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The system is intended to produce cross-sectional images of the body by computer reconstruction of X-ray transmission data taken at different angles and planes, including Axial, Cine, Helical (Volumetric), Cardiac, and Gated acquisitions. These images may be obtained either with or without contrast. This device may include signal analysis and display equipment supports, components and accessories.

This device may include data and image processing to produce images in a variety of trans-axial and reformatted planes. Further the images can be post processed to produce additional imaging planes or analysis results.

The system is indicated for head, whole body, cardiac and vascular X-ray Computed Tomography applications in patients of all ages.

The device output is a valuable medical tool for the diagnosis of disease, trauma, or abnormality and for planning, guiding, and monitoring therapy.

The proposed device Revolution Ascend Sliding is a head and whole-body CT system composed of a gantry, transporter, operator console with a host computer, power distribution unit, and interconnection cables. The system also includes image acquisition and reconstruction hardware/software, general system software, accompanying documents, and associated accessories/interconnections.

Revolution Ascend Sliding generates cross-sectional images of the body by computer reconstruction of xray transmission data taken at different angles and planes, including Axial, Cine, Helical (Volumetric), Cardiac, and Gated acquisitions modes.

The provided text does NOT include details about acceptance criteria and the study that proves the device meets the acceptance criteria in the format requested.

Here's why and what information IS available:

This device is a Computed Tomography (CT) X-ray System, specifically a hardware modification. The 510(k) summary focuses on demonstrating substantial equivalence to a predicate device (Revolution Ascend, K213938) based on engineering design, performance, and image quality specifications. It's not an AI/CADe device that would typically have the kind of performance metrics (sensitivity, specificity, AUROC) and associated study designs you're asking for.

Therefore, most of the requested fields cannot be filled from this document.

Here's what information I can extract and why other fields are not applicable:

• A table of acceptance criteria and the reported device performance: This detail is not provided. The document states that the device "maintains the identical/equivalent performance and image quality specifications" to its predicate and that "Non-clinical bench test results demonstrated the subject device performs equivalently to the predicate device." However, specific numerical acceptance criteria and reported performance values for those criteria are not listed.
• Sample sized used for the test set and the data provenance: Not applicable in the context of this document. This is not a study evaluating diagnostic performance on a dataset of patient cases. The testing mentioned is "engineering design V &V and bench testing."
• Number of experts used to establish the ground truth for the test set and the qualifications of those experts: Not applicable. No ground truth establishment by experts is described for a diagnostic performance study.
• Adjudication method (e.g. 2+1, 3+1, none) for the test set: Not applicable.
• 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. This is not an AI-assisted diagnostic device.
• If a standalone (i.e. algorithm only without human-in-the-loop performance) was done: Not applicable.
• The type of ground truth used (expert consensus, pathology, outcomes data, etc): Not applicable.
• The sample size for the training set: Not applicable. No training set is mentioned as this isn't an AI/ML device.
• How the ground truth for the training set was established: Not applicable.

What the document does state about testing and compliance:

• Testing Philosophy: The device was tested through "engineering design V &V and bench testing" to demonstrate substantial equivalence to the predicate device.
• Compliance: The device is "in compliance with AAMI/ANSI ES 60601-1 and IEC60601-1 Ed. 3.2 and its associated collateral and particular standards, 21 CFR Subchapter J, and NEMA standards XR 25, XR 26, and XR 28."
• Image Quality Testing: Image quality testing was done "in accordance with IEC 61223-3-5 ed.2 to demonstrate the overall system performance in a standardized and referenceable manner."
• Clinical Testing: "The Revolution Ascend Sliding CT system can be fully tested on the engineering bench thus no additional clinical testing was required." This indicates that the regulatory body agreed that bench testing was sufficient to demonstrate safety and effectiveness for this type of device modification.
• Quality Assurance Measures: Includes "Risk Analysis and Control, Required Reviews, Design Reviews, Testing on unit level (Module verification), Integration testing (System verification), Performance testing (Verification), Safety testing (Verification)."

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The Auto Positioning feature provides an alternate, streamlined and efficient workflow and safety checks for the CT technologist in setting up CT examinations of the initiation of the first scout scan.

Auto Positioning acquires 3D spatial information of the individual patient on the table and combines it with information from the selected protocol to automatically calculate and visually display the scout's start and end locations. Concurrently it checks for proper patient orientation, determines the table height for optimum patient centering, and checks for potential contact between the patient and the gantry. Upon acceptance by the technologist the patient is automatically moved to the correct scout start location.

Use of Auto Positioning is intended to provide consistent patient positioning for optimal image quality and automatic exposure control.

Auto Positioning is an optional feature developed for use with GE CT systems. The purpose of this feature is to provide both a streamlined workflow and enhanced quality and safety checks during the exam setup process up to the initiation of the first scout scan. Incorporation of this optional feature does not preclude the technologist from preforming the existing manual workflow on the CT system, if desired.

Auto Positioning uses a fixed, ceiling mounted, off the shelf, 2D/3D video camera that is capable of determining distances to points in its field of view. It displays standard RGB video images on the CT system's existing gantry-mounted touchscreens. Information from the standard output of the camera, precise spatial information of the individual CT system's gantry and table installation geometry, and information contained in the user-selected protocol is used to determine the anatomical landmark location and the start and end locations for the scout scan(s).

Information from the standard output of the camera, precise spatial information of the individual CT system's gantry and table installation geometry, and information contained in the userselected protocol is used to determine the anatomical landmark location and the start and end locations for the scout scan(s).

Addition functionality of Auto Positioning includes performing safety checks for patient orientation and the potential for the patient to come into contact with the gantry while the patient is placed into the gantry and during scanning.

The GE Auto Positioning device is a patient positioning workflow enhancement tool for CT systems. It uses a 2D/3D video camera and deep learning to automate the process of setting the landmark, patient centering, scout's start and end locations, and the scout's start table position. It also performs safety checks for patient orientation and potential patient-gantry collision.

