Novel image analysis method using ultrasound elastography for noninvasive evaluation of hepatic fibrosis in patients with chronic hepatitis C

Combi-Elasto Evaluation of the Degree of Liver Fibrosis in Children with Cholestatic Liver Disease

Cholestatic liver disease is a common liver disease in infants and young children. Liver fibrosis is a key factor affecting the prognosis, and liver transplantation is the only treatment option for liver cirrhosis. This study aimed to explore the efficacy of Combi-elasto for diagnosing liver fibrosis in children affected by cholestatic liver disease. A total of 64 children with S1-S4-grade liver fibrosis were enrolled. The general data, routine ultrasound, Combi-elasto, aspartate aminotransferase-to-platelet ratio index (APRI) and Fibrosis-4 (FIB-4) score were compared among children with different grades of liver fibrosis, and the efficacy of the above indexes for evaluating the degree of liver fibrosis was reported. There were remarkable differences in liver size, liver echogenicity, Young's modulus (E), fibrosis index (FI), activity index (AI) and FIB-4 score among the groups (all p < 0.05). E and liver echogenicity were the independent impact factors of liver fibrosis. The areas under the curve of E, APRI, FIB-4 score and the combined model (E+ liver echogenicity) in the evaluation of liver fibrosis were 0.84, 0.61, 0.66 and 0.90, respectively. Ultimately, we concluded that CE is an effective method to evaluate liver fibrosis in children with cholestatic liver disease.

Artificial intelligence - based ultrasound elastography for disease evaluation - a narrative review

Ultrasound elastography (USE) provides complementary information of tissue stiffness and elasticity to conventional ultrasound imaging. It is noninvasive and free of radiation, and has become a valuable tool to improve diagnostic performance with conventional ultrasound imaging. However, the diagnostic accuracy will be reduced due to high operator-dependence and intra- and inter-observer variability in visual observations of radiologists. Artificial intelligence (AI) has great potential to perform automatic medical image analysis tasks to provide a more objective, accurate and intelligent diagnosis. More recently, the enhanced diagnostic performance of AI applied to USE have been demonstrated for various disease evaluations. This review provides an overview of the basic concepts of USE and AI techniques for clinical radiologists and then introduces the applications of AI in USE imaging that focus on the following anatomical sites: liver, breast, thyroid and other organs for lesion detection and segmentation, machine learning (ML) - assisted classification and prognosis prediction. In addition, the existing challenges and future trends of AI in USE are also discussed.

In Search of an Imaging Classification of Adenomyosis: A Role for Elastography?

Adenomyosis is a complex and poorly understood gynecological disease. It used to be diagnosed exclusively by histology after hysterectomy; today its diagnosis is carried out increasingly by imaging techniques, including transvaginal ultrasound (TVUS) and magnetic resonance imaging (MRI). However, the lack of a consensus on a classification system hampers relating imaging findings with disease severity or with the histopathological features of the disease, making it difficult to properly inform patients and clinicians regarding prognosis and appropriate management, as well as to compare different studies. Capitalizing on our grasp of key features of lesional natural history, here we propose adding elastographic findings into a new imaging classification of adenomyosis, incorporating affected area, pattern, the stiffest value of adenomyotic lesions as well as the neighboring tissues, and other pathologies. We argue that the tissue stiffness as measured by elastography, which has a wider dynamic detection range, quantitates a fundamental biologic property that directs cell function and fate in tissues, and correlates with the extent of lesional fibrosis, a proxy for lesional "age" known to correlate with vascularity and hormonal receptor activity. With this new addition, we believe that the resulting classification system could better inform patients and clinicians regarding prognosis and the most appropriate treatment modality, thus filling a void.

A Novel Technique for the Evaluation and Interpretation of Elastography in Salivary Gland Involvement in Primary Sjögren Syndrome

Ultrasound (US) of major salivary glands (MSG) evaluates echogenicity, border features and vascularization, with elastography, it can detect tissue elasticity and glandular fibrosis, related to inflammation in Primary Sjögren’s syndrome (pSS). This study aimed to develop a novel technique by pixel analysis for evaluation and interpretation of elastography in MSG in pSS. A cross-sectional and observational multicenter study was conducted. The US of MSG performed in orthogonal planes in grayscale, Doppler, and shear-wave elastography. For elastography images of each gland were analyzed with the open-source program ImageJ to perform a pixel analysis. Statistical analysis was performed with the IBM-SPSS v25 program. Fifty-nine women with a mean age of 57.69 (23–83) years were recruited; pSS mean duration of 87 (5–275) months, and 12 healthy women without sicca symptoms as a control group with a mean age of 50.67 (42–60) years. Intragroup analysis showed p-values >0.05 between sicca symptoms, ocular/dryness tests, biopsy, US, and pixel analysis; correlation between Hocevar and pixel analysis was not found (rho < 0.1, p >0.5). MSG anatomical size was 41.7 ± 28.2 mm vs. 67.6 ± 8.8 mm (p ≤ 0.0001); unstimulated whole saliva flow rate was 0.80 ± 0.80 ml/5 min vs. 1.85 ± 1.27 ml/5 min (p = 0.016). The elastography values (absolute number of pixels) were 572.38 ± 99.21 vs. 539.69 ± 93.12 (p = 0.290). A cut-off point risk for pSS identified with less than 54% of red pixels in the global MSG mass [OR of 3.8 95% CI (1.01–15.00)]. Pixel analysis is a new tool that could lead to a better understanding of the MSG chronic inflammatory process in pSS.

Combinational Elastography

Heart failure (HF) can cause liver congestion and stiffness. Elastography is used to noninvasively measure organ stiffness. Liver fibrosis (LF) is monitored by shear wave and strain elastography. However, shear wave velocity (Vs) on shear wave elastography varies under the influence of fibrosis and congestion, and the LF index by strain elastography reflects only LF progression. Little is known about the usefulness of these methods in HF patients. This prospective study evaluated combined shear wave and strain elastography (i.e., combinational elastography) for assessing liver congestion. A total of 51 patients with HF (33 outpatients and 18 inpatients) and 10 healthy participants were included. Further, the relationships between combinational elastography and clinical characteristics in 51 patients with HF and the effects of medical treatment on these relationships in 18 inpatients with HF were investigated. Vs was significantly higher in the HF group than in the control group (1.68 ± 0.47 versus 1.21 ± 0.16, P = 0.002). The LF index did not significantly differ (1.39 ± 0.40 versus 1.33 ± 0.15, P = 0.680). Vs decreased after treatment (from 2.01 ± 0.61 to 1.62 ± 0.49 m/seconds; P = 0.026), while the LF index did not change (from 1.21 ± 0.29 to 1.26 ± 0.27; P = 0.664). Brain natriuretic peptide level (r = 0.343; P = 0.003) and composite congestion scores (r = 0.455; P < 0.001) were correlated with Vs. Combinational elastography is useful for assessing liver congestion, differentiating between liver congestion and fibrosis, and assessing therapeutic effects in HF patients.

How does the extent of fibrosis in adenomyosis lesions contribute to heavy menstrual bleeding?

Purpose

To investigate how the extent of fibrosis in adenomyosis lesions contributes to heavy menstrual bleeding (HMB).

Methods

We recruited 57 women with histologically confirmed adenomyosis, 29 of whom reported moderate/heavy bleeding (MHB) (menstrual blood loss (MBL) ≥20 but <100 mL) and the remaining 28, excessive MBL (EXB; ≥100 mL). Lesional stiffness was measured by transvaginal elastosonography. Full-thickness uterine tissue columns containing the lesion and its neighboring endometrial-myometrial interface (EMI) and endometrial tissues were evaluated for tissue fibrosis and immunohistochemical analysis of HIF-1α, COX-2, EP2, and EP4.

Results

The lesional stiffness in the EXB group was significantly higher than that of MHB, and consistently, the extent of lesional fibrosis and the extent of tissue fibrosis in both EMI and eutopic endometrium were also significantly higher. In adenomyotic lesions and their neighboring EMI and eutopic endometrial tissues, the immunostaining of HIF-1α, COX-2, EP2, and EP4 was significantly reduced. The extent of fibrosis and the immunostaining levels of HIF-1α, COX-2, EP2, and EP4 were negatively correlated in all tissues.

Conclusions

Lesional fibrosis begets stiffening matrix, propagating fibrosis to neighboring EMI and eutopic endometrium, resulting in reduced PGE2 and HIF-1α signaling, and thus likely reduced hypoxia necessary for endometrial repair, leading to HMB.

