(262 days)
syngo.MR Applications is a syngo based post-acquisition image processing software for viewing, manipulating, evaluating, and analyzing MR, MR-PET, CT, PET, CT-PET images and MR spectra.
The syngo.MR Applications are syngo based post-processing software/applications to be used for viewing and evaluating ' MR images provided by a maqnetic resonance diagnostic device and enabling structured evaluation of MR images. syngo.MR Brain Morphometry extends the MR Neurology workflow and offers a comprehensive package for the automatic calculation of the volume properties of different brain structures using MPRAGE datasets, which are typically acquired for a typical MR examination of the head.
With this premarket submission, the new functionality syngo.MR Brain Morphometry is introduced to extend the MR Neurology workflow that is a part of the formerly cleared medical device syngo.MR Applications (K180336).
Here's a breakdown of the acceptance criteria and study information for syngo.MR Brain Morphometry, based on the provided text:
Acceptance Criteria and Reported Device Performance
The document states that "Acceptance criteria for performance tests were defined based on a literature review. In all validation experiments, syngo.MR Brain Morphometry passed the acceptance criteria." However, it does not explicitly list the specific numerical acceptance criteria. Instead, it provides the reported device performance in terms of correlation coefficients.
| Performance Metric | Acceptance Criteria (from literature review) | Reported Device Performance |
|---|---|---|
| Accuracy | Not explicitly stated (passed literature-based criteria) | Correlation with reference device: 0.95 (grey matter), 0.80 (hippocampus), 0.92 (white matter) |
| Repeatability | Not explicitly stated (passed literature-based criteria) | Volume correlation: 0.96 (grey matter, hippocampus, white matter), 0.99 (ventricular system) |
| Reproducibility | Not explicitly stated (passed literature-based criteria) | Volume correlation: 0.97 (grey matter), 0.94 (hippocampus), 0.98 (white matter) |
Study Details
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Sample Size Used for the Test Set and Data Provenance:
- Test Set Sample Size: 1200 subjects.
- Data Provenance: The dataset consisted of Alzheimer's patients (AD), mild cognitive impaired patients (MCI), and healthy controls (HC). The country of origin and whether the data was retrospective or prospective are not specified in the provided text.
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Number of Experts Used to Establish the Ground Truth for the Test Set and Qualifications of Those Experts:
- The document primarily describes a validation study comparing the automated results to a "reference." It does not explicitly state that human experts were used to establish a ground truth for the test set in the traditional sense of consensus reading for image interpretation. The "reference" appears to be an established method or device, but details on its nature (e.g., manual segmentation by neuro-radiologists) are not provided.
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Adjudication Method:
- Not applicable/Not described. The validation appears to be against a "reference" rather than through an adjudication process among human readers.
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Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study:
- No, a MRMC comparative effectiveness study was not explicitly conducted or described. The study focused on the standalone performance of the algorithm against a reference.
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Standalone Performance:
- Yes, a standalone (algorithm only) performance evaluation was conducted. The performance metrics (accuracy, repeatability, reproducibility) were quantified for syngo.MR Brain Morphometry.
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Type of Ground Truth Used:
- The accuracy of volumetric results was validated by comparing the automated results to a "reference." The specific nature of this reference (e.g., manual segmentation, results from another validated software, pathology) is not detailed.
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Sample Size for the Training Set:
- The sample size for the training set is not provided in the document. The text focuses on the validation of the new feature.
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How the Ground Truth for the Training Set Was Established:
- This information is not provided in the document.
§ 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).