Assessment of Chronic Allograft Injury in Renal Transplantation Using Diffusional Kurtosis Imaging

Abstract Background: Chronic allograft injury (CAI) is a significant reason for which many grafts were lost. The study was conducted to assess the usefulness of diffusional kurtosis imaging (DKI) technology in the non-invasive assessment of CAI. Methods: Between February 2019 and October 2019, 110 renal allograft recipients were included to analyze relevant DKI parameters. According to estimated glomerular filtration rate (eGFR) (mL/min/ 1.73m2) level, they were divided to 3 groups: group 1, eGFR≥60 (n=10); group 2, eGFR 30–60 (n=69); group 3, eGFR<30 (n=31). We performed DKI on a clinical 3T magnetic resonance imaging (MRI) system. We measured the area of interest to determine the mean kurtosis (MK), mean diffusivity (MD), and apparent diffusion coefficient (ADC) of the renal cortex and medulla. We performed a Pearson correlation analysis to determine the relationship between eGFR and the DKI parameters. We used the receiver operating characteristic (ROC) curve to estimate the predicted values of DKI parameters in the CAI evaluation. We randomly selected five patients from group 2 for biopsy to confirm CAI.Results: With the increase of creatinine, ADC, and MD of the cortex and medulla decrease, while MK of the cortex and medulla gradually increase. Among the three different eGFR groups, significant differences were found in cortical and medullary MK (P =0.039, P <0.001, P <0.001, respectively). Cortical and medullary ADC and MD are negatively correlated with eGFR (r=-0.49, -0.44, -0.57, -0.57, respectively; P<0.001), while cortical and medullary MK are positively correlated with eGFR (r=0.42, 0.38; P<0.001). When 0.491 was set as the cutoff value, MK's CAI assessment showed 87% sensitivity and 100% specificity. All five patients randomly selected for biopsy from the second group confirmed glomerulosclerosis and tubular atrophy/interstitial fibrosis.Conclusion: The DKI technique is related to eGFR as allograft injury progresses, and is expected to become a potential non-invasive method for evaluating CAI.

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Assessment of chronic allograft injury in renal transplantation using diffusional kurtosis imaging

BMC Medical Imaging ◽

10.1186/s12880-021-00595-3 ◽

2021 ◽

Vol 21 (1) ◽

Author(s):

Xin Zheng ◽

Min Li ◽

Pan Wang ◽

Xiangnan Li ◽

Qiang Zhang ◽

...

Keyword(s):

Imaging System ◽

Interstitial Fibrosis ◽

Pearson Correlation ◽

Characteristic Curve ◽

Mean Diffusivity ◽

Magnetic Resonance Imaging System ◽

Diffusional Kurtosis Imaging ◽

Non Invasive ◽

Area Of Interest ◽

Group 2

Abstract Background Chronic allograft injury (CAI) is a significant reason for which many grafts were lost. The study was conducted to assess the usefulness of diffusional kurtosis imaging (DKI) technology in the non-invasive assessment of CAI. Methods Between February 2019 and October 2019, 110 renal allograft recipients were included to analyze relevant DKI parameters. According to estimated glomerular filtration rate (eGFR) (mL/min/ 1.73 m2) level, they were divided to 3 groups: group 1, eGFR ≥ 60 (n = 10); group 2, eGFR 30–60 (n = 69); group 3, eGFR < 30 (n = 31). We performed DKI on a clinical 3T magnetic resonance imaging system. We measured the area of interest to determine the mean kurtosis (MK), mean diffusivity (MD), and apparent diffusion coefficient (ADC) of the renal cortex and medulla. We performed a Pearson correlation analysis to determine the relationship between eGFR and the DKI parameters. We used the receiver operating characteristic curve to estimate the predicted values of DKI parameters in the CAI evaluation. We randomly selected five patients from group 2 for biopsy to confirm CAI. Results With the increase of creatinine, ADC, and MD of the cortex and medulla decrease, MK of the cortex and medulla gradually increase. Among the three different eGFR groups, significant differences were found in cortical and medullary MK (P = 0.039, P < 0.001, P < 0.001, respectively). Cortical and medullary ADC and MD are negatively correlated with eGFR (r = − 0.49, − 0.44, − 0.57, − 0.57, respectively; P < 0.001), while cortical and medullary MK are positively correlated with eGFR (r = 0.42, 0.38; P < 0.001). When 0.491 was set as the cutoff value, MK's CAI assessment showed 87% sensitivity and 100% specificity. All five patients randomly selected for biopsy from the second group confirmed glomerulosclerosis and tubular atrophy/interstitial fibrosis. Conclusion The DKI technique is related to eGFR as allograft injury progresses and is expected to become a potential non-invasive method for evaluating CAI.

