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510(k) Data Aggregation

    K Number
    K213302
    Device Name
    exoplan
    Manufacturer
    Date Cleared
    2022-05-03

    (211 days)

    Product Code
    Regulation Number
    892.2050
    Reference & Predicate Devices
    Why did this record match?
    Applicant Name (Manufacturer) :

    exocad GmbH

    AI/MLSaMDIVD (In Vitro Diagnostic)TherapeuticDiagnosticis PCCP AuthorizedThirdpartyExpeditedreview
    Intended Use

    exoplan is a medical software, intended to support the planing of dental implants using the visualization of the implant placement within images of the patient's anatomy. The process is based on CT/CBCT data sets originating from other medical devices, and can be supported by optical scan(s) of the patient's anatomy as well as a virtual prosthetic proposal. exoplan allows the design of surgical guides to support the placement of endosseous dental implants in guided surgery. The design of surgical guides is based on 3D surface data representing the preoperative situation and approved implant positions. Alternatively, instead of optical surface data a second CBCT/CT dataset can be used. The software exports the planning and design results as geometrical data and a digital 3D model of the surgical guide to support the manufacture of a separate physical product.

    exoplan does not extend or change indications of dental implants. Usage of a surgical guide designed with the software does not change the necessary due diligence required compared to conventional (non-guided) surgery.

    The software is intended to be used only by dental professionals with sufficient medical training in dental implantology and surgical dentistry in office environments suitable for reading diagnostic dental DICOM data sets. exoplan shall not be used for any purpose other than planning dental implant placement or design of surgical guides.

    Device Description

    exoplan is a standalone software application for the purpose of pre-operative implant planning and design of surgical guides to support the surgical intervention.

    The software application runs on "off-the-shelf" PC hardware with Microsoft Windows 10 operating system (64 Bit), off-the shell GPU card and otherwise standard peripheral components.

    The device allows importing 3D CT and optical scans from teeth, dental impression, or stone models) from compatible intraoral or desktop scanners. While the planning of implant position is mainly based on the information of the CT data, the design of a surgical quide is based on the STL data of the optical scan. Both modalities are registered to a common coordinate system to ensure that the implant positions defined by a user can be used for design of a surgical guide.

    exoplan uses so called component libraries, which contain (e.g., physical dimensions, compatibility, etc.) provided by the original manufacturer of a component, and cover all components that can be used during treatment and necessary to consider during planning, e.g. implants, drills and drill sleeves. The libraries are digitally signed. This ensures that any modification of the content of a library will be detected by exoplan. The issue is then reported to the user and documented in the Implant Planning Report or the Surgical Protocol.

    exoplan has no contact with the patient.

    AI/ML Overview

    The provided text primarily focuses on the FDA 510(k) Summary for the "exoplan" device, describing its indications for use, device description, and a comparison to predicate and reference devices. It does mention "Non-Clinical Performance Testing" and that "Furthermore, accuracy tests were performed to verify that the planning results are as accurate as defined." However, it does NOT provide specific details about the acceptance criteria or the study that definitively proves the device meets those criteria, outside of a general statement about software verification, validation, and accuracy tests. It explicitly states, "Clinical testing is not a requirement and has not been performed."

    Therefore, based on the provided text, I cannot fully answer all aspects of your request. I can only provide the information that is explicitly stated or strongly implied.

    Here's an attempt to answer your questions based on the limited information available:


    Acceptance Criteria and Device Performance Study for exoplan (K213302)

    Based on the provided 510(k) Summary, specific quantitative acceptance criteria and detailed performance study results are not explicitly disclosed. The document generally refers to "Software verification and validation" and "accuracy tests."

    1. A table of acceptance criteria and the reported device performance

    The document states:

    • "Each user requirement and each derived product requirement has an own acceptance criteria."
    • "Furthermore, accuracy tests were performed to verify that the planning results are as accurate as defined."

    However, no specific quantitative acceptance criteria or corresponding reported device performance values are provided in this document. The document only generally states that "the verification of the device has been completed" and that "the results of verification and validation ensure that the new device is as safe and as effective."

