(203 days)
AI-Rad Companion Brain MR is a post-processing image analysis software that assists clinicians in viewing, analyzing and evaluating MR brain images.
AI-Rad Companion Brain MR provides the following functionalities:
- Automatic segmentation and quantitative analysis of individual brain structures
- Quantitative comparison of each brain structure with normative data from a healthy population
- Presentation of results for reporting that includes all numerical values as well as visualization of these results
AI-Rad Companion Brain MR is an enhancement to the predicate, syngo.MR Application (K182904). Just as in the predicate, AI-Rad Companion Brain MR addresses the automatic quantification and visual assessment of the volumetric properties of various brain structures based on T1 MPRAGE datasets. These datasets are acquired as part of a typical head MR acquisition. The results are directly archived in PACS as this is the standard location for reading by radiologist. From a predefined list of 30 structures (e.g. Hippocampus, Caudate, Left Frontal Grey Matter, etc.), volumetric properties are calculated as absolute and normalized volumes with respect to the total intercranial volume. The normalized values for a given patient are compared against age-matched mean and standard deviations obtained from a population of healthy reference subjects.
As an update to the previously cleared device, the following modifications have been made:
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- Modified Intended Use Statement
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- Addition of a customizable deviation map
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- Architectural enhancement for the clinical extension to be deployed with the AI-Rad Companion Engine platform in a cloud-based environment
The provided text is a Siemens 510(k) summary for AI-Rad Companion Brain MR, focusing on its substantial equivalence to a predicate device. It explicitly states, "No clinical tests were conducted to test the performance and functionality of the modifications introduced within AI-Rad Companion Brain MR." Therefore, the document does not contain the information requested in your prompt regarding acceptance criteria and a study proving the device meets those criteria.
The prompt asks for details about a study that proves the device meets acceptance criteria, including a detailed table of acceptance criteria and reported performance, sample sizes, ground truth establishment, expert qualifications, and MRMC study details. None of this information is present in the provided document.
The document primarily focuses on:
- The device's intended use (post-processing image analysis for MR brain images, including segmentation, quantitative analysis, and comparison with normative data).
- Its classification as a Class II device.
- Its substantial equivalence to an existing predicate device (syngo.MR Applications, K182904).
- The fact that it is an "enhancement" to the predicate, with modifications including a modified intended use statement, a customizable deviation map, and architectural enhancements for cloud-based deployment.
- Non-clinical tests (software validation, bench testing, conformance to industry standards like ISO 14971, IEC 62304, DICOM, and cybersecurity).
- A clear statement that no clinical tests were conducted.
To answer your prompt, clinical study data, which are not present here, would be required.
§ 892.2050 Medical image management and processing system.
(a)
Identification. A medical image management and processing system is a device that provides one or more capabilities relating to the review and digital processing of medical images for the purposes of interpretation by a trained practitioner of disease detection, diagnosis, or patient management. The software components may provide advanced or complex image processing functions for image manipulation, enhancement, or quantification that are intended for use in the interpretation and analysis of medical images. Advanced image manipulation functions may include image segmentation, multimodality image registration, or 3D visualization. Complex quantitative functions may include semi-automated measurements or time-series measurements.(b)
Classification. Class II (special controls; voluntary standards—Digital Imaging and Communications in Medicine (DICOM) Std., Joint Photographic Experts Group (JPEG) Std., Society of Motion Picture and Television Engineers (SMPTE) Test Pattern).