A Multicenter Study to Optimize Microembolic Signal Classification Based on Double--Blind Multiparametric Assessment by Human Experts Using an Universal Graphical Interface [MESOMEGA]

NCT07172165 | Enrolling By Invitation DMC

• 1 other identifier: MESOMEGA
• Study Type: observational
• Target: 850
• Locations: 1 country
• Sites: 1

Brief Summary

Microembolic signals (MES) is a powerful predictor of future embolic events. This study aims to develop and validate a accurate model of classification of MES obtained by transcranial Doppler. monitoring of However, MES detection is technically demanding and requires expert interpretation. By providing a reproducible framework for MES interpretation, this work aims to facilitate MES integration into future clinical trials and decision-making.

Conditions

Microemboli; Stroke; Transcranial Doppler Ultrasound

Keywords

microembolic signals (MES); decision tree; stroke; microemboli; transcranial Doppler; diagnostic standard; prediction model

Outcome Measures

Primary Outcomes (1)

• Classification of each signal as MES or Non-MES

  A MES or non-MES will be considered as such the two experts agree. If the two experts do not agree, a special board (RA, WM) will decide on classification. "Recordings that remain undetermined, or those classified as undetermined by both experts, will be excluded from the primary analysis of this study. All experts will be blinded to each other, any identification tag or clinical information. We will include five predictors in the primary analysis which are: the presence of characteristic audible signal increase, characteristic wave-like raw Doppler signals, the Emboli-to-Background Ratio (EBR), Emboli-to-mirror-ratio (EMR), time length and average velocity of maximum intensity. The calculation and definition of each predictor is detailed in table 3 and in supplemental information (Proposal for a systematic analysis and reporting of microembolic signal detection of the Microembolic Signal Detection Working Groups of the World Organization of Neurosonology).

  From enrollment until December of 2026

Secondary Outcomes (4)

• Trimmed version of the model

  From enrollment until December of 2026

• Model with extra-features

  From enrollment until December of 2026

• Inter-expert variability in feature extraction.

  From enrollment until December of 2026

• Delphi process

  From enrollment until December of 2026

Study Arms (1)

Transcranial Doppler clips database

Clips of MES and non-MES events. Each clip will be 20 seconds (-10 and +10 seconds in reference to the marked event). The data presented will not be modified from its original form. The final database that will be used for expert evaluation will include the necessary clips and proportions to ensure maximum reproducibility and generalization of the data. Clips will be obtained from at least 3 different types or brands of TCD machines. A single machine cannot be the source of more than 50% of the final data set. MES will be from a variety of sources including patients with atherosclerotic disease, cardioembolic stroke, or embolic stroke of unknown source.

Diagnostic Test: Expert double-blind evaluation

Interventions

Expert double-blind evaluation DIAGNOSTIC_TEST

Expert reading will be using TCDPlayer and will be blinded to clinical data, source information, and other assessments. They will manually annotate six predefined signal features: characteristic audible signal increase, characteristic wave-like of raw Doppler signals, Emboli-to-Background Ratio, Emboli-to-Mirror Ratio, signal duration, and average velocity of maximum intensity. Analysis will be completed within 90 days.

Transcranial Doppler clips database

Eligibility Criteria

• Age: 18 Years+
• Sex: all
• Healthy Volunteers: No
• Age Groups: Adult (18-64), Older Adult (65+)
• Sampling Method: Probability Sample

Study Population

Clips of Transcranial Doppler monitoring either MES or non-MES high intensity transient signals (e.g. artifacts, speckle).

You may qualify if:

• MES of presumed solid form or non-MES high intensity transient signals
• Obtained from on a human subject with age equal to or more than 18years old
• Obtained from proximal middle cerebral artery (M1 segment)
• Clip with 20 seconds duration with clearly event of interest marked using TCDPlayer
• With an overall background spectrum of reasonable quality to be analyzed

You may not qualify if:

• MES in gaseous form
• Use of ultrasound contrast agent or agitated saline in the previous 24 hours
• Obtained from patients with mechanical valve
• Obtained from patient during any cardiac surgery or endovascular procedure1
• Obtained from patient with recent severe trauma
• Clips with multiples inseparable MES (e.g. curtain)

Sponsors & Collaborators

• Sound Vascular Neurology: collaborator
• RISE-Heatlh: collaborator
• CRU-RISE: collaborator
• University of Ostrava: collaborator
• Justus-Liebig University Gießen Medical Center: collaborator
• University of Bern: collaborator
• Centro Hospitalar De São João, E.P.E.: collaborator
• Houston Methodist DeBakey Heart & Vascular Center: collaborator
• Universidade do Porto: lead
• Maastricht University Medical Center: collaborator

Study Sites (1)

Faculty of Medicine University Porto

Porto, 4200-319, Portugal

Location

Related Publications (10)

• Collins GS, Moons KGM, Dhiman P, Riley RD, Beam AL, Van Calster B, Ghassemi M, Liu X, Reitsma JB, van Smeden M, Boulesteix AL, Camaradou JC, Celi LA, Denaxas S, Denniston AK, Glocker B, Golub RM, Harvey H, Heinze G, Hoffman MM, Kengne AP, Lam E, Lee N, Loder EW, Maier-Hein L, Mateen BA, McCradden MD, Oakden-Rayner L, Ordish J, Parnell R, Rose S, Singh K, Wynants L, Logullo P. TRIPOD+AI statement: updated guidance for reporting clinical prediction models that use regression or machine learning methods. BMJ. 2024 Apr 16;385:e078378. doi: 10.1136/bmj-2023-078378.

