(100 days)
Quantib™ ND is a non-invasive medical imaging processing application that is intended for automatic labeling, visualization, and volumetric quantification of segmentable brain structures from a set of magnetic resonance (MR) images. The Quantib™ ND output consists of segmentations, visualizations and volumetric measurements of brain structures and white matter hyperintensities. Volumetric measurements may be compared to reference centile data. It is intended to provide the trained medical professional with complementary information for the evaluation and assessment of MR brain images and to aid the trained medical professional in quantitative reporting. Quantib™ ND is a software application on top of Myrian®.
Quantib™ ND is a post-processing analysis module for Myrian®, which provides 3D image visualization tools that create and display user-defined views and streamlines interpretation and reporting. It is intended for automatic labeling, visualization, and volumetric quantification of identifiable brain structures from magnetic resonance images (a 3D T1-weighted MR image, with an additional T2-weighted FLAIR MR image for white matter hyperintensities (WMH) segmentation). The segmentation system relies on a number of atlases each consisting of a 3D T1-weighted MR image and a label map dividing the MR image into different tissue segments. Quantib™ ND provides quantitative information on both the absolute and relative volume of the segmented regions. The automatic WMH segmentation is to be reviewed and if necessary. edited by the user before validation of the segmentation, after which volumetric information is accessible. Quantib ND consists of Quantib ND Baseline, which provides analysis of images of one time-point, and Quantib ND Follow-Up, which provides longitudinal analysis of images of two time-points. Quantib ND Follow-Up can only process images that have been processed by Quantib ND Baseline. Quantib ND is intended to provide the trained medical professional with complementary information for the evaluation and assessment of MR brain images and to aid the radiology specialist in quantitative reporting.
Here's a summary of the acceptance criteria and the study that proves the device meets them, based on the provided text:
1. Table of Acceptance Criteria and Reported Device Performance
The document does not explicitly state acceptance criteria in the form of pre-defined thresholds for Dice index or absolute difference of relative volumes. However, the performance data is presented against manual segmentations, implying that the acceptance criteria are generally "good agreement" or "sufficient similarity" to manual segmentations, as judged by the provided metrics. For the purpose of this table, I'll assume that the reported values demonstrate that the device met an implicit acceptance standard.
| Brain Structure / Metric | Acceptance Criteria (Implicit) | Reported Device Performance (Mean ± Std. Dev.) |
|---|---|---|
| Brain Tissue Segmentations | ||
| Brain Dice Index | "Good agreement" | 0.96 ± 0.01 |
| Brain Absolute Diff. of Rel. Volumes [pp] | "Good agreement" | 1.7 ± 1.3 |
| CSF Dice Index | "Good agreement" | 0.78 ± 0.05 |
| CSF Absolute Diff. of Rel. Volumes [pp] | "Good agreement" | 1.8 ± 1.3 |
| ICV Dice Index | "Good agreement" | 0.98 ± 0.01 |
| Hippocampus Segmentations | ||
| Hippocampus total Dice Index | "Good agreement" | 0.84 ± 0.03 |
| Hippocampus total Absolute Diff. of Rel. Volumes [pp] | "Good agreement" | 0.03 ± 0.02 |
| Hippocampus right Dice Index | "Good agreement" | 0.84 ± 0.03 |
| Hippocampus right Absolute Diff. of Rel. Volumes [pp] | "Good agreement" | 0.01 ± 0.01 |
| Hippocampus left Dice Index | "Good agreement" | 0.84 ± 0.03 |
| Hippocampus left Absolute Diff. of Rel. Volumes [pp] | "Good agreement" | 0.01 ± 0.01 |
| Lobe Segmentations (Dataset C) | ||
| Frontal lobe total Dice Index | "Good agreement" | 0.95 ± 0.01 |
| Frontal lobe total Absolute Diff. of Rel. Volumes [pp] | "Good agreement" | 1.95 ± 0.90 |
