Evidence map›Paper›PMID 36479066›Full record

ArticleFrontiers in oncology2022

Anatomical variation analysis of left upper pulmonary blood vessels and bronchi based on three-dimensional reconstruction of chest CT.

Youjun Deng, Songhua Cai, Chujian Huang, Wenyi Liu, Longde Du, Chunguang Wang, Ran Jia, Shengcheng Lin, Xin Yu, Xiangyang Yu and 8 more

Open access · goldAbstract read
In one paragraph

Article in Frontiers in oncology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
11citing 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

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

  1. Pooled it
  2. Review
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  7. Review
  8. Anatomy of the lung revisited by 3D-CT imaging.Video-assisted thoracic surgery · 2023
    Article
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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

18 authors at 1 institution in 1 country.

Youjun DengNational Cancer Center, National Clinical Research Center for Cancer, Cancer Hospital & Shenzhen Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Shenzhen, China.
Songhua CaiNational Cancer Center, National Clinical Research Center for Cancer, Cancer Hospital & Shenzhen Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Shenzhen, China.
Chujian HuangNational Cancer Center, National Clinical Research Center for Cancer, Cancer Hospital & Shenzhen Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Shenzhen, China.
Wenyi LiuNational Cancer Center, National Clinical Research Center for Cancer, Cancer Hospital & Shenzhen Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Shenzhen, China.
Longde DuNational Cancer Center, National Clinical Research Center for Cancer, Cancer Hospital & Shenzhen Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Shenzhen, China.
Chunguang WangNational Cancer Center, National Clinical Research Center for Cancer, Cancer Hospital & Shenzhen Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Shenzhen, China.
Ran JiaNational Cancer Center, National Clinical Research Center for Cancer, Cancer Hospital & Shenzhen Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Shenzhen, China.
Shengcheng LinNational Cancer Center, National Clinical Research Center for Cancer, Cancer Hospital & Shenzhen Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Shenzhen, China.
Xin YuNational Cancer Center, National Clinical Research Center for Cancer, Cancer Hospital & Shenzhen Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Shenzhen, China.
Xiangyang YuNational Cancer Center, National Clinical Research Center for Cancer, Cancer Hospital & Shenzhen Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Shenzhen, China.
Yikun YangNational Cancer Center, National Clinical Research Center for Cancer, Cancer Hospital & Shenzhen Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Shenzhen, China.
Chenglin YangNational Cancer Center, National Clinical Research Center for Cancer, Cancer Hospital & Shenzhen Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Shenzhen, China.
Hongbo ZhaoNational Cancer Center, National Clinical Research Center for Cancer, Cancer Hospital & Shenzhen Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Shenzhen, China.
Zhe WangNational Cancer Center, National Clinical Research Center for Cancer, Cancer Hospital & Shenzhen Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Shenzhen, China.
Lixu WangNational Cancer Center, National Clinical Research Center for Cancer, Cancer Hospital & Shenzhen Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Shenzhen, China.
Kai MaNational Cancer Center, National Clinical Research Center for Cancer, Cancer Hospital & Shenzhen Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Shenzhen, China.
Zhentao YuNational Cancer Center, National Clinical Research Center for Cancer, Cancer Hospital & Shenzhen Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Shenzhen, China.
Xiaotong GuoNational Cancer Center, National Clinical Research Center for Cancer, Cancer Hospital & Shenzhen Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Shenzhen, China.
Chinese Academy of Medical Sciences & Peking Union Medical College · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: With its growing popularity and potential outcome, preoperative three-dimensional reconstruction of chest computed tomography (CT) has been widely used in video-assisted thoracic surgery (VATS) segmentectomy for treating non-small cell lung cancer (NSCLC). This study aimed to summarize the experience of anatomical variation analysis of left upper pulmonary blood vessels and bronchi based on the three-dimensional reconstruction of chest CT. Materials and methods: A total of 103 patients with early-stage NSCLC were chosen to undergo VATS segmentectomy based on preoperative three-dimensional reconstruction of chest CT in our institute from September 2019 to July 2022. Data such as clinical characteristics and variations in blood vessels and bronchi were reviewed in this study. Results: The branches of the left lingular pulmonary artery may mutate into the LS1 + 2 + 3. A1 + 2 has four subtypes. The distribution of variation is relatively balanced, and the most common variation is type I (35/103, 33.9%). Most lingular arteries originate from the oblique cleft side of the lingular bronchus (79/103,76.7%). Most V(1 + 2)c* are small developments (70/103, 68.0%). The venous return of the proper segment mainly depends on V(1 + 2)b + c. The variation in the left upper lobe bronchus is complex. The most common variant is the bifurcation type (type A to G, 92/103, 89.3%) and bifurcation type A (62/103, 60.2%). The posterior apical segment artery of the left upper lobe is not accompanied by its bronchus. Conclusions: The variation types of blood vessels and bronchus in the upper lobe of the left lung are complex. Preoperative CT-based three-dimensional reconstruction of pulmonary arteries, veins, and bronchi is of great significance. It can help understand the variations, accurately locate lesions before the surgery, and effectively plan surgeries.

Indexed as

anatomical variationCTNSCLCpulmonarysegmentectomythree-dimensionalVATS

Identifiers

PMID36479066
PMCPMC9720281
OpenAlexW4309745355

What OpenQuestion holds

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LicenceCC BY
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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.