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Deep Vein ThrombosisDVT GUARDNCT06652568

Determining the Validity of ThinkSono Guidance for Ultrasound Image Acquisition and Remote Detection

A study testing ThinkSono System in people with Deep Vein Thrombosis and Deep Vein Thrombosis, Pulmonary Embolus, run by ThinkSono, Ltd. at 5 sites in United States.

Completed

Finished. The study has ended and is not enrolling. Results may be posted on the official record.

Official record

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Trial summary

The purpose of this study is to confirm the safety and efficacy of ThinkSono Guidance, a software data collection and communication tool designed to collect ultrasound data to help detect blood clots in veins. The ThinkSono system is CE Mark approved in the European Union and in clinical use in Europe. Read more about this study

Who is it for?
Ages 18 years and older
What is being tested?
ThinkSono System
Type of treatment
Medical device
Could I receive a placebo?
No, everyone receives an active treatment
How many people
634 participants
Where
5 sitesUnited States
Study dates
8 Nov 2023to 8 Dec 2025
Phase
Interventional

Key requirements

Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.

  • Ages 18 years and older
  • All sexes
  • No healthy volunteers
  • Adult, Older adult

Who may be able to join

  • The participant is willing to provide written informed consent to participate in this research.
  • The participant is over the age of 18
  • The participant has symptoms suggestive of a deep venous thrombosis (DVT)
  • The diagnostic DVT algorithm indicates that an ultrasound is needed

Who cannot join

  • Patient consent not given or retracted during the study.
  • Local imaging specialists fail to scan the patient or fail to produce a conclusive imaging diagnosis.
  • Incomplete ThinkSono Guidance scan due to logistical or other issues such as pain, lack of patient cooperation, barriers such as a cast or other physical limitations.
  • Pregnant women
  • Patients who undergo a local imaging scan and initiation of new treatment for DVT (e.g. lytic agents, therapeutic anticoagulation, or intervention after the local imaging scan) before a ThinkSono scan can be performed.

Trial locations and contacts

5 sites in 1 country.

5 sites in 1 country

United States5 sites
  • University of Wisconsin-Madison

    Madison, Wisconsin, 53792

  • NYU Langone Health

    New York, New York, 10016

  • Temple Health

    Philadelphia, Pennsylvania, 19140

  • Allegheny Health Network

    Pittsburgh, Pennsylvania, 15212

  • South Texas Veterans Health System

    San Antonio, Texas, 78229

Other trials in United States

About this study

The purpose of this study is to confirm the safety and efficacy of ThinkSono Guidance, a software data collection and communication tool designed to collect ultrasound data to help detect blood clots in veins. The ThinkSono system is CE Mark approved in the European Union and in clinical use in Europe. Usually, when an ultrasound is conducted to detect blood clots in veins, a sonographer (trained technologist who conducts ultrasounds) and/or radiologist will conduct the procedure, including a compression ultrasound exam, and the scan may require a bulky cart and ultrasound equipment. ThinkSono Guidance is a mobile software application that enables other healthcare professionals such as nurses, non-radiologist physicians including general practitioners, and other allied healthcare professionals to perform the ultrasound at the point of care using guidance from the software app. This is a multi-site non-randomized, double-blinded, prospective cohort pivotal study.

Read the detailed description

Deep vein thrombosis (DVT) is well recognized to cause significant morbidity and mortality both at the time of diagnosis and post-diagnosis. With an estimated incidence of 1- 2 per 1,000 people, over to 300,000 people in the US will be diagnosed with venous thromboembolism (VTE) per annum and two-thirds of these will be DVT. However, positive cases only represent 12-25% of the total number of patients who present with suspected DVT. In other words, between 75-88% of suspected DVT cases, when fully investigated, are negative. Estimates have placed the yearly cost of VTE to the US healthcare system at up to $10 billion.

It is notoriously difficult to diagnose a DVT by clinical acumen alone. The standard approach to making a diagnosis of proximal DVT currently involves an algorithm combining pre-test probability assessment through the Wells score, and compression ultrasonography. Handheld ultrasound probes have recently become available. These probes have enabled 'app-based' compression ultrasonography to be performed without the need for bulky cart or laptop-based ultrasound machines. These new machines have a small form factor, meaning only the ultrasound probe is required for diagnostic purposes in conjunction with a smartphone or tablet.

