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510(k) Data Aggregation
(62 days)
AMERICAN MEDICAL SALES, INC.
The Catella Diagnostic Workstation, Version 4.0, is a medical image and information management system that allows easy viewing, selection, processing, printing, telecommunications, and media interchange of multimodality medical images from a variety of diagnostic imaging systems. The Catella PACS interfaces to various storage and printing devices using DICOM or similar interface standards. The system is available for diagnostic and nondiagnostic workstations, including workstations designed as web-based, remote viewers or CD-viewer workstations. The software may be installed as a PC-based stand alone system, a software application, a web-based or SDK format, and is designed to be integrated with various DICOM compliant OEM systems.
The Catella PACS displays, stores, prints, and telecommunicates images from a number of medical modalities, including but not limited to MR, CT, DR, CR, X-ray, Angiography, Ultrasound, or digitizers. The Catella Diagnostic Workstation, Version 4.0 performs other user-defined post-processing functions, such as multi-planar reformatting of images. The Catella PACS can display processed data from certain FDA-cleared third party image processing systems that create DICOM output. With proper links, the Catella Workstation also can invoke FDA-cleared third party image processing systems for advanced image processing, such as 3D display. It can also access RIS and HIS systems and can be used to review patient information.
The Catella Diagnostic Workstation, Version 4.0, is not intended for use for primary diagnostic interpretation of mammographic images.
The Catella Diagnostic Workstation, Version 4.0 is a multi-modality PCdriven review workstation that operates on a standard Windows operating system. Each workstation may include a high performance computer, communications capability, medical grade, high-resolution monitors and video cards, trackball or mouse, microphone, keyboard, foot pedal and ergonomically designed display cart. The system is available for diagnostic and non-diagnostic workstations, including workstations designed as webbased, remote viewers or CD-viewer workstations. The software may be installed as a PC-based stand alone system, a software application, a webbased or SDK format, and is designed to be integrated with various DICOM compliant OEM systems.
The Catella Diagnostic Workstation, Version 4.0 includes the following software features:
- The Catella Diagnostic Workstation, Version 4.0 allows the user to . select a study to view, archive, and perform administrative tasks.
- . The Catella Diagnostic Workstation, Version 4.0 includes multimodality viewing capabilities, allowing the user to view images from various modalities.
- . Digitized mammographic images displayed on the Catella Diagnostic Workstation, Verison 4.0 must not be used for primary diagnostic interpretation.
- . Lossy compressed mammographic images should not be used for primary diagnosis and contain a warning.
- DICOM query/retrieve and print, which allows retrieval of DICOM . data from any DICOM-compliant device that is configured for query and retrieval.
The Catella Diagnostic Workstation, Version 4.0 also provides various software components described in the User Manual, including:
- . Software for viewing images, playing audio, or viewing or dictating reports
- . Zoom, pan, window/level
- . Menu options
- Annotations, standard software tools .
- . Stack/Cine viewing mode
- . DICOM query/receive
- DICOM-compliant methods of lossless and lossy image compression . (JPEG2000 and JPEG)
- . Outputs DICOM medical image data to printers that adhere to appropriate regulatory standards.
- . Outputs medical imaging data in DICOM format to archives that use appropriate media that are designed to prevent data loss.
- . Enables storage and reading of digitized images.
Here's an analysis of the provided text regarding the Catella Diagnostic Workstation, Version 4.0, structured according to your request:
Acceptance Criteria and Study for the Catella Diagnostic Workstation, Version 4.0
The provided 510(k) summary for the Catella Diagnostic Workstation, Version 4.0, focuses on demonstrating substantial equivalence to predicate devices rather than proving specific performance metrics against pre-defined acceptance criteria through a dedicated study. This is a common approach for PACS systems, where the primary concern is the safe and effective display, storage, and communication of medical images, similar to already-cleared devices.
The document states: "The potential hazards have been studied and controlled as part of the product development process, including risk analysis, test and design considerations, and planned verification and validation testing processes. The Catella Diagnostic Workstation, Version 4.0 provides images and data management capabilities comparable to the predicate devices." This implies that verification and validation were performed to ensure the device functions as intended and safely, consistent with its intended use and comparison to predicates.
1. Table of Acceptance Criteria and Reported Device Performance
Based on the provided document, specific quantitative acceptance criteria or detailed performance metrics from a study are not explicitly stated or included. The submission relies on demonstrating substantial equivalence to predicate devices which are already on the market and presumed safe and effective.
Therefore, the table would look like this, reflecting the lack of explicit quantitative criteria often seen in performance claims for AI/CAD devices:
Acceptance Criteria (Explicitly Stated) | Reported Device Performance |
---|---|
Not explicitly defined as quantitative performance criteria for a specific clinical task. The basis of acceptance is substantial equivalence to predicate devices. | The device provides "images and data management capabilities comparable to the predicate devices." This implies functional equivalence in viewing, selection, processing, archiving, printing, and media interchange of multi-modality images. |
2. Sample Size Used for the Test Set and Data Provenance
The document does not specify a separate test set, its sample size, or the provenance of any data used for a performance study. The substantial equivalence argument does not require a clinical performance study with a test set in the same way an AI/CAD device might.
3. Number of Experts Used to Establish Ground Truth for the Test Set and Qualifications
Since no specific test set or performance study is detailed, there is no information on the number of experts used or their qualifications for establishing ground truth.
4. Adjudication Method for the Test Set
As there is no mention of a test set or performance study, no adjudication method is described.
5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study Was Done
No, a Multi-Reader Multi-Case (MRMC) comparative effectiveness study was not done or reported in this 510(k) summary. This type of study demonstrates improved human performance with AI assistance, which is not the type of claim this device is making.
6. If a Standalone (i.e. algorithm only without human-in-the-loop performance) Was Done
No, a standalone performance study of an algorithm without human-in-the-loop performance was not done or reported. The device is a "workstation" and focuses on display and management functionality.
7. The Type of Ground Truth Used
Given the nature of the device (a PACS workstation) and the 510(k) summary, which focuses on substantial equivalence rather than a clinical performance claim, there is no mention of a specific "ground truth" used in the context of a diagnostic or algorithmic performance study. The ground truth for a PACS primarily relates to the accurate and lossless display and management of image data, which is typically verified through technical testing and functional validation, not expert consensus on pathology or outcomes.
8. The Sample Size for the Training Set
The document does not specify a training set sample size. This device is a software workstation for image management, not an AI/ML algorithm that requires a training set in the conventional sense.
9. How the Ground Truth for the Training Set Was Established
Since there is no training set mentioned or implied for an AI/ML algorithm, the method for establishing ground truth for a training set is not applicable and not detailed in this submission.
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