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Cao J, Feng H, Li L, Ling W, Wang H. High-frequency ultrasound for assessing the renal characteristics of spontaneous type 2 diabetes mellitus db/db mice. Exp Anim 2025; 74:151-159. [PMID: 39462547 PMCID: PMC12044364 DOI: 10.1538/expanim.24-0114] [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: 09/01/2024] [Accepted: 10/21/2024] [Indexed: 10/29/2024] Open
Abstract
There are few ultrasonographic studies on the spontaneous type 2 diabetes mellitus db/db mouse. Our objective was to dynamically investigate and assess renal morphological and hemodynamic changes in spontaneous T2DM db/db mice through high-frequency ultrasound. Eighteen male db/db mice (the model group) and twelve male db/+ mice (the control group) were included. Body weight and fasting blood glucose were measured at the ages of 8, 16 and 32 weeks. High-frequency ultrasound examinations were conducted at the same ages. Compared with those in the control group, hematoxylin-eosin and Masson staining revealed pathological changes in the renal tissue of the db/db mice at 16 weeks of age, and the lesions were significantly aggravated at 32 weeks of age. The body mass of the mice in the model group increased significantly at 8, 16 and 32 weeks of age, and the kidney volume measured by ultrasound also increased with age. Compared with those of the control group, the blood flow scores determined via power Doppler were significantly different. The peak systolic velocity (PSV), end diastolic velocity (EDV), and resistive index (RI) of the renal artery and the PSV, EDV, and RI of the segmental artery were significantly different at the sixteenth week compared with those that at the eighth week. The results of high-frequency ultrasound revealed that the renal hemodynamics of db/db mice changed at the sixteenth weeks.
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Affiliation(s)
- Jiazhi Cao
- Department of Medical Ultrasound, West China Hospital of Sichuan University, 37 Guoxuexiang, Chengdu 610041, P.R. China
| | - Hao Feng
- West China Clinical Medical College of Sichuan University, 37 Guoxuexiang, Chengdu 610041, P.R. China
| | - Lutong Li
- West China Clinical Medical College of Sichuan University, 37 Guoxuexiang, Chengdu 610041, P.R. China
| | - Wenwu Ling
- Department of Medical Ultrasound, West China Hospital of Sichuan University, 37 Guoxuexiang, Chengdu 610041, P.R. China
| | - Hong Wang
- Department of Medical Ultrasound, West China Hospital of Sichuan University, 37 Guoxuexiang, Chengdu 610041, P.R. China
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Fasoula NA, Xie Y, Katsouli N, Reidl M, Kallmayer MA, Eckstein HH, Ntziachristos V, Hadjileontiadis L, Avgerinos DV, Briasoulis A, Siasos G, Hosseini K, Doulamis I, Kampaktsis PN, Karlas A. Clinical and Translational Imaging and Sensing of Diabetic Microangiopathy: A Narrative Review. J Cardiovasc Dev Dis 2023; 10:383. [PMID: 37754812 PMCID: PMC10531807 DOI: 10.3390/jcdd10090383] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/31/2023] [Revised: 08/21/2023] [Accepted: 08/25/2023] [Indexed: 09/28/2023] Open
Abstract
Microvascular changes in diabetes affect the function of several critical organs, such as the kidneys, heart, brain, eye, and skin, among others. The possibility of detecting such changes early enough in order to take appropriate actions renders the development of appropriate tools and techniques an imperative need. To this end, several sensing and imaging techniques have been developed or employed in the assessment of microangiopathy in patients with diabetes. Herein, we present such techniques; we provide insights into their principles of operation while discussing the characteristics that make them appropriate for such use. Finally, apart from already established techniques, we present novel ones with great translational potential, such as optoacoustic technologies, which are expected to enter clinical practice in the foreseeable future.
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Affiliation(s)
- Nikolina-Alexia Fasoula
- Institute of Biological and Medical Imaging, Helmholtz Zentrum München, 85764 Neuherberg, Germany; (N.-A.F.); (Y.X.); (N.K.); (V.N.)
- Chair of Biological Imaging at the Central Institute for Translational Cancer Research (TranslaTUM), School of Medicine, Technical University of Munich, 81675 Munich, Germany
| | - Yi Xie
- Institute of Biological and Medical Imaging, Helmholtz Zentrum München, 85764 Neuherberg, Germany; (N.-A.F.); (Y.X.); (N.K.); (V.N.)
- Chair of Biological Imaging at the Central Institute for Translational Cancer Research (TranslaTUM), School of Medicine, Technical University of Munich, 81675 Munich, Germany
| | - Nikoletta Katsouli
- Institute of Biological and Medical Imaging, Helmholtz Zentrum München, 85764 Neuherberg, Germany; (N.-A.F.); (Y.X.); (N.K.); (V.N.)