Liver fibrosis index as a novel prognostic factor in patients with pulmonary arterial hypertension

Liver dysfunction is an important determinant of the prognosis of left heart failure patients. However, few studies have reported on cardiohepatic interactions in right heart failure patients, a condition that is an important prognostic factor in pulmonary arterial hypertension (PAH). This study aimed to evaluate the existence and extent of hepatic fibrosis and its contribution as a prognostic factor in PAH. This prospective study enrolled 60 consecutive patients with PAH in the International University of Health and Welfare Mita Hospital from June 2016 to December 2017. After the application of the exclusion criteria, 35 patients were assessed for hepatic fibrosis, using real-time tissue elastography, and for clinical deterioration. Sixteen healthy controls were also assessed for comparison. The liver fibrosis index (LFI) was significantly higher in PAH patients than in healthy controls (1.214 ± 0.047 vs. 0.911 ± 0.059, P < 0.001), suggesting that PAH patients exhibited mild liver fibrosis. However, patients with deterioration (vs. no deterioration) had significantly higher LFI values (1.507 ± 0.078 vs. 1.080 ± 0.034, P < 0.001), independent from other established liver function parameters. A receiver operating characteristic curve analysis identified that an LFI ≥ 1.275 indicated a significant probability of clinical deterioration (hazard ratio: 8.4 (95% CI 1.5-45.4, P = 0.012), independent from other known PAH prognostic factors. PAH patients may exhibit subclinical liver fibrosis associated with chronic right heart failure. The LFI can serve as both a non-invasive evaluation of liver fibrosis and a predictive marker for the deterioration of PAH patients.

Real-Time Tissue Elastography to Evaluate Hepatic Hypoxic-Ischemic Injury Caused by Brain Death

ABSTRACT

This study aimed to explore the potential of real-time tissue elastography (RTE) in evaluating hepatic hypoxic-ischemic injury caused by brain death. We performed RTE and biopsy for 50 donated liver. Hematoxylin-eosin staining was used to observe hepatocyte acidophilic change. Liver grafts were divided into 2 groups, one nonacidophilic change (n = 7) and the other with acidophilic change (n = 43). Correlation and difference analysis were performed for hematoxylin-eosin staining results and RTE parameters. The result indicated that 4 of the 11 RTE parameters, namely, the area of low strain within the region of interest (%AREA), contrast (CONT), inverse difference moment (IDM), and correlation (CORR) were related to hepatocytes acidophilic change (r = 0.284, P = 0.046; r = 0.349, P = 0.013; r = -0.444, P = 0.001; r = -0.381, P = 0.00). Whereas %AREA and CONT of the nonacidophilic change group were lower than that of the acidophilic change group (P < 0.05), IDM and CORR in nonacidophilic change group were higher than that of the acidophilic change group (P < 0.05); the remaining parameters were not statistically different between 2 groups (P > 0.05). Analysis of receiver operating characteristic curve indicated that the area under the curve of %AREA, CONT, IDM, and CORR were 0.75, 0.79, 0.81, and 0.77, respectively. Based on this, we concluded that the quantitative analysis parameters of RTE could preliminary assess hepatic hypoxic-ischemic injury caused by brain death.

The association between renal elasticity evaluated by Real-time tissue elastography and renal fibrosis

BACKGROUND

The progression of chronic kidney disease (CKD) depends on the extent of fibrosis in the kidneys; however, a renal biopsy is necessary to evaluate the severity of renal fibrosis. Real-time tissue elastography (RTE), which measures heartbeat-induced tissue displacement, can assess the elasticity of organs. Here, we aimed to investigate the correlation between renal elasticity and the extent of fibrosis in renal biopsy samples.

METHODS

We investigated 29 consecutive patients who underwent a renal biopsy at Ehime University Hospital from February 2018 to August 2019. Renal fibrosis was categorized into three grades, mild (< 25%), moderate (25-50%), and severe (> 50%), based on the total affected area within the biopsy sample. The association between renal elasticity assessed by RTE and the grade of renal fibrosis was evaluated, and a receiver operating characteristic curve was used to distinguish the severity of renal fibrosis.

RESULTS

The mean age and estimated glomerular filtration rate (eGFR) were 58.8 years and 55.2 mL/min/1.73 m², respectively. The median urine protein-to-creatinine ratio was 1.24 g/gCr. The mean renal elasticity of mild, moderate, and severe renal fibrosis was 3.40, 3.98, and 4.77, respectively. Renal elasticity of native kidneys was significantly positively correlated with the grade of renal fibrosis (ρ = 0.529, P = 0.003). At the cutoff point of 3.81, the area under the curve, sensitivity, and specificity were 0.778, 68.4%, and 81.8%, respectively.

CONCLUSION

Real-time tissue elastography is a promising, non-invasive method for assessing renal fibrosis in patients with CKD.

Establishing a novel method for assessing elasticity of internal anal sphincter using ultrasonic real-time tissue elastography

BACKGROUND

Evaluating anorectal function using real-time tissue elastography (RTE) has not been reported. A previous study reported that in the internal anal sphincter (IAS) of surgical specimens of patients with rectal cancer who underwent abdominoperineal resection, there was an increased fibrosis trend in those who underwent pre-operative chemoradiotherapy (CRT) compared with non-CRT. We speculated that CRT might have induced sclerosis of the IAS because of fibrosis. Therefore, we aimed to establish a method of quantitating the degree of IAS hardness using RTE on endoanal ultrasonography.

METHODS

RTE was performed with freehand manual compression under a defined pressure at the middle anal canal. Using the most compressive point in the strain graph, we traced the region of interest in the IAS. The strain histogram showed a frequency distribution of colours according to the degree of strain (numeric scan ranging from 0 to 255; smaller number indicated harder tissue). We defined the mean of the strain histogram as 'elasticity'. Ten patients with locally advanced rectal cancer who underwent pre-operative CRT were prospectively enrolled. We statistically evaluated the correlation between IAS elasticity and maximum resting pressure (MRP) values both at pre- and post-CRT. MRP was examined concurrently with the examination of IAS elasticity.

RESULTS

Representativity of elasticity measurements was demonstrated. It revealed a trend: IAS elasticity had a moderate inverse correlation with MRP (r = 0.41, P = 0.07), regardless of whether measurements were made before or after CRT.

CONCLUSION

We established a completely novel method for the assessment of elasticity of the IAS, using RTE on endoanal ultrasonography.

Normal values of combinational elastography in adult liver: the influence of age

PURPOSE

We aimed to clarify the normal values obtained by simultaneous use of shear wave imaging and strain imaging (combinational elastography) in liver and reveal how aging influences them.

METHODS

In our checkup center, 257 examinees were diagnosed with normal liver based on questionnaires about liver disease and their drinking history, liver function test results, and ultrasound B-mode study findings. We estimated the values of combinational elastography and considered the correlation between the values and age. A multivariate analysis was performed concerning several features and the liver fibrosis (LF) index. We divided examinees into a younger group (< 65 years old) and an older group (≥ 65 years old), and assessed the effect of age on the LF index.

RESULTS

The mean shear wave velocity (Vs) of shear wave measurement (SWM) was 1.10 ± 0.17 m/s (range 0.84-1.93), and the mean LF index of real-time tissue elastography (RTE) was 1.371 ± 0.458 (range 0.258-3.173). There was no significant correlation between Vs and age. However, the LF index increased significantly with age. The multivariate analysis showed that age (P < 0.001) and BMI (P < 0.05) significantly affected the LF index. Indeed, the LF index in the older group was significantly higher than that in the younger group (P < 0.001).

CONCLUSION

In adult liver, the normal Vs of SWM was 1.10 ± 0.17 m/s, and the normal LF index of RTE was 1.371 ± 0.458. The LF index increased significantly with age in contrast to Vs; therefore, the influence of age should be considered when using combinational elastography.

