qXR-BT
Contact vendor for pricing
Regulatory Status Disclosed
Overview
qXR-BT by Qure.ai is an artificial intelligence-powered image analysis software designed to assist clinicians in assessing breathing tube placements. The tool automates the measurement and localization of both endotracheal and tracheostomy tubes on digital chest radiographs.
The software is primarily designed for:
- Specialties: Critical care medicine, pulmonology, emergency medicine, and radiology.
- Care Settings: Intensive care units (ICUs), emergency departments, and inpatient hospital wards where intubated patients require routine monitoring.
qXR-BT integrates directly into existing clinical workflows, operating in parallel with standard image interpretation systems such as PACS, DICOM viewers, and imaging worklists. The algorithm is vendor-agnostic, allowing it to process images captured by both portable and stationary X-ray machines.
Notable capabilities include:
- Automated detection of the breathing tube tip relative to the carina.
- Automated measurement of tube placement distance.
- Rapid processing that generates positional accuracy reports in under a minute to assist with clinical decision-making.
Reviewed by Pouyan Golshani, MD — Interventional Radiologist
Key Features
- Automates measurement of endotracheal and tracheostomy tube placement
- Analyzes tube position and provides a report on positional accuracy
- Vendor-agnostic, works on portable and stationary X-ray machines
- Provides results in less than a minute
- Generates a secondary digital chest X-ray image with markers and labels
- Outputs DICOM and PDF reports
- Integrates into existing PACS/RIS workflows
- Aids clinicians in rapidly identifying proper tube positioning
- Uses pre-trained convolutional neural networks (CNNs)
Use Cases
- Assessing breathing tube placements in intubated patients
- Improving accuracy and optimizing patient care in critical care settings
- Reducing processing times and solving workflow delays in radiology
- Providing confidence to residents and junior clinicians in measuring breathing tube placement
- Supporting rapid identification of correctly positioned or misplaced tubes
- Pre-read assistance for chest X-rays
What Physicians Need to Know
DICOM Support & Standards
qXR-BT supports DICOM for both input (PA/AP view chest X-rays) and output. The output includes a secondary DICOM series with labeled overlays indicating the location and extent of segmented structures, suitable for viewing in PACS or radiology viewers. It also generates PDF reports.
PACS Integration Method
Designed for seamless integration with existing PACS, RIS, DICOM viewers, and imaging worklists. X-rays are transmitted to qXR-BT via PACS functions, and results are returned to the user's PACS or other specified radiology software/database. Integration can also occur via AI marketplaces or distribution platforms, or as a standalone web-based solution.
Reading Room Workflow Impact
Automates the measurement and assessment of breathing tube (endotracheal and tracheostomy) placement, providing a report on positional accuracy. It aims to decrease processing times and alleviate workflow delays, particularly in critical care settings. The tool offers adjunctive information to clinicians, helping to rapidly identify if a tube is properly positioned or requires extra attention, thereby enhancing confidence for residents and junior clinicians.
AI Model Architecture (deep learning approach)
The qXR-BT analysis module utilizes a set of pre-trained convolutional neural networks (CNNs) as its core processing component. This deep learning algorithm is coupled with pre-processing and post-processing modules to handle DICOM inputs and convert outputs into visual and tabular formats.
Processing Speed (per study)
The algorithm analyzes tube position, automates measurements, and provides a report on positional accuracy in less than a minute, with reported processing times ranging from 10 to 60 seconds per study.
FDA Clearance Pathway (510k/De Novo)
qXR-BT received 510(k) clearance from the U.S. Food and Drug Administration (FDA) as an automated Radiological Image Processing Software.
Supported Modalities (CT/MRI/X-ray/US)
Specifically designed for digital chest X-rays (PA and AP views) for adult patients. The algorithm is vendor-agnostic and compatible with both portable and stationary X-ray machines.
Sensitivity & Specificity Data
While specific sensitivity and specificity data directly for qXR-BT's breathing tube placement detection were not explicitly detailed in the provided search results, the broader qXR platform (of which qXR-BT is a part in some regions) has demonstrated high accuracy in various chest X-ray analyses. For example, qXR has shown up to 96% sensitivity and 100% specificity for pneumothorax and pleural effusion, 99.7% sensitivity for stratifying normal vs. abnormal CXRs, and 99% sensitivity for lung nodule detection.
