Brain WMH

by Quantib BV  · Based in Netherlands → — AI-powered neuroimaging analysis for precise brain health assessment.
Neurology Radiology

Contact for pricing
Regulatory Status Disclosed

Overview

Quantib Brain WMH, now integrated into DeepHealth’s Neuro Suite, is an FDA-cleared artificial intelligence (AI) software designed to support radiologists in interpreting brain MRI scans. It provides automatic labeling, visualization, and volumetric quantification of segmentable brain structures and white matter hyperintensities (WMH) from magnetic resonance (MR) images. The tool measures brain atrophy and detects WMH, which are critical neuroimaging features related to aging, dementia, and multiple sclerosis. It offers automatic atrophy analysis and longitudinal WMH analyses, distinguishing between new and previously identified WMHs. The output includes segmentations, visualizations, and volumetric measurements of grey matter, white matter, and cerebrospinal fluid, which can be compared to reference centile data. The software is deployed through the Quantib AI Node platform, enabling efficient workflow integration and web browser access to results.

Reviewed by Pouyan Golshani, MD — Interventional Radiologist

Key Features

  • Automatic labeling, visualization, and volumetric quantification of brain structures
  • Detection and quantification of white matter hyperintensities (WMH)
  • Automatic atrophy analysis and longitudinal atrophy analysis
  • Longitudinal WMH analyses, distinguishing new and previously identified WMHs
  • Comparison of volumetric measurements to reference centile data
  • Easy review and editing of WMH segmentation in an internet browser
  • Clear overviews of quantitative results in a report per analysis
  • Segmentations in DICOM secondary capture format
  • Color-coded anatomical overlays on T1 images and standard PACS viewers
  • Comprehensive reports integrating quantified measurements and segmentation results

Use Cases

  • Support radiologists in interpreting brain MRI scans
  • Measures brain atrophy and detects white-matter hyperintensities
  • Provides insight into atrophy related to Alzheimer's disease or other types of dementia
  • Tracking of neurodegeneration over time
  • Monitoring of Multiple Sclerosis (MS) patients
  • Aid in quantitative reporting for trained medical professionals

What Physicians Need to Know

Brain MRI Analysis
Automates segmentation, visualization, and volumetric quantification of brain structures including grey matter, white matter, cerebrospinal fluid, and white matter hyperintensities (WMH) from MR images (3D T1, 2D/3D T2 FLAIR). Provides segmentation overlays and draft radiology reports with normative comparisons.
Neurodegenerative Disease Screening
Offers insights into atrophy associated with Alzheimer's disease, other dementias, and supports monitoring of Multiple Sclerosis (MS) patients by tracking WMH development and differentiating between new and previously identified lesions. Facilitates longitudinal analysis for tracking changes over time and compares volumetric measurements to reference centile data.
Physician Tip

Leverage the quantitative measurements for objective assessment and consistent follow-up in neurodegenerative disease management. Utilize the longitudinal analysis feature to track subtle changes in brain atrophy and WMH progression over time. Always review and, if necessary, edit the automated WMH segmentations before final validation to ensure accuracy in quantitative reporting. Integrate the comprehensive reports into multidisciplinary team communications for enhanced patient care.

The tool integrates via AI marketplaces or distribution platforms, and can also function as a standalone third-party application. It provides output in formats such as segmentation overlays and draft radiology reports, including DICOM secondary capture format for segmentations, enabling seamless PACS integration for immediate visual assessment.

Details

Category Neurology AI, Radiology & Imaging AI
Pricing Contact for pricing — Subscription-based; tiers typically based on number of installations and users.
DeploymentOn-premise (locally on dedicated hardware) via Quantib AI Node platform, with web browser access
Compliance
BAA AvailableUnknown AI-estimated
HIPAA CompliantUnknown AI-estimated
FDA Status Yes AI-estimated

FDA 510(k) cleared (K251527) for Brain WMH. It is a non-invasive medical imaging processing application intended for automatic labeling, visualization, and volumetric quantification of segmentable brain structures and white matter hyperintensities from MR images. It aids trained medical professionals in the evaluation and assessment of MR brain images and quantitative reporting for patients 22 years or older, without pathologies (e.g., tumor or stroke), treatment-induced features, and without contrast enhancement.

Integrations
EHR Not specified
Specialties Neurology, Radiology

What the Web Says

Quantib Brain WMH is an FDA-cleared and CE-marked AI-powered software designed to automatically label, visualize, and volumetrically quantify white matter hyperintensities (WMHs) from T2-weighted FLAIR MR images. It aims to assist trained medical professionals in evaluating and assessing MR brain images and aid in quantitative reporting, especially for conditions related to aging, dementia, and multiple sclerosis. The software provides segmentations and volumetric measurements of WMHs, and its newer versions also offer automatic longitudinal atrophy and WMH analyses.

Overall: Positive

Strengths

  • Automated segmentation and volumetric quantification of WMHs, streamlining clinical workflow.
  • Aids in quantitative reporting and evaluation of brain MR images for conditions like dementia and multiple sclerosis.
  • Offers longitudinal analysis for tracking WMH progression over time.
  • Validated for accuracy against manual segmentations on diverse datasets.
  • FDA-cleared and CE-marked, indicating regulatory compliance and safety.
  • Can operate as a plug-in for GE Advantage Workstation, integrating into existing radiology environments.

