Virtual Touch quantification using acoustic radiation force impulse (ARFI) technology for the evaluation of focal solid renal lesions: preliminary findings

Shear wave elastography in the characterization of renal cell carcinoma and angiomyolipoma

BACKGROUND

Detection and characterization of renal lesions are common in daily clinical practice.

PURPOSE

To investigate the effectiveness of shear wave elastography (SWE), a novel radiological examination technique, in the characterization of renal masses.

MATERIAL AND METHODS

The study included a total of 68 patients (33 men, 35 women; mean age = 57.71 ± 12.08 years; age range = 19-83 years) who underwent SWE. SWE measurements were obtained at depths of 2-8 cm from the probe surface in two different positions from an analysis window of approximately 0.5 × 1.0 cm on ultrasound. The cutoff SWE was calculated for the differentiation of renal cell carcinoma (RCC) and angiomyolipoma (AML) by receiver operating characteristic (ROC) analysis. When the result was statistically significant, the sensitivity, specificity, accuracy, and positive and negative predictive values of the test were calculated.

RESULTS

Mass-to-parenchyma SWE ratios of RCCs were significantly higher than those of AMLs (P = 0.003). In ROC curve analysis, the SWE cutoff was 1.215 m/s to differentiate RCCs from AMLs. The area under the ROC curve was calculated as 0.74 (95% CI = 0.610-0.871, sensitivity = 70.7%, specificity = 70.6%, positive predictive value = 87.8%, negative predictive value = 44.4%).

CONCLUSION

The SWE technique is increasingly used and may be useful in distinguishing RCC and AML lesions, and especially clear cell and non-clear cell RCCs.

Can acoustic radiation force impulse imaging (ARFI) accurately diagnose renal masses?: A protocol of systematic review and meta-analysis

BACKGROUND

Renal masses are increasingly being discovered because of the wide accessibility of modern high resolution imaging procedures. Previous clinical studies have reported that acoustic radiation force impulse imaging (ARFI) is used for diagnosis of renal masses. However, no study has investigated this topic systematically. Therefore, this study will evaluate the diagnostic value of ARFI for the diagnosis of renal masses.

METHODS

A systematic search using the databases of Cochrane Library, EMBASE, Pubmed, WANGFANG, and China National Knowledge Infrastructure will be performed to identify studies in which patients with renal masses are assessed by ARFI. Two investigators will independently screen the literature and extract the data. Any discrepancies will be resolved via discussion with the senior author. Study quality will be assessed by the Quality Assessment of Diagnostic Accuracy Studies 2 tool, and pooled sensitivity and specificity of various ARFI findings for the diagnosis of renal masses will be determined. Summary receiver operating characteristic curve will be used to assess the overall performance of ARFI.

RESULTS

This study will evaluate the diagnostic value of ARFI for the diagnosis of renal masses through sensitivity, specificity, positive and negative likelihood ratio, and diagnostic odds ratio.

CONCLUSION

This study will summarize the most recent evidence that focusing on the diagnosis of ARFI for renal masses.

STUDY REGISTRATION

INPLASY202060105.

Differential diagnosis of <3 cm renal tumors by ultrasonography: a rapid, quantitative, elastography self-corrected contrast-enhanced ultrasound imaging mode beyond screening

OBJECTIVES

To assess the combined diagnostic strategy of contrast-enhanced ultrasound (CEUS) and acoustic radiation force impulse (ARFI) in the precise differential diagnosis of clear cell renal cell carcinoma (CCRCC) and urothelium carcinoma of the renal pelvis (UCRP) with other small renal tumors (SRTs) ＜3 cm in size.

METHODS

The elastography self-corrected CEUS (ESC) mode was established to perform the quantitative differential diagnosis of SRTs (<3 cm). The kidney shear wave velocity (SWV) value recorded by ARFI showed substantial variability in patients with CCRCC (high elasticity value) and UCRP (low elasticity value) compared with other renal masses, thus providing critical self-correction information for the ultrasound differential diagnosis of SRTs.

RESULTS

In this work, the ESC observations and the corresponding ESC criteria show a remarkable 94.6% accuracy in reference to the gold standards, thus allowing the quantitative, early triple distinction of CCRCC with UCRP and other SRTs in patients with suspicious SRTs.

CONCLUSIONS

This ARFI self-corrected CEUS diagnostic strategy is far beyond a screening method and may have the potential to identify a window of therapeutic opportunity in which emerging therapies might be applied to patients with CCRCC and UCRP, reducing overtreatment and medical costs.

ADVANCES IN KNOWLEDGE

In our study, a new rapid and non-invasive elastography self-corrected CEUS (ESC) ultrasound imaging mode was developed, which was useful in the triple distinction of CCRCC, UCRP, and other SRTs with 94.6% accuracy. ESC is a promising method in the differential diagnosis of SRTs with accuracy and practicability far beyond a single screening model.

