A method for failure restoration re-treatment decision based on dynamic occlusion analysis

Abstract

The application discloses a failure restoration retreatment decision method based on dynamic occlusion analysis, which constructs a four-dimensional virtual biomechanical model containing patient anatomical structure and dynamic function through multi-modal data fusion, can embed patient real three-dimensional mandibular movement trajectory to simulate functional movement, break through the static analysis blind area, and reduce the dynamic interference missed diagnosis rate; relying on the quantitative indexes and threshold values of the occlusal contact displacement amount, occlusal contact distribution symmetry and occlusal adjustment amount of the maximum intercuspidation and centric relation position, replacing the doctor's experience judgment, improving the objectivity, repeatability and accuracy of the failure restoration retreatment decision, avoiding excessive or insufficient adjustment and grinding; through virtual pre-adjustment, the treatment effect is preformed, the irreversible operation risk is avoided, and the number of patient rechecks and trial and error cost are reduced; meanwhile, the four-dimensional virtual model can be connected to the design and production of the final restoration, and the accuracy, safety and efficiency of the failure restoration retreatment are improved.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of oral prosthetic medicine, and particularly relates to a failure prosthesis re-treatment decision-making method based on dynamic occlusion analysis. BACKGROUND

[0002] In full-arch fixed prosthesis treatment, some prostheses may fail due to improper initial design, manufacturing errors or changes in the patient's oral environment, etc., which may manifest as occlusal discomfort, prosthesis damage, periodontal problems of abutment teeth or temporomandibular joint disorders, etc. For such failed prostheses, how to make accurate re-treatment decisions is a core challenge faced by clinicians.

[0003] At present, the closest prior art in the clinic is to use a mechanical articulator for diagnostic occlusal analysis (DOA). This technical solution usually includes the following steps: (1) using materials such as silicone rubber or wax to obtain jaw relationship records in the patient's mouth; (2) obtaining upper and lower plaster models by taking impressions and pouring; (3) using face bows and jaw records to transfer and fix the plaster models to a mechanical semi-adjustable or fully adjustable articulator; (4) the doctor subjectively judges the occlusal contact points, early contact points and occlusal interference points by the marks left on the model by occlusal paper and manually simulating limited mandibular movements (such as forward and backward extension, lateral movement).

[0004] However, this traditional method has the following problems:

[0005] Single analysis dimension, lack of dynamic function evaluation: the mechanical articulator cannot accurately reproduce the individualized and complex three-dimensional mandibular movement trajectory of the patient, especially the non-midline movement of the condyle in cases of joint morphological abnormalities. Its analysis is based on static or simplified movement simulation, which cannot perform true dynamic functional occlusal analysis, resulting in missed diagnosis of occlusal interference during movement.

[0006] High subjectivity, lack of objective quantitative standards: the identification of occlusal contact points, the judgment of interference point severity and the decision of adjustment amount completely depend on the doctor's naked eye observation and hand experience, lacking objective data support (such as the precise three-dimensional coordinates of the interference point and the required adjustment depth in μm), resulting in inaccurate and non-reproducible diagnostic results with large differences between different doctors.

[0007] Long error chain, overall accuracy difficult to guarantee: from taking jaw records in the mouth, taking impressions, pouring to model transfer and upper articulator, each step of operation introduces errors, with high cumulative error, poor stability and reproducibility. This often leads to significant deviations between the occlusion on the articulator and the real situation in the patient's mouth, and using unreliable analysis results to guide treatment may even exacerbate the problem.

[0008] It is impossible to realize the prediction and simulation before treatment: doctors cannot accurately simulate and visualize the effect of the adjustment before implementing irreversible clinical operations (such as adjusting natural teeth or prostheses), the treatment risk is high, and the trial and error cost is large. SUMMARY

[0009] The embodiment of the application provides a failure prosthetic re-treatment decision method based on dynamic occlusion analysis, and precise, quantitative and predictable failure prosthetic re-treatment decision is realized.

[0010] In order to achieve the above-mentioned purpose, the technical scheme of the embodiment of the application is:

[0011] In a first aspect, the embodiments of the present application provide a failure prosthesis retreatment decision method based on dynamic occlusion analysis, comprising: collecting multi-modal data of a target patient at the intercuspal position and the centric relation position, the multi-modal data including intraoral three-dimensional scanning data, CBCT image data, dynamic occlusion analysis data, facial scanning, and clinical symptom and medical history data; the dynamic occlusion analysis data includes individualized mandibular movement trajectory data of the target patient; time synchronization and spatial registration are performed on the multi-modal data to construct a four-dimensional virtual biomechanical model including the prosthesis, adjacent teeth, opposing teeth, jaw bones, joints, and individualized mandibular movement trajectory of the target patient; the four-dimensional virtual biomechanical model is loaded into a virtual articulator, and the individualized mandibular movement trajectory of the target patient is loaded into the virtual articulator to simulate mandibular functional movement and realize dynamic occlusion analysis; the dynamic occlusion analysis results include the adaptability of the prosthesis and the abutment, the marginal fit, the occlusion interference, and the abnormal occlusion force distribution; based on the dynamic occlusion analysis results, whether adjustment of the articulator is needed is determined according to a quantitative decision rule, the quantitative decision rule including: taking the maxilla as the reference, registering the mandibular positions at the intercuspal position and the centric relation position, comparing the occlusal contact displacement and the occlusal contact distribution symmetry between the intercuspal position and the centric relation position, and determining whether the adjustment condition is met, including: if the occlusal contact displacement at the intercuspal position and the centric relation position is less than or equal to a preset displacement threshold and the occlusal contact distribution is uniform, no adjustment of the articulator is needed; if the occlusal contact displacement at the intercuspal position and the centric relation position is less than the preset displacement threshold and the occlusal contact distribution is uneven, or the displacement is greater than the preset displacement threshold and the occlusal contact distribution is uneven, or the displacement is not available, the adjustment amount required to achieve uniform occlusal contact is calculated; the adjustment operation is simulated in the four-dimensional virtual biomechanical model, wherein, when the displacement is less than or equal to the preset displacement threshold, the simulation of the adjustment operation is performed at the original intercuspal position of the target patient; when the displacement is greater than the preset displacement threshold or the displacement is not available, the simulation of the adjustment operation is performed at the centric relation position; after the adjustment, the stability of the occlusal contact and the force distribution after the adjustment is verified; if the adjustment amount is within the preset adjustment amount range, an adjustment guidance scheme is generated; if the adjustment amount exceeds the preset adjustment amount range, it is determined that the adjustment cannot be directly performed, and a retreatment scheme including occlusal reconstruction or orthodontic treatment is generated.

