| 20110313276 | NON-INVASIVE IN VITRO METHOD FOR QUANTIFYING LIVER LESIONS - An in-vitro non-invasive method for quantifying the lesions of the liver of the patient with metabolic steatosis addressing a diagnostic target, i.e. fibrosis, steatosis and/or steato-hepatitis (NASH) and measuring at least one marker selected from the group consisting of biomarkers and possibly clinical markers and possibly scores, the biomarkers being selected from the group consisting of glycemia, AST (aspartate aminotransferase), ALT (alanine aminotransferase), AST/ALT, AST.ALT, ferritin, platelets, prothrombin index, hyaluronic acid, haemoglobin, triglycerides; the biomarker selected from weight, body mass index, sex and age, hip perimeter, abdominal perimeter and ratio thereof; the scores being selected from score of fibrosis, area of fibrosis, fractal dimension of fibrosis, score of steatosis, area of steatosis, fractal dimension of steatosis and combining the measures in a mathematical function combining the measures through a binary (or ordinal) logistic function or multiple linear regression including the markers in order to obtain an end value. | 12-22-2011 |
| 20110306849 | Diagnosis of Liver Fibrosis and Cirrhosis - This invention relates to method of diagnosing the presence and/or severity of a liver pathology and/or of monitoring the effectiveness of a curative treatment against a liver pathology in an individual, leading to a score, comprising the combination, of at least one blood test and of at least one data issued from a physical method of diagnosing liver fibrosis, said data being selected from the group consisting of medical imaging data and clinical measurements, said combination being performed through a mathematical function. This invention also relates to a method wherein the combination through a mathematical function, of at least one blood test and of at least one data issued from a physical method of diagnosing liver fibrosis, is performed at least twice and the at least two resulting scores are combined in an algorithm based on the diagnostic reliable intervals. | 12-15-2011 |
