Data mining framework for fatty liver disease classification in ultrasound: a hybrid feature extraction paradigm

PURPOSE: Fatty liver disease (FLD) is an increasing prevalent disease that can be reversed if detected early. Ultrasound is the safest and ubiquitous method for identifying FLD. Since expert sonographers are required to accurately interpret the liver ultrasound images, lack of the same will result in interobserver variability. For more objective interpretation, high accuracy, and quick second opinions, computer aided diagnostic (CAD) techniques may be exploited. The purpose of this work is to develop one such CAD technique for accurate classification of normal livers and abnormal livers affected by FLD. METHODS: In this paper, the authors present a CAD technique (called Symtosis) that uses a novel combination of significant features based on the texture, wavelet transform, and higher order spectra of the liver ultrasound images in various supervised learning-based classifiers in order to determine parameters that classify normal and FLD-affected abnormal livers. RESULTS: On evaluating the proposed technique on a database of 58 abnormal and 42 normal liver ultrasound images, the authors were able to achieve a high classification accuracy of 93.3% using the decision tree classifier. CONCLUSIONS: This high accuracy added to the completely automated classification procedure makes the authors' proposed technique highly suitable for clinical deployment and usage.

Fatty liver characterization and classification by ultrasound

Steatosis, also known as fatty liver, corresponds to an abnormal retention of lipids within the hepatic cells and reflects an impairment of the normal processes of synthesis and elimination of fat. Several causes may lead to this condition, namely obesity, diabetes, or alcoholism. In this paper an automatic classification algorithm is proposed for the diagnosis of the liver steatosis from ultrasound images. The features are selected in order to catch the same characteristics used by the physicians in the diagnosis of the disease based on visual inspection of the ultrasound images. The algorithm, designed in a Bayesian framework, computes two images: i) a despeckled one, containing the anatomic and echogenic information of the liver, and ii) an image containing only the speckle used to compute the textural features. These images are computed from the estimated RF signal generated by the ultrasound probe where the dynamic range compression performed by the equipment is taken into account. A Bayes classifier, trained with data manually classified by expert clinicians and used as ground truth, reaches an overall accuracy of 95% and a 100% of sensitivity. The main novelties of the method are the estimations of the RF and speckle images which make it possible to accurately compute textural features of the liver parenchyma relevant for the diagnosis.

Fatty liver automatic diagnosis from ultrasound images

In this paper an automatic classification algorithm is proposed for the diagnosis of the liver steatosis, also known as, fatty liver, from ultrasound images. The features, automatically extracted from the ultrasound images used by the classifier, are basically the ones used by the physicians in the diagnosis of the disease based on visual inspection of the ultrasound images. The main novelty of the method is the utilization of the speckle noise that corrupts the ultrasound images to compute textural features of the liver parenchyma relevant for the diagnosis. The algorithm uses the Bayesian framework to compute a noiseless image, containing anatomic and echogenic information of the liver and a second image containing only the speckle noise used to compute the textural features. The classification results, with the Bayes classifier using manually classified data as ground truth show that the automatic classifier reaches an accuracy of 95% and a 100% of sensitivity.

Classification and staging of chronic liver disease from multimodal data

Chronic liver disease (CLD) is most of the time an asymptomatic, progressive, and ultimately potentially fatal disease. In this study, an automatic hierarchical procedure to stage CLD using ultrasound images, laboratory tests, and clinical records are described. The first stage of the proposed method, called clinical based classifier (CBC), discriminates healthy from pathologic conditions. When nonhealthy conditions are detected, the method refines the results in three exclusive pathologies in a hierarchical basis: 1) chronic hepatitis; 2) compensated cirrhosis; and 3) decompensated cirrhosis. The features used as well as the classifiers (Bayes, Parzen, support vector machine, and k-nearest neighbor) are optimally selected for each stage. A large multimodal feature database was specifically built for this study containing 30 chronic hepatitis cases, 34 compensated cirrhosis cases, and 36 decompensated cirrhosis cases, all validated after histopathologic analysis by liver biopsy. The CBC classification scheme outperformed the nonhierachical one against all scheme, achieving an overall accuracy of 98.67% for the normal detector, 87.45% for the chronic hepatitis detector, and 95.71% for the cirrhosis detector.

