(30 days)
Not Found
Unknown
The summary describes automated image processing for segmentation and quantification but does not explicitly mention the use of AI or ML algorithms. While these tasks can be performed using AI/ML, the description of the process (pre-processing, segmentation, calculation) is generic enough to potentially be implemented with traditional image processing techniques. The lack of mention of training or testing data characteristics typically associated with AI/ML models further contributes to the uncertainty.
No
The device is described as software for automatic labeling, visualization, and volumetric quantification of brain structures from MR images. It does not state that it provides therapy or is directly involved in treating a condition.
Yes
The device is intended for automatic labeling, visualization, and volumetric quantification of segmentable brain structures from MR images, which helps automate the current manual process of identifying, labeling, and quantifying the volume of segmentable brain structures. This quantitative information can diagnose, monitor, or assess disease progression, making it a diagnostic device.
Yes
The device description explicitly states that icobrain is "software" and details its function as processing input MR images to produce reports and overlaid segmentations. There is no mention of any accompanying hardware component that is part of the device itself.
Based on the provided information, this device is not an IVD (In Vitro Diagnostic).
Here's why:
- IVD Definition: In vitro diagnostics are tests performed on samples taken from the human body, such as blood, urine, or tissue, to detect diseases, conditions, or infections.
- Device Function: The description clearly states that icobrain processes MR images (Magnetic Resonance images) of the brain. This is an in vivo imaging technique, meaning it is performed on a living subject, not on a sample taken from the body.
- Intended Use: The intended use is for automatic labeling, visualization, and volumetric quantification of brain structures from these MR images. This is a form of medical image analysis, not a diagnostic test performed on a biological sample.
Therefore, icobrain falls under the category of medical image processing software, not an in vitro diagnostic device.
N/A
Intended Use / Indications for Use
icobrain is intended for automatic labeling, visualization and volumetric quantification of segmentable brain structures from a set of MR images. This software is intended to automate the current manual process of identifying, labeling and quantifying the volume of segmentable brain structures identified on MR images.
icobrain consists of two distinct image processing pipelines: icobrain cross and icobrain long.
icobrain cross is intended to provide volumes from images acquired at a single timepoint icobrain long is intended to provide changes in volumes between two images that were acquired on the samer, with the same image acquisition protocol and with same contrast at two different timepoints The results of icobrain cross cannot be compared with the results of icobrain long.
Product codes (comma separated list FDA assigned to the subject device)
LLZ
Device Description
icobrain is intended for automatic labeling, visualization and volumetric quantification of segmentable brain structures from a set of MR images. This software is intended to automate the current manual process of identifying, labeling and quantifying the volume of segmentable brain structures identified on MR images.
icobrain consists of two distinct image processing pipelines: icobrain cross and icobrain long.
- icobrain cross is intended to provide volumes from images acquired at a single timepoint
- · icobrain long is intended to provide changes in volumes between two images that were acquired on the same scanner, with the same image acquisition protocol and with same contrast at two different timepoints
The results of icobrain cross cannot be compared with the results of icobrain long.
As input, icobrain uses TI-weighted and a fluid-attenuated inversion recovery (FLAIR) DICOM MR images from a single or from multiple time points. In case of multiple time points, i.e. multiple MRI scans from the same subject, for each time point one FLAIR and one TI image are used as input. During the pre-processing, the scan type (TI, FLAIR) is detected for every input image before it is converted from DICOM format to NIFTI format. The image processing then performs the actual segmentation and calculates the volumes of the brain structures. In case MRI scans from the same subject on multiple time points are available, the changes in volume of the brain structures are calculated as well. Finally, the computed volumes and volume changes (in case of multiple time points) are summarized into an electronic report and (some) segmentations are overlaid on the input images.
The software displays the following volumetric measures in three reports
Report I:
- unnormalized volume and volume changes (total, new, enlarging and shrinking) of FLAIR white matter hyperintensities, in different regions (peri-ventricular, juxta-cortical, infra-tentorial, deep white matter).
- unnormalized volume and volume changes (total, new, enlarging and shrinking) of TI white matter hyperintensities and hypointensities.
