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510(k) Data Aggregation
(81 days)
Magnetic resonance imaging (MRI) and magnetic resonance angiography (MRA) of the Head: Magical lobes (hippocampus), internal auditory canals, orbits and anterior optic pathways, I chiporal loocs (inppooaliffalo), interesonance angiography (MRA). Upper Neck: Skull base, Cranio-cervical junction, cervical carotid artery. Upper Extremities: Shoulder, Craino-cavicular (AC) joint, elbow, peripheral nerves. Lower Extremities: Knee, ankle and Achilles tendon, foot. Pediatric applications.
Model 235GE-64: Multi Purpose Flex Array Coil. Compatible with GE Signa 1.5T MRI systems with Phased Array option.
The provided documentation details a 510(k) summary for the Model 235GE-64: Multi Purpose Flex Array Coil, a magnetic resonance specialty coil. This submission aims to demonstrate substantial equivalence to legally marketed predicate devices, primarily focusing on safety and imaging performance.
Here's an analysis of the acceptance criteria and the study characteristics:
1. Table of Acceptance Criteria and Reported Device Performance
The acceptance criteria for the Model 235GE-64 coil are based on demonstrating "no change" compared to the predicate device when used in conjunction with the GE 1.5T Signa MRI system. This implies that the device's performance should be equivalent to that of the predicate, and not degrade the existing system's capabilities.
Parameter | Acceptance Criteria (Expected Performance) | Reported Device Performance (with Model 235GE-64 Coil) |
---|---|---|
Safety Parameters | ||
Maximum Static Magnetic Field | No change from predicate | No change |
Rate of Magnetic Field Change | No change from predicate | No change |
RF Power Deposition | No change from predicate | No change |
Acoustic Noise Levels | No change from predicate | No change |
Biocompatibility | No change from predicate | No change |
Imaging Performance Parameters | ||
Specification Volume | No change from predicate | No change |
Signal-to-Noise Ratio | No change from predicate | No change |
Image Uniformity | No change from predicate | No change |
Geometric Distortion | No change from predicate | No change |
Slice Thickness and Gap | No change from predicate | No change |
High Contrast Spatial Resolution | No change from predicate | No change |
2. Sample Size Used for the Test Set and Data Provenance
The document does not specify the sample size used for any test set (e.g., number of patients, number of images). It also does not provide information on data provenance (e.g., country of origin, retrospective or prospective nature). The evaluation appears to be based on engineering and performance testing against established MRI system specifications rather than clinical data from a specific test set.
3. Number of Experts Used to Establish Ground Truth and Qualifications
The document does not mention the involvement of experts to establish a ground truth for a test set. This type of FDA submission (510(k) for a coil) typically relies on technical specifications and comparisons rather than expert-derived ground truth from a clinical study.
4. Adjudication Method for the Test Set
As no specific test set requiring expert ground truth is described, there is no mention of an adjudication method.
5. Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study
A Multi-Reader Multi-Case (MRMC) comparative effectiveness study was not performed or described in this 510(k) summary. The study focuses on the coil's technical performance and safety equivalence, not on comparing human reader performance with and without AI assistance.
6. Standalone (Algorithm Only) Performance Study
This device is a magnetic resonance imaging coil, not an AI algorithm. Therefore, a standalone (algorithm only) performance study was not performed.
7. Type of Ground Truth Used
The "ground truth" for this submission is implicitly the performance specifications and safety limits of the predicate MRI system and its existing coils. The goal is to demonstrate that the new coil does not degrade these established parameters. There is no mention of pathology, outcome data, or expert consensus used as ground truth in a clinical sense.
8. Sample Size for the Training Set
Since this is a physical medical device (an MRI coil) and not an AI algorithm, there is no concept of a "training set" in the context of machine learning.
9. How the Ground Truth for the Training Set Was Established
As there is no training set, this question is not applicable.
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