The intravoxel incoherent motion (IVIM) model, first introduced in the 1980s by Denis le Bihan, attributes the strong signal decay at small diffusion weightings to blood perfusion. This model provides not only information on the tissue diffusivity , but also about perfusion fraction and the pseudo-diffusion coefficient. The signal can be described by a biexponential function that reads:
S(b) / S0 = (1–f)⋅exp(–b⋅D) + f⋅exp(–b⋅D*)
with unweighted signal S0 and the diffusion weighted signal S(b). This biexponential model assumes two separate compartments; one compartment representing incoherently flowing blood (corresponding to f and D*) and one tissue compartment that experiences diffusive motion.
We have been active in the field of IVIM research for more than a decade by now. Conducted research projects include works proving that blood flow is indeed responsible for the IVIM effect , studies evaluating the clinical value of IVIM (e.g. for grading of pancreatic lesions ), and works on optimizing the acquisition protocol . We have explored the use of flow-compensated diffusion-encoding gradients , which mainly suppress the IVIM effect and can be used to estimate the parameters of le Bihan’s IVIM model. For this approach, it is of importance to know exactly the diffusion coefficient of blood .
Recent works focus on tri-exponential IVIM (Fig. 1). Advances in acquisition techniques made in recent years have made possible the more precise and accurate measurement of the IVIM curve and it has recently be reported that the IVIM curve appears to be tri-exponential at small b-values (b ≤ 10 s/mm2) (e.g. [6,7]):
S(b) / S0 = (1-–f1–f2)⋅exp(–b⋅D) + f1⋅exp(–b⋅D1*) + f2⋅exp(–b⋅D2*),
with two perfusion fractions f1 and f2, and two pseudo-diffusion coefficients D1* and D2*. We are currently working on making use of the echo time dependence of this curve  as it might reveal information on blood oxygenation in tissue. Since measuring tri-exponential IVIM curves is particularly challenging, we work on optimizing the sequences and acquisition protocols.
Figure 1. IVIM signal curve of the liver.
At small b-values, a tri-exponential model fits the data much better than a bi-exponential model.
 Lemke A, Laun FB, Simon D, Stieltjes B, Schad LR.
An in vivo verification of the intravoxel incoherent motion effect in diffusion-weighted imaging of the abdomen.
Magn Reson Med. 2010 Dec;64(6):1580-5.
 Lemke A, Laun FB, Klauss M, Re TJ, Simon D, Delorme S, Schad LR, Stieltjes B.
Differentiation of pancreas carcinoma from healthy pancreatic tissue using multiple b-values: comparison of apparent diffusion coefficient and intravoxel incoherent motion derived parameters.
Invest Radiol. 2009 Dec;44(12):769-75.
 Lemke A, Stieltjes B, Schad LR, Laun FB.
Toward an optimal distribution of b values for intravoxel incoherent motion imaging.
Magn Reson Imaging. 2011 Jul;29(6):766-76.
 Wetscherek A, Stieltjes B, Laun FB.
Flow-compensated intravoxel incoherent motion diffusion imaging.
Magn Reson Med. 2015 Aug;74(2):410-9.
 Funck C, Laun FB, Wetscherek A.
Characterization of the diffusion coefficient of blood.
Magn Reson Med. 2018 May;79(5):2752-2758.
 Cercueil JP, Petit JM, Nougaret S, Soyer P, Fohlen A, Pierredon-Foulongne MA, Schembri V, Delhom E, Schimdt S, Denys A, Aho S, Guiu B.
Intravoxel incoherent motion diffusion-weighted imaging in the liver: comparison of mono-, bi- and tri-exponential modelling at 3.0-T.
Eur Radiol. 2015;25(6):1541-50
 Kuai ZX, Liu WY, Zhu YM.
Effect of multiple perfusion components on pseudo-diffusion coefficient in intravoxel incoherent motion imaging.
Physics in medicine and biology. 2017;62(21):8197-209.
 Riexinger AJ, Martin J, Rauh S, Wetscherek A, Pistel M, Kuder TA, Nagel AM, Uder M, Hensel B, Muller L and Laun FB.
On the Field Strength Dependence of Bi- and Triexponential Intravoxel Incoherent Motion (IVIM) Parameters in the Liver.
J Magn Reson Imaging. 2019.