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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.

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.

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.

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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