RSNA/ACR Validation
Qure.ai actively participates in events like RSNA, showcasing its AI solutions. The company emphasizes clinical validation in multiple geographies, and research collaborations have involved institutions like Massachusetts General Hospital and Harvard Medical School.
Physician Tip
qXR-BT serves as a valuable adjunct for confirming breathing tube placement on adult chest X-rays, particularly beneficial in high-volume or critical care settings. It can enhance confidence for less experienced clinicians and streamline workflow by automating measurements. Physicians should always review the original images and integrate the AI's findings with other clinical information for final diagnostic decisions, as the tool provides adjunctive information and is not a substitute for the original PA/AP image. The rapid processing speed can aid in timely interventions.
qXR-BT is designed for straightforward integration into existing radiology workflows, supporting DICOM input and output. It can connect with PACS, RIS, and other radiology software systems, allowing for automated image transmission and results delivery. Deployment options include cloud-based, locally on dedicated hardware, or locally virtualized (VM, Docker). Secure communication and data protection are emphasized, with encryption for API and on-premise server communications, and use of secure cloud hosting partners.
Details
| Category | Radiology & Imaging AI, Triage & ER/ICU AI |
| Pricing | Contact vendor for pricing |
| Deployment | Cloud-based, On-premise (dedicated hardware or virtualized) |
| Compliance | |
| BAA Available | Unknown AI-estimated |
| HIPAA Compliant | Unknown AI-estimated |
| FDA Status |
1 AI-estimated qXR-BT received 510(k) clearance from the U.S. Food and Drug Administration (FDA) on January 20, 2022 (K212690). It is cleared as an automated Radiological Image Processing Software intended to facilitate confirmation of the position of a breathing tube and an anatomical landmark on adult chest X-rays. |
| Integrations | |
| EHR | Not specified |
| Specialties | Critical Care, Emergency Medicine, Radiology |
What the Web Says
Qure.ai's qXR-BT is an AI-powered algorithm designed to assist physicians in assessing breathing tube (BT) placement on chest X-rays. It aims to automate measurements and rapidly identify correct or incorrect tube positioning, which is crucial in critical care settings where incorrect placements can be life-threatening. The software is FDA 510(k) cleared and integrates with existing radiology workflows.
Overall: PositiveStrengths
- Automates measurement and assessment of breathing tube placement.
- Provides rapid analysis and reporting (less than a minute).
- Aids in improving accuracy and optimizing patient care, especially in emergency services and ICUs.
- Vendor-agnostic, working with both portable and stationary X-ray machines.
- Integrates with existing PACS, DICOM viewers, and imaging worklists.
- Reduces processing times and workflow delays.
Limitations
- The qXR-BT image provides adjunctive information and is not a substitute for the original PA/AP image.
- Intended for use by licensed physicians trained in evaluating breathing tube placement.
- No specific cons found from tech reviewers, Reddit, G2, or Capterra for qXR-BT directly, though general Qure.ai reviews mention a desire for improved support and guidance on usability.
Based on reviews from: TestDynamics, accessdata.fda.gov, Applied Radiology, Reddit, Health Technology Review, BioSpace, Qure.ai, G2, Imaging Technology News
Last updated: 2026-07-19
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Press & Coverage
Qure.ai
Qure.ai's breathing tube placement AI technology receives FDA clearance
Qure.ai received 510(k) clearance from the FDA for its qXR-BT AI algorithm, designed to assist doctors in assessing breathing tube placements using chest X-rays. This solution automates the measurement process for both endotracheal and tracheostomy tubes.
2022-01
Imaging Technology News
Qure.ai's Breathing Tube Placement AI Technology Receives FDA Clearance
Qure.ai announced FDA 510(k) clearance for its qXR-BT AI algorithm, which helps clinicians assess breathing tube placements from chest X-rays by automating measurements for endotracheal and tracheostomy tubes.
