Evidence map›Paper›PMID 36389309›Full record

ArticleJournal of thoracic disease2022

Utility of high-frequency B-mode and contrast-enhanced ultrasound for the differential diagnosis of benign and malignant pleural diseases: a prospective study.

Hongwei Yang, Yuxin Zhang, Dongjun Wei, Wuxi Chen, Shiyu Zhang, Liantu He, Haixing Liao, Qing Tang, Jianhua Liu

Open access · diamondAbstract read
In one paragraph

Article in Journal of thoracic disease, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed, 1 pooled it
1.5field-weighted citation impact, top 16% of its field
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

9 citing papers in PubMed, 1 synthesis or guideline pooled it, 11 citations in OpenAlex.

  1. Pooled it
  2. Article
  3. Review
  4. Review
  5. Article
  6. Advanced imaging techniques and artificial intelligence in pleural diseases: a narrative review.European respiratory review : an official journal of the European Respiratory Society · 2025
    Review
  7. Review
  8. Review
  9. Imaging of pleural disease.Breathe (Sheffield, England) · 2024
    Review
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

9 authors at 4 institutions in 1 country.

Hongwei Yang *Department of Ultrasound, First Affiliated Hospital of Jinan University, Guangzhou, China.
Yuxin Zhang *Department of Ultrasound, First Affiliated Hospital of Guangzhou Medical University, Guangzhou, China.
Dongjun Wei *Department of Ultrasound, First Affiliated Hospital of Guangzhou Medical University, Guangzhou, China.
Wuxi ChenDepartment of Ultrasound, First Affiliated Hospital of Guangzhou Medical University, Guangzhou, China.
Shiyu ZhangDepartment of Ultrasound, First Affiliated Hospital of Guangzhou Medical University, Guangzhou, China.
Liantu HeDepartment of Ultrasound, First Affiliated Hospital of Guangzhou Medical University, Guangzhou, China.
Haixing Liao *Department of Ultrasound, First Affiliated Hospital of Guangzhou Medical University, Guangzhou, China.
Qing Tang *Department of Ultrasound, First Affiliated Hospital of Guangzhou Medical University, Guangzhou, China.
Jianhua Liu *Department of Medical Ultrasound, Guangzhou First People's Hospital, School of Medicine, South China University of Technology, Guangzhou, China.
First Affiliated Hospital of Guangzhou Medical University · CNGuangzhou Medical University · CNFirst Affiliated Hospital of Jinan University · CNGuangzhou First People's Hospital · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Pleural disease is a prevalent condition. As precision therapy advances, noninvasive imaging modalities play even more important roles in the evaluation of pleural diseases. This study investigated the diagnostic capabilities of high-frequency B-mode ultrasound (US) and contrast-enhanced US (CEUS) in terms of differentiating between benign and malignant pleural diseases. Methods: Patients with unexplained thickened pleurae were prospectively analyzed via transthoracic US. High-frequency B-mode US was used to derive the pleural thickness, morphology, and echogenicity. We analyzed the high-frequency CEUS data including the enhancement mode and time intensity curve (TIC). The cause of pleural thickening was confirmed by pleural biopsy and follow-up after the biopsy. We analyzed the differences in various ultrasonic features between the malignant and benign groups. Moreover, we plotted receiver operator curves (ROCs) and obtained the area under the curves, sensitivities, and specificities of all significant continuous variables. Multivariate logistic regression was used to assess the combined usefulness of multiple US indicators in terms of predicting malignant pleurae. Results: Thirty malignant and twenty benign thickened pleurae were finally diagnosed via pleural biopsy and at least six months of follow-up. The pleural morphology and enhancement modes significantly differed between the two groups (all P<0.05). The thickness derived from B-mode US and CEUS were significantly thicker in the malignant group (both P<0.05). Arrival time (AT) and the time to peak (TTP) of TIC were significantly shorter in the malignant group, whereas peak intensity and the area under the TIC were significantly higher in the malignant group (all P<0.05). The area under the ROC for pleural thickness derived from B-mode US was 0.819; pleural thickness derived from CEUS was 0.848; AT was 0.804; TTP was 0.750; peak intensity was 0.745; the area under the TIC was 0.743; and the combined various B-mode and CEUS parameter was 0.975. Conclusions: Pleural thickness, morphology, enhancement mode, and the TIC of high-frequency US aided the differentiation of benign from malignant pleural diseases. Combined analysis of US indicators further improved the diagnostic capability.

Indexed as

diagnostic capabilityhigh-frequency ultrasound (high-frequency US)Pleural disease

Identifiers

PMID36389309
PMCPMC9641343
OpenAlexW4307809094

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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.