Here's an analysis of its acceptance criteria and the study that proves its effectiveness:

1. Table of Acceptance Criteria and Reported Device Performance

The provided document does not explicitly list a table of acceptance criteria with corresponding performance metrics for the Auto Positioning device. However, it indicates that "All testing met its predefined acceptance criteria." The narrative suggests the criteria would relate to the accuracy of landmark location, scout scan start and end locations, proper patient centering, correct patient orientation detection, and gantry collision prevention.

Based on the information, the reported device performance is that all non-clinical bench testing, which included the evaluation of landmark location and scout scan's start and end location, successfully met its predefined acceptance criteria. The document also states that the device was developed under GE Healthcare's quality system, and all subsystem and system verification testing, including hazard mitigation, demonstrated that the Auto Positioning feature meets its design inputs and user needs.

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

The document explicitly states: "Because Auto Postioning is for the exam setup process up to the initiation of the first scout scan, and does not involve diagnostic imaging or diagnostic evaluation, non-clinical bench testing is appropriate."

And further: "The Auto Positioning can be fully tested on the engineering bench thus no additional clinical testing was required."

Therefore, no clinical test set with patient data (and thus no associated sample size or data provenance) was used for direct performance evaluation for this 510(k) submission. The testing was conducted on an "engineering bench."

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

Since the testing was non-clinical bench testing and no clinical test set was used, there is no mention of experts or their qualifications for establishing ground truth from patient data. The "ground truth" for the non-clinical testing would have been established by engineering specifications and measurements. Engineers or technical experts involved in the design and verification would have assumed this role.

4. Adjudication Method for the Test Set

As there was no clinical test set using human readers, there was no adjudication method employed.

5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study was done

No, an MRMC comparative effectiveness study was not done. The document states that no clinical testing was required or performed. The device is focused on workflow enhancement and safety checks, not diagnostic image interpretation.

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

Yes, the primary evaluation was a standalone "algorithm only" performance, given the context of "non-clinical bench testing" and the statement that the device "can be fully tested on the engineering bench." The system's ability to accurately determine landmark locations, scout start/end points, patient orientation, and gantry collision potential was evaluated without human intervention in the positioning process itself. The technologist's role is to accept the automatically calculated positions.

7. The Type of Ground Truth Used

For the non-clinical bench testing described, the ground truth would have been based on:

• Engineering Specifications: Precisely defined parameters and measurements for expected landmark locations, optimal patient centering, and safe gantry clearance.
• Physical Measurements: Direct measurements of dummy patients, phantoms, or test setups on the engineering bench to represent ideal or boundary conditions. These measurements would then be compared against the device's output.

8. The Sample Size for the Training Set

The document mentions that "Auto Positioning uses Deep Learning CNNs to determine the scout's landmark location and the patient orientation." However, it does not provide any information regarding the sample size of the training set used for these Deep Learning Convolutional Neural Networks (CNNs).

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

The document does not describe how the ground truth for the training set was established for the Deep Learning CNNs. Typically, for such applications, ground truth for training data would involve:

• Manual Annotation by Experts: CT technologists or other medical imaging professionals manually identifying landmarks and patient orientations in a large dataset of patient images or 3D scans.
• Synthetic Data Generation: Creating artificial data with known ground truth based on anatomical models.
• Measurement from Phantoms/Physical Setups: Using a controlled environment with phantoms where the exact positions and orientations are known.

Without further information, the specific method used for the Auto Positioning device's deep learning training ground truth remains unknown from the provided text.

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The system is intended to produce cross-sectional images of the body by computer reconstruction of x-ray transmission data taken at different angles and planes, including Axial, Cine, Helical (Volumetric), Cardiac, and Gated acquisitions. These images may be obtained either with or without contrast. This device may include signal analysis and display equipment, patient and equipment supports, components and accessories.

This device may include data and image processing to produce images in a variety of trans-axial and reformatted planes. Further the images can be post processed to produce additional imaging planes or analysis results.

The system is indicated for head, whole body, cardiac and vascular X-ray Computed Tomography applications in patients of all ages.

The device output is a valuable medical tool for the diagnosis of disease, trauma, or abnormality and for planning, guiding, and monitoring therapy.

The Revolution Maxima CT system is composed of a gantry, patient table, operator console, host computer, and power distribution unit (PDU), and interconnecting cables. The system also includes image acquisition and reconstruction hardware/software, general system software, accompanying documents, and associated accessories, interconnections. The Revolution Maxima system is an evolutionary configuration of the predicate Optima CT660 CT system (K131576). All of the hardware functionality is identical to the predicate, however, some hardware changes have been made that did not change the system's performance specifications such as the new liquid metal bearing tube for improved tube life and reliability, the upgraded DAS and detector to improve the manufacturability and lower electronic nosie for better low signal performace and thermal management.

Identical to the predicate, Revolution Maxima generates cross-sectional images of the body by computer reconstruction of x-ray transmission data taken at different angles and planes, including Axial, Cine, Helical (Volumetric), Cardiac, and Gated acquisitions modes. Revolution Maxima's Intended Use and Indications for Use remain identical to those of the predicate device.

The Revolution Maxima CT system is a head and whole body CT system incorporating the same basic fundamental operating principles and the same indications for use as the predicate device. It's materials and construction are identical to our existing marketed products. Revolution Maxima remains compliant with IEC 60601-1 Ed. 3.1 and associated collateral and particular standards, NEMA XR 25, XR 28, and 21 CFR Subchapter J performance standards. The accompanying documents also contain the information in support of IEC61223-3-5 Ed. 1.0 for acceptance testing.

The performance and image quality specifications are identical/equivalent to the predicate. The gantry has a 70 cm bore with a maximum FOV of 50 cm. Available rotation speeds range from 0.35 to 2.0 seconds. Same as the predicate, the Revolution Maxima has three types of reconstruction methods available: FBP, ASiR, and ASiR-V (K133640). The performance of ASiR-V on Revolution Maxima is identical to that on the predicate Optima CT660.

