(57 days)
MR DWI/FLAIR Measurement V1.0 is an image processing application indicated for use in the analysis of:
(1) MR Diffusion-weighted imaging (DWI)
(2) MR FLAIR images.
The device is intended to be used by trained professionals with medical imaging education including, but not limited to, physicians and medical technicians in the imaging assessment workflow:
- computation of the map relative to the water diffusion, i.e., ADC map; .
- . extraction and communication of metrics derived from the above map, i.e., hypointense area on ADC, and FLAIR series as well as ratios with contralateral information on FLAIR images.
The results of MR DWI/FLAIR Measurement V1.0 are intended to be used in conjunction with other patient information and, based on professional judgment, to assist the clinician in the medical imaging assessment. Trained professionals are responsible for viewing the full set of native images per the standard of care.
The device does not alter the original medical image. MR DWI/FLAIR Measurement V1.0 is not intended to be used as a standalone diagnostic device and shall not be used to take decisions with diagnosis or therapeutic purposes. Patient management decisions should not solely be based on MR DWI/FLAIR Measurement V1.0 results.
MR DWI/FLAIR Measurement V1.0 can be integrated and deployed through technical platforms responsible for transferring, storing, converting formats, notifying of detected image variations and display of DICOM imaging data.
Olea Medical proposes MR DWI/FLAIR Measurement V1.0 as an image processing application, Picture Archiving Communications System (PACS) software module that is intended for use in a technical environment which incorporates a Medical Image Communications Device as its technical platform.
MR DWI/FLAIR Measurement V1.0 is an executable application which can run on the OLEA Platform. The OLEA Platform is a Medical Image Communications Device and outside the scope of this submission. MR DWI/FLAIR Measurement V1.0 is a docker totally independent from the OLEA platform in which it is integrated and has a dedicated Input/Output channels to be able to be integrated and deployed through any compatible configurable technical platform. Input DICOM images are received via the dedicated file system in which the application is integrated. When launched, the MR DWI/FLAIR Measurement V1.0 will retrieve and automatically analyze the image series. The output images will be sent to the same dedicated file system and can be visualized from any DICOM viewer by loading these results from the allocated file system.
To be used, the MR DWI/FLAIR Measurement V1.0 docker needs an independent technical base, which is provided by a Medical Image Communications Device (MICD). The technical platform allows the docker to:
- receive the inputs
- provide the outputs
- . visualize the outputs through Olea Platform viewer and/or export to other third party DICOM viewers.
The provided text describes the 510(k) clearance for Olea Medical's MR DWI/FLAIR Measurement V1.0. While it details performance testing, it does not explicitly state "acceptance criteria" in the format of a table with specific thresholds. Instead, it presents the results of comparative testing against a predicate device (Olea Sphere V3.0) and indicates that the performance demonstrated substantial equivalence.
Here's a breakdown of the requested information based on the provided text, with an acknowledgment where specific details (like explicit acceptance criteria thresholds) are not explicitly stated:
Device Performance and Acceptance Criteria Study Details
1. Table of Acceptance Criteria and Reported Device Performance
The acceptance criteria are not explicitly stated as numerical thresholds for specific metrics (e.g., "Dice score > 0.90"). Instead, the acceptance is demonstrated through comparative testing showing substantial equivalence to the predicate device, Olea Sphere V3.0. The performance is reported in terms of agreement and similarity with the predicate.
| Metric (Implicit Acceptance Criteria: Substantial Equivalence to Predicate) | Reported Device Performance (Compared to Predicate Olea Sphere V3.0) |
|---|---|
| Relative FLAIR (Bias) | Average estimated bias (average of differences) was close to zero (0.004). |
| Relative FLAIR (95% Limits of Agreement) | 95% of measurement differences ranged between -0.013 and +0.021. |
| DICE Index for ADC Hypointense Area Segments (FLAIR images) | Excellent, ranging from 0.816 to 0.976. (Applies to both Relative and Normalized FLAIR) |
| Normalized FLAIR (Bias) | Average estimated bias (average of differences) was close to zero (0.05). |
| Normalized FLAIR (95% Limits of Agreement) | 95% of measurement differences ranged between -0.100 and +0.199. |
Implicit Acceptance: The performance metrics, particularly the low bias and tight limits of agreement for FLAIR measurements and the excellent DICE indexes, demonstrate that the MR DWI/FLAIR Measurement V1.0 performs comparably to the predicate device, thus meeting the implicit acceptance criterion of substantial equivalence.
2. Sample Size Used for the Test Set and Data Provenance
- Test Set (for comparative clinical image study): Not explicitly stated how many cases were used for the comparative clinical image study that produced the Bland-Altman and DICE index results.
- Test Set (for Diffusion Brain Extraction Tool - BET): 28 cases from multiple institutions.
- Data Provenance: Cases came from multiple institutions (for the BET algorithm testing), different from the training and validation sets. DICOM data were sourced from Siemens, General Electric, Philips, and Canon manufacturers. The text does not specify the country of origin or whether the data was retrospective or prospective.
3. Number of Experts Used to Establish Ground Truth for the Test Set and Qualifications
- Number of Experts: Not explicitly stated for the overall "comparative clinical image study."
- Qualifications of Experts: For the Diffusion Brain Extraction Tool (BET) algorithm, the reference standard was established by "expert clinicians." Specific qualifications (e.g., years of experience, subspecialty) are not provided beyond "expert clinicians."
4. Adjudication Method for the Test Set
- Adjudication Method: Not explicitly stated. The text mentions "manual segmentation performed by expert clinicians" for the BET ground truth, implying individual expert assessment, but does not detail a consensus or adjudication process.
5. Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study
- MRMC Study: No, a multi-reader multi-case (MRMC) comparative effectiveness study was not reported. The study focused on comparing the device's measurements directly to a predicate device's measurements (algorithm-to-algorithm comparison for the main performance metrics and algorithm-to-expert segmentation for the BET component), rather than human readers with and without AI assistance.
- Effect Size: Not applicable, as no MRMC study was performed.
6. Standalone (Algorithm Only Without Human-in-the-Loop Performance) Study
- Yes, the performance data presented (Bland-Altman analysis for FLAIR measurements and DICE indexes) represents a standalone comparison between the subject device's algorithmic outputs and the predicate device's outputs. The Diffusion Brain Extraction Tool (BET) component also had standalone performance evaluated against expert manual segmentations.
- The device is explicitly stated as "not intended to be used as a standalone diagnostic device" and results are to be used "in conjunction with other patient information" and to "assist the clinical imaging assessment." The performance study, however, validates the algorithm's output accuracy against a reference.
7. Type of Ground Truth Used
- For the Diffusion Brain Extraction Tool (BET) algorithm, the ground truth was expert manual segmentation.
- For the overall device performance (Relative/Normalized FLAIR measurements, ADC hypointense area segmentation), the "ground truth" was essentially the outputs of the predicate device (Olea Sphere V3.0), as the study aimed to demonstrate substantial equivalence by comparing the new device's outputs to the established predicate's outputs.
8. Sample Size for the Training Set
- Training Set (for Diffusion Brain Extraction Tool - BET): 218 cases.
9. How the Ground Truth for the Training Set Was Established
- The text states, "The reference standard was established by manual segmentation performed by expert clinicians" for the Diffusion Brain Extraction Tool (BET) algorithm. This implies that the ground truth for training (and validation/testing) was established through expert manual segmentation.
§ 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).