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DESS Dental Smart Solutions abutments are intended to be used in conjunction with endosseous dental implants in the maxillary or mandibular arch to provide support for prosthetic restorations.

All digitally designed custom abutments for use with DESS Ti Base abutments or Pre-Milled Blank abutments are to be sent to a Terrats Medical validated milling center for manufacture.

The purpose of this submission is to add components to the DESS Dental Smart Solutions system, which includes dental implants, abutments, and prosthetic components cleared previously in various submissions. The previously cleared abutments and prosthetic components are compatible with a variety of original equipment manufacturer (OEM) dental implants as well as DESS Dental Smart Solutions dental implants.

This submission adds various abutments to the DESS and OEM implant lines as summarized on the following pages in Table 1 Summary of Subject Device Abutment Designs, and Table 2 Summary of Subject Device Abutment Sizes.

The subject device abutment designs include Cover Screws, Healing Abutments, Temporary Abutments, Ti Base Abutments, AURUM Base Abutments (Ti Base abutments with a screw channel design that allows easier instrument access to the abutment screw), CoCr Base Abutments, Pre-Milled Blank Abutments, Multi-Unit Abutments (straight and angled), DESSLoc Abutments (Locator-type abutments), and abutment screws.

This document is a 510(k) summary for the DESS Dental Smart Solutions, a line of endosseous dental implant abutments. It details the device's characteristics, intended use, and a comparison to predicate devices to establish substantial equivalence.

Based on the provided text, the device itself is a physical medical device (dental implant abutments and associated components), not a software or AI-driven system. Therefore, the questions related to AI acceptance criteria, training/test sets, expert adjudication, MRMC studies, and ground truth establishment for AI would not be directly applicable to this product as described.

The document focuses on establishing substantial equivalence to previously cleared predicate devices through:

• Identical Intended Use: The device is intended for "functional and esthetic rehabilitation of the edentulous mandible or maxilla" by providing support for prosthetic restorations, which is the same as the predicate devices.
• Similar Technological Characteristics: The device utilizes similar designs, materials (Ti-6Al-4V, Co-Cr-Mo alloy), manufacturing processes, and sterilization methods as its predicates.
• Performance Data: Non-clinical testing (mechanical testing per ISO 14801, MR environment assessment) and comparison to existing data from predicate devices are used to demonstrate safety and effectiveness.

Therefore, many of the requested elements for describing AI acceptance criteria and studies are not present or applicable in this document.

However, I can extract information relevant to the device's performance assessment and criteria for its type of submission.

Here's an attempt to answer the questions based solely on the provided text, acknowledging that the nature of the device (a physical implant component) means many AI-specific questions will be answered as "Not Applicable" (N/A):

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

The document does not explicitly state quantifiable "acceptance criteria" in a table format with corresponding "reported device performance" metrics for this specific 510(k) submission. Instead, it relies on demonstrating substantial equivalence to existing predicate devices.

The underlying "acceptance criteria" for demonstrating substantial equivalence for this device type are primarily through:

• Mechanical Testing (ISO 14801): This is a critical performance standard for dental implants and abutments. The document states that mechanical testing was "conducted according to ISO 14801 to support the performance." The acceptance criteria would be successful completion of these tests, demonstrating the device's mechanical strength and fatigue resistance are comparable to or better than predicate devices. The reported performance is simply that the tests supported the performance.
• Material Conformance: Materials must conform to specific ASTM standards (e.g., ASTM F136 for Ti-6Al-4V, ASTM F1537 for Co-Cr-Mo). The reported performance is that the materials conform to these standards.
• Biocompatibility: While not detailed in this excerpt, the mention of "biocompatibility" in relation to predicates implies conformance to relevant biocompatibility standards (e.g., ISO 10993 series). The reported performance is that it is compatible.
• Sterilization Validation: Demonstrated sterility assurance level (SAL) of 10⁻⁶ via validated methods (moist heat or gamma irradiation). The reported performance is that validation was performed and met this SAL.
• Dimensional Compatibility: The abutments must fit the corresponding OEM implants correctly. The reported performance is that reverse engineering dimensional analysis confirmed compatibility.

Due to the nature of the document being a 510(k) summary focusing on substantial equivalence rather than a full study report, specific numerical performance results for the device tests are not provided in this text.

