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The 7D Surgical System is a stereotaxic image guidance system intended for the spatial positioning and orientation of neurosurgical instruments used by surgeons. The system is also intended to be used as the primary surgical luminaire during image guided surgery. The device is indicated for posterior approach spine surgery where reference to a rigid anatomical structure can be identified.

The 7D Surgical System is intended for use as a stereotaxic image guided surgical navigation system during spine surgery. The system provides image registration between preoperative scan data and data captured intraoperatively from the 7D Surgical System structured light scanner and/or user selected points. The system provides guidance data by tracking and displaying the position and orientation of wireless optically tracked Spinal Instruments including the 7D Surgical Pedicle Probe and Awl, now including the Universal Tracking Clamp, relative to the patient. Position and orientation data of tracked Spinal Instruments are linked to the preoperative scan data using the 7D Surgical System workstation. The system is intended to be used as the primary surgical luminaire for image guided surgery. Similar to the previously cleared 7D Surgical System and Brainlab, the system tracks the position and orientation of a Universal Tracking Clamp.

The system is intended to be used for both image fusion and navigation for neurological applications where reference to a rigid structure can be identified relative to a preoperative image data of the anatomy.

The Tracking System enables the surgeon to view the position and orientation of 7D Surgical System Spinal Instruments relative to registered preoperative image data while performing the surgical procedure. Each of the 7D Surgical System instruments, including the Universal Tracking Clamp, utilizes commercially available passive reflective marker spheres to determine the position and orientation of instruments. Each tracked Instruments requires a unique marker position configuration to enable the tracking system to distinguish the tools from one to the other.

The Software links all system components and displays navigational data to the surgeon. lt provides methods for loading preoperative scans and guides the surgeon through the process of surface model creation, structured light acquisition, registration, registration verification, and navigation.

The 7D Surgical Universal Tracking Clamp consists of two different size tracking arrays which hold the reflective marker spheres both with a unique marker arrangement to distinguish one from the other. The tracker arrays attach to two different clamps of different sizes which attach to 30 party spinal surgical instruments. The Universal Tracking Clamp when attached to 30 party spinal instruments requires calibration in order to accurately display the position and orientation of the tool in the 7D Surgical System software.

Here's a breakdown of the acceptance criteria and the study that proves the device meets them, based on the provided FDA 510(k) summary:

1. Table of Acceptance Criteria and Reported Device Performance

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

The provided document describes non-clinical performance testing conducted on phantom models. It does not specify a numerical sample size (e.g., number of cases or runs) for the accuracy testing.

• Data Provenance: The testing was conducted internally by 7D Surgical, Inc. on phantom models, simulating clinical use. There is no mention of country of origin for data as it's a simulated environment, nor whether it's retrospective or prospective, as it's not a human clinical study.

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

This information is not provided in the document. The ground truth for the non-clinical accuracy testing was established by physical measurements or "otherwise" in a simulated environment, not through expert consensus in a clinical setting.

4. Adjudication Method for the Test Set

This information is not applicable as the ground truth was established through physical measurements on phantom models, not through expert review requiring adjudication.

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

No, an MRMC comparative effectiveness study was not performed and is not mentioned. The document explicitly states: "A clinical trial was not required to demonstrate safety and effectiveness of the 7D Surgical System."

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

The described non-clinical accuracy testing is a form of standalone performance evaluation for the device's ability to track and display positions accurately on phantom models. While it involves a human operator using the system, the focus of the accuracy tests (Target Registration Error, Angular Trajectory Error, and ASTM F2554-10 compliance) is on the system's intrinsic measurement and navigation capabilities, separate from overall human surgical outcomes. Therefore, it implicitly evaluates the algorithm's performance in determining position and orientation.

7. Type of Ground Truth Used

For the non-clinical accuracy testing:

• Physical Measurement: The document states that Target Registration Error (TRE) and Angular Trajectory Error (ATE) evaluate the error discrepancy between the position reported by the image-guided surgery system and the "ground truth position measured physically or otherwise." This indicates that a physically measured gold standard was used on the phantom models.
• ASTM F2554-10 Standard: Compliance with this standard also implies a defined method for establishing ground truth for positional accuracy.

8. Sample Size for the Training Set

The document does not specify a training set sample size or details about a training set. As this is a device for image-guided surgery (navigation), rather than an AI-driven diagnostic or predictive algorithm learning from large datasets, the concept of a "training set" in the context of machine learning is not directly applicable here. The system uses algorithms for structured light scanning, image registration, and tracking, but these are typically developed and validated through engineering principles and specific test cases rather than large-scale data training.

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

Since a "training set" in the context of machine learning is not explicitly mentioned or applicable to the type of device described, this information is not provided. The device's underlying algorithms and functionalities would have been developed and tested against engineering specifications and internal validation criteria.

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The CAS-One Liver system is indicated for open liver surgical procedures where image guidance may be appropriate and where the patient can tolerate long apneic periods under general anesthesia.

The CAS-One Liver system is indicated for open liver surgical procedures where image aujdance may be appropriate and where the patient can tolerate long apneic periods under general anesthesia. It visualizes the position and pose of surgical instruments relative to a three-dimensional model of the patients liver in real-time.

The provided text describes the CAS-One Liver system, its indications for use, and a summary of performance data submitted for its 510(k) premarket notification. However, it does not contain specific acceptance criteria for device performance or a detailed study proving the device meets those criteria.

The document states:

• "Bench testing to show the accuracy and reproducibility was conducted and shown to meet the defined acceptance criteria for various functionality of the system (such as calibration, tracking and registration)."

This indicates that acceptance criteria were defined and testing was performed, but the document does not report what those criteria were, nor does it provide the results of the tests against those criteria.

Therefore, I cannot provide the requested information about acceptance criteria, reported device performance, sample sizes, ground truth, or details of a comparative effectiveness study.

Here's what can be extracted, based on the absence of the requested information:

1. Table of acceptance criteria and reported device performance:

   • The document states "Bench testing to show the accuracy and reproducibility was conducted and shown to meet the defined acceptance criteria for various functionality of the system (such as calibration, tracking and registration)."
   • CRITERIA NOT SPECIFIED.
   • REPORTED PERFORMANCE NOT SPECIFIED.

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

   • NOT SPECIFIED. The document only mentions "Bench testing."

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

   • NOT SPECIFIED, as details of the "Bench testing" are not provided.

4. Adjudication method for the test set:

   • NOT SPECIFIED.

5. If a multi-reader multi-case (MRMC) comparative effectiveness study was done, and the effect size:

   • NO, an MRMC comparative effectiveness study is not mentioned. The device is a navigation system for surgical procedures, and the testing described is "Bench testing" for accuracy and reproducibility, not a study of human reader improvement with AI assistance.

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

   • The "Bench testing" for "accuracy and reproducibility" of "calibration, tracking and registration" could be considered standalone performance, as it tests the system's technical function. However, the exact details of how "human-in-the-loop" was excluded or included are NOT SPECIFIED.

7. The type of ground truth used:

   • For "Bench testing" of a navigation system, ground truth would typically be established through precise measurements from calibrated instruments, phantoms, or simulated environments. However, the specific type of ground truth used for the CAS-One Liver system's bench testing is NOT SPECIFIED.

8. The sample size for the training set:

   • The document implies a "virtual surgery planning tool" (MeVis Medical Solutions, Bremen, Germany) that processes CT/MRI scans. This tool likely uses algorithms that would have been "trained," but the details of any training set for the CAS-One Liver system's own components (if applicable for navigation algorithms) are NOT SPECIFIED. The document focuses on the end-use navigation system's performance.

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

   • NOT SPECIFIED.

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