(231 days)
The SIGNA Pioneer is a whole body magnetic resonance scanner designed to support high resolution, high signal-to-noise ratio, and short scan times.
It is indicated for use as a diagnostic imaging device to produce axial, sagittal, coronal, and oblique images, spectroscopic images, parametric maps, and/or spectra, dynamic images of the structures of the entire body, including, but not limited to, head, neck, TMJ, spine, breast, heart, abdomen, pelvis, joints, prostate, blood vessels, and musculoskeletal regions of the body.
Depending on the region of interest being imaged, contrast agents may be used.
The images produced by the SIGNA Pioneer reflect the spatial distribution or molecular environment of nuclei exhibiting magnetic resonance. These images and/or spectra when interpreted by a trained physician yield information that may assist in diagnosis.
The SIGNA Pioneer features a 3.0T superconducting magnet with a 70cm bore size. The RF receiver is equipped with 97 RF channels. The data acquisition system accommodates 32 channels for image reconstruction simultaneously. The system uses a combination of time-varying magnetic fields (gradients) and RF transmissions to obtain information regarding the density and position of nuclei exhibiting magnetic resonance. The system can image in the sagittal, coronal, axial, oblique, and double oblique planes, using various pulse sequences and reconstruction algorithms. The SIGNA Pioneer uses multi-drive RF transmit for imaging of the head and body regions. The SIGNA Pioneer is designed to conform to NEMA DICOM standards.
The provided document is a 510(k) summary for the GE Healthcare SIGNA Pioneer Magnetic Resonance Diagnostic Device. It states that the device has been found substantially equivalent to a predicate device (Discovery MR750w 3.0T, K142085). The summary primarily focuses on affirming that the SIGNA Pioneer performs equivalently to the predicate device and meets established safety standards rather than establishing new acceptance criteria for an AI/algorithm-driven device.
Therefore, the information requested in the prompt, which is typically relevant for studies evaluating the performance of AI/algorithm-driven devices against specific acceptance criteria, is largely not present in this document. This document describes a traditional medical device (an MRI scanner) and its substantial equivalence to another MRI scanner, not a standalone AI diagnostic software.
However, I can extract the relevant information that is present and identify what is missing based on your questions.
1. Table of Acceptance Criteria and Reported Device Performance
The document does not present specific "acceptance criteria" in the format of a table with numerical thresholds for performance metrics for an AI/algorithm. Instead, it states that the device was verified to meet safety criteria and demonstrated acceptable diagnostic imaging performance, which is "substantially equivalent" to the predicate device.
| Acceptance Criterion (Implicit) | Reported Device Performance (Summary) |
|---|---|
| Safety Compliance | Complies with IEC 60601-1, IEC 60601-1-2, IEC 60601-2-33, ISO 10993-1, NEMA MS, and NEMA PS3 standards for MRI and DICOM. Verified to meet the same local SAR safety criteria as the predicate device via human modeling simulations for RF multi-drive transmit. |
| Diagnostic Imaging Performance | Clinical images and clinical results summary demonstrate acceptable diagnostic imaging performance. Image quality is substantially equivalent to that of the predicate device. |
| Intended Use | Indications for Use are identical to the predicate device. |
2. Sample Size Used for the Test Set and Data Provenance
- Test Set Sample Size: Not specified. The document only mentions "clinical images and clinical results summary" were used, but no numbers are provided for cases or subjects.
- Data Provenance: Not specified (e.g., country of origin, retrospective/prospective).
3. Number of Experts Used to Establish Ground Truth for the Test Set and Qualifications
- Number of Experts: Not specified.
- Qualifications: The document states that "images and/or spectra when interpreted by a trained physician yield information that may assist in diagnosis." This implies physicians were involved in interpreting clinical data, but their number and specific qualifications (e.g., years of experience, subspecialty) are not detailed.
4. Adjudication Method for the Test Set
- Not specified.
5. Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study
- Was it done?: No, a traditional MRMC comparative effectiveness study as typically understood for AI-assisted reading was not performed or described. The comparison is between the SIGNA Pioneer MRI device and a predicate MRI device, focusing on substantial equivalence in overall performance and safety, not on how an AI improves human reader performance.
- Effect size of AI improvement: Not applicable, as this was not an AI assistance study.
6. Standalone (Algorithm Only Without Human-in-the-Loop Performance) Study
- Was it done?: No. This document describes an MRI scanning device, which produces images for physician interpretation. It is not an algorithm that performs a diagnosis in a standalone manner. The device's "performance" refers to the quality of the images it produces and its adherence to safety standards.
7. Type of Ground Truth Used
- The document implies that "clinical images and clinical results" were evaluated, likely against the interpretations of "trained physicians" (expert consensus based on clinical findings) for diagnostic imaging performance. However, specific methodologies for establishing ground truth (e.g., pathology, long-term outcomes) are not detailed.
8. Sample Size for the Training Set
- Not applicable/Not specified. This device is a hardware scanner, not a machine learning algorithm that requires a training set in the conventional sense for its primary function. While some integrated software features might have been developed using data, the document does not distinguish or describe a "training set" for the fundamental device performance.
9. How the Ground Truth for the Training Set Was Established
- Not applicable/Not specified for the reasons stated above.
§ 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.