Research and application of IDEAL-IQ sequence of magnetic resonance imaging for fat content measurement
Objective Evaluating the accuracy of the IDEAL-IQ sequence in measuring liver fat content and identifying the factors influencing measurement accuracy.Methods Using the single channel head coil,eight channel head coil,and eight channel abdominal coil of GE Discovery MR750 3.0T,high parameter scanning was performed on water lipid mixed solution models with different concentrations.Multiple fat content measurements were conducted on the GE AW4.6 workstation,and linear regression analysis was performed on the measured values to discuss the correlation between the measured values and known configuration values,and to analyze the accuracy of measuring the water fat mixture phantom in different coils.Results For the aqueous lipid mixture solution model with a known concentration,the IDEAL-IQ sequence was employed in the univariate linear regression analysis of data measured by three different coils.The P-values for the three regression models were all less than 0.0001,indicating significant differences at the α=0.0001 level.The models demonstrated good fitting,achieving a confidence level of 99.99%.Scanning with the same parameters but different coils results in image noise due to varying signal-to-noise ratios.Using a small ROI for measurement can lead to substantial deviations in the results for the same slice.Conclusion The IDEAL-IQ sequence is feasible,reliable,and highly accurate for quantitative measurement of fat content.However,the quality of scanned images has an impact on measurement stability and accuracy.The greater the image noise,the more unstable the measurement results and the greater the deviation of the measurement values.Under clinical scanning conditions,clinical physicians should measure liver fat content by taking the average of appropriate ROI multi-point measurements,while also avoiding the initial and end layers in the liver scanning layer.If the selected area falls within the initial and final layers,it may lead to overestimation of fat content.
Magnetic resonance imaging technologyIDEAL-IQFat content measurementClinical precise measurement
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