Failure restoration retreatment decision-making method based on dynamic occlusion analysis

Abstract

The invention discloses a failure restoration retreatment decision-making method based on dynamic occlusion analysis, and the method comprises the steps: constructing a four-dimensional virtual biomechanical model which comprises a patient anatomical structure and a dynamic function through multi-modal data fusion, and enabling the model to be embedded into a real three-dimensional mandibular movement track of a patient to simulate functional movement, thereby breaking through a static analysis blind area, and achieving the real three-dimensional mandibular movement of the patient. The missed diagnosis rate of dynamic interference is reduced; based on quantitative indexes and thresholds such as occlusal contact displacement, occlusal contact distribution symmetry and adjustment quantity of the maximum tooth tip staggering position and the median relation position, experience judgment of doctors is replaced, objectivity, repeatability and accuracy of failure repair and retreatment decision are improved, and excessive or insufficient adjustment is avoided; the treatment effect rehearsal is realized through virtual presetting, the irreversible operation risk is avoided, and the number of times of re-visit and the trial and error cost of a patient are reduced; and meanwhile, the four-dimensional virtual model can be connected with transition and design and manufacturing of a final restoration, so that the accuracy, safety and efficiency of retreatment of a failed restoration are improved.

Description

Technical Field

[0001] This application relates to the field of oral prosthodontics, and in particular to a decision-making method for the retreatment of failed prostheses based on dynamic occlusal analysis. Background Technology

[0002] In fixed prosthodontic treatment of the entire dental arch, some restorations may fail due to improper initial design, fabrication errors, or changes in the patient's oral environment. This can manifest as occlusal discomfort, restoration damage, periodontal problems in the abutment teeth, or temporomandibular joint disorder. For these failed restorations, making accurate retreatment decisions is a core clinical challenge.

[0003] Currently, the closest existing technology in clinical practice is diagnostic occlusal analysis (DOA) using a mechanical mandrel. This technique typically includes the following steps: (1) obtaining a jaw position record in the patient's mouth using materials such as silicone rubber or wax; (2) obtaining a plaster model of the upper and lower jaws through impression taking and casting; (3) transferring and fixing the plaster model to a mechanical semi-adjustable or fully adjustable mandrel using a facebow and jaw position record; (4) the doctor subjectively judges the occlusal contact point, premature contact point, and occlusal interference point by using the imprint left on the model by occlusal paper and manually simulating limited mandibular movements (such as protrusion, extension, and lateral movement).

[0004] However, this traditional method has the following problems: The analysis is limited in scope and lacks dynamic functional assessment: Mechanical mandibular frames cannot accurately reproduce the individualized and complex three-dimensional mandibular movement trajectory of patients, especially the non-central movement of the condyle in cases of joint morphology abnormalities. Their analysis is based on static or minimally simplistic motion simulations and cannot perform true dynamic functional occlusion analysis, leading to missed diagnoses of mandibular interference during movement.

[0005] The diagnosis is highly subjective and lacks objective quantitative standards: the identification of occlusal contact points, the judgment of the severity of interference points, and the decision on the amount of adjustment all rely on the doctor's visual observation and tactile experience, lacking objective data support (such as the precise three-dimensional coordinates of interference points and the required adjustment depth in μm), resulting in inaccurate and non-reproducible diagnostic results and large differences between different doctors.

[0006] The error chain is long, making it difficult to guarantee overall accuracy: from intraoral jaw positioning and recording, impression taking, and molding to model transfer and articulation, each step introduces errors, resulting in high cumulative errors and poor stability and repeatability. This often leads to a significant deviation between the occlusion on the articulator and the actual situation in the patient's mouth, and using unreliable analysis results to guide treatment may actually exacerbate the problem.

