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Centricity PACS-IW with Universal viewer is a software only product that is part of a Picture Archiving and Communication System (PACS) medical device. Centricity PACS-IW with Universal Viewer is a device that displays medical images (including mammograms) and data from various imaging sources. Images and data can be viewed, communicated, processed and displayed within the system or across computer networks at distributed locations. Lossy compressed mammographic images and digitized film screen images must not be reviewed for primary image interpretations. Mammographic images may only be interpreted using an FDA approved monitor that offers at least 5 Megapixel resolution and meet other technical specifications reviewed and accepted by the FDA. Typical users of this system are trained professionals, including but not limited to radiologists, physicians, nurses, medical technicians, and assistants.

Centricity PACS-IW with Universal Viewer is an Internet based medical image display and interpretation software product that is part of a picture archiving and communications system. It provides users with capabilities relating to the acceptance, transfer, display, storage, and digital processing of medical images (including digital mammograms). Centricity PACS-IW with Universal Viewer includes features to access and manage medical imaging studies from Computed Tomography (CT), Magnetic Resonance (MR), Ultrasound (US), Nuclear medicine (NM). Computerized radiography (CR). Diaital mammography (MG),Digital x-ray (DX), Positron Emission Tomography (PET/PT), X-Ray Angiography (XA), Digital Intra-oral X-Ray (IO), Radiofluoroscopic x-ray (RF), Secondary Capture Images (SC), Visible Light (VL) Endoscopic, Microscopic and Photographic Image Storage, Slide Coordinates Microscopic Image Storage, Presentation States (PS), Key Image Notes (KIN) and other DICOM imaging modalities. Centricity PACS-IW with Universal Viewer is designed to be deployed over conventional TCP/IP networking infrastructure available in in most healthcare organizations and utilizes commercially available computer platforms and operating systems. The system does not produce any origing| medical images. All images located on the Centricity PACS, PACS-IW, and Enterprise Archive systems have been received from DICOM compliant modalities and/or image acquisition systems. The Universal Viewer Zero Foot Print (ZFP) clinical viewer is an optional viewer which allows trained professionals to display and manipulate images stored in Centricity Enterprise Archive or other DICOM archive devices. These trained professionals include but are not limited to physicians, radiologists, nurses, medical technicians, and assistants. The Universal Viewer Zero Foot Print option is not intended for primary diagnosis.

Here's a breakdown of the acceptance criteria and study information for the Centricity PACS-IW with Universal Viewer, based on the provided text:

1. Table of Acceptance Criteria and Reported Device Performance

The provided document does not contain a specific table of acceptance criteria or quantified device performance metrics. Instead, it states that the device did not require clinical studies. The "acceptance" in this context refers to demonstrating substantial equivalence to a predicate device through non-clinical means.

The "performance" is implicitly deemed acceptable because the device leverages the same fundamental scientific technology as its predicate and the modifications are primarily related to user interface, integration, and minor enhancements, which were validated through non-clinical testing.

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

• Sample Size for Test Set: Not applicable. The document explicitly states: "The subject of this premarket notification submission, Centricity PACS-IW with Universal Viewer, did not require clinical studies to support substantial equivalence."
• Data Provenance: Not applicable, as no clinical studies were performed. The non-clinical testing data provenance is not specified (e.g., country of origin).

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

Not applicable, as no clinical studies were performed and no separate "test set" with expert-established ground truth for performance evaluation is mentioned beyond internal verification and validation.

4. Adjudication Method for the Test Set

Not applicable, as no clinical studies or a separate "test set" requiring adjudication for ground truth were performed.

5. Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study

No, a Multi-Reader Multi-Case (MRMC) comparative effectiveness study was not done. The document explicitly states that clinical studies were not required.

