain the filtered signal.

[0080] Step 303: Superimposed average processing is performed on the filtered signal to obtain a filtered electrically induced compound action potential signal.

[0081] In the embodiment of the application, the filtered signals collected multiple times are aligned in time sequence, the signal average value of each time point is calculated, and the average value set is taken as the filtered electrically induced compound action potential signal.

[0082] The embodiment of the application retains the effective components in the signal, reduces noise interference, improves the stability and reliability of the signal, and provides high-quality electrophysiological data for subsequent function evaluation by amplifying, converting, filtering and superimposed average processing of the electrically induced compound action potential signal.

[0083] The application provides a specific embodiment, step 301, signal amplification and analog-digital conversion processing are performed on the electrically induced compound action potential signal to generate a digital signal, specifically including the following steps: Step 311: analyze the waveform amplitude distribution of the electrically evoked compound action potential signal to determine the peak amplitude range.

[0084] In this step, the waveform amplitude distribution refers to the distribution of the amplitude values of the electrically evoked compound action potential signal with respect to time, and the amplitude data distribution used to determine the peak amplitude range. The peak amplitude range refers to the amplitude interval in which the peak values of the electrically evoked compound action potential signal are concentrated, and is used to select the key amplitude range of the signal amplification gain coefficient.

[0085] In the embodiments of the present application, the waveform of the electrically evoked compound action potential signal is scanned, the frequency and distribution interval of different amplitude values are counted, and the amplitude interval in which the peak values are concentrated is identified, and the interval is determined as the peak amplitude range.

[0086] Step 312: select the signal amplification gain coefficient according to the relative position relationship between the peak amplitude range and the preset amplitude interval.

[0087] In this step, the preset amplitude interval refers to the amplitude range suitable for signal amplification. The signal amplification gain coefficient refers to the proportional coefficient used for amplitude amplification of the electrically evoked compound action potential signal, and is used to adjust the signal amplitude to an appropriate range.

[0088] In the embodiments of the present application, the upper and lower limit difference between the peak amplitude range and the preset amplitude interval is compared to determine the corresponding signal amplification gain coefficient.

[0089] Step 313: amplify the electrically evoked compound action potential signal using the signal amplification gain coefficient to obtain an amplified analog signal.

[0090] In this step, the amplified analog signal refers to the analog signal obtained after the electrically evoked compound action potential signal is amplified by the signal amplification gain coefficient.

[0091] In the embodiments of the present application, the signal amplifier is used to multiply each amplitude value of the electrically evoked compound action potential signal by the signal amplification gain coefficient, so that the signal amplitude is proportionally increased to generate an amplified analog signal.

[0092] Step 314: equally interval sample the amplified analog signal to obtain a plurality of sampling points, and determine the digital code of each sampling point according to the analog amplitude value of each sampling point and in combination with a preset digital code interval.

[0093] In this step, the sampling point refers to a discrete point obtained by equally spaced sampling of the amplified analog signal. The analog amplitude value refers to the amplitude of the analog signal corresponding to the sampling point. The preset digital coding interval refers to a plurality of continuous amplitude intervals set in advance, each interval corresponding to a specific digital code. The digital code refers to a digital identifier obtained after matching the analog amplitude value with the preset digital coding interval.

[0094] In the embodiment of the present application, the amplified analog signal is collected at fixed time intervals, the analog amplitude value at each time is recorded to form a sampling point, and the analog amplitude value of each sampling point is matched with the preset digital coding interval to obtain the digital code of each sampling point.

[0095] Step 315: arranging all digital codes in time sequence to generate a digital signal.

[0096] In the embodiment of the present application, all digital codes are sequentially combined in the order of sampling time to form a digital signal containing time sequence information.

[0097] The embodiment of the present application selects the signal amplification gain coefficient dynamically and performs analog-to-digital conversion, so that the electrically evoked compound action potential signal retains effective signal characteristics and avoids signal distortion in the digitalization process, thereby improving the quality and accuracy of the digital signal.

