Transcutaneous vs. intraoperative quantitative ultrasound for staging bovine hepatic steatosis

Pixel-based small-window parametric ultrasound imaging for liver tumor characterization

Purpose

Characterizing liver tumors remains a challenge in clinical practice. Ultrasound parametric imaging based on statistical distribution can enhance image contrast compared with B-mode imaging, requiring scatterers following specific distributions. This study proposes a pixel-based small-window parametric ultrasound imaging method using weighted horizontally normalized Shannon entropy (WhNSE) and fuzzy entropy (FE) to improve detectability liver tumor.

Methods

Pixel-based parametric imaging requires a sliding window to traverse across the B-mode image with the step of one pixel, while calculating the entropy by the pixel values in the window. The entropy is assigned to the center pixel of the sliding window. The entropy image is obtained after getting the entropy values of all pixels. FE and WhNSE are two novel entropies first applied to parametric imaging. The detection abilities of regions of interest (ROI) and the contrast-to-noise ratio (CNR) were evaluated through simulations and clinical explorations.

Results

In simulations, FE imaging showed the highest improvement in detecting hyperechoic ROIs, with a CNR gain up to 457.31% (p < 0.01) in simulations. WhNSE imaging demonstrated the best performance in hyperechoic ROI detection, with a CNR of 1.607 ± 0.816 (p = 0.05), significantly higher than B-mode images.

Conclusions

The proposed pixel-based parametric imaging method based on fuzzy entropy and weighted horizontally normalized Shannon entropy both effectively enhance the contrast and detectability of ultrasound images. The imaging enhancement method of the pixel-based fuzzy entropy imaging with proper parameters got better detection performance, due to the consideration of the relationship of neighboring pixels.

Noninvasive Staging of Hepatic Steatosis Using Calibrated 2D US with Liver Biopsy as the Reference Standard

Background Accumulation of lipid in the liver (ie, hepatic steatosis) is the basis of nonalcoholic fatty liver disease (NAFLD). Asymptomatic steatosis can lead to nonalcoholic steatohepatitis and downstream complications. Purpose To assess the diagnostic performance of calibrated US (CAUS) as a method for detection and staging of hepatic steatosis in comparison with liver biopsy. Materials and Methods Two-dimensional US images in 223 consecutive patients who underwent US-guided liver biopsy from May 2012 to February 2016 were retrospectively analyzed by two observers using CAUS. CAUS semiautomatically estimates echo-level and texture parameters, with particular interest in the residual attenuation coefficient (RAC), which is the remaining steatosis-driven attenuation obtained after correction of the beam profile. Data were correlated with patient characteristics and histologically determined steatosis grades and fibrosis stages. The data were equally divided into training and test sets to independently train and test logistic regression models for detection (>5% fat) and staging (>33% and >66% fat) of hepatic steatosis by using area under the receiver operating characteristic curve (AUC) analysis. Results A total of 195 patients (mean age, 50 years ± 13 [SD]; 110 men) were included and divided into a training set (n = 97 [50%]) and a test set (n = 98 [50%]). The average CAUS interobserver correlation coefficient was 0.95 (R range, 0.87-0.99). The best correlation with steatosis was found for the RAC parameter (R = 0.78, P < .01), while no correlation was found for fibrosis (R = 0.14, P = .054). Steatosis detection using RAC showed an AUC of 0.97 (95% CI: 0.94, 1.00), and the multivariable AUC was found to be 0.97 (95% CI: 0.95, 1.00). The predictive performance for moderate and severe hepatic steatosis using RAC was 0.93 (95% CI: 0.88, 0.98) and 0.93 (95% CI: 0.87, 0.98), respectively. Conclusion The calibrated US parameter residual attenuation coefficient detects and stages steatosis accurately with limited interobserver variability, and performance is not hampered by the presence of fibrosis. © RSNA, 2022 Online supplemental material is available for this article. See also the editorial by Grant in this issue.

