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Selby NM, Francis ST. Assessment of Acute Kidney Injury using MRI. J Magn Reson Imaging 2025; 61:25-41. [PMID: 38334370 PMCID: PMC11645494 DOI: 10.1002/jmri.29281] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/30/2023] [Revised: 01/19/2024] [Accepted: 01/23/2024] [Indexed: 02/10/2024] Open
Abstract
There has been growing interest in using quantitative magnetic resonance imaging (MRI) to describe and understand the pathophysiology of acute kidney injury (AKI). The ability to assess kidney blood flow, perfusion, oxygenation, and changes in tissue microstructure at repeated timepoints is hugely appealing, as this offers new possibilities to describe nature and severity of AKI, track the time-course to recovery or progression to chronic kidney disease (CKD), and may ultimately provide a method to noninvasively assess response to new therapies. This could have significant clinical implications considering that AKI is common (affecting more than 13 million people globally every year), harmful (associated with short and long-term morbidity and mortality), and currently lacks specific treatments. However, this is also a challenging area to study. After the kidney has been affected by an initial insult that leads to AKI, complex coexisting processes ensue, which may recover or can progress to CKD. There are various preclinical models of AKI (from which most of our current understanding derives), and these differ from each other but more importantly from clinical AKI. These aspects are fundamental to interpreting the results of the different AKI studies in which renal MRI has been used, which encompass different settings of AKI and a variety of MRI measures acquired at different timepoints. This review aims to provide a comprehensive description and interpretation of current studies (both preclinical and clinical) in which MRI has been used to assess AKI, and discuss future directions in the field. LEVEL OF EVIDENCE: 1 TECHNICAL EFFICACY: Stage 3.
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Affiliation(s)
- Nicholas M Selby
- Centre for Kidney Research and Innovation, Academic Unit for Translational Medical Sciences, School of Medicine, University of Nottingham, Nottingham, UK
- Department of Renal Medicine, University Hospitals of Derby and Burton NHS Foundation Trust, Derby, UK
| | - Susan T Francis
- Sir Peter Mansfield Imaging Centre, School of Physics and Astronomy, University of Nottingham, Nottingham, UK
- NIHR Nottingham Biomedical Research Centre, Nottingham University Hospitals NHS Trust and The University of Nottingham, Nottingham, UK
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Wang Y, Wang B, Qin J, Yan H, Chen H, Guo J, Wu PY, Wang X. Use of multiparametric MRI to noninvasively assess iodinated contrast-induced acute kidney injury. Magn Reson Imaging 2024; 114:110248. [PMID: 39357626 DOI: 10.1016/j.mri.2024.110248] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/25/2024] [Revised: 09/06/2024] [Accepted: 09/29/2024] [Indexed: 10/04/2024]
Abstract
PURPOSE To gauge the utility of multiparametric MRI in characterizing pathologic changes after iodinated contrast-induced acute kidney injury (CI-AKI) in rats. METHODS We randomly grouped 24 rats injected with 8 g iodine/kg of body weight (n = 6 each) and 6 rats injected with saline as controls. All rats underwent T1, T2 mapping and diffusion kurtosis imaging (DKI) after contrast injection at 0 (control), 1, 3, 7, 13 days. T1, T2, and mean kurtosis (MK) values were performed in renal outer/inner stripes of outer medulla (OSOM and ISOM) and cortex (CO), and their diagnosis performance for CI-AKI also been evaluated. Serum creatinine (SCr), insulin-like growth factor-binding protein 7 (IGFBP7), tissue inhibitor metalloproteinase 2 (TIMP-2), aquaporin-1 (AQP1), α-smooth muscle actin (α-SMA), and histologic indices were examined. RESULTS Compared with controls, urinary concentrations of both TIMP-2 and IGFBP7 were obviously elevated from Day 1 to Day 13 (all p < 0.05). T2 values were significantly higher than control group for Days 1 and 3, and T1 and MK increased were more remarkable at all time points (Days 1-13) in CI-AKI (all p < 0.05) than control group. Changes in T1 and MK strongly correlated with renal injury scores of all anatomical compartments and with expression levels of AQP1 and moderately correlated with α-SMA. Changes in T2 values correlating moderately with renal scores of CO, ISOM and OSOM and AQP1. The MK obtained the highest area under the receiver operating characteristic (ROC) curve of 0.846 with a sensitivity of 70.8 % and specificity of 88.9 %. CONCLUSIONS Combined use of multiparametric MRI could be a valid noninvasive method for comprehensive monitoring of CI-AKI. Among these parameters, MK may achieve the best diagnostic performance for CI-AKI.
