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510(k) Data Aggregation
(32 days)
MODIFICATION TO SUPEROPEN 0.23T, MODEL NAM-P023A
The Superopen 0.23T(Modified) is intended to produce images that 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 (T), 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.
The Superopen 0.23T(Modified) is an imaging device, and is intended to provide the physician with indications for use. The system obtains images non-invasively and without the use of ionizing radiation. The MRI 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 MRI 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 diagnosis determination.
The Superopen 0.23T(Modified) is a 0.35T permanent magnet MRI system. The magnet is mainly made of NdFeB material. The system software based on Windows (TM) is an interactive program with user-friendly interface. Its functions cover scanning control, image reconstruction and image/archive management and maintenance.
This document is a 510(k) summary for the Superopen 0.23T (Modified) Magnetic Resonance Diagnostic Device. It outlines the general information, intended uses, device description, and its substantial equivalence to a predicate device.
It's important to note that this 510(k) pertains to a magnetic resonance imaging (MRI) system, which is a diagnostic imaging device that produces images based on physical properties (proton distribution, relaxation times, flow). The context of this document is a regulatory submission for a medical device that generates images, not an AI or software device that analyzes images to provide a diagnosis or finding.
Therefore, the requested information about "acceptance criteria and the study that proves the device meets the acceptance criteria" in the context of an AI/software device performance (e.g., sensitivity, specificity, FROC, reader studies) is not directly applicable to this 510(k) submission for an MRI hardware system.
This 510(k) submission focuses on demonstrating the substantial equivalence of the modified MRI system to its predicate device, primarily through technical specifications, safety standards, and performance that is comparable to the predicate. It does not present clinical studies with specific performance metrics like sensitivity or specificity against a ground truth for diagnostic accuracy, as those are typically assessed for AI algorithms that interpret images.
However, I can extract information related to the device's technical specifications and how its performance is established to meet regulatory requirements through compliance with recognized standards.
No. 1 & No. 6: Table of Acceptance Criteria and Reported Device Performance / Standalone Performance
Since this is an MRI hardware system and not an AI algorithm, the concept of "acceptance criteria" and "reported device performance" are primarily related to its technical specifications, safety, and image quality for general diagnostic use, rather than specific disease detection metrics. The document asserts substantial equivalence to the predicate device (K033315: Superopen 0.23T).
The "performance" of an MRI system is typically demonstrated through:
- Compliance with recognized standards: This ensures safety and fundamental operational characteristics.
- Image quality assessment: This is typically done through phantom studies and clinical examples to show the system can produce diagnostically acceptable images.
- Demonstration of intended capabilities: Showing it can perform various imaging sequences and image different anatomical regions.
Therefore, a direct table of "acceptance criteria" with numerical performance metrics like sensitivity/specificity for a specific diagnostic task is not present in this document because it's not a diagnostic AI/software. Instead, the document implies that the device performs equivalently to the predicate by meeting safety standards and having comparable technical capabilities.
Implied "Acceptance Criteria" (based on the document's content):
| Acceptance Criteria Category | Description | Reported Device Performance/Evidence in Document |
|---|---|---|
| Intended Use | Ability to produce images reflecting spatial distribution of protons, useful for diagnosis by a trained physician. | "The Superopen 0.23T(Modified) is intended to produce images that reflect the spatial distribution of protons (hydrogen nuclei) exhibiting magnetic resonance." |
| "When interpreted by a trained physician, these images provide information that can be useful in determining a diagnosis." | ||
| Substantial Equivalence | Device is comparable in type and substantially equivalent to predicate device (Superopen 0.23T, K033315) in technology and intended uses. | "The Superopen 0.23T(Modified) is of comparable type and substantially equivalent to the Superopen 0.23T (K033315) in that they are similar in technology and intended uses." |
| Safety Standards | Compliance with relevant electrical and medical device safety standards. | Listed Applicable Standards: IEC60601-1, IEC60601-2-33, 21 CFR Subchapter J, IEC60825-1, DICOM 3.0, NEMA MS Series (MS1-MS8). |
| Technical Specifications | Open-permanent-magnet system, 0.35T magnet, Gradient Subsystem, RF Subsystem, Windows-based software, 2D/3D image production, various imaging capabilities (e.g., SE, STIR, FLAIR, FE, FSE, MRA, EPI, Diffusion). | Device Description and Imaging Capabilities section details these features, confirming that the modified device has these core technical capabilities, similar to the predicate. |
| Anatomical Regions | Capable of imaging Head, Body, Spine, Extremities. | Explicitly stated in "Indications for use" table. |
| Diagnostic Uses | Capable of T1, T2, proton density weighted imaging, Diffusion weighted imaging, MR Angiography, and imaging processing. | Explicitly stated in "Indications for use" table. |
Since this is an MRI system, a "standalone performance" (like for an AI algorithm) is not applicable in the same way. The device itself is "standalone" in its function as an imaging system, and its performance is assessed by its ability to generate images that meet quality and safety standards, comparable to the predicate.
No. 2, 3, 4, 5, 7, 8, 9:
These questions are geared towards the evaluation of an AI/software diagnostic device's clinical performance, typically involving a test set of cases, ground truth established by experts, and statistical analysis (e.g., sensitivity, specificity, FROC, reader studies).
As this 510(k) is for an MRI hardware system and does not include a clinical performance study demonstrating diagnostic accuracy for specific findings, the document does not provide information for the following points:
- Sample size used for the test set and data provenance: No clinical test set for diagnostic accuracy is described.
- Number of experts used to establish the ground truth: Not applicable, as there's no clinical ground truth for diagnostic performance analysis mentioned.
- Adjudication method: Not applicable.
- Multi-reader multi-case (MRMC) comparative effectiveness study: No such study is mentioned or required for this type of hardware submission.
- Type of ground truth used: Not applicable for a hardware submission focused on substantial equivalence.
- Sample size for the training set: Not applicable, as this is not an AI/ML device that requires a training set for diagnostic classification.
- How the ground truth for the training set was established: Not applicable.
In summary: The provided 510(k) document is for an MRI hardware system (Superopen 0.23T Modified), demonstrating its substantial equivalence to a predicate device (Superopen 0.23T) based on technical features, safety standards compliance, and stated intended uses and capabilities. It does not contain information on clinical performance studies or acceptance criteria typically associated with AI/software diagnostic devices.
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