Fast diffusion kurtosis imaging of fibrotic mouse kidneys

Renal interstitial fibrotic assessment using non-Gaussian diffusion kurtosis imaging in a rat model of hyperuricemia

BACKGROUND

To investigate the feasibility of Diffusion Kurtosis Imaging (DKI) in assessing renal interstitial fibrosis induced by hyperuricemia.

METHODS

A hyperuricemia rat model was established, and the rats were randomly split into the hyperuricemia (HUA), allopurinol (AP), and AP + empagliflozin (AP + EM) groups (n = 19 per group). Also, the normal rats were selected as controls (CON, n = 19). DKI was performed before treatment (baseline) and on days 1, 3, 5, 7, and 9 days after treatment. The DKI indicators, including mean kurtosis (MK), fractional anisotropy (FA), and mean diffusivity (MD) of the cortex (CO), outer stripe of the outer medulla (OS), and inner stripe of the outer medulla (IS) were acquired. Additionally, hematoxylin and eosin (H&E) staining, Masson trichrome staining, and nuclear factor kappa B (NF-κB) immunostaining were used to reveal renal histopathological changes at baseline, 1, 5, and 9 days after treatment.

RESULTS

The HUA, AP, and AP + EM group MKOS and MKIS values gradually increased during this study. The HUA group exhibited the highest MK value in outer medulla. Except for the CON group, all the groups showed a decreasing trend in the FA and MD values of outer medulla. The HUA group exhibited the lowest FA and MD values. The MKOS and MKIS values were positively correlated with Masson's trichrome staining results (r = 0.687, P < 0.001 and r = 0.604, P = 0.001, respectively). The MDOS and FAIS were negatively correlated with Masson's trichrome staining (r = -626, P < 0.0014 and r = -0.468, P = 0.01, respectively).

CONCLUSION

DKI may be a non-invasive method for monitoring renal interstitial fibrosis induced by hyperuricemia.

Based on functional and histopathological correlations: is diffusion kurtosis imaging valuable for noninvasive assessment of renal damage in early-stage of chronic kidney disease?

PURPOSE

To evaluate the potential of 3 T magnetic resonance diffusion kurtosis imaging (DKI) in assessing the renal damage in early-stage of chronic kidney disease (CKD) patients with normal or slightly changed functional index, using histopathology as reference standard.

METHODS

49 CKD patients and 18 healthy volunteers were recruited in this study. CKD patients were divided into two groups based on estimated glomerular filtration rate (eGFR): Study group I (eGFR ≥ 90 ml/min/1.73 m2 [n = 20]) and Study group II (eGFR < 90 ml/min/1.73 m2 [n = 29]). DKI was performed in all participants. The DKI parameters (mean kurtosis [MK], mean diffusivity [MD], fractional anisotropy [FA]) of renal cortex and medulla were measured. The differences of parenchymal MD, MK and FA values among the different groups were compared. The correlations between DKI parameters and clinicopathological characteristics were assessed. Diagnostic performance of DKI to assess renal damage in early-stage of CKD was analyzed.

RESULTS

The cortex MD and MK showed significant difference among three groups (P < 0.05): trend of cortex MD: Study group II < Study group I < control group; trend of cortex MK: control group < Study group I < Study group II. The cortex MD and MK and medulla FA were correlated with eGFR and Interstitial fibrosis/Tubular atrophy score (0.3 < r < 0.5). Cortex MD and MK yielded an AUC of 0.752 for differentiating healthy volunteers from CKD patients with eGFR ≥ 90 ml/min/1.73 m2.

CONCLUSION

DKI shows potential in non-invasive and multi-parameter quantitative assessment of renal damage in early-stage of CKD patients and provide additional information for changes in renal function and histopathology.

Early assessment of acute kidney injury in severe acute pancreatitis with multimodal DWI: an animal model

OBJECTIVES

To evaluate the feasibility of multimodal diffusion-weighted imaging (DWI) for detecting the occurrence and severity of acute kidney injury (AKI) caused by severe acute pancreatitis (SAP) in rats.

METHODS

SAP was induced in thirty rats by the retrograde injection of 5.0% sodium taurocholate through the biliopancreatic duct. Six rats underwent MRI of the kidneys 24 h before and 2, 4, 6, and 8 h after this AKI model was generated. Conventional and functional MRI sequences were used, including intravoxel incoherent motion imaging (IVIM), diffusion tensor imaging (DTI), and diffusion kurtosis imaging (DTI). The main DWI parameters and histological results were analyzed.

RESULTS

The fast apparent diffusion coefficient (ADC) of the renal cortex was significantly reduced at 2 h, as was the fractional anisotropy (FA) value of the renal cortex on DTI. The mean kurtosis (MK) values for the renal cortex and medulla gradually increased after model generation. The renal histopathological score was negatively correlated with the medullary slow ADC, fast ADC, and perfusion scores for both the renal cortex and medulla, as were the ADC and FA values of the renal medulla in DTI, whereas the MK values of the cortex and medulla were positively correlated (r = 0.733, 0.812). Thus, the cortical fast ADC, medullary MK, FADTI, and slow ADC were optimal parameters for diagnosing AKI. Of these parameters, cortical fast ADC had the highest diagnostic efficacy (AUC = 0.950).