Tissue Characterization of Puborectalis Muscle From 3-D Ultrasound

Pelvic floor (PF) muscles have the role of preventing pelvic organ descent. The puborectalis muscle (PRM), which is one of the female PF muscles, can be damaged during child delivery. This damage can potentially cause irreversible muscle trauma and even lead to an avulsion, which is disconnection of the muscle from its insertion point, the pubic bone. Ultrasound imaging allows diagnosis of such trauma based on comparison of geometric features of a damaged muscle with the geometric features of a healthy muscle. Although avulsion, which is considered severe damage, can be diagnosed, microdamage within the muscle itself leading to structural changes cannot be diagnosed by visual inspection through imaging only. Therefore, we developed a quantitative ultrasound tissue characterization method to obtain information on the state of the tissue of the PRM and the presence of microdamage in avulsed PRMs. The muscle was segmented as the region of interest (ROI) and further subdivided into six regions of interest (sub-ROIs). Mean echogenicity, entropy and shape parameter of the statistical distribution of gray values were analyzed on two of these sub-ROIs nearest to the bone. The regions nearest to the bones are also the most likely regions to exhibit damage in case of disconnection or avulsion. This analysis was performed for both the muscle at rest and the muscle in contraction. We found that, for PRMs with unilateral avulsion compared with undamaged PRMs, the mean echogenicity (p = 0.02) and shape parameter (p < 0.01) were higher, whereas the entropy was lower (p < 0.01). This method might be applicable to quantification of PRM damage within the muscle.

Assessment of the frequency dependence of acoustic properties on material, composition, and scatterer size of the medium

PURPOSE

The aim of this study was to elucidate the frequency dependence of the speed of sound (SoS) and attenuation coefficients in phantoms with controlled attenuation properties (scatterer density, scatterer size, absorption control material) and rat livers.

METHODS

The frequency dependence of SoS and attenuation coefficients were evaluated with ultrasound (1-15 MHz) by observing multiple phantoms with different scatterer sizes, densities, and presence or absence of evaporated milk as absorbing media. Normal and fatty model rat livers were examined with the same protocol.

RESULTS

The phantom results revealed that the scatterer density and SoS of the base media were the dominant factors causing the changes in SoS. Frequency dependence was not observed in SoS. Assessment of the attenuation coefficient showed that the frequency dependence was mainly affected by absorption attenuation when the scatterer was as small as a hepatocyte (i.e. ≤ 10 µm). Scattering attenuation was also observed to affect frequency dependence when the scatterer was as large as lipid droplets (i.e. ≤ 40 µm).

CONCLUSION

Assuming a consistent size of the main scatterers in the evaluation medium, the frequency dependence of the SoS and attenuation coefficients may provide insight into the scatterer density and the contribution of absorption and scattering attenuation. Further studies in the higher frequency band (up to about 50 MHz) are expected to advance the clinical application of high-frequency ultrasound.

Associations between ultrasound measurements and hematochemical parameters for the assessment of liver metabolic status in Holstein-Friesian cows

Metabolic disorders, including hepatic lipidosis and ketosis, severely affect animal health status and welfare with a large economic burden in dairy herds. The gold standard for diagnosing hepatic lipidosis is the liver biopsy, which is impractical and invasive for the screening at farm level. Ultrasound (US) imaging is a promising technique for identifying liver dysfunction, but standardized specifications in physiological conditions are needed. Herein, we described the features of four US measurements, namely the liver predicted triacylglycerol (pTAG) content, liver depth (LD), and portal vein area (PVA) and depth (PVD) and we investigated their associations with a set of hematochemical (HC) indicators in 342 clinically healthy Holstein Friesian dairy cows. Liver pTAG content was negatively associated with hematocrit and positively with globulin, whereas PVA was negatively associated with thiol group levels, and LD positively with ceruloplasmin. We found significant interactions between some HC parameters and parity: in particular, creatinine, thiol groups and globulin for PVA, and aspartate aminotransferase, paraoxonase and ceruloplasmin for PVD. This study offers new insights on variations in liver function occurring after calving and pave the way for the potential use of minimally invasive techniques for prompt detection of metabolic disorders in dairy herds.