Revolution Maxima includes most of the available features on the current production predicate device Optima CT660. The new changes incorporated into Revolution Maxima are primarily addition of a few features found on other GE current production CT systems, e.g. updated newer ITE host computer, Digital Tilt as an alternative to the tilted gantry, improved metal artifacts reduction called Smart MAR and 1024x1024 Recon. Digital Tilt is a software reformatting of the reconstructed images so that they appear like those reconstructed from a tilted gantry. The smaller pixel sizes of 1024 Recon improves the spatial resolution which is useful in clinical applications that would benefit from increased spatial resolution, especially those applications where a large display field of view is desired to simultaneously image corresponding left/right anatomy for comparison (e.g. highresolution lungs, internal auditory canals).

There are other unique changes for Revolution Maxima which includes new gantry covers with more aesthetic and modern industry design, new gantry display panel on two tablets with high resolution touchscreens, one on each side of the gantry for improved access and usability. These gantry display tablets replace the single display screen located at the top center of the gantry in the predicate device and host the web based user interface for a new and improved workflow called "Express mode" which seamlessly displays the related protocols associated with order information in the RIS

This 510(k) summary for the Revolution Maxima CT system by GE Hangwei Medical Systems Co.,Ltd. describes its substantial equivalence to a predicate device, the Optima CT660. Therefore, the information provided is primarily focused on demonstrating that the new device is as safe and effective as the predicate, rather than establishing de novo acceptance criteria with standalone performance studies against a clinical ground truth.

Here's an analysis of the provided information, addressing your points where possible:

1. Table of Acceptance Criteria and Reported Device Performance

There isn't a table of specific acceptance criteria in the traditional sense of diagnostic performance metrics (e.g., sensitivity, specificity, AUC) for the Revolution Maxima. Instead, the "acceptance criteria" are implied by the claim of substantial equivalence to the predicate device, Optima CT660. The reported device performance is that it performs equivalently to the predicate.

• Non-clinical bench test results demonstrated the subject device performs equivalently to the predicate device.
• Image quality and dose performance confirmed using standard IQ and QA phantoms.
• Performance testing in accordance with IEC 61223-3-5 ed 2 (FDIS). |
  | Compliance with relevant standards and regulations | - In compliance with AAMI/ANSI ES 60601-1 and IEC60601-1 Ed. 3.1 and associated collateral and particular standards.
• Compliance to applicable CDRH 21 CFR subchapter J requirements.
• Compliance to NEMA standards XR 25, XR 26, and XR 28.
• Designed and manufactured under the Quality System Regulations of 21 CFR 820 and ISO 13485. |
  | Image quality specifications | Identical/equivalent to the predicate (Optima CT660), including ASiR and ASiR-V performance. |
  | Functional equivalence | - Operates on the same fundamental principles.
• Has the same intended use and indications for use.
• Hardware functionality is identical in some aspects, with new components not changing performance specifications (e.g., tube, DAS, detector for manufacturability and lower electronic noise).
• New features (1024x1024 Recon, Smart MAR, Digital Tilt) are additions, not changes to core functionality. |

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

The document explicitly states: "The Revolution Maxima can be fully tested on the engineering bench thus no additional clinical testing was required." This indicates that no human patient imaging test set was used for a clinical study to establish standalone diagnostic performance. Instead, testing relied on non-clinical bench tests, image quality and QA phantoms.

Therefore:

• Sample size for test set: Not applicable (no human patient test set).
• Data provenance: Not applicable (no human patient data). The data provenance refers to phantom and bench test data.

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

Since no clinical test set was used, there were no experts needed to establish ground truth for a clinical diagnostic performance evaluation. The "ground truth" for the non-clinical tests would be the known properties of the phantoms and the expected physical performance metrics, assessed by engineers and physicists rather than medical experts for diagnostic accuracy.

4. Adjudication Method for the Test Set

Not applicable, as no clinical test set requiring expert adjudication was used.

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 such MRMC study was performed or is mentioned. The device is a CT scanner, not an AI-assisted diagnostic tool that integrates with human readers in that manner. The "AI" mentioned (ASiR, ASiR-V) are iterative reconstruction algorithms incorporated into the image processing of the CT scanner itself to improve image quality and reduce dose, not a separate AI system intended for radiologists' interpretative assistance.

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

This refers to the performance of the CT system itself in generating images. The non-clinical testing served this purpose:

• Standalone Performance: Yes, standalone system performance was evaluated through non-clinical bench tests, image quality (IQ), and dose performance using standard IQ and QA phantoms. This includes specific tests like Metal Artifact Reduction (MAR) testing and image quality testing on 1024x1024 Recon, and performance testing in accordance with IEC 61223-3-5 ed 2 (FDIS). The results demonstrated equivalence to the predicate device.

7. The Type of Ground Truth Used (expert consensus, pathology, outcomes data, etc)

For the non-clinical tests, the "ground truth" was based on:

• Known phantom properties: Phantoms designed with specific, measurable physical characteristics (e.g., density, spatial resolution patterns).
• Physical laws and engineering specifications: The expected performance based on the design and validated against established physical principles and engineering parameters.
• Compliance with industry standards: Meeting the specified requirements of standards like IEC 61223-3-5, NEMA XR 25, 26, 28, etc.

8. The Sample Size for the Training Set

Not applicable. This is a 510(k) for a CT scanner, not a machine learning algorithm that requires a training set of images with ground truth labels. While the iterative reconstruction algorithms (ASiR, ASiR-V) might have involved data for their development, that information is not part of this 510(k) summary focused on the substantial equivalence of the overall CT system.

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

Not applicable, as there is no mention of a training set in this context.

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The GE Revolution ACT Computed Tomography X-ray system is intended to produce cross- sectional images of the body by computer reconstruction of x-ray transmission data taken at different angles and planes, for patients of all ages, including Axial, Cine, Helical.

These images may be obtained either with or without contrast. This device may include signal analysis and display equipment, patient, and equipment supports, components and accessories.

This device may include data and image processing to produce images in a variety of trans-axial and reformatted planes. Further the images can be post processed to produce additional imaging planes or analysis results.

