Effect of proteinuria at relapse on shear wave velocity assessed using ultrasound elastography in children with idiopathic nephrotic syndrome

PURPOSE

Shear wave velocity (SWV) is an ultrasound elastography technique that provides much information for kidney disease assessment. However, the factors that alter SWV are not fully understood; it is unclear whether the variation in SWV seen in proteinuria associated with disease progression is due to tissue or proteinuria. This study investigated the effect of proteinuria on SWV.

METHODS

This prospective observational study compared SWV at remission with SWV at relapse in children treated for idiopathic nephrotic syndrome (INS) between April 2020 and December 2023. All relapses without oral steroids during the observation period were measured. SWV at remission was defined as the date closest to relapse during which repeated measurements were taken approximately every 3 months after steroid discontinuation.

RESULTS

Eight patients were treated for INS with a median observation period of 21.9 months (11.8-27.1). Of the 15 relapses, five that met the definition were considered for the study. The median interval between the measurement at relapse and remission was 40 days (11-55). SWV was significantly lower at relapse than remission (2.40 ± 0.20 m/s vs. 2.14 ± 0.15 m/s, P < 0.01).

CONCLUSIONS

SWV decreased in the presence of severe proteinuria at relapse compared to the remission measurements. Although more cases need to be studied, the decrease in SWV may reflect the mechanism by which protein leaks into the urine, not just a direct change caused by the presence of proteinuria.

Explorative study using ultrasound time-harmonic elastography for stiffness-based quantification of skeletal muscle function

Time-harmonic elastography (THE) is an emerging ultrasound imaging technique that allows full-field mapping of the stiffness of deep biological tissues. THE's unique ability to rapidly capture stiffness in multiple tissues has never been applied for imaging skeletal muscle. Therefore, we addressed the lack of data on temporal changes in skeletal muscle stiffness while simultaneously covering stiffness of different muscles. Acquiring repeated THE scans every five seconds we quantified shear-wave speed (SWS) as a marker of stiffness of the long head (LHB) and short head (SHB) of biceps brachii and of the brachialis muscle (B) in ten healthy volunteers. SWS was continuously acquired during a 3-min isometric preloading phase, a 3-min loading phase with different weights (4, 8, and 12 kg), and a 9-min postloading phase. In addition, we analyzed temporal SWS standard deviation (SD) as a marker of muscle contraction regulation. Our results (median [min, max]) showed both SWS at preloading (LHB: 1.04 [0.94, 1.12] m/s, SHB: 0.86 [0.78, 0.94] m/s, B: 0.96 [0.87, 1.09] m/s, p < 0.001) and the increase in SWS with loading weight to be muscle-specific (LHB: 0.010 [0.002, 0.019] m/s/kg, SHB: 0.022 [0.017, 0.042] m/s/kg, B: 0.039 [0.019, 0.062] m/s/kg, p < 0.001). Additionally, SWS during loading increased continuously over time by 0.022 [0.004, 0.051] m/s/min (p < 0.01). Using an exponential decay model, we found an average relaxation time of 27 seconds during postloading. Analogously, SWS SD at preloading was also muscle-specific (LHB: 0.018 [0.011, 0.029] m/s, SHB: 0.021 [0.015, 0.027] m/s, B: 0.024 [0.018, 0.037] m/s, p < 0.05) and increased by 0.005 [0.003, 0.008] m/s/kg (p < 0.01) with loading. SWS SD did not change over loading time and decreased immediately in the postloading phase. Taken together, THE of skeletal muscle is a promising imaging technique for in vivo quantification of stiffness and stiffness changes in multiple muscle groups within seconds. Both the magnitude of stiffness changes and their temporal variation during isometric exercise may reflect the functional status of skeletal muscle and provide additional information to the morphological measures obtained by conventional imaging modalities.