[0007] Unable to predict and simulate before treatment: Doctors cannot accurately simulate and visualize the effects of adjustments before performing irreversible clinical procedures (such as grinding natural teeth or restorations), resulting in high treatment risks and high trial-and-error costs. Summary of the Invention

[0008] This application provides a method for decision-making on the retreatment of failed restorations based on dynamic occlusion analysis, thereby achieving precise, quantitative, and predictable decision-making on the retreatment of failed restorations.

[0009] To achieve the above objectives, the technical solution of this invention is as follows: In a first aspect, embodiments of the present invention provide a method for decision-making regarding the retreatment of failed restorations based on dynamic occlusal analysis, comprising: acquiring multimodal data of the target patient at the intercuspal and centric relation positions, the multimodal data including intraoral three-dimensional scan data, CBCT image data, dynamic occlusal analysis data, facial scan data, and clinical symptom and medical history data; the dynamic occlusal analysis data including individualized mandibular movement trajectory data of the target patient; performing temporal synchronization and spatial registration of the multimodal data to construct a model including the target patient's restoration, adjacent teeth, opposing teeth, jawbone, joint, and individual... A four-dimensional virtual biomechanical model of mandibular movement trajectory was constructed. This model was then loaded onto a virtual articulator, where the individualized mandibular movement trajectory of the target patient was loaded to simulate mandibular functional movement and achieve dynamic occlusion analysis. The results of the dynamic occlusion analysis included the fit between the prosthesis and abutment teeth, marginal occlusion, occlusal interference, and abnormal occlusal force distribution. Based on the dynamic occlusion analysis results, a quantitative decision-making rule was used to determine whether occlusal adjustment was necessary. This rule included: using the maxilla as a reference, registering the mandibular position at the intercuspal position and the centric relation position, and comparing... The occlusal contact displacement and symmetry of the occlusal contact distribution between the two positions of intercuspal and centric relation are used to determine whether the adjustment conditions are met. These conditions include: if the occlusal contact displacement between the intercuspal and centric positions is less than or equal to a preset displacement threshold and the occlusal contact distribution is uniform, then no adjustment is needed; if the occlusal contact displacement between the intercuspal and centric positions 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 unavailable, the adjustment amount required to achieve uniform occlusal contact is calculated; in four dimensions... The virtual biomechanical model simulates occlusal adjustment. 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 is greater than the preset displacement threshold or the displacement is unavailable, the simulated adjustment is performed at the centric relation position. After adjustment, the stability of occlusal contact and force distribution is verified. If the adjustment is within the preset adjustment range, an adjustment guidance plan is generated. If the adjustment exceeds the preset adjustment range, it is determined that direct adjustment is not possible, and a retreatment plan including occlusal reconstruction or orthodontic treatment is generated.

[0010] In some possible implementations, individualized mandibular motion trajectory data is acquired through electromagnetic tracking systems, electronic face bows (Zebris), or optical tracking systems (Modjaw).

[0011] In some possible implementations, multimodal data is synchronized in time and registered in space to construct a four-dimensional virtual biomechanical model that includes the target patient's restoration, adjacent teeth, opposing teeth, jawbone, joint, and individualized mandibular motion trajectory. This includes: accurately registering and fusing multimodal data 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; and then embedding dynamic occlusal contact distribution information and individualized mandibular motion trajectory data to form a four-dimensional virtual biomechanical model with dynamic functions.

[0012] In some possible implementations, dynamic occlusion analysis is achieved 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 (CNN) and recurrent neural networks (RNN / LSTM) to process image-based occlusion data and time-series motion data, respectively.

[0013] In some possible implementations, the adjustment guidance scheme is output in at least one of the following ways: visually highlighting the area to be adjusted and the amount of adjustment in the software interface; generating a graphic diagnostic report; outputting data to an augmented reality device and projecting it onto the patient's intraoral space; or outputting data to a CAD / CAM system to directly create a pre-adjusted prosthesis.

[0014] In some possible implementations, the method also includes: digital cross-registration, which precisely aligns the diagnostic digital model with the old restoration with the working digital model after tooth preparation before and after restoration removal to ensure stable transfer of jaw position relationships.

