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CAS-One IR is a user controlled, stereotactic accessory intended to assist in planning, navigation and manual advancement of one or more instruments, as well as in verification of instrument position and performance during Computed Tomography (CT) guided procedures.

In planning, the desired needle configuration and performance is defined relative to the target anatomy.

In navigation, the instrument position is displayed relative to the patient and guidance for needle alignment is provided while respiratory levels are monitored.

In verification, the achieved instrument configuration and performance are displayed relative to the previously defined plan through an overlay of the pre- and post- treatment image data.

CAS-One IR is indicated for use with rigid straight instruments such as needles and probes used in CT guided interventional procedures performed by physicians trained for CT procedures.

CAS-One IR is intended to be used for patients older than 18 years and eligible for CT-guided percutaneous interventions.

The system consists of the following main components:

• . A mobile navigation platform: this platform can be moved in and out of radiology rooms and is positioned next to the patient in front of the CT scanner. The platform includes two touch screens, a camera, and a computer.
• . Instruments: The instrument set comprises a guide arm, aiming device and a navigational pointer that are connected to each other and assist the user in aligning and positioning a needle trajectory relative to the patient. After positioning the aiming device using the guide arm, the aiming device is aligned with respect to the desired entry point (translational alignment) and rotationally oriented to the desired insertion angle.
• CAS-One IR software: The software provides the step-by-step workflow assistance for needle ● navigation. It provides a means for users to precisely plan a single or multiple needle trajectories, navigate a needle to this exact position and validate the inserted needle's position to the planned position.

Let's break down the information regarding the acceptance criteria and the study that proves the device meets them, based on the provided FDA 510(k) summary for CAS-One IR (K232022).

First, it's important to note that this 510(k) submission primarily focuses on demonstrating substantial equivalence to a predicate device (CAS-One IR, K152473). Therefore, the "study" described is a non-clinical performance testing and algorithm validation study, specifically addressing the differences and new features of the updated device. It is not an MRMC comparative effectiveness study or a typical standalone performance study with clinical endpoints.

Here's a breakdown of the requested information:

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

The document explicitly mentions acceptance criteria for the segmentation algorithms.

For instrument detection algorithms, the performance is generally described as "reliability was gauged by analyzing the ground truth positions and the positions identified by the algorithm," and "These validation efforts provide a robust foundation for asserting the accuracy and effectiveness of the algorithms." Specific quantitative performance metrics for instrument detection are not provided in this summary, but it states they were assessed against ground truth.

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

The document does not specify the sample size for the test set used for algorithm validation. It also doesn't provide information about the data provenance (e.g., country of origin, retrospective or prospective nature). It only mentions "ground truth data annotated by personnel considered expert in the domain."

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 states that the ground truth data was "annotated by personnel considered expert in the domain." It does not specify the number of experts or their specific qualifications (e.g., years of experience, specific medical specialty like radiologist).

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

The document does not specify any adjudication method for establishing the ground truth for the test set. It simply states "annotated by personnel considered expert in the domain."

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

No, a multi-reader multi-case (MRMC) comparative effectiveness study was not conducted. The document explicitly states: "Clinical testing was not required to demonstrate the safety and effectiveness of the device." The studies performed were non-clinical performance and algorithm validation.

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

Yes, a standalone algorithm validation was performed. The "Algorithm validation" section describes testing the segmentation algorithms (comparing mean DICE coefficient with state-of-the-art algorithms) and instrument detection algorithms (gauging reliability by comparing algorithm-identified positions with ground truth). These are evaluations of the algorithm's performance in isolation.

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

The ground truth used for algorithm validation was expert annotation/segmentation. The document states, "Test protocols were systematically executed to assess the performance of the algorithmic validation procedures involved comparisons with ground truth data annotated by personnel considered expert in the domain." This implies the ground truth for segmentation and instrument positions was established by human experts.

8. The sample size for the training set

The document does not provide the sample size for the training set. It focuses on the validation of the algorithms rather than their development or training data.

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

The document does not provide information on how the ground truth for the training set was established. Given the focus on substantial equivalence and non-clinical testing, this level of detail about training data is typically not required in a 510(k) summary if the primary claim relies on equivalence and validation of specific new features.

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CAS-One IR is a user controlled, stereotactic accessory intended to assist in planning, navigation and manual advancement of one or more instruments, as well as in verification of instrument position and performance during Computed Tomography (CT) guided procedures.

In planning, the desired needle configuration and performance is defined relative to the target anatomy.

In navigation, the instrument position is displayed telative to the patient and guidance for needle alignment is provided while respiratory levels are monitored.

