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Meticuly patient-specific tianium mesh implant is a device that is designed individually for each patient. This device is intended for use in selective trauma of the craniofacial skeleton (e.g., frontal bone, temporal bone, occipital bone, parietal bone, sphenoid bone, supraorbital process, vomer), cranial and craniofacial surgery, and reconstructive procedures.

Meticuly's Patient-specific Titanium Mesh Implant is a device designed individually to replace each patient's bony voids in the cranial and/or craniofacial skeleton comprises of frontal bone, temporal bone, occipital bone, parietal bone, sphenoid bone, supraorbital process, vomer. This patient-specific device is intended to be used with titanium screws. The subject device has been validated and tested with titanium screws with the diameter of 1.4 mm - 1.8 mm (K141452 : Jeil Medical's LeForte Neuro system screws). The implant is made of titanium alloys produced via additive manufacturing (Laser Powder Bed Fusion). The surgeon approves the design of the mesh implant prior to fabrication of the implant device.

The provided text describes the Meticuly Patient-Specific Titanium Mesh Implant and its substantial equivalence determination by the FDA. However, it does not contain the specific information requested regarding an AI/ML powered device, specifically:

• It does not describe acceptance criteria or reported device performance in terms of metrics like sensitivity, specificity, accuracy, or F1-score, which are typical for AI/ML devices.
• It does not specify sample sizes for test or training sets in terms of patient numbers or image counts, nor data provenance (country of origin, retrospective/prospective).
• It does not mention the number or qualifications of experts used for ground truth, any adjudication methods, or MRMC comparative effectiveness studies.
• It does not refer to standalone performance for an algorithm or the type of ground truth (e.g., pathology, outcomes data).

Instead, the document details the performance testing for a physical medical device (a patient-specific titanium mesh implant). The performance tests focus on material properties, manufacturing quality, biocompatibility, sterilization, packaging, and mechanical properties. The "comparative device modeling with Finite Element Analysis (FEA)", "comparative mechanical testing with modified compression test", and "comparative roughness testing" are all hardware-related validation activities, not AI/ML algorithm validation.

Therefore, I cannot fulfill the request to provide the acceptance criteria and study details for an AI-powered device based on the provided text, as the text describes a physical implant and its regulatory submission, not an AI/ML device.

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The Additive Orthopaedics 3D Printed Bone Segments are intended to be used for internal bone fixation for bone fractures or osteotomies in the ankle and foot, such as:

*Cotton (opening wedge) osteotomies of the medial cuneiform *Evans lengthening osteotomies

The Additive Orthopaedics 3D Printed Bone Segments are intended for use with ancillary plating fixation.

The Additive Orthopaedics 3D Printed Bone Segments are not intended for use in the spine.

It is a patient specific device.

The Additive Orthopaedics Patient Specific 3D Printed Bone Segments is a simple one piece device constructed individually for each patient using CT image data. It is intended to be used for internal bone fixation for bone fractures or osteotomies in the foot and ankle. The segments are additively manufactured from medical grade titanium alloy (Ti-6AL-4V Eli). It is a patient specific device. The bone segments come in a variety of configurations that depend on the geometry of the application. The surgeon approves the design of the 3D Printed Bone Segments by comparing his/her design requirements to engineering drawings prior to the construction of the implant device.

This is a 510(k) premarket notification for a medical device, not an AI/ML device. Therefore, the requested information about acceptance criteria and studies (such as MRMC, standalone performance, ground truth, sample sizes for training/test sets, and expert qualifications) is not typically found in this type of document because it pertains to the evaluation of AI/ML algorithm performance.

Here's what can be extracted from the document regarding the device's evaluation, rephrased to align with the spirit of the request, focusing on how the device meets the regulatory requirements for "substantial equivalence":

Device Name: Additive Orthopaedics Patient Specific 3D Printed Bone Segments
510(k) Number: K180239

1. Table of Acceptance Criteria and Reported Device Performance

Since this is a non-AI/ML device submission, there are no "acceptance criteria" in the traditional sense of performance metrics like AUC, sensitivity, or specificity. Instead, the "acceptance criteria" are related to demonstrating substantial equivalence to a predicate device. The "performance" is shown through comparative testing against that predicate.

Study Proving Device Meets Criteria (Substantial Equivalence Study):

The submission highlights a substantial equivalence study based on non-clinical evidence.

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

This information is not applicable and not provided in the document. The evaluation is based on demonstrating equivalence in materials, manufacturing, indications, and non-clinical performance characteristics (morphological, mechanical, biocompatibility) rather than a "test set" of patient data for an algorithm. The "data" here refers to test results from the device itself and the predicate.

3. Number of Experts Used to Establish Ground Truth and Qualifications:

This information is not applicable. "Ground truth" in the context of an AI/ML device (e.g., expert consensus on medical images) is not relevant for this type of device submission. The verification of the patient-specific design is done by the surgeon.

4. Adjudication Method for the Test Set:

Not applicable. There is no "test set" in the sense of evaluating diagnostic performance.

5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study was done:

No, an MRMC study was not done. This type of study is relevant for evaluating the impact of AI on human reader performance, which doesn't apply to this 3D-printed bone segment device.

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

Not applicable. This device is a physical, patient-specific implant, not a standalone algorithm.

7. The type of ground truth used:

The concept of "ground truth" (e.g., pathology, outcomes data) as it applies to AI/ML diagnostic or prognostic devices is not relevant here. For device design, the "ground truth" for the patient-specific geometry is derived from the patient's CT image data and subsequently "verified by the surgeon."

8. The Sample Size for the Training Set:

Not applicable. There is no machine learning "training set" for this device. The device is custom-designed for each patient based on their CT scan data.

9. How the Ground Truth for the Training Set was Established:

Not applicable, as there is no training set. The patient-specific designs are generated using individual patient CT image data, and the final design is approved by the surgeon.

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