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The NAVIO 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 NAVIO 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 determined. These procedures include unicondylar knee replacement (UKR), patellofemoral arthroplasty (PFA), and total knee arthroplasty (TKA).

The NAVIO system is indicated for use with cemented implants only.

The NAVIO system is a computer-assisted orthopedic surgical navigation and surgical burring system. The system uses established technologies of navigation, via a passive infrared tracking camera, to aid the surgeon in establishing a bone surface model for the target surgery and in planning the surgical implant location, based on intraoperativelydefined bone landmarks and known geometry of the surgical implant. The NAVIO system then aids the surgeon in executing the surgical plan by using a standard off-theshelf surgical drill motor and bur (Anspach eMax2 Plus System, cleared via K080802), which has been adapted using a tracking system.

The surgical bur is inserted into a handpiece, which allows the bur to move within the handpiece. The NAVIO system software controls the cutting engagement of the surgical bur based on its proximity to the planned target surface. The cutting control is achieved in two ways:

• Exposure control adjusts the bur's exposure with respect to a guard. If the surgeon encroaches on a portion of bone that is not to be cut, the NAVIO system retracts the bur inside the guard, disabling cutting.
• . Speed control regulates the signal going to the drill motor controller itself and will limit the speed of the drill if the target surface is approached. This mode of operation is useful in shaping surfaces of the condyle as well as placing post holes and fixation features for femoral and tibial cut guides.

Additionally, the surgeon can disable both controls and operate the NAVIO system handpiece as a standard navigated surgical drill. The surgeon must press on a footpedal to activate the surgical bur and enable cutting in all modes.

Here's a breakdown of the acceptance criteria and the study information for the NAVIO™ Surgical System (NAVIO system) based on the provided text:

1. Table of Acceptance Criteria and Reported Device Performance

The document does not explicitly list quantitative acceptance criteria in a table format. Instead, it states that the device was verified against the "same accuracy specifications required for the predicate device." The reported performance is a qualitative statement of meeting these specifications.

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

• Sample Size: Not explicitly stated. The text mentions "simulated knees (sawbones)". The number of sawbones used is not provided.
• Data Provenance: The test data comes from bench testing using "simulated knees (sawbones)." This implies a controlled, non-clinical environment, not human data. The country of origin is not specified but is presumably where Blue Belt Technologies (or its successor, Smith & Nephew) conducts R&D/testing.

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

• Number of Experts: Not explicitly stated.
• Qualifications of Experts: The testing was "performed by trained technical support personnel." Specific qualifications (e.g., years of experience, medical background) are not detailed beyond "trained technical support personnel."

4. Adjudication Method for the Test Set

Not applicable. The testing was described as "verification accuracy testing" using simulated knees performed by technical support personnel, not a process involving adjudication of expert opinions on a test set.

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

• MRMC Study: No, an MRMC comparative effectiveness study was not conducted. This device is a surgical navigation and burring system (a robotic surgical assistant), not a diagnostic AI system typically evaluated with MRMC studies.

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

The study was primarily focused on verifying the accuracy and performance of the device's components (tracking camera, OS) in assisting the surgeon with predefined spatial boundaries and controlled burring. While the accuracy testing itself might assess the core algorithm's precision, the overall device is designed to be human-in-the-loop. The text indicates the surgeon uses the system: "The NAVIO system is intended to assist the surgeon..." and "...aids the surgeon in executing the surgical plan..." Therefore, a purely standalone clinical assessment would not be relevant for this type of device. The accuracy testing performed on sawbones could be considered a form of standalone performance assessment in a controlled environment as it evaluates the system's ability to accurately control the bur, but it's not a clinical standalone performance study.

7. The Type of Ground Truth Used

The ground truth for the "verification accuracy testing" was based on the "planned target surface" and "predefined boundaries generated during the planning process." In a bench setting with sawbones, the "ground truth" would be the precise, known dimensions and locations of the planned cuts or shapes defined by the system's software and verified against physical measurements or ideal models. It's not pathology, expert consensus on images, or outcomes data, but rather engineering-defined specifications for cutting accuracy.

8. The Sample Size for the Training Set

Not applicable. This submission concerns updates to an existing device (a new tracking camera and OS upgrade), and the study described is a verification and validation study for these changes, not the initial development or training of a machine learning model. The device itself is a computer-assisted surgical system, not explicitly described as employing a machine learning algorithm that requires a training set in the way a diagnostic AI would.

This document focuses on demonstrating that hardware/software updates did not negatively impact the already cleared device's performance, rather than on the initial establishment of performance for a novel AI algorithm.

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

Not applicable, as there was no mention of a training set for a machine learning model.

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