VIP会员
PDFf-r2* model, 725 iron-lipid integrated model, 725 PDFf-r2 model, 725 PDFf-r2* model characteristics
- 16 sample bottles: (0/50), (0/150), (0/350), (0/600), (10/50), (10/150), (10/350), (10. 600), (20/50), (20/150), (20/350), (20. 600), (30/50), (30/150), (30/350), (30. 600) [% PDFf/s-1] (under 3t)
- Simulator vials are filled with gel to minimize motion hypocrisy。
- Asymmetrically placed sample bottles are used to avoid ambiguity in sample bottles from the right, the upper and the lower。
- Combination of filling solution to minimize lipid for pseudo-image
Clinical significance of PDFf-r2* quantitative analysis
Unusual fat and iron depositions in the liver are the main tissue characteristics of many diseases. For example, metabolic functionally impaired fatty liver (masld, formerly known as non-alcoholic fatty liver, nafld) is becoming the leading cause of liver disease. Iron overloads coexist with masl, and liver iron levels are also important indicators of total iron levels in patients with hereditary haemoglobinism and multiple blood transfusions. Overloading of liver fat and iron leads to liver damage and fibrosis, which eventually develops into liver cirrhosis, liver function failure and liver cell cancer. It is noteworthy that fat and iron sediments are also often present as key tissue characteristics of other organ diseases such as heart, pancreas and kidneys. Non-intrusive mri biomarkers based on proton density fat fractions (PDFf) and iron content (r2*) have been in use in recent years. The chemical diversion code mri method can estimate PDFf and r2* from the same set of multiple echo data. This is critical because the r2* signal decay rate increases with the linearity of iron concentrations, and if the signal estimation model does not take this factor into account, it interferes with the quantitative analysis of fat. Similarly, the presence of fat can interfere with the quantitative analysis of iron. Our PDFf-r2* model can more accurately test and guarantee the quality of PDFf and r2* quantitative methods。