Comparison of readout-segmented and conventional single-shot for echo-planar diffusion-weighted imaging in the assessment of kidney interstitial fibrosis

Noninvasive diagnosis of interstitial fibrosis in chronic kidney disease: a systematic review and meta-analysis

RATIONALE AND OBJECTIVES

Researchers have delved into noninvasive diagnostic methods of renal fibrosis (RF) in chronic kidney disease, including ultrasound (US), magnetic resonance imaging (MRI), and radiomics. However, the value of these diagnostic methods in the noninvasive diagnosis of RF remains contentious. Consequently, the present study aimed to systematically delineate the accuracy of the noninvasive diagnosis of RF.

MATERIALS AND METHODS

A systematic search covering PubMed, Embase, Cochrane Library, and Web of Science databases for all data available up to 28 July 2023 was conducted for eligible studies.

RESULTS

We included 21 studies covering 4885 participants. Among them, nine studies utilized US as a noninvasive diagnostic method, eight studies used MRI, and four articles employed radiomics. The sensitivity and specificity of US for detecting RF were 0.81 (95% CI: 0.76-0.86) and 0.79 (95% CI: 0.72-0.84). The sensitivity and specificity of MRI were 0.77 (95% CI: 0.70-0.83) and 0.92 (95% CI: 0.85-0.96). The sensitivity and specificity of radiomics were 0.69 (95% CI: 0.59-0.77) and 0.78 (95% CI: 0.68-0.85).

CONCLUSIONS

The current early noninvasive diagnostic methods for RF include US, MRI, and radiomics. However, this study demonstrates that US has a higher sensitivity for the detection of RF compared to MRI. Compared to US, radiomics studies based on US did not show superior advantages. Therefore, challenges still exist in the current radiomics approaches for diagnosing RF, and further exploration of optimized artificial intelligence (AI) algorithms and technologies is needed.

Probing Renal Microstructure and Function with Advanced Diffusion MRI: Concepts, Applications, Challenges, and Future Directions

Diffusion measurements in the kidney are affected not only by renal microstructure but also by physiological processes (i.e., glomerular filtration, water reabsorption, and urine formation). Because of the superposition of passive tissue diffusion, blood perfusion, and tubular pre-urine flow, the limitations of the monoexponential apparent diffusion coefficient (ADC) model in assessing pathophysiological changes in renal tissue are becoming apparent and motivate the development of more advanced diffusion-weighted imaging (DWI) variants. These approaches take advantage of the fact that the length scale probed in DWI measurements can be adjusted by experimental parameters, including diffusion-weighting, diffusion gradient directions and diffusion time. This forms the basis by which advanced DWI models can be used to capture not only passive diffusion effects, but also microcirculation, compartmentalization, tissue anisotropy. In this review, we provide a comprehensive overview of the recent advancements in the field of renal DWI. Following a short introduction on renal structure and physiology, we present the key methodological approaches for the acquisition and analysis of renal DWI data, including intravoxel incoherent motion (IVIM), diffusion tensor imaging (DTI), non-Gaussian diffusion, and hybrid IVIM-DTI. We then briefly summarize the applications of these methods in chronic kidney disease and renal allograft dysfunction. Finally, we discuss the challenges and potential avenues for further development of renal DWI. LEVEL OF EVIDENCE: 5 TECHNICAL EFFICACY: Stage 2.

Value of multiparametric magnetic resonance imaging for evaluating chronic kidney disease and renal fibrosis

OBJECTIVES

To identify optimized MRI markers for evaluating chronic kidney disease (CKD) and renal interstitial fibrosis (IF).

MATERIALS AND METHODS

This prospective study included 43 patients with CKD and 20 controls. The CKD group was divided into mild and moderate-to-severe subgroups based on pathological results. Scanned sequences included T1 mapping, R2* mapping, intravoxel incoherent motion imaging, and diffusion-weighted imaging. One-way analyses of variance were used to compare MRI parameters among groups. Correlations of MRI parameters with estimated glomerular filtration rate (eGFR) and renal IF were analyzed using age as covariates. The support vector machine (SVM) model was used to evaluate the diagnostic efficacy of multiparametric MRI.

RESULTS

Compared to control values, renal cortical apparent diffusion coefficient (cADC), medullary ADC (mADC), cortical pure diffusion coefficient (cDt), medullary Dt (mDt), cortical shifted apparent diffusion coefficient (csADC), and medullary sADC (msADC) values gradually decreased in the mild and moderate-to-severe groups, while cortical T1 (cT1) and medullary T1 (mT1) values gradually increased. Values of cADC, mADC, cDt, mDt, cT1, mT1, csADC, and msADC were significantly associated with eGFR and IF (p < 0.001). The SVM model indicated that multiparametric MRI combining cT1 and csADC can distinguish patients with CKD from controls with high accuracy (0.84), sensitivity (0.70), and specificity (0.92) (AUC: 0.96). Multiparametric MRI combining cT1 and cADC exhibited high accuracy (0.91), sensitivity (0.95), and specificity (0.81) for evaluating IF severity (AUC: 0.96).

CONCLUSION

Multiparametric MRI combining T1 mapping and diffusion imaging may be of clinical utility in non-invasive assessment of CKD and IF.

CLINICAL RELEVANCE STATEMENT

This study shows that multiparametric MRI combining T1 mapping and diffusion imaging may be clinically useful in the non-invasive assessment of chronic kidney disease (CKD) and interstitial fibrosis; this could provide information for risk stratification, diagnosis, treatment, and prognosis.

KEY POINTS

• Optimized MRI markers for evaluating chronic kidney disease and renal interstitial fibrosis were investigated. • Renal cortex/medullary T1 values increased as interstitial fibrosis increased; cortical shifted apparent diffusion coefficient (csADC) correlated significantly with eGFR and interstitial fibrosis. • Support vector machine (SVM) combining cortical T1 (cT1) and csADC/cADC effectively identifies chronic kidney disease and accurately predicts renal interstitial fibrosis.

