Evidence map›Paper›PMID 29150624›Full record

ArticleScientific reports2017

Semiquantative Visual Assessment of Sub-solid Pulmonary Nodules ≦3 cm in Differentiation of Lung Adenocarcinoma Spectrum.

Fu-Zong Wu, Po-An Chen, Carol C Wu, Pei-Lun Kuo, Shu-Ping Tsao, Chu-Chun Chien, En-Kuei Tang, Ming-Ting Wu

Abstract read
In one paragraph

Article in Scientific reports, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers.

0numbers the graph read from it
0cells of the map it votes in
23citing 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

23 citing papers in PubMed.

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  15. [Expert Consensus for Thermal Ablation of Pulmonary Subsolid Nodules (2021 Edition)].Zhongguo fei ai za zhi = Chinese journal of lung cancer · 2021
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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

8 authors.

Fu-Zong WuDepartment of Radiology, Kaohsiung Veterans General Hospital, Kaohsiung, Taiwan. cmvwu1029@gmail.com.
Po-An ChenDepartment of Radiology, Kaohsiung Veterans General Hospital, Kaohsiung, Taiwan.
Carol C WuDepartment of Radiology, University of Texas MD Anderson Cancer Center, Houston, TX, USA.
Pei-Lun KuoDepartment of Radiology, Kaohsiung Veterans General Hospital, Kaohsiung, Taiwan.
Shu-Ping TsaoDepartment of Radiology, Kaohsiung Veterans General Hospital, Kaohsiung, Taiwan.
Chu-Chun ChienDepartment of Pathology and Laboratory Medicine, Kaohsiung Veterans General Hospital, Kaohsiung, Taiwan.
En-Kuei TangDepartment of Surgery, Kaohsiung Veterans General Hospital, Kaohsiung, Taiwan.
Ming-Ting WuDepartment of Radiology, Kaohsiung Veterans General Hospital, Kaohsiung, Taiwan. wu.mingting@gmail.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

We aimed to analyze CT features of persistent subsolid nodules (SSN) ≦3 cm diagnosed pathologically as adenocarcinoma spectrum to investigate whether parameters enable distinction between invasive pulmonary adenocarcinomas (IPAs) and pre-invasive lesions. A total of 129 patients with 141 SSNs confirmed with surgically pathologic proof were retrospectively reviewed. Of 141 SSNs, there were 57 pure ground-glass nodules (GGNs), 22 heterogeneous GGNs, and 62 part-solid nodules. SSN subclassification showed a significant linear trend with invasive degree of the adenocarcinoma spectrum (pure GGNs 7%; heterogeneous GGNs 36.4%; part-solid nodules 85.5%, P for trend <0.0001). For IPA detection in 141 SSNs, a solid part of ≧3 mm was the most specificity (sensitivity, 76.9%; specificity, 94.7%), followed by air-bronchogram sign (sensitivity, 53.8%; specificity, 89.5%), SSN subclassification (sensitivity, 81.5%; specificity, 88.2%), and a lesion size ≧12 mm (sensitivity, 84.6%; specificity, 76.3%). For IPA detection in 79 pure or heterogeneous GGNs, the heterogeneous GGN sign was the most useful finding, with most specificity (sensitivity, 66.7%; specificity, 79.1%), followed by CT attenuation (HU) of ≧-493 (sensitivity, 75%; specificity, 74.6%) and a lesion size ≧10 mm (sensitivity, 83.3%; specificity, 70.1%). In conclusion, this simple combined visual and semiquantitative analysis of CT features helps distinguish IPAs from pre-invasive lesions.

Indexed as

Adenocarcinoma of LungDiagnosis, DifferentialFemaleHumansImage Processing, Computer-AssistedMaleMiddle AgedSolitary Pulmonary NoduleTomography, X-Ray Computed

Identifiers

PMID29150624
PMCPMC5694004

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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.