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Optimal region-of-interest MRI R2* measurements for the assessment of hepatic iron content in thalassaemia major
Authors:Meiyan Feng  Xinyuan Zhang  Huashuai Gao  Yikai Xu  Binquan Lin  Jianyun Liao  Wufan Chen  Yanqiu Feng
Affiliation:1. School of Biomedical Engineering, Southern Medical University, Guangzhou, China;2. Department of Diagnostic Imaging Centre, Nanfang Hospital, Southern Medical University, Guangzhou, China;3. Department of Pediatrics, Nanfang Hospital, Southern Medical University, Guangzhou, China
Abstract:

Objectives

To evaluate the performance of region-of-interest (ROI)-based MRI R2* measurements by using the first-moment noise-corrected model (M1NCM) to correct the non-central Chi noise in magnitude images from phased arrays for hepatic iron content (HIC) assessment.

Methods

R2* values were quantified using the M1NCM model. Three approaches were employed to determine the representative R2*: fitting of the ROI-averaged signal (average-then-fit, ATF); outputting the median and mean of R2*s from the pixel-wise fitting of decay signals within the ROI (denoted as PWFmed and PWFmea, respectively). The accuracy and precision of the three approaches were evaluated on synthesized data. The agreement among these approaches and their intra- and inter-observer reproducibility were assessed on 105 thalassaemia major patients.

Results

Simulations showed that ATF consistently yielded the highest accuracy and precision at varying noise levels. By contrast, PWFmed and PWFmea slightly and significantly overestimated high R2* at poor signal-to-noise ratios, respectively. Patient study showed that ATF agreed well with PWFmed, whereas PWFmea produced high R2* measurements for patients with severe HIC. No significant difference was observed in the reproducibility of the three approaches.

Conclusions

PWFmea tends to overestimate high R2*, whereas ATF and PWFmed can produce more accurate R2* measurements for HIC assessment.
Keywords:Magnetic resonance imaging   R2* relaxometry   Hepatic iron content   Region-of-interest   Noise-corrected model
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