Fast Strain Estimation and Frame Selection in Ultrasound Elastography Using Machine Learning

Ultrasound elastography aims to determine the mechanical properties of the tissue by monitoring tissue deformation due to internal or external forces. Tissue deformations are estimated from ultrasound radio frequency (RF) signals and are often referred to as time delay estimation (TDE). Given two RF frames I₁ and I₂ , we can compute a displacement image, which shows the change in the position of each sample in I₁ to a new position in I₂ . Two important challenges in TDE include high computational complexity and the difficulty in choosing suitable RF frames. Selecting suitable frames is of high importance because many pairs of RF frames either do not have acceptable deformation for extracting informative strain images or are decorrelated and deformation cannot be reliably estimated. Herein, we introduce a method that learns 12 displacement modes in quasi-static elastography by performing principal component analysis (PCA) on displacement fields of a large training database. In the inference stage, we use dynamic programming (DP) to compute an initial displacement estimate of around 1% of the samples and then decompose this sparse displacement into a linear combination of the 12 displacement modes. Our method assumes that the displacement of the whole image could also be described by this linear combination of principal components. We then use the GLobal Ultrasound Elastography (GLUE) method to fine-tune the result yielding the exact displacement image. Our method, which we call PCA-GLUE, is more than 10× faster than DP in calculating the initial displacement map while giving the same result. This is due to converting the problem of estimating millions of variables in DP into a much simpler problem of only 12 unknown weights of the principal components. Our second contribution in this article is determining the suitability of the frame pair I₁ and I₂ for strain estimation, which we achieve by using the weight vector that we calculated for PCA-GLUE as an input to a multilayer perceptron (MLP) classifier. We validate PCA-GLUE using simulation, phantom, and in vivo data. Our classifier takes only 1.5 ms during the testing phase and has an F1-measure of more than 92% when tested on 1430 instances collected from both phantom and in vivo data sets.

Dilatation of lymphatic vessels increases liver stiffness on transient elastography irrespective of fibrosis

AIM

Liver stiffness measured using transient elastography (TE) is affected by tissue viscosity. The role of intrahepatic lymphatic fluid in liver stiffness is unclear. The present study aimed to investigate the effects of lymphatic vessel dilatation on liver stiffness.

METHODS

Patients with chronic liver disease (n = 116) were enrolled from June 2018 to March 2020. All specimens were acquired by laparoscopic liver biopsy. Biopsy samples were stained with D2-40 for lymphatic vessel quantification based on a five-point scale for each specimen. Independent associations of liver stiffness measured by TE, strain elasticity (liver fibrosis index), and controlled attenuation parameter with fibrosis, lymphatic vessels, alanine aminotransferase, bilirubin, and steatosis were evaluated.

RESULTS

Fibrosis, splenic stiffness measurement, and splenic volume were significantly correlated with the area of lymphatic vessels. Fibrosis, lymphatic vessels, and alanine aminotransferase were independent factors significantly associated with liver stiffness measurement (LSM; standardized coefficient [β] = 0.375, P < 0.001; β = 0.342, P < 0.001; and β = 0.359, P < 0.001, respectively). Fibrosis was the only independent factor significantly associated with liver fibrosis index (β = 0.360, P < 0.001), whereas the fat deposit area was the only independent factor significantly associated with controlled attenuation parameter (β = 0.455, P < 0.001). The areas under the receiver operating characteristic curves for diagnosing controlled ascites based on LSM, liver fibrosis index, splenic stiffness measurement, collagen proportionate area, and area of lymphatic vessels were 0.94, 0.66, 0.76, 0.64, and 0.79, respectively.

CONCLUSIONS

Lymphatic vessel dilatation can affect liver stiffness measured using TE. Liver stiffness measurement is a predictive factor for ascites.

Deep learning networks on chronic liver disease assessment with fine-tuning of shear wave elastography image sequences

Chronic liver disease (CLD) is currently one of the major causes of death worldwide. If not treated, it may lead to cirrhosis, hepatic carcinoma and death. Ultrasound (US) shear wave elastography (SWE) is a relatively new, popular, non-invasive technique among radiologists. Although many studies have been published validating the SWE technique either in a clinical setting, or by applying machine learning on SWE elastograms, minimal work has been done on comparing the performance of popular pre-trained deep learning networks on CLD assessment. Currently available literature reports suggest technical advancements on specific deep learning structures, with specific inputs and usually on a limited CLD fibrosis stage class group, with limited comparison on competitive deep learning schemes fed with different input types. The aim of the present study is to compare some popular deep learning pre-trained networks using temporally stable and full elastograms, with or without augmentation as well as propose suitable deep learning schemes for CLD diagnosis and progress assessment. 200 liver biopsy validated patients with CLD, underwent US SWE examination. Four images from the same liver area were saved to extract elastograms and processed to exclude areas that were temporally unstable. Then, full and temporally stable masked elastograms for each patient were separately fed into GoogLeNet, AlexNet, VGG16, ResNet50 and DenseNet201 with and without augmentation. The networks were tested for differentiation of CLD stages in seven classification schemes over 30 repetitions using liver biopsy as the reference. All networks achieved maximum mean accuracies ranging from 87.2%-97.4% and area under the receiver operating characteristic curves (AUCs) ranging from 0.979-0.990 while the radiologists had AUCs ranging from 0.800-0.870. ResNet50 and DenseNet201 had better average performance than the other networks. The use of the temporal stability mask led to improved performance on about 50% of inputs and network combinations while augmentation led to lower performance for all networks. These findings can provide potential networks with higher accuracy and better setting in the CLD diagnosis and progress assessment. A larger data set would help identify the best network and settings for CLD assessment in clinical practice.

Ultrasound-based liver elastography: current results and future perspectives

Chronic liver disease affects 185 million population worldwide. It encompasses a heterogenous disease spectrum, but all can lead to the development of liver fibrosis. The degree of liver fibrosis is not only a prognosticator, but has also been used to guide the treatment strategy and to evaluate treatment response. Traditionally, staging of liver fibrosis is determined on histological analysis using samples obtained from an invasive liver biopsy. Ultrasound-based liver elastography is a non-invasive method of assessing diffuse liver disease in patients with known chronic liver disease. The use of liver elastography has led to a significant reduction in the number of liver biopsies performed to assess the severity of liver fibrosis and a liver biopsy is now reserved for only select sub-groups of patients. The aim of this review article is to discuss the key findings and current evidence for ultrasound-based elastography in diffuse liver disease as well as the technical challenges and to evaluate the potential research direction.

Diagnostic performance of real-time tissue elastography in chronic hepatitis C patients with sustained virological response

BACKGROUND AND AIMS

Real-time tissue elastography is a non-invasive method for measuring liver elasticity. However, there are no reports evaluating the value of real-time tissue elastography for liver fibrosis in hepatitis C virus-infected patients with sustained virological response. The aim of this study is to clarify the diagnostic performance of real-time tissue elastography in patients with sustained virological response.

METHODS

In this prospective study, we enrolled 425 chronic hepatitis C patients who underwent liver biopsy: 118 patients with sustained virological response (45.8% women) and 307 patients with hepatitis C virus (51.1% women). The post-sustained virological response biopsy was performed 5.9 ± 1.8 years after the therapy. Liver fibrosis index measurements as assessed using real-time tissue elastography were performed on the same day of biopsy.

RESULTS

The respective mean liver fibrosis index values for fibrosis stages F0, F1, F2, F3, and F4 were 2.82 ± 0.33, 2.90 ± 0.51, 3.06 ± 0.58, 3.65 ± 0.24, and 3.83 ± 0.65, respectively, in patients with sustained virological response. The diagnostic accuracies expressed as areas under the receiver operating characteristic curves in patients with sustained virological response were 0.776 for the diagnosis of significant fibrosis (≥F2), 0.885 for severe fibrosis (≥F3), and 0.860 for cirrhosis (F4), respectively. The optimum cut-off values liver fibrosis index were 3.14 for ≥F2, 3.24 for ≥F3, and 3.30 for F4 in patients with sustained virological response.

CONCLUSION

Real-time tissue elastography is an acceptable method for predicting the severity of fibrosis in hepatitis C virus patients with sustained virological response.

A New Multimodel Machine Learning Framework to Improve Hepatic Fibrosis Grading Using Ultrasound Elastography Systems from Different Vendors

The purpose of the work described here was to determine if the diagnostic performance of point and 2-D shear wave elastography (pSWE; 2-DSWE) using shear wave velocity (SWV) with a new machine learning (ML) technique applied to systems from different vendors is comparable to that of magnetic resonance elastography (MRE) in distinguishing non-significant (<F2) from significant (≥F2) fibrosis. We included two patient groups with liver disease: (i) 144 patients undergoing pSWE (Siemens) and MRE; and (ii) 60 patients undergoing 2-DSWE (Philips) and MRE. Four ML algorithms using 10 SWV measurements as inputs were trained with MRE. Results were validated using twofold cross-validation. The performance of median SWV in binary grading of fibrosis was moderate for pSWE (area under the curve [AUC]: 0.76) and 2-DSWE (0.84); the ML algorithm support vector machine (SVM) performed particularly well (pSWE: 0.96, 2-DSWE: 0.99). The results suggest that the multivendor ML-based algorithm SVM can binarily grade liver fibrosis using ultrasound elastography with excellent diagnostic performance, comparable to that of MRE.

