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The MedCAD® AccuPlate® Patient-Specific Plate is intended for prescription use in oral and maxillofacial surgery, trauma and reconstructive surgery.

Specific Indications for Use:

• Primary mandibular reconstruction with bone graft
• Temporary bridging until delayed secondary reconstruction
• Secondary mandibular reconstruction
• Comminuted mandibular fractures
• Fractures of edentulous and/or atrophic mandibles
• Unstable mandibular fractures
• Maxillary reconstruction with or without bone graft
• Maxillary trauma

MedCAD® AccuPlate® Patient-Specific Plates are metal bone plates used in conjunction with commercially available metal bone screws for the fixation to bone, specifically in the areas of the mandible and maxilla. The design and dimensions of each plate within the envelope specification is based upon the patient's anatomical data (CT scan, CBCT scan, or MRI), and the intended anatomy to be fixated as determined from input provided by the surgeon. The plates are designed by MedCAD in consultation with the surgeon and manufactured by MedCAD only. MedCAD® AccuPlate® Patient-Specific Plates are not intended to be bent or modified in surgery. The MedCAD® AccuPlate® Patient-Specific Plates are manufactured from commercially pure titanium, are provided non-sterilized prior to use, and are intended for single use only. Plates are fastened to bone using commercially available bone screws with diameters ranging from 2.0 mm to 2.7 mm and lengths ranging from 4.0 mm to 23.0 mm.

This document is a 510(k) Premarket Notification from the FDA regarding the MedCAD® AccuPlate® Patient-Specific Plate. It is a medical device clearance document, not a study report for an AI/software device. Therefore, it does not contain the information typically presented for acceptance criteria and study results of an AI or software as a medical device (SaMD).

The document concerns a patient-specific bone plate used in oral and maxillofacial surgery. The "performance data" section refers to non-clinical functional and material testing (e.g., static and dynamic bending, screw pushout testing, sterilization, and biocompatibility validation) to demonstrate substantial equivalence to predicate devices, not performance metrics of an AI or software.

Therefore, I cannot provide the requested information regarding acceptance criteria and study results for an AI/software medical device because this document does not describe such a device or study.

Specifically:

1. A table of acceptance criteria and the reported device performance: The document mentions "All test method acceptance criteria were met" for sterilization validation and that mechanical tests showed the device "meets the performance of the predicate / reference devices." However, it does not provide specific acceptance values or performance metrics for these non-clinical tests in a table format that would be relevant to an AI/software device.
2. Sample sizes used for the test set and the data provenance: Not applicable to this type of device. The "test set" would refer to physical prototypes in mechanical testing, not a dataset for software.
3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts: Not applicable. Ground truth for physical device performance is established through engineering specifications and standardized testing protocols.
4. Adjudication method for the test set: Not applicable.
5. If a multi-reader multi-case (MRMC) comparative effectiveness study was done: Not applicable. This type of study is for evaluating human performance with and without AI assistance for clinical tasks, which is not the scope of this bone plate device.
6. If a standalone (i.e., algorithm only without human-in-the-loop performance) was done: Not applicable. This is not an algorithm.
7. The type of ground truth used: For physical performance testing, the ground truth is defined by engineering standards (e.g., ASTM F382 for bending, ISO 10993-1 for biocompatibility).
8. The sample size for the training set: Not applicable. This is a manufactured physical device, not an AI model.
9. How the ground truth for the training set was established: Not applicable.

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