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Centricity Universal Viewer is a device that displays medical images and data from various imaging sources, and from other healthcare information sources. Medical images and data can be displayed, communicated, stored, and processed.

Typical users of this system are authorized healthcare professionals.

Centricity Universal Viewer is intended to assist in the viewing, analysis, diagnostic interpretation, and sharing of images and other information.

Mammography images may only be interpreted using a monitor compliant with requirements of local regulations and must meet other technical specifications reviewed and accepted by the local regulatory agencies.

Contraindications:

Centricity Universal Viewer is contraindicated for the use of lossy compressed mammographic images. Lossy compressed mammographic images and digitized film screen images must not be reviewed for primary image interpretations.

Centricity Universal Viewer is an Internet based medical image display and interpretation software product that is part of a picture archiving and communications system that assists radiologists and cardiologists in their diagnostic workflows. It provides users with capabilities relating to the acceptance, transfer, display, storage, and digital processing of medical images (including digital mammograms).

Centricity Universal Viewer provides APIs (Application Program Interfaces) to integrate with third-party medical devices and non-medical devices, which include integration with Tomtec-Arena™(K132544) for advanced cardiology applications.

Centricity Universal Viewer supports DICOM SOP classes to access and manage medical imaging studies from , Computed Tomography (CT), Magnetic Resonance (MR), Ultrasound (US), Nuclear Medicine (NM), Computerized Radiography (CR), Digital mammography (MG), Digital X-ray (DX), Positron Emission Tomography (PET/PT), X-Ray Angioaraphy (XA), Diaital 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 Universal Viewer is not intended for the diagnosis of digital pathology images.

Centricity Universal Viewer is designed to be deployed over conventional TCP/IP networking infrastructure available in most healthcare organizations and utilizes commercially available computer platforms and operating systems.

The system does not produce any original medical images. All images located on the Centricity Universal Viewer have been received from DICOM compliant modalities and/or image acquisition systems.

The provided text is a 510(k) Summary for the GE Healthcare Centricity Universal Viewer. This document demonstrates substantial equivalence to a predicate device, rather than proving that the device meets specific acceptance criteria through a clinical study.

Therefore, many of the requested sections about acceptance criteria, study details, ground truth, and expert involvement are not applicable or cannot be extracted from this type of regulatory submission.

However, I can provide information based on what is available in the document:

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

This document does not describe specific numerical acceptance criteria or performance metrics for the Centricity Universal Viewer in the way one would find in a clinical performance study for an AI algorithm. Instead, it focuses on software verification and validation activities to ensure functional equivalence to a predicate device.

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

The document does not specify a "test set" in the context of a clinical performance study with patient data. The testing mentioned (unit, integration, system, simulated use) refers to software engineering verification and validation activities. Therefore, details about sample size, data provenance, or retrospective/prospective nature are not available.

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. The document describes software verification and validation, not a clinical study where ground truth would be established by experts.

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

Not applicable. The document describes software verification and validation, not a clinical study requiring ground truth adjudication.

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

No MRMC comparative effectiveness study is mentioned in this document. The device is a Picture Archiving and Communication System (PACS) viewer, not an AI-assisted diagnostic tool in the sense of providing specific interpretive recommendations. Its purpose is to display and process images for human interpretation.

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

This is not an AI algorithm acting in a standalone capacity. It is an image display and processing system intended for human-in-the-loop diagnostic interpretation.

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

Not applicable. Ground truth in the context of clinical performance evaluation is not discussed. Software validation focused on ensuring the system performs as designed and intended.

8. The sample size for the training set

Not applicable. This document describes a PACS viewer, not a machine learning or AI algorithm that requires a "training set" of data in the common sense.

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

Not applicable, as there is no "training set" referenced for an AI/ML algorithm within this document.

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Indications for use of TomTec-Arena software are quantification and reporting of cardiovascular, fetal, and abdominal structures and function of patients with suspected disease to support the physicians in the diagnosis.

