AVIEW Lung Nodule CAD
Overview
AVIEW Lung Nodule CAD is an AI-based Computer-Aided Detection (CAD) software developed by Coreline Soft Co. It is designed to assist radiologists in the detection and analysis of pulmonary nodules (with diameters between 3-20 mm) during the review of CT examinations of the chest, particularly for asymptomatic populations. The software acts as an adjunctive tool, providing information to alert radiologists to regions of interest that may otherwise be overlooked, and can be used as a second reader after the radiologist’s initial assessment.
Beyond nodule detection, AVIEW Lung Nodule CAD is part of the broader AVIEW platform, which offers comprehensive analysis for what Coreline Soft refers to as the ‘Big 3’ thoracic diseases: lung cancer (via nodule analysis), chronic obstructive pulmonary disease (COPD), and coronary artery calcification (CAC). It can simultaneously analyze these conditions from a single low-dose CT scan, providing quantitative results for emphysema and CAC scoring. The system aims to automate tedious manual tasks, reduce radiologist workload, and improve the efficiency and accuracy of lung cancer screening and other thoracic disease diagnoses.
Reviewed by Pouyan Golshani, MD — Interventional Radiologist
Key Features
- AI-based pulmonary nodule detection (3-20 mm) on CT scans
- Nodule classification (solid, part-solid, non-solid)
- 3D nodule size and volume quantification
- Automatic report generation based on Lung-RADS classification
- Nodule matching and volume doubling time (VDT) calculation for follow-up comparisons
- Simultaneous analysis of lung nodules, emphysema, and coronary artery calcification (Big 3)
- Quantitative emphysema analysis (e.g., Low Attenuation Area - LAA, emphysema index)
- Coronary Artery Calcification (CAC) scoring (Agatston, volume, mass scores)
- Integration with Picture Archiving and Communication Systems (PACS) and Radiological Information Systems (RIS)
- Customizable operation settings for sensitivity or specificity
Use Cases
- Lung cancer screening programs and early detection of pulmonary nodules
- Quantitative analysis and monitoring of emphysema
- Assessment and scoring of coronary artery calcification
- Reducing radiologist workload and improving reading efficiency
- Monitoring nodule growth and risk stratification over time
- Supporting clinical decision-making for thoracic diseases
What Physicians Need to Know
AVIEW Lung Nodule CAD, particularly the AVIEW LCS+ platform, offers a valuable opportunity for opportunistic screening of coronary artery calcification (CAC) during routine low-dose chest CT scans for lung cancer screening. This can aid in early cardiovascular risk stratification without requiring additional dedicated cardiac imaging. Physicians should leverage the automated CAC scoring and detailed arterial segmentation for comprehensive patient assessment. The tool's ability to act as a 'second reader' for lung nodules can enhance detection sensitivity and reduce reading time, while its adherence to Lung-RADS and standard CAC scoring ensures consistent reporting.
AVIEW Lung Nodule CAD is designed for seamless integration into standard radiology workflows. It complies with DICOM standards, allowing linkage with Picture Archiving and Communication Systems (PACS). The system supports various DICOM output formats, including DICOM SC, Encapsulated PDF, Key Images, DICOM GSPS, DICOM SEG, and DICOM SR. It also features worklist integration and the ability to generate pre-populated reports, streamlining the reporting process. Deployment options include cloud-based, hybrid solutions, or local installation on dedicated hardware or virtualized environments.
Details
| Category | Cardiology AI, Oncology AI, Radiology & Imaging AI |
| Pricing |
Contact for pricing
|
| Deployment | Cloud-based, Hybrid solution, Locally on dedicated hardware, Locally virtualized (virtual machine, Docker) |
| Compliance | |
| BAA Available | Unknown AI-estimated |
| HIPAA Compliant | Unknown AI-estimated |
| FDA Status |
1 AI-estimated AVIEW Lung Nodule CAD received FDA 510(k) clearance (K251203) on December 3, 2025, as a Computer-Aided Detection (CAD) software. It is intended to assist radiologists in the detection of pulmonary nodules (3-20 mm) during the review of CT examinations of the chest for asymptomatic populations, and may be used as a second reader. |
| Integrations | |
| EHR | Not specified |
| Specialties | Cardiology, Pulmonology, Radiology |
What the Web Says
AVIEW Lung Nodule CAD, developed by Coreline Soft, is an AI-powered computer-aided detection (CAD) software designed to assist radiologists in identifying and analyzing pulmonary nodules on CT scans. It aims to improve detection sensitivity, reduce reading time, and standardize reporting based on guidelines like Lung-RADS. While studies suggest it can enhance nodule detection and potentially reduce workload, some sources indicate that there isn't yet enough evidence to recommend it for routine clinical use outside of research, particularly for people with suspected lung cancer or for reasons unrelated to cancer suspicion.
Overall: MixedStrengths
- Increased sensitivity in lung nodule detection, including small nodules.
- Reduces radiologists' reading time and workload.
- Provides 3D size, volume, and classification (solid, part-solid, non-solid) of nodules.
- Automates Lung-RADS classification and generates structured reports.
- Facilitates longitudinal tracking of nodules by comparing current and prior examinations.
- FDA cleared and meets international security standards.
Limitations
- Not enough evidence to recommend for routine clinical use outside of research for certain patient groups.
- Potential for increased false positives, leading to unnecessary follow-up for benign nodules.
- Some studies show AI-CAD systems can be inferior to radiologists as a primary reader for nodule detection.
- Workload reduction and time-saving claims by the vendor could not always be independently validated.
- Concerns about the quality of evidence in some systematic reviews regarding AI for lung nodule detection.
- May require further optimization for seamless integration into existing radiology infrastructures.
Based on reviews from: NICE, Alma Medical Imaging, AuntMinnie, PMC (PubMed Central), accessdata.fda.gov, Thorax (journal), Radailogy, Coreline Soft (Press Release), Sectra Amplifier Marketplace, Journal of Thoracic Disease, AJR (American Journal of Roentgenology), Reddit, Rayscape AI
Last updated: 2026-07-21
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