Readout-segmented diffusion weighted imaging of the testis at 3.0 T: comparison with single-shot echo-planar imaging

OBJECTIVE

The current study aimed to explore the feasibility of readout-segmented echo-planar imaging (RS-EPI) of the testis at 3.0 T, by comparing with single-shot echo-planar imaging (SS-EPI) in qualitative image quality and quantitative apparent diffusion coefficient (ADC) values.

METHODS

66 patients undergoing scrotal MRI for various clinical indications were included retrospectively. RS-EPI image quality was rated from 1 (severe distortion or artifact, or nondiagnostic) to 4 (nearly no distortion or artifact, or outstanding). The comparative image quality (RS- vs. SS-EPI) was rated from - 2 (SS-EPI severe or greater conspicuity) to 2 (RS-EPI severe or greater conspicuity). The confidence interval of proportions (CIOP) of comparative image quality and Wilcoxon rank sum test were performed to assess the preferences between RS-EPI and SS-EPI. Paired samples t-test and Bland-Altman analysis were performed to compare the mean ADC values of RS-EPI and SS-EPI. The mean, maximum, and minimum ADC values measured by RS-EPI were compared in normal testicular parenchyma, benign and malignant intratesticular lesions.

RESULTS

The evaluation of RS-EPI image quality showed RS-EPI with the characteristics of slight geometric distortion and susceptibility artifact, and good lesion conspicuity. The assessment of comparative image quality showed SS-EPI with obvious geometric distortion and susceptibility artifact, and RS-EPI preferred in lesion conspicuity. The CIOP ranged from 97 to 100% among three readers, with preferring to RS-EPI improving image quality (P < 0.001). There was a strong correlation and good agreement between mean ADC values measured by RS-EPI and SS-EPI. The mean, maximum and minimum ADC values by RS-EPI were significantly different in normal testicular parenchyma, benign and malignant intratesticular lesions.

CONCLUSION

RS-EPI DWI of the testis improved image quality in geometric distortion, susceptibility artifacts, and lesion conspicuity, and provided highly correlated and consistent mean ADC values when compared to SS-EPI DWI, indicating the feasibility of RS-EPI DWI of testes.

Accelerated Diffusion-Weighted MR Image Reconstruction Using Deep Neural Networks

Under-sampling in diffusion-weighted imaging (DWI) decreases the scan time that helps to reduce off-resonance effects, geometric distortions, and susceptibility artifacts; however, it leads to under-sampling artifacts. In this paper, diffusion-weighted MR image (DWI-MR) reconstruction using deep learning (DWI U-Net) is proposed to recover artifact-free DW images from variable density highly under-sampled k-space data. Additionally, different optimizers, i.e., RMSProp, Adam, Adagrad, and Adadelta, have been investigated to choose the best optimizers for DWI U-Net. The reconstruction results are compared with the conventional Compressed Sensing (CS) reconstruction. The quality of the recovered images is assessed using mean artifact power (AP), mean root mean square error (RMSE), mean structural similarity index measure (SSIM), and mean apparent diffusion coefficient (ADC). The proposed method provides up to 61.1%, 60.0%, 30.4%, and 28.7% improvements in the mean AP value of the reconstructed images in our experiments with different optimizers, i.e., RMSProp, Adam, Adagrad, and Adadelta, respectively, as compared to the conventional CS at an acceleration factor of 6 (i.e., AF = 6). The results of DWI U-Net with the RMSProp, Adam, Adagrad, and Adadelta optimizers show 13.6%, 10.0%, 8.7%, and 8.74% improvements, respectively, in terms of mean SSIM with respect to the conventional CS at AF = 6. Also, the proposed technique shows 51.4%, 29.5%, 24.04%, and 18.0% improvements in terms of mean RMSE using the RMSProp, Adam, Adagrad, and Adadelta optimizers, respectively, with reference to the conventional CS at AF = 6. The results confirm that DWI U-Net performs better than the conventional CS reconstruction. Also, when comparing the different optimizers in DWI U-Net, RMSProp provides better results than the other optimizers.

The utility of texture analysis of kidney MRI for evaluating renal dysfunction with multiclass classification model

We evaluated a multiclass classification model to predict estimated glomerular filtration rate (eGFR) groups in chronic kidney disease (CKD) patients using magnetic resonance imaging (MRI) texture analysis (TA). We identified 166 CKD patients who underwent MRI comprising Dixon-based T1-weighted in-phase (IP)/opposed-phase (OP)/water-only (WO) images, apparent diffusion coefficient (ADC) maps, and T2* maps. The patients were divided into severe, moderate, and control groups based on eGFR borderlines of 30 and 60 mL/min/1.73 m². After extracting 93 texture features (TFs), dimension reduction was performed using inter-observer reproducibility analysis and sequential feature selection (SFS) algorithm. Models were created using linear discriminant analysis (LDA); support vector machine (SVM) with linear, rbf, and sigmoid kernels; decision tree (DT); and random forest (RF) classifiers, with synthetic minority oversampling technique (SMOTE). Models underwent 100-time repeat nested cross-validation. Overall performances of our classification models were modest, and TA based on T1-weighted IP/OP/WO images provided better performance than those based on ADC and T2* maps. The most favorable result was observed in the T1-weighted WO image using RF classifier and the combination model was derived from all T1-weighted images using SVM classifier with rbf kernel. Among the selected TFs, total energy and energy had weak correlations with eGFR.

