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Vantage 2.5 is a software program, which will be marketed as an addition to ADAC Laboratories Gamma Camera products. This is a modification of the Vantage 2.0 ExSPECT software package, cleared in 510k K971878.

Vantage 2.5 is intended to provide quality assurance enhancements to nuclear medicine images acquired using the gold Gama Camera Systems. It includes scatter correction capability for scatter correction capability for

Vantage 2.5 is a software program, which will be marketed as an optional addition to ADAC Laboratories Gamma Camera products. This is a modification of the Vantage 2.0 ExSPECT software package, cleared in 510(k) K971878.

Vantage 2.5 is a computer program that provides a patient's anatomical information using the external radioactive scanning line sources with special collimation to minimize patient exposure, and the acquisition electronics and software, cleared in 510(k) K943596 for Vantage 1.0 and in 510(k) K971878 for Vantage 2.0 ExSPECT.

The system uses the same imaging technique of Single Photon Emission Computed Tomography (SPECT) with attenuation correction, as in Vantage 2.0 ExSPECT, but adds Quality Assurance (QA) Tools by using Pre-Scan, Automatic Energy Window Checking and Transmission QA Reference.

This 510(k) summary for the Vantage 2.5 Gamma Camera System does not contain the detailed information necessary to complete the acceptance criteria table and answer all the questions regarding the study. The document primarily focuses on demonstrating substantial equivalence to a predicate device and describes the general function of the software.

Here's what can be extracted and what information is missing:

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

This information is not provided in the document. The 510(k) summary states, "Images were acquired using the protocol outlined in the Vantage user manual," but it does not specify any acceptance criteria or present performance data for the Vantage 2.5 itself. The basis for clearance appears to be substantial equivalence to the Vantage 2.0 ExSPECT, which implies a similar performance profile, but no specific metrics are given for Vantage 2.5.

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

This information is not provided in the document.

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)

This information is not provided in the document.

4. Adjudication method (e.g., 2+1, 3+1, none) 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

An MRMC study is not mentioned in the document. Given the description, Vantage 2.5 is a software program that enhances quality assurance for nuclear medicine images and provides scatter correction. It is not described as an AI-assisted diagnostic tool for human readers.

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

A standalone performance study focused on specific metrics is not explicitly described. The document states that the "Vantage 2.0 ExSPECT and Vantage 2.5 devices have the same indications for use, source type and geometry, system hardware, operating principles, and reconstruction algorithms, with the exception of minor modifications to the acquisition software." This implies that its performance is presumed to be similar to Vantage 2.0, which was previously cleared, rather than providing new standalone performance data for Vantage 2.5 itself. The "Quality Assurance (QA) Tools" are functions, not necessarily requiring a standalone performance study in the way an AI diagnostic algorithm might.

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

This information is not provided in the document.

8. The sample size for the training set

This information is not provided in the document. The submission focuses on modifications to existing software rather than the development of a new algorithm with a distinct training set.

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

This information is not provided in the document.

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