At present, although the new handheld probes are smaller and are better suited for point of care diagnosis, they still require an experienced radiologist or sonographer to perform the compression exam. This means that these devices can only be used wherever sonographers/radiologists are based most often i.e. hospital radiology departments. However, due to recent advances in "machine learning", software is now being developed for these 'app-based' probes that can assist non-radiology specialist healthcare professionals (e.g. nurses, non-radiologist physicians, general practitioners and other allied healthcare professionals) to carry out the compression ultrasound exam with minimal training.

ThinkSono Guidance is a guidance software expected to help non-radiology specialist healthcare professionals produce compression ultrasound image data that meet or exceed the minimal image quality criteria for a remote diagnosis by an expert (e.g. radiologist). The ThinkSono system is CE Mark approved in the European Union and in clinical use in Europe.

This study is a multi-site non-randomized, double-blinded, prospective cohort pivotal study. The purpose of this study is to confirm the safety and efficacy of ThinkSono Guidance as per the intended use defined as:

ThinkSono Guidance is a guidance, data acquisition and communication tool that guides non-ultrasound-trained healthcare staff to collect point of care compression ultrasound data in the proximal deep venous system of the lower extremity for interpretation by qualified clinicians.

Being tested
ThinkSono System
Keywords
Deep vein thrombosis, Artificial intelligence, Machine learning, Ultrasound
Medical subject headings
Venous Thrombosis, Pulmonary Embolism

What participants receive

What participants receive. In a randomised study each person is assigned to one group by chance.

  • ThinkSono SystemDevice

    The ThinkSono Guidance System is a guidance software expected to help non-radiology specialist healthcare professionals produce compression ultrasound image data that meet or exceed the minimal image quality criteria for a remote diagnosis by an expert (e.g. radiologist).

Study groups in NCT06652568
Study groupRoleWhat they receive
Single ArmOtherThis arm of patients will undergo an ultrasound scan using the ThinkSono system and a comparison standard of care duplex ultrasound scan.
Receives: Device: ThinkSono System

What is being measured

The primary outcome is the main question the study is designed to answer.

  1. Image Quality Adequacy

    ThinkSono Guidance achieves adequate image quality with an American College of Emergency Physicians (ACEP) score equal to or greater than 3 in at least 60% of scans to show that non-ultrasound-trained operators can acquire relevant cine-loops (an expectation ≥75%, lower CI ≥60%). The ACEP score is a score on a scale of 1-5 assessing utilized as the national standard for image quality evaluation. Further information is available at: https://www.acep.org/siteassets/uploads/uploaded-files/acep/clinical-and-practice-management/policy-statements/information-papers/emergency-ultrasound-standard-reporting-guidelines---2018.pdf.

    Measured: Measured during ThinkSono Guidance scanning (median scan time of 5.4 minutes).

Secondary outcomes (4)
  1. Triage Sensitivity

    The sensitivity for overall triage performance for proximal DVT is at least 85%.

    Measured: Measured during ThinkSono Guidance scanning (median scan time of 5.4 minutes).

  2. Triage Specificity

    The specificity for overall triage performance for proximal DVT is at least 30%.

    Measured: Measured during ThinkSono Guidance scanning (median scan time of 5.4 minutes).

  3. Prioritization Specificity

    Prioritization specificity quantifies how reliably the system identifies patients who merit high-urgency imaging specialist assessment based on their ThinkSono scans. A high prioritization specificity means that there are very few false-positive scans that lead to patients being prioritized unnecessarily. Further details are available in the trial protocol and statistical analysis plan.

    ThinkSono Guidance achieves specificity for prioritizing patients of at least 93%. This means that at least 93% of scans without proximal lower extremity DVT were not labeled as false positives by reviewers of ThinkSono Guidance scans.

    Measured: Measured during ThinkSono Guidance scanning (median scan time of 5.4 minutes).

  4. Predictive Values

    To observe the negative-predictive-value and positive-predictive-value of ThinkSono Guidance triage performance.

