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The Discovery MR750 3.0T, Discovery MR450 1.5T, Discovery MR750w 3.0T and the Optima MR450w 1.5T systems are whole body magnetic resonance scanners 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, TMJ, spine, breast, 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 the Discovery MR750 3.0T, Discovery MR450 1.5T, Discovery MR750w 3.0T and the Optima MR450w 1.5T systems 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.

The Discovery MR750 3.0T, Discovery MR450 1.5T, Discovery MR750w 3.0T and the Optima MR450w 1.5T are whole body magnetic resonance scanners designed to support high resolution, high signal-to-noise ratio, and short scan times. The systems feature a superconducting magnet operating at 1.5 Tesla or 3.0 Telsa. The data acquisition system accommodates up to 32 independent receive channels in various increments and multiple independent coil elements per channel during a single acquisition series. The system uses a combination of time-varying magnetic 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 and reconstruction algorithms.

This Discovery MR750 3.0T, Discovery MR450 1.5T, Discovery MR750w 3.0T, and the Optima MR450w 1.5T systems are designed to conform to NEMA DICOM standards (Digital Imaging and Communications in Medicine).

Modification for which this Special 510(k) is being filed is a Training PC which was introduced in the DV25.1 program. This modification allows users to train new technologist, optimize protocols, and evaluate pulse sequence development in the off-line environment.

The provided text is a 510(k) summary for a GE Medical Systems device, the Discovery MR750, Discovery MR450, Discovery MR750w, and Optima MR450w MR systems. The submission is for a modification to the existing predicate devices, specifically the introduction of a "Training PC."

Therefore, the document does not contain information about a study proving the device meets acceptance criteria for its core diagnostic function. Instead, it focuses on demonstrating substantial equivalence for the new modification (the Training PC) to the predicate devices.

Here's a breakdown of the requested information based on the provided text, and where it is missing for a typical medical device performance study:

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

• Missing. The document does not describe specific acceptance criteria for diagnostic performance or reported performance metrics of the MRI system's imaging capabilities. The modification is for a "Training PC," and the "performance" described relates to compliance with standards and quality assurance processes for this feature.

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

• Missing. No clinical or image-based test set information is provided as the submission is not for a new diagnostic device but a modification (Training PC).

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)

• Missing. No information on experts or ground truth establishment is provided as there is no diagnostic image test set described.

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

• Missing. No information on adjudication is provided.

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

• Missing. No MRMC study was done, as this submission is for a modification to an existing MRI system's training component, not a new AI-assisted diagnostic tool.

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

• Missing. Not applicable. This is not an algorithm-only device.

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

• Missing. No ground truth data is described.

8. The sample size for the training set

• Missing. No training set information is provided, as the submission concerns a "Training PC" (a computer for user training) and not an AI algorithm's training data.

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

• Missing. Not applicable.

Information Present in the Document (Related to the "Training PC" Modification):

The document states:

• Device Description (Modification): "Modification for which this Special 510(k) is being filed is a Training PC which was introduced in the DV25.1 program. This modification allows users to train new technologist, optimize protocols, and evaluate pulse sequence development in the off-line environment." (Page 4)
• Non-Clinical Tests: The system (with the Training PC addition) "complies with the NEMA standards, including NEMA PS3.1-3.20 for DICOM conformance." (Page 5)
• Quality Assurance Measures applied to the development of the system with the addition of the new feature training PC:
  • Risk Analysis
  • Requirements Reviews
  • Design Reviews
  • Testing on unit level (Module verification)
  • Integration testing (System verification)
  • Simulated use testing (Validation) (Page 5)
• Clinical Tests: "The modification that prompted this submission did not require clinical testing." (Page 5)
• Conclusion: "GE Healthcare considers the Discovery MR750 3.0T, Discovery MR450 1.5T, Discovery MR750w 3.0T, and Optima MR450w 1.5T to be as safe, as effective, and performance is substantially equivalent to the predicate device(s)." (Page 5)

In summary, this document is a 510(k) for a minor modification (a training component) to an already cleared MRI system. It relies heavily on non-clinical testing showing compliance with standards and internal quality assurance processes to demonstrate substantial equivalence for the modification, rather than providing diagnostic performance data for the core MRI system or its "Training PC" feature.

