Search Results

The AUTOLIGN is intended for use as a medical front-end device providing tools for management of orthodontic models, systematic inspection, detailed analysis, treatment simulation and virtual appliance design options (Export of Models, Indirect Bonding Transfer Media) based on 3D models of the patient's dentition before the start of an orthodontic treatment. It can also be applied during the treatment to inspect and analyze the progress of the treatment. It can be used at the end of the treatment to evaluate if the outcome is consistent with the planned/desired treatment objectives. The use of the AUTOLIGN requires the user to have the necessary training and domain knowledge in the practice of orthodontics, as well as to have received a dedicated training in the use of the software.

The AUTOLIGN is stand-alone software which utilizes images of the patient's intraoral anatomy from intraoral cameras and/or desktop laboratory scanners to create a 3D virtual dental model that can be used in the same manner as a traditional physical dental model. AUTOLIGN facilitates the segmentation and editing of the 3D virtual digital model as well as analysis which can be used in secondary orthodontic treatment planning. The software allows for measurement- including Bolton analyses. The models and analysis produced by the proposed Software can be exported to an orthodontic laboratory or directly to orthodontic appliance manufacturers for use in orthodontic treatment planning and design of orthodontic appliances. The material used for vacuum pressing (thermoforming) the final device appliances of sequential aligners on the production cast is DURAN®, but those which satisfy all the requirements specified on the Autoling User Manual can also be used.

The provided text describes the AUTOLIGN device and its comparison to predicate devices, but it does not contain specific acceptance criteria, a detailed study proving the device meets those criteria, or the requested information about sample sizes, ground truth establishment, or clinical study details.

The document is a 510(k) summary for the AUTOLIGN device, which is a software tool for orthodontic treatment planning and design. Its purpose is to demonstrate substantial equivalence to legally marketed predicate devices, not to present a detailed clinical validation study with specific performance metrics.

Here's what can be extracted and what is missing based on your request:

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

• Acceptance Criteria: Not explicitly stated in terms of quantitative performance metrics for the device itself (e.g., accuracy, sensitivity, specificity for specific measurements or analyses). The "acceptance" is implicitly that the software functions as intended and is as safe and effective as the predicate device.
• Reported Device Performance: The document only states that "The software passed the testing and performed per its intended use." No specific performance metrics or quantitative results are provided.

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

• Sample Size: Not mentioned.
• Data Provenance: Not mentioned.

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)

• Number of Experts: Not mentioned.
• Qualifications of Experts: Not mentioned.
• Ground Truth Establishment: Not mentioned.

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

• Not mentioned.

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

• An MRMC study is not mentioned. The study described is a non-clinical software verification and validation, along with a comparison to predicate devices. There is no mention of human readers or AI assistance in a comparative effectiveness context.

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

• The document implies standalone testing as it states "The AUTOLIGN underwent software, hardware, integration, verification and validation testing... The software passed the testing and performed per its intended use." However, specific standalone performance metrics (e.g., algorithm accuracy for segmenting teeth, or measuring arch length) are not provided. The device itself is described as "stand-alone software."

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

• Not mentioned.

8. The sample size for the training set

• Not mentioned, as there is no specific mention of a machine learning model or training set in the context of the device's validation.

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

• Not mentioned (for the same reason as point 8).

Summary of what is available from the text:

• Device Name: AUTOLIGN
• Regulatory Status: Class II medical device (K192847)
• Intended Use: Front-end device for managing orthodontic models, systematic inspection, detailed analysis, treatment simulation, and virtual appliance design based on 3D models of patient dentition.
• Non-clinical Tests: Software, hardware, integration, verification, and validation testing were performed according to FDA guidance.
• Result of Non-clinical Tests: "The software passed the testing and performed per its intended use."
• Predicate Device Comparison: The report extensively compares the AUTOLIGN's indications for use and technological characteristics to three predicate devices (Ortho System™, Orchestrate 3D, CEREC Ortho Software) to establish substantial equivalence.

In conclusion, the provided text focuses on regulatory approval through substantial equivalence to predicate devices and general software validation, rather than a detailed clinical study with quantitative acceptance criteria and performance metrics for the AUTOLIGN itself.

Ask a specific question about this device