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Benefit of Machine Learning to Diagnose Deep Vein Thrombosis Compared to Gold Standard Ultrasound

NCT05288413 · Status: WITHDRAWN · Type: OBSERVATIONAL

Last updated 2023-01-30

No results posted yet for this study

Summary

The study coordinator aims to compare gold standard deep vein thrombosis (DVT) diagnostic performed by a specialist sonographer to a scan by a non-specialist with a newly developed an automated DVT (AutoDVT) detection software device.

The title of the project is: Benefit of Machine learning to diagnose Deep Vein thrombosis compared to gold standard Ultrasound.

Currently the process from the DVT symptom begin, to diagnosis and then treatment is all but not straightforward. It implements a laborious journey for the patient from their general practitioner (GP) to accident and emergency (A\&E), then to a specialist sonographer.

However, handheld Ultrasound devices have recently become available and they have been implemented with a machine learning software. The startup company ThinkSono developed a software which is hoped to divide between thrombosis and no thrombosis. In this single-blinded pilot study, patients which present at St Mary's DVT Clinic will be scanned by the specialist and then by a non-specialist with the machine learning supported device. The accuracy and sensitivity of this device will be compared to the gold standard.

This would mean that DVT could be diagnosed at point of care by a non-specialist such as a community nurse or nursing home nurse, for example beneficial for multimorbid confused nursing home patients. This technology could reduce A\&E crowding and free up specialist sonographer to focus on other clinical tasks. These improvements could significantly reduce the financial burden for the National Health System (NHS).

The AutoDVT has a CE (as the logo CЄ, which means that the manufacturer or importer affirms the good's conformity with European health, safety, and environmental protection standards) Certificate under the directive 93/42/ European Economic Community (EEC) for medical devices. It is classified in Class 1 - Active Medical Device - Ultrasound Imaging System Application Software (40873).

Furthermore, following standards and technical specifications have been applied: British Standard (BS) European Norm (EN) International Organisation for Standardisation (ISO) 13485:2016, BS EN ISO 14971:2012, Data Coordination Board (DCB)0129:2018, ISO 15233-1:2016.

Conditions

  • Deep Venous Thrombosis of Leg
  • Deep Vein Thrombosis

Interventions

DEVICE

3-compression Ultrasound scan with AutoDVT software integrated Ultrasound probe

The study coordinator, Miss Kerstin Saupe will perform a three-point compression ultrasound scan (USS) of the upper leg with the AutoDVT software. The AutoDVT software will store the results of the scan for retroperspective analysis and review. Effectiveness of AutoDVT as diagnostic tool will be evaluated in perspective to different patient groups, eg. patients with adipositas or maligner disease,

Sponsors & Collaborators

  • Imperial College London

    lead OTHER

Principal Investigators

  • Mohammed F Aslam, MBA, PhD · Imperial College London

Eligibility

Min Age
18 Years
Max Age
90 Years
Sex
ALL
Healthy Volunteers
No

Timeline & Regulatory

Start
2022-03-01
Primary Completion
2022-08-01
Completion
2022-08-01

Countries

  • United Kingdom

Study Locations

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Read the full study record

This page highlights key information. For complete eligibility criteria, study locations, investigator contacts, and the full protocol, visit the original record on ClinicalTrials.gov.

View NCT05288413 on ClinicalTrials.gov