CT texture analysis can help differentiate between malignant and benign lymph nodes in the mediastinum in patients suspected for lung cancer

Author:

Andersen Michael Brun1,Harders Stefan Walbom1,Ganeshan Balaji2,Thygesen Jesper1,Torp Madsen Hans Henrik1,Rasmussen Finn1

Affiliation:

1. Aarhus University Hospital, Department of Radiology, Aarhus, Denmark

2. University College Hospital, Institute of Nuclear Medicine, London, UK

Abstract

Background In patients with non-small-cell lung carcinoma NSCLC the lymph node staging in the mediastinum is important due to impact on management and prognosis. Computed tomography texture analysis (CTTA) is a postprocessing technique that can evaluate the heterogeneity of marked regions in images. Purpose To evaluate if CTTA can differentiate between malignant and benign lymph nodes in a cohort of patients with suspected lung cancer. Material and Methods With tissue sampling as reference standard, 46 lymph nodes from 29 patients were analyzed using CTTA. For each lymph node, CTTA was performed using a research software “TexRAD” by drawing a region of interest (ROI) on all available axial contrast-enhanced computed tomography (CT) slices covering the entire volume of the lymph node. Lymph node CTTA comprised image filtration-histogram analysis undertakes two stages: the first step comprised an application of a Laplacian of Gaussian filter to highlight fine to coarse textures within the ROI, followed by a quantification of textures via histogram analysis using mean gray-level intensity from the entire volume of the lymph nodes. Results CTTA demonstrated a statistically significant difference between the malignant and the benign lymph nodes ( P = 0.001), and by binary logistic regression we obtained a sensitivity of 53% and specificity of 97% in the test population. The area under the receiver operating curve was 83.4% and reproducibility was excellent. Conclusion CTTA may be helpful in differentiating between malignant and benign lymph nodes in the mediastinum in patients suspected for lung cancer, with a low intra-observer variance.

Publisher

SAGE Publications

Subject

Radiology, Nuclear Medicine and imaging,General Medicine,Radiological and Ultrasound Technology

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