- Chair of Biological Imaging at the Central Institute for Translational Cancer Research (TranslaTUM), School of Medicine, Technical University of Munich, 81675 Munich, Germany
| | - Mario Reidl
- Institute of Biological and Medical Imaging, Helmholtz Zentrum München, 85764 Neuherberg, Germany; (N.-A.F.); (Y.X.); (N.K.); (V.N.)
- Chair of Biological Imaging at the Central Institute for Translational Cancer Research (TranslaTUM), School of Medicine, Technical University of Munich, 81675 Munich, Germany
| | - Michael A. Kallmayer
- Department for Vascular and Endovascular Surgery, Klinikum rechts der Isar, Technical University of Munich (TUM), 81675 Munich, Germany; (M.A.K.); (H.-H.E.)
| | - Hans-Henning Eckstein
- Department for Vascular and Endovascular Surgery, Klinikum rechts der Isar, Technical University of Munich (TUM), 81675 Munich, Germany; (M.A.K.); (H.-H.E.)
| | - Vasilis Ntziachristos
- Institute of Biological and Medical Imaging, Helmholtz Zentrum München, 85764 Neuherberg, Germany; (N.-A.F.); (Y.X.); (N.K.); (V.N.)
- Chair of Biological Imaging at the Central Institute for Translational Cancer Research (TranslaTUM), School of Medicine, Technical University of Munich, 81675 Munich, Germany
- DZHK (German Centre for Cardiovascular Research), Partner Site Munich Heart Alliance, 80336 Munich, Germany
| | - Leontios Hadjileontiadis
- Department of Biomedical Engineering, Healthcare Engineering Innovation Center (HEIC), Khalifa University, Abu Dhabi P.O. Box 127788, United Arab Emirates;
- Department of Electrical and Computer Engineering, Aristotle University of Thessaloniki, 54124 Thessaloniki, Greece
| | | | - Alexandros Briasoulis
- Aleksandra Hospital, National and Kapodistrian University of Athens Medical School, 11527 Athens, Greece;
| | - Gerasimos Siasos
- Sotiria Hospital, National and Kapodistrian University of Athens Medical School, 11527 Athens, Greece;
| | - Kaveh Hosseini
- Cardiac Primary Prevention Research Center, Cardiovascular Disease Research Institute, Tehran University of Medical Sciences, Tehran 1411713138, Iran;
| | - Ilias Doulamis
- Department of Surgery, The Johns Hopkins Hospital, School of Medicine, Baltimore, MD 21287, USA;
| | | | - Angelos Karlas
- Institute of Biological and Medical Imaging, Helmholtz Zentrum München, 85764 Neuherberg, Germany; (N.-A.F.); (Y.X.); (N.K.); (V.N.)
- Chair of Biological Imaging at the Central Institute for Translational Cancer Research (TranslaTUM), School of Medicine, Technical University of Munich, 81675 Munich, Germany
- Department for Vascular and Endovascular Surgery, Klinikum rechts der Isar, Technical University of Munich (TUM), 81675 Munich, Germany; (M.A.K.); (H.-H.E.)
- DZHK (German Centre for Cardiovascular Research), Partner Site Munich Heart Alliance, 80336 Munich, Germany
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Chen J, Jin P, Song Y, Feng L, Lu J, Chen H, Xin L, Qiu F, Cong Z, Shen J, Zhao Y, Xu W, Cai C, Zhou Y, Yang J, Zhang C, Chen Q, Jing X, Huang P. Auto-Segmentation Ultrasound-Based Radiomics Technology to Stratify Patient With Diabetic Kidney Disease: A Multi-Center Retrospective Study. Front Oncol 2022; 12:876967. [PMID: 35860551 PMCID: PMC9290767 DOI: 10.3389/fonc.2022.876967] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/16/2022] [Accepted: 05/31/2022] [Indexed: 12/12/2022] Open
Abstract
Background An increasing proportion of patients with diabetic kidney disease (DKD) has been observed among incident hemodialysis patients in large cities, which is consistent with the continuous growth of diabetes in the past 20 years. Purpose In this multicenter retrospective study, we developed a deep learning (DL)-based automatic segmentation and radiomics technology to stratify patients with DKD and evaluate the possibility of clinical application across centers. Materials and Methods The research participants were enrolled retrospectively and separated into three parts: training, validation, and independent test datasets for further analysis. DeepLabV3+ network, PyRadiomics package, and least absolute shrinkage and selection operator were used for segmentation, extraction of radiomics variables, and regression, respectively. Results A total of 499 patients from three centers were enrolled in this study including 246 patients with type II diabetes mellitus (T2DM) and 253 patients with DKD. The mean intersection-over-union (Miou) and mean pixel accuracy (mPA) of automatic segmentation of the data from the three medical centers were 0.812 ± 0.003, 0.781 ± 0.009, 0.805 ± 0.020 and 0.890 ± 0.004, 0.870 ± 0.002, 0.893 ± 0.007, respectively. The variables from the renal parenchyma and sinus provided different information for the diagnosis and follow-up of DKD. The area under the curve (AUC) of the radiomics model for differentiating between DKD and T2DM patients was 0.674 ± 0.074 and for differentiating between the high and low stages of DKD was 0.803 ± 0.037. Conclusion In this study, we developed a DL-based automatic segmentation, radiomics technology to stratify patients with DKD. The DL technology was proposed to achieve fast and accurate anatomical-level segmentation in the kidney, and an ultrasound-based radiomics model can achieve high diagnostic performance in the diagnosis and follow-up of patients with DKD.