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The Discovery MR750 3.0T, Discovery MR450 1.5T, Discovery MR750w 3.0T and the Optima MR450w 1.5T systems are whole body magnetic resonance scanners 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, coronal, and oblique images, spectroscopic images, parametric maps, and or spectra, dynamic images of the structures of the entire body, including, but not limited to, head, neck, TMJ, spine, breast, heart, abdomen, pelvis, 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 the Discovery MR750 3.0T, Discovery MR750w 3.0T and the Optima MR450w I.ST systems reflect the spaial 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.

The Discovery MR750 3.0T. Discovery MR450 1.5T, Discovery MR750w 3.0T and the Optima MR450w 1.5T Systems are whole body magnetic resonance scanners designed to support high resolution, high signal-to-noise ratio, and short scan times. The Systems each feature a superconducting magnet. The data acquisition system accommodates up to 32 independent receive channels in various increments and multiple independent coil elements per channel during a single acquisition series. Each system uses a combination of time-varying magnetic fields (gradients) and RF transmissions to obtain information regarding the density and position of elements exhibiting magnetic resonance. Each system can image in the sagittal, coronal, axial, oblique, and double oblique planes, using various pulse sequences and reconstruction algorithms.

The DV24 release is introducing new software features onto these existing MR Systems. There are also hardware modifications to the GEM configurations for Silenz compatibility. The Silenz feature used to reduce the acoustic noise generated during an MR examination is only available on the Optima MR450w GEM and Discovery MR750w GEM configurations.

The Discovery MR750 3.0T. Discovery MR450 1.5T. Discovery MR750w 3.0T and the Optima MR450w 1.5T Systems are designed to conform to NEMA DICOM standards (Digital Imaging and Communications in Medicine).

The GE Healthcare Discovery MR750 3.0T, Discovery MR450 1.5T, Discovery MR750w 3.0T, and Optima MR450w 1.5T Magnetic Resonance Diagnostic Devices did not undergo a study with specific acceptance criteria related to new AI features or performance metrics. This is because the submission (K132376) primarily focused on the introduction of new software features (DV24 release) and hardware modifications for Silenz compatibility on existing MR systems.

The submission states: "The subject of this premarket submission... did not require external clinical studies to support substantial equivalence." Instead, the focus was on demonstrating that the updated systems maintain the same imaging performance as their predicate devices.

Here's a breakdown of the information based on the provided document, addressing the requested points where applicable, and noting where the information is not provided because it pertains to an AI/performance study that was not conducted:

1. Table of Acceptance Criteria and Reported Device Performance

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

• Sample Size: Not explicitly stated for a dedicated test set against specific performance criteria. "Internal scans were conducted as part of validation for workflow and image quality for the addition of the new features." The exact number of scans is not provided.
• Data Provenance: "Internal scans" suggests the data was generated within GE Healthcare. The country of origin and whether it was retrospective or prospective is not specified.

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

• This information is not provided. The study did not involve establishing a ground truth by experts in the context of a comparative performance study. The focus was on maintaining existing performance standards.

4. Adjudication Method for the Test Set

• Not applicable as a traditional adjudication method for a performance study was not described.

5. If a Multi Reader Multi Case (MRMC) Comparative Effectiveness Study Was Done, and the Effect Size

• No, a Multi Reader Multi Case (MRMC) comparative effectiveness study was not described or performed for this submission. The submission explicitly states, "The subject of this premarket submission... did not require external clinical studies to support substantial equivalence."

6. If a Standalone (i.e. algorithm only without human-in-the-loop performance) Was Done

• Not applicable. This submission relates to physical MR imaging devices and software updates, not a standalone AI algorithm with specific performance metrics.

7. The Type of Ground Truth Used

• No explicit "ground truth" as typically defined for AI performance studies was established. The "ground truth" was implicitly the existing imaging performance of the predicate devices. The internal validation aimed to ensure the new features did not degrade this established performance.

8. The Sample Size for the Training Set

• This information is not applicable. The document does not describe the development of a machine learning model with a separate training set. The "new software features" refer to changes in the MR system's operational software, not an AI algorithm trained on a dataset.

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

• Not applicable, as there was no described training set for an AI algorithm.

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