Evaluation of liver iron content using synchrotron radiation CT in iron-overload mice

R. Tang, B. Shi, F. Yan, G.Y. Yang, K.-M. Chen

JOURNAL OF INSTRUMENTATION(2019)

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摘要
Evaluation of liver iron content (LIC) is crucial for the judgment of hepatic iron overload (HIO). Here, we evaluated the potential utility of synchrotron radiation (SR) CT for quantifying LIC in mice suffered from HIO. The mice models of HIO were made by the injection of iron dextran. A series of total iron injection doses of 0, 12.5, 25, 50 and 100 mg were used. SR CT imaging was performed using a detector with the pixel size of 6.5 mu m x 6.5 mu m at the energy level of 12 keV. The iron micro-depositions were pathologically confirmed using Prussian blue staining. The reconstructed transverse sections were obtained by applying the filtered back projection (FBP) algorithm with PITRE software. 3D visualization was performed using Amira 5.4. LIC was confirmed by an inductively coupled plasma (ICP) spectrometer. SR CT-derived LIC (LICCT) was defined as the volume ratio of iron depositions to the liver. The volume ratio was measured using ImageJ software. SR CT presented a high-spatial resolution to clearly display iron micro-depositions in the iron-overload liver. Additionally, iron micro-depositions were found to distribute unevenly on 3D images. The LIC(CT)s were 0, (1.890 +/- 0.172)%, (4.148 +/- 0.282)%, (6.769 +/- 0.201)%, and (12.912 +/- 0.270)% for injection doses of 0 mg, 12.5 mg, 25 mg, 50 mg and 100 mg, respectively. LICCT had a strong linear correlation with injection dose (R-2 = 0.9930, P < 0.0001) or ICP-derived LIC (LICICP) (R-2 = 0.9644, P < 0.0001). The linear correlation between LICCT and LICICP could be expressed by an equation. Using this equation, LIC could be predicted by measuring LICCT. Therefore, SR CT imaging showed potential ability to quantify LIC. The imaging modality may be used for the evaluation of disease progression and therapeutic efficacy in mice models.
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关键词
Computerized Tomography (CT) and Computed Radiography (CR),Medical-image reconstruction methods and algorithms,computer-aided diagnosis
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