OBJECTIVES: To determine whether texture analysis of non-contrast enhanced computed tomography (CT) images in apparently disease-free areas of the liver is altered by the presence of extra- and intra-hepatic malignancy in colorectal cancer patients. MATERIALS AND METHODS: Hepatic attenuation and texture were assessed from non-contrast enhanced CT in three groups of colorectal cancer patients: (A) 15 controls with no malignancy; (B) nine patients with extra-hepatic malignancy but no liver involvement; (C) eight patients with hepatic metastases. Regions of interest were manually constructed only over apparently normal areas of liver tissue excluding major blood vessels and areas of intra-hepatic fat, which may otherwise alter CT texture irrespective of the presence of malignancy. Texture was analysed on unfiltered images and following band-pass image filtration to highlight image features at different spatial frequencies (fine: 2 pixels/1.68 mm in width, medium: 6 pixels/5.04 mm and coarse: 12 pixels/10.08 mm). The relative contributions made to the image by features at two different spatial frequencies were expressed as filter ratios (fine/medium, fine/coarse and medium/coarse). Texture was quantified as mean grey-level intensity, entropy and uniformity. RESULTS: Texture was not altered on unfiltered images whereas relative texture analysis following image filtration identified differences in fine to medium texture ratios in apparently disease-free areas of the liver in patients with hepatic metastases as compared to patients with no tumour (entropy, p=0.0257) and patients with extra-hepatic disease (uniformity, p=0.0143). CONCLUSIONS: Relative texture analysis of unenhanced hepatic CT can reveal changes in apparently disease-free areas of the liver that have previously required more complex perfusion measurements for detection.
OBJECTIVES: To determine whether texture analysis of non-contrast enhanced computed tomography (CT) images in apparently disease-free areas of the liver is altered by the presence of extra- and intra-hepatic malignancy in colorectal cancerpatients. MATERIALS AND METHODS: Hepatic attenuation and texture were assessed from non-contrast enhanced CT in three groups of colorectal cancerpatients: (A) 15 controls with no malignancy; (B) nine patients with extra-hepatic malignancy but no liver involvement; (C) eight patients with hepatic metastases. Regions of interest were manually constructed only over apparently normal areas of liver tissue excluding major blood vessels and areas of intra-hepatic fat, which may otherwise alter CT texture irrespective of the presence of malignancy. Texture was analysed on unfiltered images and following band-pass image filtration to highlight image features at different spatial frequencies (fine: 2 pixels/1.68 mm in width, medium: 6 pixels/5.04 mm and coarse: 12 pixels/10.08 mm). The relative contributions made to the image by features at two different spatial frequencies were expressed as filter ratios (fine/medium, fine/coarse and medium/coarse). Texture was quantified as mean grey-level intensity, entropy and uniformity. RESULTS: Texture was not altered on unfiltered images whereas relative texture analysis following image filtration identified differences in fine to medium texture ratios in apparently disease-free areas of the liver in patients with hepatic metastases as compared to patients with no tumour (entropy, p=0.0257) and patients with extra-hepatic disease (uniformity, p=0.0143). CONCLUSIONS: Relative texture analysis of unenhanced hepatic CT can reveal changes in apparently disease-free areas of the liver that have previously required more complex perfusion measurements for detection.
Authors: Marco Ravanelli; Giorgio Maria Agazzi; Elena Tononcelli; Elisa Roca; Paolo Cabassa; Gianluca Baiocchi; Alfredo Berruti; Roberto Maroldi; Davide Farina Journal: Radiol Med Date: 2019-06-06 Impact factor: 3.469
Authors: Barbara Juarez Amorim; Angel Torrado-Carvajal; Shadi A Esfahani; Sara S Marcos; Mark Vangel; Dan Stein; David Groshar; Onofrio A Catalano Journal: Mol Imaging Biol Date: 2020-10 Impact factor: 3.488
Authors: Balaji Ganeshan; Sandra Abaleke; Rupert C D Young; Christopher R Chatwin; Kenneth A Miles Journal: Cancer Imaging Date: 2010-07-06 Impact factor: 3.909
Authors: Pier Paolo Mainenti; Federica Romano; Laura Pizzuti; Sabrina Segreto; Giovanni Storto; Lorenzo Mannelli; Massimo Imbriaco; Luigi Camera; Simone Maurea Journal: World J Radiol Date: 2015-07-28