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To evaluate the feasibility of simultaneous quantification of liver fibrosis, liver steatosis and abnormal iron deposition using mDixon Quant based on radiomics analysis, and to eliminate the interference among different histopathologic features. One hundred and twenty rabbits that were administered CCl4 for 4–16 weeks and a cholesterol rich diet for the initial 4 weeks in the experimental group and 20 rabbits in the control group were examined using mDixon. Radiomics features of the whole liver were extracted from PDFF and R2* and radiomics models for discriminating steatosis: S0-S1 vs. S2-S4, fibrosis: F0–F2 vs. F3–F4 and iron deposition: normal vs. abnormal were constructed respectively and evaluated using receiver operating characteristic (ROC) curves with the histopathological results as reference standard. Combined corrected models merging the radscore and the other two histopathologic features were evaluated using multiple logistic regression analyses and compared with radiomics models. The area under the ROC curve (AUC) of the radiomics model with PDFF features was 0.886 and 0.843 in the training and the test set, respectively, for the diagnosis of liver steatosis grade S0–1 and S2-S4. The radiomics model based on R2* features were 0.815 and 0.801 for distinguishing F0-F2 and F3-F4 and 0.831 and 0.738 for discriminating abnormal iron deposition in the training and test set, respectively. The corrected model for liver steatosis and fibrosis (0.944 and 0.912 in the test set) outperformed the radiomics models by eliminating the interference of histopathologic features(P < 0.05), but had comparable diagnostic performance for abnormal iron deposition(P > 0.05). It is feasible for mDixon to simultaneously quantify whole liver steatosis, fibrosis and iron deposition based on radiomics analysis. It is valuable to minimize the interference of different pathological features for the assessment of liver steatosis and fibrosis. • The feasibility of mDixon Quant based on radiomics analysis for simultaneous quantification of liver fibrosis, liver steatosis and abnormal iron deposition was unknown. • To eliminate interference of fat, fibrosis and iron to signal decay can improve the diagnostic performance of radiomics model • Liver fibrosis, liver steatosis and abnormal iron deposition is the key feature of many chronic liver disorder (CLD) [ABSTRACT FROM AUTHOR]

Introduction: Iron deposition in liver is a major finding in thalassemic patients. Histologic grading of iron deposition is widely used in many institutions and various grading systems have been introduced. The aim of this study was to introduce a new histologic scoring system (Markaze Tebbi Koodakan: MTK 1, 2 and 3) which considers size and density of iron granules as well as zone of iron deposition and verify this system with atomic absorption spectrometry (AAS method). Materials and methods: Liver biopsies from 63 patients were evaluated, 40 (63.5%) were male and 20 (36.5%) were female. The mean age of the patients was 8.01±3.7 and the age range was from 1.8 to 15 years. Iron scoring was performed according to Sindram & Marx and MTK 1-3 scoring systems.Paraffin blocks were processed for AAS and the results of the iron analysis (HIC: hepatic iron concentration) were reported as µmol/g dry liver weight. The statistical analysis was performed using SPSS, version 16 (SPSS Inc., Chicago, IL, USA). Results: The mean (SD) of hepatic iron concentration was 230.9 (121.2) µmol/g dry weight. The relationship between the variables HIC, HII (hepatic iron index) and all histological grading of iron (S&M and MTK1-3) was very strong. Significant differences were identified between the mean HIC in scores 1 & 2 of all histological iron scorings (S&M and MTK 1-3), but no significant differences identified in other adjacent scores in all histological iron scorings (S&M and MTK 1, 2 and 3). Discussion and conclusion: New scoring system introduced by us in this study was very much the same as simple Sindram and Marx classification. So it is concluded that although size of iron granules is important in lower scores, but in higher scores it is not as much important as the zone in which iron granules are deposited.