    2. Sample size used for the test set and the data provenance (e.g., country of origin of the data, retrospective or prospective)

    The document does not specify the sample size used for any "test set" or "accuracy tests." It also does not provide any information regarding data provenance (e.g., country of origin, retrospective or prospective).

    3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts

    The document does not specify the number of experts or their qualifications used to establish ground truth for any test set.

    4. Adjudication method (e.g. 2+1, 3+1, none) for the test set

    The document does not mention any adjudication method for a test set.

    5. If a multi reader multi case (MRMC) comparative effectiveness study was done, If so, what was the effect size of how much human readers improve with AI vs without AI assistance

    The document explicitly states: "Clinical testing is not a requirement and has not been performed." Therefore, no MRMC comparative effectiveness study was conducted, and no effect size regarding human reader improvement with AI assistance is available.

    6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done

    The document describes "accuracy tests" and "software verification and validation," implying a standalone evaluation of the algorithm's performance against predefined criteria. However, no specific data or metrics from such standalone performance are provided. The device (exoplan) is described as a "medical software, intended to support the planing of dental implants," indicating a human-in-the-loop use case.

    7. The type of ground truth used (expert consensus, pathology, outcomes data, etc.)

    The document refers to "accuracy tests... to verify that the planning results are as accurate as defined." Given the nature of the device (dental implant planning software), the ground truth for these "accuracy tests" would most likely involve measurements against known physical or digital standards, or potentially comparisons to expert-derived ideal plans. However, the exact type of ground truth (e.g., physical phantoms, simulated anatomical models, or expert consensus on ideal implant placement) is not explicitly stated. Pathology or outcomes data would not typically be applicable to pre-operative planning software validation as it's not a diagnostic or outcome-predicting tool.

    8. The sample size for the training set

    The document does not mention a training set size. This is likely because the device, as described, is a software tool for planning and design, rather than an AI/ML model that would typically require a distinct training set (though verification and validation apply to all software).

    9. How the ground truth for the training set was established

    Since no training set is mentioned as applicable to this type of software according to the document, the establishment of its ground truth is not applicable/not described.

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    K Number
    K193352
    Device Name
    AbutmentCAD
    Manufacturer
    Date Cleared
    2021-07-21

    (595 days)

    Product Code
    Regulation Number
    872.3630
    Reference & Predicate Devices
    Why did this record match?
    Applicant Name (Manufacturer) :

    exocad GmbH

    AI/MLSaMDIVD (In Vitro Diagnostic)TherapeuticDiagnosticis PCCP AuthorizedThirdpartyExpeditedreview
    Intended Use

    The AbutmentCAD module is intended as an aid to the restoration in partially or fully edentulous mandibles and maxillae. AbutmentCAD is a software device intended to be used by trained professionals in dental practices or dental laboratories for the design of patient specific implant borne prosthetics such as one-piece abutments, two-piece/hybrid abutments, single or multi-unit screw-retained restorations. The design result is intended to be used by the manufacturer of an endosseous dental implant abutment to create the final device.

    Device Description

    AbutmentCAD is a software application for the purpose of designing patient-specific implant-based dental restorations, such as one-piece abutments, two-piece/hybrid abutments and single or multi-unit screw retained restorations. The AbutmentCAD software can be used with basic dental CAD systems such as exocad's ChairsideCAD. AbutmentCAD is used solely for the patient-specific components of abutments and screw retained crowns and bridges. The software application runs on "off-the-shelf" PC hardware with current Microsoft Windows operating system and standard peripheral components.

    AI/ML Overview

    Here's an analysis of the provided text regarding the acceptance criteria and study for AbutmentCAD:

    Note: The provided document is a 510(k) Summary, which is a premarket notification for demonstrating substantial equivalence to a legally marketed predicate device. It does not present a detailed clinical study with performance metrics in the way a typical AI-based diagnostic device FDA clearance would. Instead, it focuses on software verification and validation, ensuring the software performs its intended function within defined parameters and adheres to design limitations.


    Acceptance Criteria and Reported Device Performance

    The document primarily focuses on the software's ability to accurately enforce design limitations and correctly process data, rather than diagnostic accuracy metrics.