The GE Revolution ACT CT Scanner System is indicated for head, whole body and vascular X-ray Computed Tomography applications.

The device output is a valuable medical tool for the diagnosis of disease, trauma, or abnormality and for planning, guiding and monitoring therapy.

The multi-slice GE Revolution ACT CT scanner is currently commercially available and in clinical use in various other countries including the EU, Japan, China, and India.

It is a general purpose, 16-slice (detector row) CT scanning system with a z-coverage of 20 mm and a maximum gantry rotation speed of 0.98 seconds. Revolution ACT is designed to help enable greater patient access to CT imaging in facilities that otherwise might not be able to obtain multi-slice CT technology with both current standard and advanced CT features and function.

Revolution ACT uses the same technology, operating principles, features, and functions as the GE Optima CT520 predicate device (K123596) and other cleared GE CT scanners. The system consists of the gantry, patient table, operator console, power distribution unit (PDU), associated accessories, and software options. The Revolution ACT is also available in an 8-detector row (10 mm z-coveragre configuration (Revolution ACTs) using the identical (but depopulated) detector/DAS. The changes from the predicate device do not affect the intended use or patient population.

Becaues the Revolution ACT does not support cardiac or other gated acquisitions, and has a slower rotation time thatn the predicate device, its indications for use were modified by removing cardiac and gated acquisitions and cardiac applications.

The provided text describes the Revolution ACT Computed Tomography X-ray system and its substantial equivalence to the predicate device, Optima CT520. However, the text does NOT contain specific acceptance criteria with numerical values or a direct comparative study that reports device performance against such criteria for AI-related functions.

The document mainly focuses on establishing substantial equivalence to a predicate device for a CT scanner system, emphasizing hardware and imaging performance rather than an AI/ML component with specific performance metrics.

Based on the provided text, here’s a breakdown of the requested information, highlighting where the information is absent:

Acceptance Criteria and Study for Revolution ACT CT Scanner System (as per provided document)

The document primarily establishes substantial equivalence for a CT scanner system, Revolution ACT, to a predicate device, Optima CT520 (K123596). It focuses on the device's ability to produce cross-sectional images for diagnostic purposes. The "acceptance criteria" discussed are largely tied to compliance with standards and demonstration of equivalent performance to the predicate device in terms of image quality and safety.

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

The document explicitly states that the Revolution ACT "maintains virtually the same image quality specifications and dose performance as its predicate" and that "verification testing along with additional engineering testing demonstrated Revolution ACT's equivalent performance to currently marketed the predicate and other cleared GE CT devices and is therefore as safe and effective."

However, a quantitative table with specific acceptance criteria (e.g., minimum spatial resolution, maximum noise level, sensitivity, specificity, or accuracy metrics) and corresponding reported performance values for the Revolution ACT is not provided in the given text. This section of the document describes general compliance and equivalence.

The text mentions a comparison of:

• CT number accuracy
• CT number uniformity
• Image noise (standard deviation)
• Modulation Transfer Function (MTF)
• Noise Power Spectrum
• Slice thickness

It states these comparisons were "provided" but does not present the actual values or the acceptance criteria for these metrics.

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

• Test Set Sample Size: Not explicitly stated for specific quantitative performance tests. The document refers to "engineering bench testing" and "images from both a uniform phantom and one with embedded LCD objects."
• Data Provenance: Phantoms were used for engineering bench testing. For clinical verification, "sample clinical images" were reviewed. The origin of these clinical images (e.g., country) is not specified.
• Retrospective or Prospective: Not specified for the clinical images used for review. Phantom studies are inherently controlled.

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

• Number of Experts: "A board certified radiologist." (Singular)
• Qualifications of Experts: "Board certified radiologist."

4. Adjudication method for the test set:

• Adjudication Method: "Sample clinical images reviewed by a board certified radiologist." This implies a single expert review, so no multi-reader adjudication method (e.g., 2+1, 3+1) is described.

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 Comparative Effectiveness Study: No, an MRMC comparative effectiveness study involving human readers and AI assistance is not described in the provided text. The device is a CT scanner, and while it has "signal analysis and display equipment" and "data and image processing," the document does not focus on an AI-assisted diagnostic function. The primary focus is on the scanner's core imaging performance and safety. The "SmartPlan" feature mentioned is for workflow enhancement (initial scan setup parameters) and not for diagnostic assistance that would typically be evaluated in an MRMC study for improved reader performance.

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

• Standalone Performance Study: The document does not describe a standalone performance study for an AI algorithm. The device itself (the CT scanner) undergoes performance testing against engineering specifications. The "ASiR" (Adaptive Statistical Iterative Reconstruction) algorithm is mentioned as being ported to new hardware, and its performance is verified through clinical image review by a radiologist, but this is not presented as a standalone AI algorithm evaluation.

7. The type of ground truth used:

• For engineering bench testing: Physical phantoms with known properties (uniform phantom, phantom with embedded LCD objects).
• For clinical image review: Implied clinical diagnosis/reference for the "sample clinical images reviewed by a board certified radiologist." However, the explicit nature of this ground truth (e.g., pathology, outcomes data) is not detailed. It is likely derived from standard clinical practice and radiologist interpretation.

8. The sample size for the training set:

• Training Set Sample Size: Not applicable/not provided. The document describes a CT scanner and its underlying technologies. While reconstruction algorithms like ASiR might involve models, the document does not detail their training or associated datasets. The focus is on the hardware platform and its imaging capabilities.

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

• Ground Truth for Training Set: Not applicable/not provided, as no training set for an AI/ML diagnostic algorithm is described.

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The OEC Elite MiniView (mobile mini C-Arm) is designed to provide physicians with real time goopic visualization of patients of all ages. It is intended to aid physicians and surgeons during diagnostic or therapeutic treatment/surgical procedures of the limbs/extremities and shoulders including, but not limited to, orthopedics and emergency medicine.