CONCLUSIONS

The fast ADC of the renal cortex is the core indicator of early AKI, and the medullary MK value might serve as a sensitive biomarker for grading renal injury in SAP rats.

CLINICAL RELEVANCE STATEMENT

The multimodal parameters of renal IVIM, DTI, and DKI are potential beneficial for the early diagnosis and severity grading of renal injury in SAP patients.

KEY POINTS

• The multimodal parameters of renal DWI, including IVIM, DTI, and DKI, may be valuable for the noninvasive detection of early AKI and the severity grading of renal injury in SAP rats. • Cortical fast ADC, medullary MK, FA, and slow ADC are optimal parameters for early diagnosis of AKI, and cortical fast ADC has the highest diagnostic efficacy. • Medullary fast ADC, MK, and FA as well as cortical MK are useful for predicting the severity grade of AKI, and the renal medullary MK value exhibits the strongest correlation with pathological scores.

Optimization of quasi-diffusion magnetic resonance imaging for quantitative accuracy and time-efficient acquisition

PURPOSE

Quasi-diffusion MRI (QDI) is a novel quantitative technique based on the continuous time random walk model of diffusion dynamics. QDI provides estimates of the diffusion coefficient, <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:semantics><mml:mrow><mml:mspace/> <mml:msub><mml:mi>D</mml:mi> <mml:mrow><mml:mn>1</mml:mn> <mml:mo>,</mml:mo> <mml:mn>2</mml:mn></mml:mrow> </mml:msub> </mml:mrow> <mml:annotation>$$ {D}_{1,2} $$</mml:annotation></mml:semantics> </mml:math> in mm²  s^-1 and a fractional exponent, <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:semantics><mml:mrow><mml:mi>α</mml:mi></mml:mrow> <mml:annotation>$$ \upalpha $$</mml:annotation></mml:semantics> </mml:math> , defining the non-Gaussianity of the diffusion signal decay. Here, the b-value selection for rapid clinical acquisition of QDI tensor imaging (QDTI) data is optimized.

METHODS

Clinically appropriate QDTI acquisitions were optimized in healthy volunteers with respect to a multi-b-value reference (MbR) dataset comprising 29 diffusion-sensitized images arrayed between <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:semantics><mml:mrow><mml:mi>b</mml:mi> <mml:mo>=</mml:mo> <mml:mn>0</mml:mn></mml:mrow> <mml:annotation>$$ b=0 $$</mml:annotation></mml:semantics> </mml:math> and 5000 s mm^-2 . The effects of varying maximum b-value ( <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:semantics> <mml:mrow><mml:msub><mml:mi>b</mml:mi> <mml:mi>max</mml:mi></mml:msub> </mml:mrow> <mml:annotation>$$ {b}_{\mathrm{max}} $$</mml:annotation></mml:semantics> </mml:math> ), number of b-value shells, and the effects of Rician noise were investigated.

RESULTS

QDTI measures showed <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:semantics> <mml:mrow><mml:msub><mml:mi>b</mml:mi> <mml:mi>max</mml:mi></mml:msub> </mml:mrow> <mml:annotation>$$ {b}_{\mathrm{max}} $$</mml:annotation></mml:semantics> </mml:math> dependence, most significantly for <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:semantics><mml:mrow><mml:mi>α</mml:mi></mml:mrow> <mml:annotation>$$ \upalpha $$</mml:annotation></mml:semantics> </mml:math> in white matter, which monotonically decreased with higher <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:semantics> <mml:mrow><mml:msub><mml:mi>b</mml:mi> <mml:mi>max</mml:mi></mml:msub> </mml:mrow> <mml:annotation>$$ {b}_{\mathrm{max}} $$</mml:annotation></mml:semantics> </mml:math> leading to improved tissue contrast. Optimized 2 b-value shell acquisitions showed small systematic differences in QDTI measures relative to MbR values, with overestimation of <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:semantics><mml:mrow><mml:mspace/> <mml:mspace/> <mml:msub><mml:mi>D</mml:mi> <mml:mrow><mml:mn>1</mml:mn> <mml:mo>,</mml:mo> <mml:mn>2</mml:mn></mml:mrow> </mml:msub> </mml:mrow> <mml:annotation>$$ \kern0.50em {D}_{1,2} $$</mml:annotation></mml:semantics> </mml:math> and underestimation of <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:semantics><mml:mrow><mml:mi>α</mml:mi></mml:mrow> <mml:annotation>$$ \upalpha $$</mml:annotation></mml:semantics> </mml:math> in white matter, and overestimation of <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:semantics> <mml:mrow><mml:msub><mml:mi>D</mml:mi> <mml:mrow><mml:mn>1</mml:mn> <mml:mo>,</mml:mo> <mml:mn>2</mml:mn></mml:mrow> </mml:msub> </mml:mrow> <mml:annotation>$$ {D}_{1,2} $$</mml:annotation></mml:semantics> </mml:math> and <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:semantics><mml:mrow><mml:mi>α</mml:mi></mml:mrow> <mml:annotation>$$ \upalpha $$</mml:annotation></mml:semantics> </mml:math> anisotropies in gray and white matter. Additional shells improved the accuracy, precision, and reliability of QDTI estimates with 3 and 4 shells at <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:semantics> <mml:mrow><mml:msub><mml:mi>b</mml:mi> <mml:mi>max</mml:mi></mml:msub> <mml:mo>=</mml:mo> <mml:mn>5000</mml:mn></mml:mrow> <mml:annotation>$$ {b}_{\mathrm{max}}=5000 $$</mml:annotation></mml:semantics> </mml:math>  s mm^-2 , and 4 b-value shells at <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:semantics> <mml:mrow><mml:msub><mml:mi>b</mml:mi> <mml:mi>max</mml:mi></mml:msub> <mml:mo>=</mml:mo> <mml:mn>3960</mml:mn></mml:mrow> <mml:annotation>$$ {b}_{\mathrm{max}}=3960 $$</mml:annotation></mml:semantics> </mml:math>  s mm^-2 , providing minimal bias in <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:semantics> <mml:mrow><mml:msub><mml:mi>D</mml:mi> <mml:mrow><mml:mn>1</mml:mn> <mml:mo>,</mml:mo> <mml:mn>2</mml:mn></mml:mrow> </mml:msub> </mml:mrow> <mml:annotation>$$ {D}_{1,2} $$</mml:annotation></mml:semantics> </mml:math> and <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:semantics><mml:mrow><mml:mi>α</mml:mi></mml:mrow> <mml:annotation>$$ \upalpha $$</mml:annotation></mml:semantics> </mml:math> compared to the MbR.