The usefulness of ultrasound in the classification of chronic liver disease

Chronic Liver Disease is a progressive, most of the time asymptomatic, and potentially fatal disease. In this paper, a semi-automatic procedure to stage this disease is proposed based on ultrasound liver images, clinical and laboratorial data. In the core of the algorithm two classifiers are used: a k nearest neighbor and a Support Vector Machine, with different kernels. The classifiers were trained with the proposed multi-modal feature set and the results obtained were compared with the laboratorial and clinical feature set. The results showed that using ultrasound based features, in association with laboratorial and clinical features, improve the classification accuracy. The support vector machine, polynomial kernel, outperformed the others classifiers in every class studied. For the Normal class we achieved 100% accuracy, for the chronic hepatitis with cirrhosis 73.08%, for compensated cirrhosis 59.26% and for decompensated cirrhosis 91.67%.

Chronic liver disease staging classification based on ultrasound, clinical and laboratorial data

In this work the identification and diagnosis of various stages of chronic liver disease is addressed. The classification results of a support vector machine, a decision tree and a k-nearest neighbor classifier are compared. Ultrasound image intensity and textural features are jointly used with clinical and laboratorial data in the staging process. The classifiers training is performed by using a population of 97 patients at six different stages of chronic liver disease and a leave-one-out cross-validation strategy. The best results are obtained using the support vector machine with a radial-basis kernel, with 73.20% of overall accuracy. The good performance of the method is a promising indicator that it can be used, in a non invasive way, to provide reliable information about the chronic liver disease staging.

Diffuse liver disease classification from ultrasound surface characterization, clinical and laboratorial data

In this work liver contour is semi-automatically segmented and quantified in order to help the identification and diagnosis of diffuse liver disease. The features extracted from the liver contour are jointly used with clinical and laboratorial data in the staging process. The classification results of a support vector machine, a Bayesian and a k-nearest neighbor classifier are compared. A population of 88 patients at five different stages of diffuse liver disease and a leave-one-out cross-validation strategy are used in the classification process. The best results are obtained using the k-nearest neighbor classifier, with an overall accuracy of 80.68%. The good performance of the proposed method shows a reliable indicator that can improve the information in the staging of diffuse liver disease.

Global and local detection of liver steatosis from ultrasound

Liver steatosis is a common disease usually associated with social and genetic factors. Early detection and quantification is important since it can evolve to cirrhosis. Steatosis is usually a diffuse liver disease, since it is globally affected. However, steatosis can also be focal affecting only some foci difficult to discriminate. In both cases, steatosis is detected by laboratorial analysis and visual inspection of ultrasound images of the hepatic parenchyma. Liver biopsy is the most accurate diagnostic method but its invasive nature suggest the use of other non-invasive methods, while visual inspection of the ultrasound images is subjective and prone to error. In this paper a new Computer Aided Diagnosis (CAD) system for steatosis classification and analysis is presented, where the Bayes Factor, obatined from objective intensity and textural features extracted from US images of the liver, is computed in a local or global basis. The main goal is to provide the physician with an application to make it faster and accurate the diagnosis and quantification of steatosis, namely in a screening approach. The results showed an overall accuracy of 93.54% with a sensibility of 95.83% and 85.71% for normal and steatosis class, respectively. The proposed CAD system seemed suitable as a graphical display for steatosis classification and comparison with some of the most recent works in the literature is also presented.

