qCT LN Quant
Contact for pricing
Regulatory Status Disclosed
Overview
qCT LN Quant by Qure.ai Technologies is an FDA-cleared AI-powered chest CT solution designed for advanced quantitative characterization and tracking of solid lung nodules. It assists radiologists and pulmonologists in analyzing morphological data across single or multiple thoracic studies, providing crucial insights for lung cancer screening and progression monitoring. The tool measures various nodule diameters (average, short-axis, long-axis, effective), estimates volume doubling time, and generates detailed 2D and 3D reconstructions. Furthermore, it offers Brock malignancy risk scores and management suggestions based on Fleischner Society guidelines, streamlining clinical decision-making and enhancing workflow efficiency. qCT LN Quant is part of Qure.ai’s comprehensive lung cancer care continuum, which also includes solutions for nodule detection on X-rays and a multi-modality nodule management platform that integrates with Electronic Medical Records.
Reviewed by Pouyan Golshani, MD — Interventional Radiologist
Key Features
- Advanced quantitative characterization of solid lung nodules (average, short-axis, long-axis, effective diameters)
- Analysis of morphological data across single or multiple thoracic studies
- Estimated volume doubling time and tracking of nodules over time
- Generates detailed 2D and 3D reconstructions
- Provides Brock malignancy risk scores
- Offers Fleischner Society guidelines-based management suggestions
- Supports radiologists and pulmonologists in lung nodule analysis
- Integrates with Electronic Medical Records (EMRs) via qTrack for comprehensive nodule management
- Potentially eligible for CPT codes for reimbursement (0722T for CT tissue quantification and 3D reconstruction code)
Use Cases
- Lung nodule analysis and quantification on CT scans
- Lung cancer screening and early detection programs
- Progression monitoring of lung nodules over time
- Enhancing radiology workflow efficiency and triage
- Supporting clinical decision-making for lung nodule management
What Physicians Need to Know
Key Capabilities
Provides advanced quantitative characterization of solid lung nodules, measuring average, short-axis, long-axis, and effective diameters. It analyzes morphological data across single or multiple thoracic studies, estimates volume doubling time, and tracks nodules over time. The tool generates detailed 2D and 3D reconstructions, calculates Brock malignancy risk scores, and offers Fleischner Society guidelines-based management suggestions. It also includes a Lung-RADS calculator feature and processes solid lung nodules u2265 6mm on non-contrast CT scans.
Clinical Utility
Enhances lung cancer care through early detection, precise tracking, and streamlined workflows. It supports radiologists and pulmonologists in analyzing lung nodules and monitoring volumetric growth, aiding in consistent and reliable clinical decision-making. The solution combines nodule quantification with evidence-based risk assessments and management suggestions, reducing manual effort and improving workflow efficiency and patient outcomes. It also strengthens the reliability of detection and measurement, which are critical for lung programs and nurse navigators.
Integration Options
Operates as a cloud module that interacts with DICOM modalities or Picture Archiving and Communication Systems (PACS) to receive de-identified scans and return results. It integrates with Electronic Medical Records (EMRs) as part of Qure.ai's broader lung cancer care continuum (qTrack platform). Outputs can be returned to PACS as a new series with segmentation burnt on (if PACS supports GSPS) or viewed on Qure.ai's web application. It is designed to fit within existing radiology workflows.
Compliance Status
FDA-cleared (510(k) clearance). The device adheres to ISO 13485:2016 and IEC 62304:2006+A1:2015 regulatory standards.
Pricing Model
Potentially eligible for reimbursement under two CPT codes: CPT 0722T for tissue quantification and a 3D reconstruction code. Qure.ai offers business case planning cost calculators to assist healthcare providers in evaluating the financial viability and return on investment.
User Experience
Features user-assisted semi-automatic segmentation of nodules with interactive fine-tuning. The segmented regions are presented as an overlay with highlighting and labeling. Users are provided with 2D and 3D reconstructed views of nodules, along with quantitative characteristics. The tool aims to reduce tedious manual effort and overall cycle time, while preserving physician control. Qure.ai provides a dedicated clinical education team to ensure users understand and trust the AI outputs.
