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K Number
K980495
Device Name
MUSE CARDIOVASCULAR INFORMATION SYSTEM
Manufacturer
MARQUETTE MEDICAL SYSTEMS, INC.
Date Cleared
1998-05-07

(87 days)

Product Code
LOS
Regulation Number
N/A
Type
Traditional
Panel
CV
Reference & Predicate Devices
K840932
AI/MLSaMDIVD (In Vitro Diagnostic)TherapeuticDiagnosticis PCCP AuthorizedThirdpartyExpeditedreview
Intended Use

The MUSE CV is a large capacity client server based computer system that accesses, stores and manages cardiovascular information. The information can consist of measurements, text, and digitized waveforms. MUSE CV is intended to be used in a hospital environment by trained operators. MUSE CV is designed for network compatibility and interfaces with other hospital information systems through various communication protocols. MUSE CV provides the ability to serially compare/trend cardiovascular information. Use of MUSE CV is intended for accessing, storage and management of both adult and pediatric cardiovascular information.

Device Description

MUSE CV is a large capacity client server based computer system that accesses, stores and manages cardiovascular information. The information can consist of measurements, text, and digitized waveforms.

AI/ML Overview

This document describes a 510(k) premarket notification for the "MUSE Cardiovascular Information System". It's important to note that this submission does not contain acceptance criteria or performance study results in the typical sense of evaluating an AI/ML device.

The document states that the MUSE CV system employs the same functional technology as predicate devices, with improvements in "speed, performance and reliability." It also claims compliance with "voluntary standards as detailed in Section 9 of this submission," but Section 9 is not provided in the given text.

The "performance" section mentions quality assurance measures applied during development, but these are general development practices and not specific study results or acceptance criteria for a device performance claim like accuracy, sensitivity, or specificity.

Therefore, many of the requested fields cannot be filled from the provided text because the submission focuses on substantial equivalence to predicate devices based on functional technology and general quality assurance, rather than detailed performance metrics of a novel AI/ML algorithm.

Here's a breakdown based on the information available:

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

    • Acceptance Criteria: Not explicitly stated as quantifiable performance metrics (e.g., accuracy, sensitivity, specificity). The criteria appear to be compliance with voluntary standards and demonstrating that the device is "as safe, as effective, and performs as well as the predicate devices."
    • Reported Device Performance: The document only states that "The results of these measurements demonstrated that MUSE CV is as safe, as effective, and performs as well as the predicate devices." No specific quantitative performance values are provided.

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

    • Not specified. There is no mention of a traditional "test set" or clinical study data.

  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):

    • Not applicable. No ground truth establishment process is described as there's no clinical performance study detailed.

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

    • Not applicable. No test set or expert adjudication 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. This type of study is not mentioned. The device's primary function is described as storing, managing, and facilitating serial comparison/trending of cardiovascular information, not 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:

    • Not applicable in the typical AI sense. The device is a "Cardiovascular Information System" for data management, not a standalone diagnostic algorithm. While it performs "serial comparison" and "serial trending," its performance is evaluated against predicate devices based on a broader system functionality, not specific diagnostic accuracy.

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

    • Not applicable. No ground truth for performance evaluation is described.

  8. The sample size for the training set:

    • Not applicable. This is not an AI/ML device that requires a training set in the typical sense.

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

    • Not applicable. As above, no training set is mentioned.

Summary based on available information:

The provided document is a 510(k) summary focused on demonstrating substantial equivalence of the "MUSE Cardiovascular Information System" to existing predicate devices. It emphasizes functional and technological similarity, as well as adherence to general quality assurance and voluntary standards. It does not detail specific performance studies with quantitative metrics, test sets, or ground truth establishment typically associated with the evaluation of AI/ML diagnostic or assistive devices.

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