GuidewireRx offers VascularAssist, an AI‑powered platform that automatically detects and quantifies peripheral arterial lesions on CTA runoff studies, generating structured report elements and severity scores. The system overlays stenosis locations on the original images, provides risk‑stratification alerts, and integrates directly with existing PACS/RIS via DICOM and HL7, helping radiology departments improve diagnostic accuracy and reporting efficiency.
Funding
Funding not disclosed
Founders
Product
Problem
Peripheral vascular disease is often under‑detected on CT angiography because radiologists must manually assess complex runoff images, leading to missed diagnoses, reporting errors, and inefficient use of imaging time.
Solution
GuidewireRx’s VascularAssist platform applies artificial intelligence and advanced image‑processing algorithms to automatically analyze peripheral CTA runoff studies. The system highlights arterial stenoses, quantifies disease severity, and flags patients at risk, enabling radiologists to generate more accurate reports faster. Integrated visual overlays and structured findings support treatment planning and streamline referrals to vascular specialists. By embedding the AI workflow into existing PACS/RIS environments, VascularAssist improves diagnostic confidence without requiring additional hardware or extensive training.
Target Audience
Primary customers are hospital radiology departments and independent radiology practices that interpret peripheral CTA studies and seek to improve reporting efficiency and diagnostic quality.
Features
- AI‑driven detection and quantification of peripheral arterial lesions on CTA runoff images
- Automated generation of structured report elements and severity scores for rapid documentation
- Visual overlay of stenosis locations and flow‑limiting lesions within the original imaging study
- Risk stratification alerts that identify “at‑risk” patients for early intervention
- Seamless integration with PACS/RIS via DICOM and HL7 interfaces, requiring no extra equipment
- Cloud‑based analytics engine that continuously learns from aggregated clinical data to refine accuracy