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The TMINI™ Miniature Robotic System is indicated as a stereotaxic instrumentation system for total knee replacement (TKA) surgery. It is to assist the surgeon by providing software-defined spatial boundaries for orientation and reference information to identifiable anatomical structures for the accurate placement of knee implant components.

The robotic device placement is performed relative to anatomical landmarks as recorded using the system intraoperatively and based on a surgical plan determined preoperatively using CT based surgical planning tools.

It includes a handheld robotic device, an optical sensor navigation system and accessories, software system, surgical instruments and accessories.

The targeted population has the same characteristics as the population that is suitable for the implant(s) compatible with the TMINI™ Miniature Robotic System. The TMINI™ Miniature Robotic System is to be used with the following knee replacement system(s) in accordance with the indications and contraindications: Enovis™ EMPOWR Knee System®.

The TMINI™ Miniature Robotic System consists of three primary components: a three-dimensional, graphical, Preoperative Planning Workstation (TPLAN Planning Station), an Optical Tracking Navigation Console (TNav) and a Robotically Controlled Hand-held Tool (TMINI Robot) that assists the surgeon in preparing the bone for implantation of TKA components.

The TPLAN Planning Station uses preoperative CT scans of the operative leg to create 3D surface models for case templating and intraoperative registration purposes. The Planning Workstation contains a library of 510(k) cleared knee replacement implant(s). The surgeon can select an implant model from this library and manipulate the 3D representation of the implant in relation to the bone model to optimally place the implant. Once the surgeon is satisfied with the implant location and orientation, the data is written to a file that is used to guide the robotically controlled hand-held tool.

The handheld robotic tool is optically tracked relative to optical markers placed in both the femur and tibia and articulates in two degrees-of-freedom, allowing the user to place bone pins in a planar manner in both bones. Mechanical guides are clamped to the bone pins, resulting in subsequent placement of cut slots and drill guide holes such that the distal femoral and proximal tibial cuts can be made in the pre-planned positions and orientations, and such that the implant manufacturer's multi-planer cutting block can be placed relative to drilled distal femoral pilot holes.

The provided text does not contain detailed information about specific acceptance criteria and a study proving the device meets them in the way described in the prompt. Instead, it focuses on demonstrating substantial equivalence to a predicate device (Rosa Knee System) for FDA clearance.

However, I can extract the information related to performance testing that is mentioned as part of the substantial equivalence claim.

Here's an attempt to answer based on the available information, highlighting where details are missing:

The TMINI™ Miniature Robotic System (K230202) underwent performance testing to support its substantial equivalence to the legally marketed predicate, Rosa Knee System (K182964).

1. Table of Acceptance Criteria and Reported Device Performance

2. Sample size used for the test set and the data provenance:

• Cutting Accuracy: The text states "< 0.5mm RMSE" as the reported device performance. It also mentions "See Section 19 for Details" regarding Cutting Accuracy and Cadaver Lab Validation. Without access to Section 19, the specific sample size, data provenance (e.g., country of origin, retrospective/prospective), and whether this refers to a test set in the context of an AI study are not available in this document. This typically refers to a performance study on cadavers or simulated bone, not an AI test set with "data provenance" in the usual imaging sense.
• For Biocompatibility, Software, EMC/Electrical Safety, and Cadaver Lab Validation, specific sample sizes and data provenance are not detailed in this summary.

3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts:

This information is not provided in the document. The performance tests mentioned (Biocompatibility, Cutting Accuracy, Cadaver Lab Validation, Software, EMC/Electrical Safety) are typically engineering and clinical performance evaluations, not diagnostic accuracy studies involving expert interpretation of data.

4. Adjudication method for the test set:

This information is not provided because the performance tests described do not involve adjudication by experts in the context of a diagnostic AI study.

5. If a multi-reader multi-case (MRMC) comparative effectiveness study was done, and if so, what was the effect size of how much human readers improve with AI vs without AI assistance:

This is irrelevant for this submission. The TMINI™ Miniature Robotic System is described as a stereotaxic instrumentation system to assist surgeons in total knee replacement surgery by providing software-defined spatial boundaries and orientation/reference information. It is not an AI-powered diagnostic tool that assists human readers (e.g., radiologists) in interpreting images. Therefore, an MRMC study is not applicable to this device type.

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

The device description indicates human-in-the-loop operation, as it "assists the surgeon" and involves a "handheld robotic device" and a "surgical plan determined preoperatively using CT based surgical planning tools." The performance claim for cutting accuracy is for the robotic system, implying its standalone mechanical accuracy, but it's always in the context of assisting a surgeon.

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

For Cutting Accuracy, the ground truth would likely be a precise physical measurement of the achieved cut planes/pin placements compared to the pre-planned positions and orientations. This would be established through metrology or other highly accurate measurement techniques in a laboratory or cadaveric setting. For other tests like Biocompatibility, Software, EMC/Electrical Safety, and Cadaver Lab Validation, the ground truth would be adherence to established standards or clinical protocols.

8. The sample size for the training set:

This information is not provided. The TMINI™ system uses CT-based surgical planning tools. While software is involved, the primary focus of the performance testing presented is on the accuracy and safety of the robotic system's physical actions rather than a machine learning model's training data.

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

This information is not provided. If there is a machine learning component, details of its training data and ground truth establishment are not included in this summary. However, given the nature of the device (robotic surgical assistance), "training set" might refer to data used to develop the planning algorithms or robotic control, which would have different ground truth establishment methods than, for example, an image classification AI.

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