892 [4]; before that, it was primarily limited to the brain [1–3, 5]. Subsequently, DWI of liver parenchyma and liver abnormalities was performed, however mainly by applica- tion of ADC quantification using the mono-exponential model [6–8]. Yamada et al. then demonstrated that the effect of microperfusion significantly contributes to the ADCs of abdominal organs and hepatic lesions [9]. They concluded by application of the bi-exponential model that the molecular diffusion coefficient Dslow and microperfu- sion fraction f are useful parameters for the characterisation of hepatic lesions. This was supported by later studies that showed the additional value of using the bi-exponential model for the clinical evaluation of hepatic parenchyma and hepatic lesions [10–14]. However, we noticed that most liver studies up to now rely on the ADC as a measure for molecular diffusion without taking into account microperfusion contamination [15–17]. Only a few liver studies avoided microperfusion contamination by choosing only higher b- values starting from 50 mm2/s for the calculation of ADCs [18–23]. Others showed that besides the MRI technique and field strength, the location of the measurement can influence the ADC significantly [21, 24–26]. We, howev- er, suspected that the variation of ADCs in different regions of the liver was due to microperfusion contami- nation. Thus, the purpose of this study was to demonstrate that mono-exponential diffusion in the liver is contami- nated by microperfusion and that the bi-exponential model is required. Methods and materials Study population The protocol of the study was approved by the hospital’s institutional review board, and informed consent was obtained from all subjects. The study population comprised 10 men and 9 women (n = 19) ranging from 20 to 62 years old (mean 32.9 years). All subjects were healthy volunteers, without relevant medical history, with a body mass index (BMI) ranging from 20 to 32 kg/m2. The only preparation before the examination was an 8-h fasting period. MR protocols All subjects were prospectively examined using MR imaging at 1.5 T (Magnetom Avanto, Siemens Medical Solutions, Erlangen, Germany). The body coil served as a transmitter and a six element spine matrix coil in combination with the body matrix as a receiver. After routine localiser- and T2-weighted imaging a series (b= 0, Eur Radiol (2012) 22:891–899 50, 100, 250, 500, 750, 1000 s/mm2) of isotropic diffusion weighted images (DWI) were acquired using a spin echo based echo-planar imaging (EPI) sequence in combination with spectral adiabatic inversion recovery (SPAIR) fat suppression. The acquisition was gated using PACE respiratory triggering (TR = 3100–6500 ms) and was tuned with the following parameters: TE 75 ms; slice-thickness 6 mm; slice-gap 18 mm; FOV 379× 284 mm; matrix 192× 144; bandwidth 1735 Hz/pixel; averages 2 and parallel acquisition technique GRAPPA with acceleration factor 2. Diffusion gradients (25 mT/m) were applied in the phase, read, and z-directions separately. In total 9 transverse slices were acquired with an 18 mm slice gap to cover the whole liver within an average total acquisition time of 8.1 min (range; 4.7–11.1 min). The image acquisition took place in an interleaved mode; first slices 1, 4 and 7 were consecutively acquired with b = 0 value, then the same slices with b = 50 value and so on up to b = 1000. Subsequently, slices 2, 5 and 8 were acquired in the same way, and finally slices 3, 6 and 9 also. Image analysis A programmable graphical and calculus environment was used (Matlab, The Mathworks, Natick, MA, USA) to develop a tool for analysing the DWI series using mono- and bi-exponential fitting procedures. First, the DWI data were loaded and the five liver regions were defined for all 19 datasets by drawing circular regions- of-interest (ROIs) with a diameter of 22.3 mm on selected transverse 6-mm slices (Fig. 1). For each dataset three slices at three different levels were selected; medial at the level of the right portal vein, cranial above the level of the left portal vein and caudal at the level of the splenic vein. The first three regions were drawn in the medial liver slice: central in the right lobe (ROI 1, segments 5/8), dorso-lateral in the right lobe (ROI 2, segments 6/7) and ventral in the left lobe (ROI 3, segments 2/3). The fourth region was drawn in the cranial liver slice, dorso-lateral in the right lobe (ROI 4, segment 7), and the last region in the caudal liver slice, near the gallbladder (ROI 5, segment 5). Any nearby visible vascular and biliary structures were avoided. For each ROI and all seven b-values the average signal intensity S was calculated and stored. Then, the signal intensities S and all seven b-values were fitted to the bi-exponential model [3]: S S0 ¼ ffast expð b DfastÞ þ fslow expð b DslowÞ 1 ð Þ where S0 is the maximum signal intensity, Dfast is the fast component representing microperfusion, ffast is the frac- tion of microperfusion, Dslow is the slow component