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Biomarkers of Chronic Renal Tubulointerstitial Injury

Journal of Histochemistry & Cytochemistry ◽

10.1369/0022155419861092 ◽

2019 ◽

Vol 67 (9) ◽

pp. 633-641 ◽

Cited By ~ 1

Author(s):

Serena M. Bagnasco ◽

Avi Z. Rosenberg

Keyword(s):

Interstitial Fibrosis ◽

Renal Tissue ◽

Experimental Models ◽

Renal Outcome ◽

Tubulointerstitial Injury ◽

Tubular Atrophy ◽

Non Invasive ◽

Diagnosis And Prognosis

Progression of renal parenchyma injury is characterized by increasing interstitial fibrosis and tubular atrophy, irrespective of the cause. Histopathologic assessment of renal tissue obtained by biopsy remains the gold standard for determining the presence and extent of tubulointerstitial scarring. Discovery of robust non-invasive means for capturing a snapshot and for longitudinal monitoring of parenchymal deterioration has been the focus of intense multimodal effort by investigators within the renal community and beyond. Research in this field has included the use of in vitro and in vivo experimental models and has fostered the development and evaluation of tissue and biofluid assays for novel analytes with potential translation to the diagnosis and prognosis of kidney disease. Here, we examine recent advances in the search of “biomarkers” for detection of renal tubulointerstitial scarring and prediction of renal outcome in human renal disease.

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Biopsy-Controlled Non-Invasive Quantification of Collagen Type VI in Kidney Transplant Recipients: A Post-Hoc Analysis of the MECANO Trial

Journal of Clinical Medicine ◽

10.3390/jcm9103216 ◽

2020 ◽

Vol 9 (10) ◽

pp. 3216

Author(s):

Manuela Yepes-Calderón ◽

Camilo G. Sotomayor ◽

Daniel Guldager Kring Rasmussen ◽

Ryanne S. Hijmans ◽

Charlotte A. te Velde-Keyzer ◽

...

Keyword(s):

Kidney Transplantation ◽

Collagen Type ◽

Interstitial Fibrosis ◽

Controlled Trial ◽

Kidney Transplant Recipients ◽

Tubular Atrophy ◽

Post Hoc Analysis ◽

Non Invasive ◽

Collagen Type Vi ◽

Post Hoc

The PRO-C6 assay, a reflection of collagen type VI synthesis, has been proposed as a non-invasive early biomarker of kidney fibrosis. We aimed to investigate cross-sectional and longitudinal associations between plasma and urine PRO-C6 and proven histological changes after kidney transplantation. The current study is a post-hoc analysis of 94 participants of the MECANO trial, a 24-month prospective, multicenter, open-label, randomized, controlled trial aimed at comparing everolimus-based vs. cyclosporine-based immunosuppression. PRO-C6 was measured in plasma and urine samples collected 6 and 24 months post-transplantation. Fibrosis was evaluated in biopsies collected at the same time points by Banff interstitial fibrosis/tubular atrophy (IF/TA) scoring and collagen staining (Picro Sirius Red; PSR); inflammation was evaluated by the tubulo-interstitial inflammation score (ti-score). Linear regression analyses were performed. Six-month plasma PRO-C6 was cross-sectionally associated with IF/TA score (Std. β = 0.34), and prospectively with 24-month IF/TA score and ti-score (Std. β = 0.24 and 0.23, respectively) (p < 0.05 for all). No significant associations were found between urine PRO-C6 and any of the biopsy findings. Fibrotic changes and urine PRO-C6 behaved differentially over time according to immunosuppressive therapy. These results are a first step towards non-invasive fibrosis detection after kidney transplantation by means of collagen VI synthesis measurement, and further research is required.

