Home / Clinical Decision Support & Reference / EFAI Neurosuite CT Midline Shift Assessment System (MLS-CT-100)

EFAI Neurosuite CT Midline Shift Assessment System (MLS-CT-100)

by Ever Fortune.AI Co., Ltd. · Based in Taiwan → — Revolutionize the healthcare industry with Everfortune. AI's cutting-edge digital solution, utilizing the latest advancements in AI and big data analysis to improve patient outcomes.

Emergency Medicine Neurosurgery Radiology

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Overview

The EFAI Neurosuite CT Midline Shift Assessment System (MLS-CT-100) by Ever Fortune.AI is a radiological computer-assisted triage and notification software designed to enhance the efficiency of emergency and neurology workflows. Utilizing advanced deep learning techniques, the system automatically analyzes non-contrast head CT images to identify features suggestive of midline shift (MLS) in individuals aged 18 years and above. Upon detection, it alerts the PACS/RIS workstation, enabling radiologists to review studies with potential MLS earlier than in standard care workflows. This AI-powered tool is intended to aid in prioritizing the clinical assessment of non-contrast head CT cases, thereby supporting timely intervention and improved patient outcomes.

Ever Fortune.AI specializes in AI solutions for the healthcare sector, focusing on medical big data and cloud-based biomedical platforms. The company is committed to innovative developments in artificial intelligence, smart medicine, and precision medicine, with a vision to provide solutions to experts anytime, anywhere.

Reviewed by Pouyan Golshani, MD — Interventional Radiologist

Key Features

Automated detection of midline shift (MLS) on non-contrast head CTs
Deep learning-based image analysis
Alerts PACS/RIS workstations for suspected MLS cases
Prioritization of clinical assessment for urgent cases
Aids radiologists in earlier review of critical studies
Designed for adult patients (18 years and above)
Software workflow tool for triage and notification

Use Cases

Expediting the review of non-contrast head CTs in emergency settings
Prioritizing radiologist worklists for suspected midline shift
Assisting in timely diagnosis and intervention for neurological emergencies
Improving workflow efficiency in neuroradiology departments

What Physicians Need to Know

Evidence Base

The EFAI Neurosuite CT Midline Shift Assessment System (MLS-CT-100) utilizes deep learning algorithms to analyze non-contrast head CT images for suspected midline shift (MLS). Midline shift is a critical indicator of brain trauma severity and is associated with increased intracranial pressure, which can lead to brain stem compression and death if untreated. The system aims to assist in prioritizing the clinical assessment of CT cases with features suggestive of MLS. Research has explored the use of AI and deep learning for automated MLS detection and quantification, with studies reviewing various AI-based methods. A significant MLS, often defined as greater than 5 mm, is considered clinically meaningful and can predict poor neurological outcomes.

Clinical Validation Studies

The EFAI MLS-CT system has undergone performance validation studies. In a standalone validation study, the system demonstrated a sensitivity of 0.961 (95% CI=0.903-0.985) and a specificity of 0.955 (95% CI=0.916-0.973), with an AUROC of 0.983 (95% CI=0.967-0.996). These results were found to be substantially equivalent to a predicate device. Other research in the field of automated MLS detection using deep learning has shown varying results. One study using a 3D convolutional neural network (CNN) model trained on 156 head CT scans and tested on 20, reported an accuracy of 55%, with a sensitivity of 40% and specificity of 70%. Another automated system achieved an overall accuracy of 90.24%, improving to 92.68% with manual calibrations. A deep learning architecture applied to point-of-care MRI for MLS estimation in stroke patients was found to be non-inferior to neuroradiologist estimates (p<1e-5). This system's MLS measurements were associated with stroke severity and predicted worse outcomes.

Alert Fatigue Management

The EFAI Neurosuite CT Midline Shift Assessment System is designed to aid in workflow triage by flagging suspected positive findings of pathologies in head CT images, including midline shift. It makes case-level output available to a PACS/workstation for worklist prioritization or triage. The system is intended to help prioritize the clinical assessment of non-contrast head CT cases. The goal is to allow radiologists to review studies with features suggestive of MLS earlier than in a standard workflow. If a significant midline shift (larger than 5 mm) is detected, a 'modest alert' should notify the user.

Differential Diagnosis Support

The EFAI MLS-CT is a software workflow tool designed to identify suspected MLS findings. It is not intended to direct attention to specific portions of an image or to anomalies other than MLS. Midline shift can result from various conditions that cause mass effect and increased intracranial pressure, such as traumatic brain injury, hematoma, stroke, brain swelling, tumors, or abscesses. The system flags suspected positive findings of intracranial hemorrhage, mass effect, midline shift, and cranial fracture.