The OEC Elite™ MiniView™ is a mobile fluoroscopic mini C-arm system that provides fluoroscopic images of patients of all ages during diagnostic, treatment, and surgical procedures of the shoulders, limbs, and extremities. The system consists of a C-arm attached to an image processing workstation. A CsI(TI) - CMOS flat panel detector and the identical X-ray source monoblock are used for image acquisition.

The C-arm supports the high-voltage generator, X-ray tube, X-ray controls, collimator, and the FPD. The C-arm is capable of performing linear (vertical, horizontal, orbital) and rotational motions that allow the user to position the X-Ray imaging components at various angles and distances with respect to the patient extremity anatomy to be imaged. The C and support arm are mechanically balanced allowing for ease of movement and capable of being "locked" in place using an electronically controlled braking system. The workstation is a stable mobile platform that supports the C-arm, image display monitor(s), image processing equipment/software, recording devices, data input/output devices and power control systems.

The OEC Elite™ MiniView™ is a mobile fluoroscopic mini C-arm system. The provided document is a 510(k) Premarket Notification Submission, which focuses on demonstrating substantial equivalence to a predicate device, rather than defining and proving acceptance criteria in the typical sense of a clinical trial for a novel AI device. However, based on the information provided, we can extract details about the performance evaluation done to demonstrate this equivalence.

Here's an analysis based on the provided text, structured according to your request:

1. Table of Acceptance Criteria and Reported Device Performance

The document does not explicitly present a table of acceptance criteria with corresponding performance metrics like sensitivity, specificity, or AUC as one might find for an AI diagnostic algorithm. Instead, the evaluation focuses on demonstrating that the performance of the proposed device (OEC Elite™ MiniView™) is at least equivalent to the predicate device (OEC Mini 6800 Digital Mobile C-arm) and reference devices in terms of image quality and clinical capability.

The "acceptance criteria" here implicitly revolve around ensuring the safety and effectiveness of the updated device, which includes:

• Meeting design input and user needs.
• Compliance with regulatory standards (IEC 60601-1 Ed.3 series, IEC 60601-2-54, IEC 60601-2-43, and 21CFR Subchapter J performance standards).
• Image quality and clinical capability at least equivalent to the predicate device.

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

• Test Set Sample Size: The document mentions a cadaver study involving two cadavers on which nineteen orthopedic procedures were performed across a variety of extremity anatomies.
• Data Provenance: The cadaver study was performed as part of the submission process, implying it was a prospective evaluation specifically for this device. The country of origin of the cadavers is not specified in the provided text.

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

• Number of Experts: Two independent physicians were used to evaluate the images.
• Qualifications of Experts: The document states they were "two independent physicians", and given the nature of the device (fluoroscopic imaging for orthopedic procedures), it's highly probable these were orthopedic surgeons or radiologists with expertise in musculoskeletal imaging and procedures. However, their specific specializations or years of experience are not explicitly stated in the provided text.

4. Adjudication Method for the Test Set

The document states: "The performance of the subject device to the predicate was also performed by two independent physicians." It further states that the "study confirmed the clinical capability and overall quality of the images produced by the OEC Elite™ MiniView™ was at least equivalent to that of the Mini 6800 Digital Mobile C-Arm." This implies a consensus or comparative evaluation by the two physicians. However, a specific adjudication method (e.g., 2+1, 3+1, etc.) is not explicitly detailed. It's presented as a direct comparison where both physicians apparently agreed on the equivalence.

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

• Not a typical MRMC study: The evaluation described is not a traditional MRMC comparative effectiveness study focused on quantifying human reader improvement with AI assistance. This device is an imaging system (hardware and software for image acquisition and processing), not an AI-powered diagnostic aide designed to improve human reader performance for a specific task.
• Focus on System Equivalence: The study aimed to demonstrate the system's overall clinical capability and image quality equivalence to a predicate device, as evaluated by human readers (the two physicians), rather than measuring the effect size of AI assistance on human readers.

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

• Standalone "Algorithm" Performance: The device itself is an imaging system, not purely an algorithm. Its performance is inherent in the images it produces. Therefore, "standalone" in this context refers to the system's ability to produce diagnostically acceptable images.
• Bench Testing and Image Quality Tests: The document details extensive "engineering bench testing" and "image quality/performance testing" identified for fluoroscopy. These tests evaluate the system's technical image output without human interpretation as the primary endpoint. This can be considered the equivalent of "standalone" performance for an imaging device. Specifically mentioned are:
  • Demonstration of system performance.
  • Imaging performance evaluation using anthropomorphic phantoms (including a pediatric anthropomorphic phantom).
  • All image quality/performance testing identified for fluoroscopy in FDA's "Information for Industry: X-ray Imaging Devices - Laboratory Image Quality and Dose Assessment, Tests and Standards" was performed.

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

• For the Cadaver Study (Test Set): The ground truth for evaluating clinical capability and image quality seems to be based on expert consensus (or agreement) between the two independent physicians regarding the equivalence of the images produced by the OEC Elite™ MiniView™ compared to the predicate device for diagnostic and procedural guidance in the cadaveric setting. There is no mention of pathology or outcomes data for this specific evaluation, as it's a technical performance and clinical utility assessment on cadavers.
• For Bench Testing: The ground truth for bench testing and phantom studies would be defined by known physical properties of the phantoms and established engineering specifications and standards for image quality metrics.

8. The Sample Size for the Training Set

The document describes a medical imaging device (C-arm), not an AI algorithm that requires a separate training set. Therefore, the concept of a "training set sample size" as typically applied to machine learning models is not applicable here. The device's underlying technology and software architecture are based on existing, proven designs (predicate and reference devices), with modifications validated through engineering bench tests and the cadaver study.

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

As noted in point 8, there is no explicit "training set" in the context of an AI algorithm described in this document. The device's development involved standard engineering practices, which could be considered an iterative design and testing process that refines the system's performance. The "ground truth" during this development would be based on engineering specifications, performance targets, and established imaging principles, rather than a labeled dataset for training an AI model.