- · normalized volume and volume changes of the whole brain (sum of white and grey matter),
- · normalized volume and volume changes of grey matter
Report 2:
- normalized volume and volume changes of the frontal, temporal and parietal lobe
- · normalized volume and volume changes of the hippocampi
- · unnormalized volume and volume changes of FLAIR white matter hyperintensities
Report 3:
- unnormalized volume and volume changes (total, new, enlarging and shrinking) of FLAIR white matter hyperintensities, in different regions (sub-cortical, corpus callosum, brainstem)
- · normalized volume and volume changes of the cortical gray matter
- · normalized volume and volume changes of the hippocampi
The whole brain, gray matter, cortical gray matter, frontal lobe, temporal lobe, parietal lobe and hippocampal volumes are normalized for head size by comparing to a healthy population using a statistical model. The reported FLAIR or TI white matter hyperintensities volumes are not normalized since they are not comparable to a reference population.
Mentions image processing
Yes
Mentions AI, DNN, or ML
Not Found
Input Imaging Modality
MR images
Anatomical Site
brain structures
Indicated Patient Age Range
Not Found
Intended User / Care Setting
Not Found
Description of the training set, sample size, data source, and annotation protocol
Not Found
Description of the test set, sample size, data source, and annotation protocol
Not Found
Summary of Performance Studies (study type, sample size, AUC, MRMC, standalone performance, key results)
Quality and safety: icobrain has been designed, developed and tested in accordance with ISO 14971:2007, IEC 62304:2006, IEC 62366:2014, ISO 12052:2006, CFR 21 part 820, and ISO 13485:2016. The changes made in icobrain compared to the original device do not affect the safety of the device, based on failure mode and effects analysis on the added functionality, and risk category classification of new software components.
Product performance: To demonstrate the performance of icobrain, the measured volumes and volume changes of the segmentable brain structures are validated for accuracy and reproducibility. The subjects upon whom the device was tested include healthy subjects, Alzheimer's disease patients, traumatic brain injury patients, and depression patients. In the accuracy experiments, the volumes / volume changes are compared to simulated and/or manually labeled ground truth volumes / volume changes. In the reproducibility experiments, the volumes / volume changes are compared on test-retest image data sets. A literature review has been performed to set relevant acceptance criteria for each type of experiments passed the acceptance criteria. The experiments encompassed 463 subject datasets in total. Averaged over all experiments, the Pearson correlation coefficient between the compared measurements was 0.91 and the intraclass correlation coefficient was 0.89. Besides the validation experiments, verification tests demonstrate the system as a whole provides all the capabilities necessary to operate according to its intended use.
Key Metrics (Sensitivity, Specificity, PPV, NPV, etc.)
Pearson correlation coefficient: 0.91
Intraclass correlation coefficient: 0.89
Predicate Device(s): If the device was cleared using the 510(k) pathway, identify the Predicate Device(s) K/DEN number used to claim substantial equivalence and list them here in a comma separated list exactly as they appear in the text. List the primary predicate first in the list.
Reference Device(s): Identify the Reference Device(s) K/DEN number and list them here in a comma separated list exactly as they appear in the text.
Not Found
Predetermined Change Control Plan (PCCP) - All Relevant Information for the subject device only (e.g. presence / absence, what scope was granted / cleared under the PCCP, any restrictions, etc).
Not Found
§ 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).
0
Image /page/0/Picture/0 description: The image contains the logo of the U.S. Food and Drug Administration (FDA). On the left, there is the Department of Health & Human Services logo. To the right of that is the FDA logo, which is a blue square with the letters "FDA" in white. To the right of the blue square is the text "U.S. FOOD & DRUG ADMINISTRATION" in blue.