TomTec-Arena™ is a clinical software package for reviewing, quantifying and reporting digital medical data. The software is compatible with different TomTec Image-Arena™ platforms and TomTec-Arena Server®, their derivatives or third party platforms.

Platforms enhance the workflow by providing the database, import, export and other services. All analyzed data and images will be transferred to the platform for archiving, reporting and statistical quantification purposes.

TomTec-Arena™ TTA2 consists of the following optional modules:

• Image-Com
• 4D LV-Analysis and 4D LV-Function
• 4D RV-Function
• 4D Cardio-View
• 4D MV-Assessment
• Echo-Com
• 2D Cardiac-Performance Analysis
• 2D Cardiac-Performance Analysis MR
• 4D Sono-Scan
• Reporting
• Worksheet
• TomTec-Arena Client

The provided text does not contain detailed acceptance criteria or a study that explicitly proves the device meets those criteria. Instead, it describes a substantial equivalence submission for the TomTec Arena TTA2, a picture archiving and communications system.

The document focuses on demonstrating that the new device is substantially equivalent to previously marketed predicate devices (TomTec-Arena 1.0 and Image-Arena 4.5). It outlines changes made to the device, primarily bug fixes, operability enhancements, and feature changes (repackaging or new appearance of existing technology).

It explicitly states: "Substantial equivalence determination of this subject device was not based on clinical data or studies." This means that a detailed clinical performance study with defined acceptance criteria for the device's diagnostic performance was not conducted as part of this submission for determining substantial equivalence.

While non-clinical performance data (software testing and validation) was performed according to internal company procedures, the acceptance criteria for this testing are not explicitly stated in a quantifiable manner within the provided text, beyond "expected results and acceptance (pass/fail) criteria have been defined in all test protocols."

Therefore, most of the requested information regarding acceptance criteria, study details, sample sizes, expert qualifications, and ground truth establishment cannot be extracted from the provided text.

Here is a summary of what can be extracted:

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

   • Acceptance Criteria: Not explicitly stated in quantifiable terms for the device's diagnostic performance. The document mentions "expected results and acceptance (pass/fail) criteria have been defined in all test protocols" for internal software testing.
   • Reported Device Performance:
     • All automated tests were reviewed and passed.
     • Feature complete test completed without deviations.
     • Functional tests are completed.
     • Measurement verification is completed without deviations.
     • All non-verified bugs have been evaluated and are rated as minor deviations and deferred to the next release.
     • The overall product concept was clinically accepted and supports the conclusion that the device is as safe as effective, and performs as well as or better than the predicate device.
     • The Risk-Benefit Assessment concludes that the benefit is superior to the risk, and the risk is low.
     • The data are sufficient to demonstrate compliance with essential requirements covering safety and performance.
     • The claims made in the device labeling are substantiated by clinical data (via literature review).

2. Sample size used for the test set and the data provenance: Not applicable, as no clinical study with a test set was detailed. Non-clinical software testing involved various test cases but the sample size (number of test cases) and their provenance are not specified.

3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts: Not applicable, as no clinical study with a test set requiring expert ground truth was detailed.

4. Adjudication method for the test set: Not applicable.

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 applicable. The device is a "Picture archiving and communications system" and "Image Review and Quantification Software," not explicitly an AI-assisted diagnostic device, and no MRMC study was mentioned.

6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done: Not applicable. The focus is on software functionality and equivalence to predicate devices, not AI algorithm performance.

7. The type of ground truth used (expert consensus, pathology, outcomes data, etc.): For non-clinical software testing, the "ground truth" would be the expected output of the software functions based on established specifications and requirements. For the "clinical acceptance" mentioned, it refers to a literature review, implying published clinical data served as the basis for concluding safety and effectiveness relative to predicate devices and general medical standards.

8. The sample size for the training set: Not applicable, as this is not an AI/ML device with a training set.

9. How the ground truth for the training set was established: Not applicable.

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