Diffusion tractography of kidney by high angular resolution diffusion imaging

Abstract

Diffusion magnetic resonance imaging (MRI) has been utilized to probe the renal microstructures but investigating the three-dimensional (3D) tubular network still presents significant challenges due to the complicated architecture of kidney. This study aims to assess whether high angular resolution diffusion imaging (HARDI) could improve the reconstruction of 3D tubular architectures. Kidneys from both mice and rats were imaged using 3D diffusion-weighted pulse sequences at 9.4 T. Five healthy mouse kidneys were scanned at an isotropic spatial resolution of 40 μm, with a b value of 1500 s/mm² across 46 diffusion encoding directions. The study employed diffusion tensor imaging (DTI) and generalized Q-sampling imaging (GQI) to examine the tubular orientation distributions and tractography, validated by conventional histology. Fractional anisotropy (FA) and mean diffusivity (MD) were quantified and compared among the inner medullar (IM), outer medullar (OM), and cortex (CO) at different angular resolutions. FA values, estimated with 6 diffusion-weighted images (DWIs), were significantly overestimated by 49.9% (p < 0.001) in IM, 179.4% (p < 0.001) in OM, and 225.5% (p < 0.001) in CO, compared to using 46 DWIs. In contrast, MD exhibited less variations to angular resolution variations (3.4% in IM, 4.2% in OM, and 4.6% in CO). Both DTI and GQI at high angular resolution successfully traced renal tubular structures throughout the kidney, with GQI demonstrating superior performance in generating more continuous tracts. Furthermore, disrupted renal tubule structures were observed in a chronic kidney disease (CKD) rat model. HARDI, especially when combined with the GQI approach, holds promise in tracking complicated 3D tubule architectures and may serve as a potent tool for kidney disease research.

Keywords: CKD; DTI; GQI; HARDI; Kidney; MRI; Tractography.

Graphical abstract

Fig. 1

The representative DWI, MD, FA images of a mouse kidney. The kidney was segmented into three parts: inner medulla (IM, red), outer medulla (OM, green), and cortex (CO, blue). DWI: diffusion-weighted image; MD: mean diffusivity; FA: fractional anisotropy.

Fig. 2

The comparative representation of FA and MD maps of the kidney. This visualization incorporates results from 6, 12, 24, 36, and 46 DWIs. The FA values were higher with 6 DWIs (red arrows in IM). In contrast, the MD maps (purple arrows in IM) showed less variation. IM: internal medullar; DWI: diffusion-weighted image; FA: fractional anisotropy; MD: mean diffusivity.

Fig. 3

The FA and MD profiles of IM (a, d), OM (b, e), and CO (c, f) at different DWIs. Compared to the FA values with 46 DWIs (the ground truth), significantly higher FA values were found with low DWIs. The MD values reached a plateau when the DWIs were higher than 6. IM: inner medullar; OM: outer medullar; CO: cortex. ∗p < 0.05; ∗∗p < 0.001.

Fig. 4

Tractography results of the kidney at different DWIs (b-d, f-h) and different view angles (a, e). Tractography with higher DWIs showed more intact tracts (yellow arrows). Tractography failed with the minimum diffusion tensor imaging model requirement (6 DWIs).

Fig. 5

The track density imaging (TDI) derived from DTI and GQI models with 46 DWIs. Both DTI and GQI were able to track tubules throughout the kidney, while GQI provides more intact tracts in certain regions (green, red, and purple arrows).

Fig. 6

Imaging comparison for validation: hematoxylin and eosin staining (a), Masson's trichrome image (b), and mean diffusivity map (c). Few crossing fibers were resolved in the IM. The crossing fibers were dominated in the OM and CO. Compared to the IM (green arrows), the OM and CO showed more complicated tubule distributions in histology staining (black and white arrows).

Fig. 7

The structure (a, b) and tractography (c, d) differences in the control (CON) and chronic kidney disease (CKD) rat kidneys. Both renal structure (white and red arrows) and tractography are disrupted in the CKD kidneys as shown by yellow arrows.