March 8, 2018
icometrix NV % Dirk Smeets VP Clinical Applications Kolonel Begaultlaan 1b /12 Leuven, 3012 BELGIUM
Re: K180326
Trade/Device Name: icobrain Regulation Number: 21 CFR 892.2050 Regulation Name: Picture archiving and communications system Regulatory Class: Class II Product Code: LLZ Dated: February 2, 2018 Received: February 6, 2018
Dear Dirk Smeets:
We have reviewed your Section 510(k) premarket notification of intent to market the device referenced above and have determined the device is substantially equivalent (for the indications for use stated in the enclosure) to legally marketed predicate devices marketed in interstate commerce prior to May 28, 1976, the enactment date of the Medical Device Amendments, or to devices that have been reclassified in accordance with the provisions of the Federal Food. Drug, and Cosmetic Act (Act) that do not require approval of a premarket approval application (PMA). You may, therefore, market the device, subject to the general controls provisions of the Act. The general controls provisions of the Act include requirements for annual registration, listing of devices, good manufacturing practice, labeling, and prohibitions against misbranding and adulteration. Please note: CDRH does not evaluate information related to contract liability warranties. We remind you, however, that device labeling must be truthful and not misleading.
If your device is classified (see above) into either class II (Special Controls) or class III (PMA), it may be subject to additional controls. Existing major regulations affecting your device can be found in the Code of Federal Regulations, Title 21, Parts 800 to 898. In addition, FDA may publish further announcements concerning your device in the Federal Register.
Please be advised that FDA's issuance of a substantial equivalence determination does not mean that FDA has made a determination that your device complies with other requirements of the Act or any Federal statutes and regulations administered by other Federal agencies. You must comply with all the Act's requirements, including, but not limited to: registration and listing (21 CFR Part 807); labeling (21 CFR Part 801); medical device reporting of medical device-related adverse events) (21 CFR 803); good manufacturing practice requirements as set forth in the quality systems (QS) regulation (21 CFR Part 820);
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Page 2 - Dirk Smeets
and if applicable, the electronic product radiation control provisions (Sections 531-542 of the Act); 21 CFR 1000-1050.
Also, please note the regulation entitled, "Misbranding by reference to premarket notification" (21 CFR Part 807.97). For questions regarding the reporting of adverse events under the MDR regulation (21 CFR Part 803), please go to http://www.fda.gov/MedicalDevices/Safety/ReportaProblem/default.htm for the CDRH's Office of Surveillance and Biometrics/Division of Postmarket Surveillance.
For comprehensive regulatory information about mediation-emitting products, including information about labeling regulations, please see Device Advice (https://www.fda.gov/MedicalDevices/DeviceRegulationandGuidance/) and CDRH Learn (http://www.fda.gov/Training/CDRHLearn). Additionally, you may contact the Division of Industry and Consumer Education (DICE) to ask a question about a specific regulatory topic. See the DICE website (http://www.fda.gov/DICE) for more information or contact DICE by email (DICE@fda.hhs.gov) or phone (1-800-638-2041 or 301-796-7100).
Sincerely,
Robert Sauer
for Robert A. Ochs. Ph.D. Director Division of Radiological Health Office of In Vitro Diagnostics and Radiological Health Center for Devices and Radiological Health
Enclosure
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DEPARTMENT OF HEALTH AND HUMAN SERVICES Food and Drug Administration
Indications for Use
510(k) Number (if known)
K180326
Device Name icobrain
Indications for Use (Describe)
icobrain is intended for automatic labeling, visualization and volumetric quantification of segmentable brain structures from a set of MR images. This software is intended to automate the current manual process of identifying, labeling and quantifying the volume of segmentable brain structures identified on MR images. icobrain consists of two distinct image processing pipelines: icobrain cross and icobrain long.
icobrain cross is intended to provide volumes from images acquired at a single timepoint icobrain long is intended to provide changes in volumes between two images that were acquired on the samer, with the same image acquisition protocol and with same contrast at two different timepoints The results of icobrain cross cannot be compared with the results of icobrain long.