Limitations

  • Requires user review and validation of WMH segmentations before reporting.
  • Older versions of Quantib Brain required both FLAIR and T1 scans, though newer versions only need T2 FLAIR.
  • Diagnostic agreement between different software packages for normative brain volumetry can be moderate.
  • While WMH are associated with cognitive decline, the exact relationship and efficacy of interventions targeting WMH reduction still require further research.

Based on reviews from: RadAI Slice, AuntMinnie, SourceForge, PubMed, FDA.report, X-ray Interpreter

Last updated: 2026-07-19

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Press & Coverage

FDA
510(k) Premarket Notification - Brain WMH
Quantib BV received FDA clearance for its Brain WMH software, a Class II medical device intended for automatic labeling, visualization, and volumetric quantification of white matter hyperintensities (WMH) from T2w FLAIR MR images. The device is designed to provide trained medical professionals with complementary information for evaluating and assessing MR brain images.
2025-09
Nyquist AI Blog
Data Update: October 2025 - Nyquist AI Blog
This blog post highlights key FDA device approvals and regulatory updates from September 2025, including the clearance of Quantib BV's Brain WMH (K251527) in the radiology category. It notes the device's approval date as September 25, 2025.
2025-10
RadAI Slice
AI CT model predicts HCC risk in cirrhosis with AUC up to 0.87 | Rad AI Slice
RadAI Slice mentions the FDA 510(k) clearance of Quantib BV's Brain WMH (K251527), which automates white matter hyperintensity quantification. This news is part of a weekly roundup of radiology AI news articles.
2025-10
NC DHHS
ECU Health Chowan Hospital - NC DHHS
A document from ECU Health Chowan Hospital mentions Quantibu2122 Brain as medical imaging processing software that includes a WMH segmentation function for longitudinal analysis. This software is part of the advanced applications available on a GE Signa Artist MRI Scanner.
2024-11
T2S Group
SIGNAu2122 Pioneer - T2S Group
This brochure for GE Healthcare's SIGNAu2122 Pioneer MRI system highlights Quantibu2122 Brain as a medical imaging processing software. It notes that Quantibu2122 Brain is intended for automatic labeling, visualization, and volumetric quantification of segmentable brain structures, including white matter hyperintensity (WMH) candidates.
unknown
X-ray Interpreter (RadAI Slice)
Quantib Brain | FDA Radiology AI Device - X-ray Interpreter
This entry details Quantib Brain, a software application approved by the FDA in 2018 for automatic labeling, visualization, and volumetric quantification of brain structures and white matter lesions on MRI scans. It also lists 'Brain WMH' as another device from Quantib BV, with a 510K approval in 2025.
2018-03
X-ray Interpreter (RadAI Slice)
Quantib Brain 1 | FDA Radiology AI Device - X-ray Interpreter
This article describes Quantib Brain 1, an AI-powered software tool FDA-approved in 2016 that automatically labels and measures brain structures from MRI scans, including white matter hyperintensities. It also mentions 'Brain WMH' as a 2025 510K approval for Quantib BV.
2016-06
ResearchGate
Examples of deep white matter hyperintensity (A) and periventricular... - ResearchGate
This research diagram refers to the use of automated segmentation software, Quantibu2122 Brain (GE Healthcare), for volumetric analysis of brain MRI, specifically in the context of white matter hyperintensities.
unknown

Videos

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Frequently Asked Questions

AI algorithms can automate the segmentation and quantification of White Matter Hyperintensities (WMH) from MRI scans, providing objective metrics like volume and location. This can enhance diagnostic consistency, track disease progression more accurately, and potentially streamline radiologist workflow by flagging areas of interest.
Physicians must ensure that any AI tool used for WMH analysis has appropriate regulatory clearance (e.g., FDA 510(k), CE Mark) for its intended use. Strict adherence to HIPAA, GDPR, and other data privacy regulations is crucial, requiring secure data handling, anonymization, and patient consent protocols.
AI solutions generally offer superior efficiency by automating time-consuming manual segmentation, significantly reducing radiologist workload. While accuracy can vary by algorithm, many AI tools demonstrate comparable or even improved inter-rater reliability and consistency compared to human readers, especially for large datasets.
Pricing models often include per-study fees, annual subscriptions, or enterprise licenses, varying by vendor and features. Currently, specific reimbursement codes for AI-driven WMH quantification are evolving, and physicians may need to explore existing CPT codes for image analysis or seek institutional coverage.
AI algorithms can exhibit biases if trained on unrepresentative datasets, potentially leading to reduced accuracy in diverse populations or with atypical WMH patterns. Performance can also be sensitive to variations in MRI scanner types, acquisition parameters, and image quality, requiring careful validation in specific clinical settings.
Most AI solutions are designed for seamless integration with existing Picture Archiving and Communication Systems (PACS) for image retrieval and Electronic Health Record (EHR) systems for reporting, often via standard protocols like DICOM and HL7. Required IT infrastructure typically involves secure cloud connectivity or on-premise servers with sufficient computational power, depending on the deployment model.
Ethical considerations include ensuring transparency in how AI algorithms arrive at their conclusions, avoiding over-reliance that could diminish clinical judgment, and addressing potential issues of algorithmic bias that might exacerbate health disparities. Physicians retain ultimate responsibility for patient care, even with AI assistance.

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Suggest an Edit → | Last Verified: 2026-04-19 | First Added: 2026-04-19
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