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The GE Optima CT520 Computed Tomography X-ray system is intended to produce crosssectional images of the body by computer reconstruction of x-ray transmission data taken at different angles and planes, patient for all ages, including Axial, Cine, Helical, Cardiac, and Gated acquisitions. These images may be obtained either with or without contrast. This device may include signal analysis and display equipment, patient, and equipment supports, components and accessories.

This device may include data and image processing to produce images in a variety of trans-axial and reformatted planes. Further the images can be post processed to produce additional imaging planes or analysis results. The GE Optima CT520 CT Scanner System is indicated for head, whole body, cardiac and vascular X-ray Computed Tomography applications. The device output is a valuable medical tool for the diagnosis of disease, trauma, or abnormality and for planning, guiding, and monitoring therapy.

The Optima CT520 CT Scanner System is composed of a gantry, patient table, operator console, and line voltage adaptor. It also includes image acquisition hardware, image acquisition and reconstruction software, associated accessories and connections/interfaces to accessories.

The system generates images through the computer reconstruction of data acquired at different angles and planes of the rotating gantry. The gantry can rotate at up to 0.8 seconds per rotation. and can acquire up to 16 slices/rows of data per rotation with a maximum total collimation coverage of 20mm in the z direction. The system can be operated in Axial, Cine, Helical, Cardiac and Gated acquisition modes.

To improve the siting footprint, the power distribution unit (PDU) has been integrated into the gantry base; except for standalone line voltage adaptor, if needed. The PDU components' function and performance remain the same. This change has been fully tested and certified by a NRTL to continue to meet all applicable IEC/UL safety standards.

The Optima CT520 represents evolutionary modifications to the predicate device (BrightSpeed Elite Select CT System (K082816)). The modifications include hardware upgrades due to technology obsolesces (e.g. console), ROHS compliance, system siting footprint optimization, and IEC Edition 3 compliance, as well as software changes to improve workflow and usability. incorporate Dose Check and quality fixes, assist in product marketing position by feature availability, and feature technology flow-down from cleared premium tier products (e.g. ASiR), The Optima CT520 is a general purpose, mid-tier 16-slice CT scanner that incorporates GE's innovative technology and feature functionality.

The Optima CT520 uses virtually the same materials and identical operating principle as our existing marketed product, except in the case of using the compensatory ROHS compliance material. The image chain components (tube, collimator, detector. DAS) are virtually identical to the BrightSpeed Elite Select.

The changes do not affect the intended use, the indications for use, patient population nor fundamental operating principles of the currently commercially available predicate system and are the identical or similar to other GE CT systems and features previously cleared.

The GE Optima CT520 is a Computed Tomography (CT) X-ray system. The modifications to the predicate device (BrightSpeed Elite Select CT System (K082816)) primarily involve hardware upgrades due to technology obsolescence (e.g., console), ROHS compliance, system siting footprint optimization, IEC Edition 3 compliance, and software changes to improve workflow and usability, incorporate Dose Check, and other enhancements. The device uses virtually the same materials and identical operating principles as its predicate.

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

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

• Test Set: No specific numerical sample size is provided for a dedicated "test set" in the context of a clinical performance study. The primary method of demonstrating substantial equivalence involved engineering testing and an assessment of "sample clinical images."
• Data Provenance: The document does not specify the country of origin for the "sample clinical images" or whether they were retrospective or prospective. It only states that "sample clinical images representing a various acquisition modes and body regions were provided for reference."

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

• Number of Experts: Two independent radiologists.
• Qualifications of Experts: Not specified beyond being "independent radiologists." No details like years of experience or subspecialty are provided.

4. Adjudication method for the test set:

• Adjudication method: A Likert scale assessment was provided by the two independent radiologists. The document does not specify an adjudication method like 2+1 or 3+1; rather, it suggests an individual assessment by each radiologist.

5. If a multi-reader, multi-case (MRMC) comparative effectiveness study was done:

• MRMC Study: No, a Multi-Reader Multi-Case (MRMC) comparative effectiveness study was not performed. The submission explicitly states, "Clinical data was not needed to establish safety and effectiveness, all changes were able to be fully verified and validated on the bench, and the testing did not reveal any new questions of safety or effectiveness." The "sample clinical images" were provided for reference and assessed for diagnostic quality, not as part of a formal MRMC study to compare reader performance with and without AI assistance.

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

• Standalone Performance: Not applicable. The device is a CT scanner, not an AI algorithm intended for standalone diagnostic interpretation without human-in-the-loop performance. The "AI" mentioned in the description refers to "feature technology flow-down from cleared premium tier products (e.g. ASiR)" which likely refers to advanced image reconstruction techniques, not a standalone diagnostic AI algorithm.

7. The type of ground truth used:

• Type of Ground Truth: For the "sample clinical images," the ground truth was based on a Likert scale assessment of diagnostic quality provided by two independent radiologists. This can be categorized as expert consensus/opinion regarding image quality, rather than definitive pathology, clinical outcomes, or a pre-established "ground truth."

8. The sample size for the training set:

• Training Set Sample Size: The document does not mention a specific "training set" sample size. The modifications are described as "evolutionary modifications" and "hardware and software platform changes" building upon a predicate device. The development process emphasizes verification and validation against established standards and internal procedures rather than a machine learning training paradigm with a distinct training set.

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

• Training Set Ground Truth: Not applicable, as no distinct "training set" in the context of machine learning with established ground truth is described. The device's development focused on adherence to existing standards, internal quality control procedures, and demonstrating that the modifications did not alter the fundamental safety and effectiveness of the existing predicate device.

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1.5T Brivo MR355 and 1.5T Optima MR360 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 1.5T Brivo MR355 and 1.5T Optima MR360 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.

1.5T Brivo MR355 and 1.5T Optima MR360 is a whole body magnetic resonance scanner designed to support high resolution, high signal-to-noise ratio, and short scan times. The 1.5T Brivo MR355 and 1.5T Optima MR360 features a superconducting magnet operating at 1.5 Tesla. The system uses a combination of time-varying magnetic fields (gradients) and RF transmissions to obtain information regarding the density and position of nuclei exhibiting magnetic resonance. The data acquisition system accommodates 16 independent receive channels and multiple independent coil elements per channel during a single acquisition series.

