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The AutoTac System™ Titanium Tack is intended to fixate and stabilize bioresorbable and non-resorbable barrier membranes used for regeneration of tissue in the oral cavity or in other clinical situations that require membrane use or fixation.

The proposed membrane fixation tack is fabricated from titanium alloy as specified in ASTM F136 - Specification for Wrought Titanium 6AL-4V ELI Alloy for Surgical Implant Applications. This material was selected because of its known biocompatibility and mechanical properties. The tack is comprised of a low-profile, round, lens shaped head and a cvlindrical shaft that is tapered to a point at its free end. The shaft is provided with a circular rib (barb) that aids in retention of the tack under normal loading conditions. Three opposing tabs extend from the head of each tack and are designed to secure the tack within the delivery mechanism while transporting to the surgical site. The tack is designed for implantation during the healing period during which tissue regeneration takes place. The tacks are provided non-sterile and are to be sterilized by the user using accepted steam sterilization techniques. The autoclavable tack holder is manufactured from ULTEM medical grade material and consists of 21 receptacles for the tacks. A rotating lid serves to capture the tacks during handling so that the tacks do not dislodge from the autoclavable tack holder. Titanium inserts serve to hold the tack so that the end of the tack does not create wear debris after continued use. The autoclavable tack holder can hold up to 21 tacks.

Here's an analysis of the provided 510(k) summary regarding the BioHorizons Implant Systems, Inc. Titanium Tack, focusing on acceptance criteria and study details:

1. Table of Acceptance Criteria and Reported Device Performance

2. Sample Size Used for the Test Set and Data Provenance

The provided document does not specify a sample size for the "non-clinical testing." It generally refers to "bone analogs" and "in-vitro testing" without quantifiable sample numbers for tacks or tests performed.

The data provenance is in-vitro laboratory testing. There is no information provided about the country of origin, nor is it stated whether the data is retrospective or prospective, as it's not a clinical study.

3. Number of Experts Used to Establish Ground Truth and Qualifications

This information is not applicable to the "non-clinical testing" described. The "ground truth" for this type of testing is established by engineering and material science principles, measured directly through physical tests on bone analogs and the device itself, rather than expert interpretation.

4. Adjudication Method

This information is not applicable. Adjudication methods are typically used in clinical studies or multi-reader image interpretations to resolve discrepancies among experts. The non-clinical tests described are objective, physical measurements.

5. Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study

A multi-reader multi-case (MRMC) comparative effectiveness study was not conducted. The provided information details non-clinical, in-vitro mechanical testing of the device itself, not a study involving human readers or assessment of AI assistance.

6. Standalone (Algorithm Only) Performance Study

A standalone performance study was not conducted. This device is a physical medical implant, not an AI algorithm. Therefore, "algorithm only" performance is not relevant.

7. Type of Ground Truth Used

The ground truth used for the non-clinical testing was based on:

• Objective physical measurements: Assessing the depth of penetration into bone analogs.
• Visual inspection: Confirming the absence of structural deformation.
• Mechanical force testing: Demonstrating that the membrane would tear before the tack dislodged, indicating superior retention force of the tack.

8. Sample Size for the Training Set

This information is not applicable. The device is a physical implant, not an AI model that requires a training set.

9. How the Ground Truth for the Training Set Was Established

This information is not applicable for the same reason as above (no training set for a physical device).

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The AUTOTAC System™ is intended to fixate and stabilize bioresorbable and non-bioresorbable barrier membranes used for regeneration of tissue in the and normbloroonbable ituations that require membrane use/fixation.

The AUTOTAC System™ is intended to fixate or stabilize bioresorbable barrier membranes used for regeneration of tissue and/or bone in the oral cavity or in other clinical situations that require membrane use/fixation.

The AUTOTAC System™ consists of components and instruments designed to fixate and stabilize bioresorbable and non-bioresorbable barrier membranes used for regeneration of tissue and/or bone in the oral cavity or in other clinical situations that require membrane use/fixation. The system provides an anchoring mechanism for the membranes to resident and adjacent bone or tissue at the surgical site. The Tissue Tack is fabricated from a well-known bioresorbable polymer and has a round, flat head, and two circular ribs on the shaft to prevent the implanted tack from slipping out. The tack is provided sterile by either gamma or ETO sterilization and is not intended to be re-sterilized by the user.

Here's an analysis of the provided text regarding the AUTOTAC System™, focusing on acceptance criteria and supporting studies:

This document is a 510(k) summary for a medical device modification (K011675), which primarily focuses on demonstrating substantial equivalence to a predicate device rather than presenting a detailed clinical study for novel device performance. As such, it does not contain all the typically requested information for a comprehensive study design demonstrating acceptance criteria.

Specifically, the document primarily addresses the mechanical performance and safety of the device through laboratory testing and clinical consultation, but it does not provide quantitative acceptance criteria or detailed study results in a format typically expected for demonstrating clinical effectiveness or accuracy in the way an AI/software device would.

However, I will extract and infer information where possible based on the provided text.

Acceptance Criteria and Reported Device Performance

Study Information (Based on available text)

Given the nature of this 510(k) for a physical device (a fixation tack), the study information requested is typically for software/AI devices or more complex clinical trials. The provided document details a regulatory submission for substantial equivalence of a physical medical device, not a performance study of an AI algorithm. Therefore, many of the requested fields are not applicable (N/A) or not detailed in this type of document.

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

   • Test Set Sample Size: Not specified. The document mentions "mechanical tests" and "laboratory studies" but does not give sample sizes for these tests.
   • Data Provenance (country of origin, retrospective/prospective): Not specified. "Laboratory studies" generally imply controlled, prospective testing in a lab environment rather than clinical data from a specific country or population.

