Linearization improves the repeatability of quantitative Dynamic Contrast-Enhanced MRI

Abstract

2We studied the effect of linearization on the repeatability of the Tofts and reference 3 region models (RRM) for Dynamic Contrast-Enhanced MRI (DCE MRI). We compared the 4 repeatabilities of these two linearized models, the standard non-linear version, and semi-5 quantitative methods of analysis. to estimate K trans , while LRRM and NRRM were used to estimate K trans relative to muscle 13 (R Ktrans ). Repeatability was assessed by calculating the within-subject coefficient of variation 14 (wSCV) and the percent intra-subject variation (iSV) determined with the Gage repeatability and 15 reproducibility (R&R) analysis. 16The iSV for R Ktrans using LRRM was two-fold lower compared to NRRM at all simulated 17 and experimental conditions. A similar trend was observed for the Tofts model, where LTM was 18 at least 50% more repeatable than the NTM under all experimental and simulated conditions. 19The semi-quantitative metrics iauc64 and MER were as equally reproducible as K trans and R Ktrans 20 estimated by LTM and LRRM respectively. The iSV for iauc64 and MER were significantly 21 lower than the iSV for slope and TTP. 22In simulations and experimental results, linearization improves the repeatability of 23 quantitative DCE MRI by at least 30%, making it as repeatable as semi-quantitative metrics.

Improved repeatability of dynamic contrast‐enhanced MRI using the complex MRI signal to derive arterial input functions: a test‐retest study in prostate cancer patients

“…Given that repeatability not only depends on the choice of AIF, but, for example, also on the model, field strength, acquisition protocol, and location of ROI, it is difficult to compare our wCV data directly to existing literature. However, in general, the reported wCV of K trans in ROIs is higher than what we observed for K trans obtained with AIF COMPLEX (range, 12.5–57%) . Rata et al reported a lower wCV of 7.5% when using a population AIF in a group of patients with abdominal tumors.…”

Simultaneously spatial and temporal higher-order total variations for noise suppression and motion reduction in DCE and IVIM

“…The DCE/IVIM maps are retrieved on the reconstructed signals with HOTVs. We implement a linear DCE solver to significantly boost the speed of parameter estimation while preserving the consistency and repeatability against initial estimations [55,56,57]. A Segmented-Unconstrained algorithm, which is likely the most frequently used algorithm in IVIM analysis [58,59], is adopted in our demonstration section below.…”

“…Subsequently, we implemented the linear leastsquares method to acquire the PK parameters. [56,57]. This method is preferred to the conventional nonlinear least-squares method [1], because it is faster and it does not require initial estimation, and has no local optima problems.…”

“…However, with the original data, it's impossible to generate acceptable parametric maps by conventional DCE mapping algorithms. While with the improved reconstruction of MRI frame time series and using standardized AIF [57], it's still possible for conventional DCE mapping algorithms to be able to generate parametric maps with reasonable quality. (d) are after filtering.…”

Prospective assessment of DCE-MRI parameters associated with advanced mandibular osteoradionecrosis after IMRT for head and neck cancer

“…25 Subsequently, we implemented the linear least-squares method to acquire the PK parameters. 25,26 This method is preferred to the conventional nonlinear least-squares method 24 , because it is faster and it does not require initial estimation, and has no local optima problems.…”