Input or output interoperability
DICOM is explicitly referenced in the described input, output, or workflow.
exact submission · checked 2026-09-01The model card does not establish every supported DICOM object, transfer method, or local interface.
FDA-cleared profile
Quantib ND
Quantib B.V.
Authorized purpose: Automatic labeling, visualization, and volumetric quantification of segmentable brain structures from MR images, with complementary segmentations, visualizations, and volume measurements for trained professionals evaluating MR brain images and preparing quantitative reports.
Evidence status: each field states its source quality, applicability, and review date. Research pending, information not established, and vendor documentation pending remain distinct outcomes.
Product overview
Start with the essentials
Authorized purpose: Automatic labeling, visualization, and volumetric quantification of segmentable brain structures from MR images, with complementary segmentations, visualizations, and volume measurements for trained professionals evaluating MR brain images and preparing quantitative reports.
Overview status: Source-reviewed overview
- What does this software do? Authorized purpose: Automatic labeling, visualization, and volumetric quantification of segmentable brain structures from MR images, with complementary segmentations, visualizations, and volume measurements for trained professionals evaluating MR brain images and preparing quantitative reports.
- Which images or clinical context are in scope? Modality: MRI Anatomy or clinical context: Brain structures and white matter hyperintensities Input: A 3D T1-weighted MR image for brain-structure segmentation plus an additional T2-weighted FLAIR MR image for white-matter-hyperintensity segmentation; longitudinal analysis uses images from two or more time points.
- Who uses it? Intended users: Trained medical professionals, including radiology specialists.
- What does the software produce? Output: Automatic segmentations, visualizations, and absolute and relative volumes for brain tissue, CSF, ICV, hippocampus, lobes, cerebellum, and white matter hyperintensities, with single-time-point or longitudinal reports and export of reports and segmentations to a configured DICOM node such as PACS.
- What is its most important limitation? Key limitation: White-matter-hyperintensity segmentation must be reviewed and, if necessary, edited before validation. Longitudinal workflows require two or more time points. Results are complementary information for trained medical-professional review, not an independent diagnostic claim. The FDA performance sets were component-specific and do not establish every protocol or local client configuration.
Clinical takeaway
Clinical role: Automatic labeling, visualization, and volumetric quantification of segmentable brain structures from MR images, with complementary segmentations, visualizations, and volume measurements for trained professionals evaluating MR brain images and preparing quantitative reports.
Evidence takeaway
Evidence from the reviewed source record: FDA algorithm testing compared automated and manual segmentations. Brain-structure testing used 33 T1-weighted scans for brain tissue, CSF, and ICV, 89 T1-weighted scans for hippocampus, and 13 T1-weighted scans for lobes; Dice values ranged from 0.78 to 0.99 across the reported structures. White-matter-hyperintensity testing used 45 paired T1-weighted and T2-weighted FLAIR images and reported mean Dice overlap 0.61 +/- 0.13; relative-volume difference was 0.2 +/- 0.2 percentage points over 38 non-contrast cases. These are segmentation and volume-agreement endpoints.
Clinical details
What this tool is for
Start with the authorized purpose, then verify how it fits your service line and reading workflow.
- Exact purpose
- Automatic labeling, visualization, and volumetric quantification of segmentable brain structures from MR images, with complementary segmentations, visualizations, and volume measurements for trained professionals evaluating MR brain images and preparing quantitative reports.
- Intended users
- Trained medical professionals, including radiology specialists.
- Care setting and population
- Clinical radiology workflow using a Linux-based server-client system accessible by web browser from configured client systems; the FDA packet does not specify a facility type.
- Workflow role
- Post-acquisition MR segmentation and volumetric post-processing; white-matter-hyperintensity results require user review, editing when needed, and validation, followed by report and DICOM export.
- Required input
- A 3D T1-weighted MR image for brain-structure segmentation plus an additional T2-weighted FLAIR MR image for white-matter-hyperintensity segmentation; longitudinal analysis uses images from two or more time points.
- Output and human action
- Automatic segmentations, visualizations, and absolute and relative volumes for brain tissue, CSF, ICV, hippocampus, lobes, cerebellum, and white matter hyperintensities, with single-time-point or longitudinal reports and export of reports and segmentations to a configured DICOM node such as PACS.
- Limitations
- White-matter-hyperintensity segmentation must be reviewed and, if necessary, edited before validation. Longitudinal workflows require two or more time points. Results are complementary information for trained medical-professional review, not an independent diagnostic claim. The FDA performance sets were component-specific and do not establish every protocol or local client configuration.
Regulatory identity
FDA record and catalog context
The FDA listing establishes the regulatory identity. It does not by itself establish local workflow fit, pricing, security, or performance in your environment.
Implementation
Questions for IT, informatics, and operations
Use these fields to structure a vendor demo, security review, and implementation estimate.
- Integration
- Reports and segmentations are automatically exported to a configured DICOM node, such as a PACS system, and can be viewed with a DICOM viewer; the packet describes a Linux server-client platform and browser clients but does not establish interface versions or local compatibility.
- Deployment and data flow
- On-cloud
Deployment category preserved from the prior exact-submission review; hosting region, data flow, and current commercial configuration still require vendor confirmation.
- Security and privacy
- Vendor documentation pending
Exact-release security controls, data retention, hosting boundaries, and scoped assurance documentation require vendor confirmation.
- Training and support
- Vendor documentation pending
Current training prerequisites, competency checks, and support commitments for the exact configuration require vendor confirmation.