Diagnostic Performance of Ultrasound Shear Wave Elastography in Solid Small (≤4 cm) Renal Parenchymal Masses

The aim of the study was to analyze the diagnostic performance of shear wave elastography (SWE) in differentiating between malignant and benign solid renal parenchymal masses ≤4 cm, compared with conventional ultrasound. A total of 20 healthy volunteers and 117 patients had been included in this study. Conventional ultrasound and SWE were performed in all volunteers and patients. The elasticity of healthy cortex and the elastic parameters of tumors such as mean elasticity (E_mean), minimum elasticity (E_min), maximum elasticity (E_max), standard deviation and elasticity ratio of the lesion to surrounding cortex (E_ratio) were measured on SWE images. Diagnostic performance of SWE was compared with that of conventional ultrasound. The cortical elasticity values of healthy right and left kidneys were 4.7 ± 1.7 and 4.5 ± 1.5 kPa, respectively. Of the 117 renal tumors, 68 were renal cell carcinomas (RCCs) and 49 were benign. E_mean, E_min and E_ratio were significantly lower in RCCs compared with benign lesions: E_mean 7.2 ± 2.5 kPa versus 10.0 ± 2.4 kPa, E_min 2.5 ± 2.4 kPa versus 5.6 ± 2.3 kPa, E_ratio 1.6 ± 0.5 versus 2.2 ± 0.6 (all p values < 0.001). The cutoff values of 9.15 kPa for E_mean, 3.55 kPa for E_min and 1.99 for E_ratio had the highest areas under the receiver operating characteristics curve (0.801 for E_mean, 0.832 for E_min and 0.806 for E_ratio). Combining E_mean, E_min and E_ratio with conventional ultrasound improved the specificity for predicting RCCs to 87.8%, but the sensitivity was not increased.

Point Shear Wave Elastography Using Machine Learning to Differentiate Renal Cell Carcinoma and Angiomyolipoma

The question of whether ultrasound point shear wave elastography can differentiate renal cell carcinoma (RCC) from angiomyolipoma (AML) is controversial. This study prospectively enrolled 51 patients with 52 renal tumors (42 RCCs, 10 AMLs). We obtained 10 measurements of shear wave velocity (SWV) in the renal tumor, cortex and medulla. Median SWV was first used to classify RCC versus AML. Next, the prediction accuracy of 4 machine learning algorithms-logistic regression, naïve Bayes, quadratic discriminant analysis and support vector machines (SVMs)-was evaluated, using statistical inputs from the tumor, cortex and combined statistical inputs from tumor, cortex and medulla. After leave-one-out cross validation, models were evaluated using the area under the receiver operating characteristic (ROC) curve (AUC). Tumor median SWV performed poorly (AUC = 0.62; p = 0.23). Except logistic regression, all machine learning algorithms reached statistical significance using combined statistical inputs (AUC = 0.78-0.98; p < 7.1 × 10-3). SVMs demonstrated 94% accuracy (AUC = 0.98; p = 3.13 × 10-6) and clearly outperformed median SWV in differentiating RCC from AML (p = 2.8 × 10-4).

Intra- and inter-operator reproducibility of US point shear-wave elastography in various organs: evaluation in phantoms and healthy volunteers

PURPOSE

This study was conducted in order to assess the intra- and interoperator reproducibility of shear-wave speed (SWS) measurement on elasticity phantoms and healthy volunteers using ultrasound-based point shear-wave elastography.

MATERIALS AND METHODS

This study was approved by the institutional review board. Two operators measured the SWS of five elasticity phantoms and seven organs (thyroid, lymph node, muscle, spleen, kidney, pancreas, and liver) of 30 healthy volunteers with 1.0-4.5 MHz convex (4C1) and 4.0-9.0 MHz linear (9L4) transducers. The phantom measurements were repeated ten times, while the volunteer measurements were performed five times each. Intra- and interoperator reproducibility was assessed. Interoperator reproducibility was also evaluated with the 95% Bland-Altman limits of agreement (LOA).

RESULTS

In phantoms, all intraclass correlation coefficients (ICCs) were above 0.90 and the 95% LOA between the two operators were less than ± 18%. In volunteers, intraoperator ICCs were > 0.75 for all regions except the pancreas. Interoperator ICC was above 0.75 for the right lobe of the liver (depth 4 cm) and the kidney, but the 95% LOA was less than ± 25% only for the liver.

CONCLUSION

Although excellent in phantoms, interoperator reproducibility was insufficient for all regions in the volunteers other than the right hepatic lobe at a depth of 4 cm. Clinicians should be aware of the 95% LOA when using SWS in patients.