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Effect of resveratrol on tubular damage and interstitial fibrosis in kidneys of rats exposed to cigarette smoke

Toxicology and Industrial Health ◽

10.1177/0748233709346755 ◽

2009 ◽

Vol 25 (8) ◽

pp. 539-544 ◽

Cited By ~ 22

Author(s):

Meltem Kuruş ◽

Murat Ugras ◽

Mukaddes Esrefoglu

Keyword(s):

Cigarette Smoke ◽

Interstitial Fibrosis ◽

Periodic Acid ◽

Control Group ◽

Albino Rats ◽

Tubular Damage ◽

Tubular Atrophy ◽

Hydropic Degeneration ◽

Group 4 ◽

Group 2

The aim of this study was to evaluate the effect of resveratrol on kidney tissue of rats exposed to cigarette smoke. Forty adult male Wistar Albino rats were divided into four groups. Animals in group 1 was the control group. For 6 weeks, group 2 was exposed to cigarette smoke; group 3 received daily intraperitoneal injections of resveratrol (10 mg/kg/d); and group 4 was exposed to both cigarette smoke and intraperitoneal resveratrol. All rats were sacrificed with cervical dislocation. The kidney tissues were obtained, fixed in Bouin’s fixative and embeded in paraffin blocks. Samples were sectioned to 4-5 microns thickness, stained with hematoxylin/eosin (H/E), Masson’s trichromic, periodic acid-schiff (PAS) and were examined by light microscopy for tubular injury and interstitial fibrosis. Results were compared by non-parametric tests. Hydropic degeneration, tubular atrophy, tubulo-interstitial fibrosis, interstitial cell infiltration, vacuolar degeneration and desquamation were prominent in group 2. In group 4, hydropic degeneration, epithelial cell vacuolization and desquamation was not observed, but occasional tubular atrophy and dilation were observed. Our study suggests that, some morphological alterations in the rat kidney, due to cigarette smoke may be prevented by resveratrol.

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Artificial Intelligence assessment of Renal Scarring (AIRS study)

Kidney360 ◽

10.34067/kid.0003662021 ◽

2021 ◽

pp. 10.34067/KID.0003662021

Author(s):

Chanon Chantaduly ◽

Hayden R. Troutt ◽

Karla A. Perez Reyes ◽

Jonathan E. Zuckerman ◽

Peter D. Chang ◽

...

Keyword(s):

Artificial Intelligence ◽

Machine Learning ◽

Kidney Biopsy ◽

Interstitial Fibrosis ◽

Renal Scarring ◽

Machine Learning Algorithms ◽

Ct Scans ◽

Tubular Atrophy ◽

Kidney Fibrosis ◽

Non Invasive

Background: The goal of the Artificial Intelligence in Renal Scarring (AIRS) study is to develop machine learning tools for non-invasive quantification of kidney fibrosis from imaging scans. Methods: We conducted a retrospective analysis of patients who had one or more abdominal computed tomography (CT) scans within 6 months of a kidney biopsy. The final cohort encompassed 152 CT scans from 92 patients which included images of 300 native kidneys and 76 transplant kidneys. Two different convolutional neural networks (slice-level and voxel-level classifiers) were tested to differentiate severe vs mild/moderate kidney fibrosis (≥50% vs <50%). Interstitial fibrosis and tubular atrophy scores from kidney biopsy reports were used as ground-truth. Results: The two machine learning models demonstrated similar positive predictive value (0.886 vs 0.935) and accuracy (0.831 vs 0.879). Conclusions: In summary, machine learning algorithms are a promising non-invasive diagnostic tool to quantify kidney fibrosis from CT scans. The clinical utility of these prediction tools, in terms of avoiding renal biopsy and associated bleeding risks in patients with severe fibrosis, remains to be validated in prospective clinical trials.

