qER-Quant
Overview
Qure.ai’s qER-Quant is an AI-powered software designed for the automated analysis and quantification of non-contrast head CT (NCCT) images. It leverages deep learning algorithms to precisely quantify volumes of intracranial structures and lesions, including intracranial hyperdensities, lateral ventricles, and midline shift. This tool assists clinicians in rapidly assessing the severity of conditions such as traumatic brain injury (TBI), hemorrhagic stroke, and hydrocephalus.
The software is intended to automate the manual process of identifying, labeling, and quantifying brain structures, providing quantitative measurements that aid in diagnostic and treatment decisions. It also supports the comparison of multiple CT scans over time to monitor disease progression. qER-Quant integrates into standard radiology workflows, supporting various input and output formats like DICOM, PDF, and free text. Qure.ai emphasizes data privacy and security, adhering to HIPAA and GDPR standards, and offers flexible deployment options including cloud-based and on-premise solutions.
Reviewed by Pouyan Golshani, MD — Interventional Radiologist
Key Features
- Quantification of intracranial hyperdensities
- Quantification of lateral ventricles
- Quantification of midline shift
- Automatic labeling and visualization of brain structures
- Assists in determining severity of trauma, lesion, or underlying disease
- Comparison of multiple CT scans over time for progression monitoring
- Reduces door-to-scan interpretation times
- Accelerates communication of critical results to stroke teams
- Integration with standard reading environments (PACS/RIS)
- Supports DICOM GSPS, DICOM secondary capture, PDF, and free text output
Use Cases
- Assessing injury severity in traumatic brain injury (TBI)
- Assessing injury severity in hemorrhagic stroke
- Assessing injury severity in hydrocephalus
- Monitoring progression of neurological conditions
- Emergency room triage and prioritization of critical cases
- Supporting diagnostic and treatment decisions for neurocritical care
What Physicians Need to Know
Leverage qER-Quant's precise volumetric quantification of intracranial hyperdensities, lateral ventricles, and midline shift to objectively assess injury severity and track pathology progression over time. This quantitative data can enhance diagnostic confidence, support treatment planning, and facilitate consistent monitoring, especially in conditions like hemorrhagic stroke, traumatic brain injury, and hydrocephalus. Utilize the automated ASPECTS scoring for rapid evaluation of ischemic stroke severity. Integrate the mobile notifications for immediate alerts on critical findings to expedite patient triage and team activation.
qER-Quant is designed for seamless integration into existing radiology workflows. It interacts with Picture Archiving and Communication Systems (PACS) to receive scans and return results, and can also integrate with Radiological Information Systems (RIS). Deployment options include cloud-based or locally virtualized (VM, Docker) solutions, and it supports integration via AI marketplaces or distribution platforms.
Details
| Category | Neurology AI, Radiology & Imaging AI |
| Pricing | Contact for pricing |
| Deployment | Cloud-based; Locally virtualized (virtual machine, Docker); On-premise |
| Compliance | |
| BAA Available | Yes AI-estimated |
| HIPAA Compliant | Yes AI-estimated |
| FDA Status |
Yes AI-estimated qER-Quant received US FDA 510(k) clearance (K211222) on July 30, 2021, as an automated Radiological Image Processing Software. It is intended for automatic labeling, visualization, and quantification of intracranial hyperdensities, lateral ventricles, and midline shift from Non-Contrast head CT (NCCT) images. |
| Integrations | |
| EHR | Not specified |
| Specialties | Neurology, Neurosurgery, Radiology |
What the Web Says
Qure.ai's qER-Quant is an AI-powered software designed to assist physicians in rapidly assessing and quantifying the severity of neurological conditions like traumatic brain injury, hemorrhagic stroke, and hydrocephalus from head CT scans. It has received FDA 510(k) clearance and is praised for its ability to reduce diagnostic errors, accelerate treatment decisions, and monitor disease progression over time. Physicians and healthcare professionals highlight its value in emergency settings and long-term care due to its precision and automation in interpreting CT scans.
Overall: PositiveStrengths
- Rapid analysis of head CT scans, enabling quicker diagnosis and treatment decisions.
- Quantification of injury severity and tracking of pathology progression over time.
- Reduces the margin for human error in CT scan interpretation.
- FDA 510(k) clearance, solidifying its standing as a reliable medical solution.
- Seamless integration into existing hospital infrastructure and radiology workflows.
- Supports billable CPT codes, potentially creating new revenue streams for healthcare facilities.
Limitations
- No specific cons were found in the provided search results regarding qER-Quant from physicians, healthcare IT, tech reviewers, Reddit, G2, or Capterra.
- Some general Qure.ai products require specific alignment with revenue-cycle teams for successful reimbursement coding.
- Clinical effectiveness for subtle nodules (of other Qure.ai products) depends on specific imaging quality standards.
Based on reviews from: Qure.ai, AuntMinnie, G2, TestDynamics, Imaging Technology News, PR Newswire, Health AI Register, ResearchGate, WallStreetZen, Wall Street Survivor
Last updated: 2026-07-20
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