DocumentCode :
557354
Title :
Statistical evaluation of fitting models of diffusion tensor imaging in characterizing normal porcine myocardium
Author :
Liu, Wei ; Zou, Chao ; Zhang, Na ; Wu, Yin ; Sun, Yunxu
Volume :
1
fYear :
2011
fDate :
15-17 Oct. 2011
Firstpage :
73
Lastpage :
76
Abstract :
It has been long believed that the decay of diffusion-attenuated signal in MRI complied with monoexponential manner. However, a number of researches found that diffusion signal tended to deviate pronouncedly from monoexponential model with increase of b values in some tissues, such as brain, kidney and prostate. The purpose of the current study was by fitting in each diffusion direction separately in diffusion tensor imaging (DTI), to analyze whether a mono- or biexponential or diffusion kurtosis imaging model gives the best fitting model of DTI in describing diffusion characteristics in normal porcine myocardium. Five non-zero b values between 500 and 2000 s/mm2 were selected and their corresponding myocardial diffusion signal used to fit the three diffusion models in each diffusion direction separately. Statistical tests showed that biexponential model fitted better than the diffusion kurtosis imaging model, and monoexponential model gave the worst fitting performance. The results suggest that diffusion tensor imaging of myocardium may be modeled biexponentially to derive accurate characterization of myocardial microstructure.
Keywords :
biodiffusion; biomedical MRI; brain; kidney; medical image processing; muscle; neurophysiology; MRI; brain; diffusion kurtosis imaging model; diffusion tensor imaging; diffusion-attenuated signal; kidney; monoexponential model; myocardial microstructure; normal porcine myocardium; prostate; statistical evaluation; tissues; Analytical models; Brain modeling; Diffusion tensor imaging; Fitting; Myocardium; Diffusion tensor imaging; biexponential model; diffusion kurtosis imaging; monoexponential model; myocardium;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Biomedical Engineering and Informatics (BMEI), 2011 4th International Conference on
Conference_Location :
Shanghai
Print_ISBN :
978-1-4244-9351-7
Type :
conf
DOI :
10.1109/BMEI.2011.6098253
Filename :
6098253
Link To Document :
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