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Affiliation(s)
- Yongfang Wang
- Department of Medical Imaging, First Hospital of Shanxi Medical University, Taiyuan 030000, Shanxi, China; Shanxi Key Laboratory of Intelligent Imaging, The First Hospital of Shanxi Medical University, Taiyuan, Shanxi Province, China, 030001; Department of Medical Imaging, Shanxi Medical University, Taiyuan 030000, Shanxi, China
| | - Bin Wang
- Department of Medical Imaging, First Hospital of Shanxi Medical University, Taiyuan 030000, Shanxi, China
| | - Jiangbo Qin
- Department of Medical Imaging, First Hospital of Shanxi Medical University, Taiyuan 030000, Shanxi, China
| | - Haili Yan
- Department of Medical Imaging, First Hospital of Shanxi Medical University, Taiyuan 030000, Shanxi, China
| | - Haoyuan Chen
- Department of Medical Imaging, First Hospital of Shanxi Medical University, Taiyuan 030000, Shanxi, China; Department of Medical Imaging, Shanxi Medical University, Taiyuan 030000, Shanxi, China
| | - Jinxia Guo
- GE Healthcare, MR Research China, Beijing 100000, China.
| | - Pu-Yeh Wu
- GE Healthcare, MR Research China, Beijing 100000, China
| | - Xiaochun Wang
- Department of Medical Imaging, First Hospital of Shanxi Medical University, Taiyuan 030000, Shanxi, China; Shanxi Key Laboratory of Intelligent Imaging, The First Hospital of Shanxi Medical University, Taiyuan, Shanxi Province, China, 030001; Department of Medical Imaging, Shanxi Medical University, Taiyuan 030000, Shanxi, China.
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Qin J, Xie S, Yu Y, Yang J, Zhao Y, Qiu C, Li X, Zhang C, Hu Z, Tong D, Zhu J, Kuehn B, Shen W. Evaluation of Kidney Injury Using Arterial Spin Labeling and Blood Oxygen Level-Dependent MRI: An Experimental Study in Rats With Carbon Tetrachloride-Induced Liver Cirrhosis. J Magn Reson Imaging 2024; 60:2090-2101. [PMID: 38299767 DOI: 10.1002/jmri.29265] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/27/2023] [Revised: 01/16/2024] [Accepted: 01/17/2024] [Indexed: 02/02/2024] Open
Abstract
BACKGROUND Serum creatinine (Scr) may be not suited to timely and accurately reflect kidney injury related to chronic liver disease. Currently, the ability of arterial spin labeling (ASL) and blood oxygen level-dependent (BOLD) sequences to evaluate renal blood flow (RBF) and blood oxygen in chronic liver disease remains to be verified. PURPOSE To investigate the value of ASL and BOLD imaging in evaluating hemodynamics and oxygenation changes during kidney injury in an animal model of chronic liver disease. STUDY TYPE Prospective. ANIMAL MODEL Chronic liver disease model was established by subcutaneous injection of carbon tetrachloride. Forty-three male Sprague-Dawley rats (8 weeks) were divided into a pathological group (0, 2, 4, 6, 8, 12 weeks, each group: N = 6) and a continuous-scanning group (N = 7). FIELD STRENGTH/SEQUENCE 3-T, ASL, BOLD, and T2W. ASSESSMENT Regions of interest in the cortex (CO), outer stripe of the outer medulla (OSOM), and inner stripe of the outer medulla (ISOM) are manually delineated. The RBF and T2* values at each time point (0, 2, 4, 6, 8, 12 weeks) are measured and compared. Hematoxylin-eosin score (HE Score, damage area scoring method), alpha-smooth muscle actin (α-SMA), hypoxia-inducible factor-1alpha (HIF-1α), peritubular capillar (PTC) density, Scr, and neutrophil gelatinase-associated lipocalin were harvested. STATISTICAL TESTS Analysis of variance, Spearman correlation analysis, Kruskal-Wallis tests, and receiver operating characteristic analysis with the area under the curve (AUC). A P-value <0.05 was considered statistically significant. RESULTS Renal RBF and T2* values of CO, OSOM, and ISOM were significantly different from baseline. Both RBF and T2* were significantly correlated with HE Score, α-SMA, HIF-1α, and PTC density (|r| = 0.406-0.853). RBF demonstrated superior diagnostic capability in identifying severe kidney injury in this model of chronic liver disease (AUC = 0.964). DATA CONCLUSION Imaging by ASL and BOLD may detect renal hemodynamics and oxygenation changes related to chronic liver disease early. EVIDENCE LEVEL 5 TECHNICAL EFFICACY: Stage 2.
