Autoimmune hepatitis in India: profile of an uncommon disease

BACKGROUND: Autoimmune hepatitis (AIH) has been reported to show considerable geographical variation in frequency and clinical manifestations. It is considered a rare cause of liver disease in India. The present study was undertaken to determine the incidence, clinical, biochemical and histological profile of AIH in this part of the world. METHODS: Patients presenting with acute or chronic liver disease between January 1999 and June 2002 were evaluated prospectively. AIH was diagnosed using the international autoimmune hepatitis group criteria. Workup included clinical, biochemical, USG, viral markers, UGI endoscopy, AI markers (ANA, SMA, Anti-LKM, AMA, RF, p-ANCA) using indirect immunofluorescence and liver biopsy if possible. RESULTS: Forty-one of 2401 (1.70%) patients were diagnosed to have autoimmune liver disease. Out of these, 38 had autoimmune hepatitis and the rest 3 had primary biliary cirrhosis. The mean age of the patients of autoimmune hepatitis was 36.2 (15.9) years, 34 (89.4%) were females, and the duration of symptoms was 20.3 (20.5) months. Nineteen (50%) of them presented with chronic hepatitis, 13 (34.2%) as cirrhosis, 5 (13.1%) with acute hepatitis and 1 (2.6%) with cholestatic hepatitis. The presentations were jaundice in 21 (55.2%), pedal edema and hepatomegaly in 17 (44.7%), splenomegaly in 13 (34.2%), encephalopathy, abdominal pain in 9 (23.6%) and fever in 8 (21%). Twelve had esophageal varices and 3 had bled. Biochemical parameters were ALT 187 (360) U/L, AST 157 (193) U/L, ALP 246 (254) U/L, globulin 4.1 (1.6) g/dL, albumin 2.8 (0.9) g/dL, bilirubin 5.2 (7.4) mg/dL, prothrombin time 17 (7) sec and ESR 47 (17) sec. The autoimmune markers were SMA (24), ANA (15), both SMA and ANA (4), AMA (1), rheumatoid factor (2), pANCA (1), and Anti-LKM in none. Thirty (79%) patients had definite AIH and eight (21%) had probable AI hepatitis. Associated autoimmune diseases was seen in 15/38 (39.4%), diabetes 4, hypothyroidism 3, vitiligo 2, thrombocytopenia 2, rheumatoid arthritis 2, Sjogren's syndrome 1 and autoimmune polyglandular syndrome III in 1. Viral markers were positive in two patients, one presenting as acute hepatitis and HEV-IgM positive and another anti-HCV positive. CONCLUSION: In India, autoimmune hepatitis is uncommon and usually presents with chronic hepatitis or cirrhosis, acute hepatitis being less common. Age at presentation was earlier but clinical parameters and associated autoimmune diseases were similar to that reported from the west. Primary biliary cirrhosis is rare. Type II AIH was not observed

Diagnosis of Hashimoto's thyroiditis in ultrasound using tissue characterization and pixel classification

Hashimoto's thyroiditis is the most common type of inflammation of the thyroid gland, and accurate diagnosis of Hashimoto's thyroiditis would be helpful to better manage the disease process and predict thyroid failure. Most of the published computer-based techniques that use ultrasound thyroid images for Hashimoto's thyroiditis diagnosis are limited by lack of procedure standardization because individual investigators use various initial ultrasound settings. This article presents a computer-aided diagnostic technique that uses grayscale features and classifiers to provide a more objective and reproducible classification of normal and Hashimoto's thyroiditis-affected cases. In this paradigm, we extracted grayscale features based on entropy, Gabor wavelet, moments, image texture, and higher order spectra from the 100 normal and 100 Hashimoto's thyroiditis-affected ultrasound thyroid images. Significant features were selected using t-test. The resulting feature vectors were used to build the following three classifiers using tenfold stratified cross validation technique: support vector machine, k-nearest neighbor, and radial basis probabilistic neural network. Our results show that a combination of 12 features coupled with support vector machine classifier with the polynomial kernel of order 1 and linear kernel gives the highest accuracy of 80%, sensitivity of 76%, specificity of 84%, and positive predictive value of 83.3% for the detection of Hashimoto's thyroiditis. The proposed computer-aided diagnostic system uses novel features that have not yet been explored for Hashimoto's thyroiditis diagnosis. Even though the accuracy is only 80%, the presented preliminary results are encouraging to warrant analysis of more such powerful features on larger database