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ZeTTA PACS is intended for use in hospitals and diagnostic centers as a PACS to receive, store, retrieve, and display medical images from DICOM-compliant modalities, including CT, MRI, ultrasound, and radiographic devices. The system enables healthcare professionals to securely access and analyze diagnostic images over hospital networks.

Typical users of ZeTTA PACS include trained professionals such as physicians, radiologists, and medical technicians.

For mammography, only preprocessed DICOM for-presentation images can be interpreted for primary image diagnosis in mammography. Lossy compressed mammographic images and digitized film screen images must not be reviewed for primary image interpretations. Mammographic images may only be interpreted using a monitor that meets technical specifications identified by FDA.

ZeTTA PACS is a Windows-based Picture Archiving and Communication System (PACS) used in hospitals and diagnostic centers to receive, store, retrieve, distribute, and display medical images from various DICOMcompliant modalities, such as CT, MRI, ultrasound, and radiographic devices. This system supports the DICOM 3.0 standard and is designed to allow healthcare professionals to securely access and manage medical images over hospital networks.

ZeTTA PACS supports more than two high-resolution monitors to facilitate efficient image interpretation. It provides advanced layout options, multi-worklist functionality, and DICOM GSPS (Grayscale Presentation State), enhancing diagnostic and analytical efficiency. Additionally, it offers image analysis tools such as ruler and angle, along with image manipulation features like windowing and zoom, enabling healthcare professionals to perform more accurate analyses.

ZeTTA PACS integrates multiple medical imaging sources into a centralized solution, ensuring secure storage and management. It is useful across various medical fields such as radiology, and neurology. However, it does not provide diagnostic decision-making functions, and all diagnoses, treatments, and prescriptions must be made by qualified medical professionals.

Furthermore, ZeTTA PACS does not support mobile devices and is designed for use in network-based desktop and workstation environments, ensuring stable and secure management of medical images.

The provided document describes the ZeTTA PACS, a medical image management and processing system, and its substantial equivalence to a predicate device. However, the document does not contain an acceptance criteria table or a detailed study proving the device meets specific acceptance criteria in the manner requested.

The "Determination of Substantial Equivalence" section in the K241694 submission (page 6-7) compares the proposed device (ZeTTA PACS) to the predicate device (Infinitt PACS 7.0) based on various features and functionalities. This comparison is used to argue for substantial equivalence, not to demonstrate performance against pre-defined quantitative acceptance criteria for things like diagnostic accuracy or sensitivity/specificity.

Here's an analysis based on the information provided, highlighting what is present and what is missing:

1. A table of acceptance criteria and the reported device performance

• Not present in the requested format. The document provides a detailed comparison table between the proposed device and its predicate, outlining functionalities like worklist modes, study list features, image display options, and output capabilities. It consistently concludes "Same" for these features, indicating functional equivalence, but it does not present quantitative performance metrics against specific acceptance criteria.

2. Sample size used for the test set and the data provenance (e.g. country of origin of the data, retrospective or prospective)

• Not present. The document mentions "Performance Testing" was conducted, confirming that "ZeTTA PACS meets all performance test criteria and that all functions work without errors." However, it does not specify the sample size of images or cases used for this testing, nor does it provide details about the data provenance (e.g., country of origin, retrospective/prospective nature).

3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts (e.g. radiologist with 10 years of experience)

• Not applicable/Not present. Since a clinical performance study with an explicit ground truth assessment by experts is not described for the ZeTTA PACS itself, this information is not provided. The device is a PACS system for managing and viewing images, not an AI-powered diagnostic tool that produces interpretations.

4. Adjudication method (e.g. 2+1, 3+1, none) for the test set

• Not applicable/Not present. For the same reasons as point 3, an adjudication method for a test set's ground truth is not relevant or provided in this context.

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

• Not present. The device described (ZeTTA PACS) is a Picture Archiving and Communication System; it does not explicitly feature AI-assisted diagnostic capabilities. Therefore, an MRMC study comparing human readers with and without AI assistance is not described.

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

• Not applicable/Not present. ZeTTA PACS is a software system for image management and display, not a standalone diagnostic algorithm. Its function is to facilitate human interpretation, not to provide independent diagnostic outputs.

7. The type of ground truth used (expert consensus, pathology, outcomes data, etc)

• Not applicable/Not present. As this is a PACS system and not an AI diagnostic device, the concept of "ground truth" for diagnostic accuracy is not directly applicable to its stated function in this submission. The tests performed were likely functional and performance tests to ensure the system handles images correctly, displays them accurately, and supports its specified features.

8. The sample size for the training set

• Not applicable/Not present. ZeTTA PACS is not described as an AI/ML-driven device requiring a training set in the way a diagnostic algorithm would. It is a traditional software system for image management.

9. How the ground truth for the training set was established

• Not applicable/Not present. For the same reason as point 8, this information is not relevant or provided.

Summary of what is available regarding "acceptance criteria" and "study":

The document focuses on demonstrating substantial equivalence to an existing predicate device (Infinitt PACS 7.0) based on functional and technical characteristics.

• "Acceptance Criteria" (Implicit): The implicit acceptance criteria appear to be the functionalities and performance of the predicate device, or general industry standards for PACS systems. The comparison table (pages 6-7) outlines the features of both the proposed and predicate devices, and the consistent "Same" in the "SE Decision" column indicates that the proposed device meets these functional requirements.
• "Study" (Performance Testing): "Performance Testing" was conducted to confirm that "ZeTTA PACS meets all performance test criteria and that all functions work without errors." (Page 9, "Non-Clinical Test Summary"). This implies internal testing was performed to ensure the software's functionality, stability, and adherence to design specifications. However, specific test methodologies, quantitative results, or external validation studies are not detailed.
• No Clinical Studies: The document explicitly states, "No clinical studies were considered necessary and performed." (Page 9, "Clinical Test Summary"). This further confirms that no studies involving human subjects for diagnostic accuracy or effectiveness were part of this submission.

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