2022-01
Medical Device Network
FDA grants 510(k) clearance to Qure.ai's artificial intelligence algorithm
The FDA granted 510(k) clearance to Qure.ai's qXR-BT AI algorithm, which automates the measurement process for endotracheal and tracheostomy tubes using chest X-rays to help clinicians assess breathing tube placement.
2022-01
Qure.ai
Qure.ai receives 510(k) FDA clearance for x-ray solution
Qure.ai received FDA 510(k) clearance for its AI-enabled chest X-ray solution, qXR, for triaging pneumothorax and pleural effusion. This adds to their existing FDA-cleared portfolio, which includes qXR-BT for breathing tube placement.
2023-09
DeciBio
Digital Health | Q1 2022 Update - DeciBio
Qure.ai's breathing tube placement algorithm (qXR-BT) received FDA approval, complementing its qXR platform for detecting abnormalities using chest X-rays. This algorithm automates endotracheal tube measurements, crucial for rapid and accurate placement, especially during the COVID-19 pandemic.
2022-04
Medimaging.net
Chest X-ray AI Identifies Improper Breathing Tube Placement - Medimaging.net
Qure.ai's qXR-BT AI algorithm uses pre-trained convolutional neural networks to analyze chest X-rays and determine the position of breathing tube tips relative to the carina. It automates measurements and provides a report on positional accuracy in under a minute, aiding clinicians in critical care.
2022-01
AuntMinnie
Qure.ai gets nod for AI tube placement software | AuntMinnie
Qure.ai received U.S. Food and Drug Administration clearance for its qXR-BT software, an AI-powered tool designed to guide breathing tube placement on X-ray images.
2022-01
Journal of Imaging Informatics in Medicine (PMC)
Analysis of Validation Performance of a Machine Learning Classifier in Interstitial Lung Disease Cases Without Definite or Probable Usual Interstitial Pneumonia Pattern on CT Using Clinical and Pathology-Supported Diagnostic Labels - PMC
This peer-reviewed article mentions Qure.ai Technologies' qXR-BT device as an FDA-approved product that identifies features of pulmonary fibrosis by chest radiograph, alongside other machine learning classifiers for interstitial lung disease.
2024-01
Videos
Product demos, reviews, and walkthroughs for qXR-BT.
No videos found. Search YouTube directly
Frequently Asked Questions
qXR-BT is an AI-powered software developed by Qure.ai that assists physicians in confirming the accurate placement of endotracheal and tracheostomy breathing tubes on adult chest X-rays. It analyzes the X-ray images, automates measurements, and generates a secondary image with markings and a report detailing the tube's positional accuracy, typically within a minute.
No, qXR-BT is intended as an aid for chest X-ray interpretation and is not a diagnostic device or a substitute for professional medical judgment. It is FDA 510(k) cleared as an automated Radiological Image Processing Software (Class II device) in the US and holds CE certification in Europe, signifying compliance with health and safety standards.
qXR-BT is designed for seamless integration with standard radiology workflows and IT systems, including Picture Archiving and Communication Systems (PACS) and Radiology Information Systems (RIS). It is vendor-agnostic, meaning it can work with various X-ray machines, and typically receives images via PACS transmission functions, returning results in DICOM or PDF formats.
qXR-BT is specifically intended for use on adult chest X-rays and is not designed for pediatric patients. It provides adjunctive information and should not be used as a substitute for the original PA/AP image or to determine patient management plans, as clinicians remain responsible for the final interpretation.
Qure.ai is committed to information security and regulatory compliance, adhering to standards like IEC 62304 for software development and IT security. They are also GDPR-compliant, implementing measures for data minimization, purpose limitation, and storage duration, and undergo annual third-party audits.
While qXR-BT specifically focuses on breathing tube placement, other AI solutions exist for broader chest X-ray interpretation, triage, and detection of various abnormalities. Competitors in the general chest X-ray AI space include Lunit INSIGHT CXR, Aidoc, and Annalise.ai, among others.
The pricing for qXR-BT is typically based on a subscription model. Specific pricing details are usually obtained by contacting the vendor, Qure.ai, directly, as it can be based on factors like the number of analyses or installations.
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| Last Verified: 2026-04-19 | First Added: 2026-04-19