[0098] The present application provides a specific embodiment, step 104, based on the relative length of the telomere, the width of the oval window, the included angle, and the filtered electrically evoked compound action potential signal, the cochlear implant adaptability score of the presbycusis patient is calculated, when the cochlear implant adaptability score exceeds the adaptability threshold, the presbycusis patient is determined as a candidate patient suitable for cochlear implantation, specifically including the following steps: Step 401: extracting a characteristic wave amplitude value from the filtered electrically evoked compound action potential signal.

[0099] In this step, the characteristic wave amplitude value refers to the amplitude value corresponding to the characteristic waveform peak extracted from the filtered electrically evoked compound action potential signal, which is a key electrophysiological indicator for calculating the cochlear implant adaptability score.

[0100] In the embodiment of the present application, the waveform of the filtered electrically evoked compound action potential signal is analyzed, the characteristic waveform peak is identified, the amplitude value corresponding to the peak is measured, and the amplitude value is determined as the characteristic wave amplitude value.

[0101] Step 402: according to the preset correlation degree, set the weight coefficients corresponding to the relative length of the telomere, the width of the oval window, the included angle, and the characteristic wave amplitude value, and calculate the cochlear implant adaptability score of the presbycusis patient according to the weight coefficients.

[0102] In this step, the preset correlation degree refers to the pre-set correlation strength between each index and the cochlear implant effect, which is used as a reference standard for assigning weight coefficients.

[0103] In the embodiments of the present application, the clinical correlation data of each index and the cochlear implant effect is analyzed, and the corresponding weight coefficients are assigned to the relative length of telomere, oval window width, angle and characteristic wave amplitude. The calculation formula is: cochlear implant adaptability score = (relative length of telomere x corresponding weight coefficient of relative length of telomere) + (oval window width x weight coefficient of oval window width) + (angle x weight coefficient of angle) + (characteristic wave amplitude x weight coefficient of characteristic wave amplitude). The values of each index are multiplied by the corresponding weight coefficients and then summed to obtain the cochlear implant adaptability score.

[0104] Step 403: According to the historical data of senile deaf patients and the specific needs of clinical practice, set an adaptability threshold. When the cochlear implant adaptability score exceeds the adaptability threshold, the senile deaf patient is determined to be a candidate patient suitable for cochlear implantation.

[0105] In this step, the historical data of senile deaf patients refers to the clinical data of senile deaf patients who have received cochlear implantation or related examinations in the past, which is used as reference data for setting the adaptability threshold. The specific requirements of clinical practice refer to specific requirements for the success rate, rehabilitation effect, risk control and other aspects of cochlear implantation surgery in clinical practice.

[0106] In the embodiments of the present application, the adaptability scores and postoperative effect data of senile deaf patients who have received cochlear implantation in the past are counted, and combined with the specific requirements of clinical practice for surgical success rate and rehabilitation expectation, an adaptability threshold is determined. The cochlear implant adaptability score of the current patient is compared with the threshold. If it exceeds, it is determined to be a candidate patient.

[0107] The embodiments of the present application realize comprehensive quantitative evaluation of the adaptability of senile deaf patients to cochlear implantation by weighted integration of multi-dimensional indexes and threshold setting based on clinical data, improve the scientificity and clinical adaptability of the screening results, and provide a reliable basis for screening candidate patients.

[0108] Figure 2 A structure diagram of a multi-modal screening system for senile deaf cochlear implant candidate patients is provided for the embodiments of the present application, as shown in FIG. 1, which includes: Figure 2 The acquisition module 21 is configured to acquire the relative length of telomere DNA in the peripheral blood sample data of the senile deaf patient, and the temporal bone three-dimensional image of the senile deaf patient.

[0109] ​The analysis module 22 is configured to analyze the three-dimensional image of the temporal bone to obtain an oval window width and an angle between a horizontal segment of the facial nerve and a promontory.

[0110] The processing module 23 is configured to obtain an electrically evoked compound action potential signal of the auditory nerve of the presbycusis patient under the electric stimulation of the preset parameter, and perform a band-pass filtering process on the electrically evoked compound action potential signal to obtain a filtered electrically evoked compound action potential signal.