Comparing the clinical utility of single-shot, readout-segmented and zoomit echo-planar imaging in diffusion-weighted imaging of the kidney at 3 T

We compared the clinical utility of single-shot echo-planar imaging (SS-EPI) using different breathing schemes, readout-segmented EPI and zoomit EPI in the repeatability of apparent diffusion coefficient (ADC) measurements, cortico-medullary contrast to noise ratio (c-mCNR) and image quality. In this institutional review board-approved prospective study, some common clinically applicable diffusion-weighted imaging (b = 50, 400, 800 s/mm²) of kidney on 3.0 T MRI were performed on 22 volunteers using SS-EPI with breath-hold diffusion-weighted imaging (BH-DWI), free-breathing (FB-DWI), navigator-triggered (NT-DWI) and respiratory-triggered (RT-DWI), readout-segmented DWI (RS-DWI), and Zoomit DWI (Z-DWI). ADC and c-mCNR were measured in 12 anatomic locations (the upper, middle, and lower pole of the renal cortex and medulla), and image quality was assessed on these DWI sequences. A DWI with the optimal clinical utility was decided by systematically assessing the ADC repeatability, c-mCNR and image quality among the DWIs. For ADC measurements, Z-DWI had an excellent intra-observer agreement (intra-class correlation coefficients (ICCs): 0.876–0.944) and good inter-observer agreement (inter-class ICCs: 0.798–0.856) in six DWI sequences. Z-DWI had the highest ADC repeatability in most of the 12 anatomic locations of the kidneys (mean ADC absolute difference: 0.070–0.111 × 10⁻³ mm²/s, limit of agreement: 0.031–0.056 × 10⁻³ mm²/s). In all DWIs, Z-DWI yielded a slightly higher c-mCNR than other DWIs in most representative locations (P > 0.05), which was significantly higher than BH-DWI and FB-DWI in the middle pole of both kidneys and the upper pole of the left kidney (P < 0.05). In addition, Z-DWI yielded image quality that was similar to RT-DWI and NT-DWI (P > 0.05) and superior to BH-DWI, FB-DWI and RS-DWI (P < 0.05). Our results suggest that Z-DWI provides the highest ADC reproducibility, better c-mCNR and good image quality on 3.0 T MRI, making it the recommended sequence for clinical DWI of the kidney.

Assessment of Rat Sciatic Nerve Using Diffusion-Tensor Imaging With Readout-Segmented Echo Planar Imaging

Objectives

This study aimed to compare readout-segmented-3, readout-segmented-5, and readout-segmented-7 echo-planar imaging (RS3-EPI, RS5-EPI, and RS7-EPI) of DTI in the assessment of rat sciatic nerve at 3T MR.

Methods

Eight male adult healthy Sprague-Dawley rats were scanned at 3T MR with RS-3 EPI, RS5-EPI, and RS-7 EPI DTI. The image quality of RS-3 EPI, RS-5 EPI, and RS-7 EPI in terms of the nerve morphology, distortions of the nearby femur, muscles, and homogeneity of neuromuscular were evaluated by two experienced radiologists. The correlations between the histopathological and DTI parameters, including fractional anisotropy (FA) and radial diffusivity (RD), were calculated, respectively, and compared in RS-3, RS-5, and RS-7 EPI. The image quality scores for RS-3 EPI, RS-5 EPI, and RS-7 EPI were compared using the Wilcoxon rank-sum test. The correlation between DTI and histopathological parameters was calculated using the Pearson correlation coefficient.

Results

RS-5 EPI yielded the best SNR-values corrected for the acquisition time compared to RS3-EPI and RS7-EPI. The image quality scores of RS-5 EPI were superior to those of RS-3 and RS-7 EPI (P = 0.01–0.014) and lower artifacts of the ventral/dorsal margin and femur (P = 0.008–0.016) were shown. DTT analysis yielded a significantly higher number of tracts for RS5-EPI compared to RS3-EPI (P = 0.007) but no significant difference with RS7-EPI (P = 0.071). For the three sequences, FA and RD were well-correlated with the myelin-related histopathological parameters (|r| 0.709–0.965, P = 0.001–0.049). The overall correlation coefficients of FA and RD obtained from RS-5 EPI were numerically higher than that with both RS3-EPI and RS7-EPI.

Conclusion

For the rat sciatic nerve DTI imaging, RS-5 EPI offered the best image quality and SNR-values corrected for the acquisition time. The FA and RD derived from the RS-5 EPI were the most sensitive quantitative biomarkers to detect rat sciatic nerve histopathological change.

Performance of Single-Shot Echo-Planar Imaging in Diffusion Tensor Imaging in Rat Sciatic Nerve Compared With Readout-Segmented Echo-Planar Imaging

Objectives

To compare the performances of single-shot echo-planar imaging (SS–EPI) and readout-segmented echo-planar imaging (RS–EPI) for diffusion tensor imaging (DTI) of the rat sciatic nerve.

Methods

Eight healthy adult male Sprague-Dawley rats were anesthetized and scanned with a 3T MRI scanner using SS–EPI and RS–EPI DTI sequences. The image quality in terms of the morphology of the nerve, distortions of the nearby femur, muscles, and homogeneity of neuromuscular were evaluated and scored. The correlations between the DTI parameters including fractional anisotropy (FA), axial diffusivity (AD), radial diffusivity (RD), apparent diffusion coefficient (ADC), and histopathological parameters were calculated by using the Pearson correlation coefficient and compared by the modified Fisher Z-transform, respectively.

Results

The quality scores were higher for the images from the SS–EPI sequence compared with the RS–EPI sequence for characteristics such as sharpness of the sciatic nerve margin (P = 0.008), artifacts of the sciatic nerve (P = 0.008), and homogeneity of the neuromuscular region (P = 0.007), as well as the contrast-to-noise ratio (CNR) of DW images (P < 0.001). The correlation coefficients were higher for the FA and RD values from the SS–EPI sequence compared with those from the RS–EPI sequence. Furthermore, the correlation coefficients between FA and myelin thickness (P = 0.027), FA and diameter of the myelinated fiber (P = 0.036), as well as RD and myelin thickness (P = 0.05) were statistically higher for the SS–EPI sequence compared with those for the RS–EPI sequence.

