Effect of multiple perfusion components on pseudo-diffusion coefficient in intravoxel incoherent motion imaging. (11th October 2017)

• Record Type: Journal Article
• Authors: Kuai, Zi-Xiang; Liu, Wan-Yu; Zhu, Yue-Min
• Is Part Of: Physics in medicine & biology. Volume 62:Number 21(2017:Nov.)
• Page Start: 8197
• Page End: 8209
• Publication Date: 2017-10-11
• Subjects: multi-component perfusion -- pseudo-diffusion -- intravoxel incoherent motion -- diffusion-weighted imaging -- abdominal; Biophysics -- Periodicals; Medical physics -- Periodicals; 610.153
• DOI: 10.1088/1361-6560/aa8d0c
• Languages: English
• ISSNs: 0031-9155

Abstract

Abstract: The aim of this work was to investigate the effect of multiple perfusion components on the pseudo-diffusion coefficient D * in the bi-exponential intravoxel incoherent motion (IVIM) model. Simulations were first performed to examine how the presence of multiple perfusion components influences D * . The real data of livers ( n = 31), spleens ( n = 31) and kidneys ( n = 31) of 31 volunteers was then acquired using DWI for in vivo study and the number of perfusion components in these tissues was determined together with their perfusion fraction and D *, using an adaptive multi-exponential IVIM model. Finally, the bi-exponential model was applied to the real data and the mean, standard variance and coefficient of variation of D * as well as the fitting residual were calculated over the 31 volunteers for each of the three tissues and compared between them. The results of both the simulations and the in vivo study showed that, for the bi-exponential IVIM model, both the variance of D * and the fitting residual tended to increase when the number of perfusion components was increased or when the difference between perfusion components became large. In addition, it was found that the kidney presented the fewest perfusion components among the three tissues. The present study demonstrated that multi-component perfusion is a main factor that causes high variance of D * and the bi-exponential model should be used only when the tissues under investigation have few perfusion components, for example the kidney.