Here's a breakdown of the acceptance criteria and study information based on the provided document:

1. Table of Acceptance Criteria and Reported Device Performance

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

• Test Set Sample Size: The document states, "Internal scans were conducted as part of validation for workflow and image quality, and sample clinical images are included in the submission." However, a specific number for a "test set" (i.e., a dataset used for independent evaluation of the device's performance against ground truth) is not provided. The term "internal scans" and "sample clinical images" suggest internal testing rather than a formal test set with defined sample size.
• Data Provenance: Not explicitly stated. The company is GE Healthcare, with a submitter address in Beijing, China, but the origin of the "internal scans" and "sample clinical images" is not specified. It's safe to assume it's retrospective data gathered for internal validation.

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

• Number of Experts: Not specified.
• Qualifications of Experts: Not specified.

4. Adjudication Method for the Test Set

• Adjudication Method: Not applicable/not described. This submission did not involve a formal clinical study with a test set requiring expert 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

• MRMC Study: No, an MRMC comparative effectiveness study was not conducted and is not mentioned.
• Effect Size: Not applicable.

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

• Standalone Study: No, this device is a Magnetic Resonance Imaging System, not an AI algorithm. Its performance is inherent to its hardware and software specifications for image acquisition, not for an independent diagnostic algorithm.

7. The Type of Ground Truth Used (expert consensus, pathology, outcomes data, etc.)

• Type of Ground Truth: For the "internal scans" for workflow and image quality, the ground truth would likely be based on technical specifications, image quality metrics, and potentially visual assessment by technical experts or radiologists comparing against established benchmarks or the predicate device's performance. There's no mention of expert consensus for diagnostic accuracy, pathology, or outcomes data in specific clinical scenarios.

8. The Sample Size for the Training Set

• Training Set Sample Size: Not applicable. This device is an MRI system, not an AI algorithm that requires a "training set" in the machine learning sense. The development and validation involved standard engineering processes, not machine learning model training.

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

• Ground Truth Establishment for Training Set: Not applicable, as there was no training set for an AI algorithm. The device's "ground truth" for its development would be based on engineering specifications, physical principles of MRI, and comparison to existing, cleared MRI systems.

Summary of the Study:

The submission explicitly states: "The subject of this premarket submission, 1.5T Brivo MR355 and 1.5T Optima MR360 did not require clinical studies to support substantial equivalence. Internal scans were conducted as part of validation for workflow and image quality, and sample clinical images are included in the submission."

Therefore, the "study" proving the device meets acceptance criteria was primarily a non-clinical validation process (risk analysis, requirements, design reviews, module verification, system verification, performance testing, safety testing, simulated use testing) demonstrating compliance with voluntary standards and substantial equivalence to a predicate device (1.5T Brivo MR355 and 1.5T Optima MR360 K103330). The "acceptance criteria" were implied to be the device's ability to produce high-quality MRI images across various body parts, consistent with its intended use and comparable to the predicate device's performance, as verified through internal testing and compliance with relevant standards. No formal clinical efficacy or diagnostic accuracy studies involving patient outcomes or expert adjudication were conducted or deemed necessary for this 510(k) clearance.

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The GE 8CH Foot Ankle Coil is a receive-only RF surface coil designed for use with 1.5T MRI systems manufactured by GE Healthcare. The 8ch Foot Ankle Coil for GE 1.5T MRI systems is indicated for use for foot and ankle imaging. The nucleus excited is hydrogen.

The GE 8CH Foot Ankle Coil is a surface coil used for Magnetic Resonance Imaging. It's tuned to image Protor nuclei in a receive-only configuration. It is comprised of 8 individual Phased Array coil elements each utilizing an integrated preamplifier to improve image quality. The geometry is optimized for use with parallel imaging techniques.

The GE 8CH Foot Ankle Coil comprises the coil and the base plate. The coil conforms to patients' anatomy, accommodating various foot contours while minimizing patient discomfort. The base plate separated from the coil part is used to place the patients' anatomy on the table.

The GE 8CH Foot Ankle Coil is a receive-only RF surface coil designed for use with 1.5T MRI systems manufactured by GE Healthcare. The 8ch Foot Ankle Coil for GE 1.5T MRI systems is indicated for use for foot and ankle imaging. The nucleus excited is hydrogen.

The GE 8CH Foot Ankle Coil is 8-element phased array RF receive only coils with integrated preamplifiers. The coil designs consist of RF chokes with switching diodes to provide decoupling which isolates the coil elements from RF fields during RF transmission. This coil is designed based on the same technology as the predicate device.

The provided GE Healthcare 510(k) Premarket Notification Submission (K122694) details the substantial equivalence of the GE 8CH Foot Ankle Coil to a predicate device. This submission focuses on the safety and effectiveness of the coil itself, rather than the performance of an AI algorithm. Therefore, many of the requested details, such as AI model performance metrics (sensitivity, specificity, AUC), ground truth establishment for AI, sample sizes for test and training sets for AI, expert qualifications, and MRMC studies, are not applicable to this type of medical device submission.

The acceptance criteria and "study" described herein relate to the verification testing of the hardware device.

1. Table of Acceptance Criteria and Reported Device Performance

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

This submission does not discuss a "test set" in the context of an AI algorithm. Instead, it refers to "Sample clinical images" that were performed implicitly as part of the validation of the physical coil's performance.

• Sample Size: Not explicitly stated as a number of images or cases. The document mentions "Sample clinical images included in Section 20 Performance Testing - clinical."
• Data Provenance: The clinical images were "performed within GE Healthcare facilities." This implies a prospective or controlled retrospective acquisition within GE's own environment for verification purposes. The country of origin is not specified, but GE Healthcare has global operations.

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

Not applicable. This is a hardware device submission, not an AI algorithm submission that requires expert-established ground truth for image interpretation. The verification tests are primarily engineering and safety-related.