2. Sample sizes used for the test set and the data provenance

• Sample Size for Mechanical Testing: The document states "mechanical testing conducted according to ISO 14801." For such tests, ISO 14801 typically specifies minimum sample sizes (e.g., 10-11 samples for static strength, typically more for fatigue). The exact number of samples used for this specific submission is not explicitly stated, but it would have followed the standard's requirements.
• Data Provenance: The mechanical testing and material analyses are assumed to be "non-clinical data submitted or referenced" by the manufacturer, Terrats Medical SL, based in Barcelona, Spain. The "reverse engineering dimensional analysis" was done by Terrats Medical SL or through contractual agreement. This is prospective testing performed to support the 510(k). The document itself does not specify the country of origin for the underlying OEM implant data used for reverse engineering, although the OEM companies are listed (e.g., Astra Tech AB, BioHorizons).

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

N/A. This is a physical device. Ground truth, in the context of AI, refers to validated labels for data used to train and test an algorithm. For a physical device, performance is evaluated through engineering and biocompatibility testing against defined standards. There are no "experts" establishing ground truth in the AI sense. Testing would be performed by qualified engineers and technicians.

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

N/A. Adjudication methods are typically used in clinical studies involving interpretation (e.g., by radiologists) to resolve discrepancies. This document describes non-clinical performance testing of a physical device.

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

N/A. This product is a dental implant abutment, not an AI software intended to assist human readers.

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

N/A. This is a physical device, not an algorithm.

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

N/A. For engineering tests of physical devices, the "ground truth" is typically derived from established engineering principles, international standards (e.g., ISO 14801 for mechanical properties, ASTM for materials), and the physical properties of the materials and designs themselves. There isn't "expert consensus" or "pathology" in the AI or clinical trials sense.

8. The sample size for the training set

N/A. This is a physical device; there's no "training set" in the machine learning sense. The device is manufactured based on established engineering designs and material specifications.

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

N/A. No training set for AI. For device manufacturing, the "ground truth" for design and production parameters comes from established engineering best practices, prior successful device designs (predicate devices), and adherence to quality systems regulations (21 CFR Part 820).

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DESS Dental Smart Solutions abutments are intended to be used in conjunction with endosseous dental implants in the maxillary or mandibular arch to provide support for prosthetic restorations.

The purpose of this submission is to expand the DESS Dental Smart Solutions abutment system by a change in sterilization status to provide products sterile to the end user that were previously cleared to be provided non-sterile. The subject device abutments and abutment screws were cleared previously to be provided non-sterile to the end user in K170588, K191986, K212628, and K22288. All subject device components will now be provided sterile.

The subject device components include Healing Abutments, Multi-Unit Abutments (0, 17°, and 30°), and abutment screws.

The provided text is a 510(k) summary for the DESS Dental Smart Solutions, an endosseous dental implant abutment. It details the device, its intended use, and its substantial equivalence to previously cleared predicate and reference devices. However, this document does not contain the acceptance criteria or a study proving the device meets those criteria in the context of an AI/ML medical device.

The 510(k) submission for this dental abutment focuses on establishing substantial equivalence based on:

• Design and Material: The subject device components are identical in design, material (Ti-6Al-4V alloy, DLC coating), and technological characteristics to previously cleared devices.
• Manufacturing: The manufacturing process is consistent with previously cleared devices.
• Biocompatibility: Referenced from previous K-clearances.
• Sterilization: The main change in this submission is expanding the system to provide products sterile to the end-user via gamma irradiation, which was validated by referencing a previous K-clearance (K212538).
• MR Environment Testing: Non-clinical analysis was performed to evaluate the subject devices in the MR environment, referencing published literature and FDA guidance.
• Shelf Life Testing: Referenced from a previous K-clearance (K212538) for samples after accelerated aging.

Therefore, I cannot fulfill your request to describe the acceptance criteria and a study proving an AI/ML device meets them based on the provided text, as this document is not about an AI/ML medical device. It's about dental implant abutments and establishes substantial equivalence through non-clinical performance data and comparison to predicate devices, not through AI/ML performance metrics.

To provide the information you requested, I would need a document detailing the validation of an AI/ML medical device, which would include definitions of acceptance criteria (e.g., accuracy, sensitivity, specificity), details of training and test datasets, ground truth establishment, and potentially clinical effectiveness studies if applicable.

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DESS Dental Smart Solutions abutments are intended to be used in conjunction with endosseous dental implants in the maxillary or mandibular arch to provide support for prosthetic restorations.

