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The Clear Guide SCENERGY is software that provides fusion of images from Computed Tomography (CT), Magnetic Resonance (MR), and Ultrasound (US) modalities. US images can be fused with either CT or MR.

The Clear Guide SCENERGY utilizes the Clear Guide CORE and Clear Guide SuperPROBE platform to display images of the target regions and the projected path of the interventional instrument, while taking into account patient movement and deformation. Instrumentation used with the Clear Guide SCENERGY might include an interventional needle or needle-like rigid device, such as a biopsy needle, an aspiration needle, or an ablation needle. The device is intended to be used in any interventional or diagnostic procedure where the combination of these modalities is used for visualization, except for procedures on the brain. The device is intended for use in a clinical setting.

The Clear Guide SCENERGY guidance system is intended to be an accessory to existing ultrasound imaging systems, to provide image fusion, instrument tracking, and image/instrument guidance functionality to operators during image-guided medical interventions that utilize data from multiple modalities (e.g., ultrasound and computed-tomography (CT), ultrasound and magnetic resonance (MR)). The Clear Guide SCENERGY uses optical detection technology to identify and track objects in the field of view. By pairing this information with the aforementioned imaging data, the Clear Guide SCENERGY executes proprietary software algorithms to display fused images in real-time to the clinician. These segmentation and registration algorithms are automated. Segmentation results are deterministic, meaning that new inputs (e.g., new CT or MR) would be required to change the segmentation output. Registration can be reset by the user at any time during use.

Acceptance Criteria and Study for Clear Guide SCENERGY

This document describes the acceptance criteria and the study that demonstrates the Clear Guide SCENERGY device meets these criteria. The information is extracted from the provided text.

1. Table of Acceptance Criteria and Reported Device Performance

The provided text describes performance testing without explicitly stating numerical acceptance criteria with pass/fail thresholds. However, it indicates that the device's performance was evaluated against the intended function and compared to the predicate device. The performance categories are inferred from the "Performance Data" and "Software Verification and Validation Testing" sections.

Study Details:

The provided text details various performance tests conducted to demonstrate the substantial equivalence of the Clear Guide SCENERGY to its predicate device. This appears to be a standalone performance study focused on the device's functional capabilities.

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

• Sample Size for Test Set:
  • Segmentation Testing: "phantom datasets" (specific number not provided).
  • Fusion Testing: No specific number of datasets mentioned, but "identifiable landmarks or surfaces" were used.
  • Systematic Error (Tip-to-Tip) Testing: "Phantom datasets were utilized" (specific number not provided).
• Data Provenance: The study primarily used phantom datasets. There is no mention of human subject data, country of origin, or whether the data was retrospective or prospective.

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

• Segmentation Testing: "manual selection in phantom datasets" was used as ground truth. The number and qualifications of experts performing this manual selection are not provided.
• Fusion Testing: "identifiable landmarks or surfaces seen on ultrasound and CT, or ultrasound and MR" were used for TRE assessment. It is not specified how these identifiable landmarks were established or if expert input was involved in defining them.
• Systematic Error (Tip-to-Tip) Testing: "ground truth CT (or MR)" was used to define the actual needle point. It is not specified how this ground truth was established or if experts were involved.

4. Adjudication Method for the Test Set

The document does not specify any formal adjudication method (e.g., 2+1, 3+1) for establishing ground truth or evaluating disagreements, as expert consensus is not explicitly detailed.

5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study was done

No, a Multi-Reader Multi-Case (MRMC) comparative effectiveness study was not explicitly mentioned or described. The study focused on technical performance rather than human reader improvement with or without AI assistance.

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

Yes, a standalone performance study was done. The described "Performance Data" and "Software Verification and Validation Testing," including "Segmentation Testing," "Fusion Testing," and "Systematic Error (Tip-to-Tip) Testing," all evaluate the algorithm's performance directly against established ground truth (e.g., manual selection, identifiable landmarks, ground truth CT/MR needle point) without human interaction being part of the primary measurement of the device's accuracy.

7. The Type of Ground Truth Used

• Segmentation Testing: Ground truth was established by manual selection in phantom datasets.
• Fusion Testing: Ground truth for TRE assessment relied on identifiable landmarks or surfaces within fused images.
• Systematic Error (Tip-to-Tip) Testing: Ground truth was based on the needle point seen by ground truth CT (or MR) in phantom datasets.

In all cases, the ground truth was based on objective measurements or established references within phantom models, rather than pathology or patient outcomes.

8. The Sample Size for the Training Set

The document does not provide information about the sample size used for the training set. The descriptions focus solely on performance "testing" using phantom datasets.

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

Since information regarding a training set is not provided, the method for establishing its ground truth is also not specified. The details are centered on the evaluation of the device as a pre-trained system.

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