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Non-Sterile Zirconia Block (Model name: ARENA Star, MontBlanc) are indicated for the production of artificial teeth in fixed or removable dentures, or for jacket crowns, facings, and veneers.

Non-Sterile Zirconia Block (Model name: ARENA Star. MontBlanc), used to produce dental restoration to support designing computer for dental use and to process cutting as a manufacture unit, on which CAD/CAM system is applied for processing and sintering.

This document is a 510(k) Premarket Notification from the FDA regarding a dental device, specifically "Non-Sterile Zirconia Block (ARENA Star, Mont Blanc)". It focuses on demonstrating substantial equivalence to a predicate device, rather than providing a detailed study that proves the device meets specific acceptance criteria through clinical or even extensive non-clinical performance data against set thresholds.

Therefore, many of the requested details about acceptance criteria, performance studies, sample sizes, expert involvement, and ground truth establishment (typical for AI/software as a medical device submissions) are not present in this document. This submission primarily relies on showing similarity in material properties and intended use to an already cleared device.

Here's an attempt to answer your questions based solely on the provided text:

Device: Non-Sterile Zirconia Block (ARENA Star, Mont Blanc)

1. Table of acceptance criteria and the reported device performance

The document does not present a table of acceptance criteria with specific quantitative thresholds that the device was tested against in a performance study, nor does it report detailed device performance metrics beyond stating that tests "passed the evaluation criteria and met the requirement."

Instead, it relies on comparison to a predicate device and adherence to a recognized standard (ISO 6872:2015). The "acceptance criteria" are implied by meeting the requirements of this standard and demonstrating equivalence to the predicate.

Note: The document explicitly states "No clinical study is included in this submission." The reported performance is based on non-clinical, in-vitro testing.

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

The document does not specify the sample sizes (e.g., number of blocks, number of samples tested for biocompatibility, etc.) used for the non-clinical tests.

The data provenance is from non-clinical tests conducted by ARUMDENTISTRY Co., Ltd. (Republic of Korea, based on the submitter's address). The tests are in-vitro studies, not clinical data from patients. The document does not specify if the data is retrospective or prospective, but given it's non-clinical testing, it would generally be considered prospective for the purpose of this submission.

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

This question is not applicable to this submission. The "ground truth" for material properties is established through standardized laboratory testing methods (e.g., measuring flexural strength, chemical composition, biocompatibility assays), not through expert consensus or interpretation of medical images. No human readers or experts are mentioned in the context of "ground truth" for the performance tests conducted.

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

This question is not applicable. Adjudication methods (like 2+1, 3+1) are typically used in clinical studies involving human interpretation (e.g., radiology reads) to establish a consensus ground truth. The tests performed are objective, laboratory measurements of material properties, not subjective assessments requiring adjudication.

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

This question is not applicable. This device is a dental material (zirconia block) used for manufacturing dental prosthetics, not an AI-powered diagnostic or assistive tool. Therefore, MRMC studies and assessment of AI assistance for human readers are not relevant. The document explicitly states, "No clinical study is included in this submission."

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

This question is not applicable. This device is a physical dental material, not an algorithm or software. Therefore, "standalone algorithm-only performance" is not a concept that applies here.

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

The "ground truth" for the non-clinical tests is based on objective, quantitative measurements of material properties according to recognized international standards (e.g., ISO 6872:2015 for mechanical properties, ISO 10993 series for biocompatibility). For instance, flexural strength is measured directly, rather than being determined by expert consensus or pathology.

8. The sample size for the training set

This question is not applicable. This is a physical device submission demonstrating substantial equivalence to a predicate, not a machine learning or AI device that requires a training set.

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

This question is not applicable, as there is no training set for this type of device submission.

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The NB 1 SA Implant System is indicated for use in partially or fully edentulous mandibles and maxillae, in support of single or multiple-unit restorations including; cemented retained, screw retained, or overdenture restorations, and terminal or intermediate Abutment support for fixed bridgework. NB 1 SA Implant System is dedicated for two stage surgical procedures and for immediate loading when there is good primary stability and an appropriate occlusal load. Also, implants with diameters larger than 5mm are indicated for molar regions.

The NB 1 SA Implant System is composed of ARUM NB 1 SA Fixture, ARUM NB Cover Screw, ARUM NB Healing Abutment, ARUM Cemented Abutment (Hex, Non-Hex), and Abutment screw. ARUM NB 1 SA Fixture is a thread type implant body made of TI CP4 according to ASTM F67 which will be placed in the alveolar bone to replace the function of the missing tooth. The surface of the fixture is treated with SLA (Sandblasted with Large grit and Acid-etching). The fixture is placed in the anterior or posterior site of maxillary or mandibular jawbone considering bone quality and bone quantity and it is connected with dental prostheses.

The document provided is a 510(k) Premarket Notification for the NB 1 SA Implant System. It primarily focuses on demonstrating substantial equivalence to predicate devices based on technological characteristics and non-clinical test data, rather than reporting on a specific study that evaluates device performance against acceptance criteria in a clinical setting.

Therefore, many of the requested details about acceptance criteria, device performance, sample sizes for test and training sets, ground truth establishment, and MRMC studies are not present in this document. The information provided heavily relies on non-clinical tests to support the substantial equivalence claim.

Here's an attempt to answer the questions based only on the provided text, indicating when information is not available:

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

Based on the provided text, the acceptance criteria are largely linked to meeting the requirements of specific ISO and ASTM standards for non-clinical testing. The "reported device performance" is that the results of these tests "met the criteria of the standards and demonstrated the substantial equivalence with the predicate device."

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

• Sample Size for Test Set: Not specified in the document. The testing described is primarily non-clinical (sterilization, shelf-life, biocompatibility, LAL endotoxin, material characteristics).
• Data Provenance: Not explicitly stated as "country of origin for data." The submitter is Arumdentistry Co., Ltd. from Daejeon, Republic of Korea. The testing itself is non-clinical and conducted in vitro or ex vivo (e.g., material testing, microbial inactivation). The document does not describe human subject data.
• Retrospective or Prospective: Not applicable as the described tests are non-clinical hardware tests.

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. The ground truth for the non-clinical tests is established by the specified international standards and guidelines (e.g., ISO, ASTM, AAMI/ANSI). No human expert "ground truth" derived from clinical data is described.

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

Not applicable. The described tests are non-clinical and do not involve adjudication by experts in the context of diagnostic interpretation.

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

No MRMC comparative effectiveness study is mentioned. The device is an endosseous dental implant system, not an AI-powered diagnostic tool for human readers.

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

This section is not applicable to the device described. The NB 1 SA Implant System is a physical dental implant.

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

For the non-clinical tests, the "ground truth" is defined by the technical specifications and performance requirements established in the referenced international standards (e.g., SAL of 10^-6 for sterility, specific material properties, successful validation of sterilization cycles, biocompatibility under ISO guidelines, etc.). No clinical ground truth (like pathology or outcomes data) is discussed for this 510(k).

8. The sample size for the training set

Not applicable. This document describes non-clinical testing of a physical medical device, not a machine learning algorithm that requires training data.

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

Not applicable, as no training set is mentioned or relevant to the device described.

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