(42 days)
Materialise's 3Matic is intended for use as software for computer assisted design and manufacturing of medical exo- and endo-prostheses, patient specific medical and dental/orthodontic accessories and dental restorations.
Software for computer assisted design and manufacturing of medical and dental prostheses.
This 510(k) summary for the 3Matic software does not include a detailed study proving the device meets specific acceptance criteria with reported performance metrics. Instead, it relies on substantial equivalence to predicate devices (SimPlant System and Etkon ES-1) without presenting new performance data for 3Matic itself.
Therefore, many of the requested details about acceptance criteria and study design are not available in the provided document.
Here's a breakdown of what can be extracted and what is not available:
1. Table of Acceptance Criteria and Reported Device Performance
| Acceptance Criteria | Reported Device Performance |
|---|---|
| Not Available (NA) | NA |
| The document states substantial equivalence to predicate devices but does not define specific performance acceptance criteria for 3Matic or report any quantitative performance metrics for the device. |
2. Sample size used for the test set and the data provenance
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Sample Size (Test Set): NA
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Data Provenance: NA
The document does not describe any specific test set or data used to evaluate 3Matic's performance.
3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts
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Number of Experts: NA
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Qualifications of Experts: NA
As there is no described test set or ground truth establishment, this information is not applicable.
4. Adjudication method for the test set
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Adjudication Method: NA
No test set or ground truth adjudication process is 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
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MRMC Study: No.
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Effect Size: NA
The document does not mention any MRMC study or an assessment of human reader performance with or without AI assistance.
6. If a standalone (i.e. algorithm only without human-in-the loop performance) was done
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Standalone Performance Study: No.
No standalone performance study is described for the 3Matic software.
7. The type of ground truth used (expert consensus, pathology, outcomes data, etc.)
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Type of Ground Truth: NA
No ground truth is described as having been used to evaluate 3Matic.
8. The sample size for the training set
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Sample Size (Training Set): NA
The document does not provide details about a training set for the 3Matic software.
9. How the ground truth for the training set was established
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Training Set Ground Truth Establishment: NA
No training set or its ground truth establishment is described.
Summary of the Document's Approach:
The provided 510(k) summary for the Materialise 3Matic system establishes its safety and effectiveness through substantial equivalence to existing predicate devices (SimPlant System and Etkon ES-1). This means that the manufacturer asserted, and the FDA agreed, that the 3Matic device is as safe and effective as the predicate devices because it shares similar technological characteristics and is intended for the same use.
This regulatory pathway typically does not require new clinical or performance studies if the differences from the predicate device do not raise new questions of safety or effectiveness. Therefore, the document focuses on demonstrating these similarities rather than presenting novel performance data for 3Matic itself against predefined acceptance criteria.
§ 892.2050 Medical image management and processing system.
(a)
Identification. A medical image management and processing system is a device that provides one or more capabilities relating to the review and digital processing of medical images for the purposes of interpretation by a trained practitioner of disease detection, diagnosis, or patient management. The software components may provide advanced or complex image processing functions for image manipulation, enhancement, or quantification that are intended for use in the interpretation and analysis of medical images. Advanced image manipulation functions may include image segmentation, multimodality image registration, or 3D visualization. Complex quantitative functions may include semi-automated measurements or time-series measurements.(b)
Classification. Class II (special controls; voluntary standards—Digital Imaging and Communications in Medicine (DICOM) Std., Joint Photographic Experts Group (JPEG) Std., Society of Motion Picture and Television Engineers (SMPTE) Test Pattern).