Modifications of pancreatic diffusion MRI by tissue characteristics: what are we weighting for?

Noam Nissan

doi:10.1002/nbm.3728

Modifications of pancreatic diffusion MRI by tissue characteristics: what are we weighting for?

NMR in Biomedicine ◽

10.1002/nbm.3728 ◽

2017 ◽

Vol 30 (8) ◽

pp. e3728 ◽

Cited By ~ 5

Author(s):

Noam Nissan

Keyword(s):

Diffusion Mri ◽

Tissue Characteristics

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Effects of Multi-Shell Free Water Correction on Glioma Characterization

Diagnostics ◽

10.3390/diagnostics11122385 ◽

2021 ◽

Vol 11 (12) ◽

pp. 2385

Author(s):

Lea Starck ◽

Fulvio Zaccagna ◽

Ofer Pasternak ◽

Ferdia A. Gallagher ◽

Renate Grüner ◽

...

Keyword(s):

Diffusion Mri ◽

Free Water ◽

Diagnostic Value ◽

Cancer Heterogeneity ◽

Necrotic Tumor ◽

Treatment Naïve ◽

Corrected Data ◽

Mean And Variance ◽

Tissue Characteristics

Diffusion MRI is a useful tool to investigate the microstructure of brain tumors. However, the presence of fast diffusing isotropic signals originating from non-restricted edematous fluids, within and surrounding tumors, may obscure estimation of the underlying tissue characteristics, complicating the radiological interpretation and quantitative evaluation of diffusion MRI. A multi-shell regularized free water (FW) elimination model was therefore applied to separate free water from tissue-related diffusion components from the diffusion MRI of 26 treatment-naïve glioma patients. We then investigated the diagnostic value of the derived measures of FW maps as well as FW-corrected tensor-derived maps of fractional anisotropy (FA). Presumed necrotic tumor regions display greater mean and variance of FW content than other parts of the tumor. On average, the area under the receiver operating characteristic (ROC) for the classification of necrotic and enhancing tumor volumes increased by 5% in corrected data compared to non-corrected data. FW elimination shifts the FA distribution in non-enhancing tumor parts toward higher values and significantly increases its entropy (p ≤ 0.003), whereas skewness is decreased (p ≤ 0.004). Kurtosis is significantly decreased (p < 0.001) in high-grade tumors. In conclusion, eliminating FW contributions improved quantitative estimations of FA, which helps to disentangle the cancer heterogeneity.

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