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Selby NM, Francis ST. Assessment of Acute Kidney Injury using MRI. J Magn Reson Imaging 2024. [PMID: 38334370 DOI: 10.1002/jmri.29281] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [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 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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Tao Q, Zhang D, Zhang Q, Liu C, Ye S, Feng Y, Liu R. Mitochondrial targeted ROS Scavenger based on nitroxide for Treatment and MRI imaging of Acute Kidney Injury. Free Radic Res 2022; 56:303-315. [PMID: 35746859 DOI: 10.1080/10715762.2022.2093724] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/04/2022]
Abstract
INTRODUCTION Overproduction of reactive oxygen species (ROS) during oxidative stress is a hallmark of acute kidney injure (AKI), which induced the damage to the renal cells and mitochondrial injury. PURPOSE In this contribution, we prepared mitochondrial targeted nitroxide, which linked 3-carboxy-2,2,5,5-tetramethylpyrrolidine 1-oxyl (carboxy-PROXYL) with (2-aminoethyl)triphenylphosphonium bromide (TPP), named TPP-PROXYL to eliminate the ROS in situ and image the oxidative stress reaction by MRI. METHODS 2,7-Dichlorodihydrofluorescein diacetate (DCFH-DA) staining, mitochondrial membrane potential assay (JC-1) staining and transmission electron microscope (TEM) experiments were processed to verify that TPP-PROXYL could target mitochondria, scavenge the ROS, and prevent damage to mitochondria in live cells. Contrast enhanced MRI also been used to monitor these redox reaction in AKI model. RESULTS TPP-PROXYL demonstrated excellent ROS T1-weighted magnetic resonance imaging (MRI) enhancement in vitro and in vivo, with r1 value about 0.190 mM-1·s-1. In vivo AKI treatment experiments proved that TPP-PROXYL could improve the survival rate of mice and inhibit kidney damage. Moreover, the great ROS scavenging capability and the renal damage reduction during AKI treatment of TPP-PROXYL was verified via MR imaging technology. CONCLUSION Collectively, this research provides TPP-PROXYL would serve as a powerful platform to realize ROS scavenging, treatment and MR imaging of AKI.
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Affiliation(s)
- Quan Tao
- School of Biomedical Engineering, Southern Medical University, Guangzhou, China.,Guangdong Provincial Key Laboratory of Medical Image Processing, Southern Medical University, Guangzhou, China.,Guangdong Province Engineering Laboratory for Medical Imaging and Diagnostic Technology, Southern Medical University, Guangzhou, China.,Key Laboratory of Mental Health of the Ministry of Education & Guangdong-Hong Kong-Macao Greater Bay Area Center for Brain Science and Brain-Inspired Intelligence, Southern Medical University, Guangzhou, China
| | - Di Zhang
- School of Biomedical Engineering, Southern Medical University, Guangzhou, China.,Guangdong Provincial Key Laboratory of Medical Image Processing, Southern Medical University, Guangzhou, China.,Guangdong Province Engineering Laboratory for Medical Imaging and Diagnostic Technology, Southern Medical University, Guangzhou, China.,Key Laboratory of Mental Health of the Ministry of Education & Guangdong-Hong Kong-Macao Greater Bay Area Center for Brain Science and Brain-Inspired Intelligence, Southern Medical University, Guangzhou, China
| | - Qianqian Zhang
- School of Biomedical Engineering, Southern Medical University, Guangzhou, China.,Guangdong Provincial Key Laboratory of Medical Image Processing, Southern Medical University, Guangzhou, China.,Guangdong Province Engineering Laboratory for Medical Imaging and Diagnostic Technology, Southern Medical University, Guangzhou, China.,Key Laboratory of Mental Health of the Ministry of Education & Guangdong-Hong Kong-Macao Greater Bay Area Center for Brain Science and Brain-Inspired Intelligence, Southern Medical University, Guangzhou, China
| | - Chuang Liu
- School of Biomedical Engineering, Southern Medical University, Guangzhou, China.,Guangdong Provincial Key Laboratory of Medical Image Processing, Southern Medical University, Guangzhou, China.,Guangdong Province Engineering Laboratory for Medical Imaging and Diagnostic Technology, Southern Medical University, Guangzhou, China.,Key Laboratory of Mental Health of the Ministry of Education & Guangdong-Hong Kong-Macao Greater Bay Area Center for Brain Science and Brain-Inspired Intelligence, Southern Medical University, Guangzhou, China
| | - Sheng Ye
- School of Biomedical Engineering, Southern Medical University, Guangzhou, China.,Guangdong Provincial Key Laboratory of Medical Image Processing, Southern Medical University, Guangzhou, China.,Guangdong Province Engineering Laboratory for Medical Imaging and Diagnostic Technology, Southern Medical University, Guangzhou, China.,Key Laboratory of Mental Health of the Ministry of Education & Guangdong-Hong Kong-Macao Greater Bay Area Center for Brain Science and Brain-Inspired Intelligence, Southern Medical University, Guangzhou, China
| | - Yanqiu Feng
