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Multiparametric magnetic resonance imaging shows promising results to assess renal transplant dysfunction with fibrosis.

ABSTRACT: Here we assessed the diagnostic value of a quantitative multiparametric magnetic resonance imaging (mpMRI) protocol for evaluation of renal allograft dysfunction with fibrosis. Twenty-seven renal transplant patients, including 15 with stable functional allografts (eGFR mean 71.5 ml/min/1.73m²), and 12 with chronic dysfunction/established fibrosis (eGFR mean 30.1 ml/min/1.73m²), were enrolled in this prospective single-center study. Sixteen of the patients had renal biopsy (mean 150 days) before the MRI. All patients underwent mpMRI at 1.5T including intravoxel-incoherent motion diffusion-weighted imaging, diffusion tensor imaging, blood oxygen level dependent (BOLD R₂*) and T₁ quantification. True diffusion D, pseudodiffusion D*, perfusion fraction PF, apparent diffusion coefficient (ADC), fractional anisotropy (FA), R₂* and T₁ were calculated for cortex and medulla. ?T₁ was calculated as (100x(T₁ Cortex-T₁ Medulla)/T₁ Cortex). Test-retest repeatability and inter-observer reproducibility were assessed in four and ten patients, respectively. mpMRI parameters had substantial test-retest and interobserver repeatability (coefficient of variation under 15%), except for medullary PF and D* (coefficient of variation over 25%). Cortical ADC, D, medullary ADC and ?T₁ were all significantly decreased, while cortical T₁ was significantly elevated in fibrotic allografts. Cortical T₁ showed positive correlation to the Banff fibrosis and tubular atrophy scores. The combination of ?T₁ and cortical ADC had excellent cross-validated diagnostic performance for detection of chronic dysfunction with fibrosis. Cortical ADC and T₁ had good performance for predicting eGFR decline at 18 months (4 or more ml/min/1.73m²/year). Thus, the combination of cortical ADC and T₁ measurements shows promising results for the non-invasive assessment of renal allograft histology and outcomes.

SUBMITTER: Bane O

PROVIDER: S-EPMC6983343 | biostudies-literature | 2020 Feb

REPOSITORIES: biostudies-literature

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Multiparametric magnetic resonance imaging shows promising results to assess renal transplant dysfunction with fibrosis.

Bane Octavia O Hectors Stefanie J SJ Gordic Sonja S Kennedy Paul P Wagner Mathilde M Weiss Amanda A Khaim Rafael R Yi Zhengzi Z Zhang Weijia W Delaney Veronica V Salem Fadi F He Cijiang C Menon Madhav C MC Lewis Sara S Taouli Bachir B

Kidney international 20191030 2

Here we assessed the diagnostic value of a quantitative multiparametric magnetic resonance imaging (mpMRI) protocol for evaluation of renal allograft dysfunction with fibrosis. Twenty-seven renal transplant patients, including 15 with stable functional allografts (eGFR mean 71.5 ml/min/1.73m<sup>2</sup>), and 12 with chronic dysfunction/established fibrosis (eGFR mean 30.1 ml/min/1.73m<sup>2</sup>), were enrolled in this prospective single-center study. Sixteen of the patients had renal biopsy ( ...[more]

PMID: 31874802

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Project description:BACKGROUND AND OBJECTIVES:Fibrosis is a major cause of kidney allograft injury. Currently, the only means of assessing allograft fibrosis is by biopsy, an invasive procedure that samples <1% of the kidney. We examined whether magnetic resonance elastography, an imaging-based measure of organ stiffness, could noninvasively estimate allograft fibrosis and predict progression of allograft dysfunction. DESIGN, SETTING, PARTICIPANTS, & MEASUREMENTS:Kidney allograft recipients >1 year post-transplant undergoing an allograft biopsy first underwent free-breathing, flow-compensated magnetic resonance elastography on a 3.0-T magnetic resonance imaging scanner. Each patient had serial eGFR measurements after the elastography scan for a follow-up period of up to 1 year. The mean stiffness value of the kidney allograft was compared with both the histopathologic Banff fibrosis score and the rate of eGFR change during the follow-up period. RESULTS:Sixteen patients who underwent magnetic resonance elastography and biopsy were studied (mean age: 54±9 years old). Whole-kidney mean stiffness ranged between 3.5 and 7.3 kPa. Whole-kidney stiffness correlated with biopsy-derived Banff fibrosis score (Spearman rho =0.67; P<0.01). Stiffness was heterogeneously distributed within each kidney, providing a possible explanation for the lack of a stronger stiffness-fibrosis correlation. We also found negative correlations between whole-kidney stiffness and both baseline eGFR (Spearman rho =-0.65; P<0.01) and eGFR change over time (Spearman rho =-0.70; P<0.01). Irrespective of the baseline eGFR, increased kidney stiffness was associated with a greater eGFR decline (regression r2=0.48; P=0.03). CONCLUSIONS:Given the limitations of allograft biopsy, our pilot study suggests the potential for magnetic resonance elastography as a novel noninvasive measure of whole-allograft fibrosis burden that may predict future changes in kidney function. Future studies exploring the utility and accuracy of magnetic resonance elastography are needed.

