K Number
K162112
Device Name
CAAS MRV
Date Cleared
2016-09-21

(54 days)

Product Code
Regulation Number
892.2050
Panel
RA
Reference & Predicate Devices
AI/MLSaMDIVD (In Vitro Diagnostic)TherapeuticDiagnosticis PCCP AuthorizedThirdpartyExpeditedreview
Intended Use

CAAS MRV features segmentation of cardiovascular structures on different types of MR images as well as measurement and reporting tools to facilitate the following use:

· Quantitative functional and regional analyses of the heart ventricles

· Quantification of T2 and T2* relaxation values
CAAS MRV is intended to be used by or under supervision of a cardiologist. When the results provided by CAAS MRV are used in a clinical setting to support diagnosis of cardiovascular conditions, the results assurts of critic to be regarded as the sole, irrefutable basis for clinical decision making.

Device Description

CAAS MRV is designed as a stand-alone modular software package for viewing and quantification of cardiovascular MR images intended to run on a PC with a Windows operating system. The images for analysis can be read from CD, hard disk or from a PACS system and CAAS MRV provides the functionality to scan the contents of a specific directory and to organize the found DICOM MR images into patients, studies and series.

CAAS MRV contains several analysis workflows of the previously cleared predicate device CAAS MRV (K060941) for quantification of the functional and regional parameters of the heart ventricles. Contour detection performed automatically, semi-automatically or manually forms the bases for the analyses.

Functionality to quantify T2 and T2* relaxation values is added by means of the analysis module Tissue Mapping. For this specific feature, Medis MR-CT VVA is used as a predicate device. This feature is implemented in MR-CT VVA and is very similar in both control and presentation, to the CAAS MRV feature, and yields the same results.

The quantitative results of CAAS MRV support diagnosis of cardiovascular conditions.

The analysis results are available on screen and can be saved to hard-disk to enable re-analysis of the data. Also, the analysis results can be exported in various electronic formats.

The functionality is independent of the type of vendor acquisition equipment.

AI/ML Overview

Acceptance Criteria and Device Performance for CAAS MRV (K162112)

Note: The provided document is a 510(k) summary, which generally focuses on demonstrating substantial equivalence to predicate devices rather than detailing extensive clinical trials with specific acceptance criteria and outcome metrics for standalone performance or comparative effectiveness. Therefore, some requested information may not be explicitly present and is inferred where possible.

1. Table of Acceptance Criteria and Reported Device Performance

The document does not explicitly present a table of numerical acceptance criteria. Instead, it describes general validation approaches and claims equivalence rather than specific quantitative performance targets. The "Performance Data" section states that "the quantification of the tissue relaxation values (T2 and T2*) meet the accuracy and reproducibility requirements." However, the specific numerical requirements or the reported accuracy/reproducibility values are not disclosed in this document.

For the purpose of illustrating the expected format, if such a table were present, it might look like this:

Performance MetricAcceptance CriteriaReported Device Performance (as described/implied)
Quantification of T2/T2 relaxation values (Tissue Mapping)**[Specific numerical accuracy targets, e.g.,

§ 892.2050 Medical image management and processing system.

(a)
Identification. A medical image management and processing system is a device that provides one or more capabilities relating to the review and digital processing of medical images for the purposes of interpretation by a trained practitioner of disease detection, diagnosis, or patient management. The software components may provide advanced or complex image processing functions for image manipulation, enhancement, or quantification that are intended for use in the interpretation and analysis of medical images. Advanced image manipulation functions may include image segmentation, multimodality image registration, or 3D visualization. Complex quantitative functions may include semi-automated measurements or time-series measurements.(b)
Classification. Class II (special controls; voluntary standards—Digital Imaging and Communications in Medicine (DICOM) Std., Joint Photographic Experts Group (JPEG) Std., Society of Motion Picture and Television Engineers (SMPTE) Test Pattern).