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The SIGNA Prime Elite is a whole body magnetic resonance scanner designed to support high signal-to-noise ratio, and short scan times. It is indicated for use as a diagnostic imaging device to produce axial, sagittal, coronal, and oblique images, spectroscopic images, parametric maps, and/or spectra, dynamic images of the structures and/or functions of the entire body, including, but not limited to, head, neck, heart, abdomen, pelvis, joints, prostate, blood vessels, and musculoskeletal regions of the body.

Depending on the region of interest being imaged, contrast agents may be used. The images produced by SIGNA Prime Elite reflect the spatial distribution or molecular environment of nuclei exhibiting magnetic resonance.

These images and/or spectra when interpreted by a trained physician yield information that may assist in diagnosis.

SIGNA Prime Elite is a whole body magnetic resonance scanner designed to support high resolution, high signal-to-noise ratio, and short scan time. The system uses a combination of time-varying magnet fields (Gradients) and RF transmissions to obtain information regarding the density and position of elements exhibiting magnetic resonance. The system can image in the sagittal, coronal, axial, oblique, and double oblique planes, using various pulse sequences, imaging techniques and reconstruction algorithms. The system features a 1.5T superconducting magnet with 60 cm bore size. The system is designed to conform to NEMA DICOM standards (Digital Imaging and Communications in Medicine).

The document does not provide a table of acceptance criteria and reported device performance. It focuses on demonstrating substantial equivalence to a predicate device rather than presenting specific quantitative performance metrics against pre-defined acceptance criteria.

Here's an analysis of the provided information concerning acceptance criteria and study details:

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

The document does not contain a specific table outlining quantitative acceptance criteria and corresponding reported device performance metrics. It indicates that the SIGNA Prime Elite's image quality performance was compared to the predicate device through bench and clinical testing and found to be "substantially equivalent."

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 states: "The subject of this premarket submission, the SIGNA Prime Elite, did not require clinical studies to support substantial equivalence. Sample clinical images have been included in this submission."

Therefore, there is no formal test set sample size mentioned for a specific clinical performance study. The "sample clinical images" are used to demonstrate acceptable diagnostic image performance, but details about their sample size, provenance (country of origin), or whether they are retrospective or prospective are not provided.

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)

Since no formal clinical study with a defined test set and ground truth establishment is described, this information is not provided. The document mentions that images "when interpreted by a trained physician yield information that may assist in diagnosis," but it doesn't specify expert review for a test set.

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

As there is no formal test set described for a clinical performance study, an adjudication method is not applicable and not mentioned.

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

The document states that the SIGNA Prime Elite is a "whole body magnetic resonance scanner." There is no mention of AI assistance or a multi-reader multi-case (MRMC) comparative effectiveness study comparing human readers with and without AI assistance. The submission is for an imaging device, not an AI-powered diagnostic tool.

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

This question is not applicable as the device is a magnetic resonance scanner, not an algorithm that operates standalone without human interpretation.

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

Given that clinical studies were not required and only "sample clinical images" were included to demonstrate acceptable diagnostic image performance, there is no mention of a formally established ground truth type (e.g., expert consensus, pathology, outcomes data) for a test set. The images are expected to be interpreted by a "trained physician."

8. The sample size for the training set

The document describes the SIGNA Prime Elite as a new 1.5T MR system. It is a hardware device with associated software, not a machine learning model. Therefore, the concept of a "training set" in the context of machine learning is not applicable and not mentioned.

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

As the device is an MR scanner and not an AI/ML model requiring a training set, this information is not applicable and not provided.

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The SIGNA Prime is a whole body magnetic resonance scanner designed to support high resolution, high signal-to-noise ratio, and short scan times. It is indicated for use as a diagnostic imaging device to produce axial, sagittal, coronal, and oblique images, spectroscopic images, parametric maps, and/or spectra, dynamic images of the structures and/or functions of the entire body, including, but not limited to, head, neck, TMI, spine, abdomen, pelvis, joints, prostate, blood vessels, and musculoskeletal regions of the body.
Depending on the region of interest being imaged, contrast agents may be used. The images produced by SIGNA Prime reflect the spatial distribution or molecular environment of nuclei exhibiting magnetic resonance.
These images and/or spectra when interpreted by a trained physician yield information that may assist in diagnosis.