| Occipital lobe total Dice Index | "Good agreement" | 0.88 ± 0.03 |
| Occipital lobe total Absolute Diff. of Rel. Volumes [pp] | "Good agreement" | 0.87 ± 0.75 |
| Parietal lobe total Dice Index | "Good agreement" | 0.89 ± 0.03 |
| Parietal lobe total Absolute Diff. of Rel. Volumes [pp] | "Good agreement" | 2.81 ± 1.13 |
| Temporal lobe total Dice Index | "Good agreement" | 0.91 ± 0.01 |
| Temporal lobe total Absolute Diff. of Rel. Volumes [pp] | "Good agreement" | 1.33 ± 0.76 |
| Cerebellum total Dice Index | "Good agreement" | 0.98 ± 0.01 |
| Cerebellum total Absolute Diff. of Rel. Volumes [pp] | "Good agreement" | 0.47 ± 0.20 |
| White Matter Hyperintensities (WMH) | ||
| WMH Dice Overlap | "Good agreement" | 0.61 ± 0.13 |
| WMH Absolute Diff. of Rel. Volumes [pp] | "Good agreement" (for non-CE cases) | 0.2 ± 0.2 |
2. Sample Sizes Used for the Test Set and Data Provenance
- Brain Tissue, CSF, ICV (Dataset A):
- Sample Size: 33 T1w MR images.
- Data Provenance: "carefully selected to include data from multiple vendors and a series of representative scan settings." No specific country of origin or retrospective/prospective status is mentioned, but the description implies a historical or retrospective collection.
- Hippocampus (Dataset B):
- Sample Size: 89 T1w images.
- Data Provenance: Not explicitly detailed beyond being T1w images. Implied retrospective.
- Lobes (Dataset C):
- Sample Size: 13 T1w MR images.
- Data Provenance: Not explicitly detailed. Implied retrospective.
- White Matter Hyperintensities:
- Sample Size: 45 3D T1w images (7 contrast-enhanced), each with corresponding T2w FLAIR images.
- Data Provenance: "represented various scan settings." Implied retrospective.
- Note: The absolute difference of relative volumes for WMH was computed over 38 cases (those without contrast-enhancement).
3. Number of Experts Used to Establish the Ground Truth for the Test Set and Their Qualifications
- The document states that the segmentations were compared to "manual segmentations."
- It does not specify the number of experts who performed these manual segmentations nor their qualifications (e.g., radiologist with X years of experience).
4. Adjudication Method for the Test Set
- The document only mentions "manual segmentations" as the ground truth. It does not provide any information about an adjudication method (such as 2+1, 3+1, or none) for these manual segmentations. It implies a single manual segmentation was used as the reference.
5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study Was Done
- No, the provided text does not describe a multi-reader multi-case (MRMC) comparative effectiveness study evaluating how much human readers improve with AI vs. without AI assistance. The study focuses solely on the standalone performance of the AI algorithm compared to manual segmentations.
6. If a Standalone Study (Algorithm Only Without Human-in-the-Loop Performance) Was Done
- Yes, a standalone performance study was done. The "Algorithm Performance" section details the comparison of the Quantib™ ND algorithm's segmentations and volume measurements against manual segmentations, without human-in-the-loop interaction with the AI.
7. The Type of Ground Truth Used
- The type of ground truth used was expert manual segmentation. The text explicitly states, "To validate the quality of Quantib™ ND volume measurements and segmentations, these were compared to manual segmentations of the same scan and their derived volumes."
8. The Sample Size for the Training Set
- The document does not provide information regarding the sample size used for the training set of the Quantib™ ND algorithm. It only discusses the test sets used for validation.
9. How the Ground Truth for the Training Set Was Established
- The document does not provide information on how the ground truth for the training set was established. It only details the method for establishing ground truth for the validation/test sets (manual segmentations).
