Effect of Fat: Assessment of Apparent Diffusion Coefficient

Effect of Fat: Assessment of Apparent Diffusion Coefficient Abstract Objectives: Recent studies have indicated that excessive fat may confound assessment of diffusion in organs with high fat content, such as the liver and breast. However, the extent of this effect in the kidney, which is not considered a major fat deposition site, remains unclear. This study tested the hypothesis that renal fat may impact DWI parameters, and proposes a three-compartment model (TCM) to circumvent this effect. Methods: Using computer simulations, we investigated the effect of fat on assessment of apparent diffusion coefficient (ADC), intravoxel incoherent-motion (IVIM) and TCM-derived pure-diffusivity. In domestic pigs fed a high-cholesterol (Obese) or normal diet (Lean) (n=7 each), DWI parameters were calculated using IVIM and correlated to renal histology. IVIM-derived pure diffusivity was also compared among 15 essential hypertension (EH) patients classified by BMI (high vs. normal). Finally, pure diffusivity was calculated and compared in 8 patients with atherosclerotic renal artery stenosis (ARAS) and 5 healthy subjects using IVIM and TCM. Results: Simulations showed that unaccounted fat results in the underestimation of intravoxel incoherent-motion (IVIM)-derived pure-diffusivity, particularly at lower fat contents. Moreover, TCM, which incorporates highly diffusion-weighted images (b>2500s/mm2), could correct for fat-dependent underestimation. Animal studies confirmed lower ADC and pure-diffusivity in Obese vs. Lean pigs with otherwise healthy kidneys. Similarly, EH patients with high BMI had lower ADC (1.9 vs. 2.110-3 mm2/s) and pure-diffusivity (1.7 vs. 1.910-3mm2/s) than those with normal BMI.   Pure-diffusivity calculated using IVIM was not different between the ARAS and healthy subjects, but TCM revealed significantly lower diffusivity in ARAS. Conclusions: Excessive renal fat may cause underestimation of renal ADC and pure-diffusivity, which may hinder detection of renal pathology. Models accounting for fat contribution may help reduce the variability of diffusivity calculated using DWI. Keywords: Renal adiposity, Diffusion-weighted imaging, intravoxel incoherent motion, obesity.   Ã‚   Over the past two decades, diffusion-weighted imaging (DWI) has evolved to an important tool for studying neurological disorders (1-3), while application of this method for characterization of abdominal pathological conditions awaited improved hardware and robust pulse sequences over nearly a decade (4). In the kidney, DWI has been used to investigate chronic kidney disease (CKD) (5), renal lesions (6), and deteriorating allografts (7). Nevertheless, the contribution of tubular flow and hemodynamics to the apparent diffusion constant (ADC), the diffusion quantitative index of the single compartment mono-exponential model, complicates tissue characterization and renal DWI analysis (8). This encouraged implementation of models incorporating a larger number of compartments to differentiate pure diffusion from pseudo-diffusive components. Indeed, in the kidney the intra-voxel incoherent motion (IVIM) analytical method, which utilizes a two-compartment model associated with pure diffusion and flow, showed superiority over the mono-exponential decay model (9, 10). However, recent studies on hepatic DWI identified fat as a potential third compartment with a significant confounding effect (11, 12), even in non-steatotic livers (13, 14) or other organs (15). Abdominal DWI is typically performed using an echo-planar imaging (EPI) readout, which uses a water-only excitation. Selected excitation or fat suppression methods prevent contribution of the fat signal associated with peaks spectrally distant from water, but cannot effectively eliminate the signal from fat components with resonance frequencies close to water proton frequency. For instance, peaks between 4.2-5.3 ppm associated with triglycerides, which account for nearly 8.7% of the total in vivo fat content, remain unsuppressed (11). Moreover, in the kidney, which is located in the vicinity of bowel, susceptibility artifacts may significantly reduce the efficacy of spectral fat suppression. Because the diffusion constant of lipid molecules is orders of magnitude smaller than that in water an d remains nearly unattenuated over the conventional range of b-values, the amplitude of the fat signal, especially at high b-values, can be prominent compared to the attenuated water signal (16), and therefore has a considerable impact on DWI parameters assessment (17). The epidemic of obesity stresses the importance of characterization of the effect of ectopic fat on DWI parameters, particularly in subjects with high body mass index (BMI). Increased renal adiposity (18, 19) may potentially interfere with interpretation of DWI in the kidney in obese subjects, but to date this effect has not been evaluated. The aim of this study was to explore the effect of renal fat accumulation and suboptimal suppression on DWI parameters. We investigated this effect using computer simulations