Literature DB >> 28267528

Non-small cell lung cancer: Spectral computed tomography quantitative parameters for preoperative diagnosis of metastatic lymph nodes.

Fengfeng Yang1, Jie Dong2, Xiuting Wang1, Xiaojiao Fu1, Tong Zhang3.   

Abstract

OBJECTIVE: To investigate the application value of spectral computed tomography (CT)quantitative parameters for preoperative diagnosis of metastatic lymph nodes in patients with non-small cell lung cancer (NSLC).
METHODS: 84 patients with suspected lung cancer who underwent chest dual-phase enhanced scan with gemstone spectral CT imaging (GSI) mode were selected. GSI quantitative parameters including normalized iodine concentrations (NIC), water concentration, slope of the spectral Hounsfield unit curve (λHU) were measured. The two-sample t test was used to statistically compare these quantitative parameters. Receiver operating characteristic (ROC) curves were drawn to establish the optimal threshold values.
RESULTS: A total of 144 lymph nodes were included, with 48 metastatic lymph nodes and 96 non-metastatic lymph nodes. The slope of the spectral Hounsfeld unit curve (λHU) measured during both arterial and venous phases were signifcantly higher in metastatic than in benign lymph nodes (P<0.05). The area under the ROC curve (AUC=0.951) of λHU of the arterial phase (AP) was the largest. When the optimal threshold values of λHU was 2.75, the sensitivity, specificity, and overall accuracy in the diagnosis of metastatic lymph nodes were 88.2%, 88.4%, 87.0%, respectively.
CONCLUSION: Conventional CT diagnostic criteria established in accordance with size (lymph node maximal short axis diameter ≥10mm) as the basis for judging metastatic lymph node. In quantitative assessment using spectral CT imaging, quantitative parameters showed higher accuracy than qualitative assessment of conventional CT based on the size for preoperative diagnosis of metastatic lymph nodes.
Copyright © 2017 Elsevier B.V. All rights reserved.

Entities:  

Keywords:  Curve slope; Lymph node; Quantitative parameter; Spectral CT

Mesh:

Substances:

Year:  2017        PMID: 28267528     DOI: 10.1016/j.ejrad.2017.01.026

Source DB:  PubMed          Journal:  Eur J Radiol        ISSN: 0720-048X            Impact factor:   3.528


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