Potential value of three-dimensional ultrasonography in diagnosis of diabetic nephropathy in Chinese diabetic population with kidney injury

Clinical and Translational Imaging and Sensing of Diabetic Microangiopathy: A Narrative Review

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.

Auto-Segmentation Ultrasound-Based Radiomics Technology to Stratify Patient With Diabetic Kidney Disease: A Multi-Center Retrospective Study

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.

Renal Protective Effects of Inonotus obliquus on High-Fat Diet/Streptozotocin-Induced Diabetic Kidney Disease Rats: Biochemical, Color Doppler Ultrasound and Histopathological Evidence

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.