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:BackgroundRenal fibrosis is a key driver of progression in chronic kidney disease (CKD). Recent advances in diagnostic imaging techniques have shown promising results for the noninvasive assessment of renal fibrosis. However, the specificity and accuracy of these techniques are controversial because they indirectly assess renal fibrosis. This limits fibrosis assessment by imaging in CKD for clinical practice. To validate magnetic resonance imaging (MRI) assessment for fibrosis, we derived representative models by mapping histology-proven renal fibrosis and imaging in CKD.MethodsNinety-seven adult Chinese CKD participants with histology were studied. The kidney cortex interstitial extracellular matrix volume was calculated by the Aperio ScanScope system using Masson's trichrome slices. The kidney cortex microcirculation was quantitatively assessed by peritubular capillary density using CD34 staining. The imaging techniques included intravoxel incoherent motion diffusion-weighted imaging and magnetic resonance elastography (MRE) imaging. Relevant analyses were performed to evaluate the correlations between MRI parameters and histology variables. Multiple linear regression models were used to describe the relationships between a response variable and other variables. The best-fit lines, which minimize the sum of squared residuals of the multiple linear regression models, were generated.ResultsMRE values were negatively associated with the interstitial extracellular matrix volume (Rho = -0.397, p < 0.001). The best mapping model of extracellular matrix volume with the MRE value and estimated glomerular filtration rate (eGFR) we obtained was as follows: Interstitial extracellular matrix volume = 218.504 - 14.651 × In(MRE) - 18.499 × In(eGFR). DWI-fraction values were positively associated with peritubular capillary density (Rho = 0.472, p < 0.001). The best mapping model of peritubular capillary density with DWI-fraction value and eGFR was as follows: Peritubular capillaries density = 17.914 + 9.403 × (DWI - fraction) + 0.112 × (eGFR).ConclusionsThe study provides histological evidence to support that MRI can effectively evaluate fibrosis in the kidney. These findings picture the graphs of the mapping model from imaging and eGFR into fibrosis, which has significant value for clinical implementation.

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.

Project description:ObjectivesSolid renal masses have unknown malignant potential with commonly utilized imaging. Biopsy can offer a diagnosis of cancer but has a high non-diagnostic rate and complications. Reported use of multiparametric magnetic resonance imaging (mpMRI) to diagnose aggressive histology (i.e., clear cell renal cell carcinoma (ccRCC)) via a clear cell likelihood score (ccLS) was based on retrospective review of cT1a tumors. We aim to retrospectively assess the diagnostic performance of ccLS prospectively assigned to renal masses of all stages evaluated with mpMRI prior to histopathologic evaluation.MethodsIn this retrospective cohort study from June 2016 to November 2019, 434 patients with 454 renal masses from 2 institutions with heterogenous patient populations underwent mpMRI with prospective ccLS assignment and had pathologic diagnosis. ccLS performance was assessed by contingency table analysis. The association between ccLS and ccRCC was assessed with logistic regression.ResultsMean age and tumor size were 60 ± 13 years and 5.4 ± 3.8 cm. Characteristics were similar between institutions except for patient age and race (both p < 0.001) and lesion laterality and histology (both p = 0.04). The PPV of ccLS increased with each increment in ccLS (ccLS1 5% [3/55], ccLS2 6% [3/47], ccLS3 35% [20/57], ccLS4 78% [85/109], ccLS5 93% [173/186]). Pooled analysis for ccRCC diagnosis revealed sensitivity 91% (258/284), PPV 87% (258/295) for ccLS ≥ 4, and specificity 56% (96/170), NPV 94% (96/102) for ccLS ≤ 2. Diagnostic performance was similar between institutions.ConclusionsWe confirm the optimal diagnostic performance of mpMRI to identify ccRCC in all clinical stages. High PPV and NPV of ccLS can help inform clinical management decision-making.Key points• The positive predictive value of the clear cell likelihood score (ccLS) for detecting clear cell renal cell carcinoma was 5% (ccLS1), 6% (ccLS2), 35% (ccLS3), 78% (ccLS4), and 93% (ccLS5). Sensitivity of ccLS ≥ 4 and specificity of ccLS ≤ 2 were 91% and 56%, respectively. • When controlling for confounding variables, ccLS is an independent risk factor for identifying clear cell renal cell carcinoma. • Utilization of the ccLS can help guide clinical care, including the decision for renal mass biopsy, reducing the morbidity and risk to patients.

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Multiparametric magnetic resonance imaging shows promising results to assess renal transplant dysfunction with fibrosis.

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Multiparametric magnetic resonance imaging shows promising results to assess renal transplant dysfunction with fibrosis.

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