(49 days)
MR VessellQ Xpress is intended to provide an optimized non-invasive application to facilitate vascular anatomy and pathology analysis from a set of DICOM 3.0 compliant 3D contrastenhanced Magnetic Resonance Angiographic (MRA) images.
MR VessellQ Xpress is a post processing application which can be used in the analysis of MRA data for the purpose of vascular disease assessment.
This software is designed to assist radiologists and other clinicians in the evaluation and assessment of vascular anatomy and disease with the capability to provide a set of tools for visualizing directional vessel tortuosity, for sizing the vessel and for measuring areas of abnormalities within a vessel.
MR VessellQ Xpress is a post processing analysis software application designed to assist Radiologists, Cardiologists, and other clinicians in the evaluation and assessment of vascular anatomy.
MR VessellQ Xpress is a software package for the Advantage Workstation (AW) platform and AW Server platform. The MR VessellQ Xpress is an additional tool for the 2D and 3D analysis of DICOM compliant MR angiographic images/data , providing a number of display, measurements and batch filming/archive features to study user-selected vessels which include but are not limited to stenosis analysis and directional vessel tortuosity visualization.
The GE Healthcare MR VessellQ Xpress device, a post-processing analysis software for evaluating vascular anatomy and pathology from MRA images, did not require clinical studies to support substantial equivalence. The submission states that the device was found to be as safe and effective as, and substantially equivalent to, its predicate devices (K041521 Volume Viewer Plus by GE Medical Systems and K040746 MRA-CMS by Medis Medical Imaging Systems) based on non-clinical tests and compliance with recognized standards.
Here's a breakdown of the requested information based on the provided text:
1. Table of Acceptance Criteria and Reported Device Performance
| Acceptance Criteria | Reported Device Performance |
|---|---|
| Compliance with NEMA PS 3.1 - 3.18(2008) Digital Imaging and Communications in Medicine (DICOM) Set | MR VessellQ Xpress and its components comply with this standard. |
| Compliance with ISO 13485 Quality Systems - Model for Quality Assurance in design, development, production, installation and servicing of medical device | MR VessellQ Xpress was designed in compliance with this standard. |
| Compliance with ISO 14971 Medical devices - Application of Risk management to medical devices | MR VessellQ Xpress was designed in compliance with this standard. |
| Compliance with IEC 62304 Medical device software - Software life cycle processes | MR VessellQ Xpress was designed in compliance with this standard. |
| Compliance with IEC 62366 - Medical devices - Application of usability engineering to medical devices | MR VessellQ Xpress was designed in compliance with this standard. |
| Application of Quality Assurance Measures (Risk Analysis, Requirements Reviews, Design Reviews, Unit level testing, Integration testing, Final acceptance testing, Performance testing, Safety testing) | These quality assurance measures were applied to the development of the device. |
| No new potential safety risks | The device does not result in any new potential safety risks. |
| Performs as well as predicate devices | The device performs as well as the predicate devices currently on the market. |
2. Sample size used for the test set and the data provenance
The submission explicitly states: "MR VessellQ Xpress did not require clinical studies to support substantial equivalence." Therefore, no test set of patient data was used for a clinical study. The evaluation was based on non-clinical tests and compliance with standards.
3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts
As no clinical studies were performed, no experts were involved in establishing ground truth for a test set of patient data.
4. Adjudication method for the test set
Not applicable, as no clinical studies with a test set were conducted.
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 MRMC comparative effectiveness study was performed.
6. If a standalone (i.e. algorithm only without human-in-the loop performance) was done
The submission does not detail any standalone performance studies using clinical data. The performance claims are based on comparison to predicate devices and adherence to design/quality standards.
7. The type of ground truth used (expert consensus, pathology, outcomes data, etc.)
Not applicable in the context of a clinical test set. The ground truth for proving performance was based on adherence to engineering and quality standards, and comparison of technical specifications and intended use with predicate devices.
8. The sample size for the training set
Not applicable, as no information regarding a training set for a machine learning model is provided. The submission describes a software application that employs "the same fundamental scientific technology as its predicate devices," suggesting the device's functionality is based on established algorithms for image analysis rather than a newly trained AI model requiring a separate training set.
9. How the ground truth for the training set was established
Not applicable, as no training set is mentioned or implied for a machine learning model.
§ 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).