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December 27, 2018
Quantib BV Floor Van Leeuwen Ouality & Regulatory Manager Westblaak 106 ROTTERDAM, NL 3012 KM ZUID-HOLLAND
Re: K182564
Trade/Device Name: Ouantib ND Regulation Number: 21 CFR 892.2050 Regulation Name: Picture Archiving And Communications System Regulatory Class: Class II Product Code: LLZ Dated: November 12, 2018 Received: November 14, 2018
Dear Floor Van Leeuwen:
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. Although this letter refers to your product as a device, please be aware that some cleared products may instead be combination products. The 510(k) Premarket Notification Database located at https://www.accessdata.fda.gov/scripts/cdrh/cfdocs/cfpmn/pmn.cfm identifies combination product submissions. 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
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801); medical device reporting of medical device-related adverse events) (21 CFR 803) for devices or postmarketing safety reporting (21 CFR 4, Subpart B) for combination products (see https://www.fda.gov/CombinationProducts/GuidanceRegulatoryInformation/ucm597488.htm); good manufacturing practice requirements as set forth in the quality systems (OS) regulation (21 CFR Part 820) for devices or current good manufacturing practices (21 CFR 4, Subpart A) for combination products; 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 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,
Michael D. O'Hara
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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Indications for Use
510(k) Number (if known) K182564
Device Name Quantib™ ND 1.5
Indications for Use (Describe)
Quantib™ ND is a non-invasive medical imaging processing application that is intended for automatic labeling, visualization, and volumetric quantification of segmentable brain structures from a set of magnetic resonance (MR) images. The Quantib™ ND output consists of segmentations, visualizations and volumetric measurements of brain structures and white matter hyperintensities. Volumetric measurements may be compared to reference centile data. It is intended to provide the trained medical professional with complementary information for the evaluation and assessment of MR brain images and to aid the trained medical professional in quantitative reporting. Quantib™ ND is a software application on top of Myrian®.
| Type of Use (Select one or both, as applicable) | |
|---|---|
| ------------------------------------------------- | -- |
X Prescription Use (Part 21 CFR 801 Subpart D)
Over-The-Counter Use (21 CFR 801 Subpart C)
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Quantib™ ND 1.5 510(k) Summary
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SUBMITTER 1
Quantib B.V. Westblaak 106 3012 KM Rotterdam Phone: (+31) 108 41 17 49 Contact Person: Floor van Leeuwen Date Prepared: September 17th, 2018
Device 2
Name of Device: Quantib™ ND 1.5 Common or Usual Name: Quantib™ ND Classification Name: System, image processing, radiology (892.2050) Regulatory Class: II Product Code: Picture archiving and communication system (LLZ)
3 PREDICATE DEVICE
Device: Quantib™ Brain 1.3 Manufacturer: Quantib B.V. 510(k) Reg. No: K173939 This predicate has not been subject to a design-related recall. Classification Name: System, image processing, radiology (892.2050) Requlatory Class: II Product Code: Picture archiving and communication system (LLZ)
Device description বা
Quantib™ ND is a post-processing analysis module for Myrian®, which provides 3D image visualization tools that create and display user-defined views and streamlines interpretation and reporting. It is intended for automatic labeling, visualization, and volumetric quantification of identifiable brain structures from magnetic resonance images (a 3D T1-weighted MR image, with an additional T2-weighted FLAIR MR image for white matter hyperintensities (WMH) segmentation). The segmentation system relies on a number of atlases each consisting of a 3D T1-weighted MR image and a label map dividing the MR image into different tissue segments.
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Quantib™ ND provides quantitative information on both the absolute and relative volume of the seqmented regions. The automatic WMH segmentation is to be reviewed and if necessary. edited by the user before validation of the segmentation, after which volumetric information is accessible. Quantib ND consists of Quantib ND Baseline, which provides analysis of images of one time-point, and Quantib ND Follow-Up, which provides longitudinal analysis of images of two time-points. Quantib ND Follow-Up can only process images that have been processed by Quantib ND Baseline. Quantib ND is intended to provide the trained medical professional with complementary information for the evaluation and assessment of MR brain images and to aid the radiology specialist in quantitative reporting.