    Acceptance Criteria (Related to Performance)Reported Device Performance
    Design Limitations Enforcement Accuracy:
    Dimensional constraints (e.g., minimum/maximum height, diameter, wall thickness)Correctly triggered with an accuracy of 0.01mm.
    Angular constraints (e.g., angulation of abutment, screw channel)Correctly triggered with an accuracy of 0.5°.
    Implant Library Integrity:Libraries are digitally signed, and any modification is detected, preventing their use. (This ensures that design parameters conform to implant manufacturer specifications and are not tampered with.)
    Software Functionality and User Requirements:"Prior to release of AbutmentCAD the verification and validation of the device has been completed. Each user requirement and each product requirement derived thereof has an own acceptance criteria." (Specific performance metrics for each requirement are not detailed in this summary, but the successful completion of verification and validation is asserted.)
    Adherence to Implant Manufacturer Instructions: (Design software's ability to ensure resulting designs conform to specific instructions)"Design limitations stored in the Implant Libraries are verified so that items with design parameters beyond the defined limitations cannot be created with the AbutmentCAD software application." "With the information of design limitations... it is possible to control the design process and ensure that the design results conform to implant specific instructions of the implant manufacturer."
    A software tool for creating abutment libraries was validated to ensure design parameters are enforced.
    Manufacturing Compatibility: (Ability to generate designs compatible with manufacturing)"Additional information of specific capabilities of the machine are adhered to by AbutmentCAD directly at the stage of design to ensure that the part can be manufactured."
    Cybersecurity: (Software's robustness against cybersecurity threats)A cybersecurity analysis was performed, and exocad monitors vulnerabilities post-market. Testing includes cybersecurity requirements. (No specific performance metrics are given, but compliance with guidance is stated.)

    Details of the Study/Testing

    Given that this is a 510(k) for a CAD software, the "study" described is primarily software verification and validation testing, not a clinical trial or large-scale comparative effectiveness study for diagnostic accuracy.

    1. Sample sizes used for the test set and data provenance:

      • Test Set Sample Size: Not explicitly stated as a single number of cases. The testing involved "realistic and artificial data" for verifying design limitations.
      • Data Provenance: Not specified in terms of country of origin. The data includes "imported scan and the geometry information of objects in integrated implant libraries." The testing uses "realistic and artificial data." It is software validation, so likely a mix of simulated and real-world-representative data, potentially from internal sources. It's retrospective in the sense that it's testing a developed software against pre-existing data or simulated scenarios.
    2. Number of experts used to establish the ground truth for the test set and qualifications of those experts:

      • Number of Experts: Not specified.
      • Qualifications of Experts: Not specified. For verifying geometric and angular accuracy, the "ground truth" would likely be derived from engineering specifications, CAD standards, and the explicit instructions provided by the implant manufacturers (which form the basis of the "Implant Libraries"). "3rd party tools" were used to prove the correctness of the software.
    3. Adjudication method (e.g. 2+1, 3+1, none) for the test set:

      • Not applicable/Not mentioned. The verification tests involved checking if the software correctly enforced the predefined design limitations using precise measurements (0.01mm, 0.5° accuracy) and external tools, rather than human expert adjudication of subjective interpretations.
    4. If a multi-reader multi-case (MRMC) comparative effectiveness study was done, If so, what was the effect size of how much human readers improve with AI vs without AI assistance:

      • No, an MRMC study was not done. This device is a CAD software for design, not a diagnostic AI system intended to assist human readers in image interpretation or diagnosis. It aids in the design of dental prosthetics based on pre-established parameters.
    5. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done:

      • Yes, in essence. The core verification for enforcing design limitations and maintaining library integrity is a standalone performance assessment of the algorithm's accuracy in following its programming rules. The software itself, without human intervention during the calculation/enforcement of constraints, needs to perform accurately. However, it's explicitly "intended to be used by trained professionals in dental practices or dental laboratories for the design." So, while standalone verification of programmatic rules occurred, the overall device is a human-in-the-loop tool for design.
    6. The type of ground truth used (expert consensus, pathology, outcomes data, etc.):

      • The ground truth for design limitations is based on engineering specifications and explicit instructions provided by the original implant manufacturers. These are encoded into the "Implant Libraries." The accuracy of the software in adhering to these parameters (0.01mm for dimensions, 0.5° for angles) forms the primary ground truth for the verification testing.
    7. The sample size for the training set:

      • Not applicable / Not mentioned. This device description does not indicate the use of machine learning that would typically involve a "training set." It appears to be a rule-based CAD software where design limitations are explicitly programmed rather than learned from data. The "Implant Libraries" are essentially predefined data sets of specifications, not training data in the ML sense.
    8. How the ground truth for the training set was established:

      • Not applicable. As no machine learning training set is mentioned, this question is not relevant. The "ground truth" for the software's functionality relates to correctly implementing engineering and manufacturer specifications.
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    K Number
    K183458
    Device Name
    exoplan 2.3
    Manufacturer
    Date Cleared
    2019-08-06

    (236 days)

    Product Code
    Regulation Number
    892.2050
    Reference & Predicate Devices
    Why did this record match?
    Applicant Name (Manufacturer) :

    exocad GmbH

    AI/MLSaMDIVD (In Vitro Diagnostic)TherapeuticDiagnosticis PCCP AuthorizedThirdpartyExpeditedreview
    Intended Use

    exoplan is a medical software, intended to support the planning of dental implants using the visualization of the implant placement within images of the patient's anatomy. The process is based on CT/CBCT data sets originating from other medical devices, and can be supported by optical scan(s) of the patient's anatomy as well as a virtual prosthetic proposal.

    exoplan allows the design of surgical guides to support the placement of endosseous dental implants in guided surgery. The design of surgical guides is based on 3D surface data representive situation and approved implant positions. The software exports the planning and design results as geometrical data and a digital 3D model of the surgical guide to support the manufacture of a separate physical product. exoplan does not extend or change indications of dental implants. Usage of a surgical guide designed with the software does not change the necessary due diligence required compared to conventional (non-guided) surgery.

    The software is intended to be used only by dental professionals with sufficient medical training in dental implantology and surgical dentistry in office environments suitable for reading diagnostic dental DICOM data sets. exoplan shall not be used for any purpose other than planning dental implant placement or design of surgical guides.

    Device Description

    exoplan is a standalone software application for the purpose of pre-operative implant planning and design of surgical guides to support the surgical intervention.

    The software application runs on "off-the-shelf" PC hardware with current Microsoft Windows operating system (7, 8.1,10, 64 Bit), off-the shell GPU card and otherwise standard peripheral components.

    The device allows importing 3D CT data and dental scan data (e.g. scans from teeth, dental impression, or stone models) from compatible intraoral or desktop scanners. While the planning of implant position is mainly based on the information of the CT data, the design of a surgical quide is based on the STL data of the dental scan. Both modalities are registered to a common coordinate system to ensure that the implant positions defined by a user can be used for design of a surgical guide.

    exoplan uses so called Implant Libraries that contain information provided by the original manufacturer of a respective physical implant, reconstruction parts on top of the implant, such as stock abutments or titanium bases. Libraries also contain drilling sleeves and tools of surgical kit items, such as drills and drill handles. The libraries are digitally signed and by that any modification of a library content or the referred library parts of files will be detected by exoplan reported to the user and documented in an Implant Planning Report or Surgical Protocol document.

    exoplan has no contact with the patient.

    AI/ML Overview

    The provided document is a 510(k) summary for the medical software "exoplan 2.3". It outlines the device's indications for use, technical characteristics, and a comparison to a predicate device. The document does not contain details about a clinical study involving human readers or a multi-reader multi-case (MRMC) study. It primarily focuses on the device's technical performance and verification/validation steps.

    Here's an analysis of the acceptance criteria and the study information that is available in the document:

    1. A table of acceptance criteria and the reported device performance:

    The document includes a table titled "Summary of tests and accuracy results" on page 5, which lists several tested accuracies (acting as acceptance criteria) and their reported results.