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

   • Number of Experts: "consulting clinicians" (plural) were involved. The exact number is not stated.
   • Qualifications of Experts: Not specified beyond being "clinicians." There is no mention of specialties or years of experience. For a physical device like this, these clinicians would likely be oral surgeons, periodontists, or related specialists.

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

   • Adjudication Method: Not applicable/not specified. Clinical "adjudication" in the sense of resolving discrepancies in diagnostic reads (common for image analysis AI) is not relevant for the type of evaluation described here for a physical tack. The "consulting clinicians" likely provided a collective qualitative assessment.

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:

   • MRMC Study: No, this type of study was not done. This is a physical device, not an AI system.
   • Effect size of human readers with/without AI assistance: Not applicable.

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

   • Standalone Study: Not applicable. This is a physical device, not an algorithm.

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

   • Type of Ground Truth: For the mechanical tests, the "ground truth" would be the measured physical properties (e.g., force required for pull-out/shear) against an implicitly accepted standard for "sufficiency." For the clinical evaluation, it appears to be a qualitative "expert consensus" from the "consulting clinicians" regarding effectiveness and predictability, likely based on their professional judgment and experience with membrane fixation.

7. The sample size for the training set:

   • Training Set Sample Size: Not applicable. This is a physical device, not a machine learning model. There is no "training set."

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

   • Ground Truth for Training Set: Not applicable. There is no training set for this device.

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The AUTOTAC System™ is intended to fixate and stablize bioresorbable and non-bioresorbable barrier membranes used for regeneration of tissue in the oral cavity or in other clinical situations that require membrane use/fixation.
The AUTOTAC System™ is intended to fixate or stabilize bioresorbable barrier membranes used for regeneration of tissue and/or bone in the oral cavity or in other clinical situations that require membrane use/fixation.

The AUTOTAC System™ consists of components and instruments designed to fixate and stabilize bioresorbable and non-bioresorbable barrier membranes used for regeneration of tissue and/or bone in the oral cavity or in other clinical situations that require membrane use/fixation. The system provides an anchoring mechanism for the membranes to resident and adjacent bone or tissue at the surgical site. The Tissue Tack is fabricated from a well-known bioresorbable polymer and has a round, flat head, and two circular ribs on the shaft to prevent the implanted tack from slipping out. The tack is provided sterile and is not intended to be resterilized by the user.

The provided text describes a 510(k) premarket notification for "The AUTOTAC System™," a medical device intended to fixate and stabilize barrier membranes in tissue regeneration. The submission focuses on demonstrating substantial equivalence to predicate devices rather than providing detailed acceptance criteria and a study design with performance metrics typically found in clinical efficacy trials for novel devices.

Therefore, much of the requested information regarding specific acceptance criteria, study methodologies, and performance metrics is not available in the provided document. The 510(k) pathway primarily relies on demonstrating equivalence in terms of intended use, technological characteristics, and safety/effectiveness, often through non-clinical testing and comparison to legally marketed predicate devices.

Here's what can be extracted from the provided text:

1. Table of Acceptance Criteria and Reported Device Performance

2. Sample Size Used for the Test Set and Data Provenance

• Sample Size: Not explicitly stated for animal tests, laboratory studies, or mechanical tests. The document refers to "animal tests and laboratory studies" and "in-vitro mechanical tests" broadly.
• Data Provenance: The studies mentioned are "animal tests" and "laboratory studies," implying pre-clinical data. The country of origin is not specified, but the submission is to the US FDA. The studies are prospective in the sense that they were conducted for the purpose of this submission.

3. Number of Experts Used to Establish the Ground Truth for the Test Set and Qualifications

• Number of Experts: "Consulting clinicians" were involved in evaluating the system in animal and laboratory tests. The specific number is not provided.
• Qualifications: "Consulting clinicians" are mentioned. No further details on their specific qualifications (e.g., area of specialization, years of experience) are provided.

4. Adjudication Method for the Test Set

• No information on adjudication methods is provided. The evaluation by "consulting clinicians" is mentioned, implying expert assessment, but the process of reaching consensus or resolving discrepancies is not described.

5. Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study

• No, a multi-reader multi-case (MRMC) comparative effectiveness study was not conducted or reported in the provided text. This type of study is more common for diagnostic imaging AI systems to evaluate physician performance with and without AI assistance, which is not relevant to this device (a physical implant/fixation system).

6. Standalone (Algorithm Only) Performance Study

• No, a "standalone" performance study (in the context of an algorithm's performance without human intervention, as typically seen with AI/software as a medical device) was not conducted. The AUTOTAC System is a physical medical device. The "standalone" concept doesn't apply to the same degree as it would for a diagnostic algorithm. The device's performance is inherently tied to its use by a clinician.

7. Type of Ground Truth Used

• For the functional effectiveness, the "ground truth" seems to have been established through expert clinical observation and assessment in animal models and laboratory settings, determining "effectiveness for fixation of barrier membranes without new health risks" and leading to "clinical success."
• For mechanical tests, the "ground truth" for equivalence in pull-out strength and resistance to shear loading would be quantitative measurements of these physical properties compared to predicate devices, presumably against engineering specifications or established performance benchmarks.

8. Sample Size for the Training Set

• This concept is not applicable here. The AUTOTAC System is a physical medical device, not an AI or machine learning algorithm that requires a "training set" in the conventional sense. The "training" for such a device would be its iterative design, development, and testing processes.

9. How the Ground Truth for the Training Set Was Established

• As stated above, the concept of a "training set" doesn't apply to this physical device. Therefore, no information on how its ground truth was established is relevant or provided.

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