Quantitative Ultrasound Spectroscopy for Differentiation of Hepatocellular Carcinoma from At-Risk and Normal Liver Parenchyma

PURPOSE

Quantitative ultrasound approaches can capture tissue morphologic properties to augment clinical diagnostics. This study aims to clinically assess whether quantitative ultrasound spectroscopy (QUS) parameters measured in hepatocellular carcinoma (HCC) tissues can be differentiated from those measured in at-risk or healthy liver parenchyma.

EXPERIMENTAL DESIGN

This prospective Health Insurance Portability and Accountability Act (HIPAA)-compliant study was approved by the Institutional Review Board. Fifteen patients with HCC, 15 non-HCC patients with chronic liver disease, and 15 healthy volunteers were included (31.1% women; 68.9% men). Ultrasound radiofrequency data were acquired in each patient in both liver lobes at two focal depths (3/9 cm). Region of interests (ROIs) were drawn on HCC and liver parenchyma. The average normalized power spectrum for each ROI was extracted, and a linear regression was fit within the -6 dB bandwidth, from which the midband fit (MBF), spectral intercept (SI), and spectral slope (SS) were extracted. Differences in QUS parameters between the ROIs were tested by a mixed-effects regression.

RESULTS

There was a significant intraindividual difference in MBF, SS, and SI between HCC and adjacent liver parenchyma (P < 0.001), and a significant interindividual difference between HCC and at-risk and healthy non-HCC parenchyma (P < 0.001). In patients with HCC, cirrhosis (n = 13) did not significantly change any of the three parameters (P > 0.8) in differentiating HCC from non-HCC parenchyma. MBF (P = 0.12), SI (P = 0.33), and SS (P = 0.57) were not significantly different in non-HCC tissue among the groups.

CONCLUSIONS

The QUS parameters are significantly different in HCC versus non-HCC liver parenchyma, independent of underlying cirrhosis. This could be leveraged for improved HCC detection with ultrasound in the future.

Experimental Validation of Longitudinal Speed of Sound Estimates in the Diagnosis of Hepatic Steatosis (Part II)

This study validates a non-invasive, quantitative technique to diagnose steatosis within tissue. The proposed method is based on two fundamental concepts: (i) the speed of sound in a fatty liver is lower than that in a healthy liver and (ii) the quality of an ultrasound image is maximized when the beamformer's speed of sound matches the speed in the medium under examination. The method uses image brightness and sharpness as quantitative image-quality metrics to predict the true sound speed and capture the effects of fat infiltration, while accounting for the transmission through subcutaneous fat. Ex vivo testing on sheep liver, mouse livers and tissue-mimicking phantoms indicated the technique's ability to predict the true speed of sound with errors less than 0.5% and to quantify the inverse correlation between fat content and speed of sound.

A methodological approach for deep learning to distinguish between meningiomas and gliomas on canine MR-images

Background

Distinguishing between meningeal-based and intra-axial lesions by means of magnetic resonance (MR) imaging findings may occasionally be challenging. Meningiomas and gliomas account for most of the total primary brain neoplasms in dogs, and differentiating between these two forms is mandatory in choosing the correct therapy. The aims of the present study are: 1) to determine the accuracy of a deep convolutional neural network (CNN, GoogleNet) in discriminating between meningiomas and gliomas in pre- and post-contrast T1 images and T2 images; 2) to develop an image classifier, based on the combination of CNN and MRI sequence displaying the highest accuracy, to predict whether a lesion is a meningioma or a glioma.

