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The AnyRidge Internal Implant System is intended to be surgically placed in the maxillary or mandibular molar areas for the purpose providing prosthetic support for dental restorations (Crown, bridges, and overdentures) in partially or fully edentulous individuals. It is used to restore a patient's chewing function: Smaller implants (less than ø6.0 mm) are dedicated for immediate loading when good primary stability is achieved and with appropriate occlusal loading. Larger implants are dedicated for the molar region and are indicated for delayed loading.

The AnyRidge Internal Implant System is especially designed for use in dental implant surgery. It consists of machined titanium, screw-form, rootform endosseous dental implant. The AnyRidge Internal Implant System contains two types of fixtures, Normal ridge type and low ridge type, various abutments and instruments. This system is made from pure titanium and the surface treatment is done with R.B.M. The implants are used to replace missing teeth in various situations ranging from a single missing tooth to the completely edentulous individual. The wide ranges of size are provided to be in conformance with each patient, or to cover up in case of due to deficiency in implant operation. The system is used as two stage, root-form dental implants, associated with abutment systems, which provide the clinician with the screw (for UCLA abutments) and cement (for solid abutments) retained restoration for multi-mount options. This system has 4.0, 4.4, 4.9, 5.4, 5.9mm diameters for normal ridge and 6.4, 6.9, 7.4, 7.9, 8.4mm diameters for low ridge fixtures. In addition, this system has 7.7, 9.2, 10.7, 12.2, 14.20, 17.20mm lengths for normal ridge and 7.9, 9.4, 10.9, 12.4, 14.4mm lengths for low ridge fixtures.

The provided text describes a 510(k) premarket notification for the AnyRidge Internal Implant System, which is a dental implant system. This type of submission relies on demonstrating substantial equivalence to a legally marketed predicate device, rather than providing extensive clinical study data that would be typical for novel devices or AI/ML-driven diagnostics.

Therefore, the acceptance criteria and study information typically requested for AI/ML devices or novel medical devices with performance claims are largely not applicable in this context. The focus of this 510(k) is on demonstrating that the new device is as safe and effective as existing, legally marketed devices.

Here's a breakdown based on the provided document, addressing the requested points where applicable, and noting where information is not present:

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

For a 510(k) based on substantial equivalence for a dental implant system, the "acceptance criteria" are primarily related to meeting established standards and being comparable to predicate devices in terms of design, materials, intended use, and performance where tested (e.g., fatigue). There are no specific quantitative performance metrics (like sensitivity/specificity for a diagnostic AI) provided in this document as acceptance criteria.

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

• Not applicable / not provided: This type of information (test set sample size, provenance related to clinical data for performance evaluation in the AI/ML sense) is not relevant for a 510(k) submission for a dental implant based on substantial equivalence. The "test set" here refers to the physical device's non-clinical testing (fatigue). The non-clinical test data for fatigue testing doesn't specify a "sample size" in the context of clinical or diagnostic data, but rather the number of samples tested for the engineering evaluation. No information on data provenance relating to patient populations is provided.

3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts (e.g. radiologist with 10 years of experience)

• Not applicable / not provided: The device is a physical dental implant. There's no "ground truth" to be established by experts in the context of a diagnostic AI/ML device. The "truth" for fatigue testing is whether the implant withstands certain loads according to the ISO standard.

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

• Not applicable / not provided: No adjudication method is described as there is no diagnostic or interpretive data requiring expert consensus.

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: This device is a dental implant, not a diagnostic AI or imaging system, so MRMC studies are not relevant.

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

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

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

• Not applicable (for AI/ML context): For the non-clinical fatigue testing, the "ground truth" is adherence to the ISO 14801 standard for dental implants. This involves objective engineering measurements of material strength and durability, not clinical outcomes or expert consensus on a diagnosis.

8. The sample size for the training set

• Not applicable: This device is not an AI/ML algorithm that requires a training set.

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

• Not applicable: This device is not an AI/ML algorithm that requires a training set.

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