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510(k) Data Aggregation
(23 days)
Magnetic resonance imaging (MRI) and magnetic resonance angiography (MRA) of the cervical spine, soft tissue and vascular structures of the neck.
Model 125GE-64 Phased Array Cervical Spine Coil. Compatible with GE Signa 1.5T MRI systems with Phased Array option.
The provided 510(k) summary for the Model 125GE-64 Phased Array Cervical Spine Coil does not contain a study that demonstrates the device meets specific acceptance criteria in the manner typically found for AI/ML-enabled devices or those requiring performance validation against numerical targets. Instead, the submission focuses on substantial equivalence to predicate devices.
The acceptance criteria here are implicitly met by demonstrating that the new device does not negatively alter the performance of the integrated MRI system compared to the predicate devices. The "study" in this context is the submission of data demonstrating that various safety and imaging performance parameters remain unchanged when the new coil is used.
Here's a breakdown of the requested information based on the provided text:
1. Table of Acceptance Criteria and Reported Device Performance
Acceptance Criteria (Stated as "No Change" from predicate) | Reported Device Performance (with Model 125GE-64) |
---|---|
Safety Parameters: | |
Maximum Static Magnetic Field: No change | No change |
Rate of Magnetic Field Strength Change: No change | No change |
RF Power Deposition: No change | No change |
Acoustic Noise Levels: No change | No change |
Imaging Performance Parameters: | |
Specification Volume: No change | No change |
Signal-to-Noise Ratio: No change | No change |
Image Uniformity: No change | No change |
Geometric Distortion: No change | No change |
Slice Thickness and Gap: No change | No change |
High Contrast Spatial Resolution: No change | No change |
2. Sample Size Used for the Test Set and Data Provenance
The document does not specify a distinct "test set" in the context of a clinical performance study with a defined sample size. The evaluation relies on demonstrating "no change" in performance and safety parameters, which typically involves engineering measurements and comparisons rather than a clinical dataset. Therefore, sample size for a test set is not applicable or provided in this type of submission.
Data Provenance: Not explicitly stated as a separate clinical study. The data provenance would be from the engineering and safety testing performed by the manufacturer, Medical Advances, Inc., likely on their integrated MRI system (GE 1.5T Signa MRI system with the coil).
3. Number of Experts Used to Establish Ground Truth for the Test Set and Qualifications
Not applicable. This submission focuses on engineering and safety equivalence, not a clinical study requiring expert ground truth establishment for diagnostic accuracy or similar clinical performance.
4. Adjudication Method for the Test Set
Not applicable. No clinical test set or adjudication process is described.
5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study Was Done
No. No MRMC comparative effectiveness study is mentioned. This type of study is more common for AI/ML devices or those claiming improved diagnostic performance over human readers, which is not the case for this MRI coil submission focused on substantial equivalence.
6. If a Standalone (i.e., algorithm only without human-in-the-loop performance) Was Done
Not Applicable. This is an MRI coil, a hardware component, not an algorithm. Therefore, "standalone" performance in the context of an algorithm is not relevant. The coil's performance is demonstrated within the context of the overall MRI system.
7. The Type of Ground Truth Used
The "ground truth" in this context is established by the engineering specifications and performance characteristics of the predicate devices and the GE 1.5T Signa MRI system. The manufacturer demonstrated that the new coil, when integrated, maintained these established characteristics. Thus, it's essentially an engineering and safety specifications comparison.
8. The Sample Size for the Training Set
Not applicable. This is a hardware device; there is no "training set" in the sense of machine learning.
9. How the Ground Truth for the Training Set Was Established
Not applicable. As there is no training set, this question is not relevant.
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