Results

Eighty cases with a final diagnosis of meningioma (n = 56) and glioma (n = 24) from two different institutions were included in the study. A pre-trained CNN was retrained on our data through a process called transfer learning. To evaluate CNN accuracy in the different imaging sequences, the dataset was divided into a training, a validation and a test set. The accuracy of the CNN was calculated on the test set. The combination between post-contrast T1 images and CNN was chosen in developing the image classifier (trCNN). Ten images from challenging cases were excluded from the database in order to test trCNN accuracy; the trCNN was trained on the remainder of the dataset of post-contrast T1 images, and correctly classified all the selected images. To compensate for the imbalance between meningiomas and gliomas in the dataset, the Matthews correlation coefficient (MCC) was also calculated. The trCNN showed an accuracy of 94% (MCC = 0.88) on post-contrast T1 images, 91% (MCC = 0.81) on pre-contrast T1-images and 90% (MCC = 0.8) on T2 images.

Conclusions

The developed trCNN could be a reliable tool in distinguishing between different meningiomas and gliomas from MR images.

Technical note: Evaluation of fine needle aspiration cytology for the diagnosis of fatty liver in dairy cattle

Fatty liver is a common condition affecting dairy cattle during the periparturient period, characterized by a pathological accumulation of triglycerides (TG) in the hepatocytes. The objective of this study was to evaluate the diagnostic potential of fine needle aspiration cytology in fresh liver specimens using liver TG concentrations as a gold standard. Fifty-seven liver samples from Holstein cows were collected during processing at a slaughterhouse. Tissue and fine needle aspirate samples were obtained from the parietal upper portion of the caudate lobe. Two samples of liver tissue were collected with a 16 gauge × 15 cm biopsy needle for histological and TG concentration assessment. A third sample was collected for cytology using an 18 gauge × 5.08 cm needle. The contents of the needle were transferred to a glass slide, spread, and air-dried. Liver samples were assayed by colorimetry/fluorimetry to determine TG concentrations. Concentrations of TG <2% were considered normal. Histological and cytological evaluations were conducted by 2 different pathologists blind to the visual classification. Sensitivity (Se) and specificity (Sp) were calculated. Cytology had a Se and Sp of 73 and 85%, respectively. Histopathology had a Se and Sp of 45.9 and 100%, respectively. The likelihood of having higher scores for histopathology and cytology increased as a function of liver TG content (mg/g).

Diagnostic performance of cytology for assessment of hepatic lipid content in dairy cattle

The objective of our study was to characterize the diagnostic performance of cytology for assessing hepatic lipid content (HLC) in dairy cows by comparing microscopic evaluation of lipid vacuolation in touch imprint slide preparations of liver biopsies with quantitative measurement of triglyceride concentration ([TG]; mg/mg of wet weight) in paired biopsy samples. Our study also sought to compare the diagnostic performance of liver cytology, plasma nonesterified fatty acid concentration ([NEFA]), and plasma β-hydroxybutyrate concentration ([BHB]) derived from a measurement performed on whole blood, for assessing HLC. Chemical extraction of TG from liver tissue remains the gold standard for quantifying HLC, largely because available blood tests, although useful for detecting some types of pathology, such as increased lipid mobilization, ketosis, or hepatocellular injury, are nonspecific as to etiology. Veterinary practitioners can sample bovine liver for cytological evaluation in a fast, minimally invasive, and inexpensive manner. Thus, if highly predictive of HLC, cytology would be a practical diagnostic tool for dairy veterinarians. In our study, liver biopsy samples from Holstein cows (219 samples from 105 cows: 52 from cows 2 to 20 d prepartum, 105 from cows 0 to 10 d in milk, 62 from cows 18 to 25 d in milk) were used to prepare cytology slides and to quantify [TG] using the Folch extraction method followed by the Hantzch condensation reaction and spectrophotometric measurement. An ordinal scale (0-4) based on amount of hepatocellular cytoplasm occupied by discrete clear vacuoles was used by 3 blinded, independent observers to rank HLC in Wright-Giemsa-stained slides. Interobserver agreement in cytology scoring was good. Corresponding plasma [NEFA] and [BHB] measurements were available for 187 and 195 of the 219 samples, respectively. Liver [TG] correlated more strongly with cytology score than with NEFA or BHB, and receiver operating characteristic curve analysis showed that cytology had better diagnostic performance than either NEFA or BHB for correctly categorizing [TG] at thresholds of 5, 10, and 15%. Hepatic lipidosis in high-producing dairy cows is of major clinical and economic importance, and this study demonstrates that cytology is an accurate means of assessing HLC. Additional work is indicated to evaluate the diagnostic utility of liver cytology.