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Affiliation(s)
- Jiaming Qin
- The School of Medicine, Nankai University, Tianjin, China
| | - Shuangshuang Xie
- Department of Radiology, Tianjin First Central Hospital, Tianjin Institute of Imaging Medicine, Tianjin, China
| | - Yongquan Yu
- Department of Radiology, Weihai Central Hospital, Weihai, Shandong, China
| | - Jiaqi Yang
- First Central Clinical College, Tianjin Medical University, Tianjin, China
| | - Yumeng Zhao
- The School of Medicine, Nankai University, Tianjin, China
| | - Caixin Qiu
- Department of Radiology, Tianjin First Central Hospital, Tianjin Institute of Imaging Medicine, Tianjin, China
| | - Xiaotian Li
- The School of Medicine, Nankai University, Tianjin, China
| | - Cheng Zhang
- First Central Clinical College, Tianjin Medical University, Tianjin, China
| | - Zhandong Hu
- Department of Pathology, Tianjin First Central Hospital, Tianjin, China
| | - Dan Tong
- Department of Pathology, Tianjin First Central Hospital, Tianjin, China
| | - Jinxia Zhu
- MR Collaboration, Siemens Healthineers, Beijing, China
| | - Bernd Kuehn
- MR Application Predevelopment, Siemens Healthcare GmbH, Erlangen, Germany
| | - Wen Shen
- Department of Radiology, Tianjin First Central Hospital, Tianjin Institute of Imaging Medicine, Tianjin, China
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Chen L, Ren Y, Yuan Y, Xu J, Wen B, Xie S, Zhu J, Li W, Gong X, Shen W. Multi-parametric MRI-based machine learning model for prediction of pathological grade of renal injury in a rat kidney cold ischemia-reperfusion injury model. BMC Med Imaging 2024; 24:188. [PMID: 39060984 PMCID: PMC11282691 DOI: 10.1186/s12880-024-01320-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/11/2024] [Accepted: 06/04/2024] [Indexed: 07/28/2024] Open
Abstract
BACKGROUND Renal cold ischemia-reperfusion injury (CIRI), a pathological process during kidney transplantation, may result in delayed graft function and negatively impact graft survival and function. There is a lack of an accurate and non-invasive tool for evaluating the degree of CIRI. Multi-parametric MRI has been widely used to detect and evaluate kidney injury. The machine learning algorithms introduced the opportunity to combine biomarkers from different MRI metrics into a single classifier. OBJECTIVE To evaluate the performance of multi-parametric magnetic resonance imaging for grading renal injury in a rat model of renal cold ischemia-reperfusion injury using a machine learning approach. METHODS Eighty male SD rats were selected to establish a renal cold ischemia -reperfusion model, and all performed multiparametric MRI scans (DWI, IVIM, DKI, BOLD, T1mapping and ASL), followed by pathological analysis. A total of 25 parameters of renal cortex and medulla were analyzed as features. The pathology scores were divided into 3 groups using K-means clustering method. Lasso regression was applied for the initial selecting of features. The optimal features and the best techniques for pathological grading were obtained. Multiple classifiers were used to construct models to evaluate the predictive value for pathology grading. RESULTS All rats were categorized into mild, moderate, and severe injury group according the pathologic scores. The 8 features that correlated better with the pathologic classification were medullary and cortical Dp, cortical T2*, cortical Fp, medullary T2*, ∆T1, cortical RBF, medullary T1. The accuracy(0.83, 0.850, 0.81, respectively) and AUC (0.95, 0.93, 0.90, respectively) for pathologic classification of the logistic regression, SVM, and RF are significantly higher than other classifiers. For the logistic model and combining logistic, RF and SVM model of different techniques for pathology grading, the stable and perform are both well. Based on logistic regression, IVIM has the highest AUC (0.93) for pathological grading, followed by BOLD(0.90). CONCLUSION The multi-parametric MRI-based machine learning model could be valuable for noninvasive assessment of the degree of renal injury.
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Affiliation(s)
- Lihua Chen
- Department of Radiology, Tianjin First Central Hospital, Tianjin Institute of Imaging Medicine, No. 24 Fu Kang Road, Nan Kai District, Tianjin, 300192, China
| | - Yan Ren
- Department of Radiology, Tianjin First Central Hospital, Tianjin Institute of Imaging Medicine, No. 24 Fu Kang Road, Nan Kai District, Tianjin, 300192, China
| | - Yizhong Yuan
- Department of Radiology, Tianjin Medical University General Hospital, Tianjin, 300052, China
| | - Jipan Xu
- Department of Radiology, Tianjin First Central Hospital, Tianjin Institute of Imaging Medicine, No. 24 Fu Kang Road, Nan Kai District, Tianjin, 300192, China
| | - Baole Wen
- College of Medicine, Nankai University, Tianjin, 300350, China
| | - Shuangshuang Xie
- Department of Radiology, Tianjin First Central Hospital, Tianjin Institute of Imaging Medicine, No. 24 Fu Kang Road, Nan Kai District, Tianjin, 300192, China
| | - Jinxia Zhu
- MR Collaborations, Siemens Healthcare China, Beijing, 100102, China
| | - Wenshuo Li
- College of Computer Science, Nankai University, Tianjin, 300350, China
| | - Xiaoli Gong
- College of Computer Science, Nankai University, Tianjin, 300350, China
| | - Wen Shen
- Department of Radiology, Tianjin First Central Hospital, Tianjin Institute of Imaging Medicine, No. 24 Fu Kang Road, Nan Kai District, Tianjin, 300192, China.