CONCLUSION

A highly detailed optimization of non-Gaussian dMRI for in vivo brain imaging was performed. QDI provided robust parameterization of non-Gaussian diffusion signal decay in clinically feasible imaging times with high reliability, accuracy, and precision of QDTI measures.

Diffusion-weighted magnetic resonance imaging in rat kidney using two-dimensional navigated, interleaved echo-planar imaging at 7.0 T

The purpose of this study was to investigate the feasibility of two-dimensional (2D) navigated, interleaved multishot echo-planar imaging (EPI) to enhance kidney diffusion-weighted imaging (DWI) in rats at 7.0 T. Fully sampled interleaved four-shot EPI with 2D navigators was tailored for kidney DWI (Sprague-Dawley rats, n = 7) on a 7.0-T small bore preclinical scanner. The image quality of four-shot EPI was compared with T₂ -weighted rapid acquisition with relaxation enhancement (RARE) (reference) and single-shot EPI (ss-EPI) without and with parallel imaging (PI). The contrast-to-noise ratio (CNR) was examined to assess the image quality for the EPI approaches. The Dice similarity coefficient and the Hausdorff distance were used for evaluation of image distortion. Mean diffusivity (MD) and fractional anisotropy (FA) were calculated for renal cortex and medulla for all DWI approaches. The corticomedullary difference of MD and FA were assessed by Wilcoxon signed-rank test. Four-shot EPI showed the highest CNR among the three EPI variants and lowest geometric distortion versus T₂ -weighted RARE (mean Dice: 0.77 for ss-EPI without PI, 0.88 for ss-EPI with twofold undersampling, and 0.92 for four-shot EPI). The FA map derived from four-shot EPI clearly identified a highly anisotropic region corresponding to the inner stripe of the outer medulla. Four-shot EPI successfully discerned differences in both MD and FA between renal cortex and medulla. In conclusion, 2D navigated, interleaved multishot EPI facilitates high-quality rat kidney DWI with clearly depicted intralayer and interlayer structure and substantially reduced image distortion. This approach enables the anatomic integrity of DWI-MRI in small rodents and has the potential to benefit the characterization of renal microstructure in preclinical studies.

Renal functional and interstitial fibrotic assessment with non-Gaussian diffusion kurtosis imaging

OBJECTIVES

To evaluate the application value of diffusion kurtosis imaging (DKI) for monitoring renal function and interstitial fibrosis.

METHODS

Forty-two patients suspected of having primary nephropathy, hypertension or diabetes with impaired renal function were examined with DKI. DKI metrics of renal cortex and medulla on both sides of each patient were measured, including mean kurtosis (MK), axial kurtosis (Ka), radial kurtosis (Kr), mean diffusivity (MD) and fractional anisotropy (FA). The differences in DKI metrics between stable and impaired estimated glomerular filtration rate (eGFR) patients as well as between mild and severe interstitial fibrosis patients were compared. Correlations of DKI metrics with clinical indicators and pathology were analyzed. Diagnostic performance of DKI to assess the degree of renal dysfunction was analyzed.

RESULTS

Cortical MK, parenchymal Ka, MD and medullary FA were different in stable vs impaired eGFR patients and mild vs severe interstitial fibrosis patients (all p < .05). Negative correlation was found between Ka and eGFR (cortex: r = - 0.579; medulla: r = - 0.603), between MD and interstitial fibrosis (cortex: r = - 0.899; medulla: r = - 0.770), and positive correlation was found between MD and eGFR (cortex: r = 0.411; medulla: r = 0.344), between Ka and interstitial fibrosis (cortex: r = 0.871; medulla: r = 0.844) (all p < .05). DKI combined with mean arterial blood pressure (MAP) and urea showed good diagnostic power for assessing the degree of renal dysfunction (sensitivity: 90.5%; specificity: 89.5%).

CONCLUSIONS

Noninvasive DKI has certain application value for monitoring renal function and interstitial fibrosis.