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).

Strain elastography for noninvasive assessment of liver fibrosis: A prospective study with histological comparison

The aim of this study was to prospectively evaluate the diagnostic performance of strain elastography for the assessment of liver fibrosis in patients with chronic liver disease using Ishak (0-6) histology stage as a reference standard. Ninety-eight consecutive patients with suspected chronic liver disease scheduled for liver biopsy (n = 78) or histologically confirmed cirrhosis (n = 20) were enrolled. Liver fibrosis Index (LF Index) calculated by strain elastography, liver stiffness by transient elastography and serum fibrosis markers (aspartate aminotransferase-to-platelet ratio index and King's Score) were measured. Spearman's correlation coefficient between the LF Index, liver stiffness, serum fibrosis markers and fibrosis stage were calculated and compared using areas under the receiver-operating characteristics (AUROCs) curves. Among 73 patients who underwent strain elastography, there was weak correlation between fibrosis stage and the LF Index (Spearman's: ρ = 0.385 for Ishak score; P = 0.001). Among 52 patients who underwent strain elastography and transient elastography, the AUROC values using LF Index, transient elastography, aspartate aminotransferase-to-platelet ratio index and King's Score for diagnosing significant fibrosis (Ishak score ≥ 3) were 0.79, 0.87, 0.86 and 0.85, respectively (P < 0.0001) and for diagnosing severe fibrosis/cirrhosis (Ishak score ≥ 5) were 0.83, 0.94, 0.92 and 0.92, respectively (P < 0.0001). When comparing the diagnostic performance using LF Index, transient elastography, aspartate aminotransferase-to-platelet ratio index and King's Score, transient elastography shows a significantly higher AUROC value than LF Index in detecting severe fibrosis (P = 0.0149). The diagnostic performance of LF Index calculated by strain elastography was not statistically significantly different to the other noninvasive tests for the assessment of significant liver fibrosis but inferior to transient elastography for the assessment of severe fibrosis/cirrhosis.

Flash Imaging Used in the Post-vascular Phase of Contrast-Enhanced Ultrasonography is Useful for Assessing the Progression in Patients with Hepatitis C Virus-Related Liver Disease

Sonazoid is a commonly used contrast agent for characterizing liver tumors in ultrasonography (US). We performed flash imaging in the post-vascular phase of contrast-enhanced US (CEUS) to investigate associations between collapse of Sonazoid microbubbles (MB) and progression of liver disease. This study enrolled 409 patients (205 men, 204 women) with hepatitis C virus-related liver disease (CLD) between 2007 and 2017 (mean age 60 ± 14 y; range 20-90 y). In the post-vascular phase, 10 min after administering Sonazoid, flash imaging was performed to burst MB in the liver parenchyma; the range of bubble destruction was measured from the surface of the liver. The range of bubble destruction, stage of fibrosis, shear wave velocity (Vs), serologic markers and fibrosis-4 (FIB4) index were analyzed in 259 patients who underwent liver biopsy. Fibrosis stage was F0-1 in 108 patients, F2 in 73, F3 in 38 and F4 in 40. In 150 patients with cirrhosis, diagnosis was made based on imaging findings. The range of bubble destruction was 42.0 ± 10.4 mm in F0-1 patients, 42.9 ± 13.2 mm in F2, 51.5 ± 15.9 mm in F3 and 55.4 ± 17.3 mm in F4 and was significantly increased according to progression of fibrosis staging. The range of bubble destruction was positively correlated with Vs (r = 0.34; p < 0.01), total bilirubin (r = 0.25; p < 0.01) and FIB4 index (r = 0.38; p < 0.01). In contrast, the range of bubble destruction was negatively correlated with serum levels of albumin (r = -0.34; p < 0.01), platelet count (r = -0.35; p < 0.01) and prothrombin time (r = -0.36; p < 0.01). The results indicated that flash imaging in the post-vascular phase of CEUS was a non-invasive assessment and could predict disease progression in patients with CLD.

Could semiquantitative analysis of real-time ultrasound elastography distinguish more liver parenchyma alterations of nonalcoholic fatty liver disease in patients with polycystic ovary syndrome?

OBJECTIVE

Nonalcoholic fatty liver disease is the commonest diffuse liver disease, of which women with polycystic ovary syndrome are at an increased risk. The aim of the present study was to assess the diagnostic value of the semiquantitative strain parameters of real-time ultrasound elastography for nonalcoholic fatty liver disease in patients with polycystic ovary syndrome.

SUBJECTS AND METHODS

Thirty-five polycystic ovary syndrome patients with nonalcoholic fatty liver disease, 70 polycystic ovary syndrome patients without nonalcoholic fatty liver disease, and 70 healthy female controls of reproductive age were included. All participants underwent ultrasonic examination and semiquantitative analysis of real-time ultrasound elastography of the liver.

RESULTS

Main semi quantitative strain parameters, such as average strain value, differed significantly among groups polycystic ovary syndrome with nonalcoholic fatty liver disease, polycystic ovary syndrome without nonalcoholic fatty liver disease, and control (87.02 ± 10.16 vs. 96.31 ± 11.44 vs. 104.49 ± 7.28, p < 0.001). Clinical and laboratory parameters differed significantly between the two subgroups with low or high average strain value. For diagnostic value of average strain value for elevated aminotransferase, the area under the curve was 0.808 (range 0.721-0.895). In multiple linear regression analysis, polycystic ovary syndrome, waist circumference, and metabolic syndrome were stand-alone independent factors associated with average strain value among subjects without nonalcoholic fatty liver disease.

CONCLUSION

Semiquantitative real-time ultrasound elastography analysis could distinguish liver parenchyma alterations in patients with polycystic ovary syndrome more sensitively. The diagnostic value of the proposed method for nonalcoholic fatty liver disease need further research.

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.

Strain Elastography - How To Do It?

Tissue stiffness assessed by palpation for diagnosing pathology has been used for thousands of years. Ultrasound elastography has been developed more recently to display similar information on tissue stiffness as an image. There are two main types of ultrasound elastography, strain and shear wave. Strain elastography is a qualitative technique and provides information on the relative stiffness between one tissue and another. Shear wave elastography is a quantitative method and provides an estimated value of the tissue stiffness that can be expressed in either the shear wave speed through the tissues in meters/second, or converted to the Young's modulus making some assumptions and expressed in kPa. Each technique has its advantages and disadvantages and they are often complimentary to each other in clinical practice. This article reviews the principles, technique, and interpretation of strain elastography in various organs. It describes how to optimize technique, while pitfalls and artifacts are also discussed.

Real-time elastography (RTE): a valuable sonography-based non-invasive method for the assessment of liver fibrosis in chronic hepatitis B

PURPOSE

To investigate the diagnostic usefulness of real-time elastography (RTE) for liver fibrosis in chronic hepatitis B (CHB).

METHODS

89 CHB patients were enrolled in the cross-sectional study. Ultrasound-guided percutaneous liver biopsies, RTE, and blood testing were performed in all patients. Areas under receiver operating characteristic curves (AUROC) were used to examine the diagnostic performance of liver fibrosis index (LFI) for the assessment of liver fibrosis.

RESULTS

LFI differed significantly across histologic fibrosis stages (P < 0.05), except the comparison between S0 and S1 (P = 0.298). There was a strong positive correlation between LFI and histologic liver fibrosis stage (Spearman r = 0.831, P < 0.001). The cutoff LFI value of >2.74 indicated a sensitivity of 0.766 and a specificity of 0.872 for predicting significant liver fibrosis (S ≥ 2), and the cutoff LFI value of >3.61 indicated a sensitivity of 0.833 and a specificity of 0.878 for predicting early liver cirrhosis (S = 4). LFI showed higher AUROC for discriminating significant liver fibrosis (0.873 vs. 0.614) and early liver cirrhosis (0.923 vs. 0.769) than aspartate aminotransferase-to-platelet ratio index (APRI).

CONCLUSIONS

RTE is a valuable sonography-based non-invasive method for assessment of liver fibrosis and has better discrimination power for significant liver fibrosis and early liver cirrhosis than APRI in CHB.