Support Quality
Qure.ai has extensive global experience with AI deployments across over 3,000 sites in more than 90 countries. They offer dedicated U.S.-based teams to assist with implementation and integration, along with a clinical education team for training and adaptation.
Implementation Complexity
Implementation involves integrating the cloud-based module into existing radiology workflows and potentially with EMRs. Qure.ai provides assistance with this process, and the design aims for seamless integration.
Evidence Base
A deep-learning-based device, its performance in quantitative characterization of solid nodules has been assessed in standalone studies, demonstrating good performance and accuracy against ground truth. The model's performance was validated using large population-based prospective studies, including the Pan-Canadian Early Detection of Lung Cancer Study (PanCan) and chemoprevention trials at the British Columbia Cancer Agency (BCCA). Internal validation of a related Qure.ai product (qCT v1.1) showed an 81.4% nodule-level detection sensitivity.
Physician Tip
Leverage qCT LN Quant for standardized and precise lung nodule quantification, which can significantly reduce manual measurement variability and improve efficiency in your workflow. Integrate the Brock malignancy risk scores and Fleischner Society guidelines to streamline decision-making and ensure consistent patient management. Utilize the 2D and 3D reconstructions for a comprehensive visual assessment and to better communicate findings to patients. Remember that while the AI provides valuable insights and recommendations, it is a measurement tool intended to support, not replace, full patient evaluation and clinical judgment. Ensure your team undergoes the provided training to maximize the utility and trust in the AI's outputs.
qCT LN Quant is designed for flexible integration into existing radiology workflows, primarily through DICOM and PACS. For comprehensive lung cancer care management, consider integrating it with Qure.ai's 'qTrack' platform, which offers multi-modality nodule management and EMR integration. This creates a seamless continuum from detection to follow-up and documentation, enhancing overall patient care coordination. Verify your PACS system's compatibility with GSPS for direct output of segmented images.
Details
| Category | Oncology AI |
| Pricing | Contact for pricing |
| Deployment | Cloud, On-premise |
| Compliance | |
| BAA Available | Unknown AI-estimated |
| HIPAA Compliant | Unknown AI-estimated |
| FDA Status |
1 AI-estimated Qure.ai's qCT LN Quant (K240740) is US FDA 510(k) cleared as an automated Radiological Image Processing Software. It is intended to automatically analyze user-selected regions within lung CT to provide volumetric, diameter and computer analysis based on morphological characteristics in a single study, or over the time course of several thoracic studies, for the evaluation of user detected solid pulmonary nodules. |
| Integrations | |
| EHR | Not specified |
| Specialties | Oncology, Pulmonology, Radiology |
Ratings & Reviews
No reviews yet. Be the first to review this tool!
Rate qCT LN Quant
Press & Coverage
Qure.ai
Qure.ai Launches FDA-Cleared AI To Quantify Lung Nodules
Qure.ai announced the FDA 510(k) clearance of its AI-powered chest CT solution, qCT LN Quant, which supports radiologists and pulmonologists in analyzing lung nodules on non-contrast chest CT scans and tracking volumetric growth. This solution is part of Qure.ai's AI-powered Lung Cancer care continuum, aiming to enhance early detection and management.
2024-08
Diagnostic Imaging
FDA Clears Advanced Lung Nodule Assessment Software for CT Scans
The FDA has granted 510(k) clearance to qCT LN Quant, an AI-powered software from Qure.ai, for advanced quantitative evaluation of solid lung nodules on CT scans. The software provides measurements, estimated volume doubling time, nodule tracking, Brock malignancy risk scoring, and management suggestions based on Fleischner Society guidelines.
2024-08
AuntMinnie.com
FDA clears Qure.ai's AI CT software - AuntMinnie
Qure.ai's AI CT software, qCT LN Quant, has received FDA clearance to assist radiologists and pulmonologists in analyzing lung nodules on noncontrast chest CT scans and tracking volumetric growth. The software offers quantitative characterization, 2D and 3D reconstructions, Brock malignancy risk scores, and Fleischner Society guidelines-based management suggestions.
2024-08
Imaging Technology News (ITN)
Qure.AI's AI-powered Chest CT Solution Receives FDA Clearance
Qure.ai announced that its AI-powered chest CT solution, qCT LN Quant, has received 510(k) FDA clearance, making it available to support radiologists and pulmonologists in analyzing lung nodules and tracking volumetric growth. This solution is part of Qure.ai's comprehensive AI-powered Lung Cancer care continuum.