In verification, the achieved instrument configuration and performance are displayed relative to the previously defined plan through an overlay of the pre- and post- treatment image data.

CAS-One IR is indicated for use with rigid straight instruments such as needles and probes used in CT guided interventional procedures performed by physicians trained for CT procedures.

The system consists of three main components:

• A mobile navigation platform can be moved in and out of radiology rooms and is positioned next to the patient in front of the CT scanner. The platform includes two touch screens, a camera and a computer.
• Aiming device with trackable aiming insert: To aim the needles to their correct locations, the system uses an aiming device. The aiming device is attached to a multi-axis mechanical arm that can align the position of the aiming device around the expected needle entry position. The aiming device is first aligned to the desired entry point (translational alignment) and then alignment to the desired needle insertion angle is performed using a remote center of rotation principle (rotational alignment). There are two possible configurations of the aiming device.
• Instrument adapter clamp with trackable marker shield: As an alternative to the aiming device, trackable markershields can be attached directly to rigid needles by means of an instrument adapter. Calibration of the needle geometry is performed with a calibration unit supplied by CAScination.
• CAS-One IR software: The software provides the step-by-step workflow assistance for needle navigation. It provides a means for users to precisely plan a single or multiple needle trajectories, navigate a needle to this exact position and validate the inserted needle's position to the planned position.

The provided document is a 510(k) summary for the CAS-One IR device, detailing its intended use, description, and substantial equivalence to predicate devices. It mentions various tests performed for performance data, but does not explicitly state specific acceptance criteria or provide the detailed results of a study that directly proves the device meets those criteria in a quantitative manner.

Therefore, I cannot populate a table of acceptance criteria and reported device performance directly from this document. However, I can infer the types of performance data collected and the general conclusions drawn, addressing the other points as much as possible.

Here's a breakdown of the available information:

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

As stated, specific numerical acceptance criteria and their corresponding reported performance values are not provided in this document. The document primarily focuses on demonstrating substantial equivalence to predicate devices through various tests and evaluations.

However, based on the "Performance Data" section, we can infer the aspects of performance that were evaluated and the high-level conclusions:

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

• Sample size for test set: The document does not specify the sample size for any of the performance tests (e.g., number of cases in the phantom study, number of patients in the post-clinical evaluation, number of users in usability studies).
• Data provenance: Not specified (e.g., country of origin, retrospective or prospective nature of clinical evaluation). The document mentions a "post-clinical evaluation of interventions conducted with CAS-One IR," which implies real-world clinical data, likely retrospective if not a formal prospective clinical trial structured for regulatory submission.

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

• This information is not provided in the document. The document mentions "physicians trained for CT procedures" as the intended users, and "qualified users of varying degrees of experience" for usability studies, but no details on who established ground truth for performance evaluations.

4. Adjudication method for the test set

• This information is not provided in the document.

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 MRMC comparative effectiveness study is not mentioned in the document. The device is described as a "user controlled, stereotactic accessory intended to assist in planning, navigation and manual advancement," which implies human-in-the-loop operation rather than a standalone AI diagnostic tool. The performance description focuses on the accuracy and usability of the system as a whole, not specifically on the impact of an AI component on human reader performance improvement.

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

• A standalone (algorithm-only) performance evaluation is not explicitly mentioned for the CAS-One IR. The device is presented as an assistive system for user-controlled procedures. The "Software Verification and Validation" section confirms the software's moderate level of concern due to potential for minor injury, and that "Verification testing appropriate to the software classification was carried out." However, this relates to software quality assurance, not a standalone performance assessment of an AI algorithm in a diagnostic context.

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

• The document does not explicitly state the type of ground truth used for performance evaluations. For the "accuracy test that evaluated all needle insertion configurations... on a phantom," the ground truth would likely be the known physical positions on the phantom. For the "post-clinical evaluation," the ground truth for "accuracy" would likely relate to the achieved needle placement relative to the planned placement as observed during the procedure or from follow-up imaging, which could be considered a form of outcome data or expert assessment during the intervention.

8. The sample size for the training set

• This information is not provided in the document. The CAS-One IR is described as a "user controlled, stereotactic accessory" for navigation. It's not explicitly presented as an AI/ML device that requires a large training set in the typical sense (e.g., for image classification or segmentation). While it has software, its core function is guidance, not predictive analytics based on historical data. If there are any learning components, their training set details are not disclosed.

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

• As the sample size and nature of a training set (in the context of AI/ML) are not provided, information on how its ground truth was established is also not available in this document.

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