[0111] The calculation module 24 is configured to calculate an artificial cochlea implant adaptability score of the presbycusis patient based on the relative length of the telomere, the oval window width, the angle, and the filtered electrically evoked compound action potential signal, and determine the presbycusis patient as a candidate patient suitable for the artificial cochlea implant when the artificial cochlea implant adaptability score exceeds an adaptability threshold.

[0112] Figure 2 The presbycusis artificial cochlea implant candidate patient multi-modal screening system can perform Figure 1 The presbycusis artificial cochlea implant candidate patient multi-modal screening method of the embodiment has the implementation principle and technical effects which will not be repeated. For the specific operation manner of each module and unit of the presbycusis artificial cochlea implant candidate patient multi-modal screening system in the above embodiment, the detailed description has been made in the embodiment related to the method, and will not be described in detail here.

[0113] In one possible design, Figure 2 The presbycusis artificial cochlea implant candidate patient multi-modal screening system of the embodiment can be implemented as a computing device, such as a computer. Figure 3 As shown, the computing device can include a storage component 31 and a processing component 32.

[0114] The storage component 31 stores one or more computer instructions, wherein the one or more computer instructions are called and executed by the processing component 32.

[0115] The processing component 32 is configured to perform the above Figure 1 The presbycusis artificial cochlea implant candidate patient multi-modal screening method of the embodiment.

[0116] The processing component 32 can include one or more processors to execute computer instructions to complete all or part of the steps in the above method. Of course, the processing component can also be one or more Application-Specific Integrated Circuits (ASICs), Digital Signal Processors (DSPs), Digital Signal Process Device (DSPD), Programmable Logic Devices (PLDs), Field Programmable Gate Arrays (FPGAs), controllers, microcontrollers, microprocessors or other electronic components, for executing the above method.

[0117] The storage component 31 is configured to store various types of data to support the operation of the terminal. The storage component can be implemented by any type of volatile or non-volatile storage devices or a combination thereof, such as Random Access Memory (RAM), Static Random-Access Memory (SRAM), Electrically Erasable Programmable Read-Only Memory (EEPROM), Erasable Programmable Read-Only Memory (EPROM), Programmable Read-Only Memory (PROM), Read-Only Memory (ROM), magnetic storage, flash memory, magnetic disk or optical disk.

[0118] Of course, the computing device can also include other components, such as an input / output interface, a display component, a communication component, etc.

[0119] The input / output interface provides an interface between the processing component and peripheral interface modules, which can be output devices, input devices, etc.

[0120] The communication component is configured to facilitate wired or wireless communication between the computing device and other devices, etc.

[0121] The computing device can be a physical device or an elastic computing host provided by a cloud computing platform, and the computing device can be a cloud server, and the processing component, the storage component, etc. can be basic server resources rented or purchased from the cloud computing platform.

[0122] The embodiment of the present application further provides a computer storage medium, which stores a computer program, and the computer program can realize the above-mentioned method when being executed by a computer. Figure 1 The embodiment shown in the figure is a multi-modal screening method for an elderly deaf person who is a candidate for cochlear implantation.

[0123] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working processes of the above-mentioned system, device and unit can refer to the corresponding processes in the foregoing method embodiments, and will not be described here.

[0124] The device embodiments described above are only schematic, and the units described as separate components can or can not be physically separated, and the components shown as units can or can not be physical units, that is, they can be located in one place, or can be distributed on multiple network units. Part or all of the modules can be selected according to actual needs to achieve the purpose of the embodiment scheme. Those skilled in the art can understand and implement without creative labor.

[0125] Through the description of the foregoing embodiments, those skilled in the art can clearly understand that each embodiment can be realized by means of software and a necessary general hardware platform, and of course, it can also be realized by hardware. Based on such understanding, the above technical solutions can be embodied in the form of a software product, which can be stored in a computer readable storage medium, such as a ROM / RAM, a magnetic disk, an optical disk, etc., and includes a plurality of instructions for causing a computer device (which can be a personal computer, a server, or a network device, etc.) to execute the method described in each embodiment or some parts of the embodiment.

