Huyen T Nguyen1, Zarine K Shah1, Amir Mortazavi2, Kamal S Pohar3, Lai Wei4, Guang Jia5,6, Debra L Zynger7, Michael V Knopp8. 1. Wright Center of Innovation in Biomedical Imaging, Department of Radiology, The Ohio State University, 395 W. 12th Ave., Room 430, Columbus, OH, 43210, USA. 2. Department of Internal Medicine, The Ohio State University, Columbus, OH, USA. 3. Department of Urology, The Ohio State University, Columbus, OH, USA. 4. Center for Biostatistics, The Ohio State University, Columbus, OH, USA. 5. Department of Physics and Astronomy, Louisiana State University, Baton Rouge, LA, USA. 6. Pennington Biomedical Research Center, Baton Rouge, LA, USA. 7. Department of Pathology, The Ohio State University, Columbus, OH, USA. 8. Wright Center of Innovation in Biomedical Imaging, Department of Radiology, The Ohio State University, 395 W. 12th Ave., Room 430, Columbus, OH, 43210, USA. knopp.16@osu.edu.
Abstract
OBJECTIVES: To quantify the heterogeneity of the tumour apparent diffusion coefficient (ADC) using voxel-based analysis to differentiate malignancy from benign wall thickening of the urinary bladder. METHODS: Nineteen patients with histopathological findings of their cystectomy specimen were included. A data set of voxel-based ADC values was acquired for each patient's lesion. Histogram analysis was performed on each data set to calculate uniformity (U) and entropy (E). The k-means clustering of the voxel-wised ADC data set was implemented to measure mean intra-cluster distance (MICD) and largest inter-cluster distance (LICD). Subsequently, U, E, MICD, and LICD for malignant tumours were compared with those for benign lesions using a two-sample t-test. RESULTS: Eleven patients had pathological confirmation of malignancy and eight with benign wall thickening. Histogram analysis showed that malignant tumours had a significantly higher degree of ADC heterogeneity with lower U (P = 0.016) and higher E (P = 0.005) than benign lesions. In agreement with these findings, k-means clustering of voxel-wise ADC indicated that bladder malignancy presented with significantly higher MICD (P < 0.001) and higher LICD (P = 0.002) than benign wall thickening. CONCLUSIONS: The quantitative assessment of tumour diffusion heterogeneity using voxel-based ADC analysis has the potential to become a non-invasive tool to distinguish malignant from benign tissues of urinary bladder cancer. KEY POINTS: • Heterogeneity is an intrinsic characteristic of tumoral tissue. • Non-invasive quantification of tumour heterogeneity can provide adjunctive information to improve cancer diagnosis accuracy. • Histogram analysis and k-means clustering can quantify tumour diffusion heterogeneity. • The quantification helps differentiate malignant from benign urinary bladder tissue.
OBJECTIVES: To quantify the heterogeneity of the tumour apparent diffusion coefficient (ADC) using voxel-based analysis to differentiate malignancy from benign wall thickening of the urinary bladder. METHODS: Nineteen patients with histopathological findings of their cystectomy specimen were included. A data set of voxel-based ADC values was acquired for each patient's lesion. Histogram analysis was performed on each data set to calculate uniformity (U) and entropy (E). The k-means clustering of the voxel-wised ADC data set was implemented to measure mean intra-cluster distance (MICD) and largest inter-cluster distance (LICD). Subsequently, U, E, MICD, and LICD for malignant tumours were compared with those for benign lesions using a two-sample t-test. RESULTS: Eleven patients had pathological confirmation of malignancy and eight with benign wall thickening. Histogram analysis showed that malignant tumours had a significantly higher degree of ADC heterogeneity with lower U (P = 0.016) and higher E (P = 0.005) than benign lesions. In agreement with these findings, k-means clustering of voxel-wise ADC indicated that bladder malignancy presented with significantly higher MICD (P < 0.001) and higher LICD (P = 0.002) than benign wall thickening. CONCLUSIONS: The quantitative assessment of tumour diffusion heterogeneity using voxel-based ADC analysis has the potential to become a non-invasive tool to distinguish malignant from benign tissues of urinary bladder cancer. KEY POINTS: • Heterogeneity is an intrinsic characteristic of tumoral tissue. • Non-invasive quantification of tumour heterogeneity can provide adjunctive information to improve cancer diagnosis accuracy. • Histogram analysis and k-means clustering can quantify tumour diffusion heterogeneity. • The quantification helps differentiate malignant from benign urinary bladder tissue.
Authors: Huyen T Nguyen; Kamal S Pohar; Guang Jia; Zarine K Shah; Amir Mortazavi; Debra L Zynger; Lai Wei; Daniel Clark; Xiangyu Yang; Michael V Knopp Journal: Invest Radiol Date: 2014-06 Impact factor: 6.016
Authors: Huyen T Nguyen; Guang Jia; Zarine K Shah; Kamal Pohar; Amir Mortazavi; Debra L Zynger; Lai Wei; Xiangyu Yang; Daniel Clark; Michael V Knopp Journal: J Magn Reson Imaging Date: 2014-06-19 Impact factor: 4.813
Authors: Huyen T Nguyen; Amir Mortazavi; Kamal S Pohar; Debra L Zynger; Lai Wei; Zarine K Shah; Guang Jia; Michael V Knopp Journal: Bladder Cancer Date: 2017-10-27