and verified the error in a large animal model of obesity, and in healthy subjects and in the presence of renal pathological conditions in humans. We hypothesized that residual MR signal from fat causes underestimation of renal ADC and IVIM pure-diffusivity, the magnitude of which may approximate a reduction in these parameters elicited by renal pathology. Moreover, we suggest that the fat-dependency of DWI parameters may be corrected by estimating the MR signal of excessive fat using heavily diffusion-weighted images. Assuming that an unattenuated fat signal acts as an independent compartment, we formulated our model by adding a third exponential decay term to the bi-exponential IVIM model to account for the contribution of fat: (1) In our notation, C and are the fractions of extravascular water and fat in the DWI signal intensity. Dfast, Dslow, andDfat are diffusion coefficients for extravascular water (pure-diffusivity), intravascular flow-dependent component (pseudo-diffusion), and fat, respectively. The product of the fat diffusion coefficient and the b-values, over the conventional range of b-values is small such that the exponential part of the third term can be approximated by one. This simplifies the last term in Equation (1) to a constant signal offset as follows: (2) Considering that at higher b-values (~1000 s/mm2) conventionally used in DWI, the water-component of the signal intensity decays to nearly a few percent of its value at b0 (b=0 s/mm2), while the fat-related fraction (FRF), f, remains nearly unattenuated over the imaging b-value spectrum, the magnitude of FRF and its impact on calculated DWI parameters becomes significant. I. Simulations Simulations in this study pursued four aims. First, to show that in the absence of fat signal, the three-compartment model (TCM) reduces to IVIM. This would essentially verify that a non-zero FRF is not merely a result of overfitting the data of an intrinsically two-compartment system into a three-compartment model, and in fact represents a third independent compartment. Second, to investigate the influence of FRF, as illustrated in equation (1), on the diffusion parameters calculated using the bi-exponential IVIM model. Third, to examine the effect of signal-to-noise ratio (SNR) on the accuracy of DWI parameters assessed using IVIM and TCM, particularly since increasing the degrees of freedom in TCM per se reduces the stability of the regularization methods. Finally, to test if in the presence of fat signal the DWI parameters calculated using IVIM and TCM would be b-value dependent. We simulated the total MR signal using the TCM, including fast and slow decays associated with intra- and extravascular fluid, as well as the FRF signal as a third compartment. Simulations were performed for diffusion parameters similar to DWI values reported for the kidney (10), over a range of FRFs (0-10%) and SNRs (2.5-50dB) (Table 1). IVIM and TCM were used to extract DWI parameters. In TCM, the total MR signal intensity for all b-values was subtracted by the signal intensity from the corresponding voxel of the high b-value (>2500 s/mm2) image, and the data were then fitted to a bi-exponential model. Table 1 shows the values used in the simulations. To verify the b-value dependency, DWI parameters were calculated from a set of b-values with the highest value being either 600, 1000, or 2000 s/mm2. II. Animal study All animal procedures followed the Guideline for the Care and Use of Laboratory Animals (National Research Council, National Academy Press, Washington, DC, 1996) and were approved by the Institutional Animal Care and Use Committee at Mayo Clinic. Fourteen domestic swine in this study were fed ad lib for 16 weeks. Seven animals consumed a normal diet (Controls) and the other half (Obese) a high fat/carbohydrate diet (5B4L; Purina Test Diet, Richmond, IN) containing (in % kcal) 17% protein, 20% complex carbohydrates, 20% fructose, and 43% fat and supplemented with 2% cholesterol and 0.7% sodium cholate. We have recently shown that this diet induces obesity and adiposity (20). Diffusion-weighted MRI scans were performed at the completion of diet. Renal volume and hemodynamics were assessed 2-3 days apart from MR scans, using multi-detector computed tomography (MDCT). Prior to each in vivo study animals were anesthetized (Telazol 5mg/kg and xylazine 2mg/kg in saline), and anesthesia maintained with intravenous ketamine (0.2 mg/kg/min) and xylazine (0.03 mg/kg/min) (for CT), or inhaled 1-2% isoflurane (for MRI) throughout the course of imaging. Blood pressure was measured using an arterial catheter during the MDCT scanning session. Animals were injected with 10cc of heparin and euthanized with a lethal intravenous dose of sodium pentobarbital (100 mg/kg) a few days after the in vivo studies. Then the kidneys were removed and immersed in saline containing heparin. The tissue was stored at -80 °C or preserved in formalin for histology. a. Diffusion-weighted Imaging (DWI) DWI was performed on a 3T scanner (GE Medical Systems, Milwaukee, Wisconsin) using a torso array coil. Images were collected using a