[0126] Finally, it should be noted that: the above embodiments are only used to illustrate the technical solutions of the present application, and not to limit them; although the present application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that: it can still modify the technical solutions recorded in the foregoing embodiments, or make equivalent replacement for some technical features; and these modifications or replacements do not make the essence of the corresponding technical solutions deviate from the spirit and scope of the technical solutions of the embodiments of the present application.

Claims

1. A multimodal screening method for candidate patients with age-related hearing loss undergoing cochlear implantation, characterized in that, include: To obtain the relative telomere length of leukocyte DNA from peripheral blood samples of patients with age-related hearing loss, and three-dimensional images of the temporal bone of patients with age-related hearing loss; The three-dimensional image of the temporal bone was analyzed to obtain the width of the oval window and the angle between the horizontal segment of the facial nerve and the promontory. The electrically evoked compound action potential (EMP) signal of the auditory nerve of the elderly deaf patient under the action of electrical stimulation with preset parameters is obtained, and the EEP signal is bandpass filtered to obtain the filtered EEP signal. Based on the relative telomere length, the oval window width, the included angle, and the filtered electrically evoked compound action potential signal, the cochlear implantation fitness score of the elderly deaf patient is calculated. When the cochlear implantation fitness score exceeds the fitness threshold, the elderly deaf patient is identified as a candidate patient suitable for cochlear implantation.

2. The method according to claim 1, characterized in that, The three-dimensional image of the temporal bone was analyzed to obtain the width of the oval window and the angle between the horizontal segment of the facial nerve and the promontory, including: Identify the bony edges on both sides of the oval window from the axial view of the three-dimensional image of the temporal bone, and calculate the vertical distance at the narrowest point of the two bony edges, using the vertical distance as the width of the oval window; Based on the oblique sagittal view of the three-dimensional image of the temporal bone, an initial reference line is fitted, and based on the initial reference line, a first reference line is fitted and optimized. In the oblique sagittal view, the highest point of the bony prominence of the promontory is identified, and a straight line passing through the highest point of the bony prominence and parallel to the plane of the skull base is generated as a second reference line. Calculate the angle between the first reference line and the second reference line in the plane of the oblique sagittal view, and use the angle between the reference lines as the angle between the horizontal segment of the facial nerve and the promontory.

3. The method according to claim 2, characterized in that, Based on the oblique sagittal view of the three-dimensional image of the temporal bone, an initial reference line is fitted, and based on the initial reference line, a first reference line is optimized and fitted, including: The anatomical landmarks of the bony boundary of the facial nerve canal are identified in the oblique sagittal view of the three-dimensional image of the temporal bone. The anatomical landmarks include the posterior margin of the vestibular window, the midpoint of the horizontal segment of the facial nerve, and the origin of the pyramidal protuberance. All anatomical positioning points are fitted with straight lines to obtain the initial reference line; Based on the initial reference line, calculate the vertical deviation value of each anatomical positioning point, and determine the median value of all vertical deviation values; Anatomical localization points with vertical deviation values ​​exceeding three times the median value are marked as outliers, and weights are assigned to all outliers and non-outliers to form a weighted set of localization points. The weighted set of positioning points is weighted and fitted to generate the first reference line.

4. The method according to claim 2, characterized in that, In the oblique sagittal view, the highest point of the bony prominence of the promontory is identified, and a straight line passing through the highest point of the bony prominence and parallel to the plane of the skull base is generated as a second reference line, including: In the oblique sagittal view, the bony region of the promontory is marked, and the highest pixel point corresponding to each vertical coordinate position in the bony region of the promontory is recorded. The highest pixel point with the largest vertical coordinate value is selected as the highest point of the bony prominence of the promontory. Locate the characteristic location points of the skull base bone structure in the axial view, including the most concave point in the center of the anterior cranial fossa and the highest points on both sides of the middle cranial fossa. Connect the most concave point in the center of the anterior cranial fossa with the highest points on both sides of the middle cranial fossa to form a reference plane for the skull base; In the oblique sagittal view, an initial straight line is generated passing through the highest point of the bony prominence of the promontory, with the horizontal axis of the image as the reference. The angle of the initial straight line is adjusted until it is consistent with the extension direction of the skull base reference plane in three-dimensional space, and the adjusted straight line is used as the second reference line.

