Evidence map›Paper›PMID 39780173›Full record

ArticleRespiratory research2025

Dynamic EIT technology for real-time non-invasive monitoring of acute pulmonary embolism: a porcine model experiment.

Junyao Li, Mingxu Zhu, Yitong Guo, Weichen Li, Qing He, Yu Wang, Yuxuan Liu, Benyuan Liu, Yang Liu, Weice Wang and 2 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Respiratory research, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing 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

7 citing papers in PubMed.

  1. Observational
  2. Article
  3. New Insights into Cardiac Intensive Care.Reviews in cardiovascular medicine · 2026
    Review
  4. Article
  5. Review
  6. Article
  7. 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

12 authors.

Junyao Li *Shaanxi Provincial Key Laboratory of Bioelectromagnetic Detection and Intelligent Perception, Department of Biomedical Engineering, Air Force Medical University, Xi'an, 710032, China.
Mingxu Zhu *Shaanxi Provincial Key Laboratory of Bioelectromagnetic Detection and Intelligent Perception, Department of Biomedical Engineering, Air Force Medical University, Xi'an, 710032, China.
Yitong Guo *Shaanxi Provincial Key Laboratory of Bioelectromagnetic Detection and Intelligent Perception, Department of Biomedical Engineering, Air Force Medical University, Xi'an, 710032, China.
Weichen LiDepartment of Radiology, Functional and Molecular Imaging Key Lab of Shaanxi Province, Tangdu Hospital, Air Force Medical University, 569 Xinsi Road, Xi'an, Shaanxi, 710038, China.
Qing HeDepartment of Cardiovascular Surgery, Xijing Hospital, Xi'an, China.
Yu WangShaanxi Provincial Key Laboratory of Bioelectromagnetic Detection and Intelligent Perception, Department of Biomedical Engineering, Air Force Medical University, Xi'an, 710032, China.
Yuxuan LiuBiomedical Engineering, Department of Engineering, City University of Hong Kong, Kowloon, Hong Kong, China.
Benyuan LiuShaanxi Provincial Key Laboratory of Bioelectromagnetic Detection and Intelligent Perception, Department of Biomedical Engineering, Air Force Medical University, Xi'an, 710032, China.
Yang LiuDepartment of Cardiovascular Surgery, Xijing Hospital, Xi'an, China.
Weice WangShaanxi Provincial Key Laboratory of Bioelectromagnetic Detection and Intelligent Perception, Department of Biomedical Engineering, Air Force Medical University, Xi'an, 710032, China.
Zhenyu JiShaanxi Provincial Key Laboratory of Bioelectromagnetic Detection and Intelligent Perception, Department of Biomedical Engineering, Air Force Medical University, Xi'an, 710032, China. jizhenyu@fmmu.edu.cn.
Xuetao ShiShaanxi Provincial Key Laboratory of Bioelectromagnetic Detection and Intelligent Perception, Department of Biomedical Engineering, Air Force Medical University, Xi'an, 710032, China. shixuetao@fmmu.edu.cn.

Funding

National Natural Science Foundation of China-General Program 52477237the Key Basic Research Projects of the Basic Strengthening Plan of the Science and Technology Committee 2019-JCJQ-ZD-115-00-02the Key Research and Development Projects of the Science and Technology Committee 2022YFC2404803the National Natural Science Foundation of China under Grant No.52207008
6 · The paper itself

Abstract

backgroundAcute pulmonary embolism represents the third most prevalent cardiovascular pathology, following coronary heart disease and hypertension. Its untreated mortality rate is as high as 20-30%, which represents a significant threat to patient survival. In view of the current lack of real-time monitoring techniques for acute pulmonary embolism, this study primarily investigates the potential of the pulsatility electrical impedance tomography (EIT) technique for the detection and real-time monitoring of acute pulmonary embolism through the collection and imaging of the pulsatile signal of pulmonary blood flow.

methodsA before-and-after self-control experiment was conducted on anaesthetised domestic pigs (N = 12, 20.75 ± 2.56 kg). The changes in pulmonary perfusion caused by an acute pulmonary embolism (artificially induced) were monitored in real time using the pulsation method. This enabled the extraction of indicators such as Amplitude, Forward (Negative) Slope, and S

resultsThe perfusion alterations subsequent to embolism in the pulsatility method are highly concordant with those observed in the hypertonic saline method, as evidenced by the imaging and indicator data. In particular, the perfusion area on the side of the embolism is markedly diminished, and the absolute values of all perfusion indicators are significantly reduced. Among these, Amplitude (P < 0.001) and S

conclusionsThe EIT imaging method, which is based on the analysis of blood flow pulsation, has the potential to reflect in real time the changes in pulmonary blood flow that occur before and after an embolism. This provides a new avenue for the non-invasive real-time monitoring of patients with acute pulmonary embolism in a clinical setting.

Indexed as

Disease Models, AnimalElectric ImpedancePulmonary EmbolismAcute DiseaseAnimalsComputer SystemsLungPulmonary CirculationPulsatile FlowSwineTomographyAcute pulmonary embolismElectrical impedance tomographyPulmonary perfusionPulsatility methodV/Q

Identifiers

PMID39780173
PMCPMC11715541

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

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.