Renal fibrosis detected by diffusion-weighted magnetic resonance imaging remains unchanged despite treatment in subjects with renovascular disease

Ferguson, Christopher M.; Eirin, Alfonso; Abumoawad, Abdelrhman; Saad, Ahmed; Jiang, Kai; Hedayat, Ahmad F.; Misra, Sanjay; Glockner, James F.; Textor, Stephen C.; Lerman, Lilach O.

doi:10.1038/s41598-020-73202-0

Cited by 7 publications

(6 citation statements)

References 27 publications

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“…CKD of most origins is marked by fibrosis in addition to reduced glomerular filtration, which contributes to a decrease in the tubular volume fraction (46). In addition to pathological changes in the tubular volume, our simulations revealed that NNLS continuum modelling for renal DWI may also be useful for detection and treatment monitoring of renal fibrosis, which is an important biomarker of CKD and a powerful predictor of renal outcome (26,28). These same considerations likely apply to pathologies such as kidney lesions, polycystic kidney disease, or tumors.…”

Section: Discussionmentioning

confidence: 84%

“…Tubular atrophy and interstitial fibrosis play a major role in the microstructural changes occurring during kidney pathology e.g., renal allograft injury (24). Being able to assess renal fibrosis and alterations in the tubular volume fraction with non-invasive MRI would be clinically valuable (3,7,22,23,(25)(26)(27)(28). Second, as the renal capsule is comparatively rigid, changes in the tubular volume fraction will result in opposite changes in the renal blood volume fraction, thereby confounding the relationship between renal blood oxygenation leveldependent (BOLD) T 2 *, oxygen saturation of hemoglobin, and tissue partial pressure of oxygen (21,29).…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Continuous diffusion spectrum computation for diffusion-weighted magnetic resonance imaging of the kidney tubule system

Periquito¹,

Gladytz²,

Millward³

et al. 2021

Quant Imaging Med Surg

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Background: The use of rigid multi-exponential models (with a priori predefined numbers of components) is common practice for diffusion-weighted MRI (DWI) analysis of the kidney. This approach may not accurately reflect renal microstructure, as the data are forced to conform to the a priori assumptions of simplified models. This work examines the feasibility of less constrained, data-driven non-negative least squares (NNLS) continuum modelling for DWI of the kidney tubule system in simulations that include emulations of pathophysiological conditions.Methods: Non-linear least squares (LS) fitting was used as reference for the simulations. For performance assessment, a threshold of 5% or 10% for the mean absolute percentage error (MAPE) of NNLS and LS results was used. As ground truth, a tri-exponential model using defined volume fractions and diffusion coefficients for each renal compartment (tubule system: D tubules , f tubules ; renal tissue: D tissue , f tissue ; renal blood: D blood , f blood ;) was applied. The impact of: (I) signal-to-noise ratio (SNR) =40-1,000, (II) number of b-values (n=10-50), (III) diffusion weighting (b-range small =0-800 up to b-range large =0-2,180 s/mm 2 ), and (IV) fixation of the diffusion coefficients D tissue and D blood was examined. NNLS was evaluated for baseline and pathophysiological conditions, namely increased tubular volume fraction (ITV) and renal fibrosis (10%: grade I, mild) and 30% (grade II, moderate).Results: NNLS showed the same high degree of reliability as the non-linear LS. MAPE of the tubular volume fraction (f tubules ) decreased with increasing SNR. Increasing the number of b-values was beneficial for f tubules precision. Using the b-range large led to a decrease in MAPE ftubules compared to b-range small . The use of a medium b-value range of b=0-1,380 s/mm 2 improved f tubules precision, and further b max increases beyond this range yielded diminishing improvements. Fixing D blood and D tissue significantly reduced MAPE ftubules and provided near perfect distinction between baseline and ITV conditions. Without constraining the number of renal compartments in advance, NNLS was able to detect the (fourth) fibrotic compartment, to differentiate it from the other three diffusion components, and to distinguish between 10% vs. 30% fibrosis.Conclusions: This work demonstrates the feasibility of NNLS modelling for DWI of the kidney tubule

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Section: Discussionmentioning

confidence: 84%

Section: Introductionmentioning

confidence: 99%

Continuous diffusion spectrum computation for diffusion-weighted magnetic resonance imaging of the kidney tubule system

Periquito¹,

Gladytz²,

Millward³

et al. 2021

Quant Imaging Med Surg

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show abstract

“…Renal ADC has been shown to correlate with interstitial fibrosis in several studies [147][148][149], although less is known about the exact underlying processes affecting the DWI signal [150]. The correlation between ADC and established biochemical biomarkers of kidney function and damage (i.e., GFR and UACR) in DKD patients has been confirmed in the univariate analysis of Makvandi et al [48].…”

Section: Dwimentioning

confidence: 91%

“…By adding mGFR as one variable, however, ADC was no longer significant in the bivariate prediction of UACR, suggesting that ADC could be linked to UACR via its effect on GFR. Interestingly, the ADC remained unchanged during 3 months of therapy in patients with renovascular disease and mild fibrosis and did not correlate with eGFR, serum creatinine, renal hypoxia, or inflammation, which could suggest that these factors are not captured in the ADC values [147]. In a sub-study of the COMBINE trial, baseline cortical ADC significantly correlated with the annual, patient-specific eGFR slope over 12 months (p = 0.08), although this was no longer significant once albuminuria was adjusted for, suggesting that there is either overlapping information between ADC and traditional risk factors for CKD progression, or albuminuria is a causal pathway to CKD progression [151].…”

Section: Dwimentioning

confidence: 97%

Magnetic Resonance Imaging in Clinical Trials of Diabetic Kidney Disease

Friedli

Baid-Agrawal

Unwin

et al. 2023

JCM

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Chronic kidney disease (CKD) associated with diabetes mellitus (DM) (known as diabetic kidney disease, DKD) is a serious and growing healthcare problem worldwide. In DM patients, DKD is generally diagnosed based on the presence of albuminuria and a reduced glomerular filtration rate. Diagnosis rarely includes an invasive kidney biopsy, although DKD has some characteristic histological features, and kidney fibrosis and nephron loss cause disease progression that eventually ends in kidney failure. Alternative sensitive and reliable non-invasive biomarkers are needed for DKD (and CKD in general) to improve timely diagnosis and aid disease monitoring without the need for a kidney biopsy. Such biomarkers may also serve as endpoints in clinical trials of new treatments. Non-invasive magnetic resonance imaging (MRI), particularly multiparametric MRI, may achieve these goals. In this article, we review emerging data on MRI techniques and their scientific, clinical, and economic value in DKD/CKD for diagnosis, assessment of disease pathogenesis and progression, and as potential biomarkers for clinical trial use that may also increase our understanding of the efficacy and mode(s) of action of potential DKD therapeutic interventions. We also consider how multi-site MRI studies are conducted and the challenges that should be addressed to increase wider application of MRI in DKD.

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“…Diffusion-weighted imaging (DWI)-MRI is capable of estimating ischemia/reperfusion injury delaying graft function, 54 but it cannot predict renal artery revascularization success. 55 Very recent developments include hyperpolarized-[1- 13 C]pyruvate imaging, allowing evaluation of metabolic status directly in ischemic kidneys 56 and MRI-CEST (chemical-exchange-saturation-transfer) pH-mapping to evaluate both acid-base homeostasis and renal filtration. 57 Viability.…”

Section: Oxygenationmentioning

confidence: 99%