[0015] In some possible implementations, the method also includes: performing clinical procedures according to the adjustment guidance or retreatment plan, and verifying the treatment effect through a four-dimensional virtual biomechanical model or chairside real-time monitoring equipment.

[0016] In some possible implementations, the clinical procedure includes the following stages: Stage 1: Intraoral occlusal adjustment, where the existing prosthesis is finely adjusted according to the occlusal adjustment guidelines; Stage 2: Transitional restoration, where the poorly shaped old prosthesis is removed, and a CAD / CAM temporary prosthesis is designed and fabricated based on a four-dimensional virtual biomechanical model, with a pre-set adaptation period observed after use; Stage 3: Final restoration, where, after the temporary prosthesis has been verified to be stable, a final prosthesis is designed and fabricated based on a four-dimensional virtual biomechanical model, and the final prosthesis replicates the stable occlusal relationship of the temporary prosthesis.

[0017] One or more technical solutions provided in the embodiments of the present invention have at least the following technical effects or advantages: In this embodiment of the invention, a four-dimensional virtual biomechanical model incorporating the patient's anatomical structure and dynamic functions is constructed through multimodal data fusion. Combined with a core solution of quantitative dynamic occlusal analysis and virtual pre-adjustment, this invention specifically addresses the shortcomings of existing mechanical articulation techniques: it can embed the patient's real three-dimensional mandibular movement trajectory to simulate functional movement, overcoming the blind spots of static analysis and significantly reducing the rate of missed diagnoses due to dynamic articulation interference; relying on quantitative indicators and clear thresholds such as the amount of occlusal contact displacement, symmetry of occlusal contact distribution, and adjustment amount at the intercuspal and centric positions, it replaces the doctor's experience-based judgment, improving the objectivity, repeatability, and accuracy of retreatment decisions and avoiding over- or under-adjustment; through virtual pre-adjustment, treatment effect can be previewed, avoiding irreversible operational risks, reducing the number of patient follow-up visits and trial-and-error costs, and the preview results highly match the actual results; simultaneously, the four-dimensional virtual biomechanical model can connect the design and fabrication of transitional and final restorations, improving the accuracy, safety, and efficiency of retreatment of failed restorations. Attached Figure Description

[0018] To more clearly illustrate the embodiments of the present invention, the accompanying drawings used in the embodiments of the present invention will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0019] Figure 1 This is a schematic diagram of the existing treatment process for failed full dental arch restorations. Figure 2 A schematic flowchart illustrating an embodiment of a decision-making method for re-treatment of failed prostheses based on dynamic occlusion analysis provided for the implementation of this invention; Figure 3 This is a schematic diagram of multimodal data in an embodiment of the present invention; Figure 4 This is a schematic diagram of the four-dimensional virtual biomechanical model in an embodiment of the present invention; Figure 5 This is a schematic diagram of dynamic simulation virtual adjustment and decision-making in an embodiment of the present invention; Figure 6 A schematic diagram of the CAD / CAM system output in an embodiment of the present invention; Figure 7 This is a schematic diagram of the decision-making process for retreatment of failed prostheses based on dynamic occlusion analysis in an embodiment of the present invention. Figure 8 Images taken intraorally during the initial consultation; Figure 9Schematic diagram of curved tomographic section and CBCT / 3D reconstruction of joints; Figure 10 A schematic diagram showing the virtual adjustment of the virtual frame and the recording of the adjustment amount; Figure 11 This is a diagram illustrating intraoral administration of acetaminophen. Figure 12 This is a schematic diagram of the transitional repair phase; Figure 13 The final intraoral image of the restoration; Figure 14 This is a schematic diagram for real-time detection of dynamic bite contact at the chairside. Detailed Implementation

[0020] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of this application. All other embodiments obtained by those skilled in the art based on the embodiments of this application without creative effort are within the scope of protection of this application.