Conclusion

Diffusion tensor imaging analysis of the rat sciatic nerve showed that the image quality from the SS–EPI sequence was significantly higher compared with that from the RS–EPI sequence. Furthermore, the FA and RD derived from the SS–EPI sequence are promising and sensitive biomarkers to detect the histopathological changes in the rat sciatic nerve.

High-Resolution Diffusion-Weighted Imaging of C6 Glioma on a 7T BioSpec MRI Scanner: Correlation of Tumor Cellularity and Nuclear-to-Cytoplasmic Ratio with Apparent Diffusion Coefficient

RATIONALE AND OBJECTIVES

To determine the association of the apparent diffusion coefficient (ADC) with quantitative cellularity and the nuclear-to-cytoplasmic ratio in C6 glioma.

MATERIALS AND METHODS

Animal models bearing C6 gliomas underwent MR scans with T1 rapid acquisition with relaxation enhancement (RARE), T2 RARE, and high-resolution diffusion-weighted imaging sequences. For each model, three consecutive sections were used to draw regions of interest (ROIs) and measure ADC values; the middle section was localized in the plane with the maximal solid tumor area. The minimal, mean, and maximal ADC values were recorded for each ROI. GFAP-immunostained sections coregistered with ADC measurements were used to calculate tumor cellularity and the nuclear-to-cytoplasmic (N/C) ratio. Spearman's correlation was used to assess the relationship between ADC values and quantitative tumor cellularity as well as N/C ratios with a significance level of p < 0.05.

RESULTS

Thirty-three sections from 11 glioma-bearing rats were analyzed. The median values of the minimal, mean, and maximal ADC were 0.443 × 10^-3, 0.744 × 10^-3, and 1.140 × 10^-3 mm²/s, respectively. The median cellularity and N/C ratio were 2151.234 per 0.025 mm² and 0.857, respectively. The minimal, mean, and maximal ADCs were all significantly associated with cellularity, with correlation coefficients of -0.712 (p < 0.001), -0.631 (p < 0.001), and -0.460 (p = 0.007), respectively. The minimal and mean ADC had significant negative relationships with the N/C ratio, with correlation coefficients of -0.565 (p =  0.001) and -0.426 (p = 0.013), respectively.

CONCLUSION

The minimal ADC correlated well with cellularity and N/C ratios in C6 glioma and may be used as a biomarker of these two pathological features.

Diffusion-Magnetic Resonance Imaging predicts decline of kidney function in chronic kidney disease and in patients with a kidney allograft

Kidney cortical interstitial fibrosis is highly predictive of kidney prognosis and is currently assessed by evaluation of a biopsy. Diffusion-weighted magnetic resonance imaging is a promising non-invasive tool to evaluate kidney fibrosis. We recently adapted diffusion-weighted imaging sequence for discrimination between the kidney cortex and medulla and found that the cortico-medullary difference in apparent diffusion coefficient (ΔADC) correlated with histological interstitial fibrosis. Here, we assessed whether ΔADC as measured with diffusion-weighted magnetic resonance imaging is predictive of kidney function decline and dialysis initiation in chronic kidney disease (CKD) and patients with a kidney allograft in a prospective study encompassing 197 patients. We measured ΔADC in 43 patients with CKD (estimated GFR (eGFR) 55ml/min/1.73m²) and 154 patients with a kidney allograft (eGFR 53ml/min/1.73m²). Patients underwent a kidney biopsy and diffusion-weighted magnetic resonance imaging within one week of biopsy; median follow-up of 2.2 years with measured laboratory parameters. The primary outcome was a rapid decline of kidney function (eGFR decline over 30% or dialysis initiation) during follow up. Significantly, patients with a negative ΔADC had 5.4 times more risk of rapid decline of kidney function or dialysis (95% confidence interval: 2.29-12.58). After correction for kidney function at baseline and proteinuria, low ADC still predicted significant kidney function loss with a hazard ratio of 4.62 (95% confidence interval 1.56-13.67) independent of baseline age, sex, eGFR and proteinuria. Thus, low ΔADC can be a predictor of kidney function decline and dialysis initiation in patients with native kidney disease or kidney allograft, independent of baseline kidney function and proteinuria.

Cardiorenal Syndrome: Emerging Role of Medical Imaging for Clinical Diagnosis and Management

Cardiorenal syndrome (CRS) concerns the interconnection between heart and kidneys in which the dysfunction of one organ leads to abnormalities of the other. The main clinical challenges associated with cardiorenal syndrome are the lack of tools for early diagnosis, prognosis, and evaluation of therapeutic effects. Ultrasound, computed tomography, nuclear medicine, and magnetic resonance imaging are increasingly used for clinical management of cardiovascular and renal diseases. In the last decade, rapid development of imaging techniques provides a number of promising biomarkers for functional evaluation and tissue characterization. This review summarizes the applicability as well as the future technological potential of each imaging modality in the assessment of CRS. Furthermore, opportunities for a comprehensive imaging approach for the evaluation of CRS are defined.

Diffusion Tensor Imaging of the Spinal Cord

Spinal cord often is regarded as one of the last territories in the central nervous system where diffusion tensor imaging (DTI) can be used to probe white matter architecture. This article reviews current progress in spinal cord DTI, starting with anatomic properties and technical challenges that make spinal cord DTI a difficult task. Several possibilities offered by advanced pulse sequences that might overcome the difficulties are addressed, with associated trade-offs and limitations. Potential clinical assistance also is discussed in various spinal cord pathologies, such as myelopathy due to external compression, spinal cord tumors, acute ischemia, traumatic injury, and so forth.