    Measured: Measured during ThinkSono Guidance scanning (median scan time of 5.4 minutes).

Timeline

From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.

  1. First posted22 Oct 2024
  2. Study start8 Nov 2023
  3. Primary completion8 Dec 2025
  4. Study completion8 Dec 2025

Resources

More details

For doctors and researchers: how the study is designed, who runs it, and its registry IDs.

Study design
Study type
Interventional
Phase
Phase N/A
Primary purpose
Diagnosis
Allocation
Not applicable
Intervention model
Single group
Model description
Single arm comparison study between the ThinkSono device and standard of care venous duplex ultrasound.
Masking
None (open label)
Enrolment
634 participants (actual)
IDs, dates and publications
ClinicalTrials.gov ID
NCT06652568
Sponsor's protocol ID
012023
Acronym
DVT GUARD
Status last verified
Feb 2026
First submitted
12 Oct 2024
Last updated
17 Jul 2026
Data monitoring committee
No
FDA-regulated drug
No
FDA-regulated device
Yes
Individual data sharing
No

Publications

  • Nothnagel K, Aslam MF. Evaluating the benefits of machine learning for diagnosing deep vein thrombosis compared with gold standard ultrasound: a feasibility study. BJGP Open. 2025 Jan 2;8(4):BJGPO.2024.0057. doi: 10.3399/BJGPO.2024.0057. Print 2024 Dec.

    PubMed 38866404
  • Poulikidis KP, Gasparis AP, Labropoulos N. Prospective analysis of incidence, extent and chronicity of lower extremity venous thrombosis. Phlebology. 2014 Feb;29(1):37-42. doi: 10.1258/phleb.2012.012086. Epub 2013 May 6.

    PubMed 23131597
  • Grosse SD, Nelson RE, Nyarko KA, Richardson LC, Raskob GE. The economic burden of incident venous thromboembolism in the United States: A review of estimated attributable healthcare costs. Thromb Res. 2016 Jan;137:3-10. doi: 10.1016/j.thromres.2015.11.033. Epub 2015 Nov 24.

    PubMed 26654719
  • Prandoni P, Kahn SR. Post-thrombotic syndrome: prevalence, prognostication and need for progress. Br J Haematol. 2009 May;145(3):286-95. doi: 10.1111/j.1365-2141.2009.07601.x. Epub 2009 Feb 13.

    PubMed 19222476
  • Roberts LN, Patel RK, Donaldson N, Bonner L, Arya R. Post-thrombotic syndrome is an independent determinant of health-related quality of life following both first proximal and distal deep vein thrombosis. Haematologica. 2014 Mar;99(3):e41-3. doi: 10.3324/haematol.2013.089870. Epub 2014 Jan 17. No abstract available.

    PubMed 24441147
  • Kearon C, Julian JA, Newman TE, Ginsberg JS. Noninvasive diagnosis of deep venous thrombosis. McMaster Diagnostic Imaging Practice Guidelines Initiative. Ann Intern Med. 1998 Apr 15;128(8):663-77. doi: 10.7326/0003-4819-128-8-199804150-00011.

    PubMed 9537941
  • Kainz B, Heinrich MP, Makropoulos A, Oppenheimer J, Mandegaran R, Sankar S, Deane C, Mischkewitz S, Al-Noor F, Rawdin AC, Ruttloff A, Stevenson MD, Klein-Weigel P, Curry N. Non-invasive diagnosis of deep vein thrombosis from ultrasound imaging with machine learning. NPJ Digit Med. 2021 Sep 15;4(1):137. doi: 10.1038/s41746-021-00503-7.

    PubMed 34526639
  • Oppenheimer J, Mandegaran R, Staabs F, Adler A, Singohl S, Kainz B, Heinrich M, Geroulakos G, Spiliopoulos S, Avgerinos E. Remote Expert DVT Triaging of Novice-User Compression Sonography with AI-Guidance. Ann Vasc Surg. 2024 Feb;99:272-279. doi: 10.1016/j.avsg.2023.08.022. Epub 2023 Oct 10.

    PubMed 37820986

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