The purpose of this submission is to add components to the DESS Dental Smart Solutions system, which includes abutments compatible with a variety of original equipment manufacturers (OEM) of dental implants. This submission adds abutments, designated DESS Multi-Unit Abutments, for implant lines from Zimmer Dental and Biomet 31 (now collectively, ZimVie Dental). The subject device abutments include Multi-Unit Abutments in straight, 17° angled, and 30° angled designs, which are compatible with implants having internal hex connections. This submission is also to change how previously cleared devices are provided; the change is from previously provided nonsterile to now provided sterile. All abutments are provided with the appropriate abutment screw (if applicable) for attachment to the corresponding implant. The subject device is only intended for multi-unit restorations such as bridges and bars.

It appears there might be a misunderstanding of the provided text. The document is a 510(k) premarket notification for a dental implant abutment, not an AI/ML medical device. Therefore, the information typically required for describing an AI/ML device's acceptance criteria and study data (like sample sizes for test and training sets, expert qualifications, ground truth establishment, MRMC studies, or standalone performance) is not present.

The document discusses the substantial equivalence of the DESS Dental Smart Solutions abutment to legally marketed predicate devices. The "performance data" section refers to non-clinical testing to demonstrate the device's physical properties and compatibility, not a study evaluating an AI algorithm's diagnostic or predictive performance.

Let's break down what can be extracted from the provided text relevant to the device's acceptance, and then explain why the AI/ML specific questions cannot be answered.

Understanding the Device and its "Acceptance":

The "acceptance" in this context refers to the FDA's determination that the new DESS Dental Smart Solutions abutments are "substantially equivalent" to predicate devices already on the market. This determination is based on the device having the same intended use and similar technological characteristics (design, materials, performance via non-clinical testing).

Here's a summary of the information available in the document:

1. Table of Acceptance Criteria (or rather, Equivalence Criteria) and Reported Device Performance:

The document doesn't present acceptance criteria in a quantitative table with performance metrics like sensitivity, specificity, or accuracy, as would be common for an AI/ML device. Instead, "acceptance" is based on demonstrating substantial equivalence to predicate devices across several characteristics. The performance is shown through non-clinical testing to ensure safety and functionality.

Important Note: The "acceptance criteria" here are qualitative statements of substantial equivalence, backed by quantitative non-clinical engineering and materials testing, not performance metrics from a clinical study or an AI model's accuracy.

Regarding the AI/ML Specific Questions:

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

• Not applicable. This document is for a physical medical device (dental implant abutment), not an AI/ML algorithm. There is no "test set" in the context of data for an AI/ML model. The "testing" refers to mechanical, material, and sterilization validation.

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

• Not applicable. Ground truth establishment by experts is relevant for AI/ML diagnostic devices. This device's performance is assessed through engineering standards and material properties. Compatibility with implant systems is established through design agreements and reverse engineering data (referenced from K170588).

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

• Not applicable. Adjudication methods are used in clinical studies or for establishing ground truth labels for AI/ML datasets.

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:

• Not applicable. MRMC studies are for evaluating diagnostic efficacy, particularly with AI assistance. This device is a passive prosthetic component.

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

• Not applicable. There is no algorithm.

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

• Not applicable. The "ground truth" for this device's performance is its adherence to engineering standards (e.g., ISO 14801 for mechanical properties, ASTM for materials/MR safety) and its demonstrated compatibility with specified implant systems, rather than a clinical ground truth like disease presence.

8. The sample size for the training set:

• Not applicable. There is no AI model or training set.

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

• Not applicable. As above, no AI model or training set.

Conclusion from the document:

The provided document describes a 510(k) submission for a Class II medical device, DESS Dental Smart Solutions abutments. The "acceptance criteria" revolve around demonstrating substantial equivalence to existing legally marketed predicate devices. This is achieved through:

• Identical intended use.
• Similar technological characteristics: This includes materials (Titanium alloy), design (multi-unit, screw-retained), and geometric parameters (diameters, gingival heights).
• Performance via non-clinical testing: This includes mechanical testing (ISO 14801), MR safety testing (ASTM standards), sterilization validation (ANSI/AAMI/ISO standards), bacterial endotoxin testing (ANSI/AAMI ST72), shelf-life testing (ASTM F1980), and biocompatibility testing (ISO 10993-5).
• Compatibility with specified implant systems: This is supported by contractual agreements with OEMs (ZimVie/Terrats Medical SL) and referenced reverse engineering data.

The document explicitly states: "No clinical data were included in this submission." This further confirms that the evaluation framework is entirely non-clinical and does not involve AI/ML performance metrics, studies with human readers, or expert ground truthing as one would see for an AI-powered diagnostic tool.

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