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Chen PK, Cheng ZY, Wang YL, Xu BJ, Yu ZC, Li ZX, Gong SA, Zhang FT, Qian L, Cui W, Feng YZ, Cai XR. Renal interstitial fibrotic assessment using non-Gaussian diffusion kurtosis imaging in a rat model of hyperuricemia. BMC Med Imaging 2024; 24:78. [PMID: 38570748 PMCID: PMC10988851 DOI: 10.1186/s12880-024-01259-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/12/2023] [Accepted: 03/26/2024] [Indexed: 04/05/2024] Open
Abstract
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.
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Affiliation(s)
- Ping-Kang Chen
- Medical Imaging Center, The First Affiliated Hospital of Jinan University, No.613 West Huangpu Avenue, Tianhe District, Guangzhou, Guangdong, 510630, China
| | - Zhong-Yuan Cheng
- Medical Imaging Center, The First Affiliated Hospital of Jinan University, No.613 West Huangpu Avenue, Tianhe District, Guangzhou, Guangdong, 510630, China
| | - Ya-Lin Wang
- Medical Imaging Center, The First Affiliated Hospital of Jinan University, No.613 West Huangpu Avenue, Tianhe District, Guangzhou, Guangdong, 510630, China
| | - Bao-Jun Xu
- Medical Imaging Center, The First Affiliated Hospital of Jinan University, No.613 West Huangpu Avenue, Tianhe District, Guangzhou, Guangdong, 510630, China
| | - Zong-Chao Yu
- Nephrology department, The First Affiliated Hospital of Jinan University, Guangzhou, Guangdong, China
| | - Zhao-Xia Li
- Department of Rheumatology, The First Affiliated Hospital of Jinan University, Guangzhou, Guangdong, China
| | - Shang-Ao Gong
- Medical Imaging Center, The First Affiliated Hospital of Jinan University, No.613 West Huangpu Avenue, Tianhe District, Guangzhou, Guangdong, 510630, China
| | - Feng-Tao Zhang
- Intervention department, Huazhong University of Science and Technology Union Shenzhen Hospital, Shenzhen, Guangdong, China
| | - Long Qian
- Department of Biomedical Engineering, College of Engineering, Peking University, Beijing, China
| | - Wei Cui
- MRI Research, GE Healthcare, Beijing, China
| | - You-Zhen Feng
- Medical Imaging Center, The First Affiliated Hospital of Jinan University, No.613 West Huangpu Avenue, Tianhe District, Guangzhou, Guangdong, 510630, China.
| | - Xiang-Ran Cai
- Medical Imaging Center, The First Affiliated Hospital of Jinan University, No.613 West Huangpu Avenue, Tianhe District, Guangzhou, Guangdong, 510630, China.
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Wen D, Peng P, Yue X, Xu C, Pu Q, Ming Y, Yang H, Zhang M, Ren Y, Sun J. Comparative study of stretched-exponential and kurtosis models of diffusion-weighted imaging in renal assessment to distinguish patients with primary aldosteronism from healthy controls. PLoS One 2024; 19:e0298207. [PMID: 38330049 PMCID: PMC10852313 DOI: 10.1371/journal.pone.0298207] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/13/2023] [Accepted: 01/20/2024] [Indexed: 02/10/2024] Open
Abstract
PURPOSE To compare the ability of diffusion parameters obtained by stretched-exponential and kurtosis models of diffusion-weighted imaging (DWI) to distinguish between patients with primary aldosteronism (PA) and healthy controls (HCs) in renal assessment. MATERIALS AND METHODS A total of 44 participants (22 patients and 22 HCs) underwent renal MRI with an 11 b-value DWI sequence and a 3 b-value diffusion kurtosis imaging (DKI) sequence from June 2021 to April 2022. Binary logistic regression was used to construct regression models combining different diffusion parameters. Receiver-operating characteristic (ROC) curve analysis and comparisons were used to evaluate the ability of single diffusion parameters and combined diffusion models to distinguish between the two groups. RESULTS A total of six diffusion parameters (including the cortical anomalous exponent term [α_Cortex], medullary fractional anisotropy [FA_Medulla], cortical FA [FA_Cortex], cortical axial diffusivity [Da_Cortex], medullary mean diffusivity [MD_Medulla] and medullary radial diffusivity [Dr_Medulla]) were included, and 10 regression models were studied. The area under the curve (AUC) of Dr_Medulla was 0.855, comparable to that of FA_Cortex and FA_Medulla and significantly higher than that of α_Cortex, Da_Cortex and MD_Medulla. The AUC of the Model_all parameters was 0.967, comparable to that of Model_FA (0.946) and Model_DKI (0.966) and significantly higher than that of the other models. The sensitivity and specificity of Model_all parameters were 87.2% and 95%, respectively. CONCLUSION The Model_all parameters, Model_FA and Model_DKI were valid for differentiating between PA patients and HCs with similar differentiation efficacy and were superior to single diffusion parameters and other models.
