Determining the Validity of ThinkSono Guidance for Ultrasound Image Acquisition and Remote Detection
NCT ID: NCT06652568
Last Updated: 2025-12-15
Study Results
The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.
Basic Information
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RECRUITING
NA
500 participants
INTERVENTIONAL
2023-11-08
2025-12-31
Brief Summary
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Detailed Description
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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 Well's 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.
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). 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 the ThinkSono Guidance System as per the intended use defined as:
ThinkSono Guidance System 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.
Conditions
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Study Design
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NA
SINGLE_GROUP
DIAGNOSTIC
NONE
Study Groups
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Comparison Arm
This arm of patients will undergo an ultrasound scan using the ThinkSono system and a comparison standard of care duplex ultrasound scan.
ThinkSono System
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).
Interventions
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ThinkSono System
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).
Eligibility Criteria
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Inclusion Criteria
* 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
Exclusion Criteria
* 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.
18 Years
ALL
Yes
Sponsors
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NYU Langone Health
OTHER
Temple Health
UNKNOWN
Allegheny Health Network
OTHER
University of Wisconsin, Madison
OTHER
South Texas Veterans Health Care System
FED
ThinkSono, Ltd.
INDUSTRY
Responsible Party
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Principal Investigators
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Glenn Jacobowitz, MD
Role: PRINCIPAL_INVESTIGATOR
Northwell Health
Locations
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NYU Langone Health
New York, New York, United States
Temple Health
Philadelphia, Pennsylvania, United States
Allegheny Health Network
Pittsburgh, Pennsylvania, United States
South Texas Veterans Health System
San Antonio, Texas, United States
University of Wisconsin-Madison
Madison, Wisconsin, United States
Countries
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Central Contacts
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Facility Contacts
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References
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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.
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.
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.
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.
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.
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.
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.
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.
Related Links
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Study sponsor website
Other Identifiers
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012023
Identifier Type: -
Identifier Source: org_study_id
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