Evidence map›Paper›PMID 33398925›Full record

ArticleThoracic cancer2021

Electromagnetic navigation bronchoscopic localization versus percutaneous CT-guided localization for thoracoscopic resection of small pulmonary nodules.

Yan-Long Yang, Zi-Zhe Li, Wei-Chao Huang, Jia Zhuang, Dai-Ying Lin, Wen-Zhao Zhong, Bin Lan

Open access · goldAbstract read
In one paragraph

Article in Thoracic cancer, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 32 papers.

0numbers the graph read from it
0cells of the map it votes in
32citing papers in PubMed
4.4field-weighted citation impact, top 5% 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

32 citing papers in PubMed, 37 citations in OpenAlex.

  1. Review
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Review
  10. Article
  11. Article
  12. Review
  13. Article
  14. Article
  15. Review
  16. Article
  17. Article
  18. Article
  19. Article
  20. Application value of CT-guided localization using a coil in combination with medical adhesive in sublobar resection.Clinical & translational oncology : official publication of the Federation of Spanish Oncology Societies and of the National Cancer Institute of Mexico · 2023
    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

7 authors at 2 institutions in 1 country.

Yan-Long YangShantou Central Hospital, Shantou, China.
Zi-Zhe LiShantou Central Hospital, Shantou, China.
Wei-Chao HuangShantou Central Hospital, Shantou, China.
Jia ZhuangShantou Central Hospital, Shantou, China.
Dai-Ying LinShantou Central Hospital, Shantou, China.
Wen-Zhao ZhongGuangdong Provincial People's Hospital & Guangdong Academy of Medical Sciences, Guangzhou, China.ORCID 0000-0002-8917-8635
Bin LanShantou Central Hospital, Shantou, China.ORCID 0000-0003-3121-7643
Shantou Central Hospital · CNGuangdong Academy of Medical Sciences · CN

Funding

Shantou Science and Technology Planning Project Shanfuke [2017] 166-10
6 · The paper itself

Abstract

backgroundIdentification of small pulmonary nodules is challenging in a limited intrathoracic field during minimally invasive video-assisted thoracoscopic surgery (VATS), and preoperative localization is required. Various techniques have been reported with some failure and complications. Here, we compare the feasibility and safety between electromagnetic navigation bronchoscopic marking and computed tomography (CT)-guided percutaneous marking using indocyanine green (ICG) and iopamidol.

methodsA total of 47 patients with small-sized pulmonary nodules, scheduled to undergo video-assisted thoracoscopic limited resection, were enrolled in this study. A mixture of diluted ICG and iopamidol was injected into the lung parenchyma as a marker, using CT-guided percutaneous or electromagnetic navigation bronchoscopic injection techniques and the results were examined and compared.

resultsA total of 35 and 12 patients underwent preoperative marking by percutaneous injection and electromagnetic navigation bronchoscopic injection, respectively, in which a marker was detected in 33/35 (94.3%) and 12/12 (100%) patients. No combination of these procedures was performed in any patient. All markers were successfully detected in three patients who underwent injection marking at two different lesion sites. Pneumothorax occurred in five patients (14%) in the percutaneous marking group, which was relieved in all patients without the necessity for chest tube drainage. No other complication was observed in this study.

conclusionsElectromagnetic navigation bronchoscopic injection techniques using indocyanine green fluorescence plus iopamidol are safe and effective, and comparable with CT-guided localization. Furthermore, a bronchoscopic approach enables marking of multiple lesion areas without increasing patient risk, especially for puncture-related pneumothorax. KEY POINTS: SIGNIFICANT FINDINGS OF THE STUDY: Either computed tomography (CT)-guided percutaneous or electromagnetic navigation bronchoscopic injection techniques can be used for preoperative marking of pulmonary nodules with indocyanine green (ICG) fluorescence. WHAT THIS STUDY ADDS: Indocyanine green (ICG) is a safe and easily detectable fluorescent marker for video-assisted thoracoscopic surgery (VATS). A bronchoscopic injection approach enables marking of multiple lesion areas without increasing the risk of pneumothorax.

Indexed as

AdultAgedBronchoscopyFemaleHumansMaleMiddle AgedMultiple Pulmonary NodulesThoracic Surgery, Video-AssistedThoracoscopyTomography, X-Ray ComputedCT-guided percutaneous localizationelectromagnetic navigation bronchoscopyindocyanine green fluorescence (ICG)small pulmonary nodulesvideo-assisted thoracoscopic surgery (VATS)

Identifiers

PMID33398925
PMCPMC7882377
OpenAlexW3118891706

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.