Radiology AI Directory

FDA-cleared profile

NeuroQuant

CorTechs Labs, Inc.

Authorized purpose: NeuroQuant automatically labels, visualizes, and volumetrically quantifies segmentable brain structures and lesions from MR images, optionally using T2 FLAIR and T2* GRE/SWI for lesion analysis; outputs require radiologist/neuroradiologist review and may be compared with reference percentiles.

Quantification and segmentationNeuro MRI
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: NeuroQuant automatically labels, visualizes, and volumetrically quantifies segmentable brain structures and lesions from MR images, optionally using T2 FLAIR and T2* GRE/SWI for lesion analysis; outputs require radiologist/neuroradiologist review and may be compared with reference percentiles.

Overview status: Source-reviewed overview

Clinical takeaway

Clinical role: NeuroQuant automatically labels, visualizes, and volumetrically quantifies segmentable brain structures and lesions from MR images, optionally using T2 FLAIR and T2* GRE/SWI for lesion analysis; outputs require radiologist/neuroradiologist review and may be compared with reference percentiles.

Evidence takeaway

Evidence from the reviewed source record: FDA performance testing covered brain segmentation, FLAIR lesion segmentation, and MCH detection models; FLAIR mean Dice 0.70 (SD 0.14) and MCH median F1 0.60 were reported, with separate test sets from training.

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
NeuroQuant automatically labels, visualizes, and volumetrically quantifies segmentable brain structures and lesions from MR images, optionally using T2 FLAIR and T2* GRE/SWI for lesion analysis; outputs require radiologist/neuroradiologist review and may be compared with reference percentiles.
  • FDA source
  • Exact FDA submission
  • Checked 2026-09-07
Intended users
Medical professionals; clinical outputs must be reviewed by a radiologist or neuroradiologist and may be forwarded to the referring neurologist.
  • FDA source
  • Exact FDA submission
  • Checked 2026-09-07
Care setting and population
Medical imaging centers, hospitals, other healthcare facilities, and clinical research; age range was not stated in the reviewed exact FDA text.
  • FDA source
  • Exact FDA submission
  • Checked 2026-09-07
Workflow role
Segmentation, volumetric quantification, and longitudinal comparison support
  • FDA source
  • Exact FDA submission
  • Checked 2026-09-07
Required input
3D T1-weighted MR images; optional T2 FLAIR and T2* GRE/SWI series; DICOM Storage input from an MRI scanner or PACS; specified protocols are recommended.
  • FDA source
  • Exact FDA submission
  • Checked 2026-09-07
Output and human action
Numerical brain and lesion volumes, grayscale intensity maps, color overlays, segmented image series, and morphometric reports in standard DICOM for display on commercial DICOM workstations/PACS; age/gender-matched normative percentiles and change analysis may be provided.
  • FDA source
  • Exact FDA submission
  • Checked 2026-09-07
Limitations
Clinical output requires radiologist/neuroradiologist review; the device is prescription-only; specified acquisition protocols are recommended; and the output is not a substitute for full clinical interpretation.
  • FDA source
  • Exact FDA submission
  • Checked 2026-09-07

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.

FDA submission
K241098
  • FDA source
  • Exact FDA submission
  • Checked 2026-08-31
Modality
MRI
  • FDA source
  • Exact FDA submission
  • Checked 2026-09-07
Anatomy
Brain
  • FDA source
  • Exact FDA submission
  • Checked 2026-09-07
Clearance type
510(k)
  • FDA source
  • Exact FDA submission
  • Checked 2026-08-31
Decision date
2024-08-22
  • FDA source
  • Exact FDA submission
  • Checked 2026-08-31
FDA status
FDA-cleared
  • FDA source
  • Exact FDA submission
  • Checked 2026-08-31

Implementation

Questions for IT, informatics, and operations

Use these fields to structure a vendor demo, security review, and implementation estimate.

Integration
DICOM Storage receives MR series from an MRI scanner or PACS and returns DICOM image series and reports to DICOM workstations/PACS; transient data storage only is described.
  • FDA source
  • Exact FDA submission
  • Checked 2026-09-07
Deployment and data flow
On-premise computing appliance
  • FDA source
  • Exact FDA submission
  • Checked 2026-09-07

The exact FDA submission describes the device as a computing appliance; current hosting region and commercial deployment options were not inferred.

Security and privacy
Vendor documentation pending
  • Vendor confirmation
  • Exact FDA submission
  • Checked 2026-09-07

The reviewed sources do not establish a scoped security audit, certification, or control set.

Training and support
Vendor documentation pending
  • Vendor confirmation
  • Exact FDA submission
  • Checked 2026-09-07

Training, credentialing, and implementation support terms were not established.

Monitoring and change control
Vendor documentation pending
  • Vendor confirmation
  • Exact FDA submission
  • Checked 2026-09-07

Current post-deployment monitoring and change-control practices were not established.

DICOM Storage and PACS routing

The exact submission describes DICOM Storage receipt from an MRI scanner or PACS and standard DICOM image-series/report output for commercial DICOM workstations.

exact submission · checked 2026-09-07
Source

NeuroQuant DICOM/PACS installation workflow

The official NeuroQuant Installed Quick Start Guide describes 3D T1 DICOM input, AETitle/report selection, automated processing, and output to a configured PACS; the guide is a v3.0 family manual and is not treated as proof of the exact K241098 build.

product family · checked 2026-09-07

Family manual context; current exact-version compatibility requires confirmation.

Source

Current family workflow and report options

CorTechs' current NeuroQuant page describes cloud-based brain segmentation, quantification, comparison, and adaptable reports that integrate with radiology workflows; this current family description is not used to override the exact FDA appliance deployment.

product family · checked 2026-09-07

Family-level current product context only.

