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3Shape Implant Studio is an implant planning and surgery planning software tool intended for use by dental professionals who have appropriate knowledge in dental implantology and surgical dentistry. This software reads imaging information output from medical scanners such as CT and optical scanners. It allows pre-operative simulation of patient anatomy and dental implant placement.

Surgical guides and the planned implant position can be exported as 3D models and the guides can be manufactured using said 3D models when used as input to 3D manufacturing systems.

3Shape Implant Studio® is a stand-alone software device used to pre-operatively plan the placement of a dental implant based on the visualization of a patient's CT image, optionally aligned to an optical 3D surface scan. A virtual surgical quide can be designed and then exported to an external system for manufacturing.

The device has no patient contact being a software only device.

Here's an analysis of the provided text regarding the acceptance criteria and study for the 3Shape Implant Studio, structured as requested:

Acceptance Criteria and Device Performance Study for 3Shape Implant Studio (K202256)

Unfortunately, the provided text does not include a detailed table of acceptance criteria with reported device performance metrics. It mentions that "Each user need has its own validation acceptance criteria; each specification has its own verification acceptance criteria," and that "All test results have been reviewed and approved, showing 3Shape Implant Studio® to be substantially equivalent in safety and effectiveness to the primary predicate device." However, specific numerical targets or the device's performance against those targets are not present within this document.

Therefore, the following sections will address what information is available and highlight what is missing.

1. Table of Acceptance Criteria and the Reported Device Performance

2. Sample Size Used for the Test Set and the Data Provenance

• Sample Size: The document does not specify the sample size used for either verification or validation testing.
• Data Provenance: The document does not specify the country of origin of the data or whether it was retrospective or prospective. It only mentions that the software "reads imaging information output from medical scanners such as CT and optical scanners" and visualizes "an imported CT image from DICOM data."

3. Number of Experts Used to Establish the Ground Truth for the Test Set and the Qualifications of Those Experts

• The document does not provide any information regarding the number of experts, their qualifications, or their role in establishing ground truth for the test set.

4. Adjudication Method for the Test Set

• The document does not provide any information regarding an adjudication method for the test set.

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

• The document does not mention a multi-reader multi-case (MRMC) comparative effectiveness study.
• The device is described as an "implant planning and surgery planning software tool" intended for use by "dental professionals." It is a tool for pre-operative simulation and planning, rather than an AI-driven diagnostic or interpretative tool that would typically involve human-in-the-loop performance studies as described.

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

• Yes, the performance testing appears to be a standalone (algorithm only) assessment. The document states, "Software, hardware, and integration verification and validation testing was performed." The focus is on the software's functionality in terms of processing imaging data, enabling planning, and designing surgical guides, not on how human users perform with or without the software. The "summative evaluation" mentioned could potentially involve human interaction to assess usability but the performance itself is described as the software's inherent capabilities.

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

• The document does not explicitly state the type of ground truth used. Given the nature of an implant planning software, the "ground truth" would likely relate to the accuracy of 3D reconstructions, measurements, planning parameters, and the fit/design of surgical guides. This would typically be established by expert dental professionals using established anatomical references, CAD/CAM standards, and potentially phantom models. However, this is inferred, not stated.

8. The sample size for the training set

• The document does not mention a training set. This is because the 3Shape Implant Studio is described as software that allows pre-operative simulation and evaluation based on imported scan data, and is used for designing surgical guides. It is not presented as a machine learning or AI algorithm that implicitly learns from a dataset (i.e., it doesn't appear to be a 'learning' algorithm in the sense that it requires a training set for model development). It is a CAD design and visualization tool.

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

• As the document does not mention a training set (see point 8), there is no information on how its ground truth would have been established.

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NobelClinician® (DTX Studio Implant) is a software interface for the transfer and visualization of 2D and 3D image information from equipment such as a CT scanner for the purposes of supporting the diagnostic process, treatment planning and follow-up in the dental and cranio-maxillofacial regions.

NobelClinician® (DTX Studio Implant) can be used to support guided implant surgery and to provide design input for and review of dental restorative solutions. The results can be exported to be manufactured.