A Machine-Learning Algorithm Toward Color Analysis for Chronic Liver Disease Classification, Employing Ultrasound Shear Wave Elastography

The purpose of the present study was to employ a computer-aided diagnosis system that classifies chronic liver disease (CLD) using ultrasound shear wave elastography (SWE) imaging, with a stiffness value-clustering and machine-learning algorithm. A clinical data set of 126 patients (56 healthy controls, 70 with CLD) was analyzed. First, an RGB-to-stiffness inverse mapping technique was employed. A five-cluster segmentation was then performed associating corresponding different-color regions with certain stiffness value ranges acquired from the SWE manufacturer-provided color bar. Subsequently, 35 features (7 for each cluster), indicative of physical characteristics existing within the SWE image, were extracted. A stepwise regression analysis toward feature reduction was used to derive a reduced feature subset that was fed into the support vector machine classification algorithm to classify CLD from healthy cases. The highest accuracy in classification of healthy to CLD subject discrimination from the support vector machine model was 87.3% with sensitivity and specificity values of 93.5% and 81.2%, respectively. Receiver operating characteristic curve analysis gave an area under the curve value of 0.87 (confidence interval: 0.77-0.92). A machine-learning algorithm that quantifies color information in terms of stiffness values from SWE images and discriminates CLD from healthy cases is introduced. New objective parameters and criteria for CLD diagnosis employing SWE images provided by the present study can be considered an important step toward color-based interpretation, and could assist radiologists' diagnostic performance on a daily basis after being installed in a PC and employed retrospectively, immediately after the examination.

Acoustic Radiation Force Impulse (ARFI) Elastography and Serological Markers in Assessment of Liver Fibrosis and Free Portal Pressure in Patients with Hepatitis B

Background

The aim of this study was to investigate the feasibility of using acoustic radiation force impulse (ARFI) elastography, AST-to-platelet ratio index (APRI), and FIB-4 in assessing liver fibrosis and free portal pressure in patients with hepatitis B.

Material/Methods

We enrolled 126 patients with hepatitis B who underwent liver surgery at the General Surgery Department of the First Affiliated Hospital of Shihezi University Medical School from February 2013 to August 2015. Preoperatively, shear wave velocity (SWV) of the liver was measured with the Siemens S2000 ultrasound system to reflect liver stiffness. Serological markers were collected and fibrosis indices APRI and FIB-4 were calculated. Intraoperatively, liver tissues were harvested and free portal pressure (FPP) was measured. Postoperatively, fibrosis of liver tissues was pathologically staged.

Results

The results of SWV, APRI, FIB-4, and FPP were all correlated with the degree of liver fibrosis (Spearman correlation coefficients: r=0.777, P<0.001; r=0.526, P<0.001; r=0.471, P<0.001; p<0.000; r=0.675, p<0.000). Receiver operating characteristic curve (ROC) analysis showed that the areas under the curve (AUC) of ARFI, APRI, and FIB-4 in diagnosing liver fibrosis were 0.830, 0.768, and 0.717, respectively, for stage F≥1; 0.861, 0.773, and 0.754, respectively, for stage F≥2; 0.941, 0.793, and 0.779, respectively, for stage F≥3; and 0.945, 0.783, and 0.754, respectively, for stage F=4. SWV, APRI, and FIB-4 were all correlated with FPP (Pearson correlation coefficients: 0.387, P<0.001; 0.446, P<0.001; 0.419, P<0.001).

Conclusions

ARFI, APRI, and FIB-4 can assess liver fibrosis in patients with hepatitis B when assessing the portal venous pressure. The difference in diagnostic efficacy between the 3 was not significant.

Machine-learning-based classification of real-time tissue elastography for hepatic fibrosis in patients with chronic hepatitis B

Hepatic fibrosis is a common middle stage of the pathological processes of chronic liver diseases. Clinical intervention during the early stages of hepatic fibrosis can slow the development of liver cirrhosis and reduce the risk of developing liver cancer. Performing a liver biopsy, the gold standard for viral liver disease management, has drawbacks such as invasiveness and a relatively high sampling error rate. Real-time tissue elastography (RTE), one of the most recently developed technologies, might be promising imaging technology because it is both noninvasive and provides accurate assessments of hepatic fibrosis. However, determining the stage of liver fibrosis from RTE images in a clinic is a challenging task. In this study, in contrast to the previous liver fibrosis index (LFI) method, which predicts the stage of diagnosis using RTE images and multiple regression analysis, we employed four classical classifiers (i.e., Support Vector Machine, Naïve Bayes, Random Forest and K-Nearest Neighbor) to build a decision-support system to improve the hepatitis B stage diagnosis performance. Eleven RTE image features were obtained from 513 subjects who underwent liver biopsies in this multicenter collaborative research. The experimental results showed that the adopted classifiers significantly outperformed the LFI method and that the Random Forest(RF) classifier provided the highest average accuracy among the four machine algorithms. This result suggests that sophisticated machine-learning methods can be powerful tools for evaluating the stage of hepatic fibrosis and show promise for clinical applications.

Strain elastography for assessment of liver fibrosis and prognosis in patients with chronic liver diseases

BACKGROUND

Estimation of liver stiffness is essential in the treatment of liver diseases. Various procedures alternative to liver biopsy have been developed, and transient elastography using shear wave is an established method for evaluating liver stiffness and has been shown to be a prognostic indicator. In contrast, strain elastography (SE) has been applied to evaluate liver stiffness, however the significance remains uncertain.

METHODS

We retrospectively analyzed 598 patients who underwent SE to evaluate the ability of estimating liver stiffness and the prognosis. Elasticity index (EI) was evaluated as an indicator of liver stiffness in this study.

RESULTS

EI was increased as histological fibrosis advanced. EI was significantly different between mild fibrosis (F0-2) and advanced fibrosis (F3, 4). In contrast, EI was similar among those with different activity scores. EI showed better diagnostic performance in estimating advanced fibrosis than other serological markers and good reproducibility. Furthermore, EI was shown to be an independent prognostic factor in patients with chronic liver diseases and also with hepatocellular carcinoma (HCC) with advanced stage.

CONCLUSIONS

SE could estimate advanced liver fibrosis without influence of liver inflammation unlike other serological liver fibrosis markers. SE might be a prognostic factor in chronic liver diseases and HCC.

Non-Invasive Identification of Vulnerable Atherosclerotic Plaques Using Texture Analysis in Ultrasound Carotid Elastography: An In Vivo Feasibility Study Validated by Magnetic Resonance Imaging

The aims of this study were to quantify the textural information of strain rate images in ultrasound carotid elastography and evaluate the feasibility of using the textural features in discriminating stable and vulnerable plaques with magnetic resonance imaging as an in vivo reference. Ultrasound radiofrequency data were acquired in 80 carotid plaques from 52 patients, mainly in the longitudinal imaging view, and axial strain rate images were estimated with an ultrasound carotid elastography technique based on an optical flow algorithm. Four textural features of strain rate images-contrast, homogeneity, correlation and angular second moment-were derived based on the gray-level co-occurrence matrix in plaque regions to quantify the deformation distribution pattern. Conventional elastographic indices based on the magnitude of the absolute strain rate, such as the maximum, mean, median, standard deviation and 99th percentile of the axial strain rate, were also obtained for comparison. Composition measurement with magnetic resonance imaging identified 30 plaques as vulnerable and the other 50 as stable. The four textural features, as well as the magnitude of strain rate images, significantly differed between the two groups of plaques. The best performing features for plaque classification were found to be the contrast and 99th percentile of the absolute strain rate, with a comparative area under the receiver operating characteristic curve of 0.81; a slightly higher maximum accuracy of plaque classification can be achieved by the textural feature of contrast (83.8% vs. 81.3%). The results indicate that the use of texture analysis in plaque classification is feasible and that larger local deformations and higher level of complexity in deformation patterns (associated with the elastic or stiffness heterogeneity of plaque tissues) are more likely to occur in vulnerable plaques.

Prospective Risk Analysis of Hepatocellular Carcinoma in Patients with Chronic Hepatitis C by Ultrasound Strain Elastography

OBJECTIVE

We have reported about real-time tissue elastography (RTE), which displays relative strain by measuring the relative distortion of the tissue, and found this information to be useful for diagnosing liver fibrosis. However, its use in predicting hepatocellular carcinoma has not been reported as yet. Here, we investigated RTE to predict liver carcinogenesis in patients with chronic hepatitis C virus (HCV) infection.