Clinical Workflow Integration

The EFAI Neurosuite CT Midline Shift Assessment System is a radiological computer-assisted triage and notification software system. It analyzes non-contrast head CTs using deep learning algorithms and alerts the PACS/RIS workstation when images with features suggestive of MLS are identified. This allows for earlier review of such studies by a radiologist. The algorithm is designed to execute after the exam is verified on PACS and optimally integrates with PACS and dictation or reporting software. The user can then automatically populate the report or manually input the results, and an indicator image may be saved to PACS as part of the medical record.

Physician Tip

The EFAI Neurosuite CT Midline Shift Assessment System (MLS-CT-100) is a valuable tool for prioritizing and triaging non-contrast head CT scans in cases of suspected midline shift (MLS). While it can help identify potentially critical cases earlier, it is crucial to remember that the system's results are not intended for stand-alone clinical decision-making. Always integrate the AI's findings with your comprehensive clinical assessment, patient history, and other imaging interpretations. Pay close attention to the 'modest alerts' for significant MLS (greater than 5 mm) as these often indicate a need for urgent intervention. The system is designed to assist in workflow, not replace the expertise of medical professionals.

The EFAI Neurosuite CT Midline Shift Assessment System (MLS-CT-100) is designed for seamless integration into existing radiology workflows. It makes case-level output available to Picture Archiving and Communication Systems (PACS) and Radiology Information Systems (RIS) workstations for worklist prioritization and triage. The algorithm is intended to execute after an exam is verified on PACS and is optimized for integration with PACS and dictation or reporting software. This allows for automatic population of reports or manual input of results, and an indicator image can be saved to PACS.

At a glance

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Details

Category	Clinical Decision Support & Reference, Neurology AI
Pricing	Unknown
Compliance
BAA Available	Unknown
HIPAA Compliant	Unknown
FDA Status	Cleared AI-estimated
Integrations
EHR	Not specified
Specialties	Emergency Medicine, Neurosurgery, Radiology

What the Web Says

The EFAI Neurosuite CT Midline Shift Assessment System (MLS-CT-100) is a software workflow tool that uses deep learning to analyze non-contrast head CT scans and identify features suggestive of midline shift (MLS) in patients aged 18 and above. It is designed to aid in prioritizing the clinical assessment of these cases by alerting PACS/RIS workstations, allowing radiologists to review potentially critical studies earlier. The system is intended for triage and notification, not for standalone clinical decision-making or to direct attention to specific image anomalies other than MLS.

Overall: Positive

Strengths

Aids in prioritizing clinical assessment of CT scans with suspected MLS, potentially leading to earlier review by radiologists.
Utilizes deep learning algorithms for automated analysis of non-contrast head CTs.
Achieved high sensitivity (0.961) and specificity (0.955) in detecting features suggestive of MLS in standalone performance validation.
Can be valuable for non-specialists in emergency situations by providing automated MLS measurements.
Automated MLS measurement can improve diagnostic efficiency and accuracy.
May help in predicting intracranial pressure (ICP) based on anatomic changes.

Limitations

Not intended for standalone clinical decision-making.
Not designed to direct attention to specific portions of an image or anomalies other than MLS.
Does not rule out MLS or preclude clinical assessment of CT studies.
Limited information available from independent physician reviews, healthcare IT, tech reviewers, Reddit, G2, or Capterra specifically for this product.
Some automated MLS detection systems have faced challenges in accurately measuring large MLS with significant hematoma.
Further research and standardization of evaluation protocols are needed for AI algorithms in MLS detection to establish reliability and generalizability in clinical practice.

Based on reviews from: youtube.com, nih.gov, innolitics.com, ruralneuropractice.com, acr.org, researchgate.net, fda.gov, aihealthcarenow.com, mdpi.com, warrick.net, arxiv.org, reddit.com, semanticscholar.org, drdeepakaiims.com, scilit.com, nysora.com

Last updated: 2026-10-30

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Press & Coverage

physicianaitools.com

EFAI Neurosuite CT Midline Shift Assessment System (MLS-CT-100)

The EFAI Neurosuite CT Midline Shift Assessment System (MLS-CT-100) is an FDA-cleared AI software that automatically analyzes non-contrast head CTs to detect and prioritize cases with suspected midline shift, streamlining neurological emergency workflows. It is classified as a Clinical Decision Support & Reference tool.

2026-04

fda.gov

EFAI Neurosuite CT Midline Shift Assessment System (MLS-CT-100) FDA 510(k) Clearance

The EFAI Neurosuite CT Midline Shift Assessment System (MLS-CT-100) received FDA 510(k) clearance on December 6, 2024. This software workflow tool uses deep learning to prioritize non-contrast head CT cases with suspected midline shift in adults aged 18 and above, making case-level output available to PACS/workstations for worklist prioritization or triage.

2024-12

healthcareaiops.com

Every FDA-cleared AI device, indexed.