Geometric Distortion Correction of Renal Diffusion Tensor Imaging Using the Reversed Gradient Method

ABSTRACT

Renal echo planar diffusion tensor imaging (DTI) has clinical potential but suffers from geometric distortion. We evaluated feasibility of reversed gradient distortion correction in 10 diabetic patients and 6 volunteers. Renal area, apparent diffusion coefficient, fractional anisotropy, and tensor eigenvalues were measured on uncorrected and distortion-corrected DTI. Corrected DTI correlated better than uncorrected DTI (r = 0.904 vs 0.840, P = 0.002) with reference anatomic T2-weighted imaging, with no significant difference in DTI metrics.

Recent advances in medical image processing for the evaluation of chronic kidney disease

Assessment of renal function and structure accurately remains essential in the diagnosis and prognosis of Chronic Kidney Disease (CKD). Advanced imaging, including Magnetic Resonance Imaging (MRI), Ultrasound Elastography (UE), Computed Tomography (CT) and scintigraphy (PET, SPECT) offers the opportunity to non-invasively retrieve structural, functional and molecular information that could detect changes in renal tissue properties and functionality. Currently, the ability of artificial intelligence to turn conventional medical imaging into a full-automated diagnostic tool is widely investigated. In addition to the qualitative analysis performed on renal medical imaging, texture analysis was integrated with machine learning techniques as a quantification of renal tissue heterogeneity, providing a promising complementary tool in renal function decline prediction. Interestingly, deep learning holds the ability to be a novel approach of renal function diagnosis. This paper proposes a survey that covers both qualitative and quantitative analysis applied to novel medical imaging techniques to monitor the decline of renal function. First, we summarize the use of different medical imaging modalities to monitor CKD and then, we show the ability of Artificial Intelligence (AI) to guide renal function evaluation from segmentation to disease prediction, discussing how texture analysis and machine learning techniques have emerged in recent clinical researches in order to improve renal dysfunction monitoring and prediction. The paper gives a summary about the role of AI in renal segmentation.

Performance of simultaneous multi-slice accelerated diffusion-weighted imaging for assessing focal renal lesions in pediatric patients with tuberous sclerosis complex

BACKGROUND

Diffusion-weighted imaging (DWI) is a useful MRI technique to characterize abdominal lesions in children, but long acquisition times can lead to image degradation. Simultaneous multi-slice accelerated DWI is a promising technique to shorten DWI scan times.

OBJECTIVE

To test the feasibility of simultaneous multi-slice DWI of the kidneys in pediatric patients with tuberous sclerosis complex (TSC) and to evaluate the accelerated protocol regarding image quality and quantitative apparent diffusion coefficient (ADC) values compared to standard echoplanar DWI sequence.

MATERIALS AND METHODS

We included 33 children and adolescents (12 female, 21 male; mean age 10±5 years) with TSC and renal cyst or angiomyolipoma on 3-tesla (T) MRI from 2017 to 2019. All studies included both free-breathing standard echoplanar DWI and simultaneous multi-slice DWI sequences. Subjective and quantitative image quality was evaluated using a predefined 5-point scale. ADC values were obtained for all renal cysts and angiomyolipomas ≥5 mm. All statistical analysis was performed using Stata/SE v15.1.

RESULTS

Simultaneous multi-slice DWI ADC values were slightly lower compared to standard echoplanar DWI for both renal cysts and angiomyolipomas (mean difference 0.05×10^-3 mm²/s, 95% confidence interval [CI] 0.40-0.50 and 0.024×10^-3 mm²/s, 95% CI 0.17-0.21, respectively, with P>0.1). Our results showed that renal lesions with ADC values >1.69×10^-3 mm²/s were all cysts, whereas lesions with values <1.16×10^-3 mm²/s were all angiomyolipomas. However, ADC values could not discriminate between lipid-rich and lipid-poor angiomyolipomas (P>0.1, for both sequences).

CONCLUSION

A 55% reduction in scan time was achieved using simultaneous multi-slice DWI for abdominal imaging in children with TSC, with near identical image quality as standard DWI. These results suggest that multi-slice techniques should be considered more broadly as an MRI acceleration technique in children.

Renal Diffusion-Weighted Imaging (DWI) for Apparent Diffusion Coefficient (ADC), Intravoxel Incoherent Motion (IVIM), and Diffusion Tensor Imaging (DTI): Basic Concepts

The specialized function of the kidney is reflected in its unique structure, characterized by juxtaposition of disorganized and ordered elements, including renal glomerula, capillaries, and tubules. The key role of the kidney in blood filtration, and changes in filtration rate and blood flow associated with pathological conditions, make it possible to investigate kidney function using the motion of water molecules in renal tissue. Diffusion-weighted imaging (DWI) is a versatile modality that sensitizes observable signal to water motion, and can inform on the complexity of the tissue microstructure. Several DWI acquisition strategies are available, as are different analysis strategies, and models that attempt to capture not only simple diffusion effects, but also perfusion, compartmentalization, and anisotropy. This chapter introduces the basic concepts of DWI alongside common acquisition schemes and models, and gives an overview of specific DWI applications for animal models of renal disease.This chapter is based upon work from the COST Action PARENCHIMA, a community-driven network funded by the European Cooperation in Science and Technology (COST) program of the European Union, which aims to improve the reproducibility and standardization of renal MRI biomarkers. This introduction chapter is complemented by two separate chapters describing the experimental procedure and data analysis.

Quantitative assessment of renal structural and functional changes in chronic kidney disease using multi-parametric magnetic resonance imaging

Background

Multi-parametric magnetic resonance imaging (MRI) provides the potential for a more comprehensive non-invasive assessment of organ structure and function than individual MRI measures, but has not previously been comprehensively evaluated in chronic kidney disease (CKD).

Methods

We performed multi-parametric renal MRI in persons with CKD (n = 22, 61 ± 24 years) who had a renal biopsy and measured glomerular filtration rate (mGFR), and matched healthy volunteers (HV) (n = 22, 61 ± 25 years). Longitudinal relaxation time (T₁), diffusion-weighted imaging, renal blood flow (phase contrast MRI), cortical perfusion (arterial spin labelling) and blood-oxygen-level-dependent relaxation rate (R₂*) were evaluated.

