(23 days)
Vantage Galan 3T systems are indicated for use as a diagnostic imaging modality that produces crosssectional transaxial, coronal, sagittal, and oblique images that display anatomic structures of the head or body. Additionally, this system is capable of non-contrast enhanced imaging, such as MRA.
MRI (magnetic resonance imaging) images correspond to the spatial distribution of protons (hydrogen nuclei) that exhibit nuclear magnetic resonance (NMR). The NMR properties of body tissues and fluids are:
- Proton density (PD) (also called hydrogen density)
- Spin-lattice relaxation time (T1)
- Spin-spin relaxation time (T2)
- Flow dynamics
- Chemical Shift
Depending on the region of interest, contrast agents may be used. When interpreted by a trained physician, these images yield information that can be useful in diagnosis.
The Vantage Galan (Model MRT-3020) is a 3 Tesla Magnetic Resonance Imaging (MRI) System, previously cleared under K220192. This system is based upon the technology and materials of previously marketed Canon Medical Systems and is intended to acquire and display crosssectional transaxial, coronal, sagittal, and oblique images of anatomic structures of the head or body.
This document (K222387) is a Special 510(k) Premarket Notification for a modification to an already cleared device: the Vantage Galan 3T, MRT-3020, V8.0 with AiCE Reconstruction Processing Unit for MR.
This means that the device itself was previously cleared (under K220192) and this submission is for a minor modification: an updated Iterative Motion Correction (IMC) for brain imaging. Therefore, the information provided focuses primarily on the safety and effectiveness of this specific software change relative to the predicate device.
Given this context, the document explicitly states:
- Imaging Performance Parameters: "No change from the previous predicate submission, K220192."
- Indications For Use: "No change from the previous predicate submission, K220192."
This indicates that a comprehensive de novo study proving the device meets all acceptance criteria for a new device was not performed for this specific submission. Instead, the focus is on demonstrating that the modification does not negatively impact existing performance and safety.
However, the document does mention "image quality testing was completed which demonstrated that the subject device meets predetermined acceptance criteria" related to the IMC update. Unfortunately, the specific acceptance criteria and detailed performance from this testing are not explicitly provided in the given text.
Therefore, I cannot fully complete all sections of your request based solely on the provided text, as the detailed information on the original acceptance criteria and validating study for the core device (K220192) is not present here, and only limited information is given for the specific modification in K222387.
Based on the provided text for K222387, here is what can be extracted:
Acceptance Criteria and Study for K222387 (Modification to AiCE IMC)
The provided document (K222387) is a Special 510(k) for a modification to a previously cleared device. Therefore, the "acceptance criteria" and the "study" described here pertain to demonstrating that the modification (updated Iterative Motion Correction for brain imaging) does not compromise the safety and effectiveness of the device as previously cleared. A full, de novo study proving the entire device meets acceptance criteria is not presented, as that would have been part of the original clearance (K220192).
1. Table of Acceptance Criteria and Reported Device Performance
| Acceptance Criteria (for IMC Modification) | Reported Device Performance (Summary from K222387) |
|---|---|
| No degradation in image quality after IMC update. | "image quality testing was completed which demonstrated that the subject device meets predetermined acceptance criteria." Additionally, the purpose of the update was to "provide more consistent results in reducing motion artifacts." |
| Continued compliance with safety parameters (Static field strength, Operational Modes, SAR, dB/dt, Emergency Shutdown). | All safety parameters are "Same" as the predicate device and meet IEC standards (e.g., 4W/kg for whole body SAR). |
| Continued functionality of the device as a diagnostic imaging modality. | No change to the Indications for Use or intended use of the device. |
| Software validation requirements met. | "successful completion of software validation" |
| Risk management activities conducted. | "Risk analysis and verification/validation testing conducted through bench testing are included in this submission." "Risk management activities for this modification are included in this submission." |
Important Note: The specific quantitative metrics for image quality acceptance (e.g., specific SNR values, resolution tests, or qualitative scores) are not detailed in this summary. It states "predetermined acceptance criteria" were met, but doesn't list them.