6. Standalone Performance Study

No, a standalone (algorithm only without human-in-the-loop performance) study was not done or at least not described as a separate study for the purpose of demonstrating device performance in this submission. The device is a Picture Archiving and Communication System (PACS) component, intended to be used by human professionals (physicians, radiologists, etc.). Its performance is primarily assessed through its functionality, integration, and display capabilities as part of a human workflow, rather than as a standalone diagnostic algorithm.

7. Type of Ground Truth Used

Not applicable in the context of clinical performance evaluation. For non-clinical verification and validation testing, the "ground truth" would have been defined by the device's functional requirements and design specifications.

8. Sample Size for the Training Set

Not applicable. The Centricity PACS-IW with Universal Viewer is a software product for image DISPLAY and 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

Not applicable, as there is no "training set" for this type of software device.

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Centricity PACS-IW by GE Healthcare is a device that receives medical images (including mammograms) and data from various imaging sources. Images and data can be stored, communicated, processed and displayed within the system or across computer networks at distributed locations.

Lossy compressed mammographic images and digitized film screen images must not be reviewed for primary image interpretations. Mammographic images may only be interpreted using an FDA-approved monitor that offers at least five Mpixel resolution and meets other technical specifications reviewed and accepted by FDA.

Centricity PACS-IW is an internet based software picture archiving and communications system that provides users with capabilities relating to the acceptance, transfer, display, storage, and digital processing of medical images (including digital mammograms).

Centricity PACS-IW includes features to access and manage medical imaging studies and data from computed tomography (CT), magnetic resonance (MR), ultrasound (US), nuclear medicine (NM), computerized radiography (CR), digital radiography (DR), digital mammoqraphy (MG), digital x-ray (DX), special procedures and Interventional radiography (XA), PET/CT scan (PT), and other imaging modalities.

Centricity PACS-IW is designed to be deploved over conventional TCP/IP networking infrastructure available in most healthcare organizations utilizing commercially available computer hardware platforms and operating systems. The system does not produce any original medical images. All images located in the Centricity PACS-IW have been received from DICOM compliant modalities and/or systems.

Here's an analysis of the provided text regarding the acceptance criteria and study information for the Centricity PACS-IW device:

1. Table of Acceptance Criteria and Reported Device Performance

The provided 510(k) summary does not establish specific quantitative acceptance criteria or provide detailed numerical performance metrics for the Centricity PACS-IW. Instead, it relies on substantial equivalence to a predicate device and verification/validation testing.

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

The document explicitly states: "The subject of this premarket notification submission, Centricity PACS-IW, did not require clinical studies to support substantial equivalence."

Therefore, there is no clinical test set, sample size, or data provenance information provided for an evaluation of the device's diagnostic performance on medical images. The testing focused on software verification and validation.

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

Since no clinical test set was used for performance evaluation, no experts were involved in establishing ground truth for such a set.

4. Adjudication Method for the Test Set

Not applicable, as no clinical test set was used.

5. Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study

No. The document explicitly states that clinical studies were not required. There is no mention of an MRMC study or an effect size for human readers with and without AI assistance.

6. Standalone (Algorithm Only Without Human-in-the-Loop Performance) Study

No. The device is a PACS system, designed for human use in interpreting images. Its "performance" is primarily related to its ability to store, communicate, process, and display images reliably, rather than providing automated diagnoses.

7. Type of Ground Truth Used

For the software verification and validation testing, the "ground truth" would have been the expected behavior and outcomes defined by the software requirements and design specifications. For example, for a functional test, the ground truth would be that a specific image should display correctly or that a data transfer should complete without error.

8. Sample Size for the Training Set

Not applicable. This device is a PACS system, not an AI/ML algorithm that requires a "training set" in the conventional sense of machine learning for diagnostic inference. The "training" here refers to software development and testing cycles, not data-driven model training.

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

Not applicable, as there is no training set in the context of AI/ML for diagnostic inference. The development process likely involved thorough software engineering practices where expected behaviors and outputs were defined by system architects and engineers.

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