5. The method according to claim 1, characterized in that, The electrically evoked composite action potential signal is bandpass filtered to obtain a filtered electrically evoked composite action potential signal, including: The electrically induced composite action potential signal is amplified and converted from analog to digital to generate a digital signal. Based on the common frequency range of the electrically induced composite action potential signal, a bandpass filter frequency range is set, and the digital signal is filtered according to the bandpass filter frequency range to obtain the filtered signal. The filtered signal is then subjected to superposition and averaging to obtain the filtered electrically induced composite action potential signal.

6. The method according to claim 4, characterized in that, The electrically induced composite action potential signal is amplified and converted from analog to digital to generate a digital signal, including: Analyze the waveform amplitude distribution of the electrically induced composite action potential signal to determine the peak amplitude range; The signal amplification gain coefficient is selected based on the relative positional relationship between the peak amplitude range and the preset amplitude interval; The electrically induced composite action potential signal is amplified using the aforementioned signal amplification gain coefficient to obtain an amplified analog signal. The amplified analog signal is sampled at equal intervals to obtain multiple sampling points, and the digital code of each sampling point is determined based on the analog amplitude value of each sampling point and a preset digital encoding range. All digital codes are arranged in chronological order to generate a digital signal.

7. The method according to claim 1, characterized in that, Based on the relative telomere length, the oval window width, the included angle, and the filtered electrically evoked complex action potential signal, a cochlear implantation fitness score is calculated for the elderly patient with hearing loss. When the cochlear implantation fitness score exceeds a fitness threshold, the elderly patient with hearing loss is identified as a suitable candidate for cochlear implantation, including: The characteristic amplitude value is extracted from the filtered electrically induced composite action potential signal; Based on a preset correlation level, weighting coefficients are set for the relative telomere length, the oval window width, the included angle, and the characteristic wave amplitude value, respectively, so as to calculate the cochlear implantation suitability score of the elderly deaf patients based on the weighting coefficients. Based on historical data on elderly patients with hearing loss and specific clinical needs, an fitness threshold is set. When the cochlear implantation fitness score exceeds the fitness threshold, the elderly patient with hearing loss is identified as a candidate suitable for cochlear implantation.

8. A multimodal screening system for candidate patients with age-related hearing loss undergoing cochlear implantation, characterized in that, include: The acquisition module is used to acquire the relative telomere length of leukocyte DNA in peripheral blood samples from patients with age-related hearing loss, as well as three-dimensional images of the temporal bone of patients with age-related hearing loss. The analysis module is used to analyze the three-dimensional image of the temporal bone to obtain the width of the oval window and the angle between the horizontal segment of the facial nerve and the promontory. The processing module is used to acquire the electrically evoked compound action potential signal of the auditory nerve of the elderly deaf patient under the action of electrical stimulation with preset parameters, and to perform bandpass filtering on the electrically evoked compound action potential signal to obtain the filtered electrically evoked compound action potential signal. The calculation module is used to calculate the cochlear implantation fitness score of the elderly deaf patient based on the relative telomere length, the oval window width, the included angle, and the filtered electrically evoked compound action potential signal. When the cochlear implantation fitness score exceeds the fitness threshold, the elderly deaf patient is identified as a candidate patient suitable for cochlear implantation.

9. A computing device, characterized in that, It includes a processing component and a storage component; the storage component stores one or more computer instructions; the one or more computer instructions are invoked and executed by the processing component to implement the multimodal screening method for candidate patients for cochlear implantation in the elderly as described in any one of claims 1 to 7.

10. A computer storage medium, characterized in that, The device contains a computer program that, when executed by a computer, implements a multimodal screening method for candidate patients for cochlear implantation in the elderly as described in any one of claims 1 to 7.

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