    #Tested AccuracyReported Device Performance
    1.Visualization of iso-surface of CT data accuracy10% of the maximum voxel size (e.g., for 1mm voxel size, accuracy is 0.1mm)
    2.Density threshold accuracy in 3D CT data10% of maximum voxel size for a perfectly selected threshold.
    3.Accuracy of distance measurement in 3D CT data, rendering modes "iso-surface", "solid"General dimensional measurement accuracy of 0.01mm. Clicking on DICOM object in iso-surface or solid rendering mode has an additional limitation of 10% of the voxel size.
    4.Accuracy of distance measurement in STL meshesAchievable accuracy of 0.01mm.
    5.Accuracy of angle measurementAchievable accuracy of 0.5°.
    6.CT Data alignment accuracy, 3 Point Alignment & Best Fit Alignment3 Point Alignment: Achievable accuracy: 1mm.
    Best Fit Alignment: Achievable accuracy depends on input data resolution; for the data set used, 0.2mm.
    7.Implant placement accuracyAchievable accuracy of 0.3 mm relative to CT data.
    8.Collision detection accuracy, visualCollisions are detected: Implant/implant, marked nerve/implant, collision object mesh/implant.
    9.Collision detection accuracy0.01mm.
    10.Drill Sleeve placement accuracyAccuracy of placing a sleeve along the implant axis: 0.01mm.
    11.Drill Sleeve rotation accuracyAchievable repetitious accuracy of 1°.
    12.Accuracy of Surgical Guide bottom0.1mm in smooth areas without undercuts (relative to optical scan data plus user-defined offset).
    13.Accuracy of merged Surgical Guide parts0.01mm in smooth areas (relative to the surface of the merged parts).
    14.Accuracy of merged Surgical Guide bottom0.01mm in smooth areas (relative to the surface of the merged bottom).

    2. Sample size used for the test set and the data provenance:

    The document states: "Software verification and validation is performed in accordance with the applicable guidance document... Prior to release of exoplan the verification and validation of the device has been completed." It also mentions "The selected tests verify accuracies of critical items in the whole workflow of exoplan".

    However, the document does not explicitly state the sample size for the test set used for these accuracy measurements. It also does not specify the data provenance (e.g., country of origin, retrospective or prospective) for the CT/CBCT or optical scan data used in these tests. It only mentions the data types (CT/CBCT, optical scans) and that they originate "from other medical devices".

    3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts:

    The document does not mention the use of experts or their qualifications for establishing ground truth for the technical accuracy tests. The described tests appear to be technical verification and validation, likely against known or measured physical/digital standards, rather than expert-derived diagnoses or interpretations.

    4. Adjudication method for the test set:

    Since the document does not describe expert involvement in establishing ground truth for the technical tests, there is no adjudication method mentioned.

    5. If a multi reader multi case (MRMC) comparative effectiveness study was done, If so, what was the effect size of how much human readers improve with AI vs without AI assistance:

    The document explicitly states on page 5: "Clinical testing is not a requirement and has not been performed." This indicates that no MRMC or other human-in-the-loop performance study has been conducted or reported in this submission. Therefore, no effect size of human reader improvement with AI assistance is provided.

    6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done:

    The provided "Summary of tests and accuracy results" table (page 5) describes the performance of the "exoplan" software itself, independent of human interaction beyond input provision. These are essentially standalone performance metrics focusing on the accuracy of its various computational and visualization functions (e.g., measurement accuracy, alignment accuracy, collision detection accuracy).

    7. The type of ground truth used:

    For the technical accuracy tests, the ground truth appears to be engineering ground truth or digital ground truth, derived from:

    • Pre-defined voxel sizes and known physical dimensions for measurements.
    • Known "perfectly selected thresholds" for density.
    • Physical or digital models with established properties for alignment, implant placement, and guide fit.
    • The software's internal calculations and comparisons for collision detection and merging parts.

    There is no mention of expert consensus, pathology, or outcomes data being used as ground truth for these technical accuracy tests.

    8. The sample size for the training set:

    The document is a 510(k) summary for a "Picture archiving and communications system" that assists with dental implant planning. While it's software-based, the description of its functionalities (e.g., using "Implant Libraries" which contain manufacturers' data) suggests it might not be a machine learning/AI device in the sense that it requires a "training set" in the conventional machine learning context. The document does not mention any training set size because it doesn't describe an AI model that undergoes a training phase from data.

    9. How the ground truth for the training set was established:

    As no training set is mentioned or implied for a machine learning model, this information is not applicable and not provided in the document. The software appears to be rule-based or model-based, relying on geometric, anatomical, and manufacturer-provided data rather than learning from a large labeled dataset.

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