[0012] In some possible implementations, the individualized mandibular movement trajectory data is acquired by an electromagnetic tracking system, an electronic facebow (Zebris), or an optical tracking system (Modjaw).

[0013] In some possible implementation manners, the multi-modal data is time-synchronized and spatially registered, and a four-dimensional virtual biomechanical model containing a target patient's restoration, adjacent teeth, opposite teeth, jaw bones, joints and individualized mandibular movement trajectory is constructed, including: accurately registering and fusing the multi-modal data in a unified coordinate system, constructing an integrated three-dimensional model containing the patient's restoration, adjacent teeth, opposite teeth, jaw bones and joints, and then embedding dynamic occlusal contact distribution information and individualized mandibular movement trajectory data to form a four-dimensional virtual biomechanical model with dynamic functions.

[0014] In some possible implementation manners, the dynamic occlusion analysis is implemented by a machine learning model, and a restoration failure risk score and a re-treatment suggestion are output; the re-treatment suggestion includes adjustment, rework or removal of the restoration; the machine learning model is a combination of a convolutional neural network (CNN) and a recurrent neural network (RNN / LSTM) and is used to process image-type occlusion data and time series movement data, respectively.

[0015] In some possible implementation manners, the adjustment guide scheme is output in at least one of the following manners: visualizing and highlighting the areas and adjustment amounts that need to be adjusted in a software interface; generating a graphic diagnosis report; outputting data to an augmented reality device and projecting the data to a real scene in the patient's mouth; and outputting data to a CAD / CAM system to directly manufacture a pre-adjustment restoration.

[0016] In some possible implementation manners, the method further includes: digital cross-registration, accurately aligning the diagnostic digital model with the old restoration and the working digital model after tooth preparation before and after removal of the restoration, to ensure stable transmission of the jaw position relationship.

[0017] In some possible implementation manners, the method further includes: performing clinical operations according to the adjustment guide scheme or the re-treatment scheme, and verifying the treatment effect through the four-dimensional virtual biomechanical model or a real-time detection device at the chair.

[0018] In some possible implementation manners, the clinical operations include the following stages: a first stage of intraoral adjustment, in which the existing restoration is finely adjusted according to the adjustment guide scheme; a second stage of transitional restoration, in which the old restoration with an undesirable shape is removed, a CAD / CAM temporary restoration is designed and manufactured based on the four-dimensional virtual biomechanical model, and the temporary restoration is observed for a preset adaptation period; and a third stage of final restoration, in which, after the stability of the temporary restoration is verified, a final restoration is designed and manufactured based on the four-dimensional virtual biomechanical model, and the final restoration replicates the stable occlusal relationship of the temporary restoration.

[0019] The one or more technical solutions provided in the embodiments of the present application have at least the following technical effects or advantages:

[0020] In the embodiment of the present application, a four-dimensional virtual biomechanical model containing patient's anatomical structure and dynamic function is constructed through multi-modal data fusion, and the core scheme of combining quantitative dynamic occlusion analysis and virtual pre-adjustment is used to solve the defects of the existing mechanical articulator technology: it can simulate functional movement by embedding the real three-dimensional mandibular movement trajectory of the patient, break through the static analysis blind area, and significantly reduce the dynamic articulation interference missed diagnosis rate; relying on the quantitative indicators such as occlusal contact displacement, occlusal contact distribution symmetry and adjustment amount of the crossbite and centric relation position, and clear threshold, the doctor's experience is replaced to improve the objectivity, repeatability and accuracy of the re-treatment decision, and to avoid excessive or insufficient adjustment; the treatment effect is preformed through virtual pre-adjustment to avoid irreversible operation risk, reduce the number of patient re-visits and trial and error cost, and the preformed result is highly consistent with the actual effect; at the same time, the four-dimensional virtual biomechanical model can be connected to the design and manufacture of the final restoration, and the accuracy, safety and efficiency of the re-treatment of the failed restoration are improved. BRIEF DESCRIPTION OF DRAWINGS

[0021] In order to more clearly illustrate the embodiments of the present application, the drawings needed to be used in the embodiments of the present application will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present application, and other drawings can be obtained by those skilled in the art without creative labor on the basis of these drawings.

[0022] Figure 1 A flowchart of a re-treatment method for a failed full-arch restoration in the prior art;

[0023] Figure 2 An embodiment flowchart of a failed restoration re-treatment decision method based on dynamic occlusion analysis provided by the present application;

[0024] Figure 3 A multi-modal data diagram in the embodiment of the present application;

[0025] Figure 4 A four-dimensional virtual biomechanical model diagram in the embodiment of the present application;

[0026] Figure 5 A dynamic simulation virtual adjustment processing decision diagram in the embodiment of the present application;

[0027] Figure 6 A CAD / CAM system output diagram in the embodiment of the present application;

[0028] Figure 7 A failed restoration re-treatment decision flowchart based on dynamic occlusion analysis in the embodiment of the present application;

[0029] Figure 8 A first diagnosis intraoral image;

[0030] Figure 9 For curved fault slice and joint CBCT / three-dimensional reconstruction schematic diagram;

[0031] Figure 10 For virtual gantry virtual adjustment and record adjustment amount schematic diagram;

[0032] Figure 11 For intraoral adjustment schematic diagram;

[0033] Figure 12 For transition repair stage schematic diagram;

[0034] Figure 13 For final restoration intraoral image;

[0035] Figure 14 For chair-side real-time detection dynamic occlusal contact schematic diagram. DETAILED DESCRIPTION

[0036] The technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are part of the embodiments of the present application, rather than all the embodiments of the present application. Based on the embodiments in the present application, all other embodiments obtained by a person of ordinary skill in the art without creative work fall within the scope of protection of the present application.

