scholarly journals Diffusion tensor imaging in renal artery stenosis: a preliminary report

2020 ◽  
Vol 93 (1115) ◽  
pp. 20200101
Author(s):  
Caterina Gaudiano ◽  
Valeria Clementi ◽  
Beniamino Corcioni ◽  
Matteo Renzulli ◽  
Elena Mancini ◽  
...  

Objective: To investigate the diffusion properties in the kidneys affected by renal artery stenosis (RAS) using diffusion tensor imaging (DTI). Methods: In this prospective study, 35 patients with RAS and 15 patients without renal abnormalities were enrolled and examined using DTI. Cortical and medullary regions of interest (ROIs) were located to obtain the corresponding values of the apparent diffusion coefficient (ADC) and fractional anisotropy (FA). The cortical and medullary ADC and FA were compared in the kidney affected by variable degrees of stenosis (RAS 50–75% and >75%) vs controls, using the one-way ANOVA and Student’s t-test. The Spearman correlation test was used to correlate the mean ADC and FA values in the cortex and medulla with the estimate glomerular filtration rate (eGFR). Results: For the controls, the ADC value was significantly (p = 0.03) higher in the cortex than in the medulla; the FA value was significantly (p = 0.001) higher in the medulla than in the cortex. Compared with the controls, a significant reduction in the cortical ADC was present with a RAS of 50–75% and >75% (p = 0.001 and 0.041, respectively); a significant reduction in the medullary FA was verified only for RAS >75% (p = 0.023). The Spearman correlation test did not show a statistically significant correlation between the cortical and medullary ADC and FA, and the eGFR. Conclusion: The alterations of the diffusional parameters caused by RAS can be detected by DTI and could be useful in the diagnostic evaluation of these patients. Advances in knowledge: 1. Magnetic resonance DTI could provide useful information about renal involvement in RAS. 2. Magnetic resonance DTI allows non-invasive repeatable evaluation of the renal parenchyma, without contrast media.

2002 ◽  
Vol 13 (1) ◽  
pp. 158-169
Author(s):  
Stefan O. Schoenberg ◽  
Michael V. Knopp ◽  
Frank Londy ◽  
Sumati Krishnan ◽  
Ivan Zuna ◽  
...  

ABSTRACT. The effect of combined morphologic and functional magnetic resonance (MR) imaging on the interobserver and intermodality variability for the grading of renal artery stenosis is assessed. In a randomized, blinded tricenter analysis, seven readers evaluated 43 renal arteries on x-ray digital subtraction angiography (DSA), 3D-Gadolinium MR angiography (3D-Gd-MRA), cine phase-contrast flow measurement (PC-flow), and a combined analysis of the last two. Interobserver variability was assessed for the grading of renal artery stenosis as well as regional vessel visibility. Intermodality variability for stenosis grading was analyzed in cases in which the readers agreed on the degree of stenosis in DSA. DSA had a substantial interobserver variability for the grading of stenosis (mean κ κ 0.64). 3D-Gd-MRA revealed a slightly improved interobserver variability but incorrectly graded 6 of 34 stenoses on a two-point scale (<50%, ≥50%). The combined approach of 3D-Gd-MRA and PC-flow revealed the best (P = 0.0003) interobserver variability (median κ = 0.75) and almost perfect intermodality agreement with DSA (97% of cases). These findings were confirmed in a prospective analysis of 97 renal arteries. The vessel visibility of the renal artery ostium was significantly better in 3D-Gd-MRA than in DSA, whereas the visibility of the hilar and intrarenal vessels was significantly worse (P = 0.0001). A combined morphologic and functional MR examination significantly reduces interobserver variability and offers reliable and reproducible grading of renal artery stenosis based on stenosis morphology and hemodynamic changes. It can be considered a safe and noninvasive alternative for diagnostic DSA in cases that do not require assessment of intrarenal vessels.


1996 ◽  
Vol 14 (9) ◽  
pp. 1033-1041 ◽  
Author(s):  
Jean-Pierre Laissy ◽  
Mourad Benyounes ◽  
Olivier Limot ◽  
Anne Cinqualbre ◽  
Hakim Benamer ◽  
...  

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