Pulmonary embolism (PE)

Aidoc
Aidoc’s Pulmonary Embolism solution is a triage and notification software indicated for use in the analysis of CTPA images; flags and communicates Pulmonary Embolism (PE).
aidoc-pulmonary-embolism.png
Information source: Vendor
Last updated: Oct. 28, 2023

General Information

General
Product name Pulmonary embolism (PE)
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 Chest CTs with contrast
Input CTPA
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 CTPA 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 Pulmonary Embolism (PE).

Market

Market presence
On market since 04-2019
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

  • Prospective Evaluation of AI Triage of Pulmonary Emboli on CT Pulmonary Angiograms (read)

  • Decreased Hospital Length of Stay for ICH and PE after Adoption of an Artificial Intelligence-Augmented Radiological Worklist Triage System (read)

  • How artificial intelligence improves radiological interpretation in suspected pulmonary embolism (read)

  • Automated detection of pulmonary embolism in CT pulmonary angiograms using an AI-powered algorithm (read)
Non-peer reviewed papers on performance

  • Assessment of Artificial Intelligence Technology for Pulmonary Embolism Detection (read)
Other relevant papers