[0037] In the related description of the embodiments, the terms “include, contain, have” and the like are all open terms, which are generally preferred to be understood as containing but not limited to; the term “at least one” is generally preferred to be understood as one or more, wherein “more” refers to two or more; the term “at least one of” or the like refers to any combination of these terms, including any combination of single item or multiple items, for example, “at least one of a, b or c”, or “at least one of a, b and c”, which can represent a, b, c, a-b (i.e. a and b), a-c, b-c, or a-b-c, wherein a, b, and c can be single or multiple; the symbol “A / B” is used to describe the selection relationship of the associated objects, which generally represents the relationship of “or”.

[0038] In the following description of the embodiments, the terms used in the embodiments of the present application are only for the purpose of describing specific embodiments, and are not intended to limit the present application. The singular forms “a” and “the” used in the embodiments of the present application and the appended claims are also intended to include the plural forms, unless the context clearly indicates otherwise.

[0039] Those skilled in the art shall understand that, in the following description of the embodiments of the present application, the order of the serial numbers does not mean the order of execution, and part or all of the steps can be executed in parallel or in sequence, and the execution order of each process shall be determined according to its function and inherent logic, and shall not constitute any limitation on the implementation process of the embodiments of the present application.

[0040] Those skilled in the art shall understand that the numerical ranges in the embodiments of the present application shall be understood as also specifically disclosing each intermediate value between the upper limit and the lower limit of the range. Each smaller range between any stated value or stated range of values and any other stated value or stated range of values is also included within the present application. The upper and lower limits of these smaller ranges can be independently included or excluded from the range.

[0041] Unless otherwise specified, the technical / scientific terms used herein have the same meaning as generally understood by those skilled in the art to which the present application belongs. Although only preferred methods and materials are described herein, any methods and materials similar or equivalent to those described herein can also be used in the implementation or testing of the present application. All documents mentioned in the specification are incorporated by reference to disclose and describe the methods and / or materials related to the documents. In the event of any conflict between the content of the specification and any incorporated document, the content of the specification shall prevail.

[0042] In order to illustrate the technical solutions of the present application, the following will be described by specific embodiments.

[0043] In full-arch fixed prosthetic treatment, partial prostheses may fail due to improper initial design, manufacturing errors, or changes in the patient's oral environment, etc., resulting in discomfort, prosthetic damage, periodontal problems, or temporomandibular joint disorders. For such failed prostheses, how to make accurate re-treatment decisions is a core challenge faced by clinicians.

[0044] Currently, the closest prior art in clinical practice is to use a mechanical articulator for diagnostic occlusal analysis (DOA). See Figure 1 , and Figure 1 is a schematic diagram of the re-treatment method process for failed full-arch prostheses in the prior art. Among them, A is a facebow, B is a transfer table, C is a schematic diagram of the use of a traditional mechanical articulator (maxillo-mandibular body, condylar ball, incisal guide pin, plaster model, occlusal wax), D is an occlusal high point impression of the upper plaster model, and E is an occlusal high point impression of the lower plaster model.

[0045] The technical solution generally comprises the following steps: (1) using materials such as silicone rubber or wax to record the jaw position relationship in the patient's mouth; (2) obtaining upper and lower jaw plaster models by taking a mold and pouring a mold; (3) using a face bow and jaw position record to transfer and fix the plaster models to a mechanical semi-adjustable or fully adjustable articulator; (4) the doctor subjectively judges the occlusal contact points, early contact points and articulator interference points by the marks left on the model by the occlusal paper and manually simulates limited mandibular movements (such as forward and backward extension, lateral movement).

[0046] However, the traditional method has the following problems:

[0047] Single analysis dimension, lack of dynamic function evaluation: the mechanical articulator cannot accurately reproduce the individualized and complex three-dimensional mandibular movement trajectory of the patient, especially the non-midline movement of the condyle in cases of abnormal joint morphology, and the analysis is based on static or simplified movement simulation, which cannot perform true dynamic functional occlusion analysis, resulting in missed diagnosis of articulator interference during movement.

[0048] High subjectivity, lack of objective quantitative standard: the identification of occlusal contact points, the judgment of interference points and the decision of adjustment amount completely depend on the naked eye observation and experience of the doctor, and lack of objective data support (such as accurate three-dimensional coordinates of interference points and required adjustment depth μm value), resulting in inaccurate and non-reproducible diagnosis results, and large differences between different doctors.

[0049] Long error chain, overall precision difficult to guarantee: from taking jaw position record in the mouth, taking mold, pouring mold to model transfer and upper articulator, each operation will introduce error, and the cumulative error is high, with poor stability and repeatability. This often leads to significant deviation between the occlusion on the articulator and the real situation in the patient's mouth, and the unreliable analysis results may even exacerbate the problem.

[0050] Cannot realize prediction and simulation before treatment: the doctor cannot accurately simulate and visualize the effect of adjustment before implementing irreversible clinical operations (such as adjusting natural teeth or prostheses), and the treatment risk is high and the trial and error cost is large.