Non-invasive diagnosis of non-alcoholic fatty liver disease (NAFLD) using ultrasound image echogenicity

This paper introduces a non-invasive, quantitative technique to diagnose the progression of non-alcoholic fatty liver disease (NAFLD). The method is predicated on two fundamental principles: 1) the speed of sound in a fatty liver is lower than that in a healthy liver and 2) the quality of an ultrasound image is maximized when the beamformer's speed of sound matches the true speed of sound in the tissue being examined. The proposed method uses the echogenicity of an ultrasound image as a quantitative measure to estimate the true speed of sound within the liver parenchyma and capture its correlation with the underlying fat content. The proposed technique was evaluated in simulations and then tested ex vivo on sheep liver, mice liver (healthy and fatty) and tissue-mimicking phantoms. In the case of the phantom and sheep liver, the method was able to estimate the true speed of sound with errors of less than 0.5%; in the case of the mice livers, the method was able to accurately estimate the speed of sound within the livers (less than 1% error) and capture the correlation between fat content and speed of sound. Thereby, demonstrating the capability of ultrasound technology to non-invasively, quantitatively, and accurately diagnose NAFLD at point of care.

Texture analysis of B-mode ultrasound images to stage hepatic lipidosis in the dairy cow: A methodological study

Hepatic lipidosis is the most diffused hepatic disease in the lactating cow. A new methodology to estimate the degree of fatty infiltration of the liver in lactating cows by means of texture analysis of B-mode ultrasound images is proposed. B-mode ultrasonography of the liver was performed in 48 Holstein Friesian cows using standardized ultrasound parameters. Liver biopsies to determine the triacylglycerol content of the liver (TAGqa) were obtained from each animal. A large number of texture parameters were calculated on the ultrasound images by means of a free software. Based on the TAGqa content of the liver, 29 samples were classified as mild (TAGqa<50mg/g), 6 as moderate (50mg/g<TAGqa>100mg/g) and 13 as severe (TAG>100mg/g) in steatosis. Stepwise linear regression analysis was performed to predict the TAGqa content of the liver (TAGpred) from the texture parameters calculated on the ultrasound images. A five-variable model was used to predict the TAG content from the ultrasound images. The regression model explained 83.4% of the variance. An area under the curve (AUC) of 0.949 was calculated for <50mg/g vs >50mg/g of TAGqa; using an optimal cut-off value of 72mg/g TAGpred had a sensitivity of 86.2% and a specificity of 84.2%. An AUC of 0.978 for <100mg/g vs >100mg/g of TAGqa was calculated; using an optimal cut-off value of 89mg/g, TAGpred sensitivity was 92.3% and specificity was 88.6%. Texture analysis of B-mode ultrasound images may therefore be used to accurately predict the TAG content of the liver in lactating cows.

Quantitative Ultrasound for Staging of Hepatic Steatosis in Patients on Home Parenteral Nutrition Validated with Magnetic Resonance Spectroscopy: A Feasibility Study

Patients on home parenteral nutrition are at risk for developing liver dysfunction, which is due partly to the accumulation of lipids in the liver (steatosis) and may progress to end-stage liver disease with overt liver failure. Therefore, a timely diagnosis with easy access to repeated assessment of the degree of liver steatosis is of great importance. A pilot study was performed in 14 patients on long-term home parenteral nutrition using the computer-aided ultrasound method. Ultrasound radio frequency data were acquired using a phased array transducer and were converted into conventional B-mode images. All patients were subjected to proton magnetic resonance spectroscopy measurement of liver fat content for reference. Computer-aided ultrasound parameters similar to those in a previous validation study in cows revealed significant correlations with fat content measured by magnetic resonance spectroscopy. The most significant parameters were the residual attenuation coefficient (R = 0.95, p < 0.001) and the lateral speckle size (R = 0.77, p = 0.021). These findings indicate the potential usefulness of computer-aided ultrasound for staging of hepatic steatosis.

