(171 days)
Vantaqe Titan 3T systems are indicated for use as a diagnostic imaging modality that produces cross-sectional 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 maqnetic 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
Contrast aqent use is restricted to the approved druq indications. When interpreted by a trained physician, these imaqes yield information that can be useful in diagnosis.
The Vantage Titan 3T (Model MRT-3010/A5) is a 3 Tesla Magnetic Resonance Imaging (MRI) System and was cleared under K132160. This submission includes WFS (Water Fat Separation) software functionality and the optional subsystem, Saturn Gradient Option.
The provided text is a 510(k) summary for the Toshiba Medical Systems Corporation's Vantage Titan 3T Magnetic Resonance Imaging (MRI) System. This submission is for modifications to an already cleared device, specifically adding WFS (Water Fat Separation) software functionality and an optional Saturn Gradient Option. The document primarily focuses on demonstrating substantial equivalence to a predicate device rather than providing a detailed study proving the new features meet specific clinical acceptance criteria.
However, I can extract information related to acceptance criteria and the type of study conducted for the new features, even if it doesn't detail specific performance metrics against clinical thresholds.
Here's a breakdown of the requested information based on the provided text:
1. Table of Acceptance Criteria and Reported Device Performance
The document does not provide a table of acceptance criteria with specific quantitative thresholds for clinical performance or corresponding reported device performance metrics for the WFS software functionality or the Saturn Gradient Option.
Instead, the submission states:
- "This testing demonstrated that the software performed as specified and did not raise new issues of safety and effectiveness."
- "The additional software packages are work flow improvements and their performance was demonstrated to be equal to or better than the current methods for obtaining the same results."
These statements indicate that the "acceptance criteria" for these new features were likely focused on:
- Functionality: The WFS software correctly separates water and fat images as intended.
- Safety: No new safety concerns are introduced by the changes.
- Equivalence/Non-inferiority: Performance is at least as good as, or better than, existing methods or the predicate device's performance for the same tasks.
2. Sample Size Used for the Test Set and Data Provenance
- Test Set Sample Size: The document only mentions "representative volunteer images" for the WFS software functionality. No specific number for the volunteer images or phantom studies is provided.
- Data Provenance: Not explicitly stated, but typically, testing for such devices is conducted by the manufacturer, often using their own facilities or clinical partners. The country of origin for the manufacturing site is Japan. The nature of the study (retrospective/prospective) is not specified, but for new feature validation, it would typically involve prospective data acquisition.
3. Number of Experts Used to Establish the Ground Truth for the Test Set and Qualifications of Those Experts
The document does not specify the number of experts used or their qualifications for establishing ground truth for the "representative volunteer images" or phantom studies. However, the "Indications for Use" section mentions that images are "interpreted by a trained physician," implying that expert interpretation is crucial for diagnostic use. For the validation of image quality, typically radiologists or other medical imaging specialists would be involved.
4. Adjudication Method for the Test Set
The document does not describe any specific adjudication method (e.g., 2+1, 3+1) for evaluating the test set for the new features.
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
This submission is for an MRI system with new software features, not an AI-assisted diagnostic tool. Therefore, an MRMC comparative effectiveness study regarding human reader improvement with/without AI assistance is not applicable and was not performed. The "WFS (Water Fat Separation)" functionality is an image processing technique, not an AI interpretation tool.
6. If a Standalone (i.e. algorithm only without human-in-the-loop performance) was done
Yes, in a sense. The testing for the WFS software itself, particularly the "phantom studies," would constitute an evaluation of the algorithm's performance in a standalone manner, assessing its ability to correctly separate water and fat signals. The "representative volunteer images" would also assess the algorithm's performance on human data, but the evaluation of these images would implicitly involve a human observer (e.g., to confirm visual quality and separation). The document states, "This testing demonstrated that the software performed as specified," implying that the software's output was directly evaluated.
7. The Type of Ground Truth Used
- Phantom Studies: For phantom studies, the ground truth is typically known and engineered into the phantom itself (e.g., known fat/water ratios in different compartments). This provides an objective measure of the algorithm's accuracy in separating these components.
- Volunteer Images: For "representative volunteer images," the ground truth would likely be established through visual assessment by experts (e.g., confirming clear water/fat separation, absence of artifacts, and diagnostic quality) or potentially by comparing with established imaging sequences known to provide good fat/water separation. Pathology or outcomes data would not be the direct ground truth for this type of image processing feature.
8. The Sample Size for the Training Set
The document does not provide any information about a training set since the WFS functionality and gradient option are described as "software functionality" and "optional subsystem" being added to an existing, cleared MRI system. It does not suggest these features involved a machine learning model that required a specific training set in the conventional sense. If the WFS algorithm development involved any iterative refinement, details are not provided here.
9. How the Ground Truth for the Training Set Was Established
As no training set is described for a machine learning model, this question is not applicable based on the provided text.
§ 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.