(51 days)
Functional MR V1.0 is an optional image processing software application that is intended for use on Olea Sphere® V3.0 software package. It is intended to be used by trained professionals including, but not limited to, physicians, MR technicians, radiographers.
Functional MR V1.0 includes a software module that computes the activation map from a BOLD sequence and supports the visualization, analysis of activation maps.
Functional MR V1.0 can also be used to provide reproducible measurements of derived maps. These measurements include thresholds modification and ROI analysis.
Functional MR V1.0 may also be used as an image viewer of multi-modality digital images, including BOLD and DTI images.
When interpreted by a skilled physician, Functional MR V1.0 provides information that may be used in a clinically useful context. Patient management decisions should not be based solely on the results of Functional MR V1.0.
The functional MRI technique consists of analyzing the blood-oxygen-level dependent (BOLD) contrast images. This is a type of specialized brain and body scan is used to map neural activity in the brain or spinal cord of humans by imaging the change in blood flow (hemodynamic response) related to energy use by brain cells.
Olea Medical proposes the Functional MR V1.0 as an optional medical viewing, analysis and processing, Picture Archiving Communications System (PACS) software module that is intended for use with the Olea Sphere® V3.0 software package (K152602). Functional MR V1.0 software application runs on a standard "off-the-shelf" PC workstation.
The provided text describes a 510(k) premarket notification for the Olea Medical Functional MR V1.0 software. The submission aims to demonstrate substantial equivalence to a predicate device, nordicBrainEx v2.3.7. However, the document does not contain specific acceptance criteria, a detailed study proving the device meets those criteria, or the specific information requested in your numbered list regarding performance metrics, sample sizes, expert involvement, and ground truth establishment.
The document primarily focuses on:
- The device's intended use and functionality.
- A comparison of technological characteristics with the predicate device.
- A general statement about internal verification and validation testing, and a comparison study with the predicate.
Here's a breakdown of what is available and what is missing from the provided text, in response to your request:
1. Table of Acceptance Criteria and Reported Device Performance
The document provides a "Predicate Device Comparison Table" which lists functionalities and indicates whether both devices possess them. This table does not represent acceptance criteria as performance thresholds (e.g., sensitivity, specificity, accuracy). It merely confirms feature commonality.
| Functional MR V1.0 | nordicBrainEx® (K163324) | Reported Acceptance Criteria Met (Implicit) |
|---|---|---|
| Standard image Viewing tools | Yes | Yes |
| Loading, post-processing and exporting of images series in DICOM format | Yes | Yes |
| Measurement tools | Yes | Yes |
| 2D MPR visualization | Yes | Yes |
| 3D volume rendering visualization | Yes | Yes |
| Paradigm selection and edition | Yes | Yes |
| Activation maps | Yes | Yes |
| Skull Filtering | Yes | Yes |
| Automatic co-registration | Yes | Yes |
| Time Intensity Display | Yes | Yes |
| Motion Correction | Yes | Yes |
| Slice time correction | Yes | Yes |
| Spatial Filtering | Yes | Yes |
| Threshold adjusting | Yes | Yes |
| Makes available as outputs for Neuro-navigation systems | Yes | Yes |
| Laterality Index | N/A (Functional MR V1.0 has) | N/A (Feature not present in predicate) |
| Bonferroni Correction | N/A (Functional MR V1.0 has) | N/A (Feature not present in predicate) |
Note: The "Reported Acceptance Criteria Met" column is inferred from the statement: "The result of this comparison demonstrates that Functional MR V1.0 has a safety and effectiveness profile similar to the predicate device." This implies that for all features shared with the predicate, the performance was deemed comparable. However, no quantitative performance metrics or specific acceptance criteria are provided.
2. Sample size used for the test set and the data provenance (e.g. country of origin of the data, retrospective or prospective)
- Missing Information: The document does not specify the sample size of the test set, the country of origin of the data, or whether the study was retrospective or prospective. It only states that "additional validation testing to compare the results of Functional MR V1.0 with the predicate."
3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts (e.g. radiologist with 10 years of experience)
- Missing Information: This information is not provided. The term "ground truth" is not explicitly mentioned in the context of the comparison study.
4. Adjudication method (e.g. 2+1, 3+1, none) for the test set
- Missing Information: This information is not provided.
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 MRMC Study Described: The document describes a comparison of the results of Functional MR V1.0 with the predicate nordicBrainEx v2.3.7. It does not mention a multi-reader multi-case (MRMC) comparative effectiveness study evaluating human reader performance with and without AI assistance. Functional MR V1.0 is image processing software, not explicitly an AI-assisted diagnostic tool for human readers in the traditional sense discussed by MRMC studies. The device provides "information that may be used in a clinically useful context," but "Patient management decisions should not be based solely on the results of Functional MR V1.0."
6. If a standalone (i.e. algorithm only without human-in-the loop performance) was done
- Yes (Implicit): The comparison study appears to be a standalone comparison of the software's output ("compare the results of Functional MR V1.0 with the predicate"). The document states it "evaluate performance of BOLD sequence analysis and visualization, viewing and measurement tools..." This implies evaluating the algorithm's output directly against the predicate's output, without human interpretation as part of the primary performance metric.
7. The type of ground truth used (expert consensus, pathology, outcomes data, etc.)
- Implicit Ground Truth: Predicate Device Output: The comparison used the "results of Functional MR V1.0 with the predicate. nordicBrainEx v2.3.7 (NordicNeurolab AS®) was used as a comparison for Functional MR V1.0". This suggests that the output/results of the legally marketed predicate device served as the reference or de facto "ground truth" for the comparison for the functionalities being evaluated. There is no mention of an independent, expert-established ground truth, pathology, or outcomes data.
8. The sample size for the training set
- Not Applicable / Not Provided: As this device is primarily described as image processing software performing calculations and visualizations rather than a machine learning model requiring a distinct training set (though it could conceptually use ML for some features), a "training set" is not explicitly mentioned or quantified. If an ML component exists, its training set details are not provided.
9. How the ground truth for the training set was established
- Not Applicable / Not Provided: Similar to point 8, this information is not available given the context of 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).