Effects of kidney perfusion on renal stiffness and tissue fluidity measured with tomoelastography in an MRI-compatible ex vivo model

Stiffness plays a vital role in diagnosing renal fibrosis. However, perfusion influences renal stiffness in various chronic kidney diseases. Therefore, we aimed to characterize the effect of tissue perfusion on renal stiffness and tissue fluidity measured by tomoelastography based on multifrequency magnetic resonance elastography in an ex vivo model. Five porcine kidneys were perfused ex vivo in an MRI-compatible normothermic machine perfusion setup with adjusted blood pressure in the 50/10-160/120 mmHg range. Simultaneously, renal cortical and medullary stiffness and fluidity were obtained by tomoelastography. For the cortex, a statistically significant (p < 0.001) strong positive correlation was observed between both perfusion parameters (blood pressure and resulting flow) and stiffness (r = 0.95, 0.91), as well as fluidity (r = 0.96, 0.92). For the medulla, such significant (p < 0.001) correlations were solely observed between the perfusion parameters and stiffness (r = 0.88, 0.71). Our findings demonstrate a strong perfusion dependency of renal stiffness and fluidity in an ex vivo setup. Moreover, changes in perfusion are rapidly followed by changes in renal mechanical properties-highlighting the sensitivity of tomoelastography to fluid pressure and the potential need for correcting mechanics-derived imaging biomarkers when addressing solid structures in renal tissue.

Kidney fibrosis: Emerging diagnostic and therapeutic strategies

An increasing number of patients worldwide suffers from chronic kidney disease (CKD). CKD is accompanied by kidney fibrosis, which affects all compartments of the kidney, i.e., the glomeruli, tubulointerstitium, and vasculature. Fibrosis is the best predictor of progression of kidney diseases. Currently, there is no specific anti-fibrotic therapy for kidney patients and invasive renal biopsy remains the only option for specific detection and quantification of kidney fibrosis. Here we review emerging diagnostic approaches and potential therapeutic options for fibrosis. We discuss how translational research could help to establish fibrosis-specific endpoints for clinical trials, leading to improved patient stratification and potentially companion diagnostics, and facilitating and optimizing development of novel anti-fibrotic therapies for kidney patients.

Are the Currently Available Elastography Methods Useful in the Assessment of Chronic Kidney Disease? A Systematic Review and a Meta-Analysis

Background: We require an quantitative imaging technique for the diagnosis and assessment of chronic kidney disease (CKD). Renal elastography has been widely used in recent years in different studies; however, the results across them are not consistent and, as a result, we conducted a meta-analysis of the published literature on this topic. Methods: The databases of PubMed, Medscape, Medline were searched for all studies published in English from 2010 until November 2021 that evaluated kidney shear wave speed (SWS) by elastography in patients with CKD. Trial design, methodological information, patient characteristics, interventions, results, and outcome data were all collected from each study according to a set protocol. Results: We found 37 publications, yet only 18 studies that utilized point shear wave elastography (Virtual Touch Quantification—VTQ system) were compared because the values achieved using different types of elastography are not evaluable. Finally, 1995 attendees (1241 patients with CKD versus 781 healthy subjects as the control group) were included. When comparing mean values of kidney SWS between studies we found increased heterogeneity Q = 513.133; DF = 10; p < 0001, I2 (inconsistency) = 98.12% (95% CI for I2 97.52–98.57%). With a standardized mean difference of −0.216, patients with CKD have a lower kidney SWS than healthy controls. A positive association between kidney SWS and eGFR was also discovered across the presented studies, with a pooled correlation coefficient of 0.38 (Z = 10.3, p < 0.001), Q = 73.3, DF = 5, p < 000.1, I2 = 93.18% (95% CI for I2 87.86 to 96.18). The pooled area under the ROC curve for kidney SWS to predict chronic kidney disease was 0.831 (95% CI, p < 0.001), Q = 28.32, DF = 6, p = 0.0001, I2 = 78.8% (95% CI for I2 56.37 to 89.72). In the four articles that used the Elast-PQ method, the data presented were insufficient for statistical analysis: area under the curve (AUC) values are used to compare distinct characteristics (differentiating kidney SWS between mildly and moderately impaired kidneys, between non-diabetic/prediabetic/diabetic patients, or kidney SWS between the CKD and control group), therefore not being suitable for further evaluation. Conclusions: The results show that patients with CKD have a lower kidney SWS than healthy controls. However, the number of studies involving renal elastography that have been published is limited and show an increased heterogeneity. Further research is needed to determine which factors actually influence kidney SWS in CKD patients and, as a result, to specify the role and indication of renal elastography in clinical practice.