  PMID: 38626948 RESULT

• Riley RD, Ensor J, Snell KIE, Harrell FE Jr, Martin GP, Reitsma JB, Moons KGM, Collins G, van Smeden M. Calculating the sample size required for developing a clinical prediction model. BMJ. 2020 Mar 18;368:m441. doi: 10.1136/bmj.m441. No abstract available.

  PMID: 32188600 RESULT

• Wong KS, Chen C, Fu J, Chang HM, Suwanwela NC, Huang YN, Han Z, Tan KS, Ratanakorn D, Chollate P, Zhao Y, Koh A, Hao Q, Markus HS; CLAIR study investigators. Clopidogrel plus aspirin versus aspirin alone for reducing embolisation in patients with acute symptomatic cerebral or carotid artery stenosis (CLAIR study): a randomised, open-label, blinded-endpoint trial. Lancet Neurol. 2010 May;9(5):489-97. doi: 10.1016/S1474-4422(10)70060-0. Epub 2010 Mar 22.

  PMID: 20335070 RESULT

• Markus HS, Droste DW, Kaps M, Larrue V, Lees KR, Siebler M, Ringelstein EB. Dual antiplatelet therapy with clopidogrel and aspirin in symptomatic carotid stenosis evaluated using doppler embolic signal detection: the Clopidogrel and Aspirin for Reduction of Emboli in Symptomatic Carotid Stenosis (CARESS) trial. Circulation. 2005 May 3;111(17):2233-40. doi: 10.1161/01.CIR.0000163561.90680.1C. Epub 2005 Apr 25.

  PMID: 15851601 RESULT

• Castro P, Ferreira J, Malojcic B, Bazadona D, Baracchini C, Pieroni A, Skoloudik D, Azevedo E, Kaps M. Detection of microemboli in patients with acute ischaemic stroke and atrial fibrillation suggests poor functional outcome. Eur Stroke J. 2024 Jun;9(2):409-417. doi: 10.1177/23969873231220508. Epub 2023 Dec 27.

  PMID: 38149620 RESULT

• Das AS, Regenhardt RW, LaRose S, Monk AD, Castro PM, Sheriff FG, Sorond FA, Vaitkevicius H. Microembolic Signals Detected by Transcranial Doppler Predict Future Stroke and Poor Outcomes. J Neuroimaging. 2020 Nov;30(6):882-889. doi: 10.1111/jon.12749. Epub 2020 Jul 10.

  PMID: 32648610 RESULT

• Sheriff F, Diz-Lopes M, Khawaja A, Sorond F, Tan CO, Azevedo E, Franceschini MA, Vaitkevicius H, Li K, Monk AD, Michaud SL, Feske SK, Castro P. Microemboli After Successful Thrombectomy Do Not Affect Outcome but Predict New Embolic Events. Stroke. 2020 Jan;51(1):154-161. doi: 10.1161/STROKEAHA.119.025856. Epub 2019 Dec 4.

  PMID: 31795906 RESULT

• Padayachee TS, Parsons S, Theobold R, Linley J, Gosling RG, Deverall PB. The detection of microemboli in the middle cerebral artery during cardiopulmonary bypass: a transcranial Doppler ultrasound investigation using membrane and bubble oxygenators. Ann Thorac Surg. 1987 Sep;44(3):298-302. doi: 10.1016/s0003-4975(10)62077-2.

  PMID: 2957966 RESULT

• Farina F, Palmieri A, Favaretto S, Viaro F, Cester G, Causin F, Baracchini C. Prognostic Role of Microembolic Signals After Endovascular Treatment in Anterior Circulation Ischemic Stroke Patients. World Neurosurg. 2018 Feb;110:e882-e889. doi: 10.1016/j.wneu.2017.11.120. Epub 2017 Nov 28.

  PMID: 29191539 RESULT

• Spencer MP, Thomas GI, Nicholls SC, Sauvage LR. Detection of middle cerebral artery emboli during carotid endarterectomy using transcranial Doppler ultrasonography. Stroke. 1990 Mar;21(3):415-23. doi: 10.1161/01.str.21.3.415.

  PMID: 2408197 RESULT

MeSH Terms

Conditions

Stroke

Condition Hierarchy (Ancestors)

Cerebrovascular Disorders; Brain Diseases; Central Nervous System Diseases; Nervous System Diseases; Vascular Diseases; Cardiovascular Diseases

Study Design

• Study Type: observational
• Observational Model: COHORT
• Time Perspective: PROSPECTIVE
• Sponsor Type: OTHER
• Responsible Party: SPONSOR

Study Record Dates

• First Submitted: June 27, 2025
• First Posted: September 15, 2025
• Study Start: May 15, 2025
• Primary Completion: December 15, 2025
• Study Completion: March 15, 2026
• Last Updated: December 10, 2025

Record last verified: 2025-05

Data Sharing

• IPD Sharing: Will share
• Shared Documents: STUDY PROTOCOL, SAP, ICF, CSR, ANALYTIC CODE

Locations

PT (1)