[0021] In the relevant descriptions of this embodiment, the terms "including," "containing," and "possessing" are all open terms and are generally understood to include but not be limited to; the term "at least one" is generally understood to mean one or more, where "multiple" refers to two or more; the term "at least one of the following" or similar expressions refer to any combination of these items, including any combination of single or multiple items, for example, "at least one of a, b, or c", or "at least one of a, b, and c", which can all mean: a, b, c, ab (i.e., a and b), ac, bc, or abc, where a, b, and c can be single or multiple; the symbol "A / B" is used to describe the selection relationship of associated objects, generally indicating an "or" relationship.

[0022] In the following description of the embodiments, the terminology used in the embodiments of this application is for the purpose of describing particular embodiments only and is not intended to be limiting of the application. The singular forms "a" and "the" as used in the embodiments of this application and the appended claims are also intended to include the plural forms, unless the context clearly indicates otherwise.

[0023] Those skilled in the art should understand that, in the following description of the embodiments of this application, the sequence of numbers does not imply the order of execution. Some or all steps may be executed in parallel or sequentially. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of this application.

[0024] Those skilled in the art will understand that the numerical ranges in the embodiments of this application should be understood to specifically disclose each intermediate value between the upper and lower limits of the range. Any stated value or intermediate value within a stated range, as well as any other stated value or each smaller range between intermediate values ​​within a range, are also included within this invention. The upper and lower limits of these smaller ranges may be independently included or excluded from the range.

[0025] Unless otherwise stated, the technical / scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application pertains. While this application describes only preferred methods and materials, any methods and materials similar or equivalent to those described herein may be used in the implementation or testing of this application. All references to this specification are incorporated by way of citation to disclose and describe the methods and / or materials associated with those references. In the event of any conflict with any incorporated reference, the content of this specification shall prevail.

[0026] To illustrate the technical solution of the present invention, specific embodiments are described below.

[0027] In fixed prosthodontic treatment of the entire dental arch, some restorations may fail due to improper initial design, fabrication errors, or changes in the patient's oral environment. This can manifest as occlusal discomfort, restoration damage, periodontal problems in the abutment teeth, or temporomandibular joint disorder. For these failed restorations, making accurate retreatment decisions is a core clinical challenge.

[0028] Currently, the closest existing technology in clinical practice is diagnostic occlusal analysis (DOA) using a mechanical occlusal frame. See also... Figure 1 As shown, Figure 1 This diagram illustrates the workflow for remedial treatment of failed full dental arch restorations in existing technologies. A represents the facebow, B the transfer platform, C a diagram illustrating the use of a traditional mechanical articulator (maxillary and mandibular bodies, condylar balls, incisor guides, plaster models, and occlusal wax), D a high-point imprint of the maxillary plaster model, and E a high-point imprint of the mandibular plaster model.

[0029] The technical solution typically includes the following steps: (1) using materials such as silicone rubber or wax to obtain a record of jaw position in the patient's mouth; (2) obtaining a plaster model of the upper and lower jaws by taking and pouring a mold; (3) using a facebow and jaw position record to transfer and fix the plaster model to a mechanical semi-adjustable or fully adjustable frame; (4) the doctor subjectively judges the occlusal contact point, premature contact point and jaw interference point by using the imprint left on the model by occlusal paper and manually simulating limited mandibular movements (such as forward and backward extension and lateral movement).

[0030] However, this traditional method has the following problems: The analysis is limited in scope and lacks dynamic functional assessment: Mechanical mandibular frames cannot accurately reproduce the individualized and complex three-dimensional mandibular movement trajectory of patients, especially the non-central movement of the condyle in cases of joint morphology abnormalities. Their analysis is based on static or minimally simplistic motion simulations and cannot perform true dynamic functional occlusion analysis, leading to missed diagnoses of mandibular interference during movement.

[0031] The diagnosis is highly subjective and lacks objective quantitative standards: the identification of occlusal contact points, the judgment of the severity of interference points, and the decision on the amount of adjustment all rely on the doctor's visual observation and tactile experience, lacking objective data support (such as the precise three-dimensional coordinates of interference points and the required adjustment depth in μm), resulting in inaccurate and non-reproducible diagnostic results and large differences between different doctors.