2024-08
Healio
Q&A: FDA grants 510(k) clearance to AI-powered lung nodule management tool - Healio
The FDA has granted 510(k) clearance to qCT LN Quant, an AI solution from Qure.ai, which assists clinicians in determining lung nodule diameters, malignancy risk, and management approaches. Key features include quantitative characterization, growth tracking, 2D and 3D reconstructions, Brock malignancy risk scores, and Fleischner Society guidelines.
2024-10
Applied Radiology
Qure.ai's AI-Based Solution for Quantifying and Characterizing Lung Nodules Gets FDA Clearance | Applied Radiology
Qure.ai has received 510(k) FDA clearance for its AI-powered chest CT solution, qCT LN Quant, designed to help radiologists and pulmonologists analyze lung nodules on non-contrast chest CT scans and monitor their growth. The solution offers advanced quantitative characterization, including various diameter measurements and volume doubling time.
2024-08
Chinese Journal of Cancer Research
Current trends and future directions of artificial intelligence in lung cancer diagnosis - Articles you may be interested in
This peer-reviewed article discusses current trends in AI for lung cancer diagnosis, mentioning Qure.ai's qCT LN Quant as an FDA-cleared tool that provides advanced quantitative characterization of lung nodules, tracks volumetric growth, and offers detailed 2D and 3D reconstructions.
2026-02
Verified Market Research
Lung Cancer Screening Software Market Size, Share & 2031 Growth Trends Report
This market report highlights Qure.ai's qCT LN Quant, cleared by the FDA in August 2024, as a key AI solution for imaging centers lacking thoracic subspecialists, designed to quantify solid lung nodules on non-contrast chest CTs. It notes the increasing adoption of AI engines in lung cancer screening due to regulatory clearances and expanding mandates.
2026-01
Videos
Product demos, reviews, and walkthroughs for qCT LN Quant.
Loading videos...
Frequently Asked Questions
qCT LN Quant is typically designed to integrate seamlessly with existing PACS and EMR systems, often functioning as a post-processing tool for standard CT scans. It aims to provide quantitative lymph node analysis to augment your current diagnostic review process, potentially reducing manual workload and improving efficiency.
qCT LN Quant is expected to hold relevant regulatory clearances, such as FDA approval or CE marking, for its intended diagnostic or assistive use. It should adhere to strict data privacy regulations like HIPAA or GDPR through anonymization and secure data handling protocols, as data privacy is a crucial consideration for AI in healthcare.
qCT LN Quant differentiates itself by offering quantitative metrics and potentially improved consistency over subjective manual assessments, which can aid in treatment response monitoring. While other AI tools may exist, qCT LN Quant focuses on specific volumetric and density changes for lymph nodes, aiming to enhance diagnostic accuracy and efficiency.
Pricing models for AI tools like qCT LN Quant typically involve subscription-based licenses or per-study fees, varying by institution size and usage volume. Reimbursement for AI-assisted diagnostics is an evolving area, with new legislation being introduced to establish dedicated Medicare coverage pathways for FDA-approved AI-enabled medical devices.
Like all AI tools, qCT LN Quant may have limitations in atypical cases, rare pathologies, or with image artifacts, and it should not replace clinical judgment. Potential biases can arise from the diversity and quality of training data, making continuous human oversight by a qualified physician crucial for interpreting results and making final diagnostic or treatment decisions.
qCT LN Quant is typically validated for common solid tumor types where lymph node involvement is a critical prognostic factor, such as breast, lung, colorectal, or head and neck cancers. Its effectiveness is generally highest in regions with clear anatomical delineation of lymph nodes on CT imaging, with studies often demonstrating high sensitivity across various cancer types.
Clinical studies for AI tools in lymph node assessment often report performance through metrics like sensitivity, specificity, and agreement with expert radiologists. For example, some AI models have shown comparable or even superior performance to manual screening for lymph node metastasis, with high sensitivity and specificity in various cancer types.
Suggest an Edit →
| Last Verified: 2026-04-19 | First Added: 2026-04-19