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The Signa Magnetic Resonance System is a whole body scanner. The Signa Magnetic Resonance System is indicated for use as a diagnostic imaging device to produce transverse, sagittal, coronal and oblique images of the internal structures of the head or body. The images produced by the Signa Magnetic Resonance System reflect the spatial distribution of protons (hydrogen nuclei) exhibiting magnetic resonance. The NMR properties that determine the image appearance are proton density, spin-lattice relaxation time (T1), spin-spin relaxation time (T2) and flow. When interpreted by a trained physician, these images provide information that can be useful in determining a diagnosis.

ASSET (Array Spatial Sensitivity Encoding Technique) is an image reconstruction technique used in A conjunction with phased array coils in which the number of phase encode steps is reduced by increasing the distance between steps, or equivalently, by reducing the field of view. Aliasing or wrapping caused by the object extending outside the reduced field of view is eliminated using knowledge of the B1 fields of the coils.

The provided 510(k) summary for the GE Signa ASSET Imaging Option primarily focuses on demonstrating substantial equivalence to predicate devices and detailing the reconstruction technique. It does not contain information about specific acceptance criteria, a detailed study proving performance against those criteria, or the typical elements of a modern AI/device performance study.

Here's an analysis based on the provided document:

1. Table of Acceptance Criteria and Reported Device Performance

This information is not provided in the document. The submission states "Evaluation testing was done to verify the performance of the option," but it does not specify what those performance metrics were, what the acceptance criteria were, or the results of that evaluation.

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

This information is not provided in the document.

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

This information is not provided in the document.

4. Adjudication Method 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, and the Effect Size of How Much Human Readers Improve with AI vs. Without AI Assistance

This information is not provided in the document. The ASSET Imaging Option is described as an image reconstruction technique, not an AI-assisted diagnostic tool for human readers in the way modern AI devices are studied.

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

The document does not describe a standalone performance study in the modern sense of an algorithm making diagnostic interpretations without human intervention. The ASSET Imaging Option is a component of a diagnostic imaging system, designed to produce images that are then "interpreted by a trained physician" to aid in diagnosis.

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

This information is not provided in the document. Given the description, any "ground truth" would likely relate to the accuracy of the image reconstruction itself rather than diagnostic accuracy.

8. The Sample Size for the Training Set

This information is not provided in the document. The ASSET option is a reconstruction technique, and while it involves software, the concept of a "training set" in the context of machine learning as understood today is not applicable or discussed in this submission from 2001.

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

This information is not provided in the document, as the concept of a training set and its ground truth is not elaborated upon for this type of device and submission from 2001.

Summary of the Study Mentioned in the Document:

The document states: "The ASSET Imaging Option was developed in conformance with design control requirements as specified in 21 C.F.R. 820.30. Software hazard analysis and verification test procedures were completed. Evaluation testing was done to verify the performance of the option."

This indicates that standard design control and verification/validation activities were performed, as required for medical devices. However, the details of these tests (e.g., acceptance criteria, sample sizes, specific performance metrics, and results) are explicitly omitted from this 510(k) summary, as was common practice for submissions of this era, especially for modifications to existing predicate devices related to image acquisition/reconstruction rather than novel diagnostic algorithms. The primary "study" presented is a comparison to predicate devices, asserting substantial equivalence based on intended use and operating modes.

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The Phased Array Knee and Foot Coil is a specialty receive-only RF coil, used for obtaining diagnostic images of the knee and foot anatomy in Magnetic Resonance Imaging systems. The indications for use are the same as for standard MR Imaging. The Phased Array Knee and Foot Coil is designed for use with GE Signa HFO/i (0.7 Tesla) MRI scanner (K992746) manufactured by GE Medical Systems.

The Phased Array Knee and Foot Coil is designed to provide Magnetic Resonance Images of the knee and foot anatomies. The Phased Array Knee and Foot Coil has been designed for use with the GE Signa HFO/i 0.7T scanner.