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Affiliation(s)
- Deying Wen
- Department of Radiology, West China Hospital, Sichuan University, Chengdu, China
| | - Pengfei Peng
- Department of Radiology, West China Hospital, Sichuan University, Chengdu, China
| | - Xun Yue
- Department of Radiology, West China Hospital, Sichuan University, Chengdu, China
- Department of Radiology, Affiliated Hospital of North Sichuan Medical College, Nanchong, China
| | - Chenxiao Xu
- Department of Endocrinology and Metabolism, West China Hospital, Sichuan University, Chengdu, China
| | - Qian Pu
- Department of Radiology, West China Hospital, Sichuan University, Chengdu, China
| | - Yue Ming
- Department of Radiology, West China Hospital, Sichuan University, Chengdu, China
| | - Huiyi Yang
- Department of Radiology, West China Hospital, Sichuan University, Chengdu, China
| | | | - Yan Ren
- Department of Endocrinology and Metabolism, West China Hospital, Sichuan University, Chengdu, China
| | - Jiayu Sun
- Department of Radiology, West China Hospital, Sichuan University, Chengdu, China
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Zhu J, Chen A, Gao J, Zou M, Du J, Wu PY, Zhang J, Mao Y, Song Y, Chen M. Diffusion-weighted, intravoxel incoherent motion, and diffusion kurtosis tensor MR imaging in chronic kidney diseases: Correlations with histology. Magn Reson Imaging 2024; 106:1-7. [PMID: 37414367 DOI: 10.1016/j.mri.2023.07.002] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/02/2023] [Revised: 06/30/2023] [Accepted: 07/02/2023] [Indexed: 07/08/2023]
Abstract
OBJECTIVES To probe the correlations of parameters derived from standard DWI and its extending models including intravoxel incoherent motion (IVIM), diffusion tensor imaging (DTI), and diffusion kurtosis imaging (DKI) with the pathological and functional alterations in CKD. MATERIAL AND METHODS Seventy-nine CKD patients with renal biopsy and 10 volunteers were performed with DWI, IVIM, diffusion kurtosis tensor imaging (DKTI) scanning. Correlations between imaging results and the pathological damage [glomerulosclerosis index (GSI) and tubulointerstitial fibrosis index (TBI)], as well as eGFR, 24 h urinary protein and Scr) were evaluated.CKD patients were divided into 2 groups: group 1: both GSI and TBI scores <2 points (61 cases); group 2: both GSI and TBI scores ≥2 points (18 cases). RESULTS There were significant difference in cortical and medullary MD, and cortical D among 3 groups and between group 1 and 2. Cortical and medullary MD, cortical D, and medullary FA were negatively correlated with GSI score (r = -0.322 to -0.386, P < 0.05). Cortical and medullary MD and D, medullary FA were also negatively correlated with TBI score (r = -0.257 to -0.395, P < 0.05). These parameters were all correlated with eGFR and Scr. Cortical MD and D showed the highest AUC of 0.790 and 0.745 in discriminating mild and moderate-severe glomerulosclerosis and tubular interstitial fibrosis, respectively. CONCLUSIONS The corrected diffusion-related indices, including cortical and medullary D and MD, as well as medullary FA were superior to ADC, perfusion-related and kurtosis indices for evaluating the severity of renal pathology and function in CKD patients.