5 Indications for Use
Indications for use Quantib™ ND 1.5
Quantib™ ND is a non-invasive medical imaging processing application that is intended for automatic labeling, visualization, and volumetric quantification of segmentable brain structures from a set of magnetic resonance (MR) images. The Quantib™ ND output consists of segmentations, visualizations and volumetric measurements of brain structures and white matter hyperintensities. Volumetric measurements may be compared to reference centile data. It is intended to provide the trained medical professional with complementary information for the evaluation and assessment of MR brain images and to aid the trained medical professional in quantitative reporting. Quantib™ ND is a software application on top of Myrian®.
Indications for use predicate device (Quantib™ ND 1.3)
Quantib™ Brain is a non-invasive medical imaging processing application that is intended for automatic labeling, visualization, and volumetric quantification of segmentable brain structures from a set of magnetic resonance (MR) images. The Quantib™ Brain output consists of segmentations, visualizations and volumetric measurements of grey matter (GM), white matter (WM), and cerebrospinal fluid (CSF). The output also visualizes and quantifies white matter hyperintensity (WMH) candidates. Users need to review and if necessary, edit WMH candidates using the provided tools, before validation of the WMHs. It is intended to provide the trained medical professional with complementary information for the evaluation and assessment of MR brain images and to aid the trained medical professional in quantitative reporting. Quantib™ Brain is a post-processing plugin for the GE Advantage Workstation (AW 4.7) or AW Server (AWS 3.2) platforms.
Indications for use comparison
The intended use of the device is partially equivalent to the intended use of the previously cleared predicate device [K173939]
Comparison of technological characteristics 6
The following technological characteristics are the same for Quantib™ ND 1.5 and its predicate device Quantib™ Brain 1.3:
- . Target users, anatomical site, and usage location
- . Design
- Standards met ●
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-
. Required input
The following technological characteristics are different: -
. Indications for use and Intended use: The device is a software application on top of Myrian®; Seqmentation and quantification of separate lobes and hippocampus, comparison of whole brain, lobes, and hippocampus volumes to reference centile curves of a group representing the general population, and improved longitudinal volume change calculation using automated image registration are added.
-
. Human factors: Similar workflow, but implementation is slightly different based on existing workflow of underlying software packages
-
. Algorithm design For hippocampus segmentation, a slightly different refinement step is used than for other brain structures. Brain structures follow-up analysis is done using technological characteristics also applied elsewhere in Quantib ND and the predicate device.
-
. Performance: For measures reported by both devices, performance numbers show slight changes, attributable to the underlying software packages. Assessment of the performance of segmentation of separate lobes, hippocampus, and reference centile curves is added.
-
. Compatibility with the environment and other devices: Quantib™ ND is an add-on for Myrian, which can be installed on reqular hardware using Windows as operating system.
-
Reported measures: Whole brain measures (sum of Grey Matter [GM] and White Matter ● [WM]) are reported instead of GM and WM separately. To the reported measures the volumes of the following structures are added: Hippocampus, Frontal Lobe, Occipital Lobe, Parietal Lobe, Temporal Lobe, and Cerebellum. Reference centile curves are added, comparing these results to a group representing the general population.
Performance data 7
7.1 QUALITY AND SAFETY
Quantib™ ND 1.5 was designed in compliance with the following process standards:
- . ISO 14971 – Medical devices - Application of risk management to medical devices
- IEC 62304 Medical device software Software life cycle processes .
- IEC 62366 Medical devices Application of usability engineering to medical devices .
The following quality assurance measures were applied to Quantib™ ND 1.5 development:
- Risk and hazard analysis
- Design reviews .
- Unit level testing ●
- Integration testing ●
- System testing .
- Performance testing .
- . Usability engineering
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7.2 ALGORITHM PERFORMANCE
7.2.1 Brain Structures
To validate the quality of Quantib™ ND volume measurements and segmentations, these were compared to manual seqmentations of the same scan and their derived volumes. This analysis was performed for Brain Tissue, CSF, ICV, Hippocampus, Frontal Lobe, Occipital Lobe, Parietal Lobe, Temporal Lobe, and Cerebellum.
