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The SIGNA Architect, SIGNA Artist, 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, 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, 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 SIGNA Architect, SIGNA Artist, 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 vield information that may assist in diagnosis.

The Discovery MR750 3.0T, Discovery MR450 1.5T, Discovery MR750w 3.0T, Optima MR450w 1.5T, SIGNA Architect and SIGNA Artist 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 128 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 Discovery MR750 3.0T, Discovery MR450 1.5T, Discovery MR750w 3.0T, Optima MR450w 1.5T, SIGNA Architect. SIGNA Artist systems are designed to conform to NEMA DICOM standards (Digital Imaging and Communications in Medicine).

The original description hasn't changed from predicate devices (K160618), other than reflecting the additional receive channels available.

The modifications to these systems include the MAGIC DWI and CardioMaps software features, delivered via the DV26 program. The proposed software features will be ported over to other GE Healthcare MR systems based on appropriate design controls and evaluation of the change in accordance with FDA's Guidance—Deciding When to Submit a 510(k) for a Change to an Existing Device.

This document describes the premarket notification (510(k)) for GE Medical Systems' SIGNA Architect, SIGNA Artist, Discovery MR750 3.0T, Discovery MR450 1.5T, Discovery MR750w 3.0T and the Optima MR450w 1.5T Magnetic Resonance (MR) diagnostic devices. The submission focuses on the addition of MAGIC DWI (Diffusion-Weighted Imaging) and CardioMaps software features.

Here's an analysis of the acceptance criteria and the study that proves the device meets them, based on the provided text:

1. Table of Acceptance Criteria and Reported Device Performance

The document does not explicitly state specific quantitative acceptance criteria or performance metrics for the MAGIC DWI and CardioMaps software features in a table format. Instead, it indicates that testing was completed with "passing results per the pass/fail criteria defined in the test cases."

Implicit Acceptance Criteria (inferred from the document):

• Safety and Effectiveness: The primary acceptance criterion is that the modified software features (MAGIC DWI and CardioMaps) are "as safe and effective as the predicate" devices and do "not raise different questions of safety and effectiveness."
• Compliance with Standards: The software features must comply with voluntary standards: AAMI/ANSI 62304, AAMI/ANSI ES60601-1, and IEC 60601-2-33.
• Acceptable Performance: Phantom testing for both software features must demonstrate "acceptable performance."

Reported Device Performance:

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

• Test Set Sample Size: The document does not specify a numerical sample size for either the phantom testing or the clinical images. It generically refers to "phantom testing" and "sample clinical images."
• Data Provenance: Not explicitly stated. For phantom testing, it's typically controlled laboratory conditions. For clinical images, it's not mentioned whether they are retrospective or prospective, nor their country of origin.

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

The document does not provide this information.
The summary states that images and/or spectra are interpreted by a "trained physician," but it doesn't detail the number or qualifications of experts involved in establishing ground truth for the specific performance evaluation of the new software features.

4. Adjudication Method for the Test Set

The document does not specify an adjudication method.
It states that "passing results per the pass/fail criteria defined in the test cases" were achieved for phantom testing. For clinical images, it mentions they are "interpreted by a trained physician," implying clinical judgment, but no formal adjudication process (like 2+1 or 3+1) is described for the evaluation presented in this summary.

5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study Was Done

The document does not indicate that an MRMC comparative effectiveness study was performed.
The evaluation relies on compliance with standards, phantom testing, and presentation of sample clinical images to demonstrate "substantial equivalence" rather than a comparative effectiveness study measuring human reader improvement with AI assistance. The software features are enhancements to image acquisition and processing, not explicitly AI-assisted diagnostic tools in the context of comparative reading studies.

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

While the software features (MAGIC DWI and CardioMaps) represent algorithm-only additions, the document emphasizes that the "images and/or spectra when interpreted by a trained physician yield information that may assist in diagnosis."
The "phantom testing" and quality assurance measures (e.g., unit-level, integration, performance, safety testing) can be considered standalone evaluations of the algorithms' output quality and adherence to specifications. However, the ultimate "performance" in the diagnostic context is tied to physician interpretation. The regulatory focus here is on the system producing diagnostically useful images, not on an algorithm making a standalone diagnosis.

7. The Type of Ground Truth Used

• For Phantom Testing: The ground truth would typically be established by known physical properties or measurements of the phantom itself. The "pass/fail criteria" would be based on expected quantitative accuracy, image quality, or signal properties against these known values.
• For Clinical Images: The document mentions "images and/or spectra when interpreted by a trained physician yield information that may assist in diagnosis." This implies that the effectiveness in a clinical setting is ultimately judged by expert clinical interpretation, but it does not specify a formal "ground truth" (e.g., pathology, surgical findings, long-term outcomes) used to validate the clinical utility of the specific new software features. It's more about demonstrating that the images produced can be interpreted by a physician to assist diagnosis.

8. The Sample Size for the Training Set

The document does not provide any information regarding a training set sample size. This is likely because the referenced software features are defined as modifications to existing MR systems, and while they involve algorithms, the summary doesn't describe them as machine learning models that require distinct "training sets" in the typical sense. The development process described (risk analysis, requirements reviews, design reviews, various levels of testing) is a standard software engineering approach.

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

As no training set is mentioned for machine learning, information on how its ground truth was established is not applicable or provided in this document.

