AVIEW LCS+

Coreline Soft
The LCS+ software from Coreline Soft provides information on the 3 main lung diseases: lung cancer, COPD and coronary artery calcification based on a Low Dose, non-enhanced, non-gated CT-scan
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Information source: Vendor
Last updated: March 3, 2025

General Information

General
Product name AVIEW LCS+
Company Coreline Soft
Subspeciality Chest
Modality CT
Disease targeted Lung Cancer, COPD, coronary artery calcifications
Key-features Nodule detection, nodule classification, nodule volume quantification, VDT, Lung-RADS score, Emphysema score, CAC-score
Suggested use During: perception aid (prompting all abnormalities/results/heatmaps), report suggestion

Technical Specifications

Data characteristics
Population All adult non-enhanced chest CTs, including screening population
Input Chest CT of different vendors. Non-enhanced, non-gated
Input format DICOM
Output Emphysema index (LAA), Coronary calcification score per branch, CAD, Lung-RADS, VDT, solid/non-solid
Output format SR, PDF, copy-paste to report, Encapsulated DICOM PDF
Technology
Integration Integration in standard reading environment (PACS), Integration RIS (Radiological Information System), Stand-alone third party application, Stand-alone webbased
Deployment Locally on dedicated hardware, Locally virtualized (virtual machine, docker), Cloud-based, Hybrid solution
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 IIb , MDR
FDA 510(k) cleared , Class II
Intended Use Statements
Intended use (according to CE) AVIEW LCS PLUS is intended for the review and analysis and reporting of thoracic CT images for the purpose of characterizing nodules in the lung in a single study, or over the time course of several thoracic studies. Characterizations include nodule type, location of the nodule and measurements such as size (major axis, minor axis), estimated effective diameter from the volume of the nodule, the volume of the nodule, Mean HU (the average value of the CT pixel inside the nodule in HU), Minimum HU, Max HU, mass (mass calculated from the CT pixel value), and volumetric measures (Solid Major; length of the longest diameter measured in 3D for a solid portion of the nodule. Solid 2nd Major: The length of the longest diameter of the solid part, measured in sections perpendicular to the Major axis of the solid portion of the nodule), VDT (Volume doubling time), Lung-RADS (classification proposed to aid with findings) and CAC score and LAA analysis. The system automatically performs the measurement, allowing lung nodules and measurements to be displayed.

Market

Market presence
On market since 11-2017
Distribution channels RMS Medical Devices, Alma AI MARKETPLACE, Eureka Clinical AI
Countries present (clinical, non-research use) 10+
Paying clinical customers (institutes)
Research/test users (institutes) 10+
Pricing
Pricing model Subscription, One-off payment
Based on Number of users, Number of installations

Evidence

Evidence
Peer reviewed papers on performance

  • Histological proven AI performance in the UKLS CT lung cancer screening study: Potential for workload reduction (read)
  • Feasibility of AI as first reader in the 4-IN-THE-LUNG-RUN lung cancer screening trial: impact on negative-misclassifications and clinical referral rate (read)

  • Artificial intelligence system for identification of overlooked lung metastasis in abdominopelvic computed tomography scans of patients with malignancy (read)

  • Absolute ground truth-based validation of computer-aided nodule detection and volumetry in low-dose CT imaging (read)

  • Outstanding negative prediction performance of solid pulmonary nodule volume AI for ultra-LDCT baseline lung cancer screening risk stratification (read)

  • Variability in interpretation of low-dose chest CT using computerized assessment in a nationwide lung cancer screening program: comparison of prospective reading at individual institutions and retrospective central reading (read)

  • Implementation of the cloud-based computerized interpretation system in a nationwide lung cancer screening with low-dose CT: comparison with the conventional reading system (read)
Non-peer reviewed papers on performance
Other relevant papers