(140 days)
Your MAGNETOM MR system is indicated for use as a magnetic resonance diagnostic device (MRDD) that produces transverse, sagittal, coronal and oblique cross sectional images, spectroscopic images and that displays the internal structure and/or function of the head, body, or extremities.
Other physical parameters derived from the images and/or spectra may also be produced. Depending on the region of interest, contrast agents may be used. These images and/or spectra and the physical parameters derived from the images and/or spectra when interpreted by a trained physician yield information that may assist in diagnosis.
Your MAGNETOM MR system may also be used for imaging during interventional procedures when performed with MR compatible devices such as in-room displays and MR Safe biopsy needles.
The subject device, MAGNETOM Avanto and MAGNETOM Verio D with software syngo MR E11D, is a modification of the previously cleared predicate device, MAGNETOM Avanto and MAGNETOM Verio with software syngo MR D13A (K121434). Software version syngo E11D for MAGNETOM Avanto and MAGNETOM Verio includes software applications migrated from the previously cleared MAGNETOM Aera and Skyra systems with syngo MR E11C (K153343). Only minor adaptations were needed to support the system specific hardware and optimize the sequence/protocols. The description lists new and modified sequences/algorithms, new and modified applications, and new hardware components.
Here's the breakdown of the acceptance criteria and study information based on the provided text, specifically for the K181613 submission for MAGNETOM Avanto and MAGNETOM Verio with software syngo MR E11D:
1. Table of Acceptance Criteria and Reported Device Performance
It's important to note that the provided document is a 510(k) summary, which focuses on demonstrating substantial equivalence to a predicate device rather than presenting detailed acceptance criteria and quantitative performance results for a new, novel AI algorithm. The performance is assessed primarily through verification and validation testing against established standards and equivalency to previously cleared predicate devices.
| Acceptance Criteria (Implied) | Reported Device Performance |
|---|---|
| Safety and Effectiveness Equivalence (to predicate device) | "The conclusions from the non-clinical data suggests that the features bear an equivalent safety and performance profile as that of the predicate device." |
| "The results from each set of tests demonstrate that the device performs as intended and is thus substantially equivalent to the predicate device to which it has been compared." | |
| "There are no changes to the indications for use for the subject device as compared to that of the legally marketed predicate device." | |
| Compliance with Software Guidance (FDA) | "Software verification and validation testing was completed in accordance with the FDA guidance document, 'Guidance for the Content of Premarket Submissions for Software Contained in Medical Devices', dated May 11, 2005." |
| Compliance with MRDD Guidance (FDA) | "Performance testing was completed in accordance with the FDA guidance document, 'Submission of Premarket Notifications for Magnetic Resonance Diagnostic Devices', dated November 18, 2016." |
| Compliance with Recognized Standards | Conforms to ES60601-1:2005/(R)2012 and A1:2012, 60601-1-2 Edition 3:2007-03, 60601-2-33 Ed. 3.1:2013, ISO 14971 Second Edition 2007-03-01, 60601-1-6 Edition 3.1 2013-10, IEC 62304 Edition 1.1 2015-06. |
| Risk Management (ISO 14971) | "Risk management is ensured via compliance with ISO 14971:2007 to identify and provide mitigation of potential hazards..." |
| Proper Labeling and Instructions | "The device labeling contains instructions for use and any necessary cautions and warnings to provide for safe and effective use of the device." |
| Verification and Validation of New/Modified Features | "All features have been verified and validated to support the claim of substantial equivalence to the predicate device." |
2. Sample Size Used for the Test Set and Data Provenance
- Test Set Sample Size: The document does not explicitly state a specific sample size for a "test set" in the context of a prospective, human-read study with a defined dataset for performance evaluation. Instead, it mentions "non-clinical data" and "sample clinical images."
- Data Provenance: The document generally refers to "non-clinical data" and "sample clinical images." There is no information regarding the country of origin or whether the data was retrospective or prospective. The "sample clinical images" were provided "in accordance with the FDA guidance document, 'Submission of Premarket Notifications for Magnetic Resonance Diagnostic Devices,'" but the details of these images (e.g., number, origin) are not elaborated.
3. Number of Experts Used to Establish the Ground Truth for the Test Set and Qualifications of Those Experts
There is no information provided in the document regarding the number of experts or their qualifications for establishing ground truth for any specific test set. The submission focuses on the performance of the MR system itself, not necessarily an AI-driven image analysis tool requiring expert-adjudicated ground truth.
4. Adjudication Method for the Test Set
There is no information provided regarding any adjudication method, as the study described is not an AI performance study that typically involves expert adjudication.
5. If a Multi Reader Multi Case (MRMC) Comparative Effectiveness Study Was Done, and the Effect Size of How Much Human Readers Improve with AI vs without AI Assistance
No, an MRMC comparative effectiveness study involving AI assistance for human readers was not done or reported in this 510(k) summary. The device in question is a magnetic resonance diagnostic device (MR system) and its updated software, not an AI-driven diagnostic algorithm used to assist human readers.
6. If a Standalone (i.e. algorithm only without human-in-the-loop performance) Was Done
The document describes performance testing of the entire MR system and its software, not a standalone algorithm. The "new sequences or algorithms" and "applications" mentioned are integral parts of the MR system's functionality, producing images and spectra for interpretation by a trained physician. Therefore, a standalone algorithm-only performance study (as would be typical for an AI diagnostic device) was not performed or reported in this context.
7. The Type of Ground Truth Used
The concept of "ground truth" as typically defined for AI performance studies (e.g., pathology, outcomes data, expert consensus) is not explicitly addressed nor applied in this submission. The device's performance is evaluated against its intended function (producing images, spectra, and physical parameters) and its equivalence to a predicate device, which implies that the output (the images themselves) is the primary "truth" and is interpreted by a trained physician.
8. The Sample Size for the Training Set
Since this submission is for an updated MR system software and not a de novo AI algorithm, there is no mention or requirement for a "training set" in the context of machine learning. The software updates described include new and modified sequences or algorithms and applications, which are developed and validated through traditional software engineering and control methods, not machine learning model training.
9. How the Ground Truth for the Training Set Was Established
As there is no training set discussed in this document for an AI algorithm, the question of how ground truth was established for it is not applicable.
§ 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.