NobelClinician® is a software interface used to support the image-based diagnostic process and treatment planning of dental, cranio-maxillofacial, and related treatments. The product will also be marketed as DTX Studio implant.

The software offers a visualization technique for (CB)CT images of the patient for the diagnostic and treatment planning process. In addition, 2D image data such as photographic images and X-ray images or surface scans of the intra-oral situation may be visualized to bring diagnostic image data together. Prosthetic information can be added and visualized to support prosthetic implant planning. The surgical plan, including the implant positions and the prosthetic information, can be exported for the design of dental restorations in NobelDesign® (DTX Studio design).

Surgical planning may be previewed using the software and the related surgical template may be ordered.

This document is a 510(k) premarket notification summary for the NobelClinician® (DTX Studio Implant) software. The information provided heavily focuses on regulatory comparisons to a predicate device rather than detailed study protocols and results for meeting specific acceptance criteria in a typical clinical performance study.

Based on the provided text, the device is a "Picture archiving and communications system" (PACS) software, classified under 21 CFR 892.2050. The performance data presented are primarily non-clinical.

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

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

The document does not explicitly present a table of acceptance criteria and reported device performance in the manner typically found in a clinical study report. Instead, it states that "Software verification and validation per EN IEC 62304:2006" was performed. This implies that the acceptance criteria would be related to the successful completion of these verification and validation activities, demonstrating that the software meets its specified requirements and is fit for its intended use, as defined by the standard.

Since specific performance metrics (e.g., accuracy, precision) for diagnostic or treatment planning tasks are not quantified or presented in this regulatory summary, a table showing such criteria and performance cannot be constructed from this document.

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 provide details on the sample size used for a test set or the provenance of any data beyond indicating "non-clinical studies". This suggests that a traditional clinical test set with patient data for evaluating performance metrics was not the focus of the "performance data" section in this 510(k) summary. The listed activity "Software verification and validation per EN IEC 62304:2006" typically involves testing against synthetic data, simulated scenarios, or existing clinical datasets used for functional and performance testing of software, rather than a prospective clinical study with a defined "test set" in the sense of patient cases.

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. Given that the performance data mentioned refers to "Software verification and validation per EN IEC 62304:2006," it is unlikely that a formal ground truth establishment by a panel of clinical experts for a test set (as in a diagnostic accuracy study) was conducted or reported in this summary.

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

The document does not mention any multi-reader multi-case (MRMC) comparative effectiveness study. The "performance data" section is limited to "Non-Clinical Studies - Software verification and validation per EN IEC 62304:2006".

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

The document does not explicitly state whether a standalone algorithm-only performance study was conducted. The device is described as "a software interface for the transfer and visualization of 2D and 3D image information from equipment... for the purposes of supporting the diagnostic process, treatment planning and follow-up...". This indicates a human-in-the-loop context for its intended use. The verification and validation activities would assess the software's functional correctness for these tasks.

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

Since the document only refers to "Software verification and validation per EN IEC 62304:2006" as performance data, the specific type of "ground truth" used for these non-clinical tests is not detailed. For software testing, ground truth could involve:

• Pre-defined expected outputs for given inputs.
• Comparisons to known good results from previous versions or manually calculated values.
• Adherence to specifications and design requirements.
  Formal clinical ground truth (like pathology or outcomes data) is not mentioned.

8. The sample size for the training set

This document does not indicate that the device involves AI/machine learning requiring a "training set" in the conventional sense. The "performance data" refers to software verification and validation, which focuses on the deterministic functionality of the software according to its specifications, not statistical learning from data.

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

As there is no mention of an AI/machine learning component requiring a training set, this information is not applicable and not provided in the document.

In summary, the provided FDA 510(k) summary focuses on demonstrating substantial equivalence to a predicate device based primarily on non-clinical software verification and validation activities. It does not contain detailed information about a clinical performance study with specific acceptance criteria, test sets, expert ground truth establishment, or comparative effectiveness studies of the type you've inquired about.

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