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%.

Non-colorectal intestinal tract carcinomas in inflammatory bowel disease: results of the 3rd ECCO Pathogenesis Scientific Workshop (II)

Patients with inflammatory bowel diseases (IBD) have an excess risk of certain gastrointestinal cancers. Much work has focused on colon cancer in IBD patients, but comparatively less is known about other more rare cancers. The European Crohn's and Colitis Organization established a pathogenesis workshop to review what is known about these cancers and formulate proposals for future studies to address the most important knowledge gaps. This article reviews the current state of knowledge about small bowel adenocarcinoma, ileo-anal pouch and rectal cuff cancer, and anal/perianal fistula cancers in IBD patients.

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.

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.

Q192R polymorphism of the paraoxonase-1 gene as a risk factor for obesity in Portuguese women

Introduction - Obesity became a major public health problem as a result of its increasing prevalence worldwide. Paraoxonase-1 (PON1) is an esterase able to protect membranes and lipoproteins from oxidative modifications. At the PON1 gene, several polymorphisms in the promoter and coding regions have been identified. The aims of this study were i) to assess PON1 L55M and Q192R polymorphisms as a risk factor for obesity in women; ii) to compare PON1 activity according to the expression of each allele in L55M and Q192R polymorphisms; iii) to compare PON1 activity between obese and normal-weight women. Materials and methods - We studied 75 healthy (35.9±8.2 years) and 81 obese women (34.3±8.2 years). Inclusion criteria for obese subjects were body mass index ≥30 kg/m2 and absence of inflammatory/neoplasic conditions or kidney/hepatic dysfunction. The two PON1 polymorphisms were assessed by real-time PCR with TaqMan probes. PON1 enzymatic activity was assessed by spectrophotometric methods, using paraoxon as a substrate. Results - No significant differences were found for PON1 activity between normal and obese women. Nevertheless, PON1 activity was greater (P<0.01) for the RR genotype (in Q192R polymorphism) and for the LL genotype (in L55M polymorphism). The frequency of allele R of Q192R polymorphism was significantly higher in obese women (P<0.05) and was associated with an increased risk of obesity (odds ratio=2.0 – 95% confidence interval (1.04; 3.87)). Conclusion - 55M and Q192R polymorphisms influence PON1 activity. The allele R of the Q192R polymorphism is associated with an increased risk for development of obesity among Portuguese Caucasian premenopausal women.

Cholesterol 24S-Hydroxylase overexpression inhibits the liver X receptor (LXR) pathway by activating small guanosine triphosphate-binding proteins (sGTPases) in neuronal cells

The neuronal-specific cholesterol 24S-hydroxylase (CYP46A1) is important for brain cholesterol elimination. Cyp46a1 null mice exhibit severe deficiencies in learning and hippocampal long-term potentiation, suggested to be caused by a decrease in isoprenoid intermediates of the mevalonate pathway. Conversely, transgenic mice overexpressing CYP46A1 show an improved cognitive function. These results raised the question of whether CYP46A1 expression can modulate the activity of proteins that are crucial for neuronal function, namely of isoprenylated small guanosine triphosphate-binding proteins (sGTPases). Our results show that CYP46A1 overexpression in SH-SY5Y neuroblastoma cells and in primary cultures of rat cortical neurons leads to an increase in 3-hydroxy-3-methyl-glutaryl-CoA reductase activity and to an overall increase in membrane levels of RhoA, Rac1, Cdc42 and Rab8. This increase is accompanied by a specific increase in RhoA activation. Interestingly, treatment with lovastatin or a geranylgeranyltransferase-I inhibitor abolished the CYP46A1 effect. The CYP46A1-mediated increase in sGTPases membrane abundance was confirmed in vivo, in membrane fractions obtained from transgenic mice overexpressing this enzyme. Moreover, CYP46A1 overexpression leads to a decrease in the liver X receptor (LXR) transcriptional activity and in the mRNA levels of ATP-binding cassette transporter 1, sub-family A, member 1 and apolipoprotein E. This effect was abolished by inhibition of prenylation or by co-transfection of a RhoA dominant-negative mutant. Our results suggest a novel regulatory axis in neurons; under conditions of membrane cholesterol reduction by increased CYP46A1 expression, neurons increase isoprenoid synthesis and sGTPase prenylation. This leads to a reduction in LXR activity, and consequently to a decrease in the expression of LXR target genes.