Noninvasive Detection of Intracranial Hypertension by Novel Ultrasound Time-Harmonic Elastography

OBJECTIVE

A method for measuring intracranial pressure (ICP) noninvasively has long been sought after in neurology and neurosurgery. Treatment failure in individuals presenting with unspecific symptoms such as headache, gait disturbance, or visual impairment occurring in response to increased ICP can lead to irreversible brain injury, progressive disability, and death. Guidelines for diagnostic ICP measurement recommend intracranial placement of pressure tip catheters or lumbar puncture (LP) despite their invasiveness and possible complications. As ICP fluctuations are closely associated with changes in brain stiffness, ultrasound elastography could be a valid method to detect ICP noninvasively and with short examination times.

MATERIALS AND METHODS

In this pilot study, we have investigated the use of time-harmonic shear waves, introduced into the brain by an external shaker, and measured in real-time by transtemporal ultrasound, for deducing a noninvasive imaging marker sensitive to elevated ICP. To this end, we developed cerebral ultrasound time-harmonic elastography for the noninvasive quantification of shear wave speed (SWS) as a surrogate marker of cerebral stiffness in a short examination time of a few minutes.

RESULTS

We found that SWS in patients enrolled for LP with confirmed intracranial hypertension was 1.81 ± 0.10 m/s, distinguishing them from healthy volunteers with excellent diagnostic accuracy (1.55 ± 0.08 m/s; P < 0.001; area under the curve, 0.99). Interestingly, values in symptomatic patients decreased to normal stiffness immediately after LP (1.56 ± 0.06 m/s, P < 0.001). Moreover, invasively measured opening pressure correlated with SWS measured before LP and liquid volume drained through the spinal tap with the SWS difference between the 2 measurements.

CONCLUSIONS

Collectively, our results suggest a tight link between cerebral stiffness and ICP and demonstrate that intracranial hypertension can be detected noninvasively within short examination times, opening avenues for diagnostic applications of cerebral ultrasound time-harmonic elastography in neurology and emergency medicine.

Renal Acoustic Radiation Force Impulse Elastography in Hypertensive Nephroangiosclerosis Patients

Objective: Hypertensive nephroangiosclerosis (HN) represents the second most common cause of chronic kidney disease. Kidney damage secondary to high blood pressure favors the appearance of serum and urinary changes, but also imaging, highlighted by ultrasonography (B-mode, Doppler, Acoustic Radiation Force Impulse Elastography). Acoustic Radiation Force Impulse Elastography (ARFI) represents a new imagistic method which characterizes renal stiffness in the form of shear wave velocity (SWV). Aim: This study aims to investigate renal stiffness in HN patients, and to assess the correlations between it and urinary albumin/creatinine ratio (UACR), estimated glomerular filtration rate (eGFR), and intrarenal resistive index (RRI). Material and Methods: This cross-sectional study was performed on a group of 80 HN patients and 50 healthy, sex and age-matched, as controls. UACR (urinary immunoturbidimetry), eGFR (Jaffe method), RRI, and renal SWV (Siemens Acuson 2000) were determined in all patients and controls. Data were expressed as mean ± standard deviation. Statistical analysis was done by means Pearson’s test and t-Student test, p values of less than 0.05 were considered statistically significant. Results: UACR, eGFR, RRI and SWV showed statistically significant differences between the HN patients and controls (p < 0.0001). In the hypertensive patients group, statistically significant correlations were observed between the SWV and UACR (r = −0.7633, p < 0.00001), eGFR (r = 0.7822, p = 0.00001), and RRI (r = −0.7978, p = 0.00001). Conclusions: Kidney sonoelastography characterizes imagistically the existence of intrarenal lesions associated with essential hypertension, offering a new diagnosis method for these patients.

Elastography ultrasound with machine learning improves the diagnostic performance of traditional ultrasound in predicting kidney fibrosis

BACKGROUND

Noninvasively predicting kidney tubulointerstitial fibrosis is important because it's closely correlated with the development and prognosis of chronic kidney disease (CKD). Most studies of shear wave elastography (SWE) in CKD were limited to non-linear statistical dependencies and didn't fully consider variables' interactions. Therefore, support vector machine (SVM) of machine learning was used to assess the prediction value of SWE and traditional ultrasound techniques in kidney fibrosis.

METHODS

We consecutively recruited 117 CKD patients with kidney biopsy. SWE, B-mode, color Doppler flow imaging ultrasound and hematological exams were performed on the day of kidney biopsy. Kidney tubulointerstitial fibrosis was graded by semi-quantification of Masson staining. The diagnostic performances were accessed by ROC analysis.

