Evidence map›Paper›PMID 40245059›Full record

ArticlePloS one2025

CT features and histogram analysis of non-contrast images for differentiating malignant and benign mediastinal lymph nodes in Non-Small Cell Lung Cancer (NSCLC).

Pakorn Prakaikietikul, Yutthaphan Wannasopha, Juntima Euathrongchit, Apichat Tantraworasin

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Article in PloS one, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

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2citing papers in PubMed
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1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

4 authors.

Pakorn PrakaikietikulDepartment of Radiology, Faculty of Medicine, Chiang Mai University, Chiang Mai, Thailand.
Yutthaphan WannasophaDepartment of Radiology, Faculty of Medicine, Chiang Mai University, Chiang Mai, Thailand.ORCID 0000-0002-6727-0828
Juntima EuathrongchitDepartment of Radiology, Faculty of Medicine, Chiang Mai University, Chiang Mai, Thailand.
Apichat TantraworasinClinical Epidemiology and Clinical Statistic Center, Faculty of Medicine, Chiang Mai University, Chiang Mai, Thailand.ORCID 0000-0002-7913-2799

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveTo evaluate the diagnostic value of CT features and histogram analysis in distinguishing between malignant and benign mediastinal lymph nodes in patients with non-small cell lung cancer (NSCLC).

methodThis retrospective study analyzed non-contrast chest CT images from 40 NSCLC patients, comprising 80 pathology-proven mediastinal lymph nodes (46 benign, 34 metastasis). Morphologic features, including size, shape, margins, and internal composition, were independently assessed by two radiologists. Histogram analysis was conducted using the Synapse Vincent system with six parameters: mean attenuation, mean positive pixel (MPP), standard deviation (SD), skewness, kurtosis, and entropy. Statistical analysis included the Mann-Whitney test for continuous data, Fisher's exact test for categorical data, and receiver-operating characteristic (ROC) curve analysis to assess diagnostic accuracy, with statistical significance set at p < 0.05.

resultsMalignant lymph nodes demonstrated significantly larger sizes (p < 0.001), ill-defined margins (p = 0.024), irregular shapes (p < 0.001), and the presence of necrotic areas (p < 0.001). A nodal size cutoff of 13.0 mm and volume of 1.632 ml were strongly associated with malignancy, yielding high diagnostic accuracy with sensitivities of 70.6% and 73.5% and specificities of 95.7% and 87.0%, respectively. Significant differences were observed between benign and malignant lymph nodes in several CT histogram parameters, including mean attenuation (p = 0.004), skewness (p = 0.041), kurtosis (p = 0.005), and entropy (p < 0.001). The integrating all CT histogram parameters yielded an area under the curve (AUC) of 0.870 for differentiating between benign and malignant lymph nodes.

conclusionThe combination of morphologic CT features and CT histogram analysis offers a robust method for differentiating malignant from benign mediastinal lymph nodes in NSCLC patients, potentially enhancing diagnostic accuracy and informing treatment strategies.

Indexed as

Carcinoma, Non-Small-Cell LungLung NeoplasmsLymph NodesMediastinumTomography, X-Ray ComputedAdultAgedAged, 80 and overDiagnosis, DifferentialFemaleHumansLymphatic MetastasisMaleMiddle AgedRetrospective StudiesROC Curve

Identifiers

PMID40245059
PMCPMC12005500

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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.