Weronika Mazur‐Rosmus, William M. Spees, Artur T. Krzyżak
{"title":"The added value of diffusion tensor imaging with systematic bias correction for the assessment of liver morphology and physiology","authors":"Weronika Mazur‐Rosmus, William M. Spees, Artur T. Krzyżak","doi":"10.1002/nbm.5259","DOIUrl":null,"url":null,"abstract":"Diffusion‐weighted images of the human liver are prone to artifacts from bulk motions, poor SNR, non‐uniformity of magnetic field gradients, and non‐optimal choice of diffusion weightings. These factors markedly affect diffusion tensor imaging (DTI) metrics such as mean diffusivity (MD) and fractional anisotropy (FA).This work presents a simple preprocessing pipeline for enhanced magnetic field gradient non‐uniformity calibration and analysis of the systematic bias removal attained in each correction step.Liver DTI scans were conducted in two isotropic phantoms and one healthy volunteer. Diffusion tensor was calculated for the original data and after denoising, B1 correction, rigid body registration, and magnetic field gradient non‐uniformity correction applying the B‐matrix spatial distribution (BSD) method and then, compared with the standard approach (sDTI). MD and FA were determined in three segments of the right lobe from DTI using four different combinations of <jats:italic>b</jats:italic>‐values from the set 0, 400, and 800 s/mm<jats:sup>2</jats:sup>.Results showed that the proposed preprocessing and BSD methods have a significant impact on MD and FA values in off‐ and iso‐centered isotropic phantoms. The applied corrections applied to the human liver resulted in a 11% change in MD and a − 64% change in FA. By manipulating the <jats:italic>b</jats:italic>‐values used in the diffusion tensor calculation, DTI metrics that reflect only morphology or additional information about liver tissue physiology can be obtained.Accurate quantification of the human liver by diffusion requires appropriate preprocessing and carefully chosen <jats:italic>b</jats:italic>‐value.Noise, B1 inhomogeneity, mis‐registration, and non‐uniform magnetic field gradients significantly change distributions of DTI metrics in isotropic phantoms and the human liver. Basic preprocessing and the B‐matrix spatial distribution (BSD) method perform differently for off‐center and isocenter locations. In the human liver, they removed systematic bias of FA and MD by up to −63% and 11%, respectively. Visible variability of FA and MD among <jats:italic>b</jats:italic>‐value sets indicates the possibility of DTI sensitization to different liver compartments.","PeriodicalId":19309,"journal":{"name":"NMR in Biomedicine","volume":null,"pages":null},"PeriodicalIF":2.7000,"publicationDate":"2024-09-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"NMR in Biomedicine","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1002/nbm.5259","RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"BIOPHYSICS","Score":null,"Total":0}
引用次数: 0
Abstract
Diffusion‐weighted images of the human liver are prone to artifacts from bulk motions, poor SNR, non‐uniformity of magnetic field gradients, and non‐optimal choice of diffusion weightings. These factors markedly affect diffusion tensor imaging (DTI) metrics such as mean diffusivity (MD) and fractional anisotropy (FA).This work presents a simple preprocessing pipeline for enhanced magnetic field gradient non‐uniformity calibration and analysis of the systematic bias removal attained in each correction step.Liver DTI scans were conducted in two isotropic phantoms and one healthy volunteer. Diffusion tensor was calculated for the original data and after denoising, B1 correction, rigid body registration, and magnetic field gradient non‐uniformity correction applying the B‐matrix spatial distribution (BSD) method and then, compared with the standard approach (sDTI). MD and FA were determined in three segments of the right lobe from DTI using four different combinations of b‐values from the set 0, 400, and 800 s/mm2.Results showed that the proposed preprocessing and BSD methods have a significant impact on MD and FA values in off‐ and iso‐centered isotropic phantoms. The applied corrections applied to the human liver resulted in a 11% change in MD and a − 64% change in FA. By manipulating the b‐values used in the diffusion tensor calculation, DTI metrics that reflect only morphology or additional information about liver tissue physiology can be obtained.Accurate quantification of the human liver by diffusion requires appropriate preprocessing and carefully chosen b‐value.Noise, B1 inhomogeneity, mis‐registration, and non‐uniform magnetic field gradients significantly change distributions of DTI metrics in isotropic phantoms and the human liver. Basic preprocessing and the B‐matrix spatial distribution (BSD) method perform differently for off‐center and isocenter locations. In the human liver, they removed systematic bias of FA and MD by up to −63% and 11%, respectively. Visible variability of FA and MD among b‐value sets indicates the possibility of DTI sensitization to different liver compartments.
期刊介绍:
NMR in Biomedicine is a journal devoted to the publication of original full-length papers, rapid communications and review articles describing the development of magnetic resonance spectroscopy or imaging methods or their use to investigate physiological, biochemical, biophysical or medical problems. Topics for submitted papers should be in one of the following general categories: (a) development of methods and instrumentation for MR of biological systems; (b) studies of normal or diseased organs, tissues or cells; (c) diagnosis or treatment of disease. Reports may cover work on patients or healthy human subjects, in vivo animal experiments, studies of isolated organs or cultured cells, analysis of tissue extracts, NMR theory, experimental techniques, or instrumentation.