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Affiliation(s)
- Jifan Chen
- Department of Ultrasound in Medicine, The Second Affiliated Hospital of Zhejiang University School of Medicine, Zhejiang University, Hangzhou, China
| | - Peile Jin
- Department of Ultrasound in Medicine, The Second Affiliated Hospital of Zhejiang University School of Medicine, Zhejiang University, Hangzhou, China
- Ultrasound in Medicine and Biomedical Engineering Research Center, The Second Affiliated Hospital of Zhejiang University School of Medicine, Zhejiang University, Hangzhou, China
| | - Yue Song
- Department of Ultrasound in Medicine, The Second Affiliated Hospital of Zhejiang University School of Medicine, Zhejiang University, Hangzhou, China
- Ultrasound in Medicine and Biomedical Engineering Research Center, The Second Affiliated Hospital of Zhejiang University School of Medicine, Zhejiang University, Hangzhou, China
| | - Liting Feng
- Department of Ultrasound, Sichuan Provincial People’s Hospital, University of Electronic Science and Technology of China, Chengdu, China
| | - Jiayue Lu
- Department of Clinical Laboratory, Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Hongjian Chen
- Department of Ultrasound in Medicine, The Second Affiliated Hospital of Zhejiang University School of Medicine, Zhejiang University, Hangzhou, China
- Ultrasound in Medicine and Biomedical Engineering Research Center, The Second Affiliated Hospital of Zhejiang University School of Medicine, Zhejiang University, Hangzhou, China
- Post-Doctoral Research Center, Hangzhou Supor South Ocean Pharmaceutical Co., Ltd, Hangzhou, China
| | - Lei Xin
- Department of Ultrasound in Medicine, The Second Affiliated Hospital of Zhejiang University School of Medicine, Zhejiang University, Hangzhou, China
- Ultrasound in Medicine and Biomedical Engineering Research Center, The Second Affiliated Hospital of Zhejiang University School of Medicine, Zhejiang University, Hangzhou, China
| | - Fuqiang Qiu
- Department of Ultrasound in Medicine, The Second Affiliated Hospital of Zhejiang University School of Medicine, Zhejiang University, Hangzhou, China
- Ultrasound in Medicine and Biomedical Engineering Research Center, The Second Affiliated Hospital of Zhejiang University School of Medicine, Zhejiang University, Hangzhou, China
| | - Zhang Cong
- Department of Ultrasound in Medicine, The Second Affiliated Hospital of Zhejiang University School of Medicine, Zhejiang University, Hangzhou, China
- Ultrasound in Medicine and Biomedical Engineering Research Center, The Second Affiliated Hospital of Zhejiang University School of Medicine, Zhejiang University, Hangzhou, China
| | - Jiaxin Shen
- Department of Ultrasound in Medicine, The Second Affiliated Hospital of Zhejiang University School of Medicine, Zhejiang University, Hangzhou, China
- Ultrasound in Medicine and Biomedical Engineering Research Center, The Second Affiliated Hospital of Zhejiang University School of Medicine, Zhejiang University, Hangzhou, China
| | - Yanan Zhao
- Department of Ultrasound in Medicine, The Second Affiliated Hospital of Zhejiang University School of Medicine, Zhejiang University, Hangzhou, China
- Ultrasound in Medicine and Biomedical Engineering Research Center, The Second Affiliated Hospital of Zhejiang University School of Medicine, Zhejiang University, Hangzhou, China
| | - Wen Xu
- Department of Ultrasound in Medicine, The Second Affiliated Hospital of Zhejiang University School of Medicine, Zhejiang University, Hangzhou, China
- Ultrasound in Medicine and Biomedical Engineering Research Center, The Second Affiliated Hospital of Zhejiang University School of Medicine, Zhejiang University, Hangzhou, China
| | - Chenxi Cai
- Department of Ultrasound, The People’s Hospital of Yinshang, Anhui, China
| | - Yan Zhou
- Department of Ultrasound, Tianjin Third Central Hospital, Tianjin, China
| | - Jinfeng Yang
- Department of Ultrasound, The People’s Hospital of Yinshang, Anhui, China
| | - Chao Zhang
- Department of Ultrasound in Medicine, The Second Affiliated Hospital of Zhejiang University School of Medicine, Zhejiang University, Hangzhou, China
- Ultrasound in Medicine and Biomedical Engineering Research Center, The Second Affiliated Hospital of Zhejiang University School of Medicine, Zhejiang University, Hangzhou, China
| | - Qin Chen
