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Advantage 4D is a non-invasive software / hardware option that can be used to provide and display CT images of all phases of a breathing cycle for the evaluation of respiration-induced motion. The software will allow the user to retrospectively define the best respiratory phase from an image quality standpoint, and group images by the phase selected. Advantage 4D can also be used for target or treatment volume (DICOM Radiation Therapy Structure Sets) verification

Advantage 4D enables a patient to be scanned on a CT with normal breathing. CT data are acquired and images are reconstructed without image artifacts due to organ and tissue motion. CT Images are synchronized with respiratory signal coming from external device and organ/tissue motion within the CT data reflecting both the organ motions and the chest motion. The user can then visually determine the optimum phase to perform volume imaging and post processing [quantification, contouring, segmentation. The respiratory phase identification is also provided. In addition. Advantage 4D has the capability to display DICOM Radiation Therapy Structure Sets and can be used for target or treatment volume verification.

The provided text is a 510(k) summary for the GE Advantage 4D option, a software/hardware accessory for CT systems. It focuses on the device's technological equivalence to previously cleared devices rather than providing a detailed study that proves the device meets specific acceptance criteria.

Therefore, many of the requested details cannot be extracted from the provided document.

Here's a breakdown of what can be inferred or explicitly stated:

1. Table of Acceptance Criteria and Reported Device Performance

The document does not explicitly state acceptance criteria in terms of quantitative performance metrics for the Advantage 4D option. Instead, it relies on demonstrating substantial equivalence to predicate devices (Smart Breath Respiratory Compensation and Advantage Sim 6.0) based on similar technology, intended use, and absence of new safety risks.

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

Not specified. The document does not describe a test set or clinical study with patient data. The evaluation is based on technological comparison and risk analysis.

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

Not specified. No ground truth establishment processes involving experts are described for a test set.

4. Adjudication method for the test set

Not specified. No test set or adjudication method is described.

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. An MRMC study is not mentioned as this device is an accessory for displaying CT images synchronized with respiratory signals and does not involve AI assistance for human readers in the diagnostic process beyond presenting organized data.

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

The device is described as a "software / hardware option" that enables users to "visually determine the optimum phase" and "group images by the phase selected." While it processes data automatically to present phases, its primary function involves user interaction and interpretation of the displayed information. A standalone performance evaluation in the absence of human interaction is not described.

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

Not specified. Given the nature of the submission (510(k) for an accessory based on substantial equivalence), detailed clinical ground truth establishment for a diagnostic output is not the focus.

8. The sample size for the training set

Not specified. The document does not describe a training set as it's not a machine learning-based device requiring extensive training data.

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

Not applicable, as no training set is described.

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