Education for health: alcohol and young aged school teenagers

Introduction: Alcohol consumption starts at an early age in Portuguese people. Health problems and risk behavior associated with excessive consumption can be prevented or highly reduced through effective school programs. Health professionals, such as biomedical scientists, (BSc), are important in promoting healthy lifestyles through the transmission of knowledge. Objective: Explore the role of the BSc in promoting health via intervention and clarification actions, (ICA), with 9th grade students from Agrupamento de Escolas da Portela e Moscavide (AEPM) and Visconde Juromenha (AEVJ); Verify the relationship between participating in the ICA and the level of knowledge acquired from it. Methods: Behaviors and beliefs concerning alcohol consumption and knowledge about the repercussions of it in the human body, mainly regarding the liver, were assessed by questionnaire. The questionnaire was completed before and after the ICA, by the control group (CG) and the study group (SG), respectively. The answers concerning knowledge were given points, later converted to a score from 0 to 100%. Data was analyzed applying descriptive statistics and the t-student test using SPSS 20.0. Results: After statistical analysis, it was found an average score of 48.8% for SG and 46.2% for CG. The difference between groups was statistically significant only in AEPM where ICA included a practical methodology (microscopic and macroscopic observation of pork livers), contrary to AEVJ. Conclusions: BSc intervention through ICA’s improves teenagers’ knowledge. Theoretical knowledge associated with practical approaches improves the retention of information and the development of a conscious behavior about the consumption of alcohol.

Fatty acids, IL6, and TNFα polymorphisms: an example of nutrigenetics in Crohn's disease

Objectives - The aim of this work was to study the interaction between genetic polymorphisms (single-nucleotide polymorphisms, SNPs) of pro- and anti-inflammatory cytokines and fat intake on the risk of developing Crohn's disease (CD) or modifying disease activity. Methods - Seven SNPs in interleukin 1 (IL1), tumor necrosis factor alpha (TNFalpha), lymphotoxin alpha (LTalpha), and IL6 genes were analyzed in 116 controls and 99 patients with CD. The type of fat intake was evaluated, and the interaction between SNPs and dietary fat in modulating disease activity was analyzed. Results - Individuals who were homozygous for the IL6-174G/C polymorphism had a six-fold higher risk for CD (odds ratio (OR)=6.1; 95% confidence interval (95% CI)=1.9-19.4), whereas the TT genotype on the TNFalpha-857C/T polymorphism was associated with more active disease (OR=10.4; 95% CI=1.1-94.1). A high intake of total, saturated, and monounsaturated fats, as well as a higher ratio of n-6/n-3 polyunsaturated fatty acid (PUFA), was associated with a more active phenotype (P<0.05). Furthermore, there was an interaction between dietary fat intake and SNPs, with a high intake of saturated and monounsaturated fats being associated with active disease, mainly in patients carrying the variant alleles of the 857 TNFalpha polymorphism (OR=6.0, 95% CI=1.4-26.2; OR=5.17; 95% CI=1.4-19.2, respectively) and the 174 IL6 polymorphism (OR=2.95; 95% CI=1.0-9.1; OR=3.21; 95% CI=1.0-10.4, respectively). Finally, low intake of n-3 PUFA and high n-6/n-3 PUFA ratio in patients with the TNFalpha 857 polymorphism were associated with higher disease activity (OR=3.6; 95% CI=1.0-13.0; OR=5.92; 95% CI=1.3-26.5, respectively). Conclusions - These results show that different types of fat may interact with cytokine genotype, modulating disease activity.

A supervised versus home-based program effects on liver transplanted familial amyloidotic polyneuropathy patients: walking, fatigue and quality of life

Purpose: To evaluate the effects of a six months exercise training program on walking capacity, fatigue and health related quality of life (HRQL). Relevance: Familial amyloidotic polyneuropathy disease (FAP) is an autossomic neurodegenerative disease, related with systemic deposition of amyloidal fibre mainly on peripheral nervous system and mainly produced in the liver. FAP often results in severe functional limitations. Liver transplantation is used as the only therapy so far, that stop the progression of some aspects of this disease. Transplantation requires aggressive medication which impairs muscle metabolism and associated to surgery process and previous possible functional impairments, could lead to serious deconditioning. Reports of fatigue are common feature in transplanted patients. The effect of supervised or home-based exercise training programs in FAP patients after a liver transplant (FAPTX) is currently unknown.