[0051] Therefore, the embodiments of the present application provide a failure prosthetic re-treatment decision method based on dynamic occlusion analysis, which realizes precise, quantitative and predictable failure prosthetic re-treatment decision.

[0052] Figure 2 An embodiment process schematic diagram of a failure prosthetic re-treatment decision method based on dynamic occlusion analysis provided by the present application is shown in Figure 2 The above method can comprise:

[0053] S101, collect multi-modal data of the target patient in the intercuspal position and the centric relation position, the multi-modal data including intraoral three-dimensional scanning data, CBCT image data, dynamic occlusion analysis data, facial scanning data, and clinical symptom and medical history data; the dynamic occlusion analysis data including individualized mandibular movement trajectory data of the target patient;

[0054] It should be noted that the maximum intercuspation (MI) position refers to the position in which the upper and lower cusps have the maximum area of contact and the occlusion is the tightest, which is the main functional position for daily chewing; the centric relation (CR) position refers to the position of the lower jaw when the temporomandibular joint is in the physiological center, which is independent of tooth contact and is the reference position for evaluating occlusal relationship. When the two positions are coordinated, the occlusal function is more stable.

[0055] In some embodiments, the individualized mandibular movement trajectory data is acquired by an electromagnetic tracking system, an electronic facebow, or an optical tracking system.

[0056] Specifically, the intraoral three-dimensional scanning data can be obtained by an intraoral scanner, such as CEREC, iTero, etc., to obtain the three-dimensional data of the surface morphology of the patient's dentition, gums, and existing restorations, which is used to restore the fine structure of the teeth and restorations.

[0057] The CBCT image data can use cone beam computed tomography technology to obtain three-dimensional tomographic images of hard tissues such as jaw bones, temporomandibular joints, and tooth roots, providing an anatomical basis for bone structure analysis and evaluation of the adaptability of restorations to abutments.

[0058] The core of the dynamic occlusion analysis data includes individualized mandibular movement trajectory data of the target patient and synchronous occlusal force and electromyography data, wherein the individualized mandibular movement trajectory data can be collected by a special motion capture system, and specifically can be selected from: a Zebris Jaw Motion Analyzer system based on ultrasonic sensors, which has a sampling frequency of 100-200 Hz and a spatial accuracy of ±0.1 mm, can synchronously record the three-dimensional movement trajectory of the lower jaw and the distribution of occlusal contact force, and is suitable for routine functional motion analysis. Or it can also be based on the Modjaw system of optical infrared tracking (sampling frequency 333 Hz, spatial accuracy ±0.03 mm, can capture high-speed chewing, complex lateral movement, etc. without distortion, especially suitable for patients with abnormal joint function); electromyography data can be collected by surface electrode electromyography (EMG), and the electrodes are attached to the masseter muscle and the anterior bundle of the temporal muscle, with a sampling frequency of ≥1000 Hz to capture the high-frequency dynamic characteristics of muscle activity during occlusion.

[0059] Clinical symptoms and history data can be obtained through structured questionnaires and clinical examination records, including the length of time of prosthesis use, the location and degree of occlusal discomfort, the history of temporomandibular joint clicking / pain, and previous treatment experience, which can provide clinical background for etiological analysis.

[0060] For example, see Figure 3 as shown, Figure 3 is a schematic diagram of multi-modal data in the embodiments of the present application, wherein a is a schematic diagram of an intraoral scanner digitized impression, b is a schematic diagram of joint and dentition CBCT image, and c is a schematic diagram of mandibular movement tracing and electromyography measurement (using Zebris / 4D observation instrument Modjaw).

[0061] S102, time synchronization and spatial registration of multi-modal data are performed to construct a four-dimensional virtual biomechanical model containing the target patient's prosthesis, adjacent teeth, opposing teeth, jaw bone, joint, and individualized mandibular movement trajectory;

[0062] In some embodiments, to ensure the consistency and relevance of multi-modal data, a data synchronization strategy of time synchronization and spatial synchronization can be used for adjustment.

[0063] The time synchronization includes using an external synchronization signal to achieve hardware-level time alignment for devices that support hardware triggering, such as mandibular movement analyzers and electromyography instruments, with a synchronization accuracy of microseconds, eliminating data timestamp deviation; for devices that do not support hardware triggering, clock calibration is performed through a software built-in precision time protocol (PTP) or network time protocol (NTP) to achieve microsecond-level time alignment, thereby ensuring the timing matching of dynamic movement and electromyographic activity.

[0064] The spatial synchronization includes a dual strategy of landmark point matching and anatomical feature registration. Markers with radioresistance and reflective properties are pasted on the patient's face, making them clearly visible in CBCT images, intraoral scanning data, and dynamic motion capture, serving as a spatial reference. At the same time, anatomical feature points (such as tooth cusp points, proximal contact points, condylar apex points, etc.) are manually or semi-automatically selected on different data sets, and the Iterative Closest Point (ICP) algorithm is used to achieve precise alignment of multi-modal data in a unified coordinate system.

[0065] In some embodiments, the four-dimensional virtual biomechanical model containing the target patient's prosthesis, adjacent teeth, opposing teeth, jaw bone, joint, and individualized mandibular movement trajectory is constructed, including:

[0066] Multimodal data are precisely registered and fused in a unified coordinate system to construct an integrated three-dimensional model that includes the patient's restoration, adjacent teeth, opposing teeth, jawbone, and joint. Dynamic occlusal force distribution information and individualized mandibular movement trajectory data are then embedded to form a four-dimensional virtual biomechanical model with dynamic functions.

[0067] Specifically, firstly, all data undergoes preprocessing and initial coordinate system alignment for coarse registration. Based on the initial frames of data from all modalities (CBCT, intraoral 3D scan data, facial scans, and dynamic tracking systems), common fiducial markers are identified. Least squares or Procrustes analysis is used to calculate the optimal spatial transformation matrix (including rotation and translation) for precise alignment of the marker coordinates. Alternatively, the operator can manually or semi-automatically select a series of corresponding anatomical feature points (such as cusps, proximal contact points, pits and fissures, etc.) on different datasets. The system calculates the transformation matrix based on these paired point sets as auxiliary verification or preliminary coarse registration.

