EFAI Chestsuite XR Malpositioned ETT Assessment System (ETT-XR-100)
Overview
The EFAI Chestsuite XR Malpositioned ETT Assessment System (ETT-XR-100) is a radiological computer-aided triage and notification software. It leverages deep learning algorithms to automatically analyze chest X-ray images, specifically designed to highlight and alert potential vertical malposition of endotracheal tubes (ETTs) at the carina. Upon detection of ETT misplacement, the system proactively sends alerts to PACS/RIS workstations, enabling healthcare professionals to identify and respond to mispositioned ETTs more rapidly than conventional clinical workflows. This early intervention capability is intended to significantly enhance patient safety and improve clinical outcomes. The system is indicated for use in the analysis of chest X-ray (CXR) images in adults and assists hospital networks and appropriately trained medical specialists in workflow triage by flagging suspected positive cases of vertically malpositioned ETTs.
Reviewed by Pouyan Golshani, MD — Interventional Radiologist
Key Features
- AI-powered deep learning algorithms for chest X-ray analysis
- Automatic detection and assessment of vertical ETT malposition relative to the carina
- Computer-aided triage and notification software
- Alerts sent to PACS/RIS workstations
- Aids in prioritizing cases with suspected ETT malposition
- Intended for use in adults
- Evaluated and verified in accordance with software specifications and IEC 62304
Use Cases
- Early identification of malpositioned endotracheal tubes on chest X-rays
- Prioritization and triage of radiological medical images in hospital networks
- Assisting medical specialists in workflow triage
- Enhancing patient safety and improving clinical outcomes by enabling rapid response to ETT misplacement
What Physicians Need to Know
The EFAI Chestsuite XR Malpositioned ETT Assessment System (ETT-XR-100) is a valuable tool for workflow triage, flagging cases where the ETT distal tip is assessed as being more than 7 cm above the carina, less than 3 cm above the carina, or below the carina. Physicians should note that the system assesses solely the vertical position of the ETT and does not account for patient positioning or detect esophageal intubation. It was tested with single lumen ETTs and may generate false prioritization alerts for properly positioned double lumen ETTs. The AI results are intended to assist in prioritization and should not be used as a standalone basis for clinical decision-making or to rule out malpositioned ETTs.
The EFAI Chestsuite XR Malpositioned ETT Assessment System is a software-only device designed for deployment within a local network with an existing hospital-grade IT system. It is packaged as a Docker container. It integrates with PACS/RIS workstations by sending passive, case-level notifications to facilitate worklist prioritization and triage.
Details
| Category | Radiology & Imaging AI, Triage & ER/ICU AI |
| Pricing | Unknown |
| Deployment | PACS/RIS workstations |
| Compliance | |
| BAA Available | Unknown AI-estimated |
| HIPAA Compliant | Unknown AI-estimated |
| FDA Status |
1 AI-estimated The EFAI Chestsuite XR Malpositioned ETT Assessment System (ETT-XR-100) received U.S. FDA 510(k) clearance (K242821) on February 20, 2025. It is classified as a Class II radiological computer-aided triage and notification software (21 CFR 892.2080, Product Code QAS). |
| Integrations | |
| EHR | Not specified |
| Specialties | Critical Care, Emergency Medicine, Radiology |
What the Web Says
The EFAI Chestsuite XR Malpositioned ETT Assessment System (ETT-XR-100) is a radiological computer-assisted triage and notification software that uses deep learning to analyze chest X-rays for malpositioned endotracheal tubes (ETTs) in adults. It aims to assist hospital networks and medical specialists by flagging suspected cases for earlier review, thereby improving workflow and potentially enhancing patient safety and outcomes. The system provides a passive notification to PACS/RIS workstations, indicating cases that may benefit from prioritization, but it does not highlight specific locations on the radiographs or make standalone clinical decisions.
Overall: PositiveStrengths
- Accelerates image review workflows for radiologists and emergency physicians.
- Significantly mitigates the risk of missed diagnoses related to ETT malposition.
- Provides early intervention capability for malpositioned ETTs, enhancing patient safety and improving clinical outcomes.
- Demonstrated high sensitivity (89%) and specificity (93%) in detecting malpositioned ETTs.
- Offers consistent and reliable performance across diverse subgroups, including different genders, age groups, race/ethnicity, and X-ray manufacturers.
- Integrates seamlessly with existing X-ray workflows and PACS/RIS systems.
Limitations
- Does not mark, highlight, or direct users' attention to a specific location on the original chest radiographs.
- Results are not intended to be used on a stand-alone basis for clinical decision-making.
- Not intended to rule out malpositioned ETT or otherwise preclude clinical assessment of chest radiographs.
- Assesses solely the vertical position of the ETT distal tip relative to the carina and does not factor patient positioning or detect esophageal intubation.
- May trigger a false prioritization alert in the case of properly positioned double lumen ETTs.
- Does not provide results when the carina is not well-visualized on the X-ray image.
Based on reviews from: accessdata.fda.gov, Everfortune.AI, Healthcare+ B2B, PMC, Respiratory Therapy, AuntMinnie, EurekAlert!, Frontiers, YouTube, Imaging Technology News, Radiography, Axis Imaging News
Last updated: 2026-07-19
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