Toward an optimal distribution of b values for intravoxel incoherent motion imaging

Liver intravoxel incoherent motion (IVIM) magnetic resonance imaging: a comprehensive review of published data on normal values and applications for fibrosis and tumor evaluation

“…Including more b values and applying an optimized b value distribution reduces errors in the IVIM parameter estimates (16,34,49 (34). In ter Voert's study, the imaging time for IVIM was 5 to 6 minutes which is clinically acceptable.…”

“…A prerequisite to translating the growing interest in IVIM imaging into clinical applications is its accurate measurement of normative value of IVIM parameters and acceptable reproducibility across different clinical settings (13,14). Nevertheless, accurate IVIM quantification is challenging, partially due to the limited sampling and low signal-to-noise ratio (SNR) for fast data acquisition of the liver (15)(16)(17). Even in the brain, where there is almost no motion effect, the cross-center agreement has been recently shown to be sub-optimal.…”

Comparison of methods for estimation of the intravoxel incoherent motion (IVIM) diffusion coefficient (D) and perfusion fraction (f)

“…Because of the characteristics of the IVIM model and typical values of its parameters, estimating D* has proved to be difficult, demanding high-quality data and, as a result, long examination times [11]. Therefore, estimating only D and f has been employed in several recent studies [12][13][14].…”

Are we ready to image the incoherent molecular motion in our minds?

“…The preliminary evidence suggests that f is indeed lower in infarcted tissue [9] but the measurements of the flowrelated parameters are notoriously affected by the fitting process (full vs. asymptotic fitting) and thus, it is expected that any mismatch map should be qualitatively rather than quantitatively appreciated. The strong dependence of the f deviations on the signal-to-noise ratio (SNR) is another inherent drawback and systematic errors in f estimation appear even at moderate SNR and are exacerbated during the full-fitting process [10,11]. Specifically, the full-fitting procedure may overestimate f due to the inherent behavior of nonlinear least squares fitting in the presence of substantial noise contribution.…”

“…Interactions between the imaging gradients and Stejskal-Tanner gradients could also modify the effective b value, especially the lower ones. Last but not least, a sufficient number (10-16) and an optimal distribution of the applied b values is mandatory for reliable parameter estimation [11,12].…”