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Urinary vitronectin identifies patients with high levels of fibrosis in kidney grafts

Journal of Nephrology ◽

10.1007/s40620-020-00886-y ◽

2020 ◽

Author(s):

Laura Carreras-Planella ◽

David Cucchiari ◽

Laura Cañas ◽

Javier Juega ◽

Marcella Franquesa ◽

...

Keyword(s):

Differential Expression ◽

Kidney Transplant ◽

Interstitial Fibrosis ◽

Calcineurin Inhibitors ◽

Enzyme Linked Immunosorbent Assay ◽

Transplant Recipients ◽

Kidney Transplant Recipients ◽

Tubular Atrophy ◽

Non Invasive ◽

Noninvasive Biomarkers

Abstract Background In kidney transplantation, fibrosis represents the final and irreversible consequence of the pathogenic mechanisms that lead to graft failure, and in the late stages it irremediably precedes the loss of renal function. The invasiveness of kidney biopsy prevents this condition from being frequently monitored, while clinical data are rather unspecific. The objective of this study was to find noninvasive biomarkers of kidney rejection. Methods We carried out proteomic analysis of the urinary Extracellular Vesicles (uEVs) from a cohort of kidney transplant recipients (n = 23) classified according to their biopsy-based diagnosis and clinical parameters as interstitial fibrosis and tubular atrophy (IFTA), acute cellular rejection (ACR), calcineurin inhibitors toxicity (CNIT) and normal kidney function (NKF). Results Shotgun mass spectrometry of uEV-proteins identified differential expression of several proteins among these different groups. Up to 23 of these proteins were re-evaluated using targeted proteomics in a new independent cohort of patients (n = 41) classified in the same diagnostic groups. Among other results, we found a differential expression of vitronectin (VTN) in patients displaying chronic interstitial and tubular lesions (ci and ct mean > 2 according to Banff criteria). These results were further confirmed by a pilot study using enzyme-linked immunosorbent assay (ELISA). Conclusion Urinary vitronectin levels are a potential stand-alone biomarker to monitor fibrotic changes in kidney transplant recipients in a non-invasive fashion.

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Exploratory Study of Apparent Diffusion Coefficient Histogram Metrics in Assessing Pancreatic Malignancy

Canadian Association of Radiologists Journal ◽

10.1016/j.carj.2019.07.001 ◽

2019 ◽

Vol 70 (4) ◽

pp. 416-423 ◽

Cited By ~ 1

Author(s):

Myles T. Taffel ◽

Lyndon Luk ◽

Justin M. Ream ◽

Andrew B. Rosenkrantz

Keyword(s):

