Evidence map›Paper›PMID 36795007›Full record

ArticleRadiology and oncology2023

Multimodality CT imaging contributes to improving the diagnostic accuracy of solitary pulmonary nodules: a multi-institutional and prospective study.

Gaowu Yan, Hongwei Li, Xiaoping Fan, Jiantao Deng, Jing Yan, Fei Qiao, Gaowen Yan, Tao Liu, Jiankang Chen, Lei Wang and 7 more

Open access · goldAbstract readMulticenter Study
In one paragraph

Article in Radiology and oncology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
0.8field-weighted citation impact, top 31% 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

4 citing papers in PubMed, 4 citations in OpenAlex.

  1. Article
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  4. 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

17 authors at 5 institutions in 1 country.

Gaowu YanDepartment of Radiology, Suining Central Hospital, Suining, China.
Hongwei LiDepartment of Radiology, The Third Hospital of Mianyang and Sichuan Mental Health Center, Mianyang, China.
Xiaoping FanDepartment of Radiology, Suining Central Hospital, Suining, China.
Jiantao DengDepartment of Radiology, Suining Central Hospital, Suining, China.
Jing YanDepartment of Radiology, Suining Central Hospital, Suining, China.
Fei QiaoDepartment of CT and MRI, The First Affiliated Hospital, Shihezi University School of Medicine, Shihezi, China.
Gaowen YanDepartment of Radiology, The First People's Hospital of Suining, Suining, China.
Tao LiuDepartment of Radiology, Suining Central Hospital, Suining, China.
Jiankang ChenDepartment of Radiology, Suining Central Hospital, Suining, China.
Lei WangDepartment of Radiology, Suining Central Hospital, Suining, China.
Yang YangDepartment of Radiology, Suining Central Hospital, Suining, China.
Yong LiDepartment of Radiology, Suining Central Hospital, Suining, China.
Linwei ZhaoDepartment of Radiology, Suining Central Hospital, Suining, China.
Anup BhetuwalSichuan Key Laboratory of Medical Imaging and Department of Radiology, Affiliated Hospital of North Sichuan Medical College, Nanchong, China.
Morgan A McClureDepartment of Radiology and Imaging; Institute of Rehabilitation and Development of Brain Function, The Second Clinical Medical College of North Sichuan Medical College Nanchong Central Hospital, Nanchong, China.
Na LiDepartment of Oncology, Suining Central Hospital, Suining, China.
Chen PengDepartment of Gastroenterology, The First People's Hospital of Suining, Suining, China.
Suizhou Central Hospital · CNMianyang Third People's Hospital · CNNorth Sichuan Medical University · CNShihezi University · CNFirst People's Hospital of Nanning · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundSolitary pulmonary nodules (SPNs) are one of the most common chest computed tomography (CT) abnormalities clinically. We aimed to investigate the value of non-contrast enhanced CT (NECT), contrast enhanced CT (CECT), CT perfusion imaging (CTPI), and dual- energy CT (DECT) used for differentiating benign and malignant SPNs with a multi-institutional and prospective study. PATIENTS AND

methodsPatients with 285 SPNs were scanned with NECT, CECT, CTPI and DECT. Differences between the benign and malignant SPNs on NECT, CECT, CTPI, and DECT used separately (NECT combined with CECT, DECT, and CTPI were methods of A, B, and C) or in combination (Method A + B, A + C, B + C, and A + B + C) were compared by receiver operating characteristic curve analysis.

resultsMultimodality CT imaging showed higher performances (sensitivities of 92.81% to 97.60%, specificities of 74.58% to 88.14%, and accuracies of 86.32% to 93.68%) than those of single modality CT imaging (sensitivities of 83.23% to 85.63%, specificities of 63.56% to 67.80%, and accuracies of 75.09% to 78.25%, all

conclusionsSPNs evaluated with multimodality CT imaging contributes to improving the diagnostic accuracy of benign and malignant SPNs. NECT helps to locate and evaluate the morphological characteristics of SPNs. CECT helps to evaluate the vascularity of SPNs. CTPI using parameter of permeability surface and DECT using parameter of normalized iodine concentration at the venous phase both are helpful for improving the diagnostic performance.

Indexed as

Solitary Pulmonary NoduleHumansProspective StudiesROC CurveTomography, X-Ray Computedcomputed tomography perfusion imagingcontrast-enhanced computed tomographydual-energy computed tomographynon-enhanced computed tomographysolitary pulmonary nodule

Identifiers

PMID36795007
PMCPMC10039475
OpenAlexW4321002281

What OpenQuestion holds

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LicenceCC BY-NC-ND
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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.