Diffusion kurtosis imaging and arterial spin labeling for the noninvasive evaluation of persistent post-contrast acute kidney injury

OBJECTIVE

We investigated whether diffusion kurtosis imaging (DKI) and arterial spin labeling (ASL) facilitated the assessment of serial alterations in persistent post-contrast acute kidney injury (PC-AKI).

MATERIALS AND METHODS

We randomly divided 24 rats into four PC-AKI groups (days 1, 3, 7, and 13, n = 6/group), with an additional six control animals. We conducted functional magnetic resonance imaging (MRI), diffusion kurtosis imaging (DKI), and arterial spin-labeling (ASL) analyses. Mean kurtosis (MK), axial kurtosis (Ka), mean diffusivity (MD), fractional anisotropy (FA), radial kurtosis (Kr), and renal blood flow (RBF) maps were normalized to baseline (prior to contrast injection) to calculate adjusted △RBF, △MK, △Ka, △MD, △FA, and △Kr values. We also investigated urinary neutrophil gelatinase associated lipocalin (NGAL), serum cystatin C (CysC), aquaporin-2 (AQP2), hypoxia-inducible factor-1 (HIF-1α), and histological indices.

RESULTS

In the inner stripe of the outer medulla, when compared with controls, decreased △FA and △MD levels were observed on days 1, 3, and 7, and a distinct elevation in △MK and △Kr on days 1-13, and a persistent decrease in △RBF on days 1-13, and a prominent increase in △Ka on days 7 and 13 in PC-AKI animals (all p < 0.05). △Ka and △MK were positively correlated with AQP-2 (r = 0.8086, p < 0.0001 and r = 0.7314, p < 0.0001, respectively), and △RBF was highly correlated with HIF-1α (r = -0.7592, p < 0.0001). Moreover, both CysC and NGAL were significantly elevated in PC-AKI animals when compared with controls from days 1-13 (all p < 0.05). Renal histological data indicated severe tubular and glomerular injury at days 1-13 in all PC-AKI groups.

CONCLUSION

ASL and DKI may be noninvasively and longitudinally used to detect PC-AKI and predict further outcomes.

Magnetic resonance quantification of non-Gaussian water diffusion in hepatic fibrosis staging: a pilot study of diffusion kurtosis imaging to identify reversible hepatic fibrosis

Background

This study aimed to evaluate the diagnostic accuracy of diffusion kurtosis imaging (DKI) in differentiating early hepatic fibrosis (HF) from normal liver and advanced HF in rabbits.

Methods

A total of 35 healthy New Zealand white rabbits were included in the study. A model of HF was established in 30 rabbits through subcutaneous injections of 50% carbon tetrachloride (CCl₄)/olive oil, while 5 rabbits received saline injections. The gradually increased doses of CCl₄ were 0.1, 0.2, and 0.3 mL/kg in weeks 1 to 3, weeks 4 to 6, and weeks 7 to 10, respectively. Two injections were given each week. Two rabbits in the experimental group died. All rabbits underwent DKI with three b values (0, 500, and 1,000 s/mm²) at week 5 (n=8), week 6 (n=9), week 7 (n=8), and week 10 (n=8). Approximately 2 liver lobes per rabbit were selected for histopathology. Mean diffusivity (MD) and mean kurtosis (MK) were calculated. Discrimination capacities of DKI parameters were analyzed and compared by receiver operating characteristic (ROC) analysis.

Results

The meta-analysis of histological data in viral hepatitis (METAVIR) scoring system was used to classify liver lobes into the control group (F0, n=0), early HF group (F1-F2, n=28), and advanced HF group (F3-F4, n=28). MD and MK values were significantly different among the three groups (all P<0.05). MD value was negatively correlated with increased fibrosis level, while MK value was positively correlated with increased fibrosis level (ρ=-0.540, 0.614; P<0.05). The area under ROC curves (AUCs) for MD and MK were 0.886 and 0.875, respectively, for characterization of F0 and F1-F2, and 0.975 and 0.957 for F0 and F3-F4. AUC for MK was 0.751 for characterization of F1-F2 and F3-F4. MD performed better than MK for characterization of F0 and F1-F2 as well as F0 and F3-F4. MK showed good differentiation performance between F1-F2 and F3-F4.

Conclusions

Our results showed that DKI contributed to discriminating reversible early HF from normal liver and advanced HF and as a result, showed promise for use in HF diagnosis.

Functional magnetic resonance imaging for distinguishing type of papillary renal cell carcinoma: a preliminary study

OBJECTIVE

To investigate the feasibility of magnetic resonance diffusion kurtosis imaging (DKI) and intravoxel incoherent motion (IVIM) for distinguishing Type 1 and 2 of papillary renal cell carcinoma (PRCC).

METHODS

A total of Type 1 (n = 20) and Type 2 (n = 16) of PRCC were examined by pathology. For DKI and IVIM, mean diffusivity (MD), fractional anisotropy (FA), mean kurtosis (MK), kurtosis anisotropy (KA), radial kurtosis (RK), diffusivity (D), pseudodiffusivity (D*) and perfusion fraction (f) were performed in assessment of type of PRCC.

