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The Minimally Invasive Bunion Plating System is intended for fixation of osteotomies and corrective procedures of the hallux and associated disorders such as hallux valgus.

The Minimally Invasive Bunion Plating System consists of left and right plates composed of implant grade titanium intended for fixation of osteotomies and corrective procedures of the hallux and associated disorders such as hallux valgus. The system will incorporate both locking and non-locking screws, cannulated screws, and the necessary instruments to facilitate the placement of these implants.

This document is a 510(k) Premarket Notification from the FDA regarding a medical device, the "Minimally Invasive Bunion Plating System". It aims to establish substantial equivalence to a legally marketed predicate device, not to prove the device meets specific acceptance criteria through a study demonstrating performance.

Therefore, the requested information regarding acceptance criteria and a study proving the device meets them cannot be extracted from this document for the following reasons:

• No Acceptance Criteria or Performance Study: This document does not describe acceptance criteria related to a specific performance study (e.g., accuracy, sensitivity, specificity, or clinical outcomes) for the device's function in terms of an AI/algorithm. This is a traditional medical device (bunion plating system), not an AI/algorithm device. The "acceptance criteria" here are the FDA's regulatory criteria for market clearance (substantial equivalence), not performance metrics against a clinical ground truth.
• No Clinical Study Performed: The document explicitly states under Section V. "Clinical Test Summary": "No clinical studies were performed." This means there is no study data to report for points 1, 5, 6, 7, 8, or 9.
• Focus on Substantial Equivalence: The entire submission is built on demonstrating substantial equivalence to a predicate device based on similarities in intended use, design, materials, and mechanical safety/performance, supported by non-clinical (mechanical) testing. It does not involve a study of an AI/algorithm's performance against a human expert's assessment or a defined ground truth.

Therefore, I cannot populate the requested table or answer the specific questions about AI/algorithm performance studies. The information provided is for a physical medical device (bone plates and screws), not a software/AI device.

The "Non-Clinical Test Summary" section mentions:

• Non-Clinical Test Summary:
  • Single Cycle Bend Testing referencing ASTM F382
  • Dynamic Bend Testing referencing ASTM F382
  • "The results of these evaluations indicate that the Minimally Invasive Bunion Plating System is equivalent to the predicate devices."

This is the extent of "testing" mentioned, and it pertains to mechanical properties, not an AI's diagnostic or predictive performance.

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The Gridlock Ankle Plating System is intended for use in trauma and reconstructive procedures of the hand/foot, ankle, distal tibia, fibula, and other bones appropriate for the size of the device.

The plates (implant), screws (implant), olive wires (instrument), and guide wires (instrument) are intended for single use only.

Gridlock Ankle Plating System consists of various shape and size plates for the management of orthopedic osteotomies, reconstruction, and trauma. Features include a low profile, limited contact, capability of dynamic/manual compression, and angulated-locking threaded screw holes. The system also consists of multiple locking/standard screw lengths and diameters and the necessary instruments to facilitate the placement of these implants.

The provided document, a 510(k) summary for the "Gridlock Ankle Plating System," does not describe a study involving an algorithm or artificial intelligence (AI) for diagnostic purposes. Instead, it details the system's design, materials, and non-clinical mechanical performance tests to demonstrate substantial equivalence to existing predicate devices for bone fixation.

Therefore, the requested information regarding acceptance criteria and studies proving the device meets those criteria, specifically concerning AI performance, cannot be extracted from this document. The document focuses on the physical characteristics and mechanical properties of a surgical implant system.

Here's an analysis of what is present in the document related to "acceptance criteria" and "studies," acknowledging it's not in the context of AI performance:

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

The document doesn't provide a specific table of acceptance criteria with numerical targets and reported performance values in the way one might expect for a diagnostic AI. However, it implicitly uses a standard for equivalence to predicate devices based on mechanical testing.

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

• Sample Size: Not explicitly stated for each test (Screw Torque to Failure, Plate 4-Point Bending). These are likely conducted on a defined number of devices according to the ASTM standards.
• Data Provenance: Not applicable as these are non-clinical, in-vitro mechanical tests, not based on patient data.

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):

• Not applicable. Ground truth in this context refers to mechanical properties measured during laboratory testing, not medical diagnoses made by experts.

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

• Not applicable. This pertains to expert review of diagnostic findings, not mechanical testing.

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:

• No MRMC comparative effectiveness study was done. The device is a surgical implant, not a diagnostic tool where human readers would interpret results with or without AI assistance. The "Clinical Test Summary" explicitly states: "No clinical studies were performed."

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

• Not applicable. The device is a physical bone fixation system, not an algorithm.

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

• The "ground truth" for this device's performance evaluation is based on established mechanical standards (ASTM F543 for Screw Torque to Failure and ASTM F382 for Plate 4-Point Bending). The comparison is made against the performance of predicate devices tested under similar conditions.

8. The sample size for the training set:

• Not applicable. This refers to an AI training set, which is not relevant to this device.

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

• Not applicable. This refers to an AI training set, which is not relevant to this device.

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The Tiger Cannulated Screw System is indicated for fixation of fractures, non-unions, arthrodeses, and osteotomies of bones appropriate for the size of the device.

The Tiger Cannulated Screw System is a headed and headless, cannulated, self-drilling, self-tapping screw system for the management of bone orthopedic osteotomies and trauma. The system consists of Ø2.0-Ø7.0 mm screws and washers, and the necessary instruments to facilitate the placement of these implants. The purpose of this submission is to add Ø5.5 mm and Ø7.0 mm headed cannulated screws to the Tiger Cannulated Screw System and to modify the indications for use statement for previously cleared devices (K081510 / K112737).

This document is a 510(k) premarket notification for the "Tiger Cannulated Screw System". It primarily discusses the substantial equivalence of this device to previously marketed predicate devices rather than presenting a study demonstrating the device meets specific acceptance criteria in a clinical or AI-related context.

Therefore, many of the requested sections (2, 3, 4, 5, 6, 7, 8, 9) regarding AI-specific study details, ground truth, expert involvement, and sample sizes for training/test sets are not applicable to this document as it pertains to a traditional medical device (bone screws) and not an AI/ML device.

However, I can extract information related to non-clinical testing and the comparison to predicate devices, which serve as the "acceptance criteria" for this type of submission.

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

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

• Not applicable for this type of device. The non-clinical tests (ASTM F543-07) involve mechanical testing of the screws, not data from human patients or a test set in the AI sense. The number of screws tested for each mechanical property would typically be specified in the full test report, but it's not detailed in this 510(k) summary.

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):

• Not applicable. This submission relies on engineering and material standards for mechanical properties rather than expert clinical assessment of patient data.

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

• Not applicable. This refers to methods for resolving discrepancies in expert labeling of AI datasets, which is not relevant here.

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:

• Not applicable. This is a mechanical device, not an AI-assisted diagnostic or therapeutic tool. No MRMC study was performed.

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

• Not applicable. This device is a surgical implant, not an algorithm.

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

• For the non-clinical tests, the "ground truth" or reference standard would be the defined specifications and performance characteristics of the predicate devices and the requirements of the ASTM F543-07 standard.

8. The sample size for the training set:

• Not applicable. There is no training set as this is not an AI/ML device.

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

• Not applicable. There is no training set for this type of device.

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