The EFAI Neurosuite CT Midline Shift Assessment System (MLS-CT-100) from Ever Fortune.Ai, Co., Ltd. is listed as an FDA-cleared AI device with a decision date of December 6, 2024, under product code QAS (Radiological Computer-Assisted Triage And Notification Software).

2026-10

parikhradiology.com

EFAI Neurosuite CT Midline Shift Assessment System (MLS-CT-100)

The EFAI Neurosuite CT Midline Shift Assessment System (MLS-CT-100) is designed for the prioritization and triage of non-contrast head CT cases with features suggestive of midline shift in individuals aged 18 years and older. Its FDA decision date was December 6, 2024.

2026-03

warrick.net

EFAI Neurosuite CT Midline Shift Assessment System (MLS-CT-100) FDA 510(k) APPLICATION FOR Ever Fortune.AI, Co., Ltd.

This entry confirms the FDA 510(k) application for the EFAI Neurosuite CT Midline Shift Assessment System (MLS-CT-100) by Ever Fortune.AI, Co., Ltd.

unknown

healtharatus.com

EFAI Neurosuite CT Midline Shift Assessment System (MLS-CT-100)

The EFAI Neurosuite CT Midline Shift Assessment System (MLS-CT-100) received 510(k) clearance (K241923) on December 6, 2024. It is listed as an FDA-authorized device.

2024-12

reachmd.com

The Medical AI Diagnostic Benchmark Hub

The EFAI Neurosuite CT Midline Shift Assessment System (MLS-CT-100) by Ever Fortune.Ai, Co., Ltd. is listed in the Medical AI Diagnostic Benchmark Hub with FDA# K241923, and its evidence is currently pending.

2026-06

fda.report

Radiological Computer-Assisted Triage And… - FDA.report.

The EFAI Neurosuite CT Midline Shift Assessment System (MLS-CT-100) from Ever Fortune.Ai, Co., Ltd. is listed with a decision date of December 6, 2024, under product code QAS, which signifies Radiological Computer-Assisted Triage And Notification Software.

2024-12

Videos

Product demos, reviews, and walkthroughs for EFAI Neurosuite CT Midline Shift Assessment System (MLS-CT-100).

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Frequently Asked Questions

What is the intended use of the EFAI Neurosuite CT Midline Shift Assessment System (MLS-CT-100) and how does it support clinical decision-making?

The EFAI Neurosuite CT Midline Shift Assessment System (MLS-CT-100) is a software workflow tool designed to assist in prioritizing the clinical assessment of non-contrast head CT cases that suggest a midline shift (MLS) in adults. It uses deep learning algorithms to identify suspected MLS findings and provides case-level output to a PACS/workstation for worklist prioritization or triage. This allows radiologists to review studies with potential MLS earlier than in a standard workflow, but it is not intended for standalone clinical decision-making or to rule out MLS.

What are the performance characteristics and limitations of the EFAI Neurosuite CT Midline Shift Assessment System (MLS-CT-100)?

The EFAI MLS-CT-100 demonstrated a sensitivity of 0.961 and specificity of 0.955, with an AUROC of 0.983, which was found to be substantially equivalent to a predicate device. The average processing time per study is approximately 62.04 seconds. However, it's important to note that the system is not intended to direct attention to specific portions of an image or anomalies other than MLS, and its results should not be used as a stand-alone basis for clinical decision-making.

How does the EFAI Neurosuite CT Midline Shift Assessment System (MLS-CT-100) compare to manual assessment of midline shift?

Automated systems for MLS measurement, like the EFAI MLS-CT-100, aim to provide a fast and accurate alternative to manual measurements, which can be laborious. Studies on similar automated systems have shown high accuracy, with one achieving an overall accuracy of 90.24% (improving to 92.68% with manual calibration) and another demonstrating a mean absolute error of 0.936 mm compared to ground truth. These systems can also achieve high sensitivity and specificity for detecting significant MLS.

What are the regulatory compliance aspects of the EFAI Neurosuite CT Midline Shift Assessment System (MLS-CT-100)?

The EFAI Neurosuite CT Midline Shift Assessment System (MLS-CT-100) is classified as a Class II medical device under regulation number 21 CFR 892.2080, which pertains to Radiological Computer Aided Triage and Notification Software. It has received 510(k) premarket notification clearance from the U.S. Food & Drug Administration (FDA).

Are there any alternatives to the EFAI Neurosuite CT Midline Shift Assessment System (MLS-CT-100) for assessing midline shift?

Yes, several alternative methods and systems exist for assessing midline shift. These include manual measurement by radiologists, other automated systems utilizing deep learning or image processing techniques, and bedside methods like transcranial sonography (TCS). While TCS can provide additional information and trigger further imaging, it should not replace a CT scan for detecting MLS. Other AI-based tools for detecting critical findings in head CT scans also exist.