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The XACT ACE Robotic System is a user-controlled positioning system intended to assist in the planning and advancement of an instrument during Computed Tomography (CT) guided percutaneous procedures. The system is used for trajectory planning and is intended to assist the physician in positioning of an instrument, such as a needle, where CT imaging is used for target trajectory planning and intraoperative tracking.

The XACT ACE Robotic System is a user-controlled positioning system intended to assist in the planning and advancement of instruments during Computed Tomography (CT) quided percutaneous procedures. The system is used for trajectory planning based on CT images and is intended to assist the physician in positioning of an instrument, such as a needle, and reviewing instrument position during advancement to the target. The system guides (i.e., positions and steers) the instrument according to a predefined trajectory. The physician controls advancement of the instrument along the trajectory using a foot pedal or a pushbutton on the control room console. The system also allows for monitoring of motion associated with respiration during the procedure.

The XACT ACE Robotic System comprises the following main components:

• . XACT ACE Robot which is placed on the patient and includes the robot positioning unit & the insertion module assembly
• . XACT ACE Console which includes a Control Unit, central computer (in the Control Unit) and monitor workstation for user trajectory planning, user interface and review of instrument position

Below is the information extracted from the provided text regarding the acceptance criteria and the study proving the device meets them. It's important to note that the provided text primarily focuses on demonstrating substantial equivalence to a predicate device rather than explicitly detailing specific acceptance criteria for a novel device. The performance data section describes tests conducted, and the clinical data section reports outcomes, which implicitly relate to the device's acceptable performance.

1. A table of acceptance criteria and the reported device performance

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

• Abdominal Study:

  • Sample Size: 60 completers (33 men, 27 women)
  • Provenance: Prospective clinical trial (NCT03008603) conducted at 2 centers. Country of origin not specified, but the submitter is from Israel.

• Lung Study:

  • Sample Size: 20 patients (10 men, 10 women)
  • Provenance: Prospective clinical trial (NCT04651517) conducted at 2 clinics in the US.

3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts (e.g. radiologist with 10 years of experience)

The document does not explicitly state the number of experts or their qualifications used to establish ground truth for the clinical study "test sets." Clinical studies for robotic systems typically involve physicians (e.g., interventional radiologists) performing the procedures, and their assessment of successful targeting and outcomes implicitly serves as the ground truth.

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

The document does not specify any adjudication method (like 2+1 or 3+1) used for the clinical study outcomes or ground truth determination.

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

A multi-reader multi-case (MRMC) comparative effectiveness study with human readers (or expert operators) with and without AI assistance was not reported or implied in the provided text. The XACT ACE Robotic System is itself a robotic assistance system, and the studies evaluated its performance as a whole, rather than comparing human interpretation/performance with and without it.

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

The XACT ACE Robotic System is described as a "user-controlled positioning system intended to assist in the planning and advancement of an instrument." This inherently implies a human-in-the-loop system. Therefore, a standalone (algorithm only) performance evaluation was not done as it would not represent the intended use of the device. The "Steering Accuracy test" was evaluated in a "simulated clinical setup," which would likely involve the robotic system performing an action (steering) but still within the context of a controlled, human-planned trajectory.

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

For the clinical studies (abdominal and lung), the ground truth appears to be based on clinical outcomes data and physician assessment of the procedure's success.

• "All procedures completed with the ACE system reached the target in one needle insertion." (Abdominal study)
• "Clinical data in lung procedures confirm the performance and safety of the device, supporting the same performance profile..." (Lung study)
• "minimal adverse events."

This implies that successful targeting (reaching the intended lesion/target) and safety (absence of significant adverse events) were the primary measures of ground truth, assessed by the clinicians performing or overseeing the procedures. Pathology confirmation of biopsy results would also be an implicit ground truth where applicable, but not explicitly stated as the primary ground truth for system accuracy.

8. The sample size for the training set

The document does not provide information regarding a separate "training set" or its sample size. This type of information is typically relevant for AI/machine learning models where a distinct training phase is required. The XACT ACE Robotic System is described as a robotic positioning system with software updates, but not explicitly as a machine learning system that would require a distinct "training set" in the conventional sense for its core functionality. The performance data refers to validation and verification tests, and clinical trials for effectiveness and safety.

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

Since no "training set" is mentioned or implied for a machine learning context, the document does not describe how ground truth for a training set was established.

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