Intravoxel incoherent motion
Intravoxel incoherent motion (IVIM) imaging is a concept and a method initially introduced and developed by Le Bihan et al.[1][2] to quantitatively assess all the microscopic translational motions that could contribute to the signal acquired with diffusion MRI.
The concept introduced by D. Le Bihan is that water flowing in capillaries (at the voxel level) mimics a random walk (“pseudo-diffusion” [2]) (Fig.1), as long as the assumption that all directions are represented in the capillaries (i.e. there is no net coherent flow in any direction) is satisfied.
It is responsible for a signal attenuation in diffusion MRI, which depends on the velocity of the flowing blood and the vascular architecture.
Similarly to molecular diffusion, the effect of pseudodiffusion on the signal attenuation depends on the b value.
However, the rate of signal attenuation resulting from pseudodiffusion is typically an order of magnitude greater than molecular diffusion in tissues, so its relative contribution to the diffusion-weighted MRI signal becomes significant only at very low b values, allowing diffusion and perfusion effects to be separated.
is a parameter linked to the gradient pulse amplitude and time course (similar to the b value).
On the other hand, set of data obtained from images acquired with a multiple b values can be fitted with Eq.
The late part of the curve (towards high b values, generally above 1000 s/mm²) also presents some degree of curvature (Fig.2).
This is because diffusion in biological tissues is not free (Gaussian), but can be hindered by many obstacles (in particular cell membranes) or even restricted (i.e. intracellular).
Another alternative is the “kurtosis” model which quantifies the deviation from free (Gaussian) diffusion in the parameter
Separation of perfusion from diffusion requires good signal-to-noise ratios[9][10] and there are some technical challenges to overcome (artifacts, influence of other bulk flow phenomena, etc.).
[13][14] Indeed, there is room to improve the IVIM model and understand better its relationship with the functional vascular architecture and its biological relevance.
[10][15][16][17][18][19] Recent work has proven the validity of the IVIM concept from fMRI, with an increase in the IVIM perfusion parameters in brain activated regions, and the potential of the approach to aid in our understanding of the different vascular contributions to the fMRI signal.
By inserting “diffusion” gradient pulses in the MRI sequence (corresponding to low b-values), one may crush the contribution of the largest vessels (with high D* values associated with fast flow) in the BOLD signal and improve the spatial resolution of the activation maps.
This IVIM concept has also been borrowed to improve other applications, for instance, arterial spin labeling (ASL) [29][30] or to suppress signal from extracellular flowing fluid in perfused cell systems.
[31][32] However, IVIM MRI has recently undergone a striking revival for applications not in the brain, but throughout the body as well.
[33] Following earlier encouraging results in the kidneys,[34][35][36] or even the heart,[37] IVIM MRI really took off for liver applications.
(Another theoretical, rather unlikely interpretation would be that capillary segments become longer or more straight in those patients with liver fibrosis).
The perfusion fraction, f, which is linked to blood volume in the IVIM model, remained normal, confirming earlier results by Yamada et al.[39] Though, blood volume is expected to be reduced in liver cirrhosis.
[40][41] Signal from large vessels with rapid flow disappears quickly with very low b values, while smaller vessels with slower flow might still contribute to the IVIM signal acquired with b values larger than 200 s/mm².
[43] Many more applications are now under investigation, especially for imaging of patients suspected of cancer in the body (prostate, liver, kidney, pancreas, etc.)