SIGNA™ Prime is a whole body magnetic resonance scanner designed to support high resolution, high signal to-noise ratio, and short scan times. The systems use a combination of time-varying magnet fields (Gradients) and RF transmissions to obtain information regarding the density and position of elements exhibiting magnetic resonance. The system can image in the sagittal, coronal, axial, oblique, and oblique planes, using various pulse sequences, imaging techniques and reconstruction algorithms. The system features a 1.5T superconducting magnet with 60cm bore size. The system is designed to conform to NEMA DICOM standards (Digital Imaging and Communications in Medicine).

The provided text is a 510(k) summary for the GE Healthcare SIGNA Prime magnetic resonance diagnostic device. The summary states that the device did not require clinical studies to support substantial equivalence and instead relied on non-clinical tests and sample clinical images to demonstrate acceptable diagnostic image performance.

Therefore, the study details requested cannot be fully provided as a formal comparative effectiveness study or standalone performance study as typically understood for AI/CADe devices was not conducted with predefined acceptance criteria for diagnostic metrics.

Here's a breakdown of the available information:

1. Table of Acceptance Criteria and Reported Device Performance:

No specific numerical acceptance criteria for diagnostic performance (e.g., sensitivity, specificity, AUC) are provided in the document. The general acceptance criterion was that the image quality of the SIGNA Prime is "substantially equivalent" to that of the predicate device (SIGNA Creator, K143251).

2. Sample size used for the test set and the data provenance:

• Sample Size: The document mentions "Sample clinical images have been included in this submission" but does not specify the number of images or cases used as a "test set."
• Data Provenance: Not specified. It's unclear if these were retrospective or prospective, or the country of origin.

3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts:

• The document states that "These images and/or spectra when interpreted by a trained physician yield information that may assist in diagnosis." However, it does not specify the number or qualifications of experts who interpreted the "sample clinical images" for the purpose of demonstrating substantial equivalence. The mechanism for establishing ground truth for these sample images is not detailed.

4. Adjudication method for the test set:

• Not specified. Given that a formal clinical study with a detailed ground truth process is not described, an adjudication method for a test set is not mentioned.

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. The document explicitly states: "The subject of this premarket submission, the SIGNA™ Prime, did not require clinical studies to support substantial equivalence." Therefore, an MRMC comparative effectiveness study involving human readers with and without AI assistance was not performed or reported.

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

• The SIGNA Prime is a magnetic resonance scanner, not an AI algorithm or CADe device. Therefore, the concept of "standalone (algorithm only without human-in-the-loop performance)" is not applicable in this context. The device itself produces images for human interpretation.

7. The type of ground truth used:

• For the "sample clinical images" used to demonstrate acceptable diagnostic image performance, the ground truth is implicitly expert interpretation by a "trained physician" as stated in the Indications for Use. However, the exact methodology for establishing this ground truth for the purpose of the submission is not detailed (e.g., expert consensus vs. pathology vs. outcomes data).

8. The sample size for the training set:

• Not applicable. The SIGNA Prime is a hardware device (MRI scanner) with associated software, not an AI/ML algorithm that is "trained" on a dataset in the typical sense. While the software platform and reconstruction algorithms were likely developed and refined, the document does not describe a "training set" in the context of an AI algorithm evaluation.

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

• Not applicable. (See point 8).

Summary of the Study:

The K211980 submission for the SIGNA Prime focused on demonstrating substantial equivalence to a predicate device (SIGNA Creator, K143251). This was primarily achieved through:

• Non-clinical tests: Compliance with various electrical, safety, software, and biocompatibility standards (e.g., ANSI/AAMI ES60601-1, IEC 60601-1-2, IEC 60601-2-33, IEC 62304, IEC 60601-1-6, IEC 62366-1, ISO 10993-1, NEMA MS, NEMA PS3 DICOM).
• Risk management activities: Including risk analysis, design reviews, and various levels of testing (unit, integration, performance, simulated use).
• Sample clinical images: These images were provided to demonstrate acceptable diagnostic performance and visual equivalence to the predicate device. However, the specific methodology for selecting, evaluating, or establishing ground truth for these sample images is not detailed, nor are any quantitative metrics provided for their performance.

The submission explicitly states that clinical studies were not required to support substantial equivalence. Therefore, the detailed information typically sought for the evaluation of AI/CADe devices (such as sample sizes for test/training, expert qualifications, adjudication methods, or MRMC study results) is not present in this document.

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