[0068] Subsequently, based on coarse registration, registration is performed using the shared anatomical structures between datasets, followed by precise matching using the ICP algorithm to optimize the nearest point distance error. Generally, the dataset with the highest accuracy (usually intraoral scan data) is used as a reference, while datasets with lower accuracy or different ranges, such as CBCT-reconstructed dental models or the static maxillary portion of dynamic data, are iteratively rotated and translated using the ICP algorithm to minimize the nearest point distance error between the two model surfaces. This process uses a kd-tree to accelerate the nearest point search structure and introduces a point-to-pair filtering strategy based on normal consistency to improve registration robustness, ultimately achieving sub-millimeter spatial alignment between dynamic data and the intraoral scan dental arch model.

[0069] The registered multimodal data are integrated, merging the intraoral scan restoration / tooth model and the CBCT jaw / joint model, deleting overlapping parts, and retaining key details such as restoration edges and articular surfaces; at the same time, the model is simplified, balancing computing power and detail accuracy, to form an integrated three-dimensional model that includes the restoration, adjacent teeth, jawbone, and joint.

[0070] Finally, using the timestamps of the dynamic data as a reference, the mandibular movement trajectory (which includes 6 degrees of freedom: 3 translations + 3 rotations) is embedded frame by frame into the 3D model according to the time sequence to simulate real mandibular movements such as protrusion and lateralization, and to mark key positions such as centric relation and intercuspal position, forming a 4D model (3D + time, i.e., the four-dimensional virtual biomechanical model in this embodiment of the invention). Figure 4 As shown, Figure 4 This is a schematic diagram of a four-dimensional virtual biomechanical model in an embodiment of the present invention.

[0071] In some embodiments, the construction of a four-dimensional virtual biomechanical model may further include: adding a mapping of occlusal contact distribution.

[0072] Specifically, finite element analysis (FEA) can be used to map occlusal contact distribution data onto the tooth surface, simulate the real material properties of teeth and restorations, load dynamic occlusal force data, and display the occlusal stress distribution using a heat map, giving the model both motion simulation and mechanical analysis functions.

[0073] In some embodiments, during the multimodal data fusion process, it is necessary to address the inherent differences between heterogeneous data in a targeted manner, including: for the resolution difference between CBCT data and intraoral scan data, adjusting the data accuracy to a uniform level through voxel resampling, and combining Gaussian filtering to smooth the details and achieve matching of the two types of data in spatial resolution; for motion artifacts in dynamic trajectory data caused by unconscious patient movements or equipment acquisition errors, using the Kalman filter algorithm to smooth the signal and remove noise, effectively eliminating trajectory jumps or jitter, and ensuring the continuity and authenticity of dynamic motion data.

[0074] S103, a four-dimensional virtual biomechanical model is loaded into a virtual articulator, and the individualized mandibular movement trajectory of the target patient is loaded into the virtual articulator to simulate mandibular functional movement and realize dynamic occlusion analysis; the dynamic occlusion analysis results include the fit between the prosthesis and the abutment tooth, the marginal occlusion, occlusal interference and abnormal distribution of occlusal force;

[0075] In some embodiments, dynamic occlusion analysis is implemented through a machine learning model, which outputs a prosthesis failure risk score and a retreatment recommendation; the retreatment recommendation includes adjustment, redoing, or removal of the prosthesis; the machine learning model is a combination of convolutional neural networks and recurrent neural networks, used to process image-based occlusion data and time-series motion data, respectively.

[0076] See Figure 5 As shown, Figure 5 This is a schematic diagram illustrating the dynamic simulation virtual articulation decision-making process in this embodiment of the invention. Specifically, firstly, the constructed four-dimensional virtual biomechanical model is loaded into the virtual articulation system. This system can reproduce the basic functions of a mechanical articulation, such as jaw fixation and motion simulation. It also imports the individualized mandibular motion trajectory data of the target patient (such as the aforementioned 6-DOF time series) through a digital interface to accurately simulate the patient's daily functional motion scenarios, including centric occlusion, protrusion, lateral movement, and mastication. Simultaneously, it records dynamic parameters such as the contact sequence between the restoration and the abutment teeth, relative displacement of the jawbone, and changes in occlusal force during the movement.

[0077] Based on this, a combined model is used to analyze the differences in data types. Convolutional Neural Networks (CNNs) are used to process image-type data, such as occlusal contact heatmaps and 3D visualization images of prosthesis edge fit, extracting geometric features, such as edge gap distribution and contact point morphology, through multi-layer convolution and pooling operations. Recurrent Neural Networks (LSTMs) are used to process time-series data, such as mandibular movement trajectory and occlusal force variation curves over time, capturing motion features. The outputs of the two models are fused through a fully connected layer to form a comprehensive decision vector.

[0078] In some embodiments, the model can be trained using more than 100 successful and unsuccessful clinical repair cases, each containing multimodal data (CBCT, intraoral scan, motion trajectory, occlusion, clinical diagnosis results); three types of core features are extracted from the data: including geometric features (marginal fit, fit gap), mechanical features (occlusal force asymmetry index, interference point force value), and motion features (CR-MI displacement, motion smoothness).

