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The ImageSVR PACS is intended for the manipulation, management, and display of medical images. It can manage and display images from different modalities and interfaces and can distribute those images to various workstation, image storage and printing devices using DICOM or similar standards. Typical users of this system are trained medical professionals, including physicians, nurses, technicians and computer system professionals.

To support the diagnostic interpretation of mammography studies, ImageSVR PACS will display the full fidelity DICOM image in a non-compressed format. Mammographic images may only be interpreted using an FDA approved monitor that offers at least 5Mpixel resolution and meets other technical specifications reviewed and accepted by FDA. Lossy compressed mammographic images and digitized film screen images must not be reviewed for primary diagnosis or image interpretation.

The ImageSVR PACS is a suite of applications designed and produced by Jaguar Technology Ltd. It is a client-server based software system manages archiving, retrieving and displaying medical images. The server side application is ImageSVR PACS SERVER. And client side is ImageSVR PACS CLIENT.

Here's a breakdown of the acceptance criteria and study information for the Jaguar Technology Limited ImageSVR PACS, based on the provided text:

1. Table of Acceptance Criteria and Reported Device Performance

The provided text does not explicitly state specific quantitative acceptance criteria or detailed performance metrics for the ImageSVR PACS. Instead, it focuses on general characteristics and its substantial equivalence to a predicate device.

2. Sample Size Used for the Test Set and Data Provenance

The document does not specify a sample size for a test set, nor does it mention any specific test set data provenance (country of origin, retrospective/prospective). The evaluation appears to be based on software validation and a comparison to a predicate device rather than a clinical performance study with a patient dataset.

3. Number of Experts Used to Establish the Ground Truth for the Test Set and Qualifications of Those Experts

This information is not provided in the document. As there's no mention of a clinical test set requiring ground truth, the number or qualifications of experts are not relevant to the presented information.

4. Adjudication Method for the Test Set

This information is not provided in the document. Similar to point 3, without a defined test set requiring ground truth, an adjudication method is not discussed.

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

There is no mention of an MRMC comparative effectiveness study being conducted. The device (ImageSVR PACS) is a general PACS system for image management and display, not an AI-assisted diagnostic tool. Therefore, an effect size of human readers improving with/without AI assistance is not applicable here.

6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done

This information is not provided. The ImageSVR PACS is described as a system for image manipulation, management, and display, with a physician interpreting the images. There is no indication of a standalone algorithm performance evaluation in a diagnostic context.

7. The Type of Ground Truth Used (expert consensus, pathology, outcomes data, etc.)

The document does not describe the use of any specific ground truth type in the context of a clinical performance study. The evaluation focuses on software validation and substantial equivalence.

8. The Sample Size for the Training Set

There is no mention of a training set sample size. The ImageSVR PACS is a software system for image management and display, not a machine learning or AI-based diagnostic tool that would typically require a training set for model development.

9. How the Ground Truth for the Training Set was Established

This information is not provided as there is no mention of a training set or its associated ground truth in the context of this device.

Summary of Device Evaluation Approach:

The documentation provided for the Jaguar Technology Limited ImageSVR PACS focuses on demonstrating:

• Software Validation: Confirmation that the software functions as intended and that risks and potential hazards are classified as "Minor."
• Substantial Equivalence: A direct comparison to a legally marketed predicate device (Taiwan Electronics Data Processing Corporation Smart PACS, K022710) based on shared working principles and technologies, with differences attributed to feature design rather than safety or effectiveness.
• General Performance Characteristics: Describing its capabilities in managing, archiving, retrieving, and displaying medical images across various modalities, especially noting its handling of mammography images in full fidelity.

This type of submission is typical for PACS systems that primarily facilitate the viewing and management of medical images rather than performing automated diagnostic interpretations. Therefore, the detailed studies and ground truth methodologies associated with AI-driven diagnostic devices are not present.

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