RESULTS

The mean SNRs of IVIM and DKI images at b = 1500 and 2000 s/mm² were 8.6 ± 0.8 and 7.8 ± 0.6. Statistically significant differences were observed in MD and D values (1.11 ± 0.23 vs 0.73 ± 0.13, 0.91 ± 0.24 vs 0.49 ± 0.13, p < 0.05) between Type 1 and Type 2 of PRCC, while comparable FA, RK, D* and f values were found between Type 1 and Type 2 of PRCC (p > 0.05). Statistically significant differences were observed in MK and KA values (1.23 ± 0.16 vs 1.91 ± 0.26, 1.49 ± 0.19 vs 2.36 ± 0.39, p < 0.05) between Type 1 and Type 2 of PRCC. Areas of MD, MK, KA and D values under ROC curves for differentiating Type 1 and Type 2 of PRCC were 0.836, 0.818, 0.881 and 0.766, respectively. Using MD, MK, KA and D values of 0.93, 1.64, 1.94, 0.68 as the threshold value for differentiating Type 1 from Type 2 of PRCC, the best result obtained had a sensitivity of 85.0%, 80.0%, 90.0%, 85.0%, a specificity 75.0%, 68.7%, 87.5%, 81.2%, and an accuracy of 83.3%, 80.5%, 88.9%, 86.1%, respectively.

CONCLUSION

DKI and IVIM are feasible techniques for distinguishing type of PRCC, given an adequate SNR of IVIM and DKI images.

ADVANCES IN KNOWLEDGE

1. MD and D values are higher for Type 1 of PRCC and lower for Type 2 of PRCC.2. MK and KA values are higher for Type 2 of PRCC and lower for Type 1 of PRCC.3. DKI and IVIM can be used as clinical biomarker for PRCC type's differential diagnosis, given an adequate SNR.

Diffusion kurtosis imaging as an imaging biomarker for predicting prognosis in chronic kidney disease patients

BACKGROUND

Renal fibrosis is the strongest prognosis predictor of end-stage renal disease (ESRD) in chronic kidney disease (CKD). Diffusion kurtosis imaging (DKI) is a promising method of magnetic resonance imaging (MRI) successfully used to assess renal fibrosis in IgA nephropathy. This study first evaluated the long-term prognostic value of DKI in CKD patients.

METHODS

Forty-two patients with CKD were prospectively enrolled, and underwent DKI on a clinical 3 T MR scanner. We excluded patients with comorbidities that could affect the volume or the components of the kidney. DKI parameters, including mean kurtosis (K), mean diffusivity (D) and apparent diffusion coefficient (ADC) of kidney cortex were obtained by region-of-interest measurement. We followed up these patients for a median of 43 months and investigated the correlations between each DKI parameter and overall renal prognosis.

RESULTS

Both K and ADC values were correlated well with the eGFR on recruitment and the eGFR of the last visit in follow-up (p＜0.001). K and ADC values were also well associated with the eGFR slopes in CKD patients, both with the first-last time point slope (p = 0.011 and p＜0.001, respectively) and with the regression slope (p = 0.010 and p＜0.001, respectively). Cox proportional hazard regression indicated that lower eGFR and ADC values independently predicted eGFR loss of more than 30% and ESRD. The receiver operating characteristic analysis showed that K and ADC values were predictable for renal prognosis, and ADC displayed better capabilities for both ESRD (AUC 0.936, sensitivity 92.31%, specificity 82.76%) and the composite endpoint (eGFR loss>30% or ESRD) (AUC 0.881, sensitivity 66.67%, specificity 96.3%).

CONCLUSIONS

Renal ADC values obtained from DKI showed significant predictive value for the prognosis of CKD patients, which could be a promising noninvasive technique in follow-up.

Diffusion kurtosis imaging for the assessment of renal fibrosis of chronic kidney disease: A preliminary study

PURPOSE

To investigate the potential of diffusion kurtosis imaging (DKI) for the assessment of renal fibrosis in chronic kidney disease (CKD), using histopathology as the reference standard.

METHODS

Eighty-nine CKD patients and twenty healthy volunteers were recruited in this study. DKI was performed in all participants and all CKD patients received renal biopsy. The values of mean diffusivity (MD) and mean kurtosis (MK) in the renal cortex and medulla were compared between CKD patients and healthy volunteers. The Spearman correlation coefficient was calculated to assess the relationship between MD, MK values and the estimated glomerular filtration rate (eGFR), serum creatinine (SCr), 24 h urinary protein (24 h-UPRO), histopathological fibrosis score.

RESULTS

The medullary MD values were significantly lower than cortex, while the cortical MK values were significantly lower than medulla for all participants. Renal parenchymal MD values were significantly lower in the CKD patients than healthy controls, whereas MK values were significantly higher in the CKD patients than healthy controls. In the CKD patients, the significantly negative correlation was observed between the renal parenchymal MD values and the 24 h-UPRO, SCr, histopathological fibrosis score, as well as between the renal parenchymal MK values and the eGFR, while the significantly positive correlation was found between the renal parenchymal MD values and the eGFR, as well as between the renal parenchymal MK values and the 24 h-UPRO, SCr, histopathological fibrosis score.

CONCLUSION

DKI shows great potential in the noninvasive assessment of renal fibrosis in CKD.

Pathological assessment of chronic kidney disease with DWI: Is there an added value for diffusion kurtosis imaging?

BACKGROUND

Chronic kidney disease (CKD) is a worldwide health problem, precise functional and pathological assessment is beneficial to better treatment. Diffusion kurtosis imaging (DKI) can evaluate non-Gaussian diffusion and may help to assess renal pathology and function.