single-shot echo-planar sequence with bipolar gradient. In all animals, 4-6 coronal slices in oblique planes were collected for b-values 50, 100, 200, 300, 600, 800 and 1000 s/mm2. MR parameters were set to TR/TE 1800/79ms, field of view 35cm, Bandwidth 648Hz/pixel, Number of averages 3, slice thickness 2.5mm, and matrix size 128128. All acquisitions were performed during suspended respiration. b. MDCT imaging Renal hemodynamics were assessed from contrast-enhanced MDCT images, as previously detailed (21). A pigtail catheter was advanced through the left jugular vein to the superior vena cava to inject contrast media during the scan. Then animals were moved to MDCT unit (Somatom Sensation 64; Siemens Medical Solutions, Forchheim, Germany). Following localization of the kidneys, a bolus of iopamidol (0.5 ml/kg over 2s) was injected, and after a 3-second delay, 140 consecutive scans were acquired over approximately 3 minutes. After the flow scan and an additional contrast injection, a volume study was performed. Axial images were acquired at helical acquisition with thickness of 0.6mm and resolution of 512512, and reconstructed at 5mm thickness. c. Lipid Panel Lipid (total cholesterol, triglyceride, high density lipid (HDL)) was measured (Roche) at the Mayo Immunochemical Core Laboratory from blood samples, and low-density lipid (LDL) was calculated. d. Morphological Studies Images were acquired using an ApoTome microscope (Carl ZEISS SMT, Oberkochen, Germany). Renal fibrosis was quantified by colorimetric measurements in 5 µm slides stained for trichrome. Tubular dilation was measured in Periodic acid-Schiff (PAS)-stained slides counterstained with Hemotoxylin. Intracellular lipid accumulation was assessed by colorimetric measurements in Oil-Red-O stained slides from frozen tissue counterstained with Hematoxylin. III. Human study The study was approved by the Institutional Review Board of the Mayo Clinic, in accordance with the Declaration of Helsinki and the Health Insurance Portability and Accountability Act (HIPAA) guidelines. All patients provided written informed consent before enrollment. Fifteen patients with essential hypertension (EH) were recruited from an on-going study, to study the effect of renal fat on DWI parameters. Patients were divided in two groups based on their BMI: an obese group (n=10, BMI≠¥30kg/m2) and a lean group (n=5, BMI 20-25kg/m2). Additionally, diffusion parameters assessments in healthy vs. impaired (post-stenotic) kidneys, with and without fat correction, were compared in eight patients with atherosclerotic renal artery stenosis (ARAS), and five healthy controls. a. DWI In patients 3-8 axial images were acquired on 3T scanner (GE Medical Systems, Milwaukee, WI and Siemens Medical Systems, Erlangen, Germany) with MR parameters TR/TE, Bandwidth, Slice thickness, matrix size, and b-values were set to 2000-2400/60-94ms, 1953 Hz/pixel, 7mm, 128128 or 160160, and 100, 300, 600, 900 (s/mm2) in the first study with EH patients. In ARAS and Control subjects the TR/TE were 2600-4286/59-112ms. Pure-diffusivity was calculated from b-values ≠¥300 s/mm2 and fat-related fraction was assessed from high b-values, 2000-2500 s/mm2. b. Clinical parameters and Lipid Panel Clinical and laboratory parameters including age, sex, weight, BMI, blood pressure, serum creatinine, estimated glomerular filtration rate (eGFR), and lipid panel levels were evaluated at study entry by standard procedures. IV. Data analysis a. DWI Pixel-by-pixel maps of quantitative indices of mono-exponential model, ADC, and bi- and tri-exponential models, IVIM and TCM parameters, respectively, were generated (Figure 1), as shown previously (22). The threshold for fast vs. slow components was set to 300s/mm2 in both animal and patient studies (23). Large cortical regions of interest (ROIs) were drawn on b0 DWI images and transferred to the maps as detailed before (22). Mean values of ADC and IVIM parameters were calculated by averaging values in all corresponding ROIs for all slices in the subject. b. MDCT Using contrast-enhanced MDCT in animals, single-kidney volume, GFR, perfusion, and renal blood flow (RBF) were calculated. To calculate renal function and hemodynamics, the cortical and medullary signal attenuation vs. time curves were fitted to an extended Γ-variate model. Regional blood volumes and mean transit times were calculated to estimate cortical and medullary perfusion and blood flows (products of perfusion and the corresponding volumes). Total RBF was assessed as the sum of cortical and medullary flows. Finally, GFR was evaluated using the slope of the cortical proximal tubular curve, as previously shown (21). Data Analysis software All analyses were performed in MATLAB ® (MathWork, Natick, MA, USA) and Analyzeâ„ ¢ (Biomedical Imaging Resource, Mayo Clinic, MN, USA). V. Statistical Analysis Simulation results are shown as mean  ± STD, and in vivo results as Median [First Quartile Third Quartile]. Minimum sample size was calculated using power analysis for minimum power value of 0.8. Non-parametric Mann-Whitney was used for comparison among groups. For p values