2. Sample Size Used for the Test Set and Data Provenance
- Test Set Sample Size: Not explicitly stated for the image quality testing related to the IMC update. The document mentions "bench testing" and "image quality testing." It does not specify human subject data for this particular modification.
- Data Provenance: Not explicitly stated. Given it's a modification to an existing product by a Japanese company (Canon Medical Systems Corporation, Japan), the testing would likely have been done internally or with partners. It's unclear if this involved clinical data from specific countries or if it was purely technical/phantom-based testing for the IMC update. The submission type (Special 510(k)) often relies on substantial equivalence to the predicate, meaning extensive new clinical data is often not required for minor modifications.
3. Number of Experts and Qualifications for Ground Truth
- Number of Experts: Not specified.
- Qualifications of Experts: Not specified.
This information would be crucial for a de novo or comparative effectiveness study, but is not detailed for this type of special 510(k) where the primary focus is on the impact of a software change.
4. Adjudication Method for the Test Set
- Adjudication Method: Not specified.
5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study was done
- MRMC Study: No, an MRMC comparative effectiveness study is not described in this document. The submission is for a modification to a reconstruction processing unit, not an AI-assisted diagnostic tool that directly aids human readers in interpretation, but rather a component of the image acquisition/processing chain aiming to improve image quality for diagnostic interpretation. Therefore, a study to measure human reader improvement with/without this AI feature is not applicable in the typical sense for this device.
6. If a Standalone (i.e., algorithm only without human-in-the-loop performance) was done
- Standalone Performance: The document states "image quality testing was completed which demonstrated that the subject device meets predetermined acceptance criteria." This implies some form of standalone performance measurement (e.g., phantom studies, technical image quality metrics) was performed. However, the exact methodology and results are not detailed. The "AiCE Reconstruction Processing Unit" is an algorithm (Artificial intelligence Cleared Engine) that processes images. The IMC update is a part of this algorithm.
7. The Type of Ground Truth Used
- Type of Ground Truth: Not explicitly stated. For "image quality testing" for a reconstruction algorithm, ground truth likely involved:
- Phantoms: Known physical targets with specific properties.
- Technical Metrics: Measurements like Signal-to-Noise Ratio (SNR), Contrast-to-Noise Ratio (CNR), spatial resolution, artifact suppression measured against theoretical ideals or established benchmarks.
- Qualitative Assessment: Visual assessment by experts based on predefined criteria, though a formal adjudication process is not described.
8. The Sample Size for the Training Set
- Training Set Sample Size: Not applicable/Not provided in this document. The AiCE (Artificial intelligence Cleared Engine) is a deep learning reconstruction technology. Any training data for the neural network would have been used during the development phase of the original AiCE algorithm (K220192), not specifically detailed for this software update in K222387. This special 510(k) pertains to a modification to an existing algorithm, not the training of a new one.
9. How the Ground Truth for the Training Set Was Established
- Ground Truth for Training Set: Not applicable/Not provided in this document. As above, this pertains to the initial development of the AiCE algorithm which would have been covered in the K220192 submission.
§ 892.1000 Magnetic resonance diagnostic device.
(a)
Identification. A magnetic resonance diagnostic device is intended for general diagnostic use to present images which reflect the spatial distribution and/or magnetic resonance spectra which reflect frequency and distribution of nuclei exhibiting nuclear magnetic resonance. Other physical parameters derived from the images and/or spectra may also be produced. The device includes hydrogen-1 (proton) imaging, sodium-23 imaging, hydrogen-1 spectroscopy, phosphorus-31 spectroscopy, and chemical shift imaging (preserving simultaneous frequency and spatial information).(b)
Classification. Class II (special controls). A magnetic resonance imaging disposable kit intended for use with a magnetic resonance diagnostic device only is exempt from the premarket notification procedures in subpart E of part 807 of this chapter subject to the limitations in § 892.9.