Extended T2-IVIM model for correction of TE dependence of pseudo-diffusion volume fraction in clinical diffusion-weighted magnetic resonance imaging.

The bi-exponential intravoxel-incoherent-motion (IVIM) model for diffusion-weighted MRI (DWI) fails to account for differential T 2 s in the model compartments, resulting in overestimation of pseudodiffusion fraction f. An extended model, T2-IVIM, allows removal of the confounding echo-time (TE) dependence of f, and provides direct compartment T 2 estimates. Two consented healthy volunteer cohorts (n = 5, 6) underwent DWI comprising multiple TE/b-value combinations (Protocol 1: TE = 62-102 ms, b = 0-250 mm-2s, 30 combinations. Protocol 2: 8 b-values 0-800 mm-2s at TE = 62 ms, with 3 additional b-values 0-50 mm-2s at TE = 80, 100 ms; scanned twice). Data from liver ROIs were fitted with IVIM at individual TEs, and with the T2-IVIM model using all data. Repeat-measures coefficients of variation were assessed for Protocol 2. Conventional IVIM modelling at individual TEs (Protocol 1) demonstrated apparent f increasing with longer TE: 22.4 ± 7% (TE = 62 ms) to 30.7 ± 11% (TE = 102 ms); T2-IVIM model fitting accounted for all data variation. Fitting of Protocol 2 data using T2-IVIM yielded reduced f estimates (IVIM: 27.9 ± 6%, T2-IVIM: 18.3 ± 7%), as well as T 2 = 42.1 ± 7 ms, 77.6 ± 30 ms for true and pseudodiffusion compartments, respectively. A reduced Protocol 2 dataset yielded comparable results in a clinical time frame (11 min). The confounding dependence of IVIM f on TE can be accounted for using additional b/TE images and the extended T2-IVIM model.

Use of the temporal median and trimmed mean mitigates effects of respiratory motion in multiple-acquisition abdominal diffusion imaging.

Respiratory motion commonly confounds abdominal diffusion-weighted magnetic resonance imaging, where averaging of successive samples at different parts of the respiratory cycle, performed in the scanner, manifests the motion as blurring of tissue boundaries and structural features and can introduce bias into calculated diffusion metrics. Storing multiple averages separately allows processing using metrics other than the mean; in this prospective volunteer study, median and trimmed mean values of signal intensity for each voxel over repeated averages and diffusion-weighting directions are shown to give images with sharper tissue boundaries and structural features for moving tissues, while not compromising non-moving structures. Expert visual scoring of derived diffusion maps is significantly higher for the median than for the mean, with modest improvement from the trimmed mean. Diffusion metrics derived from mono- and bi-exponential diffusion models are comparable for non-moving structures, demonstrating a lack of introduced bias from using the median. The use of the median is a simple and computationally inexpensive alternative to complex and expensive registration algorithms, requiring only additional data storage (and no additional scanning time) while returning visually superior images that will facilitate the appropriate placement of regions-of-interest when analysing abdominal diffusion-weighted magnetic resonance images, for assessment of disease characteristics and treatment response.