Diffusion Coefficient ◽

Apparent Diffusion Coefficient ◽

Area Under The Curve ◽

Nodal Status ◽

Non Invasive ◽

T Stage ◽

Abdominal Magnetic Resonance Imaging ◽

Pancreatic Malignancy ◽

Apparent Diffusion ◽

Magnetic Resonance Imaging Mri

Purpose To evaluate whole-lesion 3D-histogram apparent diffusion coefficient (ADC) metrics for assessment of pancreatic malignancy. Methods Forty-two pancreatic malignancies (36 pancreatic adenocarcinoma [PDAC], 6 pancreatic neuroendocrine [PanNET]) underwent abdominal magnetic resonance imaging (MRI) with diffusion-weighted imaging before endoscopic ultrasound biopsy or surgical resection. Two radiologists independently placed 3D volumes of interest to derive whole-lesion histogram ADC metrics. Mann-Whitney tests and receiver operating characteristic analyses were used to assess metrics’ diagnostic performance for lesion histology, T-stage, N-stage, and grade. Results Whole-lesion ADC histogram metrics lower in PDACs than PanNETs for both readers ( P ≤ .026) were mean ADC (area under the curve [AUC] = 0.787-0.792), mean of the bottom 10th percentile (mean0-10) (AUC = 0.787-0.880), mean of the 10th-25th percentile (mean10-25) (AUC = 0.884-0.917) and mean of the 25th-50th percentile (mean25-50) (AUC = 0.829-0.829). For mean10-25 (metric with highest AUC for identifying PDAC), for reader 1 a threshold > 0.94 × 10−3 mm2/s achieved sensitivity 94% and specificity 83%, and for reader 2 a threshold > 0.82 achieved sensitivity 97% and specificity 67%. Metrics lower in nodal status ≥ N1 than N0 for both readers ( P ≤ .043) were mean0-10 (AUC = 0.789-0.822) and mean10-25 (AUC = 0.800-0.822). For mean10-25 (metric with highest AUC for identifying N0), for reader 1 a threshold <1.17 achieved sensitivity 87% and specificity 67%, and for reader 2 a threshold <1.04 achieved sensitivity 87% and specificity 83%. No metric was associated with T-stage ( P > .195) or grade ( P > .215). Conclusion Volumetric ADC histogram metrics may serve as non-invasive biomarkers of pancreatic malignancy. Mean10-25 outperformed standard mean for lesion histology and nodal status, supporting the role of histogram analysis.

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Multiparametric MRI-based radiomics analysis: differentiation of subtypes of cervical cancer in the early stage

Acta Radiologica ◽

10.1177/02841851211014188 ◽

2021 ◽

pp. 028418512110141

Author(s):

Wei Wang ◽

YiNing Jiao ◽

LiChi Zhang ◽

Caixia Fu ◽

XiaoLi Zhu ◽

...

Keyword(s):

Cervical Cancer ◽

Early Stage ◽

Area Under The Curve ◽

Multiparametric Mri ◽

Pelvic Mri ◽

Non Invasive ◽

Contrast Enhanced ◽

Apparent Diffusion ◽

Magnetic Resonance Imaging Mri ◽

Mr Sequences

Background There are significant differences in outcomes for different histological subtypes of cervical cancer (CC). Yet, it is difficult to distinguish CC subtypes using non-invasive methods. Purpose To investigate whether multiparametric magnetic resonance imaging (MRI)-based radiomics analysis can differentiate CC subtypes and explore tumor heterogeneity. Material and Methods This study retrospectively analyzed 96 patients with CC (squamous cell carcinoma [SCC] = 50, adenocarcinoma [AC] = 46) who underwent pelvic MRI before surgery. Radiomics features were extracted from the tumor volumes on five sequences (sagittal T2-weighted imaging [T2SAG], transverse T2-weighted imaging [T2TRA], sagittal contrast-enhanced T1-weighted imaging [CESAG], transverse contrast-enhanced T1-weighted imaging [CETRA], and apparent diffusion coefficient [ADC]). Clustering and logistic regression were used to examine the distinguishing capabilities of radiomics features extracted from five different MR sequences. Results Among the 105 extracted radiomics features, there were 51, 38, 37, and 2 features that showed intergroup differences for T2SAG, T2TRA, ADC, and CESAG, respectively (all P < 0.05). AC had greater textural heterogeneity than SCC ( P < 0.05). Upon unsupervised clustering of significantly different features, T2SAG achieved the highest accuracy (0.844; sensitivity = 0.920; specificity = 0.761). The largest area under the curve (AUC) for classification ability was 0.86 for T2SAG. Hence, the radiomics model from five combined MR sequences (AUC = 0.89; accuracy = 0.81; sensitivity = 0.67; specificity = 0.94) exhibited better differentiation ability than any MR sequence alone. Conclusion Multiparametric MRI-based radiomics models may be a promising method to differentiate AC and SCC. AC showed more heterogeneous features than SCC.

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Proteomic Characterization of Urinary Extracellular Vesicles from Kidney-Transplanted Patients Treated with Calcineurin Inhibitors

International Journal of Molecular Sciences ◽

10.3390/ijms21207569 ◽

2020 ◽

Vol 21 (20) ◽

pp. 7569

Author(s):

Laura Carreras-Planella ◽

Javier Juega ◽

Omar Taco ◽

Laura Cañas ◽

Marcella Franquesa ◽

...