Anatomic Regions: Knee and Foot Nuclei Excited: Hydrogen

The indications for use are the same as for standard imaging:

The Signa HFO/i 0.7T system is indicated for use as an NMR device that produces images that: (1) correspond to the distribution of protons exhibiting NMR signal, (2) depend upon NMR parameters (proton density, spin lattice relaxation time T1, spin-spin relaxation time T2) and (3) display the soft tissue structure of the head and whole body. When interpreted by a trained physician, these images yield information that can be useful in the determination of a diagnosis.

The Knee and Foot Coil package consists of a knee coil (two sizes: small and large) and an attachable foot coil. The electrical circuitry is enclosed in a durable housing assembly made of polyurethane, fiberglass, and ABS/PVC plastic alloy, which are fire rated and have high impact and tensile strength. The Knee Coil is mechanically split into two halves for easier coil handling and more accurate positioning of the patient's knee in the coil. The Foot Coil is contoured to accommodate the foot and is mechanically attached to the knee coil.

The provided document is a 510(k) summary for the "Legend 5000 Phased Array Knee and Foot Coil," an accessory for Magnetic Resonance Imaging systems, and does not describe a study that proves the device meets specific performance acceptance criteria in the way a clinical study for a new AI diagnostic would.

Instead, the document establishes substantial equivalence to predicate devices based on similarities in intended use, indications for use, materials, design, and safety features. The "Safety and Effectiveness" section outlines product features and compares them to legally marketed predicate devices, implying that if the new device shares similar characteristics and functions, it is considered safe and effective for its stated purpose.

Therefore, the requested information elements (acceptance criteria, reported performance, sample sizes, expert qualifications, adjudication, MRMC studies, standalone performance, ground truth types, and training set details) are not applicable or not explicitly stated in this type of regulatory submission for an MRI accessory. This document focuses on demonstrating equivalence rather than proving performance against specific quantitative metrics through a clinical study.

Here's a breakdown of why these elements are largely absent or not directly addressed:

• Acceptance Criteria & Reported Performance: This document doesn't define specific numerical acceptance criteria for diagnostic accuracy (e.g., sensitivity, specificity, AUC) or report quantitative performance metrics related to image quality or diagnostic yield for the coil itself. The acceptance is based on the comparison to predicate devices and the general understanding that it produces diagnostic images similar to standard MR imaging.
• Sample Size (Test Set) & Data Provenance: Not applicable. There's no "test set" of patient data in the context of a diagnostic AI study. The performance is inferred from the device's design and mechanism mirroring existing approved devices.
• Number of Experts & Qualifications (Ground Truth): Not applicable. Ground truth as understood in diagnostic AI (e.g., expert consensus on disease presence) is not established or used here. The document relies on the established safety and efficacy of the predicate MRI systems and coils.
• Adjudication Method: Not applicable.
• Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study: Not applicable. This type of study assesses human reader performance with and without an AI aid, which is not the purpose of this submission for an MRI coil.
• Standalone (Algorithm Only) Performance Study: Not applicable. The device is a hardware accessory (RF coil), not an autonomous diagnostic algorithm.
• Type of Ground Truth Used: Not applicable. No "ground truth" (e.g., pathology, outcomes data) for clinical diagnosis is being established for this device's performance in a study detailed here. The ground truth for MRI imaging, in general, is its ability to visualize anatomical structures and pathologies, which is well-established for the predicate devices.
• Sample Size for Training Set & How Ground Truth for Training Set was Established: Not applicable. This device is not an AI algorithm that undergoes a "training" phase with a dataset.

In summary, the 510(k) approval for this MRI accessory is granted based on its substantial equivalence to previously cleared devices, rather than a clinical study demonstrating performance against specific quantitative acceptance criteria. The "studies" that support its safety and effectiveness are primarily engineering and design comparisons to predicate devices, ensuring that it operates within known safety parameters and produces images compatible with diagnostic interpretations already established for MRI.

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