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SIRIO H3 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.

SIRIO H3 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.

SIRIO H3 is a user controlled, stereotactic accessory intended to assist in planning, navigation and manual advancement of needles (or similar surgical instruments), as well as in verification of theirs position and performance during Computed Tomography (CT) guided procedures.

SIRIO H3 reconstructs a 3D model of the target anatomy from a data set of previously acquired CT images by means of a semiautomatic algorithm.

The system components are:

• the patient tool
• the needle tool
• direction tool
• guide for needle
• a visualization /elaboration unit
• an infrared optical sensor mounted either on the ceiling of the CT room or on the visualization /elaboration unit

All the tools in contact both with the skin of the patient and with the surgical instruments are sterile disposable.

Here's a breakdown of the acceptance criteria and the study that proves the device meets them, based on the provided text:

1. Acceptance Criteria and Reported Device Performance

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

• Sample Size for Clinical Evaluation (Test Set): 40 patients.
• Data Provenance: The clinical evaluation was conducted by the Department of Diagnostic Imaging of the University Campus of Bio-Medico of Rome. This indicates the data is prospective and from Italy (Rome).

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

The document states "interventional procedures performed by physicians trained for CT procedures." It doesn't explicitly state the number of experts used for establishing ground truth specifically for the test set or their detailed qualifications (e.g., years of experience). However, it implies that the physicians performing the procedures in the clinical evaluation served as the ultimate arbiters of successful "performance as intended."

4. Adjudication method for the test set

The document does not specify an adjudication method (e.g., 2+1, 3+1, none) for the test set. The clinical evaluation implicitly relies on the judgment of the performing physicians.

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 comparing human readers with and without AI assistance was not conducted or reported in this submission. The device is a "CT navigation system" (stereotactic accessory) and not a diagnostic AI interpretation tool.

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

Yes, a form of "standalone" performance testing was done in the form of phantom testing for mechanical accuracy. The "Accuracy test that evaluated needle insertion configurations of SIRIO H3 was conducted on a phantom simulation of clinical use and was shown to be accurate. Accuracy is defined as the difference between the position of the sensitized real needle and the tip of the figure-guided needle. The accuracy is ≤ 2mm / 100mm." This evaluates the algorithm's guidance and the system's mechanical precision independently of patient variability.

7. The type of ground truth used

• For Mechanical and Performance (Accuracy): The ground truth was based on the "sensitized real needle" position in a phantom simulation. This is a simulated/engineered ground truth.
• For Clinical Evaluation: The ground truth was implicit from the device "performing as intended" during actual CT-guided lung biopsy procedures in 40 patients. This relies on clinical outcomes and expert observation during the procedure.

8. The sample size for the training set

The document does not provide any information regarding a training set size or if machine learning was used in a way that required a distinct training set. The device assists in planning and navigation, and reconstructs 3D models using a "semiautomatic algorithm," but it doesn't specify if this algorithm utilized a large training dataset in the modern machine learning sense. The primary performance evaluation focuses on the system's accuracy and its ability to function as intended in real-world scenarios.

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

As no training set is mentioned, there is no information on how its ground truth might have been established. If the "semiautomatic algorithm" involves traditional image processing or rule-based logic, a formal "training set" with ground truth in the typical AI sense might not have been applicable or necessary.

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