Type of Use (Select one or both, as applicable)
Prescription Use (Part 21 CFR 801 Subpart D)
Over-The-Counter Use (21 CFR 801 Subpart C)
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l Submitter
| Name: | icometrix NV |
|---|---|
| Address: | Kolonel Begaultlaan 1b / 12 |
| 3012 Leuven | |
| BELGIUM | |
| Contact Person: | Dirk Smeets |
| Telephone number: | +32 16 369 000 |
| Fax Number: | N.A. |
| E-mail: | dirk.smeets@icometrix.com |
| Date Prepared: | 01 Feb 2018 |
2 Device
| Device Trade Name: | icobrain |
|---|---|
| Common Name: | Medical Image Processing Software |
| Classification Name: | System, Image processing, Radiological |
| Number: | 892.2050 |
| Product Code: | LLZ |
| Classification Panel: | Radiology |
Image /page/3/Figure/5 description: The image shows a fraction, specifically "2 / 6". The number 2 is above the fraction bar, and the number 6 is below the fraction bar. The background is a gradient of white to blue-green.
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3 Predicate Device
| Device | icobrain |
|---|---|
| 510(k) Number | K161148 |
| Manufacturer | icometrix NV |
| Common Name: | Medical Image Processing |
| Software | |
| Classification Name: | System, Image processing, |
| Radiological | |
| Number | 892.2050 |
| Product Code | LLZ |
| Classification Panel: | Radiology |
4 Device Description
icobrain is intended for automatic labeling, visualization and volumetric quantification of segmentable brain structures from a set of MR images. This software is intended to automate the current manual process of identifying, labeling and quantifying the volume of segmentable brain structures identified on MR images.
icobrain consists of two distinct image processing pipelines: icobrain cross and icobrain long.
- icobrain cross is intended to provide volumes from images acquired at a single timepoint
- · icobrain long is intended to provide changes in volumes between two images that were acquired on the same scanner, with the same image acquisition protocol and with same contrast at two different timepoints
The results of icobrain cross cannot be compared with the results of icobrain long.
The following flowchart illustrates the overall architecture of icobrain.
Image /page/4/Figure/9 description: This image is a flowchart that shows the steps involved in image processing. The first step is to input images in DICOM format. The next steps are preprocessing, image processing, and output generation (report/images). The final step is to generate a final report in PDF or DICOM format, as well as output images in DICOM format.
As input, icobrain uses TI-weighted and a fluid-attenuated inversion recovery (FLAIR) DICOM MR images from a single or from multiple time points. In case of multiple time points, i.e. multiple MRI scans from the same subject, for each time point one FLAIR and one TI image are used as input. During the pre-processing, the scan type (TI, FLAIR) is detected for every input image before it is converted from DICOM format to NIFTI format. The image processing then performs the actual segmentation and
5
calculates the volumes of the brain structures. In case MRI scans from the same subject on multiple time points are available, the changes in volume of the brain structures are calculated as well. Finally, the computed volumes and volume changes (in case of multiple time points) are summarized into an electronic report and (some) segmentations are overlaid on the input images.
The software displays the following volumetric measures in three reports
Report I:
- unnormalized volume and volume changes (total, new, enlarging and shrinking) of FLAIR white matter hyperintensities, in different regions (peri-ventricular, juxta-cortical, infra-tentorial, deep white matter).
- unnormalized volume and volume changes (total, new, enlarging and shrinking) of TI white matter hyperintensities and hypointensities.
- · normalized volume and volume changes of the whole brain (sum of white and grey matter),
- · normalized volume and volume changes of grey matter
Report 2:
- normalized volume and volume changes of the frontal, temporal and parietal lobe
- · normalized volume and volume changes of the hippocampi
- · unnormalized volume and volume changes of FLAIR white matter hyperintensities
Report 3:
- unnormalized volume and volume changes (total, new, enlarging and shrinking) of FLAIR white matter hyperintensities, in different regions (sub-cortical, corpus callosum, brainstem)
- · normalized volume and volume changes of the cortical gray matter
- · normalized volume and volume changes of the hippocampi
The whole brain, gray matter, cortical gray matter, frontal lobe, temporal lobe, parietal lobe and hippocampal volumes are normalized for head size by comparing to a healthy population using a statistical model. The reported FLAIR or TI white matter hyperintensities volumes are not normalized since they are not comparable to a reference population.
5 Intended use
icobrain is intended for automatic labeling, visualization and volumetric quantification of segmentable brain structures from a set of MR images. This software is intended to automate the current manual process of identifying, labeling and quantifying the volume of segmentable brain structures identified on MR images.
icobrain consists of two distinct image processing pipelines: icobrain cross and icobrain long.