PURPOSE

To assess pathological and functional alterations in CKD using DKI compared with diffusion-weighted imaging (DWI).

STUDY TYPE

Prospective study.

POPULATION

70 CKD patients and 20 healthy volunteers.

FIELD STRENGTH

1.5 T.

ASSESSMENT

All participants underwent DKI, and apparent diffusion coefficient (ADC), mean diffusivity (MD), and mean kurtosis (MK) of renal parenchyma were acquired. Correlation between renal parenchymal ADC, MD, MK, and estimated glomerular filtration rate (eGFR), pathological scores were assessed. The diagnostic efficacy of ADC, MD, and MK for assessing the degree of renal pathological injury were compared.

STATISTICAL TESTS

ANOVA, Spearman correlation analysis, and ROC curve analysis.

RESULTS

The cortical ADC, MD were significantly higher than medulla for all participants, whereas medullary MK was significantly higher than cortex (P < 0.01). Whether eGFR reduced or not, renal parenchymal MK were significantly higher in patients than controls (P < 0.05). Positive correlation was found between eGFR and ADC (cortex, r = 0.562; medulla, r = 0.527), and negative correlation between eGFR and MK (cortex, r = -0.786; medulla, r = -0.709) (all P < 0.001). There was positive correlation between MK and glomerular injury (cortex, r = 0.681; medulla, r = 0.652), tubulointerstitial lesion (cortex, r = 0.650; medulla, r = 0.599) (all P < 0.001). For discrimination between mild and m-s renal injury group, the AUC values of ADC, MD, MK were cortex: 0.723, 0.655, 0.864 and medulla: 0.718, 0.581, 0.829. The AUC values of ADC, MD, MK were cortex: 0.708, 0.679, 0.770 and medulla: 0.713, 0.830, 0.780 for differentiating control group from mild renal injury group.

DATA CONCLUSION

DKI is practicable for noninvasive assessment of renal pathology and function of CKD, DKI offer better diagnostic performance than DWI. Evidence Level 1 Technical Efficacy 2.

Respiratory Motion Mitigation and Repeatability of Two Diffusion-Weighted MRI Methods Applied to a Murine Model of Spontaneous Pancreatic Cancer

Respiratory motion and increased susceptibility effects at high magnetic fields pose challenges for quantitative diffusion-weighted MRI (DWI) of a mouse abdomen on preclinical MRI systems. We demonstrate the first application of radial k-space-sampled (RAD) DWI of a mouse abdomen using a genetically engineered mouse model of pancreatic ductal adenocarcinoma (PDAC) on a 4.7 T preclinical scanner equipped with moderate gradient capability. RAD DWI was compared with the echo-planar imaging (EPI)-based DWI method with similar voxel volumes and acquisition times over a wide range of b-values (0.64, 535, 1071, 1478, and 2141 mm²/s). The repeatability metrics are assessed in a rigorous test-retest study (n = 10 for each DWI protocol). The four-shot EPI DWI protocol leads to higher signal-to-noise ratio (SNR) in diffusion-weighted images with persisting ghosting artifacts, whereas the RAD DWI protocol produces relatively artifact-free images over all b-values examined. Despite different degrees of motion mitigation, both RAD DWI and EPI DWI allow parametric maps of apparent diffusion coefficients (ADC) to be produced, and the ADC of the PDAC tumor estimated by the two methods are 1.3 ± 0.24 and 1.5 ± 0.28 × 10^-3 mm²/s, respectively (p = 0.075, n = 10), and those of a water phantom are 3.2 ± 0.29 and 2.8 ± 0.15 × 10^-3 mm²/s, respectively (p = 0.001, n = 10). Bland-Altman plots and probability density function reveal good repeatability for both protocols, whose repeatability metrics do not differ significantly. In conclusion, RAD DWI enables a more effective respiratory motion mitigation but lower SNR, while the performance of EPI DWI is expected to improve with more advanced gradient hardware.

Advanced non-invasive diagnostic techniques for visualization and estimation of kidney fibrosis

Kidney fibrosis is marked by excessive extracellular matrix deposition during disease progression. Unfortunately, existing kidney function parameters do not predict the extent of kidney fibrosis. Moreover, the traditional histology methods for the assessment of kidney fibrosis require liquid and imaging biomarkers as well as needle-based biopsies, which are invasive and often associated with kidney injury. The repetitive analyses required to monitor the disease progression are therefore difficult. Hence, there is an unmet medical need for non-invasive and informative diagnostic approaches to monitor kidney fibrosis during the progression of chronic kidney disease. Here, we summarize the modern advances in diagnostic imaging techniques that have shown promise for non-invasive estimation of kidney fibrosis in pre-clinical and clinical studies.

Multiparametric Functional Magnetic Resonance Imaging for Evaluating Renal Allograft Injury

Kidney transplantation is the treatment of choice for patients with end-stage renal disease, as it extends survival and increases quality of life in these patients. However, chronic allograft injury continues to be a major problem, and leads to eventual graft loss. Early detection of allograft injury is essential for guiding appropriate intervention to delay or prevent irreversible damage. Several advanced MRI techniques can offer some important information regarding functional changes such as perfusion, diffusion, structural complexity, as well as oxygenation and fibrosis. This review highlights the potential of multiparametric MRI for noninvasive and comprehensive assessment of renal allograft injury.

