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The Partial Knee Application (PKA), for use with the MAKO System, is intended to assist the surgeon in providing software defined spatial boundaries for orientation and reference information to anatomical structures during orthopedic procedures.

The Partial Knee Application (PKA), for use with the MAKO System, is indicated for use in surgical knee procedures in which the use of stereotactic surgery may be appropriate, and where reference to rigid anatomical bony structures can be identified relative to a CT based model of the anatomy. These procedures include unicondylar knee replacement and/or patellofemoral knee replacement.

The Implant systems with which the system is compatible:

• Restoris Multicompartmental Knee System

The MAKO System with the Partial Knee Application is a stereotactic instrument that includes a robotic arm, an integrated cutting system, an optical detector, a computer, dedicated instrumentation, operating software, a planning laptop, and tools and accessories.

The system's architecture is designed to support total and partial knee procedures and total hip procedures. With application specific hardware and software, the svstem provides stereotactic/haptic guidance during orthopedic surgical procedures by using patient CT data to assist a surgeon with pre-surgical planning, implant placement and interpretive/intraoperative navigation of the patient's anatomy.

The MAKO robotic arm, once configured for a specific application, can serve as surgeon's "intelligent" tool holder or tool guide by passively constraining the preparation of an anatomical site for an orthopedic implant with software-defined spatial boundaries.

The provided text is a 510(k) summary for the MAKO Partial Knee Application. It describes the device, its intended use, and a comparison to a predicate device. However, it does not contain the acceptance criteria and detailed study information requested in your prompt (such as specific performance metrics, sample sizes for test/training sets, expert qualifications, or details about standalone or MRMC studies).

The "Performance Data" section briefly lists three types of non-clinical performance testing:

1. Cutting Accuracy Verification
2. Cadaver Validation of Mako System with New Burr
3. Biocompatibility Evaluation

It concludes that these tests "demonstrate that the characteristics of the MAKO Partial Knee Application are equivalent to the predicate device, and that the device is as safe and as effective as the predicate and does not raise new questions of safety and effectiveness, and therefore supports a determination of Substantial Equivalence."

Therefore, based only on the provided text, I cannot complete the table or answer the specific questions about acceptance criteria, sample sizes, ground truth establishment, or expert involvement. The document focuses on regulatory equivalence rather than a detailed breakdown of performance study results.

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The Partial Knee Application (PKA), for use with the Mako System, is intended to assist the surgeon in providing software defined spatial boundaries for orientation and reference information to anatomical structures during orthopedic procedures.

The Partial Knee Application (PKA), for use with the Mako System, is indicated for use in surgical knee procedures in which the use of stereotactic surgery may be appropriate, and where reference to rigid anatomical bony structures can be identified relative to a CT based model of the anatomy. These procedures include unicondylar knee replacement and/or patellofemoral knee replacement.

The Implant systems with which the system is compatible:

• Restoris Multicompartmental Knee System

The Mako System with the Partial Knee Application is a stereotactic instrument that includes a robotic arm, an integrated cutting system, an optical detector, a computer, dedicated instrumentation, operating software, a planning laptop, and tools and accessories.

The system's architecture is designed to support total and partial knee procedures and total hip procedures. With application specific hardware and software, the system provides stereotactic/haptic guidance during orthopedic surgical procedures by using patient CT data to assist a surgeon with pre-surgical planning, implant placement and interpretive/intraoperative navigation of the patient's anatomy.

The Mako robotic arm, once configured for a specific application, can serve as surgeon's "intelligent" tool holder or tool guide by passively constraining the preparation of an anatomical site for an orthopedic implant with software-defined spatial boundaries.

This document is a 510(k) summary for the Mako Partial Knee Application, a medical device. It does not contain information about acceptance criteria or a study proving the device meets those criteria in the typical sense of an AI/ML device performance study with traditional metrics like sensitivity, specificity, or AUC.

The document focuses on demonstrating substantial equivalence to a previously cleared predicate device (Mako Surgical's Partial Knee Application cleared via K142530), based on technological characteristics and functional performance testing.

Therefore, I cannot extract the requested information regarding acceptance criteria, study design, ground truth establishment, or human reader performance for an AI/ML system from this document. The "Performance Data" section describes non-clinical performance testing for a robotic surgical assistance system, not an AI/ML diagnostic or prognostic tool.

Here's a breakdown of why the requested information cannot be provided based on the input document:

1. Acceptance Criteria and Reported Device Performance (Table): Not present. The document discusses "performance testing" but not in the context of quantitative metrics for an AI/ML model. It lists activities like "Sub-system level software functional testing" and "Resection accuracy verification," but no specific numerical acceptance criteria or results are given.
2. Sample Size and Data Provenance (Test Set): Not applicable in the context of AI/ML validation data. The performance testing mentions "Full system cadaver validation," which implies a small, non-human sample for mechanical/software function verification, not a large patient-data test set.
3. Number/Qualifications of Experts for Ground Truth: Not applicable. Ground truth, in the AI/ML sense, refers to labeling of patient data, which is not described.
4. Adjudication Method: Not applicable.
5. MRMC Comparative Effectiveness Study: Not mentioned or implied. This device is a surgical assistance system, not an imaging interpretation AI for human reader improvement studies.
6. Standalone (Algorithm-only) Performance: Not applicable as it's a robotic system with human interaction.
7. Type of Ground Truth: Not applicable in the AI/ML data labeling sense. The "ground truth" for this device's performance would be the physical accuracy of the robotic arm's movements and resections compared to a planned trajectory.
8. Sample Size for Training Set: Not applicable. This is not an AI/ML device that learns from a training set of data in the typical sense. Its software is programmed to assist with surgical procedures.
9. How Ground Truth for Training Set was Established: Not applicable.

