LesionQuant is an automated imaging software aimed at assisting physicians in their clinical evaluation process, treatment planning, and monitoring of neurodegenerative diseases by combining T2 FLAIR with 3D T1 scans for lesion and structure quantification. It automatically segments, counts, and visualizes lesions, and quantifies lesion volume changes and brain volume changes.
Product specifications Information source: Vendor
Last updated: Sept. 10, 2020
General
Product name LesionQuant
Company CorTechs Labs
Subspeciality Neuro
Modality MR
Disease targeted multiple sclerosis, neurodegenerative diseases
Key-features Lesion counts and volumes for new, active, and resolving lesions, lesion burden calculation, normative data comparisons, longitudinal change data for lesions and brain structures, lesion change summary
Suggested use Before: flagging acute findings
During: perception aid (prompting all abnormalities/results/heatmaps), interactive decision support (shows abnormalities/results only on demand)
Data characteristics
Population All MR series where lesions are suspected
Input 3D T1 MR sequence, 3D or 2D T2 MR sequence
Input format DICOM
Output Lesion and brain structure segmentation overlays, lesion and brain change overlays, quantitative report with volumetric results
Output format DICOM
Technology
Integration Integration via AI marketplace or distribution platform, Stand-alone third party application, Stand-alone webbased
Deployment Locally on dedicated hardware, Locally virtualized (virtual machine, docker), Cloud-based
Trigger for analysis On demand, triggered by a user through e.g. a button click, image upload, etc.
Processing time > 10 minutes
Certification
CE Certified, Class IIa
FDA 510(k) cleared, Class II
Market presence
On market since 08/2006
Distribution channels Nuance, Blackford, Eureka Clinical AI
Countries present (clinical, non-research use) 43
Paying clinical customers (institutes)
Research/test users (institutes)
Pricing
Pricing model Pay-per-use, Subscription
Based on Number of installations, Number of analyses
Evidence
Peer reviewed papers on performance
Non-peer reviewed papers on performance

  • Poster: Performance evaluation for automated lesion segmentation tool: LesionQuant (read)

  • White paper: LesionQuant Performance Evaluation - Accuracy and Reproducibility (read)

Other relevant papers