4. Adjudication Method for the Test Set

Not applicable. There is no mention of a human-read interpretation or adjudication process for the clinical images in the context of establishing ground truth for an algorithm. The clinical images were used to demonstrate the qualitative performance of the coil.

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. This is a submission for an MRI coil, not an AI-powered diagnostic tool. Therefore, an MRMC study comparing human readers with and without AI assistance is irrelevant to this device.

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

Not applicable. There is no AI algorithm involved in this submission.

7. The Type of Ground Truth Used

For the engineering and safety tests, the "ground truth" is defined by the technical standards (e.g., NEMA standards, IEC standards) and the physical properties and performance characteristics of the coil itself (e.g., signal-to-noise ratio, uniformity, temperature limits, B1 field tolerance). For the clinical images, the "ground truth" is the visual quality and diagnostic utility of the images produced by the coil, implicitly evaluated by GE's internal experts against established image quality criteria, though specific details of this evaluation are not provided in this summary.

8. The Sample Size for the Training Set

Not applicable. There is no AI algorithm or training set discussed in this submission.

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

Not applicable. There is no AI algorithm or training set discussed in this submission.

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The Brivo MR355 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, 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 Brivo MR355 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 modified Brivo MR355 adds (1) one dedicated coil: 4-ch Breast Array Coil: (2) two clinical applications: VIBRANT and 3D FIESTA-C. The coil and clinical applications are standard for predicate Optima MR360 (K103330). All utilize superconducting magnets, gradients, and radio frequency coils and electronics to acquire data in single voxel, two dimensional, or three dimensional datasets. The 1.5T Brivo MR355 features a superconducting magnet at 1:5 Tesla. The data acquisition system operating accommodates up to 8 independent receive channels in various increments, and multiple independent coil elements per channel The system uses a during a single acquisition series. 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 1.5T Brivo MR355 is designed to conform to NEMA DICOM standards (Digital Imaging and Communications in Medicine).

The provided text focuses on the 510(k) Premarket Notification Submission for the GE 1.5T Brivo MR355 Magnetic Resonance Imaging System. It describes the device, its intended use, and its substantial equivalence to a predicate device.

However, the document explicitly states:

"The subject of this premarket submission, GE 1.5T Brivo MR355, did not require clinical studies to support substantial equivalence."

Therefore, the submission does not contain information related to acceptance criteria or a study proving the device meets said criteria. The GE 1.5T Brivo MR355 achieved regulatory clearance based on demonstrating substantial equivalence to an existing predicate device (K103330, GE 1.5T Brivo MR355/Optima MR360) and compliance with medical standards through non-clinical tests (e.g., risk analysis, requirements reviews, design reviews, performance testing, safety testing, internal and external evaluation).

Because no clinical study was required or performed for this specific submission to demonstrate acceptance criteria, the following requested information cannot be provided from the given text:

1. A table of acceptance criteria and the reported device performance: Not applicable as no such study was conducted.
2. Sample size used for the test set and the data provenance: Not applicable.
3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts: Not applicable.
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, as this is an MR imaging device, not an AI-assisted diagnostic tool in the context of this submission.
6. If a standalone (i.e. algorithm only without human-in-the loop performance) was done: Not applicable.
7. The type of ground truth used (expert consensus, pathology, outcomes data, etc.): Not applicable.
8. The sample size for the training set: Not applicable.
9. How the ground truth for the training set was established: Not applicable.

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The Brivo MR355/ Optima MR360 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, 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 Brivo MR355/ Optima MR360 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 Brivo MR355 / Optima MR360 is a new MR system that is similar in design to previous GE Healthcare 1.5T MR systems. All utilize superconducting magnets, gradients, and radio frequency coils and electronics to acquire data in single voxel, two dimensional, or three dimensional datasets. The 1.5T Brivo MR355 / Optima MR360 features a superconducting magnet operating at 1.5 Tesla. The data acquisition system accommodates up to 8 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 1.5T Brivo MR355 / Optima MR360 is designed to conform to NEMA DICOM standards (Digital Imaging and Communications in Medicine).

The provided text is for a GE Brivo MR355/Optima MR360 510(k) Premarket Notification and does not describe acceptance criteria for an AI/ML powered device, nor does it detail a study proving its performance against such criteria. The document is for a traditional Magnetic Resonance Diagnostic Device.

Therefore, many of the requested categories (e.g., sample size for test set, number of experts for ground truth, adjudication method, MRMC study, training set sample size, how training ground truth was established) are not applicable to the provided information.

However, I can extract the performance parameters that were tested for this device, which can be interpreted as its "acceptance criteria" in the context of it being a new MR system demonstrating substantial equivalence to predicate devices.

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

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

The document mentions "Clinical images collected by volunteer scanning," indicating a prospective collection method using volunteers. No specific numerical sample size (number of volunteers or images) is given, nor is the country of origin of the data specified.

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)

This information is not provided. The document states that the images, when "interpreted by a trained physician yield information that may assist in diagnosis," but it does not detail an expert review process for establishing ground truth as one might for an AI/ML study.

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

This information is not provided in the document.

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 MRMC comparative effectiveness study was not described. This document pertains to a new MR imaging system, not an AI/ML algorithm intended to assist human readers.

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

This concept is not applicable as the device is an MR scanner, not an AI/ML algorithm. The performance tests described (SNR, image uniformity, etc.) demonstrate the standalone performance of the MR system itself.

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

For the performance parameters, the "ground truth" implicitly refers to the physical measurements and standards (NEMA, IEC, ISO). For the clinical images, the statement "All images show that the system meets the indications for use" suggests an assessment against clinical expectations or previous interpretations, likely by trained physicians, but the specific type of ground truth (e.g., expert consensus on specific findings, pathology correlation) is not detailed.

8. The sample size for the training set

The concept of a "training set" is not applicable as this is a traditional MR imaging device, not an AI/ML model that undergoes a training phase.

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

Not applicable.

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