(48 days)
Vantage Elan 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 Elan (Model MRT-2020) is a 1.5 Tesla Magnetic Resonance Imaging (MRI) System, previously cleared under K171597. 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. The Vantage Elan uses 1.4m short and 4.1 ton light weight magnet. It includes the Pianissimo™ Σ technology (scan noise reduction technology). The design of the gradient coil and the whole body coil of the Vantage Elan provides the maximum field of view of 55 x 50 cm. The Model MRT-2020/A1 is without secondary cooling system and the Model MRT-2020/A2 is with secondary cooling system.
The document describes the acceptance criteria and supporting studies for the Vantage Elan 1.5T, MRT-2020, V6.0 MRI System, specifically regarding new software functionalities and sequence enhancements.
1. Table of Acceptance Criteria and Reported Device Performance
The document does not provide a specific table of quantitative acceptance criteria with corresponding performance metrics for each new feature. Instead, it describes general conclusions after evaluation.
Here's a summary derived from the text:
| Feature Evaluated | Acceptance Criteria (Implied) | Reported Device Performance |
|---|---|---|
| T2 Map Using Pre-Contrast Pulses | T2 maps can be accurately generated from acquired data. | "It was concluded that T2 maps can be generated using the data acquired using pre-contrast pulses." |
| WFS DIXON (Water Fat Separation) | Water and fat signals are effectively separated. | "Testing verified that water signals and fat signals are separated in the water image and the fat image, respectively." |
| 2D-RMC (Real Time Motion Correction) for EPI | Effective mitigation of motion artifacts during scanning. | "Testing verified the use of 2DRMC in scanning with SEEPI2D sequence is effective." |
| SpineLine+, KneeLine+, surevol Knee, Quick Star, Fast 3D mode | Features work as intended, and images are of diagnostic quality; test results meet predetermined acceptance criteria. | "It was confirmed that these features worked as intended, the images were of diagnostic quality, and the test results met predetermined acceptance criteria." |
2. Sample Size Used for the Test Set and Data Provenance
The document mentions the use of "phantom and volunteer images" for the evaluation of T2 Map, WFS DIXON, and 2D-RMC. For SpineLine+, KneeLine+, surevol Knee, Quick Star, and Fast 3D mode, "volunteer images" were utilized.
- Sample Size (Test Set): Not explicitly stated with specific numbers of phantoms or volunteers.
- Data Provenance: Not specified (e.g., country of origin). The studies appear to be prospective as they were conducted for the purpose of verifying the new functionalities.
3. Number of Experts Used to Establish Ground Truth for the Test Set and Their Qualifications
This information is not provided in the document. The evaluations are described as "testing verified" or "it was concluded/confirmed," but there is no mention of expert involvement in establishing ground truth for the test images.
4. Adjudication Method for the Test Set
The document does not specify any adjudication method for the test set.
5. Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study
There is no mention of an MRMC comparative effectiveness study being performed, nor any effect size information regarding human reader improvement with or without AI assistance. The document focuses on the technical performance and diagnostic quality of the new features.
6. Standalone (Algorithm Only) Performance
The document describes the evaluation of software functionalities and sequence enhancements, implying standalone performance evaluation for these features. For instance, "testing verified that water signals and fat signals are separated" for WFS DIXON and "it was concluded that T2 maps can be generated" for T2 Map using pre-contrast pulses. These statements refer to the direct output and functionality of the algorithms/sequences.
7. Type of Ground Truth Used
Based on the descriptions:
- For WFS DIXON and T2 Map: The ground truth appears to be based on the expected physical and technical outcomes (e.g., successful separation of water/fat, generation of T2 maps). This would likely involve expert evaluation of the image output against expected results, potentially using quantitative metrics.
- For 2D-RMC and other imaging features (SpineLine+, KneeLine+, etc.): The ground truth is implied to be visual assessment of diagnostic image quality and confirmation that the features "worked as intended." This would likely involve expert radiologists/technicians evaluating the images to ensure they are free of artifacts, properly positioned, and diagnostically usable. It's an expert consensus or clinical utility assessment of the generated images, rather than a comparison to a definitive pathology report or outcome data.
8. Sample Size for the Training Set
The document does not provide any information regarding the sample size for a training set. Given that these are software functionalities for an MRI system, rather than an AI-driven diagnostic algorithm, direct "training data" in the typical machine learning sense might not be explicitly used or reported in this context. The functions like SpineLine+ or KneeLine+ could use pre-programmed anatomical models or algorithms rather than statistical learning from a large, labeled dataset in the way a CAD system would.
9. How the Ground Truth for the Training Set Was Established
As no training set is mentioned (see point 8), there is no information on how its ground truth would have been established.
§ 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.