Results

MRI evidenced excellent reproducibility in CKD (coefficient of variation <10%). Significant differences between CKD and HVs included cortical and corticomedullary difference (CMD) in T₁, cortical and medullary apparent diffusion coefficient (ADC), renal artery blood flow and cortical perfusion. MRI measures correlated with kidney function in a combined CKD and HV analysis: estimated GFR correlated with cortical T₁ (r = −0.68), T₁ CMD (r = −0.62), cortical (r = 0.54) and medullary ADC (r = 0.49), renal artery flow (r = 0.78) and cortical perfusion (r = 0.81); log urine protein to creatinine ratio (UPCR) correlated with cortical T₁ (r = 0.61), T₁ CMD (r = 0.61), cortical (r = −0.45) and medullary ADC (r = −0.49), renal artery flow (r = −0.72) and cortical perfusion (r = −0.58). MRI measures (cortical T₁ and ADC, T₁ and ADC CMD, cortical perfusion) differed between low/high interstitial fibrosis groups at 30–40% fibrosis threshold.

Conclusion

Comprehensive multi-parametric MRI is reproducible and correlates well with available measures of renal function and pathology. Larger longitudinal studies are warranted to evaluate its potential to stratify prognosis and response to therapy in CKD.

High resolution diffusion-weighted imaging with readout segmentation of long variable echo-trains for determining myometrial invasion in endometrial carcinoma

Background

We assessed the image quality of endometrial cancer lesions by readout segmentation of long variable echo-trains (RESOLVE) diffusion-weighted imaging (DWI) compared with that by single-shot echo-planar imaging (SS-EPI) DWI, aimed to explore the value of RESOLVE DWI for determining myometrial invasion and clinical stage in endometrial cancer.

Materials and methods

From April 2017 to March 2018, a total of 30 endometrial cancer patients (mean age 52.8 ± 9.0 years), who had undergone RESOLVE DWI and SS-EPI DWI, were included in the study. The image quality of endometrial carcinoma by two kinds of DWI scanning methods was compared qualitatively and quantitatively. The Spearman rank correlation test was used to assess the correlation of qualitative image quality scores between two readers. The accuracy of two DWI methods in detecting myometrial invasion and staging of endometrial carcinoma was calculated according to postoperative pathological results. The indexes were analyzed including sensitivity, specificity, accuracy, positive predictive value (PPV), and negative predictive value (NPV).

Results

The qualitative score of RESOLVE DWI group was superior to SS-EPI DWI group in every aspect of five aspects (all P < 0.001). Interobserver agreement of depiction was good or excellent in two DWI sequences. Signal to noise ratio and contrast to noise ratio values in RESOLVE DWI group were both higher than those in SS-EPI DWI group (P<0.001). No statistical difference of apparent diffusion coefficient value was observed between two DWI groups (P = 0.261). The specificity, accuracy, PPV, and NPV of estimating myometrial invasion by RESOLVE DWI in three cases (intramucosal lesion, <50% superficial invasion and ≥ 50% deep invasion) were all higher than those by SS-EPI DWI for endometrial carcinoma. Especially RESOLVE DWI was valuable in judging <50% superficial invasion (95%CI:0.586, 0.970). No significant difference in accuracy staging was between the two DWI groups (P = 0.125).

Conclusion

RESOLVE DWI can provide higher quality images of endometrial carcinoma than SS-EPI DWI. The high-quality images are helpful for precise assessment of myometrial invasion in endometrial cancer.

Quantitative assessment of renal allograft pathologic changes: comparisons of mono-exponential and bi-exponential models using diffusion-weighted imaging

Background

Diffusion-weighted imaging (DWI) can noninvasively assess renal allograft pathologic changes that provide useful information for clinical management and prognostication. However, it is still unknown whether the bi-exponential model analysis of DWI signals is superior to that of the mono-exponential model.

Methods

Pathologic and DWI data from a total of 47 allografts were prospectively collected and analyzed. Kidney transplant interstitial fibrosis was quantified digitally. The severity of acute and chronic pathologic changes was semi-quantified by calculating the acute composite scores (ACS) and chronic composite score (CCS). Mono-exponential total apparent diffusion coefficient (ADCT), and the bi-exponential parameters of true diffusion (D) and perfusion fraction (fp) were acquired. The diagnostic performances of both mono-exponential and bi-exponential parameters were assessed and compared by calculating the area under the curve (AUC) from receiver-operating characteristic (ROC) curve analysis.

Results

ADCT, D, and fp were all significantly correlated with interstitial fibrosis, ACS, and CCS. Cortical fp discriminated mild from moderate and severe ACS with the largest AUC of 0.89 [95% confidence interval (CI), 0.77-0.96]. Noticeably, only cortical fp could differentiate severe ACS from mild-to-moderate ACS (P<0.001) with an AUC of 0.80 (95% CI, 0.65-0.90) and a sensitivity of 100% (95% CI, 66.4-100%). Strikingly, the joint use of D and fp in either the cortex or the medulla could achieve a sensitivity of 100% for identifying either mild or severe interstitial fibrosis. Meanwhile, the serial use of cortical D and cortical fp showed the largest specificity for identifying both mild [88.9% (95% CI, 70.8-97.6%)] and severe [84.4% (95% CI, 67.2-94.7%)] interstitial fibrosis. For identifying mild CCS, the AUC of medullary ADCT (0.90, 95% CI, 0.78-0.97) was similar to that of cortical D (0.81, 95% CI, 0.67-0.91) and fp (0.86, 95% CI, 0.73-0.94), but statistically larger than that of medullary D (P=0.005) and fp (P=0.01). Furthermore, the parallel use of cortical D and cortical fp could increase the sensitivity to 95.0% (95% CI, 75.1-99.9%), whereas serial use of medullary D and medullary fp could increase the specificity to 100% (95% CI, 87.2-100%). The AUCs for differentiating severe from mild and moderate CCS were statistically insignificant among all parameters in the cortex and medulla (P≥0.15).

