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Effect of multiple perfusion components on pseudo-diffusion coefficient in intravoxel incoherent motion imaging
Zi-Xiang Kuai1,2, Wan-Yu Liu2, Yue-Min Zhu2,3
1Imaging Center, Harbin Medical University Cancer Hospital, Harbin, People's Republic of China.
Physics in Medicine and Biology
|September 16, 2017
Summary
Multi-component perfusion significantly increases pseudo-diffusion coefficient (D*) variance in the bi-exponential intravoxel incoherent motion (IVIM) model. This suggests the bi-exponential IVIM model is best suited for tissues with few perfusion components, like the kidney.
Area of Science:
- Biomedical Imaging
- Medical Physics
- Radiology
Background:
- The bi-exponential intravoxel incoherent motion (IVIM) model is widely used in diffusion-weighted imaging (DWI) to assess tissue microcirculation.
- The pseudo-diffusion coefficient (D*) is a key parameter in the IVIM model, reflecting tissue perfusion.
- Understanding factors influencing D* accuracy is crucial for reliable clinical applications of IVIM-DWI.
Purpose of the Study:
- To investigate the impact of multiple perfusion components on the pseudo-diffusion coefficient (D*) within the bi-exponential IVIM model.
- To evaluate the suitability of the bi-exponential IVIM model for tissues with varying numbers of perfusion components.
Main Methods:
- Performed computational simulations to analyze the influence of multiple perfusion components on D*.
- Acquired in vivo DWI data from livers, spleens, and kidneys of 31 healthy volunteers.
- Utilized an adaptive multi-exponential IVIM model to determine perfusion components, perfusion fraction, and D* in real data.
- Applied the bi-exponential IVIM model to real data, calculating D* variance and fitting residuals for comparison across tissues.
Main Results:
- Both simulations and in vivo data demonstrated that increased numbers of perfusion components or larger differences between them elevate D* variance and fitting residuals in the bi-exponential IVIM model.
- Kidneys exhibited the fewest perfusion components among the studied tissues (liver, spleen, kidney).
- Multi-component perfusion was identified as a primary driver of high D* variance.
Conclusions:
- The accuracy of the bi-exponential IVIM model is compromised in tissues with complex, multi-component perfusion.
- The bi-exponential IVIM model is most appropriate for tissues characterized by a limited number of perfusion components, such as the kidney.
- Clinical application of the bi-exponential IVIM model should consider the underlying tissue perfusion complexity to ensure reliable D* estimation.
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