Evidence map›Paper›PMID 36408780›Full record

ArticleThoracic cancer2023

Nondiagnostic, radial-probe endobronchial ultrasound-guided biopsy for peripheral lung lesions: The added value of radiomics from ultrasound imaging for predicting malignancy.

Jihwan Choi, Sungmin Zo, Jong Hoon Kim, You Jin Oh, Joong Hyun Ahn, Myoungkyoung Kim, Kyungjong Lee, Ho Yun Lee

Abstract read
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Article in Thoracic cancer, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

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0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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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

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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

3 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

8 authors.

Jihwan ChoiDepartment of Digital Health, SAIHST, Sungkyunkwan University, Seoul, South Korea.
Sungmin ZoDivision of Pulmonary and Critical Care Medicine, Department of Medicine, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, South Korea.
Jong Hoon KimIndustrial Biomaterial Research Center, Korea Research Institute of Bioscience and Biotechnology, Daejeon, South Korea.
You Jin OhDepartment of Health Sciences and Technology, SAIHST, Sungkyunkwan University, Seoul, South Korea.ORCID 0000-0002-2801-4100
Joong Hyun AhnBiomedical Statistics Center, Data Science Research Institute, Research Institute for Future Medicine, Samsung Medical Center.
Myoungkyoung KimDepartment of Radiology and Center for Imaging Science, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, South Korea.
Kyungjong LeeDivision of Pulmonary and Critical Care Medicine, Department of Medicine, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, South Korea.
Ho Yun LeeDepartment of Health Sciences and Technology, SAIHST, Sungkyunkwan University, Seoul, South Korea.ORCID 0000-0001-9960-5648

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectivesThis study investigated whether radiomic features extracted from radial-probe endobronchial ultrasound (radial EBUS) images can assist in decision-making for subsequent clinical management in cases with indeterminate pathologic results.

methodsA total of 494 patients who underwent radial EBUS biopsy for lung nodules between January 2017 and December 2018 were allocated to our training set. For the validation set, 229 patients with radial EBUS biopsy results from January 2019 to April 2020 were used. A multivariate logistic regression analysis was used for feature selection and prediction modeling.

resultsIn the training set, 157 (67 benign and 90 malignant) of 212 patients pathologically diagnosed as indeterminate were analyzed. In the validation set, 213 patients were diagnosed as indeterminate, and 158 patients (63 benign and 95 malignant) were included in the analysis. The performance of the radiomics-added model, which considered satellite nodules, linear arc, shape, patency of vessels and bronchi, echogenicity, spiculation, C-reactive protein, and minimum histogram, was 0.929 for the training set and 0.877 for the validation set, whereas the performance of the model without radiomics was 0.910 and 0.891, respectively.

conclusionAlthough the next diagnostic step for indeterminate lung biopsy results remains controversial, integrating various factors, including radiomic features from radial EBUS, might facilitate decision-making for subsequent clinical management.

Indexed as

Lung NeoplasmsBiopsyBronchiBronchoscopyHumansRetrospective StudiesUltrasonographyUltrasonography, Interventionalbronchoscopydiagnostic imaginglung neoplasmpathologyultrasound

Identifiers

PMID36408780
PMCPMC9834694

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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.