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The TOTAL KNEE SURGETICS NAVIGATION SYSTEM WITH IBLOCK is intended for use during stereotaxic surgery to aid the surgeon in locating anatomical structures and aligning the endoprostheses with the anatomical structures. It is specifically indicated for: Total Knee Arthroplasty

As the equivalent TOTAL KNEE SURGETICS NAVIGATION SYSTEM WITH PRAXITELES, the TOTAL KNEE SURGETICS NAVIGATION SYSTEM WITH IBLOCK consists of the following major components and subsystems: - The Station (Surgetics or NanoStation), consisting of a mobile computer system and an optical localizer - . Ancillary instruments, a specific motorized cutting block and reflective markers used for reference and registration - TOTAL KNEE SURGETICS software application with iBlock option . The main modification to the predicate device K081232 concerns the modification of the motorized cutting block PRAXITELES®.

The provided text describes a 510(k) summary for the TOTAL KNEE SURGETICS Navigation System with iBlock. Based on the available information, here is an analysis of the 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 states, "The TOTAL KNEE SURGETICS Navigation System with iBlock was tested in a non clinical setting (bench testing, specimen)". While it specifies "specimen," it does not provide a specific sample size for the test set or specify the data provenance (e.g., country of origin, retrospective or prospective).

3. Number of Experts Used to Establish the Ground Truth for the Test Set and Their Qualifications

The document does not specify the number of experts used to establish the ground truth for the test set or their qualifications. The testing appears to be non-clinical (bench testing, specimen), which typically relies on established physical standards or measurements rather than expert consensus on images.

4. Adjudication Method for the Test Set

The document does not mention an adjudication method (such as 2+1 or 3+1). Given it's non-clinical testing on specimens, human adjudication in the typical sense for image interpretation would not be applicable.

5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study was Done, What was the Effect Size of How Much Human Readers Improve with AI vs without AI Assistance

A Multi-Reader Multi-Case (MRMC) comparative effectiveness study was not conducted for this device. The study described is a non-clinical performance evaluation, not a study involving human readers or AI assistance. The device is a surgical navigation system, not an AI-based diagnostic tool.

6. If a Standalone (i.e., algorithm only without human-in-the-loop performance) was Done

The performance testing was a standalone evaluation of the device in a non-clinical setting. The statement "tested in a non clinical setting (bench testing, specimen)" implies testing the system's inherent performance characteristics (accuracy, efficiency) without direct human-in-the-loop clinical scenarios.

7. The Type of Ground Truth Used

The ground truth for the non-clinical testing (bench testing, specimen) would likely be established through physical measurements and engineering specifications to determine the accuracy of the system's guidance and its motorized cutting block. This is not explicitly stated as "expert consensus, pathology, or outcomes data," but rather implied by the nature of non-clinical, benchtop testing for a navigation system.

8. The Sample Size for the Training Set

The document does not provide information about a training set size. This device is a navigation system, and the testing described is for its performance, not for an AI model that requires a training set in the conventional sense. The "TOTAL KNEE SURGETICS software application with iBlock option" likely refers to the operational software, not a machine learning algorithm that needs a training set.

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

Since there is no mention of a training set in the context of an AI/machine learning model, there is no information about how its ground truth would have been established.

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The CTLOGICS Navigation System is an optically based surgical navigation system. It is intended for use during stereotaxic surgery to aid the surgeon in locating anatomical structures.

The system which uses patient's preoperative image data is indicated for any medical condition in which the use of stereotaxic surgery may be appropriate and where a reference to a rigid anatomical structure, such as the skull, the pelvis, a long bone, or a vertebra can be identified relative to CT-based model of the anatomical structure.

Example procedures include but are not limited to:

Posterior spinal implant procedures such as pedicle screw placement, kyphoplasty and vertebroplasty procedures, thoracic spine surgery, tumor surgery on the spinal column.

Superolateral and deltopectoral shoulder procedures, such as guiding the glenoid component on the scapula.

The CTLOGICS Navigation System consists of the following major components and subsystems:

• The Surgetics Station or the NanoStation, consisting of a mobile computer . system and an optical localizer
• Ancillary instruments and reflective markers used for reference and . registration
• . CTLOGICS Software

The provided document is a 510(k) summary for the CTLOGICS Navigation System. It describes the device, its intended use, and claims substantial equivalence to predicate devices. However, it does not contain detailed information about specific acceptance criteria or an analytical study proving the device meets those criteria, as typically found in clinical validation reports or detailed performance studies. The document primarily focuses on establishing substantial equivalence based on technological characteristics and a general statement about performance.

Here's an analysis based on the available information:

Description of Device and Performance Claims

The CTLOGICS Navigation System is an optically based surgical navigation system intended for use during stereotaxic surgery to aid surgeons in locating anatomical structures. It uses pre-operative image data (CT-based models) and reference to rigid anatomical structures (skull, pelvis, long bone, vertebra).

Performance Statement: "Analyses show that the accuracy and performance of the system was adequate for its intended use and not reduced in comparison to the predicate devices."

Missing Information Regarding Specific Acceptance Criteria and Detailed Study

The document states that "The CTLOGICS Navigation System was tested to assess that no safety and efficiency issues were raised in the device," and that "the accuracy and performance of the system was adequate for its intended use." However, it does not provide a table of acceptance criteria with specific quantitative targets (e.g., accuracy +/- X mm, precision Y mm). Without these defined criteria, it's impossible to report "device performance" against them in a structured table.

Similarly, the document refers to "analyses" and "testing" but does not describe a specific study (e.g., a formal clinical trial, a cadaver study, or a detailed benchtop accuracy study) with a defined methodology, sample size, or ground truth establishment. The performance claims are high-level and refer to an overall assessment for intended use and comparison to predicate devices, rather than a detailed report of a particular study's findings against pre-defined metrics.

Therefore, the requested table and specific details of the study cannot be fully compiled from this document.

Table of Acceptance Criteria and Reported Device Performance

Detailed Study Information (Based on available document)

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

   • Not specified. The document makes a general statement about "analyses" and "testing" but does not provide details on the sample size or the nature of the data used for testing (e.g., number of cases, type of experiments). Data provenance (country, retrospective/prospective) is also not mentioned.

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

   • Not specified. The document does not describe how ground truth was established for any performance testing.

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

   • Not specified. No information is provided about an adjudication method for a test set.

4. 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 specified/Not Applicable. This device is a surgical navigation system, not an AI-assisted diagnostic tool that typically involves "human readers." Therefore, an MRMC study in the traditional sense, comparing human reader performance with and without AI assistance, would not be relevant or described here. The "human" in the loop is the surgeon, and the device assists the surgeon, but the document doesn't detail a study measuring improvement in surgeon performance using quantifiable effect sizes.

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

   • Not explicitly stated in detail. While the system performs navigation functions independently of direct human manipulation during the process, the performance mentioned ("accuracy and performance of the system") likely refers to the overall system's capability. However, the document doesn't isolate and report specific "algorithm-only" performance metrics separate from its intended use in guiding a surgeon.

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

   • Not specified. The document does not provide details on how ground truth was established for any performance evaluation.

7. The sample size for the training set:

   • Not applicable/Not specified. This document does not describe the device as being based on machine learning or AI that would require a distinct "training set." It's a deterministic navigation system that uses pre-acquired patient images, but not in a machine learning training context.

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

   • Not applicable/Not specified. As there's no mention of a training set for machine learning, this question is not relevant to the information provided.

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