Bo-Wei Chen1, Li-Wei Chen1, Shun-Mao Yang1,2, Ching-Kai Lin3, Huan-Jang Ko2, Chung-Ming Chen1. 1. Institute of Biomedical Engineering, College of Medicine and College of Engineering, National Taiwan University, Taipei, Taiwan. 2. Department of Surgery, National Taiwan University Hospital, Hsin-Chu Branch, Taiwan. 3. Department of Internal Medicine, National Taiwan University Hospital, Taipei, Taiwan.
Abstract
BACKGROUND: Transbronchial dye marking is a preoperative localization technique aiding pulmonary resection. Post-marking computed tomography (CT) is performed to confirm the locations of the actual markings. This study aimed to evaluate the CT images of dye markings that present as ground-glass opacities (GGO), using quantitative feature analysis. METHODS: Thin-slice (1 mm) CT images of the dye markings and true ground glass nodule (GGN) lesions were obtained for quantitative analysis with gray-level co-occurrence matrix (GLCM) features. The quantification features including correlation, auto correlation, contrast, energy, entropy, and homogeneity were evaluated. Statistical analysis with boxplot was performed. RESULTS: GLCM features of multi-detector computed tomography (MDCT) images of the dye markings (n=13) and true GGN lesions (n=13) differed significantly in contrast, energy, entropy, auto correlation, and homogeneity. Cone beam computed tomographic (CBCT) image features of another group of dye markings (n=15) also showed a different distribution of feature values, than those of the MDCT images. CONCLUSIONS: Quantitative analysis of the dye marking images revealed a discriminative variance, compared with those of the true GGN lesions. Furthermore, the image textures of dye markings on MDCT and CBCT also presented with obvious discrepancies.
BACKGROUND: Transbronchial dye marking is a preoperative localization technique aiding pulmonary resection. Post-marking computed tomography (CT) is performed to confirm the locations of the actual markings. This study aimed to evaluate the CT images of dye markings that present as ground-glass opacities (GGO), using quantitative feature analysis. METHODS: Thin-slice (1 mm) CT images of the dye markings and true ground glass nodule (GGN) lesions were obtained for quantitative analysis with gray-level co-occurrence matrix (GLCM) features. The quantification features including correlation, auto correlation, contrast, energy, entropy, and homogeneity were evaluated. Statistical analysis with boxplot was performed. RESULTS: GLCM features of multi-detector computed tomography (MDCT) images of the dye markings (n=13) and true GGN lesions (n=13) differed significantly in contrast, energy, entropy, auto correlation, and homogeneity. Cone beam computed tomographic (CBCT) image features of another group of dye markings (n=15) also showed a different distribution of feature values, than those of the MDCT images. CONCLUSIONS: Quantitative analysis of the dye marking images revealed a discriminative variance, compared with those of the true GGN lesions. Furthermore, the image textures of dye markings on MDCT and CBCT also presented with obvious discrepancies.
Authors: Roy A Raad; James Suh; Saul Harari; David P Naidich; Maria Shiau; Jane P Ko Journal: Radiol Clin North Am Date: 2013-10-06 Impact factor: 2.303
Authors: Xenia Fave; Dennis Mackin; Jinzhong Yang; Joy Zhang; David Fried; Peter Balter; David Followill; Daniel Gomez; A Kyle Jones; Francesco Stingo; Jonas Fontenot; Laurence Court Journal: Med Phys Date: 2015-12 Impact factor: 4.071