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Affiliation(s)
- Jie Zhu
- Department of Radiology, Beijing Hospital, National Center of Gerontology, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, 100730, PR China
| | - Aiqun Chen
- Department of Nephrology, Beijing Hospital, National Center of Gerontology, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, 100730, PR China
| | - Jiayin Gao
- Department of Radiology, Beijing Hospital, National Center of Gerontology, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, 100730, PR China
| | - Mingzhu Zou
- Department of Radiology, Beijing Hospital, National Center of Gerontology, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, 100730, PR China
| | - Jun Du
- Department of Pathology, Beijing Hospital, National Center of Gerontology, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, 100730, PR China
| | - Pu-Yeh Wu
- GE Healthcare, Beijing 100176, China
| | - Jintao Zhang
- Department of Radiology, Beijing Hospital, National Center of Gerontology, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, 100730, PR China
| | - Yonghui Mao
- Department of Nephrology, Beijing Hospital, National Center of Gerontology, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, 100730, PR China
| | - Yan Song
- Department of Radiology, Beijing Hospital, National Center of Gerontology, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, 100730, PR China.
| | - Min Chen
- Department of Radiology, Beijing Hospital, National Center of Gerontology, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, 100730, PR China.
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Xu Q, Song Q, Wang Y, Lin L, Tian S, Wang N, Wang J, Liu A. Amide proton transfer weighted combined with diffusion kurtosis imaging for predicting lymph node metastasis in cervical cancer. Magn Reson Imaging 2024; 106:85-90. [PMID: 38101652 DOI: 10.1016/j.mri.2023.12.001] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/14/2023] [Revised: 12/07/2023] [Accepted: 12/10/2023] [Indexed: 12/17/2023]
Abstract
OBJECTIVE To investigate the value of amide proton transfer weighted (APTw) combined with diffusion kurtosis imaging (DKI) in quantitative prediction of lymph node metastasis (LNM) in cervical carcinoma (CC). METHODS Data of 19 LNM(+) and 50 LNM(-) patients with CC were retrospectively analyzed. 3.0 T MRI scan was performed before the operation, including APTw and DKI. After post-processing, quantitative magnetization transfer ratio asymmetric at 3.5 ppm [MTRasym (3.5 ppm)], mean kurtosis (MK), and mean diffusivity (MD) maps were obtained. The MTRasym(3.5 ppm), MK, and MD values were respectively measured by two observers, and intra-class correlation coefficients (ICC) were used to test the consistency of the results. The independent samples t-test or Mann-Whitney U test was used to compare the differences in the values of each parameter. The ROC curve was used to analyze the predictive performance of parameters with significant differences and their combination parameter. RESULTS The two observers had good agreement in the measurement of each data (ICC > 0.75). The MTRasym(3.5 ppm) and MK values of the LNM(+) group(3.260 ± 0.538% and 0.531 ± 0.202) were higher than those of the LNM(-) group(2.698 ± 0.597% and 0.401 ± 0.148) (P < 0.05), while there was no significant difference in MD values between the two groups(P > 0.05). The area under the curves (AUCs) of MTRasym(3.5 ppm), MK value, and MTRasym(3.5 ppm) + MK value were 0.763, 0.716, and 0.813, respectively, when predicting LNM status of CC. CONCLUSION APTw and DKI can quantitatively predict LNM status of CC, which is of importance in clinical diagnosis and treatment.
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Affiliation(s)
- Qihao Xu
- Department of Radiology, the First Affiliated Hospital of Dalian Medical University, Dalian,China
| | - Qingling Song
- Department of Radiology, the First Affiliated Hospital of Dalian Medical University, Dalian,China
| | - Yue Wang
- Department of Radiology, the First Affiliated Hospital of Dalian Medical University, Dalian,China
| | - Liangjie Lin
- Clinical and Technical Support, Philips Healthcare, Beijing, China
| | - Shifeng Tian
- Department of Radiology, the First Affiliated Hospital of Dalian Medical University, Dalian,China
| | - Nan Wang
- Department of Radiology, the First Affiliated Hospital of Dalian Medical University, Dalian,China
| | - Jiazheng Wang
- Clinical and Technical Support, Philips Healthcare, Beijing, China
| | - Ailian Liu
- Department of Radiology, the First Affiliated Hospital of Dalian Medical University, Dalian,China; Dalian Medical Imaging Artificial Intelligence Engineering Technology Research Center, Dalian, China.
