(77 days)
The 8ch Knee-Foot SPEEDER Coil is intended for use with Toshiba 1.5T MR systems to produce diagnostic images of the knee, wrist, hand, foot and ankle that can be interpreted by a trained physician.
The 8ch Knee-Foot SPEEDER coil is a receive-only, 8-channel phased array coil designed for magnetic resonance imaging (MRI) using the Toshiba 1.5T MR systems. The 8ch Knee-Foot SPEEDER coil is intended to be used for imaging the knee, wrist, hand, foot and ankle. The 8ch Knee-Foot SPEEDER coil is a reusable, non-invasive device with limited exposure with regard to duration of contact with the body. All coil elements are enclosed in a rigid plastic housing which is flame and impact resistant, and has been tested for biocompatibility. The 8ch Knee-Foot SPEEDER coil also includes the comfort pads listed in Table 10-1, which are provided with the coil shipment.
Please note: The provided document is a 510(k) summary for a medical device (an MRI coil), not a clinical study report for an AI/software as a medical device (SaMD). Therefore, much of the requested information regarding acceptance criteria for algorithm performance, human reader studies, ground truth establishment, and training/test set details for AI-driven devices is not directly available in this document.
This document focuses on the coil's physical performance (electrical safety, biocompatibility, SNR, uniformity) and its ability to produce diagnostic images interpretable by a physician, rather than the performance of an AI algorithm interpreting those images.
However, I will extract and infer as much information as possible from the provided text to address your points, acknowledging where the information is not present due to the nature of the device.
This document describes the 8ch Knee-Foot SPEEDER Coil, an 8-channel phased array coil intended for use with Toshiba 1.5T MR systems to produce diagnostic images of the knee, wrist, hand, foot, and ankle. The document is a 510(k) summary demonstrating substantial equivalence to a predicate device.
1. A table of acceptance criteria and the reported device performance
Since this is an MRI coil and not an AI algorithm, the acceptance criteria are related to physical and imaging performance rather than diagnostic accuracy metrics like sensitivity, specificity, or AUC for an AI.
| Acceptance Criteria Category | Specific Criteria (Inferred from text) | Reported Device Performance |
|---|---|---|
| Biocompatibility | Materials in direct/indirect contact with patient tissues must have a history of safe use. | All surface materials have a history of safe use in previously cleared devices. |
| Electrical Safety | Conformity to AAMI/ANSI ES60601-1. | Verified in accordance with AAMI/ANSI ES60601-1. |
| Electromagnetic Compatibility (EMC) | Conformity to IEC 60601-2-33. | Verified in accordance with IEC 60601-2-33. |
| Surface Heating | Measured temperature of the coil surface must not exceed 41°C. | The measured temperature never exceeded 41°C. |
| Signal-to-Noise Ratio (SNR) | Conformity to predetermined acceptance criteria as per NEMA MS 6. | Was found to conform to predetermined acceptance criteria. |
| Image Uniformity | Conformity to predetermined acceptance criteria as per NEMA MS 9. | Was found to conform to predetermined acceptance criteria. |
| Clinical Performance (Image Quality) | Produces diagnostic quality images of the intended anatomies (knee, wrist, hand, foot, ankle) interpretable by a trained physician. | Clinical images from volunteer scanning demonstrated the production of diagnostic quality images. |
2. Sample size used for the test set and the data provenance
- Test Set Sample Size: The document mentions "clinical images from volunteer scanning." It does not specify the number of volunteers or the number of images/imaging exams obtained.
- Data Provenance: The document does not explicitly state the country of origin. It is a US FDA submission, implying the testing likely occurred in a region compliant with US standards, but specific geographic origin of the volunteers/data is not provided. The study was "prospective" in the sense that images were explicitly obtained for the device's performance testing.
3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts
The document states that the images "can be interpreted by a trained physician." It does not specify the number of physicians involved in assessing image quality, nor their qualifications (e.g., specific sub-specialty or years of experience). The assessment appears to be a general determination of "diagnostic quality" rather than a detailed ground truth for specific pathologies.
4. Adjudication method (e.g., 2+1, 3+1, none) for the test set
Not applicable/not specified. The focus is on the coil's ability to produce images, and the assessment of "diagnostic quality" is not described as requiring formal adjudication among multiple readers.
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
Not applicable. This device is an MRI coil, not an AI algorithm. Therefore, no MRMC study involving AI assistance for human readers was performed or reported.
6. If a standalone (i.e., algorithm only without human-in-the-loop performance) was done
Not applicable. This device is an MRI coil, not an AI algorithm.
7. The type of ground truth used (expert consensus, pathology, outcomes data, etc.)
The ground truth for the clinical performance aspect was the qualitative assessment of "diagnostic quality" by a "trained physician." This is not a detailed, pathology-confirmed ground truth, but rather an assessment that the images produced by the coil were fit for their intended diagnostic purpose.
8. The sample size for the training set
Not applicable. This device is an MRI coil. There is no "training set" in the context of machine learning. The images were collected for "performance testing - clinical."
9. How the ground truth for the training set was established
Not applicable, as there is no training set for an AI algorithm.
§ 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.