Diffusion parameters derived from multi b-value DWI-data as surrogate marker for kidney function

Oliver J. Gurney-Champion^{1,2}, RenĂ© van der Bel^{3}, Martijn Froeling^{1,4}, C.T. Paul Krediet^{3}, and Aart J. Nederveen^{1}

The currently available gold standard tests to determine kidney glomerular filtration rate (GFR) and effective renal plasma flow (ERPF) are invasive, costly and time-consuming (6 hours). Recently, it was suggested that blood fraction, urine fraction and tissue fraction can also be characterized by the tri-exponential intravoxel incoherent motion (IVIM) model for diffusion weighted MR-images (DWI).^{1} Potentially, this model can provide a cheaper, faster and non-invasive method to assess similar information as the standard kidney function tests.

In this study, we hypothesize that renal function can be reliably assessed by perfusion fractions derived from a tri-exponential IVIM model. Our aim was to evaluate the sensitivity of these parameters to changes in kidney function and to test the repeatability of the method.

Our DW-scan consisted of twenty 2D coronal slices acquired with an EPI ^{2}, voxel size 3.5x3.5mm^{2}, slice thickness=3.5mm, BW=35Hz/voxel, b-values=0,2,4,8,12,18,24,32,40,50,75,110,200,300,450 and 600s/mm^{2} with 9 gradient directions.

To compensate for in-plane respiratory motion, we used a 2D rigid registration algorithm (elastix^{2}) to register each slice to the mean b=0 s/mm^{2} image. For each voxel, we fitted a tri-exponential model which returned the diffusion coefficient (D), pseudo-diffusion coefficients (D*^{1}, D*^{2}) and signal fractions with D*^{1}, D*^{2} and D (f_{1}, f_{2}, f_{3}). D*^{1} and D*^{2} were fixed to values obtained from a fit to data from all subjects at baseline. To assess kidney function, we took the mean parameter values from the voxel-wise fits to data from the kidney medulla and cortex.

To investigate how the model parameters change as a function of kidney function, we acquired DW images in 8 healthy volunteers (aged 18-24 years) on a 3T (Philips, Ingenia) scanner. The volunteers all were subjected to a continuous angiotensin-II infusion (0, 0.3, 0.9 and 3.0 ng/kg/min) during acquisition. During a second visit, the effect of the angiotensin-II on the kidney function, namely GFR and ERPF, were assessed using the gold standard ^{125}I-thalamate and ^{131}I-hippuran clearing tests, during a similar infusion protocol. We applied linear regression fits between the fit parameters and angiotensin-II dose to test if there was any response. In addition, we used a Pearson correlation test to test for correlations between the perfusion fractions, f_{1} and f_{2}, and the GFR and ERPF.

To study potential challenge unrelated trends and in order to test intra-session repeatability, we obtained time-controlled data by repeating the protocol on 6 healthy volunteers (aged 23-28), without injecting angiotensin-II. To study the

We fixed D*^{1} and D*^{2} to 9.7x10^{-3}mm^{2}/s and 551x10^{-3}mm^{2}/s, respectively.

The mean parameter values at baseline were 1.93±0.08×10^{-3}mm^{2}/s, 11.3±2.4%, 7.8±1.9% and 80.8±2.2% for D, f_{1}, f_{2} and f_{3}, respectively. The perfusion fractions in the kidneys changed as a function of angiotensin-II dose throughout the kidney (Fig 1). There was a significant response in f_{1}, f_{2} and D, which changed by -4.7 (p=0.021), 6.4 (p<0.001) and -1.2 (p<0.001) % per ng/kg/min of angiotensin-II (Fig 2). The correlation coefficient, r, between changes in f_{1} and ERPF was 0.42 (p=0.01), and f_{2} and GFR was -0.62 (p<0.001, Fig 3). These correlations were higher than those previously reported between BOLD measurements and estimated GFR, for which |r|<0.24.^{3}

^{ }The IVIM parameters from the time-controlled data had no significant changes between the first (time-controlled to baseline) and last (time-controlled to max dose) acquisition (Fig 4). For D, f_{1}, f_{2}, f_{3} the intra-session CVs were 3.5%, 14.4%, 6.5% and 1.9%, and the inter-session CVs were 1.7%, 10.4%, 13.8% and 2.2%, respectively (Fig 5).

We showed that _{1} and f_{2} derived from a tri-exponential model for DWI-data presented has potential as a surrogate marker for kidney function as: (1) they change with angiotensin-II dose, (2) they showed a stronger correlation with the golden standard kidney function tests than other MR-methods and (3) they are highly repeatable.

^{1}S.
van Baalen et al. ISMRM (2014), p. 2193.

^{2}S.
Klein et al. IEEE Trans. Med.
Imaging 29, 196–205 (2010).

^{3}H.J.
Michaely et al. Kidney Int. 81, 684–689 (2012).

Proc. Intl. Soc. Mag. Reson. Med. 24 (2016)

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