Keyword(s):

Extracellular Vesicles ◽

Interstitial Fibrosis ◽

Immunosuppressive Agents ◽

Calcineurin Inhibitors ◽

Immunosuppressive Drugs ◽

Protein Biomarkers ◽

Tubular Atrophy ◽

Kidney Fibrosis ◽

Non Invasive ◽

Specific Effects

Use of immunosuppressive drugs is still unavoidable in kidney-transplanted patients. Since their discovery, calcineurin inhibitors (CNI) have been considered the first-line immunosuppressive agents, in spite of their known nephrotoxicity. Chronic CNI toxicity (CNIT) may lead to kidney fibrosis, a threatening scenario for graft survival. However, there is still controversy regarding CNIT diagnosis, monitoring and therapeutic management, and their specific effects at the molecular level are not fully known. Aiming to better characterize CNIT patients, in the present study, we collected urine from kidney-transplanted patients treated with CNI who (i) had a normal kidney function, (ii) suffered CNIT, or (iii) presented interstitial fibrosis and tubular atrophy (IFTA). Urinary extracellular vesicles (uEV) were enriched and the proteome was analyzed to get insight into changes happening during CNI. Members of the uroplakin and plakin families were significantly upregulated in the CNIT group, suggesting an important role in CNIT processes. Although biomarkers cannot be asserted from this single pilot study, our results evidence the potential of uEV as a source of non-invasive protein biomarkers for a better detection and monitoring of this renal alteration in kidney-transplanted patients.

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A Novel Urinary Proteomics Classifier for Non-Invasive Evaluation of Interstitial Fibrosis and Tubular Atrophy in Chronic Kidney Disease

Proteomes ◽

10.3390/proteomes9030032 ◽

2021 ◽

Vol 9 (3) ◽

pp. 32

Author(s):

Lorenzo Catanese ◽

Justyna Siwy ◽

Emmanouil Mavrogeorgis ◽

Kerstin Amann ◽

Harald Mischak ◽

...

Keyword(s):

Mass Spectrometry ◽

Chronic Kidney Disease ◽

Renal Fibrosis ◽

Kidney Biopsy ◽

Interstitial Fibrosis ◽

Peptide Fragments ◽

Tubular Atrophy ◽

Non Invasive ◽

Urinary Peptide ◽

Urinary Peptides

Non-invasive urinary peptide biomarkers are able to detect and predict chronic kidney disease (CKD). Moreover, specific urinary peptides enable discrimination of different CKD etiologies and offer an interesting alternative to invasive kidney biopsy, which cannot always be performed. The aim of this study was to define a urinary peptide classifier using mass spectrometry technology to predict the degree of renal interstitial fibrosis and tubular atrophy (IFTA) in CKD patients. The urinary peptide profiles of 435 patients enrolled in this study were analyzed using capillary electrophoresis coupled with mass spectrometry (CE-MS). Urine samples were collected on the day of the diagnostic kidney biopsy. The proteomics data were divided into a training (n = 200) and a test (n = 235) cohort. The fibrosis group was defined as IFTA ≥ 15% and no fibrosis as IFTA < 10%. Statistical comparison of the mass spectrometry data enabled identification of 29 urinary peptides with differential occurrence in samples with and without fibrosis. Several collagen fragments and peptide fragments of fetuin-A and others were combined into a peptidomic classifier. The classifier separated fibrosis from non-fibrosis patients in an independent test set (n = 186) with area under the curve (AUC) of 0.84 (95% CI: 0.779 to 0.889). A significant correlation of IFTA and FPP_BH29 scores could be observed Rho = 0.5, p < 0.0001. We identified a peptidomic classifier for renal fibrosis containing 29 peptide fragments corresponding to 13 different proteins. Urinary proteomics analysis can serve as a non-invasive tool to evaluate the degree of renal fibrosis, in contrast to kidney biopsy, which allows repeated measurements during the disease course.

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