Body composition, muscle strength, functional capacity, and physical disability risk in liver transplanted familial amyloidotic polyneuropathy patients

Abstract: Background: Familial amyloidotic polyneuropathy (FAP) is a neurodegenerative disease leading to sensory and motor polyneuropathies, and functional limitations. Liver transplantation is the only treatment for FAP, requiring medication that negatively affects bone and muscle metabolism. The aim of this study was to compare body composition, levels of specific strength, level of physical disability risk, and functional capacity of transplanted FAP patients (FAPTx) with a group of healthy individuals (CON). Methods: A group of patients with 48 FAPTx (28 men, 20 women) was compared with 24 CON individuals (14 men, 10 women). Body composition was assessed by dual-energy X-ray absorptiometry, and total skeletal muscle mass (TBSMM) and skeletal muscle index (SMI) were calculated. Handgrip strength was measured for both hands as was isometric strength of quadriceps. Muscle quality (MQ) was ascertained by the ratio of strength to muscle mass. Functional capacity was assessed by the six-minute walk test. Results: Patients with FAPTx had significantly lower functional capacity, weight, body mass index, total fat mass, TBSMM, SMI, lean mass, muscle strength, MQ, and bone mineral density. Conclusion: Patients with FAPTx appear to be at particularly high risk of functional disability, suggesting an important role for an early and appropriately designed rehabilitation program.

Effects of an exercise training program in physical condition after liver transplantation in familial amyloidotic polyneuropathy: a case report

Introduction: Familial amyloidotic polyneuropathy (FAP) is a neurodegenerative disease that leads to sensory and motor polyneuropathies as well as functional limitations. So far, liver transplantation is the only treatment for FAP because the mutated protein causing the disease is mainly produced in the liver. With the increasing survival of transplant recipients, functional and cardiovascular problems as consequences of immunosuppressant side effects are increasing associated with sedentary lifestyles and/or retransplantation status. We sought to analyze the impact of exercise training programs on 1 FAP patient’s course long-term after liver transplantation. Methodology. A FAP patient (female; 49 years of age; body mass index 18.8 kg/m2) underwent a liver transplantation 133 months before assessment. She was assessed for body composition, isometric quadriceps muscle strength, functional capacity, fatigue, and levels of physical activity before and after a 6-month period of combined exercise training. Results: After the exercise training program, almost all variables were improved, namely, total body skeletal muscle mass, proximal femoral bone mineral density, quadriceps strength, maximal oxygen consumption on 6 minutes walk test (6mwt) or VO2peak, total ventilation on 6mwt, and fatigue. The improvement in distance on 6mwt (69.2 m) was clinically significant. Preintervention the levels of physical activity were below international recommendations for health; after the program they achieved the recommendations. Conclusion: The results showed an improvement in functional capacity with a decrease in future disability risk associated with a better lifestyle with respect to physical activity levels in 1 patient.

Strength, muscle quality and functional capacity in liver transplanted familial amyloidotic polineuropathy patients

Liver transplantation is the unique treatment for several end-stage diseases. Familial Amiloidotic Polineuropathy (FAP) is a neurodegenerative disease related with systemic deposition of amyloidal fiber mainly on peripheral nervous system, clinically translated by an autonomous sensitive-motor neuropathy with severe functional limitations in some cases. The unique treatment for FAP disease is a liver transplant with a very aggressive medication to muscle metabolism and force production. To our knowledge there are no quantitative characterizations of body composition, strength or functional capacity in this population.

Effects of a randomized trial of exercise on body composition of liver transplanted patients

Liver transplantation is used as a only therapy so far, that stop the progression of some aspects of familial amyloidotic polyneuropathy disease (FAP) an autossomic neurodegenerative disease. FAP often results in severe functional limitations. Transplantation requires aggressive medication which impairs bone and muscle metabolism. Malnutrition plus weight loss is already one feature of FAP patients. All this may produce negative consequences on body composition. The effect of exercise training in FAP patients after a liver transplant (FAPTX) is currently unknown. The purpose of this study is to evaluate the effects of a six months exercise training program on body composition in FAPTX patients.