- School of Biomedical Engineering, Southern Medical University, Guangzhou, China.,Guangdong Provincial Key Laboratory of Medical Image Processing, Southern Medical University, Guangzhou, China.,Guangdong Province Engineering Laboratory for Medical Imaging and Diagnostic Technology, Southern Medical University, Guangzhou, China.,Key Laboratory of Mental Health of the Ministry of Education & Guangdong-Hong Kong-Macao Greater Bay Area Center for Brain Science and Brain-Inspired Intelligence, Southern Medical University, Guangzhou, China
| | - Ruiyuan Liu
- School of Biomedical Engineering, Southern Medical University, Guangzhou, China.,Guangdong Provincial Key Laboratory of Medical Image Processing, Southern Medical University, Guangzhou, China.,Guangdong Province Engineering Laboratory for Medical Imaging and Diagnostic Technology, Southern Medical University, Guangzhou, China.,Key Laboratory of Mental Health of the Ministry of Education & Guangdong-Hong Kong-Macao Greater Bay Area Center for Brain Science and Brain-Inspired Intelligence, Southern Medical University, Guangzhou, China
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Katagiri D, Wang F, Gore JC, Harris RC, Takahashi T. Clinical and experimental approaches for imaging of acute kidney injury. Clin Exp Nephrol 2021; 25:685-699. [PMID: 33835326 PMCID: PMC8154759 DOI: 10.1007/s10157-021-02055-2] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/23/2020] [Accepted: 03/17/2021] [Indexed: 12/23/2022]
Abstract
Complex molecular cell dynamics in acute kidney injury and its heterogeneous etiologies in patient populations in clinical settings have revealed the potential advantages and disadvantages of emerging novel damage biomarkers. Imaging techniques have been developed over the past decade to further our understanding about diseased organs, including the kidneys. Understanding the compositional, structural, and functional changes in damaged kidneys via several imaging modalities would enable a more comprehensive analysis of acute kidney injury, including its risks, diagnosis, and prognosis. This review summarizes recent imaging studies for acute kidney injury and discusses their potential utility in clinical settings.
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Affiliation(s)
- Daisuke Katagiri
- Division of Nephrology and Hypertension, Vanderbilt University Medical Center, S-3223 MCN, Nashville, TN, 37232, USA.
- Department of Nephrology, National Center for Global Health and Medicine, 1-21-1 Toyama, Shinjuku-ku, Tokyo, 162-8655, Japan.
| | - Feng Wang
- Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, TN, USA
- Vanderbilt In Vivo Mouse Kidney Imaging Core, Vanderbilt University Medical Center, Nashville, TN, USA
| | - John C Gore
- Vanderbilt In Vivo Mouse Kidney Imaging Core, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Raymond C Harris
- Division of Nephrology and Hypertension, Vanderbilt University Medical Center, S-3223 MCN, Nashville, TN, 37232, USA
| | - Takamune Takahashi
- Division of Nephrology and Hypertension, Vanderbilt University Medical Center, S-3223 MCN, Nashville, TN, 37232, USA.
- Vanderbilt In Vivo Mouse Kidney Imaging Core, Vanderbilt University Medical Center, Nashville, TN, USA.
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Wang Y, Liu K, Xie X, Song B. Potential role of imaging for assessing acute pancreatitis-induced acute kidney injury. Br J Radiol 2021; 94:20200802. [PMID: 33237803 DOI: 10.1259/bjr.20200802] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/05/2023] Open
Abstract
Acute kidney injury (AKI) is a common complication of acute pancreatitis (AP) that is associated with increased mortality. Conventional assessment of AKI is based on changes in serum creatinine concentration and urinary output. However, these examinations have limited accuracy and sensitivity for the diagnosis of early-stage AKI. This review summarizes current evidence on the use of advanced imaging approaches and artificial intelligence (AI) for the early prediction and diagnosis of AKI in patients with AP. CT scores, CT post-processing technology, Doppler ultrasound, and AI technology provide increasingly valuable information for the diagnosis of AP-induced AKI. Magnetic resonance imaging (MRI) also has potential for the evaluation of AP-induced AKI. For the accurate diagnosis of early-stage AP-induced AKI, more studies are needed that use these new techniques and that use AI in combination with advanced imaging technologies.
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Affiliation(s)
- Yi Wang
- Department of Radiology, West China Hospital, Sichuan University, Chengdu, China
| | - Kaixiang Liu
- Department of Nephrology, Sichuan Academy of Medical Sciences and Sichuan Provincial People' s Hospital, University of Electronic Science and Technology of China, Chengdu, China.,Department of Nephrology, Nanchong Central Hospital, The Second Affiliated Medical College of North Sichuan Medical College, Nanchong, China
| | - Xisheng Xie
- Department of Nephrology, Nanchong Central Hospital, The Second Affiliated Medical College of North Sichuan Medical College, Nanchong, China
| | - Bin Song
- Department of Radiology, West China Hospital, Sichuan University, Chengdu, China
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