(28 days)
The Swoop® Portable MR Imaging System is a bedside magnetic resonance imaging device for producing images that display the internal structure of the head where full diagnostic examination is not clinically practical. When interpreted by a trained physician, these images provide information that can be useful in determining a diagnosis.
The Swoop® system is a portable MRI device that allows for patient bedside imaging. The system enables visualization of the internal structures of the head using standard magnetic resonance imaging contrasts. The main interface is a commercial off-the-shelf device that is used for operating the system, providing access to patient data, exam setup, exam execution, viewing MRI image data for quality control purposes, and cloud storage interactions. The system can generate MRI data sets with a broad range of contrasts. The Swoop® system user interface includes touch screen menus, controls, indicators, and navigation icons that allow the operator to control the system and to view imagery. The Swoop® System image reconstruction algorithm utilizes deep learning to provide improved image quality for T1W, T2W, and FLAIR sequences, specifically in terms of reductions in image noise and blurring.
This subject device in this submission includes modified pulse sequence options and an enhancement to the existing noise correction feature to remove residual line noise.
The information provided describes the Swoop® Portable MR Imaging System and its substantial equivalence to a predicate device, focusing on non-clinical performance testing. Here's a breakdown of the requested information:
1. Table of Acceptance Criteria and Reported Device Performance
The document details the types of testing performed rather than specific numerical acceptance criteria and performance metrics. However, it states that the device "passed all the testing in accordance with internal requirements and applicable standards to support substantial equivalence."
| Test Category | Acceptance Criteria (Implied) | Reported Device Performance |
|---|---|---|
| Software Verification | Advanced reconstruction models do not alter image features or introduce artifacts. Image quality with advanced reconstruction is acceptable. Basic software functionality is unchanged between releases. No significant cybersecurity vulnerabilities. | Device passed testing to verify: |
- Advanced reconstruction models do not alter image features or introduce artifacts.
- Image quality with advanced reconstruction is acceptable.
- Basic software functionality is unchanged between releases.
- NESSUS scan found no significant vulnerabilities. |
| Image Performance | Meets all image quality criteria defined by applicable standards (NEMA MS 1, 3, 9, 12, ACR Phantom Test Guidance, ACR standards for named sequences). | Device passed testing to verify image performance meets all image quality criteria. |
| Software Validation| Device meets user needs and performs as intended. | Validation studies confirmed the device meets user needs and performs as intended. |
| Cybersecurity | Cybersecurity controls and management are effective. | Testing verified cybersecurity controls and management. |
2. Sample Size Used for the Test Set and Data Provenance
The document does not specify a separate "test set" in the context of clinical data for evaluating the advanced reconstruction algorithm. The performance evaluation appears to be based on non-clinical phantom testing and software verification/validation. Therefore, information regarding sample size for a test set and data provenance (e.g., country of origin, retrospective/prospective) for clinical data is not provided in this document.
3. Number of Experts Used to Establish Ground Truth for the Test Set and Qualifications
Since this involves non-clinical phantom and software testing, there is no mention of experts establishing ground truth in the traditional sense of clinical image interpretation by radiologists. The "ground truth" for image quality likely refers to established physical measurements and industry standards.
4. Adjudication Method for the Test Set
Not applicable, as no clinical test set requiring adjudication by experts is described.
5. Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study
No MRMC comparative effectiveness study is mentioned. The document focuses on demonstrating substantial equivalence through non-clinical testing and comparison to a predicate device, rather than assessing the assistive capabilities for human readers.
6. Standalone (Algorithm Only) Performance
The image reconstruction algorithm utilizes deep learning to provide improved image quality. The "Software Verification" and "Image Performance" sections describe testing of this algorithm in a standalone manner (i.e., verifying its performance against image quality criteria and standards) without a human reader in the loop for assessment. Thus, standalone algorithm performance was done through non-clinical testing.
7. Type of Ground Truth Used
For the non-clinical performance evaluation, the ground truth used appears to be:
- Industry standards and established phantom measurements: For image quality assessment ("NEMA MS" standards, "ACR Phantom Test Guidance," "American College of Radiology standards for named sequences").
- Internal requirements and specifications: For software functionality and verification.
8. Sample Size for the Training Set
The document states that the Swoop® System image reconstruction algorithm utilizes deep learning. However, it does not provide any information regarding the sample size of the training set used for this deep learning algorithm.
9. How the Ground Truth for the Training Set Was Established
The document mentions the use of a deep learning algorithm for image reconstruction but does not describe how the ground truth for its training set was 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.