PURPOSE: To develop and validate an automated segmentation method that extracts the interventricular septum (IS) from myocardial black-blood images for the T2* measurement in thalassemia patients. MATERIALS AND METHODS: A total of 144 thalassemia major patients (age range, 11-51 years; 73 males) were scanned with a black-blood multi-echo gradient-echo sequence using a 1.5 Tesla Siemens Sonata system (flip angle 20°, sampling bandwidth 810 Hz/pixel, voxel size 1.56 × 1.56 × 10 mm(3) and variable fields of view (20-30) × 40 cm(2) depending on patient size). The improved Chan-Vese model with an automated initialization by the circular Hough transformation was implemented to segment the endocardial and epicardial margins of the left ventricle (LV). Consequently, the IS was extracted by analyzing the anatomical relation between the LV and the blood pool of the right ventricle, identified by intensity thresholding. The proposed automated IS segmentation (AISS) method was compared with the conventional manual method by using the Bland-Altman analysis and the coefficient of variation (CoV). RESULTS: The T2* measurements using the AISS method were in good agreement with those manually measured by experienced observers with a mean difference of 1.71% and a CoV of 4.15% (P < 0.001). CONCLUSION: Black-blood myocardial T2* measurement can be fully automated with the proposed AISS method.
PURPOSE: To develop and validate an automated segmentation method that extracts the interventricular septum (IS) from myocardial black-blood images for the T2* measurement in thalassemiapatients. MATERIALS AND METHODS: A total of 144 thalassemia major patients (age range, 11-51 years; 73 males) were scanned with a black-blood multi-echo gradient-echo sequence using a 1.5 Tesla Siemens Sonata system (flip angle 20°, sampling bandwidth 810 Hz/pixel, voxel size 1.56 × 1.56 × 10 mm(3) and variable fields of view (20-30) × 40 cm(2) depending on patient size). The improved Chan-Vese model with an automated initialization by the circular Hough transformation was implemented to segment the endocardial and epicardial margins of the left ventricle (LV). Consequently, the IS was extracted by analyzing the anatomical relation between the LV and the blood pool of the right ventricle, identified by intensity thresholding. The proposed automated IS segmentation (AISS) method was compared with the conventional manual method by using the Bland-Altman analysis and the coefficient of variation (CoV). RESULTS: The T2* measurements using the AISS method were in good agreement with those manually measured by experienced observers with a mean difference of 1.71% and a CoV of 4.15% (P < 0.001). CONCLUSION: Black-blood myocardial T2* measurement can be fully automated with the proposed AISS method.
Authors: Pandji Triadyaksa; Niek H J Prakken; Jelle Overbosch; Robin B Peters; J Martijn van Swieten; Matthijs Oudkerk; Paul E Sijens Journal: MAGMA Date: 2016-12-16 Impact factor: 2.310
Authors: Pandji Triadyaksa; Astri Handayani; Hildebrand Dijkstra; Kadek Y E Aryanto; Gert Jan Pelgrim; Xueqian Xie; Tineke P Willems; Niek H J Prakken; Matthijs Oudkerk; Paul E Sijens Journal: MAGMA Date: 2015-11-03 Impact factor: 2.310