(119 days)
The Corview software application is indicated for viewing and post-processing of cardiovascular magnetic resonance images (MRIs) to obtain Left Atrial Enhancement (LAE) quantification and visualization on a 3D model. It provides measurements of LAE within the left atrial wall.
It enables:
- . Importing Cardiac MRIs in DICOM format
- Qualitative analysis of the cardiac MRIs using display functionality such as . panning, windowing, zooming, and navigation through series/slices and phases
- . Quantitative measurement in cardiac MRIs, specifically LAE
It is intended for use by qualified medical professionals experienced in examining and evaluating cardiovascular MRIs, for the purpose of obtaining diagnostic information as part of a comprehensive diagnostic decision-making process.
The target population of Corview is not restricted. However image acquisition by an MRI scanner with cardiac capability may limit the use of the device for certain sectors of the general public.
Corview is intended to view only cardiac magnetic resonance images acquired from an MRI scanner with cardiac capabilities.
The CORVIEW software application is intended for use in the clinical setting.
CORVIEW is an independent software solution for the segmentation and quantitative analysis of digitized cardiac magnetic resonance images (MRIs). CORVIEW operates on higher-end off-the-shelf PC or Apple computers and is compatible with Cardiac MRI digital images in DICOM format from a range of commercial MRI machine vendors. The CORVIEW software platform is also designed to process MRIs received from various modes of image exchange.
CORVIEW presents a state-of-the-art method to process and quantify the extent of left atrial enhancement (LAE) within the left atrial wall by contouring and identifying the endo- and epi-cardial borders from contrast enhanced MR image sequences that have been acquired as part of a conventional cardiac MRI examination.
CORVIEW is designed for the processing of 3D image datasets allowing users to produce contour models and visualizations of left atrial structure and contrast enhancement. Based on 3D-acquired datasets, a feature classification algorithm supports the calculation of LAE. From these corresponding algorithms, total percentage of enhancement can be derived. In addition, the corresponding shape of the left atrium can also be obtained.
The provided text (K13/1158) does not contain information about the specific acceptance criteria and study details as requested. It outlines the device's description, indications for use, comparison to predicate devices, and general statements about non-clinical performance data testing, including software verification and validation. However, it lacks the granular detail needed to populate the requested table of acceptance criteria and reported performance, nor does it specify the sample sizes, expert qualifications, ground truth methods, or MRMC study details.
The document primarily focuses on regulatory compliance (510(k) summary) and demonstrating substantial equivalence to predicate devices based on technological features and general software validation. It states that "Test results meet the required pass/fail criteria" and that "risk management processes, documented verification and validation processes to ensure performance to specifications," but it doesn't describe what those specifications or criteria were.
Therefore, I cannot fulfill the request given the provided input. The document is a high-level summary for regulatory approval, not a detailed report of a performance validation study.
§ 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).