KEY POINTS

• Our phantom study indicated a high reproducibility for shear-wave speed (SWS) measurements with point shear-wave elastography (pSWE). • In volunteers, intraoperator reproducibility was generally high, but the interoperator reproducibility was not high enough except for the right hepatic lobe at 4 cm depth. • To evaluate interoperator reproducibility, the 95% limits of agreement (LOA) between operators should be considered in addition to the intraclass correlation coefficient (ICC).

Characterization of Small Renal Tumors With Magnetic Resonance Elastography: A Feasibility Study

OBJECTIVES

The aim of this study was to explore the feasibility of magnetic resonance elastography (MRE) for characterizing indeterminate small renal tumors (SRTs) as part of a multiparametric magnetic resonance (MR) imaging protocol.

MATERIALS AND METHODS

After institutional review board approval and informed consent were obtained, 21 prospective adults (15 men; median age, 55 years; age range, 25-72 years) with SRT were enrolled. Tumors (2-5 cm Ø) were imaged using 3-directional, gradient echo MRE. Viscoelastic parametric maps (shear wave velocity [c] and attenuation [α]) were analyzed by 2 independent radiologists. Interobserver agreement (Bland-Altman statistics and intraclass correlation coefficients) was assessed. Anatomical T2-weighted, dynamic contrast-enhanced (DCE) and diffusion sequences completed the acquisition protocol. Imaging parameters were compared between groups (Mann-Whitney U test).

RESULTS

Quality of MRE was good in 18 cases (mean nonlinearity <50%), including 1 papillary renal cell carcinoma and 1 metanephric adenoma. A cohort of 5 oncocytomas and 11 clear-cell renal cell carcinomas (ccRCCs) was analyzed for statistical differences. The MRE viscoelastic parameters were the strongest imaging discriminators: oncocytomas displayed significantly lower shear velocity c (median, 0.77 m/s; interquartile range [IQR], 0.76-0.79) (P = 0.007) and higher shear attenuation α (median, 0.087 mm; IQR, 0.082-0.087) (P = 0.008) than ccRCC (medians, 0.92 m/s and 0.066 mm; IQR, 0.84-0.97 and 0.054-0.074, respectively). T2 signal intensity ratio (tumor/renal cortex) was lower in oncocytomas (P = 0.02). The DCE and diffusion MR parameters overlapped substantially (P ≥ 0.1). Oncocytomas displayed a consistent MRE viscoelastic profile, corresponding to data point clustering in a bidimensional scatter plot. Values for MRE intraclass correlation coefficient were 0.982 for c and 0.984 for α, indicating excellent interobserver agreement.

CONCLUSIONS

Magnetic resonance elastography is feasible for SRT characterization; MRE viscoelastic parameters were stronger discriminators between oncocytoma and ccRCC than anatomical, DCE and diffusion MR imaging parameters.

Principles of ultrasound elastography

Tissue stiffness has long been known to be a biomarker of tissue pathology. Ultrasound elastography measures tissue mechanical properties by monitoring the response of tissue to acoustic energy. Different elastographic techniques have been applied to many different tissues and diseases. Depending on the pathology, patient-based factors, and ultrasound operator-based factors, these techniques vary in accuracy and reliability. In this review, we discuss the physical principles of ultrasound elastography, discuss differences between different ultrasound elastographic techniques, and review the advantages and disadvantages of these techniques in clinical practice.

Evaluation of Neonatal Brain Parenchyma Using 2-Dimensional Shear Wave Elastography

OBJECTIVES

The aim of this study was to evaluate the stiffness of the neonatal brain using 2-dimensional shear wave elastography in term and preterm neonates and to investigate possible stiffness differences between groups.

METHODS

A total of 83 neonates, including 44 term and 39 preterm, were included in the study. Shear wave elastographic measurements of the thalamus and occipital periventricular white matter were conducted via the anterior fontanel. The Pearson correlation coefficient was used to determine the association between the birth week and stiffness values of the thalamus and periventricular white matter. A receiver operating characteristic analysis was applied to determine the power of the stiffness of the thalamus and periventricular white matter in predicting a significant preterm classification. P < .05 was considered significant.

RESULTS

The brain parenchymal stiffness values measured from both the thalamus and periventricular white matter were found to be significantly lower in the preterm group compared with the term group. The periventricular white matter stiffness values were found to be lower than thalamus stiffness values in both groups. According to the receiver operating characteristic curve, the optimal cutoff values for determining prematurity were defined to be less than 8.28 kPa for the mean thalamus stiffness and less than 6.59 kPa for the periventricular white matter.

CONCLUSIONS

This study shows that differences between brain stiffness values in preterm and term neonates can be shown by using 2-dimensional shear wave elastography, and the results may be reference points for evaluating neonatal brain stiffness in research on patients with various illnesses.