Conclusions

Cortical fp was superior to the ADCT for identifying both mild and severe acute pathologic changes. Nevertheless, ADCT was equal to or better than single D or fp for evaluating chronic pathologic changes. Thus, both monoexponential and bi-exponential analysis of DWI images are complementary for evaluating kidney allograft pathologic changes, and the combined use of D and fp can increase the sensitivity and specificity for discriminating allograft pathologic changes severity.

Quantitative assessment of renal structural and functional changes in chronic kidney disease using multi-parametric magnetic resonance imaging

BACKGROUND

Multi-parametric magnetic resonance imaging (MRI) provides the potential for a more comprehensive non-invasive assessment of organ structure and function than individual MRI measures, but has not previously been comprehensively evaluated in chronic kidney disease (CKD).

METHODS

We performed multi-parametric renal MRI in persons with CKD (n = 22, 61 ± 24 years) who had a renal biopsy and measured glomerular filtration rate (mGFR), and matched healthy volunteers (HV) (n = 22, 61 ± 25 years). Longitudinal relaxation time (T1), diffusion-weighted imaging, renal blood flow (phase contrast MRI), cortical perfusion (arterial spin labelling) and blood-oxygen-level-dependent relaxation rate (R2*) were evaluated.

RESULTS

MRI evidenced excellent reproducibility in CKD (coefficient of variation <10%). Significant differences between CKD and HVs included cortical and corticomedullary difference (CMD) in T1, cortical and medullary apparent diffusion coefficient (ADC), renal artery blood flow and cortical perfusion. MRI measures correlated with kidney function in a combined CKD and HV analysis: estimated GFR correlated with cortical T1 (r = -0.68), T1 CMD (r = -0.62), cortical (r = 0.54) and medullary ADC (r = 0.49), renal artery flow (r = 0.78) and cortical perfusion (r = 0.81); log urine protein to creatinine ratio (UPCR) correlated with cortical T1 (r = 0.61), T1 CMD (r = 0.61), cortical (r = -0.45) and medullary ADC (r = -0.49), renal artery flow (r = -0.72) and cortical perfusion (r = -0.58). MRI measures (cortical T1 and ADC, T1 and ADC CMD, cortical perfusion) differed between low/high interstitial fibrosis groups at 30-40% fibrosis threshold.

CONCLUSION

Comprehensive multi-parametric MRI is reproducible and correlates well with available measures of renal function and pathology. Larger longitudinal studies are warranted to evaluate its potential to stratify prognosis and response to therapy in CKD.

Diffusion-weighted Renal MRI at 9.4 Tesla Using RARE to Improve Anatomical Integrity

Diffusion-weighted magnetic resonance imaging (DWI) is a non-invasive imaging technique sensitive to tissue water movement. By enabling a discrimination between tissue properties without the need of contrast agent administration, DWI is invaluable for probing tissue microstructure in kidney diseases. DWI studies commonly make use of single-shot Echo-Planar Imaging (ss-EPI) techniques that are prone to suffering from geometric distortion. The goal of the present study was to develop a robust DWI technique tailored for preclinical magnetic resonance imaging (MRI) studies that is free of distortion and sensitive to detect microstructural changes. Since fast spin-echo imaging techniques are less susceptible to B₀ inhomogeneity related image distortions, we introduced a diffusion sensitization to a split-echo Rapid Acquisition with Relaxation Enhancement (RARE) technique for high field preclinical DWI at 9.4 T. Validation studies in standard liquids provided diffusion coefficients consistent with reported values from the literature. Split-echo RARE outperformed conventional ss-EPI, with ss-EPI showing a 3.5-times larger border displacement (2.60 vs. 0.75) and a 60% higher intra-subject variability (cortex = 74%, outer medulla = 62% and inner medulla = 44%). The anatomical integrity provided by the split-echo RARE DWI technique is an essential component of parametric imaging on the way towards robust renal tissue characterization, especially during kidney disease.

Consensus-based technical recommendations for clinical translation of renal diffusion-weighted MRI

Objectives

Standardization is an important milestone in the validation of DWI-based parameters as imaging biomarkers for renal disease. Here, we propose technical recommendations on three variants of renal DWI, monoexponential DWI, IVIM and DTI, as well as associated MRI biomarkers (ADC, D, D*, f, FA and MD) to aid ongoing international efforts on methodological harmonization.

Materials and methods

Reported DWI biomarkers from 194 prior renal DWI studies were extracted and Pearson correlations between diffusion biomarkers and protocol parameters were computed. Based on the literature review, surveys were designed for the consensus building. Survey data were collected via Delphi consensus process on renal DWI preparation, acquisition, analysis, and reporting. Consensus was defined as ≥ 75% agreement.

Results

Correlations were observed between reported diffusion biomarkers and protocol parameters. Out of 87 survey questions, 57 achieved consensus resolution, while many of the remaining questions were resolved by preference (65–74% agreement). Summary of the literature and survey data as well as recommendations for the preparation, acquisition, processing and reporting of renal DWI were provided.

Discussion

The consensus-based technical recommendations for renal DWI aim to facilitate inter-site harmonization and increase clinical impact of the technique on a larger scale by setting a framework for acquisition protocols for future renal DWI studies. We anticipate an iterative process with continuous updating of the recommendations according to progress in the field.

Electronic supplementary material

The online version of this article (10.1007/s10334-019-00790-y) contains supplementary material, which is available to authorized users.

