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The impact of edema and fiber crossing on diffusion MRI metrics assessed in an ex vivo nerve phantom: Multi‐tensor model vs. diffusion orientation distribution function
Author(s) -
Ye Zezhong,
Gary Sam E.,
Sun Peng,
Mustafi Sourajit Mitra,
Glenn George Russell,
Yeh FangCheng,
Merisaari Harri,
Song Chunyu,
Yang Ruimeng,
Huang GuoShu,
Kao HungWen,
Lin ChienYuan,
Wu YuChien,
Jensen Jens H.,
Song ShengKwei
Publication year - 2021
Publication title -
nmr in biomedicine
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.278
H-Index - 114
eISSN - 1099-1492
pISSN - 0952-3480
DOI - 10.1002/nbm.4414
Subject(s) - diffusion mri , fractional anisotropy , imaging phantom , edema , anisotropy , biomedical engineering , nuclear magnetic resonance , materials science , magnetic resonance imaging , medicine , nuclear medicine , physics , radiology , optics , surgery
Diffusion tensor imaging (DTI) has been employed for over 2 decades to noninvasively quantify central nervous system diseases/injuries. However, DTI is an inadequate simplification of diffusion modeling in the presence of coexisting inflammation, edema and crossing nerve fibers. We employed a tissue phantom using fixed mouse trigeminal nerves coated with various amounts of agarose gel to mimic crossing fibers in the presence of vasogenic edema. Diffusivity measures derived by DTI and diffusion basis spectrum imaging (DBSI) were compared at increasing levels of simulated edema and degrees of fiber crossing. Furthermore, we assessed the ability of DBSI, diffusion kurtosis imaging (DKI), generalized q‐sampling imaging (GQI), q‐ball imaging (QBI) and neurite orientation dispersion and density imaging to resolve fiber crossing, in reference to the gold standard angles measured from structural images. DTI‐computed diffusivities and fractional anisotropy were significantly confounded by gel‐mimicked edema and crossing fibers. Conversely, DBSI calculated accurate diffusivities of individual fibers regardless of the extent of simulated edema and degrees of fiber crossing angles. Additionally, DBSI accurately and consistently estimated crossing angles in various conditions of gel‐mimicked edema when compared with the gold standard (r 2 = 0.92, P = 1.9 × 10 −9 , bias = 3.9°). Small crossing angles and edema significantly impact the diffusion orientation distribution function, making DKI, GQI and QBI less accurate in detecting and estimating fiber crossing angles. Lastly, we used diffusion tensor ellipsoids to demonstrate that DBSI resolves the confounds of edema and crossing fibers in the peritumoral edema region from a patient with lung cancer metastasis, while DTI failed. In summary, DBSI is able to separate two crossing fibers and accurately recover their diffusivities in a complex environment characterized by increasing crossing angles and amounts of gel‐mimicked edema. DBSI also indicated better angular resolution compared with DKI, QBI and GQI.