Incidental Pulmonary embolism (iPE)

Aidoc
Aidoc’s Incidental Pulmonary Embolism algorithm is a triage and notification software that flags and communicates suspected positive findings of pulmonary embolism and runs automatically on contrast enhanced CT protocols that include any part of the lungs.
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Information source: Vendor
Last updated: Aug. 18, 2023

General Information

General
Product name Incidental Pulmonary embolism (iPE)
Company Aidoc
Subspeciality Chest
Modality CT
Disease targeted Pulmonary embolism
Key-features Triage tool, workflow improvement
Suggested use Triage/prioritization of medical images

Technical Specifications

Data characteristics
Population Contrast-enhanced CTs
Input Contrast CT, GE or Siemens acquired
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 Contrast-enhanced CT studies of the chest (not dedicated CTPA protocol). 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 Incidental Pulmonary Embolism (iPE).

Market

Market presence
On market since 10-2020
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

  • Added value of an artificial intelligence algorithm in reducing the number of missed incidental acute pulmonary embolism in routine portal venous phase chest CT (read)

  • Artificial Intelligence Tool for Detection and Worklist Prioritization Reduces Time to Diagnosis of Incidental Pulmonary Embolism at CT (read)

  • Unreported incidental pulmonary embolism in patients with cancer: Radiologic natural history and risk of recurrent venous thromboembolism and death (read)

  • Incidental pulmonary embolism in patients with cancer : prevalence , underdiagnosis and evaluation of an AI algorithm for automatic detection of pulmonary embolism (read)

  • Detection of Incidental Pulmonary Embolism on Conventional Contrast-Enhanced Chest CT: Comparison of an Artificial Intelligence Algorithm and Clinical Reports (read)
Non-peer reviewed papers on performance

  • Abstract: Use of a Machine Learning Algorithm to Detect Incidental Pulmonary Embolus (read)
Other relevant papers