Search Results

The uMR Omega system is indicated for use as a magnetic device (MRDD) that produces sagittal. transverse, coronal, and oblique cross sectional images, and that display internal anatomical structure and/or function of the head, body and extremities.

These images and the physical parameters derived from the interpreted by a trained physician yield information that may assist the diagnosis. Contrast agents may be used depending on the region of interest of the scan.

The uMR Omega is a 3.0T superconducting magnetic resonance diagnostic device with a 75cm size patient bore. It consists of components such as magnet, RF power amplifier, RF coils, gradient power amplifier, gradient coils, patient table, spectrometer, computer, equipment cabinets, power distribution system, internal communication system, and vital signal module etc. The uMR Omega Magnetic Resonance Diagnostic Device is designed to conform to NEMA and DICOM standards.

This document is a 510(k) premarket notification for the uMR Omega Magnetic Resonance Diagnostic Device. It outlines modifications to a previously cleared device (K220332) and claims substantial equivalence to that predicate device. The information provided heavily focuses on technical characteristics and safety standards rather than detailed clinical performance studies with specific acceptance criteria related to diagnostic accuracy.

Therefore, many of the requested details, such as specific acceptance criteria for diagnostic performance, exact device performance metrics against those criteria, details of a test set for diagnostic accuracy (sample size, provenance, expert qualifications, adjudication method), human-in-the-loop studies (MRMC), or a standalone performance study in the context of diagnostic accuracy, are not explicitly present in the provided text.

The document primarily discusses technical specifications, safety, and the additions/modifications to the device. The "Performance Data" section mentions "Clinical performance evaluation" and "Performance evaluation report" for various sequences and imaging processing methods (4D Flow, MRE, CEST, T1rho, mPLD ASL, silica gel imaging). However, it does not provide the acceptance criteria for these evaluations or the results against such criteria in terms of diagnostic accuracy or clinical utility metrics. Instead, it concludes generally that "The test results demonstrated that the device performs as expected."

Based on the provided text, here's what can be extracted and what is missing:

1. Table of Acceptance Criteria and Reported Device Performance

The document does not explicitly state acceptance criteria for diagnostic performance in terms of sensitivity, specificity, accuracy, etc. for any specific medical condition. The reported performance is general compliance with technical standards and the device performing "as expected."

2. Sample size used for the test set and the data provenance

Not explicitly stated for diagnostic performance evaluations. The "Clinical performance evaluation" and "Performance evaluation report" are mentioned, but details on the patient cohort (sample size, retrospective/prospective, country of origin) are missing. These mentions are likely referring to technical performance characteristics rather than clinical diagnostic accuracy.

3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts

Not explicitly stated. Given the nature of the submission (510(k) for a device with modifications, primarily focusing on technical specifications and safety standards), a detailed ground truth establishment process for diagnostic accuracy studies is not commonly part of this type of documentation unless new clinical claims or algorithms affecting diagnostic interpretation are being introduced and require such validation. The document states that images are "interpreted by a trained physician," but this is a general statement about usage, not about expert panel for ground truth.

4. Adjudication method for the test set

Not explicitly stated.

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

No indication of an MRMC study. The document describes a Magnetic Resonance Diagnostic Device (MRI machine itself) and its embedded imaging processing methods, not an AI-assisted diagnostic tool that would typically undergo such a study.

6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done

No indication of a standalone diagnostic algorithm performance study. The listed "imaging processing methods" (4D Flow Quantification, MRE, SNAP, CEST, T1Rho, FSP+) are features of the MRI system, and their performance is implied to be evaluated as part of the overall system's technical function and image quality, not as standalone diagnostic algorithms with their own "ground truth" performance metrics.

7. The type of ground truth used

Not explicitly stated for diagnostic accuracy. For the technical performance aspects, the "ground truth" would be measurements against established physical standards and phantom data to ensure image quality, signal integrity, and safety parameters meet specifications.

8. The sample size for the training set

Not applicable/Not mentioned. This document describes an MRI machine, not a machine learning or AI algorithm that would typically have a separate training set. The "imaging processing methods" are embedded features or techniques, not typically AI models trained on large datasets in the way common AI diagnostics are.

9. How the ground truth for the training set was established

Not applicable/Not mentioned. (See point 8).

Ask a specific question about this device