Review of Quantitative Ultrasound: Envelope Statistics and Backscatter Coefficient Imaging and Contributions to Diagnostic Ultrasound

Conventional medical imaging technologies, including ultrasound, have continued to improve over the years. For example, in oncology, medical imaging is characterized by high sensitivity, i.e., the ability to detect anomalous tissue features, but the ability to classify these tissue features from images often lacks specificity. As a result, a large number of biopsies of tissues with suspicious image findings are performed each year with a vast majority of these biopsies resulting in a negative finding. To improve specificity of cancer imaging, quantitative imaging techniques can play an important role. Conventional ultrasound B-mode imaging is mainly qualitative in nature. However, quantitative ultrasound (QUS) imaging can provide specific numbers related to tissue features that can increase the specificity of image findings leading to improvements in diagnostic ultrasound. QUS imaging can encompass a wide variety of techniques including spectral-based parameterization, elastography, shear wave imaging, flow estimation, and envelope statistics. Currently, spectral-based parameterization and envelope statistics are not available on most conventional clinical ultrasound machines. However, in recent years, QUS techniques involving spectral-based parameterization and envelope statistics have demonstrated success in many applications, providing additional diagnostic capabilities. Spectral-based techniques include the estimation of the backscatter coefficient (BSC), estimation of attenuation, and estimation of scatterer properties such as the correlation length associated with an effective scatterer diameter (ESD) and the effective acoustic concentration (EAC) of scatterers. Envelope statistics include the estimation of the number density of scatterers and quantification of coherent to incoherent signals produced from the tissue. Challenges for clinical application include correctly accounting for attenuation effects and transmission losses and implementation of QUS on clinical devices. Successful clinical and preclinical applications demonstrating the ability of QUS to improve medical diagnostics include characterization of the myocardium during the cardiac cycle, cancer detection, classification of solid tumors and lymph nodes, detection and quantification of fatty liver disease, and monitoring and assessment of therapy.

Noninvasive Diagnosis of Nonalcoholic Fatty Liver Disease and Quantification of Liver Fat Using a New Quantitative Ultrasound Technique

BACKGROUND & AIMS

Liver biopsy analysis is the standard method used to diagnose nonalcoholic fatty liver disease (NAFLD). Advanced magnetic resonance imaging is a noninvasive procedure that can accurately diagnose and quantify steatosis, but is expensive. Conventional ultrasound is more accessible but identifies steatosis with low levels of sensitivity, specificity, and quantitative accuracy, and results vary among technicians. A new quantitative ultrasound (QUS) technique can identify steatosis in animal models. We assessed the accuracy of QUS in the diagnosis and quantification of hepatic steatosis, comparing findings with those from magnetic resonance imaging proton density fat fraction (MRI-PDFF) analysis as a reference.

METHODS

We performed a prospective, cross-sectional analysis of a cohort of adults (N = 204) with NAFLD (MRI-PDFF, ≥5%) and without NAFLD (controls). Subjects underwent MRI-PDFF and QUS analyses of the liver on the same day at the University of California, San Diego, from February 2012 through March 2014. QUS parameters and backscatter coefficient (BSC) values were calculated. Patients were assigned randomly to training (n = 102; mean age, 51 ± 17 y; mean body mass index, 31 ± 7 kg/m(2)) and validation (n = 102; mean age, 49 ± 17 y; body mass index, 30 ± 6 kg/m(2)) groups; 69% of patients in each group had NAFLD.

