Intravoxel incoherent motion MRI in neurological and cerebrovascular diseases

Abstract

Intravoxel Incoherent Motion (IVIM) is a recently rediscovered noninvasive magnetic resonance imaging (MRI) method based on diffusion-weighted imaging. It enables the separation of the intravoxel signal into diffusion due to Brownian motion and perfusion-related contributions and provides important information on microperfusion in the tissue and therefore it is a promising tool for applications in neurological and neurovascular diseases. This review focuses on the basic principles and outputs of IVIM and details it major applications in the brain, such as stroke, tumor, and cerebral small vessel disease. A bi-exponential model that considers two different compartments, namely capillaries, and medium-sized vessels, has been frequently used for the description of the IVIM signal and may be important in those clinical applications cited before. Moreover, the combination of IVIM and arterial spin labeling MRI enables the estimation of water permeability across the blood-brain barrier (BBB), suggesting a potential imaging biomarker for disrupted-BBB diseases.

Graphical abstract

Fig. 1

Examples of D, f and D* maps.

Fig. 2

Example of Pseudo-Diffusion (green) and Diffusion (red) contributions to IVIM signal (blue). Pseudo-diffusion (D*) and diffusion coefficients (D) are extracted from the exponential decay of green and red curves, respectively. Perfusion fraction f is obtained from the difference of the intercept of blue and red curves. (For interpretation of the references to color in this figure legend, the reader is referred to the online version of this chapter.)

Fig. 3

Example of a patient with a stroke in the middle cerebral artery territory. a) Raw image (b = 900 s/mm²). b) ADC map. c) Perfusion fraction map. d) IVIM fitting in the stroke area. e) IVIM fitting in the contralateral hemisphere (Federau et al., 2014c).

Fig. 4

Example of FLAIR images (A, D), perfusion fraction f maps (B, E) and parenchymal diffusivity D (C, F) for a small vessel disease patient (top row) and a healthy subject (bottom row) (Wong et al., 2017).

Fig. 5

Example of IVIM parameter maps for a patient with radiation necrosis (top row) and another with tumor recurrence (bottom row) (Detsky et al., 2017).

Fig. 6

Examples of ASL-DWI images. For both figures a and b, first row shows the average diffusion-weighted (ΔM) maps for b₀; second row shows ΔM including diffusion weighting (b_dw); third row shows the ratio ΔM(b_dw)/ΔM(b₀). In fourth row, in figure a it is shown the Transit time to the capillary-tissue compartment (τ_a) while in figure b it is presented the exchange rate of water from blood to tissue (k_w) (Lawrence et al., 2012)