(141 days)
mDIXON XD is a software option intended for use on Achieva, Ingenia 1.5T & 3T MR Systems. It is indicated for use in Magnetic Resonance Imaging of the human body. mDIXON XD is an enhanced 2-point fat-free mDIXON technology, available for gradient echo and spin echo acquisitions. mDIXON XD enables the combination of a fat-free technology with the MultiVane XD motion-free technique for anatomies such as head. mDIXON XD also enables subtractionless MR Angiography in areas of the body where exogenous contrast media has been approved for MR imaging.
mDIXON XD provides an improved water/fat reconstruction algorithm (7-peak fat modeling, B0correction and fat-shift correction). mDIXON XD relies on the 2-point mDIXON fat-free technology making use of unrestricted echo times and is capable of generating four image contrasts (Water, Fat, In-Phase, Out-Phase) in one scan. mDIXON XD can be used with the following:
- Multivane XD (motion correction) for the head
- MR Angiography (subtractionless MRA), removes the need for the subtraction of the pre-● and post-contrast enhanced images.
- Gradient echo (FFE Fast Field Echo) and turbo spin echo (TSE) sequences to achieve ● efficient fat-free scanning compatibility, even at large FOV or sub-millimetric resolutions
mDIXON XD is supported on the following systems: - 3.0T Ingenia
- 3.0T Achieva ●
- 1.5T Ingenia
- 1.5T Achieva ●
The functionality is supported on all available gradient performance levels. Optimized protocols will be provided for the different performance points. mDIXON XD is supported on the centralized data acquisition systems of the Achieva systems as well as the digitally networked data acquisition system of the Ingenia systems. The data acquisition system is fully transparent to the pulse sequences and mDIXON XD reconstructions.
The provided text is a 510(k) summary for the Philips Medical Systems' mDIXON XD device. It describes the device, its intended use, and provides a brief summary of nonclinical and clinical tests. However, it does not contain specific acceptance criteria, detailed study designs, or quantitative performance metrics as requested in the prompt.
Therefore, I cannot provide a table of acceptance criteria and the reported device performance, nor can I answer questions about sample sizes for test/training sets, data provenance, number/qualifications of experts, or adjudication methods, as this information is not present in the provided document.
Here's what can be extracted based on the document:
1. Table of Acceptance Criteria and Reported Device Performance:
- Acceptance Criteria: Not explicitly stated as quantitative metrics. The document broadly states that the device was "successful" and "passed" clinical user needs.
- Reported Device Performance:
- For total body and head/neck examinations: Image Quality, fat suppression, and fat suppression over large FOV were similar or better with mDIXON XD compared to e-Thrive.
- For cardiac examinations: Image quality and fat suppression were better with mDIXON XD.
- For MultiVane XD in combination with mDIXON TSE: Motion related artifacts were reduced compared to mDIXON TSE alone.
- MultiVane XD with mDIXON XD can be used with T2 in head imaging.
2. Sample size used for the test set and the data provenance:
- Sample Size for Test Set: Not specified.
- Data Provenance: Not specified (e.g., country of origin, retrospective/prospective).
3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts:
- This information is not provided. The term "clinical user needs" suggests clinical evaluation, but details on expert involvement are absent.
4. Adjudication method for the test set:
- Not specified.
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:
- No MRMC comparative effectiveness study involving human readers and AI assistance is described. The comparison is between mDIXON XD and existing technologies (e-Thrive, mDIXON TSE alone).
6. If a standalone (i.e. algorithm only without human-in-the loop performance) was done:
- The testing described is on the "device" as a whole, which is a software option for MR systems. It's an "algorithm only" performance in the sense that it evaluates the output of the software. However, it's not a standalone AI device in the modern sense of a diagnostic AI assisting or replacing a human. The clinical validation assesses image quality and artifact reduction.
7. The type of ground truth used:
- The "ground truth" implicitly used is expert judgment and assessment of "Image Quality," "fat suppression," and "motion related artifacts" as perceived by "clinical user needs." It's based on subjective clinical assessment rather than objective pathology or outcomes data.
8. The sample size for the training set:
- Not specified. The document describes verification and validation but does not detail a separate training set, suggesting this is a software update/feature validation rather than a deep learning algorithm that requires a distinct training phase.
9. How the ground truth for the training set was established:
- Neither a training set nor its ground truth establishment is mentioned.
§ 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.