- · icobrain cross is intended to provide volumes from images acquired at a single timepoint
- · icobrain long is intended to provide changes in volumes between two images that were acquired on the same scanner, with the same image acquisition protocol and with same contrast at two different timepoints
The results of icobrain cross cannot be compared with the results of icobrain long.
This intended use of the modified device is equal to the intended use of the previously cleared predicate device [K161148].
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6 Device modifications
icobrain 3.0 is an update of the icobrain 1.3 (the predicate device). The modifications of the device mostly include new measurements of brain segmentable structures, new output reports, new output images, and new output format (json).
New measurements:
- unnormalized volume and volume changes (total, new, enlarging and shrinking) of FLAIR white matter hyperintensities, in different regions (peri-ventricular, juxta-cortical, infra-tentorial, deep white matter, sub-cortical, corpus callosum, brainstem),
- unnormalized volume and volume changes (total, new, enlarging and shrinking) of T I white matter hyperintensities and hypointensities,
- · normalized volume and volume changes of the frontal, temporal and parietal lobe,
- · normalized volume and volume changes of the hippocampi,
- · normalized volume and volume changes of the cortical gray matter,
- · normalized volume and volume changes of the hippocampi.
These new measurements, together with the original measurements, are now structured in three different report types.
New output images include:
- · the segmentation of FLAIR WM hyperintensities, color-coded for the region and overlaid on the input FLAIR images,
- the segmentation of new and enlarging FLAIR WM hyperintensities, overlaid on the input FLAIR images,
- · the segmentation of frontal, temporal and parietal lobe and the hippocampi, overlaid on the input TI images.
7 Performance testing
Quality and safety
icobrain has been designed, developed and tested in accordance with the following product and process standards:
- · ISO 14971:2007 Medical devices Application of risk management to medical devices
- · IEC 62304:2006 Medical device software Software life-cycle processes
- · IEC 62366:2014 Medical devices Application of usability engineering to medical devices
- · ISO 12052:2006 Digital imaging and communication in medicine (DICOM)
- · CFR 21 part 820 Quality System Regulation for Medical Devices
- · ISO 13485:2016 Medical devices Quality management systems
The changes made in icobrain compared to the original device do not affect the safety of the device. This conclusion is based on:
- · Failure mode and effects analysis on the added functionality.
- · Risk category classification of new software components.
Product performance
To demonstrate the performance of icobrain, the measured volumes and volume changes of the segmentable brain structures are validated for accuracy and reproducibility. The subjects upon whom
7
the device was tested include healthy subjects, Alzheimer's disease patients, traumatic brain injury patients, depression patients.
In the accuracy experiments, the volumes / volume changes are compared to simulated and/or manually labeled ground truth volumes / volume changes; in the reproducibility experiments, the volumes / volume changes are compared on test-retest image data sets. A literature review has been performed to set relevant acceptance criteria for each type of experiments passed the acceptance criteria.
The experiments encompassed 463 subject datasets in total. Averaged over all experiments, the Pearson correlation coefficient between the compared measurements was 0.91 and the intraclass correlation coefficient was 0.89.
Besides the validation experiments, verification tests demonstrate the system as a whole provides all the capabilities necessary to operate according to its intended use.
8 Conclusions
Because of the identical intended use same and technological characteristics, icobrain 3.0 is substantially equivalent to a device (icobrain 1.3) that has been approved in the United States. The performance testing demonstrates that icobrain 3.0 is as safe and effective as the predicate device.
| Declarations: | • This summary includes only information that is also covered in the body of the 510(k).
• This summary does not contain any puffery or unsubstantiated labeling claims.
• This summary does not contain any raw data, i.e., contains only summary data.
• This summary does not contain any trade secret or confidential commercial information.
• This summary does not contain any patient identification information. |
| --------------- | --------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
|---|
This document is reviewed and approved by Dirk Smeets, Vice President Clinical Applications of ico metrix, based on the present data and information.
| Signature | |
|---|---|
| Date | ■ 08 Mar 2018 |
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