For brain tissue, CSF, and ICV, the test set included 33 T1w MR images (Dataset A). The set was carefully selected to include data from multiple vendors and a series of representative scan settings. For each scan we selected six (6) slices for comparison. For the hippocampus the test set included 89 T1w images (Dataset B) and for the lobes the test set included 13 T1w MR images (Dataset C). For test sets B and C all slices were segmented manually for the comparison. The results are summarized below.
| Dataset | Dice index | Absolute difference ofthe relative volumes [pp] | |
|---|---|---|---|
| Brain | A | 0.96 ± 0.01 | 1.7 ± 1.3 |
| CSF | A | 0.78 ± 0.05 | 1.8 ± 1.3 |
| ICV | A | 0.98 ± 0.01 | - |
| Hippocampus total | B | 0.84 ± 0.03 | 0.03 ± 0.02 |
| Hippocampus right | 0.84 ± 0.03 | 0.01 ± 0.01 | |
| Hippocampus left | 0.84 ± 0.03 | 0.01 ± 0.01 |
Results of comparison between manual and automatic brain structure segmentation. Reported values are averages ± std. dev., computed over 6 segmented slices of 33 scans (Dataset B all slices were segmented. The Dice index provides a measure for overlap of manual and automatic segmentations (1 = perfect overlap). The absolute differences of the relative volumes are averages ± std. dev. in percentage points.
| Dataset | Dice index | Absolute difference ofthe relative volumes [pp] | |
|---|---|---|---|
| Frontal lobe total | C | 0.95 ± 0.01 | 1.95 ± 0.90 |
| Frontal lobe right | 0.94 ± 0.02 | 1.02 ± 0.61 | |
| Frontal lobe left | 0.94 ± 0.01 | 0.93 ± 0.50 | |
| Occipital lobe total | C | 0.88 ± 0.03 | 0.87 ± 0.75 |
| Occipital lobe right | 0.88 ± 0.03 | 0.43 ± 0.36 | |
| Occipital lobe left | 0.87 ± 0.04 | 0.53 ± 0.53 | |
| Parietal lobe total | C | 0.89 ± 0.03 | 2.81 ± 1.13 |
| Parietal lobe right | 0.88 ± 0.04 | 1.45 ± 0.80 | |
| Parietal lobe left | 0.88 ± 0.02 | 1.36 ± 0.56 | |
| Temporal lobe total | C | 0.91 ± 0.01 | 1.33 ± 0.76 |
| Temporal lobe right | 0.91 ± 0.02 | 0.72 ± 0.46 | |
| Temporal lobe left | 0.91 ± 0.01 | 0.61 ± 0.39 | |
| Cerebellum total | C | 0.98 ± 0.01 | 0.47 ± 0.20 |
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| Cerebellum right | 0.97 ± 0.00 | 0.31 ± 0.13 |
|---|---|---|
| Cerebellum left | 0.97 ± 0.01 | 0.17 ± 0.11 |
Results of comparison between manual and automatic brain structure segmentation of the lobes. Reported values are averages ± std. dev., computed over 13 scans of which all slices were segmented (Dataset C). The Dice index provides a measure for overlap of manual and automatic segmentations (1 = perfect overlap). The absolute differences of the relative volumes are averages ± std. dev. in percentage points.
7.2.2 White Matter Hyperintensities
The test set for the White Matter Hyperintensities analysis included 45 3D T1w images, of which 7 contrast-enhanced, all with corresponding T2w FLAIR images. This set also represented various scan settings. WMHs were manually segmented on the T2w FLAIR images and compared to Quantib™ ND automatic segmentation output. The average Dice overlap between the manual segmentations and Quantib™ ND segmentations was 0.61 ± 0.13 (over all cases). The absolute difference of the relative volumes (for WMHs) was 0.2 ± 0.2 percentage points (over 38 cases without contrast-enhancement).
CONCLUSIONS 8
By virtue of its intended use and physical and technological characteristics, Quantib™ ND 1.5 is substantially equivalent to a device that has been approved for marketing in the United States. The performance data shows that Quantib™ ND 1.5 is as safe and effective as the predicate device.
§ 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).