Evidence map›Paper›PMID 35832440›Full record

ArticleTranslational lung cancer research2022

Partitioning the lung field based on the depth ratio in three-dimensional space.

Jingjing Huang, Chengyu Bian, Wenhao Zhang, Guang Mu, Zhipeng Chen, Yang Xia, Mei Yuan, Hideki Ujiie, Jean H T Daemen, Erik R de Loos and 4 more

Open access · diamondAbstract read
In one paragraph

Article in Translational lung cancer research, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed
2.0field-weighted citation impact, top 13% 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, 16 citations in OpenAlex.

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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

14 authors at 4 institutions in 3 countries.

Jingjing Huang *Department of Thoracic Surgery, Jiangsu Province Hospital and The First Affiliated Hospital of Nanjing Medical University, Nanjing, China.
Chengyu Bian *Department of Thoracic Surgery, Jiangsu Province Hospital and The First Affiliated Hospital of Nanjing Medical University, Nanjing, China.
Wenhao ZhangDepartment of Thoracic Surgery, Jiangsu Province Hospital and The First Affiliated Hospital of Nanjing Medical University, Nanjing, China.
Guang MuDepartment of Thoracic Surgery, Jiangsu Province Hospital and The First Affiliated Hospital of Nanjing Medical University, Nanjing, China.
Zhipeng ChenDepartment of Thoracic Surgery, Jiangsu Province Hospital and The First Affiliated Hospital of Nanjing Medical University, Nanjing, China.
Yang XiaDepartment of Thoracic Surgery, Jiangsu Province Hospital and The First Affiliated Hospital of Nanjing Medical University, Nanjing, China.
Mei YuanDepartment of Radiology, Jiangsu Province Hospital and The First Affiliated Hospital of Nanjing Medical University, Nanjing, China.
Hideki UjiieDepartment of Cardiovascular and Thoracic Surgery, Hokkaido University, Hokkaido, Japan.
Jean H T DaemenDepartment of Surgery, Division of General Thoracic Surgery, Zuyderland Medical Center, Heerlen, The Netherlands.
Erik R de LoosDepartment of Surgery, Division of General Thoracic Surgery, Zuyderland Medical Center, Heerlen, The Netherlands.
Quan ZhuDepartment of Thoracic Surgery, Jiangsu Province Hospital and The First Affiliated Hospital of Nanjing Medical University, Nanjing, China.
Weibing WuDepartment of Thoracic Surgery, Jiangsu Province Hospital and The First Affiliated Hospital of Nanjing Medical University, Nanjing, China.
Liang ChenDepartment of Thoracic Surgery, Jiangsu Province Hospital and The First Affiliated Hospital of Nanjing Medical University, Nanjing, China.
Jun WangDepartment of Thoracic Surgery, Jiangsu Province Hospital and The First Affiliated Hospital of Nanjing Medical University, Nanjing, China.
Nanjing Medical University · CNJiangsu Province Hospital · CNZuyderland Medisch Centrum · NLHokkaido University · JP

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: To explore the feasibility of the depth ratio method partitioning the lung parenchyma and the depth distribution of lung nodules in pulmonary segmentectomy. Methods: Based on the measurement units, patients were allocated to the chest group, the lobar group, and the symmetrical 3 sectors group. In each unit, the center of the respective bronchial cross-section was set as the starting point (O). Connecting the O point with the center of the lesion (A) and extending to the endpoint (B) on the pleural, the radial line (OB) was trisected to divide the outer, middle, and inner regions. The depth ratio and relevant regional distribution were simultaneously verified using 2-dimensional (2D) coronal, sagittal, and axial computed tomography images and 3-dimensional (3D) reconstruction images. Results: Two hundred and nine patients were included in this study. The median age was 53 (IQR, 44.5-62) years and 64 were males. The intra-group consistency of the depth ratio region partition was 100%. The consistency of the inter-group region partition differed among the three groups (Kappa values 0.511, 0.517, and 0.923). The chest group, lobar group, and symmetrical 3 sectors group had 69.4%, 26.3%, and 4.8% mediastinum disturbance, respectively (P<0.001). Conclusions: The depth ratio method in the symmetrical 3 sectors of the lung maximally eliminated the disturbance of the mediastinal structures and more accurately trisected the lung parenchymal in 3D space. Sublobar resection based on subsegments strategy is feasible for outer 2/3 pulmonary nodules when depth ratio is used as the measurement method.

Indexed as

3-dimensional partitionDepth ratiolung parenchyma

Identifiers

PMID35832440
PMCPMC9271427
OpenAlexW4283706998

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LicenceCC BY-NC-ND
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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.