METHODS

We enrolled 160 patients with chronic HCV, who were followed up for 39.9 ± 22.9 weeks (median). They underwent RTE and then ultrasounds every 3-6 months.

RESULTS

Respective cumulative liver cancer incidences for years 1, 2, 3, 4, and 5 were, for the entire cohort: 2.0, 5.6, 8.8, 13.1, and 23.9%; for those whose liver fibrosis index (LFI) was ≤2.0: 0.0, 0.0, 0.0, 0.0, and 0.0%; for those whose LFI was 2-2.8: 0.0, 7.4, 7.4, 13.2 and 19.9%; and for those whose LFI was >2.8: 12.9, 12.9, 21.7, 31.4, and 31.4% (p = 0.011; log-rank test).

CONCLUSIONS

Measurements of LFI by strain imaging can effectively predict liver cancer risk in patients with chronic HCV infection.

Comparison of Two-Dimensional Shear Wave Elastography and Real-Time Tissue Elastography for Assessing Liver Fibrosis in Chronic Hepatitis B

BACKGROUND

Noninvasive assessment of liver fibrosis has important clinical significance. Different techniques including two-dimensional shear-wave elastography (2D SWE) and real-time tissue elastography (RTE) are reported to be useful for the noninvasive diagnosis of hepatic fibrosis. All these techniques are affected by many factors. How to choose a reasonable method needs further studies.

PURPOSE

This study was conducted to comparatively assess the diagnostic performance of 2D SWE and RTE in patients with Chronic Hepatitis B (CHB) and influence of inflammation on the stiffness values obtained by both techniques, so as to objectively assess the reasonable choice between these 2 elastography techniques for noninvasive assessment of hepatic fibrosis in clinical practice.

MATERIALS AND METHODS

Four-hundred and thirty-seven patients with CHB meeting the inclusion criteria were enrolled in the study. All patients underwent liver stiffness measurements by using 2D SWE and RTE on the same day. Histologic fibrosis was staged and inflammation activity was graded based on the METAVIR scoring system on liver biopsy specimens.

RESULTS

The liver stiffness values by using 2D SWE and RTE both increased in parallel with the degree of liver fibrosis and the grade of inflammation. However, the diagnostic efficacy of significant fibrosis and cirrhosis using 2D SWE was significantly higher than that of RTE. The 2D SWE measurement values were statistically different in different alanine aminotransferase (ALT) levels and METAVIR activity grades; however, no statistically significant differences were observed by using RTE. The diagnostic efficacy of 2D SWE significantly varied with elevated ALT levels compared with RTE.

CONCLUSION

2D SWE was more accurate than RTE in the assessment of significant fibrosis and cirrhosis in patients with CHB. Compared with RTE, the measurement values and diagnostic performance obtained by 2D SWE were prone to be more easily affected by the inflammation fluctuations.

Development of a model based on biochemical, real‑time tissue elastography and ultrasound data for the staging of liver fibrosis and cirrhosis in patients with chronic hepatitis B

The liver fibrosis index (LFI), based on real‑time tissue elastography (RTE), is a method currently used to assess liver fibrosis. However, this method may not consistently distinguish between the different stages of fibrosis, which limits its accuracy. The aim of the present study was to develop novel models based on biochemical, RTE and ultrasound data for predicting significant liver fibrosis and cirrhosis. A total of 85 consecutive patients with chronic hepatitis B (CHB) were prospectively enrolled and underwent a liver biopsy and RTE. The parameters for predicting significant fibrosis and cirrhosis were determined by conducting multivariate analyses. The splenoportal index (SPI; P=0.002) and LFI (P=0.023) were confirmed as independent predictors of significant fibrosis. Using multivariate analyses for identifying parameters that predict cirrhosis, significant differences in γ‑glutamyl transferase (GGT; P=0.049), SPI (P=0.002) and LFI (P=0.001) were observed. Based on these observations, the novel model LFI‑SPI score (LSPS) was developed to predict the occurrence of significant liver fibrosis, with an area under receiver operating characteristic curves (AUROC) of 0.87. The diagnostic accuracy of the LSPS model was superior to that of the LFI (AUROC=0.76; P=0.0109), aspartate aminotransferase‑to‑platelet ratio index (APRI; AUROC=0.64; P=0.0031), fibrosis‑4 index (FIB‑4; AUROC=0.67; P=0.0044) and FibroScan (AUROC=0.68; P=0.0021) models. In addition, the LFI‑SPI‑GGT score (LSPGS) was developed for the purposes of predicting liver cirrhosis, demonstrating an AUROC value of 0.93. The accuracy of LSPGS was similar to that of FibroScan (AUROC=0.85; P=0.134), but was superior to LFI (AUROC=0.81; P=0.0113), APRI (AUROC=0.67; P<0.0001) and FIB‑4 (AUROC=0.719; P=0.0005). In conclusion, the results of the present study suggest that the use of LSPS and LSPGS may complement current methods of diagnosing significant liver fibrosis and cirrhosis in patients with CHB.

Non-invasive Markers of Liver Fibrosis: Adjuncts or Alternatives to Liver Biopsy?

Liver fibrosis reflects sustained liver injury often from multiple, simultaneous factors. Whilst the presence of mild fibrosis on biopsy can be a reassuring finding, the identification of advanced fibrosis is critical to the management of patients with chronic liver disease. This necessity has lead to a reliance on liver biopsy which itself is an imperfect test and poorly accepted by patients. The development of robust tools to non-invasively assess liver fibrosis has dramatically enhanced clinical decision making in patients with chronic liver disease, allowing a rapid and informed judgment of disease stage and prognosis. Should a liver biopsy be required, the appropriateness is clearer and the diagnostic yield is greater with the use of these adjuncts. While a number of non-invasive liver fibrosis markers are now used in routine practice, a steady stream of innovative approaches exists. With improvement in the reliability, reproducibility and feasibility of these markers, their potential role in disease management is increasing. Moreover, their adoption into clinical trials as outcome measures reflects their validity and dynamic nature. This review will summarize and appraise the current and novel non-invasive markers of liver fibrosis, both blood and imaging based, and look at their prospective application in everyday clinical care.

Primary biliary cirrhosis degree assessment by acoustic radiation force impulse imaging and hepatic fibrosis indicators

AIM: To evaluate the assessment of primary biliary cirrhosis degree by acoustic radiation force impulse imaging (ARFI) and hepatic fibrosis indicators.

METHODS: One hundred and twenty patients who developed liver cirrhosis secondary to primary biliary cirrhosis were selected as the observation group, with the degree of patient liver cirrhosis graded by Child-Pugh (CP) score. Sixty healthy individuals were selected as the control group. The four indicators of hepatic fibrosis were detected in all research objects, including hyaluronic acid (HA), laminin (LN), type III collagen (PC III), and type IV collagen (IV-C). The liver parenchyma hardness value (LS) was then measured by ARFI technique. LS and the four indicators of liver fibrosis (HA, LN, PC III, and IV-C) were observed in different grade CP scores. The diagnostic value of LS and the four indicators of liver fibrosis in determining liver cirrhosis degree with PBC, whether used alone or in combination, were analyzed by receiver operating characteristic (ROC) curve.

RESULTS: LS and the four indicators of liver fibrosis within the three classes (A, B, and C) of CP scores in the observation group were higher than in the control group, with C class > B class > A class; the differences were statistically significant (P < 0.01). Although AUC values of LS within the three classes of CP scores were higher than in the four indicators of liver fibrosis, sensitivity and specificity were unstable. The ROC curves of LS combined with the four indicators of liver fibrosis revealed that: AUC and sensitivity in all indicators combined in the A class of CP score were higher than in LS alone, albeit with slightly decreased specificity; AUC and specificity in all indicators combined in the B class of CP score were higher than in LS alone, with unchanged sensitivity; AUC values (0.967), sensitivity (97.4%), and specificity (90%) of all indicators combined in the C class of CP score were higher than in LS alone (0.936, 92.1%, 83.3%).

CONCLUSION: The diagnostic value of PBC cirrhosis degree in liver cirrhosis degree assessment by ARFI combined with the four indicators of serum liver fibrosis is of satisfactory effectiveness and has important clinical application value.

A new computer aided diagnosis system for evaluation of chronic liver disease with ultrasound shear wave elastography imaging

PURPOSE

Classify chronic liver disease (CLD) from ultrasound shear-wave elastography (SWE) imaging by means of a computer aided diagnosis (CAD) system.

