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Multiparametric magnetic resonance imaging of experimental chronic kidney disease: A quantitative correlation study with histology.

ABSTRACT: OBJECTIVES:In human chronic kidney disease (CKD) the extent of renal tubulointerstitial fibrosis correlates with progressive loss of renal function. However, fibrosis can so far only be assessed by histology of kidney biopsies. Magnetic resonance imaging (MRI) can provide information about tissue architecture, but its potential to assess fibrosis and inflammation in diseased kidneys remains poorly defined. MATERIALS AND METHODS:We evaluated excised kidneys in a murine adenine-induced nephropathy model for CKD by MRI and correlated quantitative MRI parameters (T1, T2, and T2* relaxation times, apparent diffusion coefficient and fractional anisotropy) with histological hallmarks of progressive CKD, including renal fibrosis, inflammation, and microvascular rarefaction. Furthermore, we analyzed the effects of paraformaldehyde fixation on MRI parameters by comparing kidney samples before and after fixation with paraformaldehyde. RESULTS:In diseased kidneys T2 and T2* relaxation times, apparent diffusion coefficient and fractional anisotropy in the renal cortex and/or outer medulla were significantly different from those in control kidneys. In particular, T2 relaxation time was the best parameter to distinguish control and CKD groups and correlated very well with the extent of fibrosis, inflammatory infiltrates, tubular dilation, crystal deposition, and loss of peritubular capillaries and normal tubules in the renal cortex and outer medulla. Fixation with paraformaldehyde had no impact on T2 relaxation time and fractional anisotropy, whereas T1 times significantly decreased and T2* times and apparent diffusion coefficients increased in fixed kidney tissue. CONCLUSIONS:MRI parameters provide a promising approach to quantitatively assess renal fibrosis and inflammation in CKD. Especially T2 relaxation time correlates well with histological features of CKD and is not influenced by paraformaldehyde fixation of kidney samples. Thus, T2 relaxation time might be a candidate parameter for non-invasive assessment of renal fibrosis in human patients.

SUBMITTER: Schley G

PROVIDER: S-EPMC6047786 | biostudies-literature | 2018

REPOSITORIES: biostudies-literature

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Multiparametric magnetic resonance imaging of experimental chronic kidney disease: A quantitative correlation study with histology.

Schley Gunnar G Jordan Jutta J Ellmann Stephan S Rosen Seymour S Eckardt Kai-Uwe KU Uder Michael M Willam Carsten C Bäuerle Tobias T

PloS one 20180716 7

<h4>Objectives</h4>In human chronic kidney disease (CKD) the extent of renal tubulointerstitial fibrosis correlates with progressive loss of renal function. However, fibrosis can so far only be assessed by histology of kidney biopsies. Magnetic resonance imaging (MRI) can provide information about tissue architecture, but its potential to assess fibrosis and inflammation in diseased kidneys remains poorly defined.<h4>Materials and methods</h4>We evaluated excised kidneys in a murine adenine-indu ...[more]

PMID: 30011301

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Project description:PurposeThe clinical utility of multiparametric magnetic resonance imaging (mpMRI) for the detection and localization of prostate cancer (PCa) has been evaluated and validated. However, the implementation of mpMRI into the clinical practice remains some burden of cost and availability for patients and society. We aimed to predict the results of prostate mpMRI using the clinical parameters and multivariable model to reduce unnecessary mpMRI scans.MethodsWe retrospectively identified 784 men who underwent mpMRI scans and subsequent prostate biopsy between 2016 and 2020 according to the inclusion criterion. The cohort was split into a training cohort of 548 (70%) patients and a validation cohort of 236 (30%) patients. Clinical parameters including age, prostate-specific antigen (PSA) derivates, and prostate volume (PV) were assessed as the predictors of mpMRI results. The mpMRI results were divided into groups according to the reports: "negative", "equivocal", and "suspicious" for the presence of PCa.ResultsUnivariate analysis showed that the total PSA (tPSA), free PSA (fPSA), PV, and PSA density (PSAD) were significant predictors for suspicious mpMRI (P < 0.05). The PSAD (AUC = 0.77) and tPSA (AUC = 0.74) outperformed fPSA (AUC = 0.68) and PV (AUC = 0.62) in the prediction of the mpMRI results. The multivariate model (AUC = 0.80) had a similar diagnostic accuracy with PSAD (P = 0.108), while higher than tPSA (P = 0.024) in predicting the mpMRI results. The multivariate model illustrated a better calibration and substantial improvement in the decision curve analysis (DCA) at a threshold above 20%. Using the PSAD with a 0.13 ng/ml2 cut-off could spare the number of mpMRI scans by 20%, keeping a 90% sensitivity in the prediction of suspicious MRI-PCa and missing three (3/73, 4%) clinically significant PCa cases. At the same sensitivity level, the multivariate model with a 32% cut-off could spare the number of mpMRI scans by 27%, missing only one (1/73, 1%) clinically significant PCa case.ConclusionOur multivariate model could reduce the number of unnecessary mpMRI scans without comprising the diagnostic ability of clinically significant PCa. Further prospective validation is required.

Project description:Background:Current magnetic resonance imaging (MRI) of pancreatic disease is qualitative in nature. Quantitative imaging offers several advantages, including increased reproducibility and sensitivity to detect mild or diffuse disease. The role of multiparametric mapping MRI in characterizing various tissue types in pancreatic disease such as chronic pancreatitis (CP) and pancreatic ductal adenocarcinoma (PDAC) has rarely been evaluated. Purpose:To evaluate the feasibility of multiparametric mapping [T1, T2, and apparent diffusion coefficient (ADC)] in defining tissue characteristics that occur in CP and PDAC to improve disease diagnosis. Materials and Methods:Pancreatic MRI was performed in 17 patients with PDAC undergoing therapy, 7 patients with CP, and 29 healthy volunteers with no pancreatic disease. T1 modified Look-Locker Inversion Recovery (T1 MOLLI), T2-prepared gradient-echo, and multi-slice single-shot echo-planar diffusion weighted imaging (SS-EPI DWI) sequences were used for data acquisition. Regions of interest (ROIs) of pancreas in PDAC, CP, and control subjects were outlined by an experienced radiologist. One-way analysis of variance (ANOVA) was used to compare the difference between groups and regions of the pancreas, and Tukey tests were used for multiple comparison testing within groups. Receiver operator characteristic (ROC) curves were analyzed, and the areas under the curves (AUCs) were calculated using single parameter and combined parameters, respectively. Results:T1, T2, and ADC values of the entire pancreas among PDAC, CP, and control subjects; and between upstream and downstream portions of the pancreas in PDAC patients were all significantly different (p < 0.05). The AUC values were 0.90 for T1, 0.55 for T2, and 0.71 for ADC for independent prediction of PDAC. By combining T1, T2, and ADC, the AUC value was 0.94 (sensitivity 91.54%, specificity 85.81%, 95% CI: 0.92-0.96), which yielded higher accuracy than any one parameter only (p < 0.001). Conclusion:Multiparametric mapping MRI is feasible for the evaluation of the differences between PDAC, CP, and normal pancreas tissues. The combination of multiple parameters of T1, T2, and ADC provides a higher accuracy than any single parameter alone in tissue characterization of the pancreas.

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Multiparametric magnetic resonance imaging of experimental chronic kidney disease: A quantitative correlation study with histology.

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Multiparametric magnetic resonance imaging of experimental chronic kidney disease: A quantitative correlation study with histology.

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