We have previously proposed an intersection profile method for reconstructing four-dimensional (4-D) magnetic resonance imaging (MRI) consisting of one breathing cycle of the thoracoabdominal region. This method captures a set of temporal sequence images in a proper sagittal plane and sets of temporal sequence images in continuous coronal slices. The former set is used as a navigator slice and the latter sets are used as data slices. A 4-D MRI is reconstructed by synchronizing the respiratory pattern found in the navigator slice and the data slices. We propose a prospective method to reduce the acquisition time for data slices. During data slice acquisition, the synchronization process between the respiratory pattern found in the navigator slice and one data slice is monitored in real time. Data acquisition will be terminated and moved to the next data slice based on a threshold value. We used 14 data sets (seven patients with certain pulmonary disease and seven healthy volunteers) previously obtained for the original intersection profile method for a simulation using the proposed method to evaluate the time reduction and impact on image quality. Each of the data set was tested using three different threshold values and the acquisition time can be reduced up to 75%. Although the quantitative evaluation of image quality was slightly worse than that by the conventional method, the difference based on the visual inspection was subtle to human eyes.
KEYWORDS: Chronic obstructive pulmonary disease, Magnetic resonance imaging, Lung, Virtual colonoscopy, Computed tomography, 3D image processing, Medical imaging, Data acquisition, Decision support systems, Gaussian filters
We have developed a method called intersection profile method to construct a 4D-MRI (3D+time) from time-series of 2D-MRI. The basic idea is to find the best matching of the intersection profile from the time series of 2D-MRI in sagittal plane (navigator slice) and time series of 2D-MRI in coronal plane (data slice). In this study, we use 4D-MRI to semiautomatically extract the right diaphragm motion of 16 subjects (8 healthy subjects and 8 COPD patients). The diaphragm motion is then evaluated quantitatively by calculating the displacement of each subjects and normalized it. We also generate phase-length map to view and locate paradoxical motion of the COPD patients. The quantitative results of the normalized displacement shows that COPD patients tend to have smaller displacement compared to healthy subjects. The average normalized displacement of total 8 COPD patients is 9.4mm and the average of normalized displacement of 8 healthy volunteers is 15.3mm. The generated phase-length maps show that not all of the COPD patients have paradoxical motion, however if it has paradoxical motion, the phase-length map is able to locate where does it occur.
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