[0079] S104. Based on the dynamic occlusion analysis results, determine whether occlusion adjustment is needed according to quantitative decision rules. The quantitative decision rules include: using the maxilla as a reference, registering the mandibular position at the intercuspal position and the centric position, comparing the occlusal contact displacement and symmetry of the occlusal contact distribution between the two positions, and determining whether the occlusion adjustment conditions are met. These conditions include: if the occlusal contact displacement between the intercuspal position and the centric position is less than a preset displacement threshold and the occlusal contact distribution is uniform, then no occlusion adjustment is needed; if the occlusal contact displacement between the intercuspal position and the centric position is less than a preset displacement threshold and the occlusal contact distribution is uneven, or the displacement is greater than a preset displacement threshold and the occlusal contact distribution is uneven, or the displacement is unavailable, then calculate the amount of occlusion adjustment required to achieve uniform occlusal contact.

[0080] Specifically, the quantitative decision-making process in step S104 revolves around two core indicators: first, the occlusal contact displacement between CR and MI (i.e., the three-dimensional spatial deviation of the tooth contact points between the two jaw positions, including the comprehensive deviation in the anterior-posterior, left-right, and vertical directions); and second, the symmetry of the occlusal contact distribution. The preset displacement threshold is set based on clinical evidence-based data, for example, it can be set to 1 mm (this threshold has been validated by numerous cases and can effectively distinguish between physiological deviations and pathological abnormalities).

[0081] If the CR-MI occlusal contact displacement is ≤1mm and the occlusal contact distribution is uniform, it indicates that the occlusal relationship conforms to the physiologically stable state and there is no obvious occlusal interference, and it is determined that no adjustment is needed. If the CR-MI occlusal contact displacement is ≤1mm and the occlusal contact is significantly uneven, or the CR-MI occlusal contact displacement is >1mm and the occlusal contact distribution is uneven, or the CR-MI displacement is unavailable, then it is determined that adjustment is needed, and the virtual adjustment amount required to achieve uniform occlusal contact is calculated based on dynamic occlusal analysis data. Specifically, the height difference and force deviation between the occlusal interference point and the ideal contact position in the virtual model can be used as a basis to accurately calculate the thickness of the tooth / restoration tissue to be removed at each location.

[0082] S105 simulates occlusal adjustment in a four-dimensional virtual biomechanical model. When the displacement is less than or equal to a preset displacement threshold, the simulated adjustment is performed at the original intercuspal position of the target patient. When the displacement exceeds the preset threshold or is unavailable, the simulated adjustment is performed at the centric relation position. After adjustment, the stability of the occlusal contact and its distribution is verified. If the adjustment is within the preset range, an adjustment guidance plan is generated. If the adjustment exceeds the preset range, it is determined that direct adjustment is not possible, and a multidisciplinary retreatment plan including occlusal splint treatment, occlusal reconstruction, or orthodontic treatment is generated.

[0083] Specifically, firstly, simulated grinding is performed in a four-dimensional virtual biomechanical model: based on the grinding amount calculated in step S104 above, the target area to be ground is located in the model, such as the restoration or tooth tissue at the premature contact point or occlusal interference site. The grinding operation is simulated using digital tools, and the distribution of occlusal contact points, occlusal force value and changes in mandibular movement trajectory after grinding are recorded simultaneously.

[0084] The subsequent verification of the occlusal adjustment effect can include three indicators: whether the occlusal contact is uniform after adjustment, whether the occlusal force distribution is symmetrical, and whether the mandibular movement is smooth, to ensure that the occlusal relationship after adjustment meets the physiological functional requirements, and to compare it with the virtual adjustment to verify the accuracy of the analysis.

[0085] The treatment plan is based on a preset adjustment range, which typically has a clinically safe threshold of 0.2-0.5 mm. This range ensures that occlusal interference is eliminated while avoiding excessive grinding that could damage healthy teeth or restorations. If the simulated adjustment falls within this range, the system generates an adjustment guidance plan, including the three-dimensional coordinates of the teeth requiring adjustment, the depth of each adjustment, and the order of operations, presented visually with highlighted heatmaps and numerical annotations. If the adjustment exceeds this range, direct adjustment is deemed too risky, potentially leading to restoration perforation, dentin exposure, secondary occlusal disturbances, or even temporomandibular joint disorder. In this case, a retreatment plan is generated, recommending occlusal splinting, occlusal reconstruction, or orthodontic treatment based on the specific cause, along with a virtual pre-simulation comparison of treatment effects.

[0086] In some embodiments, the tuning guidance scheme is output in at least one of the following ways:

[0087] The software interface visually highlights the area requiring grinding and the amount of adjustment.

[0088] Generate a text and image diagnostic report;

[0089] The data is output to an augmented reality device and projected onto the patient's mouth;

[0090] Output data to a CAD / CAM system to directly create a pre-fitted restoration.

[0091] For example, see Figure 6 As shown, Figure 6 The CAD / CAM system output diagram in this embodiment of the invention includes functional and aesthetic design, transition repair, and final repair diagrams.

[0092] In some embodiments, the above method may further include: digital cross-registration, whereby, at nodes before and after restoration removal, the diagnostic digital model containing the old restoration is precisely aligned with the working digital model after tooth preparation to maintain the stability of the occlusal relationship. Before removing the old restoration, a diagnostic digital model containing the old restoration, adjacent teeth, and occlusal relationship is obtained through intraoral scanning; after removal and completion of tooth preparation, a working digital model showing the morphology of the prepared teeth, the remaining dentition, and soft tissue is obtained through scanning again.

[0093] In some embodiments, the above method may further include: performing clinical procedures according to the treatment guidance plan or retreatment plan, and verifying the treatment effect through a four-dimensional virtual biomechanical model or chairside real-time monitoring device.

[0094] The clinical procedure includes the following stages:

[0095] Phase 1: Intraoral occlusal adjustment, which involves fine-tuning the existing restorations according to the occlusal adjustment guidelines;

[0096] Phase 2: Transitional repair, removal of the poorly shaped old prosthesis, design and fabrication of a CAD / CAM temporary prosthesis based on a four-dimensional virtual biomechanical model, and observation of the preset adaptation period after wearing;

[0097] The third stage: final restoration. After the temporary restoration has been verified to be stable, the final restoration is designed and fabricated based on a four-dimensional virtual biomechanical model. The final restoration replicates the stable occlusal relationship of the temporary restoration.

