Evidence map›Paper›PMID 42389638›Full record

ReviewFrontiers in cardiovascular medicine2026

Multimodal echocardiographic techniques in the diagnosis of cardiac tumors: applications and recent advances.

Yuan Li, Yujian Liu

Abstract readReview
In one paragraph

Review in Frontiers in cardiovascular medicine, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

2 authors.

Yuan LiDepartment of Ultrasound, Zigong Fourth People's Hospital, Zigong, Sichuan, China.
Yujian LiuDepartment of Radiology, Zigong First People's Hospital, Zigong, Sichuan, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Cardiac tumors are exceedingly rare and exhibit marked pathological heterogeneity. Early clinical manifestations are often nonspecific and easily confused with intracardiac thrombi or inflammatory vegetations, posing substantial challenges for timely recognition and clinical management. Imaging plays a pivotal role in both diagnosis and differential diagnosis. Among the available modalities, echocardiography is widely used as the initial evaluation tool due to its noninvasiveness, real-time capability, and repeatability. However, conventional two-dimensional echocardiography is limited by acoustic windows, spatial resolution, and operator dependency, resulting in suboptimal accuracy in assessing tumor vascularity, attachment sites, and benign-malignant differentiation. Recent advances in three-dimensional echocardiography, transesophageal echocardiography (TEE), contrast-enhanced ultrasound (CEUS), and speckle-tracking echocardiography (STE) have enabled a more comprehensive assessment of structural, perfusion, and functional characteristics. These multimodal approaches have demonstrated superior diagnostic performance over traditional 2D imaging in several studies. Despite the promising outlook, current research still faces significant limitations, including nonstandardized imaging and contrast parameters, insufficient cross-vendor consistency of quantitative indices, a lack of externally validated diagnostic thresholds, and a paucity of high-quality, prospective multicenter evidence. This review systematically summarizes the progress of multimodal echocardiography in cardiac tumor diagnosis over the past decade, evaluates the strengths and limitations of each modality, explores the emerging roles of artificial intelligence (AI) and radiomics in quantitative assessment, and proposes future strategies for standardization, intelligent analysis, and cross-modality integration.

Indexed as

artificial intelligencecardiac tumorscontrast-enhanced ultrasoundmultimodal echocardiographyspeckle-tracking echocardiographythree-dimensional transesophageal echocardiography

Identifiers

PMID42389638
PMCPMC13318695

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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.