Diffusion-weighted magnetic resonance imaging in bladder cancer: comparison of readout-segmented and single-shot EPI techniques

Background

To evaluate whether readout-segment echo-planar imaging (RS-EPI) can provide better image quality in assessing bladder cancer than single-shot echo-planar imaging (SS-EPI) and to compare quantitative imaging parameters derived from both techniques.

Methods

Seventy patients with bladder lesions were enrolled and underwent diffusion-weighted imaging on a 3 Tesla magnetic resonance scanner using axial RS-EPI and SS-EPI techniques. Two observers independently assessed the susceptibility, detectability, motion artefacts and blurring of the images using qualitative scores. The signal-to-noise ratio (SNR), signal intensity ratio (SIR), contrast-to-noise ratio (CNR) and ADC values of the bladder lesions were measured and compared between the two techniques and between two observers. Qualitative and quantitative comparisons of image quality were performed using the Wilcoxon signed-rank test and paired t-test. In addition, the agreement of the ADC measurements was evaluated using ICC values and Bland-Altman plots.

Results

Sixty-eight patients were included in the final analysis. The scores of image susceptibility, detectability and blurring for RS-EPI were significantly higher than those for SS-EPI (all p < 0.05), while the motion artefact was not. There were significant differences between RS-EPI and SS-EPI in the CNR and SIR values (all p < 0.05) but not in the SNR or ADC values (all p > 0.05). The ICC values and Bland-Altman plots also showed excellent agreement between the measured ADC values of the bladder lesions.

Conclusions

The RS-EPI technique provides significantly better image quality in patients with bladder cancer than the SS-EPI technique, without a significant difference in the ADC value.

Validation of the corticomedullary difference in magnetic resonance imaging-derived apparent diffusion coefficient for kidney fibrosis detection: a cross-sectional study

Background

Kidney cortical interstitial fibrosis (IF) is highly predictive of renal prognosis and is currently assessed by the evaluation of a biopsy. Diffusion magnetic resonance imaging (MRI) is a promising tool to evaluate kidney fibrosis via the apparent diffusion coefficient (ADC), but suffers from inter-individual variability. We recently applied a novel MRI protocol to allow calculation of the corticomedullary ADC difference (ΔADC). We here present the validation of ΔADC for fibrosis assessment in a cohort of 164 patients undergoing biopsy and compare it with estimated glomerular filtration rate (eGFR) and other plasmatic parameters for the detection of fibrosis.

Methods

This monocentric cross-sectional study included 164 patients undergoing renal biopsy at the Nephrology Department of the University Hospital of Geneva between October 2014 and May 2018. Patients underwent diffusion-weighted imaging, and T1 and T2 mappings, within 1 week after biopsy. MRI results were compared with gold standard histology for fibrosis assessment.

Results

Absolute cortical ADC or cortical T1 values correlated poorly to IF assessed by the biopsy, whereas ΔADC was highly correlated to IF (r=−0.52, P &lt; 0.001) and eGFR (r = 0.37, P &lt; 0.01), in both native and allograft patients. ΔT1 displayed a lower, but significant, correlation to IF and eGFR, whereas T2 did not correlate to IF nor to eGFR. ΔADC, ΔT1 and eGFR were independently associated with kidney fibrosis, and their combination allowed detection of extensive fibrosis with good specificity.

Conclusion

ΔADC is better correlated to IF than absolute cortical or medullary ADC values. ΔADC, ΔT1 and eGFR are independently associated to IF and allow the identification of patients with extensive IF.

Diffusion-weighted magnetic resonance imaging to assess diffuse renal pathology: a systematic review and statement paper

Diffusion-weighted magnetic resonance imaging (DWI) is a non-invasive method sensitive to local water motion in the tissue. As a tool to probe the microstructure, including the presence and potentially the degree of renal fibrosis, DWI has the potential to become an effective imaging biomarker. The aim of this review is to discuss the current status of renal DWI in diffuse renal diseases. DWI biomarkers can be classified in the following three main categories: (i) the apparent diffusion coefficient-an overall measure of water diffusion and microcirculation in the tissue; (ii) true diffusion, pseudodiffusion and flowing fraction-providing separate information on diffusion and perfusion or tubular flow; and (iii) fractional anisotropy-measuring the microstructural orientation. An overview of human studies applying renal DWI in diffuse pathologies is given, demonstrating not only the feasibility and intra-study reproducibility of DWI but also highlighting the need for standardization of methods, additional validation and qualification. The current and future role of renal DWI in clinical practice is reviewed, emphasizing its potential as a surrogate and monitoring biomarker for interstitial fibrosis in chronic kidney disease, as well as a surrogate biomarker for the inflammation in acute kidney diseases that may impact patient selection for renal biopsy in acute graft rejection. As part of the international COST (European Cooperation in Science and Technology) action PARENCHIMA (Magnetic Resonance Imaging Biomarkers for Chronic Kidney Disease), aimed at eliminating the barriers to the clinical use of functional renal magnetic resonance imaging, this article provides practical recommendations for future design of clinical studies and the use of renal DWI in clinical practice.

Renal Functional MRI and Its Application

Renal function varies according to the nature and stage of diseases. Renal functional magnetic resonance imaging (fMRI), a technique considered superior to the most common method used to estimate the glomerular filtration rate, allows for noninvasive, accurate measurements of renal structures and functions in both animals and humans. It has become increasingly prevalent in research and clinical applications. In recent years, renal fMRI has developed rapidly with progress in MRI hardware and emerging postprocessing algorithms. Function-related imaging markers can be acquired via renal fMRI, encompassing water molecular diffusion, perfusion, and oxygenation. This review focuses on the progression and challenges of the main renal fMRI methods, including dynamic contrast-enhanced MRI, blood oxygen level-dependent MRI, diffusion-weighted imaging, diffusion tensor imaging, arterial spin labeling, fat fraction imaging, and their recent clinical applications.

LEVEL OF EVIDENCE

5 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2018;48:863-881.