[0032] The error chain is long, making it difficult to guarantee overall accuracy: from intraoral jaw positioning and recording, impression taking, and molding to model transfer and articulation, each step introduces errors, resulting in high cumulative errors and poor stability and repeatability. This often leads to a significant deviation between the occlusion on the articulator and the actual situation in the patient's mouth, and using unreliable analysis results to guide treatment may actually exacerbate the problem.

[0033] Unable to predict and simulate before treatment: Doctors cannot accurately simulate and visualize the effects of adjustments before performing irreversible clinical procedures (such as grinding natural teeth or restorations), resulting in high treatment risks and high trial-and-error costs.

[0034] Based on this, embodiments of the present invention provide a method for decision-making on the retreatment of failed restorations based on dynamic occlusion analysis, thereby achieving precise, quantitative, and predictable decision-making on the retreatment of failed restorations.

[0035] Figure 2 A schematic flowchart illustrating an embodiment of the decision-making method for re-treatment of failed restorations based on dynamic occlusion analysis provided for the implementation of this invention is shown below. Figure 2 As shown, the above method may include: S101, collect multimodal data of the target patient in the intercuspal position and centric relation position. The multimodal data includes intraoral 3D scan data, CBCT image data, dynamic occlusal analysis data, facial scan and clinical symptoms and medical history data; the dynamic occlusal analysis data includes the target patient's individualized mandibular movement trajectory data; It should be noted that maximum intercuspation (MI) refers to the position where the upper and lower cusps have the largest contact area and the tightest occlusion, which is the primary functional position for daily chewing; centric relation (CR) refers to the position of the mandible when the temporomandibular joint is in its physiological midline, and is unrelated to tooth contact, serving as the benchmark for assessing occlusal relationships. When both are in harmony, occlusal function is more stable.

[0036] In some embodiments, individualized mandibular motion trajectory data are acquired through an electromagnetic tracking system, an electronic face bow, or an optical tracking system.

[0037] Specifically, intraoral 3D scanning data can be obtained by intraoral scanners such as CEREC and iTero to acquire 3D data of the patient's dentition, gingiva, and surface morphology of existing restorations, which can be used to reconstruct the fine structure of teeth and restorations; CBCT imaging data can be obtained using cone-beam computed tomography (CBCT) technology to acquire three-dimensional tomographic images of hard tissues such as the jawbone, temporomandibular joint, and tooth roots, providing an anatomical basis for skeletal structure analysis and assessment of the fit between restorations and abutment teeth. The core of dynamic occlusion analysis data includes individualized mandibular motion trajectory data for the target patient, as well as synchronous occlusal force and electromyography (EMG) data. Individualized mandibular motion trajectory data can be acquired using a dedicated motion capture system. Specifically, the Zebris Jaw Motion Analyzer system, based on an ultrasonic sensor, can be used. Its acquisition frequency is 100-200Hz, with a spatial accuracy of ±0.1mm, and it can simultaneously record the three-dimensional mandibular motion trajectory and occlusal contact force distribution, making it suitable for routine functional movement analysis. Alternatively, the Modjaw system, based on optical infrared tracking (acquisition frequency 333Hz, spatial accuracy ±0.03mm, capable of capturing high-speed chewing, complex lateral movements, and other details without distortion, especially suitable for patients with joint dysfunction), can be used. EMG data can be acquired using a surface electrode electromyography (EMG) device. Electrodes are attached to the masseter and anterior temporalis muscles, with a sampling frequency ≥1000Hz, to capture the high-frequency dynamic characteristics of muscle activity during occlusal movements.

[0038] Clinical symptoms and medical history data, including the duration of use of prostheses, location and degree of occlusal discomfort, history of temporomandibular joint clicking / pain, and previous treatment experience, can provide clinical background for etiological analysis through structured questionnaires and clinical examination records.

