(135 days)
CardioPACS is a software device intended to be used by medical professionals, for storage, review, query/ retrieve, analysis and post processing of DICOM medical images as may be generated by echocardiography, radiology and other modalities. The device may be used as a stand-alone product, or in a networked system.
CardioPACS is not intended to be used for reading of mammography images.
HealthView CardioPACS (version 6.0), herein after referred to as CardioPACS, is a Picture Archive Communications System. It is a "software only" medical device, to be installed on a server and workstation(s) that meet the minimum hardware requirements noted in the documentation. The hardware itself is not considered a medical device and is not part of this 510(k) submission. The device provides a trained user with the ability to find, retrieve, view, edit and manipulate images on a workstation, to assist in the diagnosis and treatment planning of patients. The device does not contact the patient and does not control any life sustaining devices.
CardioPACS is a software-only DICOM-compliant device that can be used on multiple hardware platforms (provided that the minimum hardware requirements are met) that allows viewing, editing, measuring and other digital image processing.
The provided text is a 510(k) summary for the CardioPACS (version 6.0) device. This type of submission focuses on demonstrating substantial equivalence to a predicate device rather than providing detailed clinical study results to meet specific performance acceptance criteria.
Therefore, the document does not contain information about:
- A table of acceptance criteria and reported device performance (in the context of clinical metrics like sensitivity/specificity).
- Sample size used for a test set or its data provenance.
- Number of experts used to establish ground truth or their qualifications.
- Adjudication method for a test set.
- MRMC comparative effectiveness study or human-AI improvement effect size.
- Standalone algorithm performance (as it is a PACS system designed for human use).
- Type of ground truth used for performance evaluation (e.g., pathology, outcomes data).
- Sample size for a training set.
- How ground truth for a training set was established.
Information Provided Regarding Performance and Testing:
The document states the following under "Performance Test Data":
- Acceptance Criteria Mentioned (Implicit/General): "Every identified requirement has been tested and confirmed to be performing as expected."
- Study/Testing Methods: Performance has been substantiated in multiple ways:
- Verifying accuracy of measurement tools using other cleared devices.
- Verifying the speed of performance in a simulated network environment.
- Validating retrieval speed at a validation site.
- Validating tools accuracy at a validation site.
- Compliance: The device has been tested to confirm compliance with voluntary standard DICOM version 3.0.
- Risk Management: ISO14971 (2007) standard was used to identify and mitigate potential hazards. Verification and validation testing confirmed control of these hazards.
In summary, the document describes general performance testing related to software functionality, DICOM compliance, and accuracy of measurement tools against other cleared devices, rather than a clinical study with specific diagnostic performance metrics (e.g., sensitivity, specificity) against a well-defined ground truth in a clinical population. The purpose of this 510(k) is to demonstrate substantial equivalence to predicate PACS systems, which are image management and viewing systems, not AI-driven diagnostic algorithms requiring extensive clinical performance studies.
§ 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).