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Implant Studio™ is indicated for use as a medical front-end software that can be used by medically trained professionals for the purpose of visualizing gray value images. It is intended for use as a pre-operative planning software for the placement of dental implant(s) based on imported CT image data, optionally aligned to an optical 3D surface scan. Virtual Crowns can be used for optimized implant positioning under the prosthetic aspect. The digital three dimensional model of a surgical guide for a guided surgery can be designed based on the approved implant position. This 3D data can be exported to manufacture a separate physical product.

Indications of the dental implants do not change with guided surgery compared to conventional surgery.

Use of the software requires that the user has the necessary medical training in implantology and surgical dentistry.

Implant Studio™ is a software only device used to pre-operatively plan the placement of a dental implant and to visualize a patient's CT image, optionally aligned to an optical 3D surface data. Virtual crown(s) can be used to guide the planning under the final prosthetic aspect. The surgical quide data can be designed then exported to an external system for manufacturing.

The device has no patient contact.

The provided document is a 510(k) summary for a medical device called Implant Studio™ 2015-1. It describes the device, its intended use, and comparison to predicate devices, but it does not include a detailed study proving the device meets specific acceptance criteria in terms of performance metrics.

The document discusses "verification and validation testing" with "approved acceptance criteria" but does not provide the criteria themselves, nor the specific results demonstrating performance against these criteria. It states that "clinical testing is not a requirement and has not been performed."

Therefore, based on the information provided, I cannot fulfill all parts of your request. I will extract the available information.

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

The document states:

"Prior to release, verification and validation testing of the Implant Studio 2015-1 has been completed using the approved acceptance criteria: Each user need has its own validation acceptance criteria; each specification has its own verification acceptance criteria; bug verification consists in ensuring issue is not reproducible; issues reported by beta partners must be reviewed and handled appropriately."

However, the specific "acceptance criteria" (e.g., accuracy, precision, sensitivity, specificity) and the reported device performance metrics against these criteria are not detailed or provided in the given text. The document concludes that "All test results have been reviewed and approved, showing the Implant Studio to be substantially equivalent in safety and effectiveness to the predicate," but offers no quantitative data.

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

This information is not provided in the document.

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)

This information is not provided in the document. The document primarily focuses on software verification and validation, rather than a clinical performance study involving expert assessment of data.

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

This information is not provided in the document.

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

A multi-reader multi-case (MRMC) comparative effectiveness study was not performed. The document explicitly states: "Clinical testing is not a requirement and has not been performed." The device is a "medical front-end software" for planning and visualization, not an AI diagnostic tool requiring MRMC studies for reader improvement.

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

The document mentions "software, hardware, and integration verification and validation testing" to ensure the software "functions as intended." However, it does not describe a standalone performance study in terms of clinical outcomes or specific performance metrics (e.g., accuracy of implant placement prediction) for the algorithm itself. It is a "pre-operative planning software" and relies on human professionals for its use.

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

The document does not detail the specific "ground truth" used for testing beyond stating that "each user need has its own validation acceptance criteria; each specification has its own verification acceptance criteria." This implies internal testing against defined requirements rather than a clinical ground truth like pathology or outcomes data.

8. The sample size for the training set

This information is not provided in the document. The device is a software for planning and visualization, and while it processes medical images, the document does not indicate that it is an AI/ML device that requires a "training set" in the context of typical AI model development.

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

This information is not provided in the document, as there's no mention of a "training set" or AI model training.

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