[0098] In some embodiments, and in extreme cases, multidisciplinary collaborative treatment is required, using the aforementioned four-dimensional virtual biomechanical model for occlusal splinting, occlusal reconstruction, or orthodontic treatment. For example, when failed restorations are accompanied by complex temporomandibular joint problems, malocclusion, or poor periodontal conditions, multidisciplinary collaboration involving prosthodontics, temporomandibular joint specialists, orthodontics, and periodontology is necessary. The four-dimensional virtual biomechanical model can serve as a digital bridge for cross-departmental communication, providing precise evidence for the development of collaborative treatment plans.

[0099] In this invention, by introducing individualized mandibular movement trajectory data, precise simulation of the patient's mandibular function in virtual space is achieved. This reveals dynamic interference that cannot be detected by static analysis, significantly reducing the rate of missed diagnoses. By quantitatively calculating CR-MI displacement, adjustment amount, and asymmetry in occlusal force distribution, objective and repeatable decision-making criteria for "whether adjustment is needed" are provided, replacing purely empirical judgment and making decisions more accurate and reliable. The digital workflow (intraoral scanning, digital jaw position transfer) greatly shortens the error chain, and the overall accuracy of data transfer is higher than traditional manual transfer methods, laying the foundation for precision treatment. The virtual pre-adjustment step allows doctors to simulate the adjustment effect an unlimited number of times without performing any actual manipulation on the patient, predicting treatment outcomes in advance and greatly reducing clinical risks and treatment costs.

[0100] The method of this invention will be described below with reference to a specific embodiment.

[0101] like Figure 7 As shown, Figure 7 This is a schematic diagram of the decision-making process for retreatment of failed restorations based on dynamic occlusion analysis in an embodiment of the present invention. In practical application, it includes the following:

[0102] For example, a male patient visited the prosthodontics department complaining of unstable occlusion. He reported undergoing "occlusal reconstruction" treatment at a private clinic a year prior, which included the placement of multiple temporary fillings / crowns and an implant. He was dissatisfied with the functional and aesthetic results of the restorations and wished to have them redone.

[0103] Clinical examination (such as) Figure 8As shown in the image, multiple temporary restorations were found to be poorly shaped, damaged, and with loose margins, indicating poor oral hygiene. Occlusal analysis revealed occlusion instability, with contact points mainly concentrated on the right posterior teeth, indicating occlusal interference. Lateral deviation of the mandible was observed during forceful biting. Imaging examinations (CBCT, MRI) were also performed. Figure 9 As shown, the patient's left temporomandibular joint (TMJ) shows old degenerative changes, with a slightly smaller condyle and a concave surface, but the articular disc is basically in a normal position and is currently in a relatively stable period, with only occasional clicking sounds.

[0104] Digital diagnosis and design using the methods of this invention specifically include:

[0105] (1) Determine the centric relation (CR): Find a repeatable physiological position of the mandible for the patient through muscle depolarization.

[0106] (2) Data acquisition and fusion: A digital model of the teeth was obtained by intraoral scanning and combined with the mandibular movement trajectory tracking data to construct a digital dynamic occlusion model of the patient on a virtual articulator.

[0107] (3) Virtual tuning (e.g.) Figure 10 As shown in the simulation analysis in the software, it was found that the actual CR-MI displacement in this case was less than 1 mm (the guide pin height was reduced by about 0.7 mm), but the occlusal contact was significantly uneven. After virtually adjusting the grinding amount of specific teeth (#14-#17, #21, #24-#27) by 0.2-0.4 mm, a stable and uniform occlusal contact could be obtained. This proves that adjusting the existing restoration is a feasible solution.

[0108] The treatment process includes the following stages:

[0109] The first stage, the intraoral adjustment stage, includes: making fine adjustments to the existing restorations directly inside the mouth based on the virtual design. Figure 11 For images of occlusal contact after intraoral adjustment, see [link / reference]. Figure 11 As shown, after adjustment, the bite contact becomes more uniform and stable, and the mandibular movement trajectory is also smoother.

[0110] The second stage, the transitional restoration stage, included the removal of the old restorations due to their poor morphology, which, even after adjustment, failed to meet the requirements. Using the previously obtained digital data, new CAD / CAM temporary restorations were designed and fabricated. After wearing the temporary teeth, the patient experienced initial improvement in appearance and function, and underwent a 6-month adaptation observation period to ensure the joint and muscles were stable and comfortable under the new occlusion. Follow-up examinations showed improvement in joint position. Figure 12 As shown, Figure 12 A is a schematic diagram of the 3D ablation of the transitional prosthesis, B is an intraoral image of the transitional prosthesis, and C is a CBCT scan of the joint 6 months after the transitional prosthesis.

[0111] The third stage, the final restoration stage, includes: after the temporary tooth has proven stable, the final restoration is fabricated (using materials such as zirconia crowns and glass-ceramic). The design of the final tooth completely replicates the stable occlusal relationship of the temporary tooth. After wearing the tooth, the occlusion is stable, the function is good, and the aesthetics are significantly improved. Specifically... Figure 13 As shown, Figure 13 This is an intraoral image of the final restoration.

[0112] Phase Four: Follow-up Results. A follow-up examination 16 months post-surgery showed the restoration was intact and mandibular function was normal. Figure 14 As shown, Figure 14 This is a schematic diagram for real-time detection of dynamic bite contact at the chairside.