RESULTS

BSC (range, 0.00005-0.25 1/cm-sr) correlated with MRI-PDFF (Spearman ρ = 0.80; P < .0001). In the training group, the BSC analysis identified patients with NAFLD with an area under the curve value of 0.98 (95% confidence interval, 0.95-1.00; P < .0001). The optimal BSC cut-off value identified patients with NAFLD in the training and validation groups with 93% and 87% sensitivity, 97% and 91% specificity, 86% and 76% negative predictive values, and 99% and 95% positive predictive values, respectively.

CONCLUSIONS

QUS measurements of BSC can accurately diagnose and quantify hepatic steatosis, based on a cross-sectional analysis that used MRI-PDFF as the reference. With further validation, QUS could be an inexpensive, widely available method to screen the general or at-risk population for NAFLD.

Ultrasound Imaging for Analyzing Lateral Tongue Movements during Mastication in Adults with Cerebral Palsy Compared with Adults without Oral Motor Disabilities

Described here is an ultrasound technique used to study tongue movements, particularly lateral tongue movements, during mastication. A method to analyze spatial and temporal tongue movements was developed, and the feasibility of using this method was evaluated. Biplane ultrasound images of tongue movements of four adults without oral motor disability and two adults with oral motor disability as a result of cerebral palsy, were acquired. Tongue movements were analyzed in the coronal and sagittal planes using B-mode and M-mode ultrasonography. Inter-rater and intra-rater agreement for manual tracing of tongue contours was good (ICC = 0.81 and 0.84, respectively). There were significant differences between the two adult groups in movement frequency in the horizontal direction in both coronal and sagittal planes. In the coronal plane, differences in movement frequency and range of vertical movement were detected. Data obtained from sagittal images, with the exception of vertical frequency, indicated no differences between the groups. The protocol developed in this study (using B-mode and M-mode) proved to be valid and reliable. By using this protocol with individuals with and without oral motor disability, we were able to illustrate the clinical application of our protocol to evaluation of differences in tongue movements during mastication.

Systematic review with meta-analysis: non-alcoholic steatohepatitis - a case for personalised treatment based on pathogenic targets

BACKGROUND

Non-alcoholic fatty liver disease (NAFLD) is an umbrella term, which encompasses simple steatosis and non-alcoholic steatohepatitis (NASH). The entire spectrum of NAFLD has been associated with metabolic syndrome. NASH is associated with increased mortality compared with that of the general population. Many therapeutic options for NASH have been studied. However, there is very little evidence supporting the efficacy of most regimens for the treatment of NASH.

AIM

To provide a review focusing on the current therapeutic options available for patients with NASH as well as to briefly introduce possible future interventions.

METHODS

A MEDLINE, Pubmed and Cochrane Review database search using a combination of keywords, which included non-alcoholic fatty liver disease, non-alcoholic hepatic steatosis, NAFLD, NASH, treatment, therapeutics, vitamin E, orlistat and bariatric surgery. An overall summary of the articles was developed for each section of discussion in this review.

RESULTS

NASH associated with metabolic syndrome can progress advanced fibrosis and cirrhosis. Weight loss and lifestyle modification have been shown to improve NASH. Other medications used for weight loss and metabolic syndrome have been evaluated, such as orlistat, metformin and thiazolidinediones. Alternative regimens using ursodeoxycholic acid, statins and probiotics as well as bariatric surgery have been evaluated, but have not been recommended as first-line treatment for NASH. Vitamin E for NASH patients without diabetes seems to be promising. The lack of effective treatment for NASH suggests the heterogeneity of patients presenting with the NASH phenotype. The best treatment strategy for these patients may be to identify their pathogenic target and develop personalised treatment protocols.

CONCLUSIONS

Currently, there are few options available for the management of NASH. Future targeted treatment strategies based on the pathogenic pathways may be needed to develop effective treatment for patients with NASH.