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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 system 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, 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 3.0Tsystem 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 features a superconducting magnet operating at 3.0 Tesla. 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. The Discovery MR750 3.0T uses multi-drive RF transmit for imaging of the head and body regions.

Here's a breakdown of the acceptance criteria and study information for the GE Discovery MR750 3.0T, based on the provided document:

1. Table of Acceptance Criteria and Reported Device Performance

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

The document states: "Internal scans were conducted as part of validation for workflow and image quality for the addition of the new feature."

• Sample Size: Not explicitly stated. The term "internal scans" typically implies a smaller, controlled set of images used for engineering validation rather than a large clinical trial.
• Data Provenance: "Internal scans" suggests the data was generated internally by GE Healthcare, likely on their own test subjects or phantoms. There is no mention of country of origin or whether it was retrospective or prospective in a clinical sense; it appears to be primarily technical validation.

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

This information is not provided in the document. The study described focuses on technical and imaging performance comparison to a predicate, rather than an assessment requiring expert ground truth in a diagnostic context.

4. Adjudication Method for the Test Set

This information is not provided in the document. Given the nature of the "internal scans" for workflow and image quality validation, a formal adjudication process as seen in clinical trials with multiple expert readers is unlikely to have been employed.

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

A Multi-Reader Multi-Case (MRMC) comparative effectiveness study was not done. The study described is a technical and imaging performance comparison, not an AI-assisted diagnostic study. Therefore, there is no information on human reader improvement with or without AI assistance.

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

The device itself is a Magnetic Resonance Diagnostic Device, not an AI algorithm. The tests performed were on the imaging system's performance, not a standalone algorithm.

7. The Type of Ground Truth Used (Expert Consensus, Pathology, Outcomes Data, etc.)

The document implies that the ground truth for performance was the performance of the predicate device (K132376). The goal was to demonstrate that the new device "maintains the same imaging performance results as its predicate device." This suggests a comparative "ground truth" rather than an independent gold standard like pathology. For technical performance, compliance with standards (IEC, NEMA) would also serve as a form of "ground truth."

8. The Sample Size for the Training Set

There is no mention of a training set. This type of device (a magnetic resonance scanner) does not typically involve a machine learning training set in the way an AI diagnostic algorithm would. The development involves engineering and software updates, and validation against established technical standards and predicate performance.

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

As there is no mention of a training set, this information is not applicable/not provided.

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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, sagittal, 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, TMI, 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).

The DV25 release is introducing new software features onto these existing MR Systems.

The provided text does not contain detailed acceptance criteria or a study proving the device meets specific performance criteria in the format requested.

The document is a 510(k) Premarket Notification Submission for GE Medical Systems' Discovery MR series and Optima MR series devices. It primarily focuses on demonstrating substantial equivalence to a previously cleared predicate device (K132376) for minor changes, specifically new software features (DV25 release including DISCO, MDE Plus, and Silent Suite updates) and hardware modifications for obsolescence and operating system compatibility.

Here's what can be extracted based on the provided text, and what information is not available:

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

The document does not provide a table with specific, quantifiable acceptance criteria (e.g., sensitivity, specificity, accuracy for a diagnostic task) and corresponding reported device performance. It generally states that "The testing was completed with passing results per the pass/fail criteria defined in the test cases," and "The clinical results demonstrated that the Discovery MR750 3.0T, Discovery MR450 1.5T, Discovery MR750w 3.0T and the Optima MR450w 1.5T maintain the same imaging performance results as its predicate devices (K132376)." These are high-level statements without specific metrics or thresholds.

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

• Sample Size: Not specified. The document mentions "Internal scans were conducted as part of validation for workflow and image quality," but does not provide a sample size (number of patients, cases, or images) for these internal scans.
• Data Provenance: The scans were "internal," suggesting they were conducted within GE Healthcare, but the country of origin, retrospective/prospective nature, or demographic details are not provided.

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

This information is not provided. The document makes no mention of external experts or how ground truth was established for the internal validation scans. The statement "These images and/or spectra when interpreted by a trained physician yield information that may assist in diagnosis" relates to the general use of MR images, not to the ground truth establishment for a specific study.

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

This information is not 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:

• MRMC Study: No, an MRMC comparative effectiveness study was not conducted or described. The document states, "The subject of this premarket submission... did not require external clinical studies to support substantial equivalence."
• AI Assistance Effect Size: The device described is a Magnetic Resonance (MR) scanner, not an AI-based diagnostic tool for interpretation. Therefore, the concept of human readers improving with AI assistance is not applicable to the information presented. The software updates are for scanner capabilities (image acquisition, image quality, workflow), not for AI-driven diagnostic interpretation.

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

The device is an MR scanner, which generates images that are then interpreted by a trained physician. It is not an algorithm that provides a standalone diagnosis. Therefore, standalone algorithm-only performance in the context of interpretation is not applicable. The "performance" being evaluated here relates to image quality and features of the MR scanner itself.

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

This information is not provided. Given the nature of an MR scanner (image acquisition), "workflow and image quality" validation might involve assessing image metrics, artifact presence, resolution, signal-to-noise ratio, and visual assessment of anatomical detail, rather than a clinical ground truth like pathology for a specific disease.

8. The sample size for the training set:

The document does not describe the development of a model that would require a "training set" in the context of machine learning or AI. The changes are software features and hardware modifications for an existing MR system. Therefore, this question is not applicable.

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

As there is no mention of a training set, this question is not applicable.

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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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