Visualization of live, mammalian neurons during Kainate-infusion using magnetic resonance microscopy

Since its first description and development in the late 20th century, diffusion magnetic resonance imaging (dMRI) has proven useful in describing the microstructural details of biological tissues. Signal generated from the protons of water molecules undergoing Brownian motion produces contrast based on the varied diffusivity of tissue types. Images employing diffusion contrast were first used to describe the diffusion characteristics of tissues, later used to describe the fiber orientations of white matter through tractography, and most recently proposed as a functional contrast method capable of delineating neuronal firing in the active brain. Thanks to the molecular origins of its signal source, diffusion contrast is inherently useful at describing features of the microenvironment; however, limitations in achievable resolution in magnetic resonance imaging (MRI) scans precluded direct visualization of tissue microstructure for decades following MRI's inception as an imaging modality. Even after advancements in MRI hardware had permitted the visualization of mammalian cells, these specialized systems could only accommodate fixed specimens that prohibited the observation and characterization of physiological processes. The goal of the current study was to visualize cellular structure and investigate the subcellular origins of the functional diffusion contrast mechanism (DfMRI) in living, mammalian tissue explants. Using a combination of ultra-high field spectrometers, micro radio frequency (RF) coils, and an MRI-compatible superfusion device, we are able to report the first live, mammalian cells-α-motor neurons-visualized with magnetic resonance microscopy (MRM). We are also able to report changes in the apparent diffusion of the stratum oriens within the hippocampus-a layer comprised primarily of pyramidal cell axons and basal dendrites-and the spinal cord's ventral horn following exposure to kainate.

Diffusion Kurtosis Imaging as a Tool in Neurotoxicology

This commentary serves as an introduction to the magnetic resonance imaging (MRI) technique called diffusion kurtosis imaging (DKI) employed in the study by Arab et al. in the present issue of Neurotoxicology Research. In their study, DKI is employed for longitudinal investigation of a methamphetamine intoxication model of Parkinson's disease. The study employs an impressive number of animals and combines DKI with behavioral analysis at multiple time points. The commentary discusses some aspects of the study design especially the strength of combining behavioral analysis with MRI in an effort to provide as thorough a characterization and validity assessment of the animal model and cohort as possible. The potential clinical value of combining multiple MRI techniques (multimodal MRI) in PD is discussed as well as the benefit of multimodal MRI combined with behavioral analysis and subsequent histological analysis for in-depth characterization of animal models.

Comparison of T1 Mapping and T1rho Values with Conventional Diffusion-weighted Imaging to Assess Fibrosis in a Rat Model of Unilateral Ureteral Obstruction

RATIONALE AND OBJECTIVES

The aim of this study was to investigate the potential of magnetic resonance imaging (MRI) T1 mapping and T1 relaxation time in the rotating frame (T1rho) for assessment of renal fibrosis in a rat model of unilateral ureteral obstruction (UUO).

MATERIALS AND METHODS

UUO was created in 36 rats. Six rats were scanned at each of the six time points (on days 0, 1, 3, 5, 10, and 15 after UUO). The contralateral kidneys were examined as controls. Hematoxylin-eosin, Masson's trichrome, and alpha-smooth muscle actin (α-SMA) antibody staining assays were performed. MRI data obtained with a 3.0T scanner were analyzed with α-SMA expression and Masson's staining.

RESULTS

The T1 relaxation times and T1rho values increased, and the mean apparent diffusion coefficient (ADC) values decreased with time after UUO. Simple regression analysis indicated that the mean ADCs, T1 relaxation times, and T1rho values had strong correlations with the α-SMA expression levels (R² = 0.34, R² = 0.66, R² = 0.71, respectively; P< .001) and positive Masson's staining (R² = 0.38, R² = 0.67, R² = 0.65, respectively; P< .001).

CONCLUSIONS

The T1 mapping and T1rho parameters had better correlations with α-SMA expression and Masson's staining than ADC values.

Stroke infarct volume estimation in fixed tissue: Comparison of diffusion kurtosis imaging to diffusion weighted imaging and histology in a rodent MCAO model

Diffusion kurtosis imaging (DKI) is a new promising MRI technique with microstructural sensitivity superior to conventional diffusion tensor (DTI) based methods. In stroke, considerable mismatch exists between the infarct lesion outline obtained from the two methods, kurtosis and diffusion tensor derived metrics. We aim to investigate if this mismatch can be examined in fixed tissue. Our investigation is based on estimates of mean diffusivity (MD) and mean (of the) kurtosis tensor (MKT) obtained using recent fast DKI methods requiring only 19 images. At 24 hours post stroke, rat brains were fixed and prepared. The infarct was clearly visible in both MD and MKT maps. The MKT lesion volume was roughly 31% larger than the MD lesion volume. Subsequent histological analysis (hematoxylin) revealed similar lesion volumes to MD. Our study shows that structural components underlying the MD/MKT mismatch can be investigated in fixed tissue and therefore allows a more direct comparison between lesion volumes from MRI and histology. Additionally, the larger MKT infarct lesion indicates that MKT do provide increased sensitivity to microstructural changes in the lesion area compared to MD.

