Liver volume in patients with or without chronic liver diseases. 1998

X Z Lin, and Y N Sun, and Y H Liu, and B S Sheu, and B N Cheng, and C Y Chen, and H M Tsai, and C L Shen
Department of Internal Medicine, National Cheng Kung University and Hospital, Tainan, Taiwan. Linxz@mail.ncku.edu.tw

OBJECTIVE The size of the liver is an important clinical parameter; the aim of this study is to examine the correlation between liver volume and etiology and the severity of disease, and to evaluate its usefulness in predicting survival. METHODS Patients observed in this study were comprised of thirty three patients with non-liver disease and 44 patients with chronic liver disease (alcoholic hepatitis, 9; hepatitis B, 24; and hepatitis C, 11). The liver volume was measured from digitized CT scan images. Techniques of planimetry and summation of areas were utilized for calculation. RESULTS The prediction model to estimate liver volume in patients without liver disease was: liver volume (ml)= [13 x height (cm)] +[12 x weight (Kg)] - 1530. The volume ratio (%) [(volume from reconstructed image /predicted volume) x 100] of alcoholic patients was 135.9+/-25.8, which was significantly higher than that of chronic hepatitis B (73.6+/-15.4) and chronic hepatitis C (74.5+/-20.7). Patients with chronic viral hepatitis were classified into Child-Pugh class A (N=10), B (N=14) and C (N=11). Analysis of variance and trend test revealed that the volume ratio had a significant decreasing trend from the control group (100.5+/-8.1), class A (83.4+/-13.9), class B (72.2+/-13.2) to class C (63.3+/-14.4). CONCLUSIONS Liver volume can be predicted from patients' weight and height if they have no liver disease. The liver volume ratio correlates much better with etiology and severity of the disease and is a reliable predictor for patient's survival.

UI MeSH Term Description Entries
D007091 Image Processing, Computer-Assisted A technique of inputting two-dimensional or three-dimensional images into a computer and then enhancing or analyzing the imagery into a form that is more useful to the human observer. Biomedical Image Processing,Computer-Assisted Image Processing,Digital Image Processing,Image Analysis, Computer-Assisted,Image Reconstruction,Medical Image Processing,Analysis, Computer-Assisted Image,Computer-Assisted Image Analysis,Computer Assisted Image Analysis,Computer Assisted Image Processing,Computer-Assisted Image Analyses,Image Analyses, Computer-Assisted,Image Analysis, Computer Assisted,Image Processing, Biomedical,Image Processing, Computer Assisted,Image Processing, Digital,Image Processing, Medical,Image Processings, Medical,Image Reconstructions,Medical Image Processings,Processing, Biomedical Image,Processing, Digital Image,Processing, Medical Image,Processings, Digital Image,Processings, Medical Image,Reconstruction, Image,Reconstructions, Image
D008099 Liver A large lobed glandular organ in the abdomen of vertebrates that is responsible for detoxification, metabolism, synthesis and storage of various substances. Livers
D008107 Liver Diseases Pathological processes of the LIVER. Liver Dysfunction,Disease, Liver,Diseases, Liver,Dysfunction, Liver,Dysfunctions, Liver,Liver Disease,Liver Dysfunctions
D008297 Male Males
D008875 Middle Aged An adult aged 45 - 64 years. Middle Age
D009929 Organ Size The measurement of an organ in volume, mass, or heaviness. Organ Volume,Organ Weight,Size, Organ,Weight, Organ
D011237 Predictive Value of Tests In screening and diagnostic tests, the probability that a person with a positive test is a true positive (i.e., has the disease), is referred to as the predictive value of a positive test; whereas, the predictive value of a negative test is the probability that the person with a negative test does not have the disease. Predictive value is related to the sensitivity and specificity of the test. Negative Predictive Value,Positive Predictive Value,Predictive Value Of Test,Predictive Values Of Tests,Negative Predictive Values,Positive Predictive Values,Predictive Value, Negative,Predictive Value, Positive
D011379 Prognosis A prediction of the probable outcome of a disease based on a individual's condition and the usual course of the disease as seen in similar situations. Prognostic Factor,Prognostic Factors,Factor, Prognostic,Factors, Prognostic,Prognoses
D012044 Regression Analysis Procedures for finding the mathematical function which best describes the relationship between a dependent variable and one or more independent variables. In linear regression (see LINEAR MODELS) the relationship is constrained to be a straight line and LEAST-SQUARES ANALYSIS is used to determine the best fit. In logistic regression (see LOGISTIC MODELS) the dependent variable is qualitative rather than continuously variable and LIKELIHOOD FUNCTIONS are used to find the best relationship. In multiple regression, the dependent variable is considered to depend on more than a single independent variable. Regression Diagnostics,Statistical Regression,Analysis, Regression,Analyses, Regression,Diagnostics, Regression,Regression Analyses,Regression, Statistical,Regressions, Statistical,Statistical Regressions
D005260 Female Females

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