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Wang B, Wang Y, Wang J, Jin C, Zhou R, Guo J, Zhang H, Wang M. Multiparametric Magnetic Resonance Investigations on Acute and Long-Term Kidney Injury. J Magn Reson Imaging 2024; 59:43-57. [PMID: 37246343 DOI: 10.1002/jmri.28784] [Citation(s) in RCA: 8] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/26/2022] [Revised: 04/29/2023] [Accepted: 05/01/2023] [Indexed: 05/30/2023] Open
Abstract
Acute kidney injury (AKI) is a frequent complication of critical illness and carries a significant risk of short- and long-term mortality. The prediction of the progression of AKI to long-term injury has been difficult for renal disease treatment. Radiologists are keen for the early detection of transition from AKI to long-term kidney injury, which would help in the preventive measures. The lack of established methods for early detection of long-term kidney injury underscores the pressing needs of advanced imaging technology that reveals microscopic tissue alterations during the progression of AKI. Fueled by recent advances in data acquisition and post-processing methods of magnetic resonance imaging (MRI), multiparametric MRI is showing great potential as a diagnostic tool for many kidney diseases. Multiparametric MRI studies offer a precious opportunity for real-time noninvasive monitoring of pathological development and progression of AKI to long-term injury. It provides insight into renal vasculature and function (arterial spin labeling, intravoxel incoherent motion), tissue oxygenation (blood oxygen level-dependent), tissue injury and fibrosis (diffusion tensor imaging, diffusion kurtosis imaging, T1 and T2 mapping, quantitative susceptibility mapping). The multiparametric MRI approach is highly promising but the longitudinal investigation on the transition of AKI to irreversible long-term impairment is largely ignored. Further optimization and implementation of renal MR methods in clinical practice will enhance our comprehension of not only AKI but chronic kidney diseases. Novel imaging biomarkers for microscopic renal tissue alterations could be discovered and benefit the preventative interventions. This review explores recent MRI applications on acute and long-term kidney injury while addressing lingering challenges, with emphasis on the potential value of the development of multiparametric MRI for renal imaging on clinical systems. EVIDENCE LEVEL: 1 TECHNICAL EFFICACY: Stage 2.
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Affiliation(s)
- Bin Wang
- Department of Medical Imaging, First Hospital of Shanxi Medical University, Taiyuan, Shanxi, China
- Department of Medical Imaging, Shanxi Medical University, Taiyuan, Shanxi, China
| | - Yongfang Wang
- Department of Medical Imaging, First Hospital of Shanxi Medical University, Taiyuan, Shanxi, China
| | - Jing Wang
- Department of Nuclear Medicine and PET Center, The Second Hospital of Zhejiang University School of Medicine, Hangzhou, China
- Key Laboratory of Medical Molecular Imaging of Zhejiang Province, Hangzhou, China
| | - Chentao Jin
- Department of Nuclear Medicine and PET Center, The Second Hospital of Zhejiang University School of Medicine, Hangzhou, China
- Key Laboratory of Medical Molecular Imaging of Zhejiang Province, Hangzhou, China
| | - Rui Zhou
- Department of Nuclear Medicine and PET Center, The Second Hospital of Zhejiang University School of Medicine, Hangzhou, China
- Key Laboratory of Medical Molecular Imaging of Zhejiang Province, Hangzhou, China
| | - Jinxia Guo
- GE Healthcare, MR Research China, Beijing, China
| | - Hong Zhang
- Department of Nuclear Medicine and PET Center, The Second Hospital of Zhejiang University School of Medicine, Hangzhou, China
- Key Laboratory of Medical Molecular Imaging of Zhejiang Province, Hangzhou, China
- Key Laboratory for Biomedical Engineering of Ministry of Education, Zhejiang University, Hangzhou, China
- College of Biomedical Engineering & Instrument Science, Zhejiang University, Hangzhou, China
| | - Min Wang
- Key Laboratory for Biomedical Engineering of Ministry of Education, Zhejiang University, Hangzhou, China
- College of Biomedical Engineering & Instrument Science, Zhejiang University, Hangzhou, China
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Monoexponential, biexponential, stretched-exponential and kurtosis models of diffusion-weighted imaging in kidney assessment: comparison between patients with primary aldosteronism and healthy controls. ABDOMINAL RADIOLOGY (NEW YORK) 2023; 48:1340-1349. [PMID: 36745206 DOI: 10.1007/s00261-023-03833-0] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/10/2022] [Revised: 01/23/2023] [Accepted: 01/24/2023] [Indexed: 02/07/2023]
Abstract
PURPOSE This study used various diffusion-weighted imaging (DWI) models (including monoexponential, biexponential, stretched-exponential and kurtosis models) in renal magnetic resonance imaging (MRI) to compare whether there were differences in each diffusion parameter between patients with primary aldosteronism (PA) and healthy volunteers. MATERIALS AND METHODS Twenty-two (female:male, 14:8; age, 48 ± 10 years) patients with PA and 22 age- and sex-matched healthy controls (HCs) underwent MRI examinations of the kidneys. The independent-sample t test or the Mann‒Whitney U test was used to detect differences in the diffusion metrics of the kidneys between the two groups. Univariable and multivariable linear regression were applied to analyze the correlations between diffusion parameters and the clinical indicators. RESULTS The mean diffusivity (MD, p < 0.001) and radial diffusivity (Dr, p < 0.001) values in the medulla were lower in the PA group than in the HC group. The medullary fractional anisotropy (FA, p < 0.001) was higher than that of HCs. The FA (p < 0.001) and axial diffusivity (Da, p < 0.001) values in the cortex were lower in the PA group. The cortical α (anomalous exponent term, p = 0.016) was higher in the PA patients than in the HCs. Linear regression analysis showed that log(plasma aldosterone concentration) and the estimated glomerular filtration rate (eGFR) were correlated with medullary FA. CONCLUSION The stretched-exponential model (cortical α) and the kurtosis model (FA, MD and Dr in the medulla and FA and Da in the cortex) showed significant differences between PA patients and healthy volunteers and may have potential for noninvasive renal assessment in PA patients.
