Phan Nguyen1, Farzad Bashirzadeh2, Justin Hundloe2, Olivier Salvado3, Nicholas Dowson3, Robert Ware4, Ian Brent Masters5, Manoj Bhatt6, Aravind Ravi Kumar6, David Fielding2. 1. Department of Thoracic Medicine, The Royal Brisbane and Women's Hospital, Herston, Australia; The University of Queensland, UQ Centre for Clinical Research, CSIRO Information and Communication Technologies Centre, The Royal Children's Hospital, Herston, Australia; School of Medicine, Faculty of Health Sciences, University of Queensland, St. Lucia, QLD, Australia. Electronic address: phan.nguyen@internode.on.net. 2. Department of Thoracic Medicine, The Royal Brisbane and Women's Hospital, Herston, Australia; School of Medicine, Faculty of Health Sciences, University of Queensland, St. Lucia, QLD, Australia. 3. The Australian eHealth Research Centre, CSIRO Information and Communication Technologies Centre, The Royal Children's Hospital, Herston, Australia. 4. Queensland Children's Medical Research Institute, The Royal Children's Hospital, Herston, Australia. 5. Department of Respiratory Medicine, The Royal Children's Hospital, Herston, Australia; School of Medicine, Faculty of Health Sciences, University of Queensland, St. Lucia, QLD, Australia. 6. Queensland PET Service, CSIRO Information and Communication Technologies Centre, The Royal Children's Hospital, Herston, Australia; School of Medicine, Faculty of Health Sciences, University of Queensland, St. Lucia, QLD, Australia.
Abstract
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.
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.
Authors: Xiaonan Zang; Rebecca Bascom; Christopher Gilbert; Jennifer Toth; William Higgins Journal: IEEE Trans Biomed Eng Date: 2015-10-26 Impact factor: 4.538
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