Search Results

The TDS (TECHWIN DENTAL SYSTEM) are prefabricated prosthetic components for direct connection to endosseous dental implants and are intended to be used as an aid in prosthetic rehabilitation. It is intended for use in edentulous and partially edentulous patients with established bone and completed growth period to support single unit prosthetic restorations in the mandible or maxilla. It is intended for one-stage and two-stage surgical procedures. This system is intended for delayed loading.

The TDS (TECHWIN DENTAL SYSTEM), made of Ti-6A1-4V ELI alloy (ASTM F136), is intended for use in conjunction with the appliance in partially or fully edentulous mandibles and maxillae to support single-unit loading (i.e., crown). It consists of the Dual Abutment and Healing Abutment. The surface of the abutments is uncoated or partially or half coated with TiN using AIP (Arc Ion Plating). The implant-to-abutment interface remains uncoated. All abutments are supplied non-sterile and must be autoclaved by the end-user.

This looks like a 510(k) premarket notification for a dental implant abutment system, not a software or AI-enabled device. Therefore, the detailed information about acceptance criteria, study design, sample sizes, ground truth establishment, expert adjudication, or MRMC studies for an AI/software device wouldn't be present in this document.

The document describes the acceptance criteria for the TDS (TECHWIN DENTAL SYSTEM) primarily through demonstrating substantial equivalence to an existing predicate device (K160536, Chaorum Implant System / Medimecca Co., Ltd.) through non-clinical testing.

Here's a breakdown of the information that can be extracted relevant to acceptance criteria and the studies performed, while noting the absence of AI/software-specific details:

1. Table of Acceptance Criteria and Reported Device Performance

Instead of performance metrics like sensitivity, specificity, or AUC for an AI device, the "acceptance criteria" for this physical device are met by demonstrating comparable properties and performance to the predicate device through various non-clinical tests.

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

• Sample Size: Not applicable in the context of an AI/software test set. For the non-clinical tests, specific sample sizes for material tests or sterilization validation are not detailed in this summary but would be part of the full submission.
• Data Provenance: The tests are non-clinical, primarily laboratory-based, and compare the subject device's properties against established international standards and the predicate device's characteristics. The company is based in the Republic of Korea.

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

• This is not applicable as there is no "ground truth" to be established by experts in the context of an AI/software's diagnostic performance. The evaluations are based on engineering and material science standards.

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

• Not applicable as this is not an AI/software diagnostic performance study requiring expert 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

• No. This is a physical medical device (dental implant abutment system), not an AI-enabled device. Therefore, no MRMC study was performed.

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

• No. This is a physical medical device.

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

• Not applicable to this type of device submission. The "truth" is based on the adherence of the device's physical, chemical, and biological properties to established international standards and the characteristics of the legally marketed predicate device.

8. The sample size for the training set

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

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

• Not applicable. This is not an AI/software device.

Ask a specific question about this device

The T-FIT is designed to provide a fixed anchorage point for attaching orthodontic appliances, facilitating the orthodontic movement of teeth. It is used temporarily and removed upon completion of the orthodontic treatment for use in patients aged 12 and older. The screws are intended for single use only.

The T-FIT is designed to serve as a fixed anchorage point for attaching orthodontic appliances to facilitate the movement of teeth during orthodontic treatment. The system is intended for temporary use and is removed once treatment is complete. The T-FIT is available in thread diameters Ø1.4 mm, 1.6 mm, and 2.0 mm and thread lengths of 6.0 mm, 8.0 mm, 10.0 mm, 12.0 mm, and 14.0 mm. Thread lengths of 12.0 mm and 14.0 mm are only available with Ø2.0 mm diameter models. All screws are manufactured from Ti-6Al-4V ELI titanium alloy (ASTM F 136-13). The T-FIT is provided non-sterile and is intended for single use only. Additionally, the T-FIT is designed to be used with commonly available dental surgical instruments.

The FDA 510(k) Premarket Notification for the T-FIT device does not contain information typically associated with acceptance criteria and studies for AI/ML-driven devices. The T-FIT is an orthodontic anchorage screw, a physical medical device, and the submission focuses on its material, dimensions, and mechanical performance compared to a predicate device.

Therefore, the requested information regarding acceptance criteria, reported performance, sample sizes for test sets, data provenance, expert ground truth establishment, adjudication methods, MRMC studies, standalone performance, ground truth types, and training set details are not applicable to this specific submission.

The document describes non-clinical performance testing for a physical device, primarily focusing on mechanical and biocompatibility aspects, as well as sterilization:

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

The document describes performance testing conducted according to recognized standards, rather than providing a table of specific acceptance criteria and reported performance values. The objective of these tests is to demonstrate substantial equivalence to the predicate device.

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

The document does not specify sample sizes for the mechanical tests, nor does it provide details on data provenance as these are physical device tests, not clinical data sets. The tests are "nonclinical," meaning they were conducted in a laboratory setting.

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. Ground truth, in the context of expert review, is not relevant for the mechanical and biocompatibility testing of a physical medical device.

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

Not applicable. Adjudication methods are typically used for establishing ground truth in clinical imaging or diagnostic studies, which is not the nature of the tests described here.

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 type of study is relevant for AI-assisted diagnostic devices, not for a physical orthodontic screw.

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

Not applicable. The T-FIT is a physical device, not an algorithm.

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

Not applicable. The "ground truth" for mechanical testing would be the physical properties measured under standardized conditions, and for biocompatibility, it would be the results from specified biological assays and tests against established safety limits for materials.

8. The sample size for the training set:

Not applicable. The T-FIT is a physical device; there is no "training set" in the context of machine learning.

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

Not applicable.

Ask a specific question about this device