[0039] For example, see Figure 3 As shown, Figure 3 This is a schematic diagram of multimodal data in an embodiment of the present invention, wherein a is a schematic diagram of digital impression taken by an intraoral scanner, b is a schematic diagram of CBCT images of the joints and dental arch, and c is a schematic diagram of mandibular movement trajectory recording and electromyography measurement (using the Zebris / 4D observation instrument Modjaw).

[0040] S102 performs time synchronization and spatial registration of multimodal data to construct a four-dimensional virtual biomechanical model that includes the target patient's restoration, adjacent teeth, opposing teeth, jawbone, joint, and individualized mandibular movement trajectory. In some embodiments, to ensure the consistency and correlation of multimodal data, adjustments can be made through data synchronization strategies such as time synchronization and spatial synchronization.

[0041] Time synchronization includes using external synchronization signals to achieve hardware-level time alignment for devices that support hardware triggering, such as mandibular motion analyzers and electromyography (EMG) instruments, with synchronization accuracy down to the microsecond level, eliminating data timestamp deviations; for devices that do not support hardware triggering, clock calibration is performed through 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 motion and EMG activity.

[0042] Spatial synchronization employs a dual strategy of marker matching and anatomical feature registration. Markers with both radiopaque and reflective properties are affixed to the patient's face, making them clearly visible in CBCT images, intraoral scan data, and dynamic motion capture, serving as a spatial reference. Simultaneously, anatomical feature points (such as cusp apex, proximal contact point, condylar apex, etc.) are manually or semi-automatically selected on different datasets, and the Iterative Closest Point (ICP) algorithm is used to achieve precise alignment of multimodal data in a unified coordinate system.

[0043] In some embodiments, a four-dimensional virtual biomechanical model is constructed, including the target patient's prosthesis, adjacent teeth, opposing teeth, jawbone, joint, and individualized mandibular movement trajectory, comprising: 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.

[0044] 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.

[0045] 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.

[0046] 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.

[0047] 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.

[0048] In some embodiments, the construction of a four-dimensional virtual biomechanical model may further include: adding a mapping of occlusal contact distribution.

[0049] 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.

[0050] 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.

[0051] 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; 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.

[0052] 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.

[0053] 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.

[0054] 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).

[0055] 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. 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).

[0056] 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.

[0057] 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.

[0058] 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.

[0059] 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.

[0060] 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.

[0061] In some embodiments, the tuning guidance scheme is output in at least one of the following ways: The software interface visually highlights the area requiring grinding and the amount of adjustment. Generate a text and image diagnostic report; The data is output to an augmented reality device and projected onto the patient's mouth; Output data to a CAD / CAM system to directly create a pre-fitted restoration.

[0062] 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.

[0063] 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.

[0064] 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.

[0065] The clinical procedure includes the following stages: Phase 1: Intraoral occlusal adjustment, which involves fine-tuning the existing restorations according to the occlusal adjustment guidelines; 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; 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.

[0066] 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.

[0067] 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.

[0068] The method of this invention will be described below with reference to a specific embodiment.

[0069] 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: 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.

[0070] Clinical examination (such as) Figure 8 As 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.

[0071] Digital diagnosis and design using the methods of this invention specifically include: (1) Determine the centric relation (CR): Find a repeatable physiological position of the mandible for the patient through muscle depolarization.

[0072] (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.

[0073] (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.

[0074] The treatment process includes the following stages: 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 11As shown, after adjustment, the bite contact becomes more uniform and stable, and the mandibular movement trajectory is also smoother.

[0075] 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.

[0076] 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.

[0077] 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.

[0078] 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.

[0079] 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.