METHODS

The proposed algorithm employs an inverse mapping technique (red-green-blue to stiffness) to quantify 85 SWE images (54 healthy and 31 with CLD). Texture analysis is then applied involving the automatic calculation of 330 first and second order textural features from every transformed stiffness value map to determine functional features that characterize liver elasticity and describe liver condition for all available stages. Consequently, a stepwise regression analysis feature selection procedure is utilized toward a reduced feature subset that is fed into the support vector machines (SVMs) classification algorithm in the design of the CAD system.

RESULTS

With regard to the mapping procedure accuracy, the stiffness map values had an average difference of 0.01 ± 0.001 kPa compared to the quantification results derived from the color-box provided by the built-in software of the ultrasound system. Highest classification accuracy from the SVM model was 87.0% with sensitivity and specificity values of 83.3% and 89.1%, respectively. Receiver operating characteristic curves analysis gave an area under the curve value of 0.85 with [0.77-0.89] confidence interval.

CONCLUSIONS

The proposed CAD system employing color to stiffness mapping and classification algorithms offered superior results, comparing the already published clinical studies. It could prove to be of value to physicians improving the diagnostic accuracy of CLD and can be employed as a second opinion tool for avoiding unnecessary invasive procedures.

Diagnostic Performance of Real-Time Elastography in the Assessment of Advanced Fibrosis in Chronic Hepatitis C

Background and aims

Since liver fibrosis index (LFI) was developed by Fujimoto et al., real-time elastography (RTE) has become a promising non-invasive technique to assess fibrosis in chronic hepatitis C (CHC). The aims of this study were to compare the diagnostic performance of RTE versus laboratory tests to predict advanced fibrosis (METAVIR scoring system: F ≥ 3) in patients with CHC, using liver biopsy (LB) as the reference standard; and to evaluated the impact of patient anthropometric features on RTE histogram acquisition.

Methods

This prospective study included 37 patients with CHC scheduled for LB. Aspartate aminotransferase (AST)/alanine aminotransferase (AST) ratio, AST/platelet ratio index (APRI), and Fibrosis-4 index (FIB-4) were calculated from recent (≤6 months) laboratory data. RTE was performed by two independent operators blind to each other’ findings and to LB results, using Hitachi HI-VISION Avius ultrasound system. According to Hitachi RTE software, liver elasticity was evaluated through the LFI. Percutaneous ultrasound-assisted LB was performed in the same day of RTE. All LB specimens were analyzed by an expert pathologist blind to RTE results. Hepatic fibrosis was staged according to METAVIR scoring system. The diagnostic performance of the LFI, AST/ALT ratio, APRI and FIB-4 for predicting advanced fibrosis was assessed using area under receiver-operating characteristic curve (AUROC), sensitivity, specificity, positive-predictive and negative-predictive (NPV) values.

Results

Thirty-seven LB were performed without complications. The distribution according to METAVIR scoring system was F0–1 in 13 patients (35%), F2 in 13 (35%), F3 in 9 (25%) and F4 in 2 (5%). Thirty-seven RTE procedures were performed. Histogram acquisition was successfully achieved in 32 patients (86%). Abdominal wall thickness ≥23 mm was associated with no histogram acquisition (p = 0.018). Using the optimal cut-off value of 2.38, the AUROC for the LFI was 0.73. The AUROC for the AST/ALT ratio, APRI and FIB-4 were 0.62, 0.79, and 0.82, respectively.

Conclusions

The LFI calculated by RTE showed a very good diagnostic performance to predict advanced fibrosis in CHC, with remarkable sensitivity and NPV (both 100%).

Wisteria floribunda agglutinin positive human Mac-2-binding protein as a predictor of hepatocellular carcinoma development in chronic hepatitis C patients

AIMS

Wisteria floribunda agglutinin (WFA)-positive human Mac-2-binding protein (WFA(+) -M2BP) is a new glycol marker related to liver fibrosis. The aim of the present study was to evaluate WFA(+) -M2BP as a predictor of hepatocellular carcinoma (HCC) development in patients with chronic hepatitis C.

METHODS

This case-control study included 14 patients with chronic hepatitis C who developed HCC and 52controls, matched for age, gender, and fibrosis stage. WFA(+) -M2BP was measured at biopsy and follow-up. Time zero was set at the date of liver biopsy.

RESULTS

WFA(+) -M2BP increased stepwise with progression of liver fibrosis (p < 0.001). Cumulative incidence of HCC development was significantly higher in patients with WFA(+) -M2BP ≥4.2 (p < 0.001) or in those with time-course changes in WFA(+) -M2BP (ΔWFA(+) -M2BP/year) ≥0.3 (p = 0.03). Multivariate analyses demonstrated that WFA(+) -M2BP ≥4.2 [hazard ratio (HR): 4.1, 95% confidence interval (CI): 1.1-15, p = 0.04], ΔWFA(+) -M2BP/year ≥0.3 (HR: 5.5, 95% CI: 1.5-19, p = 0.008), and AFP ≥10 ng/ml (HR: 4.7, 95% CI: 1.1-19, p = 0.03) were independent predictive factors of HCC development. Based on these data, we developed a simple scoring system to predict HCC development using these three factors. Using these scores, patients were classified into four groups; cumulative incidence of HCC development significantly increased with increasing scores (p < 0.001).

CONCLUSIONS

WFA(+) -M2BP measurements and time-course changes in WFA(+) -M2BP can be used to identify patients at high risk of HCC development. Real-time monitoring of WFA(+) -M2BP can be a novel predictor of HCC development.

WFUMB guidelines and recommendations for clinical use of ultrasound elastography: Part 3: liver

The World Federation for Ultrasound in Medicine and Biology (WFUMB) has produced these guidelines for the use of elastography techniques in liver disease. For each available technique, the reproducibility, results, and limitations are analyzed, and recommendations are given. Finally, recommendations based on the international literature and the findings of the WFUMB expert group are established as answers to common questions. The document has a clinical perspective and is aimed at assessing the usefulness of elastography in the management of liver diseases.

Noninvasive evaluation of liver fibrosis using real-time tissue elastography and transient elastography (FibroScan)

OBJECTIVES

The purpose of this study was to assess liver fibrosis with real-time tissue elastography and to compare the results with those of transient elastographic (FibroScan; Echosens, Paris, France) measurements by using liver biopsy as the reference standard.

METHODS

Real-time tissue elastography and percutaneous liver biopsy were performed in 166 patients with chronic hepatitis B (estimation group). The relationship between the parameters obtained via real-time tissue elastography and the hepatic fibrosis stage was evaluated by a stepwise multiple linear regression, and the regression equation was used to calculate the liver fibrosis index. The diagnostic performance of the liver fibrosis index was validated and compared with FibroScan in 121 other patients with chronic hepatitis B (validation group).

RESULTS

The liver fibrosis index was calculated as follows: liver fibrosis index = 0.043 low-strain area ratio + 4.520 skewness + 0.033 mean - 1.002 kurtosis. The liver fibrosis index and liver stiffness measured by FibroScan were both significantly associated with the fibrosis stage in the validation group (r= 0.667 and 0.664, respectively; both P< .001). The areas under the receiver operating characteristic curves for the liver fibrosis index and liver stiffness were 0.880 and 0.909 for predicting substantial fibrosis (scores ≥F2), 0.868 and 0.874 for predicting severe fibrosis (≥F3), and 0.752 and 0.815 for predicting cirrhosis (F4), respectively.

CONCLUSIONS

Real-time tissue elastography is an effective method for assessing liver fibrosis, with diagnostic performance similar to that of transient elastography.

Performance of real-time elastography for the staging of hepatic fibrosis: a meta-analysis

Background

With the rapid development of real-time elastography (RTE), a variety of measuring methods have been developed for the assessment of hepatic fibrosis. We evaluated the overall performance of four methods based on RTE by performing meta-analysis of published literature.

Methods

Online journal databases and a manual search from April 2000 to April 2014 were used. Studies from different databases that meet inclusion criteria were enrolled. The statistical analysis was performed using a random-effects model and fixed-effects model for the overall effectiveness of RTE. The area under the receiver operating characteristic curve (AUROC) was calculated for various means. Fagan plot analysis was used to estimate the clinical utility of RTE, and the heterogeneity of the studies was explored with meta-regression analysis.

