Evidence map›Paper›PMID 39835558›Full record

ReviewCurrent medical imaging2025

Artificial Intelligence in Transcranial Doppler Ultrasonography.

Antonio Siniscalchi, Vincenzo Inghingolo, Piergiorgio Lochner, Giovanni Malferrari

Abstract readReview
PubMed Full text at PMC Publisher
In one paragraph

Review in Current medical imaging, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Transcranial Ultrasound in the Helicopter Emergency Medical Services-A Feasibility Study.Journal of neuroimaging : official journal of the American Society of Neuroimaging
    Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Antonio SiniscalchiDepartment of Neurology and Stroke Unit, Azienda Ospedaliera di Cosenza, Italy.
Vincenzo InghingoloNeurology Unit and Stroke Unit, Department of Medicine, Casa Sollievo della Sofferenza, Italy.
Piergiorgio LochnerDepartment of Neurology and Stroke Unit, Universitätsklinikum des Saarlandes, Germany.
Giovanni MalferrariUOC Neurologia e Rete Stroke Metropolitana, Istituto delle Scienze Neurologiche di Bologna, Italy.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Transcranial Doppler is an instrumental ultrasound method capable of providing data on various brain pathologies, in particular, the study of cerebral hemodynamics in stroke, quickly, economically, and with repeatability of the data themselves. However, literature reviews from clinical studies and clinical trials reported that it is an operator-dependent method, and the data can be influenced by external factors, such as noise, which may require greater standardization of the parameters. Artificial intelligence can be utilized on transcranial Doppler to increase the accuracy and precision of the data collected while decreasing operator dependencies. In a time-dependent pathology, such as stroke, characterized by hemodynamic evolution, the use of artificial intelligence in transcranial Doppler ultrasound could represent beneficial support for better diagnosis and treatment in time-dependent pathologies, such as stroke.

Indexed as

Artificial IntelligenceStrokeUltrasonography, Doppler, TranscranialCerebrovascular CirculationHumansAntificial intelligenceCerebral hemodynamics.NeurosonologyTranscranial dopplerTranscranial duplex code color

Identifiers

PMID39835558
PMCPMC12776565

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.