Lunit INSIGHT DBT

Lunit
Lunit INSIGHT DBT analyses 3D images from DBT to support diagnosis of breast cancer. Lunit INSIGHT DBT presents the 3D slice(s) on which a suspicious lesion(s) is best shown.
lunit-insight-dbt.png
Information source: Vendor
Last updated: May 2, 2024

General Information

General
Product name Lunit INSIGHT DBT
Company Lunit
Subspeciality Breast
Modality Mammography
Disease targeted Breast cancer
Key-features Breast cancer detection, abnormality score, 3D slice(s) selection showing the suspicious lesion(s)
Suggested use Before: stratifying reading process (non, single, double read), adapting worklist order
During: perception aid (prompting all abnormalities/results/heatmaps), interactive decision support (shows abnormalities/results only on demand)

Technical Specifications

Data characteristics
Population Female aged 19 years or older; symptomatic or screening population.
Input 3D Digital Breast Tomosynthesis
Input format DICOM
Output Localization (color map, grayscale map, combined map, single color map), abnormality score for each lesion/side, binary assessment of abnormality, worklist order.
Output format DICOM Secondary Capture, DICOM GSPS(Grayscale Softcopy Presentation State), DICOM SR (Structured Report), HL7
Technology
Integration Integration in standard reading environment (PACS), Integration RIS (Radiological Information System), Integration CIS (Clinical Information System), 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 Automatically, right after the image acquisition, On demand, triggered by a user through e.g. a button click, image upload, etc.
Processing time 1 - 10 minutes

Regulatory

Certification
CE
Certified, Class IIa , MDR
FDA 510(k) cleared , Class II
Intended Use Statements
Intended use (according to CE)

Market

Market presence
On market since 03-2023
Distribution channels various
Countries present (clinical, non-research use)
Paying clinical customers (institutes)
Research/test users (institutes)
Pricing
Pricing model
Based on

Evidence

Evidence
Peer reviewed papers on performance

  • Impact of AI for Digital Breast Tomosynthesis on Breast Cancer Detection and Interpretation Time (read)
Non-peer reviewed papers on performance
Other relevant papers