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Wang B, Wang Y, Tan Y, Guo J, Chen H, Wu PY, Wang X, Zhang H. Assessment of Fasudil on Contrast-Associated Acute Kidney Injury Using Multiparametric Renal MRI. Front Pharmacol 2022; 13:905547. [PMID: 35784704 PMCID: PMC9242620 DOI: 10.3389/fphar.2022.905547] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/27/2022] [Accepted: 05/31/2022] [Indexed: 11/25/2022] Open
Abstract
Aims: To evaluate the utility of fasudil in a rat model of contrast-associated acute kidney injury (CA-AKI) and explore its underlying mechanism through multiparametric renal magnetic resonance imaging (mpMRI). Methods: Experimental rats (n = 72) were grouped as follows: controls (n = 24), CA-AKI (n = 24), or CA-AKI + Fasudil (n = 24). All animals underwent two mpMRI studies (arterial spin labeling, T1 and T2 mapping) at baseline and post iopromide/fasudil injection (Days 1, 3, 7, and 13 respectively). Relative change in renal blood flow (ΔRBF), T1 (ΔT1) and T2 (ΔT2) values were assessed at specified time points. Serum levels of cystatin C (CysC) and interleukin-1β (IL-1β), and urinary neutrophil gelatinase-associated lipocalin (NGAL) concentrations were tested as laboratory biomarkers, in addition to examining renal histology and expression levels of various proteins (Rho-kinase [ROCK], α-smooth muscle actin [α-SMA]), hypoxia-inducible factor-1α (HIF-1α), and transforming growth factor-β1 (TGF-β1) that regulate renal fibrosis and hypoxia. Results: Compared with the control group, serum levels of CysC and IL-1β, and urinary NGAL concentrations were clearly increased from Day 1 to Day 13 in the CA-AKI group (all p < 0.05). There were significant reductions in ΔT2 values on Days 1 and 3, and ΔT1 reductions were significantly more pronounced at all time points (Days 1–13) in the CA-AKI + Fasudil group (vs. CA-AKI) (all p < 0.05). Fasudil treatment lowered expression levels of ROCK-1, and p-MYPT1/MYPT1 proteins induced by iopromide, decreasing TGF-β1 expression and suppressing both extracellular matrix accumulation and α-SMA expression relative to untreated status (all p < 0.05). Fasudil also enhanced PHD2 transcription and inhibition of HIF-1α expression after CA-AKI. Conclusions: In the context of CA-AKI, fasudil appears to reduce renal hypoxia, fibrosis, and dysfunction by activating (Rho/ROCK) or inhibiting (TGF-β1, HIF-1α) certain signaling pathways and reducing α-SMA expression. Multiparametric MRI may be a viable noninvasive tool for monitoring CA-AKI pathophysiology during fasudil therapy.
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Affiliation(s)
- Bin Wang
- Department of Medical Imaging, First Hospital of Shanxi Medical University, Taiyuan, China
- Department of Medical Imaging, Shanxi Medical University, Taiyuan, China
| | - Yongfang Wang
- Department of Medical Imaging, First Hospital of Shanxi Medical University, Taiyuan, China
| | - Yan Tan
- Department of Medical Imaging, First Hospital of Shanxi Medical University, Taiyuan, China
| | - Jinxia Guo
- GE Healthcare MR Research China, Beijing, China
| | - Haoyuan Chen
- Department of Medical Imaging, Shanxi Medical University, Taiyuan, China
| | - Pu-Yeh Wu
- GE Healthcare MR Research China, Beijing, China
| | - Xiaochun Wang
- Department of Medical Imaging, First Hospital of Shanxi Medical University, Taiyuan, China
- *Correspondence: Xiaochun Wang, ; Hui Zhang,
| | - Hui Zhang
- Department of Medical Imaging, First Hospital of Shanxi Medical University, Taiyuan, China
- *Correspondence: Xiaochun Wang, ; Hui Zhang,
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