Source

Evidence

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 performance testing covered brain segmentation, FLAIR lesion segmentation, and MCH detection models; FLAIR mean Dice 0.70 (SD 0.14) and MCH median F1 0.60 were reported, with separate test sets from training.
  • FDA source
  • Exact FDA submission
  • Checked 2026-09-07
Reported sensitivity
Research pending
  • Needs research
  • Exact FDA submission
  • Checked 2026-08-31

This field has not been curated yet.

Reported specificity
Research pending
  • Needs research
  • Exact FDA submission
  • Checked 2026-08-31

This field has not been curated yet.

FLAIR lesion segmentation mean Dice

0.7 Dice

  • EndpointSegmentation overlap for FLAIR hyperintense lesions
  • Population63-patient test set; training set contained 340 T1/FLAIR series from 22 institutions
  • Tested versionNeuroQuant submitted in K241098; build not stated
Source

MCH detection median F1

0.6 F1 score

  • EndpointDetection of cerebral hypointensities associated with blood products
  • Population117-patient test set; training set contained 463 2D T2*GRE/SWI series from more than 68 institutions
  • Tested versionNeuroQuant submitted in K241098; build not stated
Source

NeuroQuant model validation across brain, FLAIR, and MCH pipelines

  • DesignRetrospective model validation with separate training and test datasets
  • PopulationBrain segmentation: 1,473 training 3D T1 series from more than 16 institutions and 30-patient test set; FLAIR: 340 training series from 22 institutions and 63-patient test set; MCH: 463 training 2D T2*GRE/SWI series from more than 68 institutions and 117-patient test set.
  • Scopeexact submission
  • Tested versionNeuroQuant submitted in K241098; build not stated
  • IndependenceIndependence not established

K241098

The FDA establishes separation of training and test data, not independent investigators or sponsorship. The reported FLAIR and MCH values are model-specific and should not be generalized to every NeuroQuant output.

Source

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
  • Vendor confirmation
  • Exact FDA submission
  • Checked 2026-09-07

No public amount, range, currency, geography, or contract term was established.

Reimbursement and coding
Aetna Clinical Policy Bulletin 0739 classifies automated quantification of brain MRI as experimental, investigational, or unproven and lists Category III CPT codes 0865T and 0866T as not covered for the indications in the bulletin. This is service-level Aetna policy, not an exact NeuroQuant eligibility or universal coverage determination.
  • Public source
  • Product family
  • Checked 2026-09-08

0865T, 0866T

Not covered for indications listed in Aetna CPB 0739; automated quantification of brain MRI is classified as experimental, investigational, or unproven

Aetna · United States; plan and benefit terms vary

Policy last reviewed 2026-07-24. This service-level policy does not prove eligibility for a particular NeuroQuant version, member, indication, site, or claim.

Source

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
Not established in reviewed sources
  • Reviewed sources checked
  • Exact FDA submission
  • Checked 2026-09-04

No native submission-identifier match was found in the checked openFDA radiology recall snapshot. Product-name, manufacturer, and adverse-event searches remain necessary; this does not establish that no recall or safety report exists.

Buyer worksheet

Open questions to take to the vendor

Open evaluation checklist

Research record

What has been checked

This audit distinguishes completed source review from fields that have not yet been researched.

Human reviewedStatus
2026-09-07Last searched
24Fields reviewed
12Source classes checked
20Screened PubMed leads
5Screened trial leads
0Unreviewed FDA recall leads

The stored PubMed, ClinicalTrials.gov, and exact-submission recall metadata candidates were screened by identifier and count. The records were not treated as a full paper, trial, or postmarket review. The current discovery snapshot contains 20 PubMed and 5 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, vendor product page, vendor manual, payer policy, literature index, trial registry, fda device recall, 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

  1. FDA 510(k) K241098: NeuroQuant

    U.S. Food and Drug Administration - Published 2024-08-22 - Accessed 2026-09-07

    Scope: identity, clinicalUse, modality, anatomy, workflow, evidence, implementation

  2. Artificial Intelligence-Enabled Medical Devices

    U.S. Food and Drug Administration - Accessed 2026-08-31

    Scope: regulatoryIdentity, modalityContext

  3. NeuroQuant model card (K241098)

    American College of Radiology - Published 2026-08-17 - Accessed 2026-09-01

    Scope: purpose, modality, intendedUsers, careSetting, output, limitations, evidenceSummary, anatomy, evidenceStudies

  4. PubMed biomedical literature index

    U.S. National Library of Medicine - Accessed 2026-09-01

    Scope: evidenceDiscovery

  5. ClinicalTrials.gov study registry

    U.S. National Library of Medicine - Accessed 2026-09-01

    Scope: evidenceDiscovery, studyStatus

  6. openFDA Device Recall API

    U.S. Food and Drug Administration - Accessed 2026-09-02

    Scope: recallDiscovery, nativeSubmissionMatching

  7. NeuroQuant installed-system quick start guide, version 3.0

    Cortechs.ai - Accessed 2026-09-08

    Scope: productFamily, DICOM, PACS, implementationCapabilities

  8. NeuroQuant brain segmentation and volumetric analysis

    Cortechs.ai - Accessed 2026-09-08

    Scope: productFamily, clinicalWorkflow, reports, implementationCapabilities, codingContext

  9. Aetna CPB 0739: Quantitative, Functional and Connectomic Analysis of Brain MRI

    Aetna - Accessed 2026-09-08

    Scope: reimbursement, coding, payerPolicy

Research history

  1. K241098 FDA decision

    Regulatory record

    510(k)

  2. Source-review record updated

    Research record

    human reviewed

  3. Reader overview source-reviewed

    Editorial review

    Source-reviewed editorial overlay

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