Effects Of Signal Intensity Inhomogeneity On Quantitative Susceptibility Mapping

Quantitative susceptibility mapping(QSM)can deconvolve the GRE phase data to determine tissue magnetic susceptibility distribution,which is widely used in clinical and scientific applications.However,scanning protocols and different reconstruction algorithms may affect the accuracy of QSM.Various QSM reconstruction algorithms have been proposed to solve the ill-posed problem of field-to-source inversion.The MEDI toolbox and STI Suite software packages integrate the most commonly QSM reconstruction algorithms,which are robust and easy to implement.The sensitivity of coils may lead to the non-uniformity of image signal intensity,which also has a great impact on the imaging quality and accuracy of susceptibility values.At present,there is no report that evaluated effects of signal intensity inhomogeneity on QSM reconstruction.Therefore,in this thesis,we investigate the effects of coil selection and intensity inhomogeneity correction on QSM reconstruction from following three sections.(1)Study on the effect of intensity inhomogeneity correction on QSM images reconstructed by MEDI algorithmThe aim of this study was to evaluate the effects of coil selection and signal intensity inhomogeneity on QSM images reconstructed using the MEDI algorithm toolbox.Thirteen healthy subjects were scanned on a 3T MRI system using 20-and 64-channel combined head-neck coils to obtain image data with and without intensity inhomogeneity correction,respectively.QSM images were reconstructed using the MEDI algorithm toolbox,and the image quality,susceptibility values,and noise levels were evaluated.The results showed that the QSM images with intensity inhomogeneity correction demonstrated improved boundaries of deep gray matter nuclei.The susceptibility values increased significantly in these nuclei.Additionally,after intensity inhomogeneity correction,QSM images acquired with 20-and 64-channel coils demonstrated better reproducibility.In conclusion,this study revealed that intensity inhomogeneity correction can improve the accuracy of susceptibility values of deep gray matter nuclei.(2)Study on the effect of intensity inhomogeneity correction on QSM images reconstructed using the STI Suite algorithmThe purpose of this study was to evaluate the effects of coil selection and signal intensity inhomogeneity on QSM images reconstructed using the STI Suite algorithm.Thirteen healthy subjects were scanned on a 3T MRI system using 20-and 64-channel combined head-neck coils to obtain image data with and without intensity inhomogeneity correction,respectively.QSM images were reconstructed using the STI Suite algorithm to compare the image quality,susceptibility values,and noise levels.QSM images reconstructed using STI Suite algorithm without intensity inhomogeneity correction showed a large missing area in the middle brain region.After intensity inhomogeneity correction,the masks automatically generated from the magnitude data were more reasonable for QSM reconstruction,resulting in more accurate QSM images.If the ideal masks were manually generated,the reconstructed QSMs were the same before and after intensity inhomogeneity correction.Additionally,QSM images acquired with 20-and 64-channel coils demonstrated good reproducibility.In conclusion,intensity inhomogeneity correction can improve the stability of QSM images reconstructed by STI Suite algorithm.(3)Study on the effect of the N4 ITK algorithm on QSM images reconstructed using the MEDI algorithm toolboxIn this study,we tried to use the post-processing algorithm N4 ITK to correct the inhomogeneity of the magnitude image,and then reconstructed the QSM images using the MEDI algorithm toolbox.The results showed that the N4 ITK algorithm could effectively improve the homogeneity of the magnitude image.The QSM images reconstructed from the corrected magnitude image had better tissue contrasts and clearer boundaries of deep nuclei.Therefore,to some extent,the N4 ITK algorithm could effectively improve the accuracy of QSM images by improving the homogeneity of the magnitude image.However,the N4 ITK algorithm needs to be optimized to improve the accuracy in susceptibility values of deep gray matter nuclei.In conclusion,inhomogeneity correction of the magnitude image can improve the accuracy of QSM images.The results of this study may help to improve the accuracy and reliability for disease diagnosis and scientific research using QSM.