In summary, the provided document describes a robotic surgical assistance system that aims to demonstrate substantial equivalence through a series of non-clinical performance and functional tests, rather than an AI/ML system that undergoes a clinical validation study with specific performance metrics and patient data.

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The Partial Knee Application (PKA), for use with the Mako System, is intended to assist the surgeon in providing software defined spatial boundaries for orientation to anatomical structures during orthopedic procedures.

The Partial Knee Application (PKA), for use with the Mako System, is indicated for use in surgical knee procedures in which the use of stereotactic surgery may be appropriate, and where reference to rigid anatomical bony structures can be identified relative to a CT based model of the anatomy. These procedures include unicondylar knee replacement and/or patellofemoral knee replacement.

The Mako System with the Partial Knee Application is a stereotactic instrument that includes a robotic arm, an integrated cutting system, an optical detector, a computer, dedicated instrumentation, operating software, a planning laptop, and tools and accessories.

The system's architecture is designed to support total and partial knee procedures and total hip procedures. With application specific hardware and software, the system provides stereotactic guidance during orthopedic surgical procedures by using patient CT data to assist a surgeon with pre-surgical planning, implant placement and interpretive/intraoperative navigation of the patient's anatomy.

The Mako robotic arm, once configured for a specific application, can serve as surgeon's "intelligent" tool holder or tool guide by passively constraining the preparation of an anatomical site for an orthopedic implant with software-defined spatial boundaries.

Based on the provided text, the Mako Partial Knee Application is a Class II medical device, product code OLO, regulated under 21 CFR 882.4560 (Stereotaxic Instrument). This device is intended to assist surgeons by providing software-defined spatial boundaries for orientation and reference to anatomical structures during orthopedic procedures, specifically unicondylar knee replacement and/or patellofemoral knee replacement. The 510(k) submission (K170584) claims substantial equivalence to the predicate device, Mako Partial Knee Application cleared via K112507.

The primary change described is the implementation of an alternate online portal for case management and file transfer, known as eRequest LifeCycle, for use during the preoperative planning phase. The performance data focuses on verifying and validating this new component's functionality and integration into the existing Mako System.

Here's an analysis of the provided information concerning acceptance criteria and the study that proves the device meets them:

1. Table of Acceptance Criteria and Reported Device Performance

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

The document does not explicitly state the sample size (e.g., number of cases or simulations) used for each test. The studies appear to be focused on the new eRequest LifeCycle portal and its integration. The data provenance is also not specified; it is implied to be internal testing by the manufacturer rather than retrospective or prospective clinical data from external sources.

3. Number of Experts and their Qualifications for Ground Truth

The document mentions "appropriate user" for the eRequest LifeCycle PKA Validation but does not specify the number or qualifications of experts (e.g., radiologists, orthopedic surgeons) used to establish ground truth or validate the functionality. This type of testing appears to be functional validation rather than diagnostic performance assessment requiring expert review.

4. Adjudication Method for the Test Set

No details regarding an adjudication method (e.g., 2+1, 3+1) are present. Given the nature of the tests ("Pass" outcomes for functional verification/validation), human adjudication of complex diagnostic interpretations is not indicated.

5. Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study

No MRMC comparative effectiveness study was mentioned. The submission focuses on the substantial equivalence of an updated component (eRequest LifeCycle portal) rather than demonstrating an improvement in human reader performance with or without AI assistance. This device is an orthopedic surgical robotic system, not an AI-powered diagnostic imaging tool that would typically involve MRMC studies for reader performance.

6. Standalone (Algorithm Only Without Human-in-the-Loop Performance) Study

While the device itself is a "stereotaxic instrument" with a "robotic arm" and "operating software," the performance data presented pertains specifically to the eRequest LifeCycle portal. The tests described are functional verification and validation of this portal's integration and workflow capability. There is no mention of a standalone algorithm performance study in the context of diagnostic accuracy, which would be typical for AI-based image analysis algorithms. The "standalone" performance here relates to the technical functioning of the software component.

7. Type of Ground Truth Used

The "ground truth" for these tests appears to be defined by the "THA Product Specifications" (for Product Specification Verification) and the "pre-operative planning workflow" and "customer requirements" (for eRequest - Full System Run Through and eRequest LifeCycle PKA Validation). This means the ground truth is established by design specifications and user requirements, not clinical outcomes, pathology, or expert consensus on patient data.

8. Sample Size for the Training Set

This information is not applicable and not provided. The described changes are related to a software portal for case management and file transfer, not an AI/ML algorithm that requires a "training set" in the conventional sense of machine learning for image analysis or prediction tasks. The "training" here relates to software development and testing, where test cases would be used, but not in the context of a machine learning training set for learning from data.

9. How the Ground Truth for the Training Set Was Established

As above, this information is not applicable. The "ground truth" for the functional tests was internal product specifications and defined workflow requirements, not clinical data requiring expert annotation or similar for machine learning purposes.

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