Results

Thirteen studies from published articles were enrolled and analyzed. The combined AUROC of the liver fibrosis index (LFI) for the evaluation of significant fibrosis (F≥2), advanced fibrosis (F≥3), and cirrhosis (F = 4) were 0.79, 0.94, and 0.85, respectively. The AUROC of the elasticity index (EI) ranged from 0.75 to 0.92 for F≥2 and 0.66 to 0.85 for F = 4. The overall AUROC of the elastic ratio of the liver for the intrahepatic venous vessels were 0.94, 0.93, and 0.96, respectively. The AUROC of the elastic ratio of the liver for the intercostal muscle in diagnosing advanced fibrosis and cirrhosis were 0.96 and 0.92, respectively. There was significant heterogeneity in the diagnostic odds ratio (DOR) for F≥2 of LFI mainly due to etiology (p<0.01).

Conclusion

The elastic ratio of the liver for the intrahepatic vein has excellent precision in differentiating each stage of hepatic fibrosis and is recommend to be applied to the clinic.

Noninvasive diagnosis of liver fibrosis: utility of data mining of both ultrasound elastography and serological findings to construct a decision tree

OBJECTIVE

Although liver biopsy is the gold standard for viral liver disease management, it is invasive and the sampling error rate is problematic. Real-time tissue elastography (RTE), a recently developed method of ultrasound elastography, can be used to assess liver fibrosis noninvasively but the overlap between fibrosis stages limits its ability to assess liver fibrosis adequately when used alone.

METHODS

A multicenter collaborative study involving 542 patients with chronic viral hepatitis and cirrhosis who were scheduled to undergo liver biopsy compared the image features obtained from RTE image analysis, the liver fibrosis index (LFI), and pathological diagnosis. RTE and a blood test were performed on the same day as the liver biopsy. Data mining was also performed to construct a decision tree, and its diagnostic performance for assessing liver fibrosis was evaluated.

RESULTS

The LFI was higher in patients with chronic hepatitis C (CHC) than in those with chronic hepatitis B (CHB). When a decision tree was constructed by data mining of RTE and serological findings, the diagnostic accuracy was very high for all fibrosis stages, with respective rates at F1, F2, F3, and F4 of 94.4, 54.1, 38.7, and 81.3% for patients with CHC and of 97.1, 50.0, 43.8, and 80.6% for patients with CHB.

CONCLUSIONS

The variation in LFI values between the different etiologies appears to reflect the difference in the development style of liver fibrosis. The decision tree for assessing liver fibrosis constructed by data mining of both RTE and serological findings had a high diagnostic performance in assessing liver fibrosis and shows promising clinical utility.

Accuracy of real-time tissue elastography for the evaluation of hepatic fibrosis in patients with chronic hepatitis B: a prospective multicenter study

BACKGROUND

The prognosis and management of hepatic fibrosis are closely related to the stage of the disease. The limitations of liver biopsy, which is the gold standard for treatment, include its invasiveness and sampling error. Ultrasound elasticity might be the most promising imaging technology for the noninvasive and accurate assessment of hepatic fibrosis. Real-time tissue elastography (RTE) measures the relative stiffness of the tissue in the region of interest caused by the heartbeat. Many studies have verified that RTE is useful for the diagnosis of hepatic fibrosis in patients with chronic hepatitis C (CHC).

PURPOSE

To determine the formula of the liver fibrosis index for chronic hepatitis B (BLFI) and to validate the diagnostic accuracy of the BLFI for hepatic fibrosis compared with the liver fibrosis index (LFI).

MATERIALS AND METHODS

RTE was performed in 747 prospectively enrolled patients with chronic hepatitis B (CHB) or cirrhosis from 8 centers in China; 375 patients were analyzed as the training set, and 372 patients were evaluated as the validation set. The fibrosis stage was diagnosed from pathological specimens obtained by ultrasound-guided liver biopsy. Nine image features were measured from strain images, and the new formula for the BLFI was obtained by combining the nine imaging features of the RTE images using multiple regression analysis of the training set. The BLFI and LFI were compared with the pathological fibrosis stage at diagnosis, and the diagnostic performances of the indexes were compared.

RESULTS

The Spearman correlation coefficient between the BLFI and hepatic fibrosis stages was significantly positive (r = 0.711, p < 0.001), and significant differences were present between all disease stages. The areas under the receiver-operating characteristic (AUROC) curves of the BLFI and LFI for predicting significant fibrosis (S0-S1 vs. S2-S4) were 0.858 and 0.858, respectively. For cirrhosis (S0-S3 vs. S4), the AUROC curves of the BLFI and LFI were 0.868 and 0.862, respectively.

CONCLUSION

The results of this large, multicenter study confirmed that RTE is valuable for the diagnosis of hepatic fibrosis in patients with CHB. However, the diagnostic efficiencies of the new BLFI and the original LFI, which were based on CHC, for the assessment of CHB hepatic fibrosis were similar; thus, the LFI has the potential to be used to directly evaluate the extent of hepatic fibrosis in patients with CHB.

Real-time elastography in the assessment of liver fibrosis: a review of qualitative and semi-quantitative methods for elastogram analysis

Despite its invasiveness, liver biopsy is still considered the gold standard for the assessment of hepatic fibrosis. Non-invasive ultrasound-based techniques are increasingly employed to assess parenchymal stiffness and the progression of chronic diffuse liver diseases. Real-time elastography is a rapidly evolving technique that can reveal the elastic properties of tissues. This review examines qualitative and semi-quantitative methods developed for analysis of real-time liver elastograms, to estimate parenchymal stiffness and, indirectly, the stage of fibrosis. Qualitative analysis is the most immediate approach for elastogram analysis, but this method increases intra- and inter-observer variability, which is seen as a major limitation of real-time elastography. Semi-quantitative methods include analysis of the histogram derived from color-coded maps, as well as calculation of the elastic ratio and fibrosis index.

Diagnostic accuracy of real-time tissue elastography for the staging of liver fibrosis: a meta-analysis

OBJECTIVE

To evaluate the overall accuracy of real-time tissue elastography (RTE) for the staging of liver fibrosis.

METHODS

We systematically reviewed 15 studies (1,626 subjects) in which sensitivity and specificity of RTE for liver fibrosis are available. For each cut-off stage of fibrosis, i.e., F ≥ 1, F ≥ 2, F ≥ 3, and F ≥ 4, summary sensitivity and specificity were estimated using a bivariate random-effects model. Publication bias was assessed using funnel plots and Egger's test.

RESULTS

Summary sensitivity and specificity were 0.79 and 0.76 for F ≥ 2, 0.82 and 0.81 for F ≥ 3, and 0.74 and 0.84 for F ≥ 4, respectively. Meta-regressions revealed scoring methods of RTE and liver diseases in the samples might not influence sensitivity and specificity of RTE. However, the estimated accuracy of RTE might be overestimated due to publication bias (p = 0.004 for F ≥ 2, p < 0.001 for F ≥ 3, and p = 0.002 for F ≥ 4).

CONCLUSIONS

RTE is not highly accurate for any cut-off stage of fibrosis. Compared with findings of meta-analyses on Transient Elastography and Acoustic Radiation Force Impulse imaging, the overall accuracy of RTE seems to be nearly identical for the evaluation of significant liver fibrosis, but less accurate for the evaluation of cirrhosis.

KEY POINTS

• Non-invasive methods for evaluating liver fibrosis are necessary to replace liver biopsy. • ARFI is as accurate as TE for evaluating liver fibrosis. • RTE may be as accurate as TE and ARFI for fibrosis. • RTE may be less accurate than TE and ARFI for cirrhosis. • The estimated accuracy of RTE may be overestimated by publication bias.

JSUM ultrasound elastography practice guidelines: basics and terminology

Ten years have passed since the first commercial equipment for elastography was released; since then clinical utility has been demonstrated. Nowadays, most manufacturers offer an elastography option. The most widely available commercial elastography methods are based on strain imaging, which uses external tissue compression and generates images of the resulting tissue strain. However, imaging methods differ slightly among manufacturers, which results in different image characteristics, for example, spatial and temporal resolution, and different recommended measurement conditions. In addition, many manufacturers have recently provided a shear wave-based method, providing stiffness images based on shear wave propagation speed. Each method of elastography is designed on the basis of assumptions of measurement conditions and tissue properties. Thus, we need to know the basic principles of elastography methods and the physics of tissue elastic properties to enable appropriate use of each piece of equipment and to obtain more precise diagnostic information from elastography. From this perspective, the basic section of this guideline aims to support practice of ultrasound elastography.