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Original Research: PULMONARY PROCEDURES |

Optical Differentiation Between Malignant and Benign Lymphadenopathy by Grey Scale Texture Analysis of Endobronchial Ultrasound Convex Probe ImagesGrey Scale Texture Analysis for Lymphadenopathy

Phan Nguyen, MBBS; Farzad Bashirzadeh, MBBS; Justin Hundloe, MBBS; Olivier Salvado, PhD; Nicholas Dowson, PhD; Robert Ware, PhD; Ian Brent Masters, MBBS, PhD; Manoj Bhatt, MBBS; Aravind Ravi Kumar, MBBS; David Fielding, MBBS, MD
Author and Funding Information

From the Department of Thoracic Medicine (Drs Nguyen, Bashirzadeh, Hundloe, and Fielding), The Royal Brisbane and Women’s Hospital; The University of Queensland, UQ Centre for Clinical Research (Dr Nguyen); Queensland PET Service (Drs Bhatt and Ravi Kumar); The Australian eHealth Research Centre (Drs Salvado and Dowson), CSIRO Information and Communication Technologies Centre; Queensland Children’s Medical Research Institute (Dr Ware); the Department of Respiratory Medicine (Dr Masters), The Royal Children’s Hospital, Herston; and School of Medicine (Drs Nguyen, Bashirzadeh, Hundloe, Fielding, Bhatt, Ravi Kumar and Masters), Faculty of Health Sciences, University of Queensland, St. Lucia, QLD, Australia.

Correspondence to: Phan Nguyen, MBBS, The University of Queensland, UQ Centre for Clinical Research, Herston, QLD, 4029; Australia, e-mail: phan.nguyen@internode.on.net


Funding/Support: The authors have reported to CHEST that no funding was received for this study.

Reproduction of this article is prohibited without written permission from the American College of Chest Physicians (http://www.chestpubs.org/site/misc/reprints.xhtml).


© 2012 American College of Chest Physicians


Chest. 2012;141(3):709-715. doi:10.1378/chest.11-1016
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Background:  Morphologic and sonographic features of endobronchial ultrasound (EBUS) convex probe images are helpful in predicting metastatic lymph nodes. Grey scale texture analysis is a well-established methodology that has been applied to ultrasound images in other fields of medicine. The aim of this study was to determine if this methodology could differentiate between benign and malignant lymphadenopathy of EBUS images.

Methods:  Lymph nodes from digital images of EBUS procedures were manually mapped to obtain a region of interest and were analyzed in a prediction set. The regions of interest were analyzed for the following grey scale texture features in MATLAB (version 7.8.0.347 [R2009a]): mean pixel value, difference between maximal and minimal pixel value, SEM pixel value, entropy, correlation, energy, and homogeneity. Significant grey scale texture features were used to assess a validation set compared with fluoro-D-glucose (FDG)-PET-CT scan findings where available.

Results:  Fifty-two malignant nodes and 48 benign nodes were in the prediction set. Malignant nodes had a greater difference in the maximal and minimal pixel values, SEM pixel value, entropy, and correlation, and a lower energy (P < .0001 for all values). Fifty-one lymph nodes were in the validation set; 44 of 51 (86.3%) were classified correctly. Eighteen of these lymph nodes also had FDG-PET-CT scan assessment, which correctly classified 14 of 18 nodes (77.8%), compared with grey scale texture analysis, which correctly classified 16 of 18 nodes (88.9%).

Conclusions:  Grey scale texture analysis of EBUS convex probe images can be used to differentiate malignant and benign lymphadenopathy. Preliminary results are comparable to FDG-PET-CT scan.

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