RESULTS

Tubulointerstitial fibrosis area was significantly correlated with eGFR among CKD patients (R = 0.450, P < 0.001). AUC of SWE, combined with B-mode and blood flow ultrasound by SVM, was 0.8303 (sensitivity, 77.19%; specificity, 71.67%) for diagnosing tubulointerstitial fibrosis (>10%), higher than either traditional ultrasound, or SWE (AUC, 0.6735 [sensitivity, 67.74%; specificity, 65.45%]; 0.5391 [sensitivity, 55.56%; specificity, 53.33%] respectively. Delong test, p < 0.05); For diagnosing different grades of tubulointerstitial fibrosis, SWE combined with traditional ultrasound by SVM, had AUCs of 0.6429 for mild tubulointerstitial fibrosis (11%-25%), and 0.9431 for moderate to severe tubulointerstitial fibrosis (>50%), higher than other methods (Delong test, p < 0.05).

CONCLUSION

SWE with SVM modeling could improve the diagnostic performance of traditional kidney ultrasound in predicting different kidney tubulointerstitial fibrosis grades among CKD patients.

Three-Dimensional Multi-Frequency Shear Wave Absolute Vibro-Elastography (3D S-WAVE) With a Matrix Array Transducer: Implementation and Preliminary In Vivo Study of the Liver

Magnetic resonance elastography (MRE) is commonly regarded as the imaging-based gold-standard for liver fibrosis staging, comparable to biopsy. While ultrasound-based elastography methods for liver fibrosis staging have been developed, they are confined to a 1D or a 2D region of interest and to a limited depth. 3D Shear Wave Absolute Vibro-Elastography (S-WAVE) is a steady-state, external excitation, volumetric elastography technique that is similar to MRE, but has the additional advantage of multi-frequency excitation. We present a novel ultrasound matrix array implementation of S-WAVE that takes advantage of 3D imaging. We use a matrix array transducer to sample axial multi-frequency steady-state tissue motion over a volume, using a Color Power Angiography sequence. Tissue motion with the frequency components {40,50,60} and {45,55,65} Hz are acquired over a (90° lateral) × (40° elevational) × (16 cm depth) sector with an acquisition time of 12 seconds. We compute the elasticity map in 3D using local spatial frequency estimation. We characterize this new approach in tissue phantoms against measurements obtained with transient elastography and MRE. Six healthy volunteers and eight patients with chronic liver disease were imaged. Their MRE and S-WAVE volumes were aligned using T1 to B-mode registration for direct comparison in common regions of interest. S-WAVE and MRE results are correlated with R² = 0.92, while MRE and TE results are correlated with R² = 0.71. Our findings show that S-WAVE with matrix array has the potential to deliver a similar assessment of liver fibrosis as MRE in a more accessible, inexpensive way, to a broader set of patients.

Recent advances in medical image processing for the evaluation of chronic kidney disease

Assessment of renal function and structure accurately remains essential in the diagnosis and prognosis of Chronic Kidney Disease (CKD). Advanced imaging, including Magnetic Resonance Imaging (MRI), Ultrasound Elastography (UE), Computed Tomography (CT) and scintigraphy (PET, SPECT) offers the opportunity to non-invasively retrieve structural, functional and molecular information that could detect changes in renal tissue properties and functionality. Currently, the ability of artificial intelligence to turn conventional medical imaging into a full-automated diagnostic tool is widely investigated. In addition to the qualitative analysis performed on renal medical imaging, texture analysis was integrated with machine learning techniques as a quantification of renal tissue heterogeneity, providing a promising complementary tool in renal function decline prediction. Interestingly, deep learning holds the ability to be a novel approach of renal function diagnosis. This paper proposes a survey that covers both qualitative and quantitative analysis applied to novel medical imaging techniques to monitor the decline of renal function. First, we summarize the use of different medical imaging modalities to monitor CKD and then, we show the ability of Artificial Intelligence (AI) to guide renal function evaluation from segmentation to disease prediction, discussing how texture analysis and machine learning techniques have emerged in recent clinical researches in order to improve renal dysfunction monitoring and prediction. The paper gives a summary about the role of AI in renal segmentation.