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510(k) Data Aggregation
(111 days)
ECHELON Oval V 5.1 MRI System
The ECHELON Oval MRI System is an imaging device, and is intended to provide the physician with physiological and clinical information, obtained non-invasively and without the use of ionizing radiation. The MR system produces transverse, coronal, sagittal, oblique, and curved cross-sectional images that display the internal structure of the head, body, or extremities. The images produced by the MR 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 (TI), spin-spin relaxation time (T2), and flow. When interpreted by a trained physician, these images provide information that can be useful in diagnosis determination.
The ECHELON OVAL V5.1 is a Magnetic Resonance Imaging System that utilizes a 1.5 Tesla superconducting magnet in a gantry design. The design was based on the ECHELON MRI system. The ECHELON OVAL has been designed to enhance clinical utility as compared to the ECHELON by taking advantage of open architecture.
This FDA 510(k) summary for the ECHELON Oval V5.1 MRI System does not contain acceptance criteria or a study proving the device meets acceptance criteria in the format often seen for AI/ML-driven devices. Instead, this document focuses on demonstrating substantial equivalence to a previously cleared predicate device (ECHELON Oval V5.0 MRI System K151015).
In the context of a 510(k) for an MRI system, acceptance criteria are typically related to the physical and performance characteristics of the imaging system itself, rather than diagnostic accuracy like in AI/ML products. The 'studies' conducted here are primarily verification and validation tests to ensure the modified device meets established safety and performance standards equivalent to the predicate.
Given these limitations from the provided text, I will answer based on the information available and point out what is missing or not applicable.
1. A table of acceptance criteria and the reported device performance
The document does not explicitly state "acceptance criteria" and "reported device performance" in a table for diagnostic accuracy, as it's not an AI/ML diagnostic device with performance metrics like sensitivity/specificity.
However, the closest equivalent in this document would be the comparison of technical specifications against established standards and the predicate device. The "Performance Evaluation" section (Page 5) states: "There is no change from the previous predicate device that would affect performance." This implies that the performance of the ECHELON Oval V5.1 MRI System is expected to be equivalent to the ECHELON Oval V5.0 MRI System (K151015) which successfully met its own performance criteria (not detailed in this document).
The "Summary of Non-Clinical Testing" (Page 9) lists the standards that the device conforms to. These standards effectively act as the "acceptance criteria" for the MRI system's physical and technical performance. The "reported device performance" implicitly matches these standards by stating conformance.
Acceptance Criteria (Standards Conformed To) | Reported Device Performance (Implicitly Met) |
---|---|
NEMA MS 1-2008 (Signal-to-noise Ratio) | Conforming |
NEMA MS 2-2008 (Two-Dimensional Geometric Distortion) | Conforming |
NEMA MS 3-2008 (Image Uniformity) | Conforming |
NEMA MS 4-2010 (Acoustic Noise Measurement) | Conforming (58 dBA, 125 dBA, 117 dBA) |
NEMA MS 5-2010 (Slice Thickness) | Conforming |
NEMA MS 8-2008 (Specific Absorption Rate) | Conforming |
AAMI / ANSI ES60601-1:2005 (Basic Safety and Essential Performance) | Conforming |
IEC 60601-1-2 Ed. 3:2007-03 (Electromagnetic Compatibility) | Conforming |
IEC 60601-2-33 Ed. 3.1 2013-04 (Magnetic Resonance Equipment specific reqs) | Conforming |
IEC 62304 Ed. 1 2006-05 (Medical Device Software - Life Cycle Processes) | Conforming |
Soft Sound functionality (Acoustic sound pressure levels) | Test results confirm acoustic levels |
2. Sample sized used for the test set and the data provenance (e.g. country of origin of the data, retrospective or prospective)
This information is not provided in the document. The document primarily focuses on technical comparisons and conformance to standards, not a clinical study on diagnostic performance with a test set of patient data.
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 and is not applicable in this context. Ground truth establishment by experts for specific diagnostic outcomes is typical for AI/ML device evaluations, not for demonstrating substantial equivalence of a new MRI system version. The "Indications for Use" mentions interpretation by a "trained physician," but this is general usage, not specific to a testing ground truth.
4. Adjudication method (e.g. 2+1, 3+1, none) for the test set
This information is not provided and is not applicable for this type of submission.
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
An MRMC study was not done. This type of study is relevant for evaluating the clinical utility and impact of AI software on human reader performance, which is not the focus of this MRI system's 510(k) submission.
6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done
A standalone performance evaluation of an algorithm was not done. This device is an MRI system, not an AI algorithm. Its performance is evaluated through its adherence to technical standards and demonstration of equivalence to its predicate.
7. The type of ground truth used (expert consensus, pathology, outcomes data, etc)
The concept of "ground truth" (e.g., pathology, expert consensus) as used in AI/ML evaluations is not applicable here. The "ground truth" for an MRI system's performance revolves around its ability to accurately and safely generate images according to its technical specifications and relevant industry standards. The summary of non-clinical testing refers to conformance with NEMA and IEC standards, which define objective measures for image quality (SNR, geometric distortion, uniformity, slice thickness), safety (acoustic noise, SAR), and software processes.
8. The sample size for the training set
This information is not provided as this is an MRI system, not an AI/ML device trained on a dataset.
9. How the ground truth for the training set was established
This information is not provided as this is an MRI system, not an AI/ML device.
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