- Department of Ultrasound, Sichuan Provincial People’s Hospital, University of Electronic Science and Technology of China, Chengdu, China
- *Correspondence: Pintong Huang, ; Xiang Jing, ; Qin Chen,
| | - Xiang Jing
- Department of Ultrasound, Tianjin Third Central Hospital, Tianjin, China
- *Correspondence: Pintong Huang, ; Xiang Jing, ; Qin Chen,
| | - Pintong Huang
- Department of Ultrasound in Medicine, The Second Affiliated Hospital of Zhejiang University School of Medicine, Zhejiang University, Hangzhou, China
- Ultrasound in Medicine and Biomedical Engineering Research Center, The Second Affiliated Hospital of Zhejiang University School of Medicine, Zhejiang University, Hangzhou, China
- Research Center for Life Science and Human Health, Binjiang Institute of Zhejiang University, Hangzhou, China
- *Correspondence: Pintong Huang, ; Xiang Jing, ; Qin Chen,
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Zhang Y, Liao H, Shen D, Zhang X, Wang J, Zhang X, Wang X, Li R. Renal Protective Effects of Inonotus obliquus on High-Fat Diet/Streptozotocin-Induced Diabetic Kidney Disease Rats: Biochemical, Color Doppler Ultrasound and Histopathological Evidence. Front Pharmacol 2022; 12:743931. [PMID: 35111043 PMCID: PMC8801815 DOI: 10.3389/fphar.2021.743931] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/19/2021] [Accepted: 12/03/2021] [Indexed: 11/30/2022] Open
Abstract
Diabetic kidney disease (DKD) is the current leading cause of end-stage renal disease. Inonotus obliquus (chaga), a medicinal fungus, has been used in treatment of diabetes. Here, we aim to identify the renal protective effects of chaga extracts on a DKD rat model which was induced by a high-fat diet and streptozotocin injection. During the total 17-weeks experiment, the biological parameters of serum and urine were examined, and the color Doppler ultrasound of renal artery, the periodic acid-Schiff staining, and electron microscopy of kidney tissue were performed. The compositions of chaga extracts were analyzed and the intervention effects of the extracts were also observed. Compared with the normal control group, the biochemical research showed that insulin resistance was developed, blood glucose and total cholesterol were elevated, urinary protein excretion and serum creatinine levels were significantly increased in the DKD model. The ultrasound examinations confirmed the deteriorated blood flow parameters of the left renal interlobar artery in the rat models. Finally, histopathological data supported renal injury on the thickened glomerular basement membrane and fusion of the foot processes. 8 weeks intervention of chaga improved the above changes significantly, and the 100 mg/kg/d chaga group experienced significant effects compared with the 50 mg/kg/d in some parameters. Our findings suggested that Doppler ultrasound examinations guided with biochemical indicators played important roles in evaluating the renal injury as an effective, noninvasive, and repeatable method in rats. Based on biochemical, ultrasound, and histopathological evidence, we confirmed that chaga had pharmacodynamic effects on diabetes-induced kidney injury and the aforementioned effects may be related to delaying the progression of DKD.
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Affiliation(s)
- Yan Zhang
- Department of Nephrology, Fifth Hospital of Shanxi Medical University (Shanxi Provincial People's Hospital), Taiyuan, China
| | - Hui Liao
- Department of Pharmacy, Fifth Hospital of Shanxi Medical University (Shanxi Provincial People's Hospital), Taiyuan, China
| | - Dayue Shen
- School of Pharmacy, Shanxi Medical University, Taiyuan, China
| | - Xilan Zhang
- School of Pharmacy, Shanxi Medical University, Taiyuan, China
| | - Jufang Wang
- Department of Ultrasonic Diagnosis, Fifth Hospital of Shanxi Medical University (Shanxi Provincial People's Hospital), Taiyuan, China
| | - Xiaohong Zhang
- Department of Ultrasonic Diagnosis, Fifth Hospital of Shanxi Medical University (Shanxi Provincial People's Hospital), Taiyuan, China
| | - Xiaocheng Wang
- Department of Statistic and Medical Record, Fifth Hospital of Shanxi Medical University (Shanxi Provincial People's Hospital), Taiyuan, China
| | - Rongshan Li
- Department of Nephrology, Fifth Hospital of Shanxi Medical University (Shanxi Provincial People's Hospital), Taiyuan, China
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