[0080] 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 decision-making method for retreatment of failed prostheses based on dynamic occlusion analysis, characterized in that, include: Multimodal data of the target patient were collected at the intercuspal position and centric relation position. The multimodal data included intraoral three-dimensional scan data, CBCT image data, dynamic occlusal analysis data, facial scan data, and clinical symptom and medical history data. The dynamic occlusal analysis data included the individualized mandibular movement trajectory data of the target patient. The multimodal data is time-synchronized and spatially registered to construct a four-dimensional virtual biomechanical model that includes the target patient's prosthesis, adjacent teeth, opposing teeth, jawbone, joint, and individualized mandibular movement trajectory. 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 compatibility between the prosthesis and the abutment teeth, the marginal occlusion, occlusal interference, and abnormal distribution of occlusal force. Based on the dynamic occlusion analysis results, a quantitative decision rule is used to determine whether occlusion adjustment is necessary. This quantitative decision rule includes: using the maxilla as a reference, registering the mandibular positions at the intercuspal and centric relation positions, comparing the occlusal contact displacement and symmetry of the occlusal contact distribution between the two positions, and determining whether occlusion adjustment conditions are met. Specifically: if the displacement is less than or equal to a preset displacement threshold and the occlusal contact distribution is uniform, then no adjustment is needed; if the displacement 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 unavailable, then the amount of occlusion adjustment required to achieve uniform occlusal contact is calculated. In the four-dimensional virtual biomechanical model, occlusal adjustment is simulated. 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 is greater than the preset displacement threshold or the displacement is unavailable, the simulated adjustment is performed at the centric position. After adjustment, the stability of occlusal contact and occlusal force distribution is verified. If the adjustment is within the preset adjustment range, an adjustment guidance plan is generated. If the adjustment exceeds the preset adjustment range, it is determined that direct adjustment is not possible, and a retreatment plan including occlusal splint treatment, occlusal reconstruction, or orthodontic treatment is generated.

2. The method according to claim 1, characterized in that, The individualized mandibular movement trajectory data is acquired through an electromagnetic tracking system, an electronic face bow, or an optical tracking system.

3. The method according to claim 2, characterized in that, The construction of the four-dimensional virtual biomechanical model, which includes the target patient's prosthesis, adjacent teeth, opposing teeth, jawbone, joint, and individualized mandibular movement trajectory, includes: The 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 contact distribution information and the individualized mandibular movement trajectory data are then embedded to form a four-dimensional virtual biomechanical model with dynamic functions.

4. The method according to claim 3, characterized in that, The dynamic occlusion analysis is implemented through a machine learning model, which outputs a prosthesis failure risk score and retreatment recommendations. The retreatment recommendations include 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.

5. The method according to claim 4, characterized in that, The tuning guidance scheme is output in at least one of the following ways: The software interface visually highlights the area requiring grinding and the amount of adjustment. Generate a text and image diagnostic report; The data is output to an augmented reality device and projected onto the patient's mouth; Output data to a CAD / CAM system to directly create a pre-fitted restoration.

6. The method according to claim 5, characterized in that, The method also includes: digital cross-registration, which involves precisely aligning the diagnostic digital model with the old restoration with the working digital model after tooth preparation before and after restoration removal to ensure stable transfer of jaw position relationship.

7. The method according to claim 1, characterized in that, The method further includes: performing clinical procedures according to the treatment guidance plan or the retreatment plan, and verifying the treatment effect through the four-dimensional virtual biomechanical model or chairside real-time monitoring device.

8. The method according to claim 7, characterized in that, The clinical procedure includes the following stages: Phase 1: Intraoral occlusal adjustment, based on the aforementioned occlusal adjustment guidelines, to perform fine-tuning of the existing prosthesis; Phase 2: Transitional repair, removing the poorly shaped old prosthesis, designing and fabricating a CAD / CAM temporary prosthesis based on the four-dimensional virtual biomechanical model, and observing the preset adaptation period after wearing it; The third stage: final repair. After the temporary prosthesis has been verified to be stable, the final prosthesis is designed and fabricated based on the four-dimensional virtual biomechanical model. The final prosthesis replicates the stable occlusal relationship of the temporary prosthesis.

Images