(15 days)
QLAB Quantification software is a software application package. It is designed to view and quantify image data acquired on Philips Medical Systems ultrasound products.
OLAB version 6.0 adds the OLAB MVO Plug-in and OLAB TMO/TMOA Plug-ins to the cleared QLAB software.
QLAB MVQ Plug-in (MVQ stands for Mitral Valve Quantification) Tool to assess lengths, distances, areas, volumes and angles of mitral valve structures from a Philips Ultrasound system 3D dataset.
QLAB TMQ/TMQA Plug-ins (TMQ and TMQA stands respectively for Tissue Motion Quantification and Tissue Motion Quantification Advanced) TMQ and TMQA plug-ins are an addition to the existing 2DQ plug-in already described on the iE33 510(k) submission K042540. The QLAB TMQ/TMQA plugins provide ultrasound tracking algorithm using pattern-matching method of wall lengthening, shortening and displacement in a set of 2D image. Radial, longitudinal, circumferential, lengths and strains are computed as well as rotation and rotation gradient and absolute speed. TMQ provides only one myocardial layer and 17 segmentation model only; TMQA will provide Multi Myocardial Layers and a choice of Segmentation on and off. CAK (Cardiac Annular Kinesis) feature is an addition to the existing 2DQ plug-in already described on the iE33 510(k) submission K042540. CAK will be a feature of existing 2DQ plug-in as well as TMQ and TMQA plug-ins. CAK is Quick survey tool of global function assessment.
The provided text does not contain specific acceptance criteria or details of a study proving the device meets acceptance criteria.
The document is a 510(k) Premarket Notification for the QLAB Quantification Software. It outlines the administrative information, device description, performance standards (or lack thereof), safety and effectiveness concerns, substantially equivalent devices, and software development processes. It concludes that the software is designed to meet United States and international standards for display and quantification of images acquired on Philips Ultrasound devices and incorporates features of legally marketed devices without raising new safety or effectiveness issues.
Missing information includes:
- Acceptance Criteria and Reported Device Performance: No specific numerical or qualitative acceptance criteria are provided for the QLAB Quantification Software, nor are there any reported performance metrics against such criteria.
- Sample Size and Data Provenance for Test Set: The document does not mention a test set, its sample size, or the provenance of any data used for testing.
- Number and Qualifications of Experts for Ground Truth: There is no information about experts used to establish ground truth.
- Adjudication Method: No adjudication method is described.
- MRMC Comparative Effectiveness Study: The document does not mention an MRMC study or any effect size for human readers with or without AI assistance.
- Standalone Performance Study: No details of a standalone (algorithm-only) performance study are provided.
- Type of Ground Truth Used: The document does not specify the type of ground truth used for any evaluations.
- Sample Size for Training Set: There is no mention of a training set or its sample size.
- How Ground Truth for Training Set was Established: This information is not present.
The document primarily focuses on regulatory compliance, device description, and claims of substantial equivalence to predicate devices, rather than detailed performance study results against specific acceptance criteria.
§ 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).