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The Prism 3000XPV system is a modification of a gamma camera system. This device is intended to be used for diagnostic imaging of organs and lesions. There is no change of intended use from that of the predicate device. This device includes adding hardware and software to a gamma camera system.

The Prism 3000XPV system is a modification of a gamma camera system. This device includes adding hardware and software to a gamma camera system.

This document, K961577 JUL 23 1996 for the PICKER INTERNATIONAL PRISM 3000XPV SYSTEM, does not contain the detailed information necessary to answer your request fully.

The document is a summary of safety and effectiveness for a 510(k) notice for a gamma camera system. It primarily focuses on demonstrating substantial equivalence to a predicate device and discussing general validation plans, rather than detailing the specific acceptance criteria and a study proving those criteria were met for a new AI/algorithm-driven device.

Here's a breakdown of what can and cannot be answered based on the provided text:

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

• Cannot be provided. The document states: "Laboratory tests will be run to validate the image quality performance of the system. The product will perform in accordance with the development specifications." However, it does not describe what these "development specifications" or "acceptance criteria" are, nor does it report any specific performance metrics (e.g., sensitivity, specificity, accuracy, image quality scores).

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

• Cannot be provided. The document mentions "Laboratory tests" but gives no details about sample size, the nature of the test set (e.g., patient data, phantoms), or data provenance.

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)

• Cannot be provided. The document states: "The system will be operated by trained health care professionals who are responsible for Nuclear Medicine diagnostic examinations." While this implies interpretation by experts, there is no mention of a formal process for establishing ground truth for a test set, the number of experts involved, or their specific qualifications for a study.

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

• Cannot be provided. No information about adjudication is present.

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. This device is a new hardware/software system for a gamma camera, not an AI or algorithm-driven assistant for human readers. The document does not describe an MRMC study or any study involving human readers with and without AI assistance, as the "AI" component (if any) is not framed in this context. The focus is on the system's performance itself, not on aiding human interpretation in a comparative effectiveness study.

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

• Standalone performance as an algorithm is not applicable in the context described. The device is a gamma camera system, which produces images for interpretation by "trained health care professionals" (human-in-the-loop). While the system has "hardware and software," its performance is likely measured on image quality parameters, not as an "algorithm only" that performs a diagnostic task without human review. The document does not provide such a study.

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

• Cannot be provided. No information about the type of ground truth is available.

8. The sample size for the training set

• Cannot be provided. The document does not mention a training set, as this is a traditional gamma camera system and not described as using machine learning requiring a training phase for an algorithm.

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

• Cannot be provided. As no training set is mentioned, this question is not applicable.

In summary: The provided document is a high-level 510(k) summary for a gamma camera system, focusing on regulatory approval through substantial equivalence. It lacks the specific details regarding device performance criteria, detailed study designs, and results that would be expected for a modern AI/ML-driven medical device, or even for a detailed performance study of a conventional device.

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