Evidence map›Paper›PMID 31879414›Full record

ArticleMedical science monitor : international medical journal of experimental and clinical research2019

Comparison of Real-Time Two-Dimensional and Three-Dimensional Contrast-Enhanced Ultrasound to Quantify Flow in an In Vitro Model: A Feasibility Study.

Si-Min Ruan, Qiao Zheng, Zhu Wang, Hang-Tong Hu, Li-Da Chen, Huan-Ling Guo, Xiao-Yan Xie, Ming-De Lu, Wei Li, Wei Wang

Abstract read
In one paragraph

Article in Medical science monitor : international medical journal of experimental and clinical research, 2019. 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. Trial
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

10 authors.

Si-Min RuanDepartment of Medical Ultrasonics, Ultrasonics Artificial Intelligence X-Lab, Institute of Diagnostic and Interventional Ultrasound, The First Affiliated Hospital of Sun Yat-sen University, Guangzhou, Guangdong, China (mainland).
Qiao ZhengDepartment of Medical Ultrasonics, Fetal Medical Center, The First Affiliated Hospital of Sun Yat-sen University, Guangzhou, Guangdong, China (mainland).
Zhu WangDepartment of Medical Ultrasonics, Ultrasonics Artificial Intelligence X-Lab, Institute of Diagnostic and Interventional Ultrasound, The First Affiliated Hospital of Sun Yat-sen University, Guangzhou, Guangdong, China (mainland).
Hang-Tong HuDepartment of Medical Ultrasonics, Ultrasonics Artificial Intelligence X-Lab, Institute of Diagnostic and Interventional Ultrasound, The First Affiliated Hospital of Sun Yat-sen University, Guangzhou, Guangdong, China (mainland).
Li-Da ChenDepartment of Medical Ultrasonics, Ultrasonics Artificial Intelligence X-Lab, Institute of Diagnostic and Interventional Ultrasound, The First Affiliated Hospital of Sun Yat-sen University, Guangzhou, Guangdong, China (mainland).
Huan-Ling GuoDepartment of Medical Ultrasonics, Ultrasonics Artificial Intelligence X-Lab, Institute of Diagnostic and Interventional Ultrasound, The First Affiliated Hospital of Sun Yat-sen University, Guangzhou, Guangdong, China (mainland).
Xiao-Yan XieDepartment of Medical Ultrasonics, Ultrasonics Artificial Intelligence X-Lab, Institute of Diagnostic and Interventional Ultrasound, The First Affiliated Hospital of Sun Yat-sen University, Guangzhou, Guangdong, China (mainland).
Ming-De LuDepartment of Medical Ultrasonics, Ultrasonics Artificial Intelligence X-Lab, Institute of Diagnostic and Interventional Ultrasound, The First Affiliated Hospital of Sun Yat-sen University, Guangzhou, Guangdong, China (mainland).
Wei LiDepartment of Medical Ultrasonics, Ultrasonics Artificial Intelligence X-Lab, Institute of Diagnostic and Interventional Ultrasound, The First Affiliated Hospital of Sun Yat-sen University, Guangzhou, Guangdong, China (mainland).
Wei WangDepartment of Medical Ultrasonics, Ultrasonics Artificial Intelligence X-Lab, Institute of Diagnostic and Interventional Ultrasound, The First Affiliated Hospital of Sun Yat-sen University, Guangzhou, Guangdong, China (mainland).

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

BACKGROUND This feasibility study aimed to compare real-time two-dimensional contrast-enhanced ultrasound (2D-CEUS) and three-dimensional contrast-enhanced ultrasound (3D-CEUS) to quantify flow in an in vitro model. MATERIAL AND METHODS Five polyvinyl chloride (PVC) tubes were used for the perfusion models and used SonoVue ultrasound contrast agent with a perfusion volume ratio of 1: 2: 4: 8: 16. The contrast was injected at a constant speed to compare the raw quantitative data of 2D-CEUS and 3D-CEUS at angles of 0°, 45°, and 90°. The coefficient of variation (CV) of the peak intensity (PI) in the model were compared and the correlations between weighted PI and perfusion volume were analyzed. RESULTS In the three angles used, real-time 3D-CEUS resulted in a more comprehensive view of the spatial relationships in the perfusion model. Using real-time 2D-CEUS, the mean CV was 0.92±0.36, and the mean CV in the real-time 3D-CEUS model was significantly less at 0.48±0.32 (p<0.001). Quantitative 3D-CEUS parameters showed a good correlation with those of 2D-CEUS with an r-value of 0.93 (p=0.02). The r-value of weighted PI and the perfusion ratio using 2D-CEUS was 0.66 (p=0.23) compared with values in 3D-CEUS of 0.84 (p=0.08). CONCLUSIONS The combination of real-time 3D-CEUS and quantitative analysis identified the spatial distribution of the changes in angle in the model, which was less influenced by sectional planes, and was more representative of the perfusion volume when compared with 2D-CEUS. Quantitative real-time 3D-CEUS requires in vivo studies to evaluate the potential role in the clinical evaluation of vascular perfusion of malignant tumors.

Indexed as

Contrast MediaFeasibility StudiesFlow Injection AnalysisImage EnhancementImage Interpretation, Computer-AssistedImaging, Three-DimensionalModels, AnatomicModels, StructuralPerfusionPerfusion ImagingPhospholipidsSulfur HexafluorideUltrasonographycontrast agent BR1Contrast MediaPhospholipidsSulfur Hexafluoride

Identifiers

PMID31879414
PMCPMC6946046

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LicenceCC BY-NC-ND
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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.