Differential microstructural alterations in rat cerebral cortex in a model of chronic mild stress depression

Chronic mild stress leads to depression in many cases and is linked to several debilitating diseases including mental disorders. Recently, neuronal tracing techniques, stereology, and immunohistochemistry have revealed persistent and significant microstructural alterations in the hippocampus, hypothalamus, prefrontal cortex, and amygdala, which form an interconnected system known as the stress circuit. Most studies have focused only on this circuit, however, some studies indicate that manipulation of sensory and motor systems may impact genesis and therapy of mood disorders and therefore these areas should not be neglected in the study of brain microstructure alterations in response to stress and depression. For this reason, we explore the microstructural alterations in different cortical regions in a chronic mild stress model of depression. The study employs ex-vivo diffusion MRI (d-MRI) to assess cortical microstructure in stressed (anhedonic and resilient) and control animals. MRI is followed by immunohistochemistry to substantiate the d-MRI findings. We find significantly lower extracellular diffusivity in auditory cortex (AC) of stress groups and a significantly higher fractional anisotropy in the resilient group. Neurite density was not found to be significantly higher in any cortical ROIs in the stress group compared to control, although axonal density is higher in the stress groups. We also report significant thinning of motor cortex (MC) in both stress groups. This is in agreement with recent clinical and preclinical studies on depression and similar disorders where significant microstructural and metabolic alterations were found in AC and MC. Our findings provide further evidence that the AC and MC are sensitive towards stress exposure and may extend our understanding of the microstructural effects of stress beyond the stress circuit of the brain. Progress in this field may provide new avenues of research to help in diagnosis and treatment intervention for depression and related disorders.

Is there evidence for more than two diffusion components in abdominal organs? - A magnetic resonance imaging study in healthy volunteers

The most commonly applied model for the description of diffusion-weighted imaging (DWI) data in perfused organs is bicompartmental intravoxel incoherent motion (IVIM) analysis. In this study, we assessed the ground truth of underlying diffusion components in healthy abdominal organs using an extensive DWI protocol and subsequent computation of apparent diffusion coefficient 'spectra', similar to the computation of previously described T₂ relaxation spectra. Diffusion datasets of eight healthy subjects were acquired in a 3-T magnetic resonance scanner using 68 different b values during free breathing (equidistantly placed in the range 0-1005 s/mm² ). Signal intensity curves as a function of the b value were analyzed in liver, spleen and kidneys using non-negative least-squares fitting to a distribution of decaying exponential functions with minimum amplitude energy regularization. In all assessed organs, the typical slow- and fast-diffusing components of the IVIM model were detected [liver: true diffusion D = (1.26 ± 0.01) × 10^-3 mm² /s, pseudodiffusion D* = (270 ± 44) × 10^-3 mm² /s; kidney cortex: D = (2.26 ± 0.07) × 10^-3 mm² /s, D* = (264 ± 78) × 10^-3 mm² /s; kidney medulla: D = (1.57 ± 0.28) × 10^-3 mm² /s, D* = (168 ± 18) × 10^-3 mm² /s; spleen: D = (0.91 ± 0.01) × 10^-3 mm² /s, D* = (69.8 ± 0.50) × 10^-3 mm² /s]. However, in the liver and kidney, a third component between D and D* was found [liver: D' = (43.8 ± 5.9) × 10^-3 mm² /s; kidney cortex: D' = (23.8 ± 11.5) × 10^-3 mm² /s; kidney medulla: D' = (5.23 ± 0.93) × 10^-3 mm² /s], whereas no third component was detected in the spleen. Fitting with a diffusion kurtosis model did not lead to a better fit of the resulting curves to the acquired data compared with apparent diffusion coefficient spectrum analysis. For a most accurate description of diffusion properties in the liver and the kidneys, a more sophisticated model seems to be required including three diffusion components.

Precision and accuracy of diffusion kurtosis estimation and the influence of b-value selection

Diffusion kurtosis imaging (DKI) is an extension of diffusion tensor imaging that accounts for leading non-Gaussian diffusion effects. In DKI studies, a wide range of different gradient strengths (b-values) is used, which is known to affect the estimated diffusivity and kurtosis parameters. Hence there is a need to assess the accuracy and precision of the estimated parameters as a function of b-value. This work examines the error in the estimation of mean of the kurtosis tensor (MKT) with respect to the ground truth, using simulations based on a biophysical model for both gray (GM) and white (WM) matter. Model parameters are derived from densely sampled experimental data acquired in ex vivo rat brain and in vivo human brain. Additionally, the variability of MKT is studied using the experimental data. Prevalent fitting protocols are implemented and investigated. The results show strong dependence on the maximum b-value of both net relative error and standard deviation of error for all of the employed fitting protocols. The choice of b-values with minimum MKT estimation error and standard deviation of error was found to depend on the protocol type and the tissue. Protocols that utilize two terms of the cumulant expansion (DKI) were found to achieve minimum error in GM at b-values less than 1 ms/μm² , whereas maximal b-values of about 2.5 ms/μm² were found to be optimal in WM. Protocols including additional higher order terms of the cumulant expansion were found to provide higher accuracy for the more commonly used b-value regime in GM, but were associated with higher error in WM. Averaged over multiple voxels, a net average error of around 15% for both WM and GM was observed for the optimal b-value choice. These results suggest caution when using DKI generated metrics for microstructural modeling and when comparing results obtained using different fitting techniques and b-values.