- Monitoring and change control
- Vendor documentation pending
Current drift, quality, uptime, alert, escalation, and incident-response commitments for the exact configuration require vendor confirmation.
Result destination
PACS is explicitly referenced as a result destination.
exact submission · checked 2026-09-01Confirm supported products, versions, routing behavior, and display requirements during local evaluation.
Supported acquisition environment
Scanner manufacturers: All
exact submission · checked 2026-09-01Confirm currently supported software versions, protocols, and site-specific acquisition configurations.
ACR exact-submission catalog context
ACR AI Central provides an exact-submission model card for Quantib ND; FDA labeling remains controlling for clinical use, limitations, and performance.
exact submission · checked 2026-09-09Evidence
Performance evidence
Metrics are shown only when they are tied to a source, endpoint, population, and tested product version. Candidate literature without exact product and version linkage is not shown as product evidence.
- Evidence summary
- FDA algorithm testing compared automated and manual segmentations. Brain-structure testing used 33 T1-weighted scans for brain tissue, CSF, and ICV, 89 T1-weighted scans for hippocampus, and 13 T1-weighted scans for lobes; Dice values ranged from 0.78 to 0.99 across the reported structures. White-matter-hyperintensity testing used 45 paired T1-weighted and T2-weighted FLAIR images and reported mean Dice overlap 0.61 +/- 0.13; relative-volume difference was 0.2 +/- 0.2 percentage points over 38 non-contrast cases. These are segmentation and volume-agreement endpoints.
- Reported sensitivity
- Research pending
This field has not been curated yet.
- Reported specificity
- Research pending
This field has not been curated yet.
No contextualized exact-version metric has completed evidence review. Regulatory-document values, when available, are shown above with their limitations.
Quantib ND regulatory performance study summary
- DesignStand-Alone Performance
- PopulationPopulation described in the exact-submission ACR model card
- Scopeexact submission
- Tested versionExact product version not reported; regulatory study summarized for FDA submission K213737
- Samplen=33
- IndependenceIndependence not established
K213737
ACR AI Central summarizes the regulatory study; consult the exact FDA materials before comparative use.
Costs and setup
Budget and ongoing governance
These are common procurement questions; unknown values remain visible until a source supports them.
- Pricing and total cost
- Vendor documentation pending
No public price or quote for the exact K213737 configuration was established in this review.
- Reimbursement and coding
- Not established in reviewed sources
No exact-product payer policy, coding instruction, or payment determination was established; eligibility must be evaluated by payer, site of service, and use case.
Safety and lifecycle
Postmarket record
Recall and adverse-event records are shown only after product matching. Adverse-event reports do not establish incidence or causality.
- Postmarket safety review
- The exact-identifier FDA recall query returned no native recall record for K213737. This limited result does not establish absence of recalls or other safety information and does not cover later versions, family records, MAUDE reports, corrections, or field notices.
Buyer worksheet
Open questions to take to the vendor
- Verify security and privacy controls: Exact-release security controls, data retention, hosting boundaries, and scoped assurance documentation require vendor confirmation.
- Verify training: Current training prerequisites, competency checks, and support commitments for the exact configuration require vendor confirmation.
- Verify pricing and total cost: No public price or quote for the exact K213737 configuration was established in this review.
- Verify reimbursement and coding relevance: No exact-product payer policy, coding instruction, or payment determination was established; eligibility must be evaluated by payer, site of service, and use case.
- Verify local validation and lifecycle monitoring: Current drift, quality, uptime, alert, escalation, and incident-response commitments for the exact configuration require vendor confirmation.
Research record
What has been checked
This audit distinguishes completed source review from fields that have not yet been researched.
Exact FDA record reviewedStatus
2026-09-20Last searched
23Fields reviewed
9Source classes checked
3Screened PubMed leads
0Screened trial leads
0Unreviewed FDA recall leads
The refreshed discovery snapshot contains 3 PubMed and 0 ClinicalTrials.gov candidate records. Discovery metadata alone does not establish exact tested-product, version, population, and endpoint applicability, so all candidates remain quarantined and none was promoted. The current discovery snapshot contains 3 PubMed and 0 ClinicalTrials.gov candidate records; its dated, count-matched human screening remains current. Unlinked candidates remain quarantined. Native FDA recall identifiers produced 0 postmarket candidate records; 0 have been reviewed (0 published, 0 rejected) and 0 remain unreviewed.
Candidate leads were screened against the exact product and tested version. Unlinked records remain quarantined.
Source classes: fda ai list, fda decision summary, acr ai central product, fda device recall, literature index, trial registry, pubmed, clinical trials, openfda device recall
Sources & history
How this profile was documented
Open the ledger for source dates, scope, and research-record updates.
View source ledger and history
Source ledger
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FDA K213737: Quantib ND
Scope: identity, clinicalUse, modality, anatomy, workflow, evidence, implementation
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Artificial Intelligence-Enabled Medical Devices
Scope: regulatoryIdentity, modalityContext
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Quantib ND model card (K213737)
Scope: intendedUsers, output, limitations, evidenceSummary, integration, anatomy, evidenceStudies, implementationCapabilities
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PubMed biomedical literature index
Scope: evidenceDiscovery
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ClinicalTrials.gov study registry
Scope: evidenceDiscovery, studyStatus
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openFDA Device Recall API
Scope: recallDiscovery, nativeSubmissionMatching
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openFDA exact recall query for K213737
Scope: postmarketSafety
Research history
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K213737 FDA decision
Regulatory record
510(k)
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Source-review record updated
Research record
fda record reviewed
-
Reader overview source-reviewed
Editorial review
Source-reviewed editorial overlay
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