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Intracranial Hemorrhage (ICH)
Intracranial Hemorrhage (ICH)
Aidoc
Aidoc’s ICH solution is a triage and notification software indicated for use in the analysis of non-enhanced head CT images; flags and communicates suspected positive findings of pathologies in head CT images, namely Intracranial Hemorrhage (ICH).
Information source:
Vendor
Last updated:
Aug. 30, 2022
General Information
Technical Specifications
Regulatory
Market
Evidence
General Information
General
Product name
Intracranial Hemorrhage (ICH)
Company
Aidoc
Subspeciality
Neuro
Modality
CT
Disease targeted
Intracranial Hemorrhage
Key-features
Triage tool, workflow improvement
Suggested use
Triage/prioritization of medical images.
Technical Specifications
Data characteristics
Population
All non-contrast head CT
Input
Non-contrast head CT
Input format
DICOM
Output
flagging and communication of positive suspected findings
Output format
Annotated images: DICOM SC or overlay Prioritization notification: own application, HL7, API, bespoke integration
Technology
Integration
Integration in standard reading environment (PACS), Integration RIS (Radiological Information System),
Deployment
Hybrid solution
Trigger for analysis
Automatically, right after the image acquisition
Processing time
1 - 10 minutes
Regulatory
Certification
CE
Certified, Class I
, MDD
FDA
510(k) cleared , Class II
Intended Use Statements
Intended use (according to CE)
Radiological computer aided triage and notification software indicated for use in the analysis of head CT images. The device is intended to assist hospital networks and appropriately trained medical specialists in workflow triage by flagging and communication of suspected positive findings of Intracranial Hemorrhage (ICH).
Market
Market presence
On market since
11-2017
Distribution channels
Philips, Eureka Clinical AI, Nuance PIN, Fujifilm, Change Healthcare, GE Edison
Countries present (clinical, non-research use)
14
Paying clinical customers (institutes)
Over 500
Research/test users (institutes)
20-30
Pricing
Pricing model
Subscription
Based on
Total imaging volume
Evidence
Evidence
Peer reviewed papers on performance
Decreased Hospital Length of Stay for ICH and PE after Adoption of an Artificial Intelligence-Augmented Radiological Worklist Triage System
(read)
Utilization of Artificial Intelligence–based Intracranial Hemorrhage Detection on Emergent Noncontrast CT Images in Clinical Workflow
(read)
Diagnostic Accuracy and Failure Mode Analysis of a Deep Learning Algorithm for the Detection of Intracranial Hemorrhage
(read)
Active Reprioritization of the Reading Worklist Using Artificial Intelligence Has a Beneficial Effect on the Turnaround Time for Interpretation of Head CT with Intracranial Hemorrhage
(read)
Analysis of head CT scans flagged by deep learning software for acute intracranial hemorrhage
(read)
Non-peer reviewed papers on performance
The utility of deep learning: evaluation of a convolutional neural network for detection of intracranial bleeds on non-contrast head computed tomography studies
(read)
Preliminary Results of Aidoc's Deep Learning Algorithm Detection Accuracy for Pathological Intracranial Hyperdense Lesions
(read)
Utility of Artificial Intelligence Tool as a Prospective Radiology Peer Reviewer -Detection of Unreported Intracranial Hemorrhage
(read)
Other relevant papers
A prospective randomized clinical trial for measuring radiology study reporting time on Artificial Intelligence-based detection of intracranial hemorrhage in emergent care head CT
(read)