[0113] This case demonstrated a precise diagnosis of the restoration failure through digital occlusal analysis (virtual articulator, mandibular movement tracking, and simulated condylar / incisal point movements), guiding subsequent articulation adjustment and restoration design. A phased treatment strategy (articulation adjustment first, followed by observation with temporary teeth, and finally, placement of the final restoration) successfully resolved the complex occlusal issues, restoring the patient's oral function and aesthetics, and promoting joint adaptation and stability.

[0114] The various embodiments in this specification are described in a progressive manner. For the same or similar parts between the various embodiments, please refer to each other. Each embodiment focuses on describing the differences from other embodiments.

[0115] The above embodiments are only used to illustrate the technical solutions of this application, and are not intended to limit this application. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some or all of the technical features therein. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of this application.

Claims

1. A method for failure restoration re-treatment decision based on dynamic occlusion analysis, characterized in that, The application relates to a method for guiding occlusal adjustment of a patient, comprising the following steps: collecting multi-modal data of the patient in an intercuspal position and a centric relation position, wherein the multi-modal data comprises intraoral three-dimensional scanning data, CBCT image data, dynamic occlusion analysis data, facial scanning data and clinical symptom and history data; the dynamic occlusion analysis data comprises individualized mandibular movement trajectory data of the patient; performing time synchronization and spatial registration on the multi-modal data to construct a four-dimensional virtual biomechanical model comprising a restoration of the patient, adjacent teeth, opposite teeth, a jaw bone, a joint and the individualized mandibular movement trajectory; loading the four-dimensional virtual biomechanical model into a virtual articulator, loading the individualized mandibular movement trajectory of the patient into the virtual articulator to simulate mandibular functional movement and realize dynamic occlusion analysis; the dynamic occlusion analysis result comprises adaptability of the restoration and an abutment, marginal tightness, occlusion interference and abnormal occlusion force distribution; judging whether occlusal adjustment is needed based on the dynamic occlusion analysis result and according to a quantitative decision rule, wherein the quantitative decision rule comprises: taking the maxilla as a reference, registering the mandibular positions in the intercuspal position and the centric relation position, comparing occlusal contact displacement and occlusal contact distribution symmetry between the two positions to judge whether the occlusal adjustment condition is met, including: if the displacement is less than or equal to a preset displacement threshold value and the occlusal contact distribution is uniform, no occlusal adjustment is needed; if the displacement is less than the preset displacement threshold value and the occlusal contact distribution is uneven, or the displacement is greater than the preset displacement threshold value and the occlusal contact distribution is uneven, or the displacement is unavailable, the required occlusal adjustment amount to achieve uniform occlusal contact is calculated; simulating the occlusal adjustment operation in the four-dimensional virtual biomechanical model, wherein when the displacement is less than or equal to the preset displacement threshold value, the simulation of the occlusal adjustment operation is performed in the recorded original intercuspal position of the patient; when the displacement is greater than the preset displacement threshold value or the displacement is unavailable, the simulation of the occlusal adjustment operation is performed in the centric relation position; after the occlusal adjustment, the stability of the occlusal contact and the occlusal contact force distribution is verified; if the occlusal adjustment amount is within a preset occlusal adjustment amount range, an occlusal adjustment guidance scheme is generated; if the occlusal adjustment amount exceeds the preset occlusal adjustment amount range, it is determined that the occlusal adjustment cannot be directly performed, and a re-treatment scheme comprising an occlusal plate treatment, occlusal reconstruction or orthodontic treatment is generated. The individualized mandibular movement trajectory data is collected by an electromagnetic tracking system, an electronic facebow or an optical tracking system. The four-dimensional virtual biomechanical model comprising the restoration of the patient, the adjacent teeth, the opposite teeth, the jaw bone, the joint and the individualized mandibular movement trajectory is constructed by: accurately registering and fusing the multi-modal data in a unified coordinate system to construct an integrated three-dimensional model comprising the restoration of the patient, the adjacent teeth, the opposite teeth, the jaw bone and the joint, and then embedding dynamic occlusal contact distribution information and the individualized mandibular movement trajectory data to form a four-dimensional virtual biomechanical model with dynamic functions. ​ ​ ​ 2. The method of claim 1, wherein, ​ 3. The method of claim 2, wherein, ​ ​ 4. The method of claim 3, wherein, The dynamic occlusion analysis is implemented by a machine learning model, which outputs a restoration failure risk score and a retreatment recommendation; the retreatment recommendation includes occlusal adjustment, redoing or removing the restoration; the machine learning model is a combination of a convolutional neural network and a recurrent neural network, which are used to process image-based occlusion data and time series motion data, respectively.

5. The method of claim 4, wherein, The occlusal adjustment guidance scheme is output in at least one of the following ways: Visualize the highlighted areas and adjustment amounts in the software interface; Generate a graphic-text diagnosis report; Output data to an augmented reality device and project it into the patient's mouth; Output data to a CAD / CAM system to directly manufacture a pre-adjusted restoration.

6. The method of claim 5, wherein, The method further comprises digital cross-registration, which accurately aligns the diagnostic digital model with the old restoration and the working digital model after tooth preparation, ensuring stable transmission of jaw position relationship.

7. The method of claim 1, wherein, The method further comprises performing clinical operations according to the occlusal adjustment guidance scheme or the retreatment scheme, and verifying the treatment effect through the four-dimensional virtual biomechanical model or real-time detection equipment at the chair.

8. The method of claim 7, wherein, The clinical operation includes the following stages: First stage: intraoral occlusal adjustment, fine occlusal adjustment of the existing restoration according to the occlusal adjustment guidance scheme; Second stage: transitional restoration, remove the old restoration with poor morphology, design and manufacture a CAD / CAM temporary restoration based on the four-dimensional virtual biomechanical model, and observe the pre-set adaptation period after wearing; Third stage: final restoration, after the stability of the temporary restoration is verified, design and manufacture a final restoration based on the four-dimensional virtual biomechanical model, the final restoration replicates the stable occlusal relationship of the temporary restoration.

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