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The 3TP Software Option is intended to be used as a post processing software package designed to provide a reliable means for visualizing the presence and pattern of contrast induced enhancement on MR datasets. 3TP supports the evaluation of dynamic MR data gathered during the injection of a bolus of contrast media. The resulting time course information can be displayed in a variety of formats, including a parametric image overlaid onto source MR images. In the hands of a trained physician the information provided by the 3TP Software Option could yield information that may assist in the interpretation of dynamic contrast enhanced studies.

The 3TP Software Option is a post processing software module. The 3TP Software Option supports the evaluation of dynamic MR data gathered after the injection of a bolus of a contrast agent. Multi-sliced MR datasets with specified time intervals are used for input. The purpose is to provide a new composite "3TP Image" that provides a trained physician with information useful for diagnostic purposes.

Here's an analysis of the provided text regarding the acceptance criteria and study for the 3TP Software Option:

It's important to note that this document is a 510(k) summary from 2003, which typically focuses on demonstrating substantial equivalence to predicate devices rather than providing extensive details on novel performance studies with statistical significance. As such, information on some of your requested points is either very limited or entirely absent.

Summary of Acceptance Criteria and Device Performance based on the document:

Study Information:

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

   • Sample Size: Not specified.
   • Data Provenance: Not specified.
   • Retrospective or Prospective: Not specified.

2. 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. The document primarily discusses internal software testing (integration and beta testing) rather than clinical performance testing with expert readers and ground truth.

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

   • Not specified. Given the nature of the described "performance testing" (integration and beta of software), formal adjudication by multiple experts for a clinical test set is not mentioned.

4. 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 MRMC comparative effectiveness study is described. The document states: "In the hands of a trained physician the information provided by the 3TP Software Option could yield information that may assist in the interpretation of dynamic contrast enhanced studies." This implies assistance, but no formal comparative effectiveness study is presented.

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

   • The "Performance Testing" section describes integration testing and beta testing. These are internal software tests to ensure functionality and stability, not standalone clinical performance evaluation against a medical ground truth. The device is explicitly intended to provide "information that may assist in the interpretation" by a "trained physician," indicating a human-in-the-loop design.

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

   • For the "Performance Testing" described (integration and beta testing), the "ground truth" would likely be the expected software output and functionality, verified by engineers/testers against software specifications. There is no mention of medical ground truth (e.g., pathology, outcomes, expert consensus) being used for performance evaluation in a clinical context.

7. The sample size for the training set:

   • This document does not describe the development or training of an AI/ML model in the modern sense. It describes a "post processing software package." Therefore, there is no mention of a "training set" as it would apply to machine learning.

8. How the ground truth for the training set was established:

   • As there's no mention of a training set for an AI/ML model, this information is not applicable.

Explanation and Context:

This 510(k) summary (from 2003) predates the widespread adoption of AI/ML in medical devices and the rigorous performance study requirements now common for such devices. The "performance testing" described ("integration testing and verification" and "software beta testing") are standard software development lifecycle activities focused on ensuring the software correctly performs its intended functions according to specifications, rather than clinical performance studies measuring diagnostic accuracy or reader improvement.

The primary argument for safety and effectiveness relies on substantial equivalence to predicate devices (GE Advantage Windows With Functool Option, GE Prostate Spectroscopy and Imaging Exam (PROSE), Philips EasyVision Quantitative Analysis Option). The 3TP Software Option "provides a post-processing means for analyzing changes in signal intensity of a contrast agent as reflected in MR images," similar to these predicate devices. The claim is that it "does not result in any additional hazards" and "does not include any new indications for use nor does the use of this device result in any new potential hazards" compared to the predicate devices. This type of submission relies on the established safety and effectiveness of the existing predicate devices, rather than comprehensive de novo clinical performance studies.

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