Evaluating the Accuracy of Susceptibility Maps Calculated from Single-echo versus Multi-echo Gradient-echo Acquisitions

For Susceptibility Mapping (SM), Laplacian-based methods (LBMs) can be used on single- or multi-echo gradient echo phase data. Previous studies have shown the advantage of using multi-echo versus single-echo data for noise reduction in susceptibility-weighted images and simulated data. Here, using simulated and acquired images, we compared the performance of two SM pipelines that used multi- or single-echo phase data and LBMs. We showed that the pipeline that fits the multi-echo data over time first and then applies LBMs gives more accurate local fields and $\chi$ maps than the pipelines that apply LBMs to single-echo phase data

Manual delineation approaches for direct imaging of the subcortex

The growing interest in the human subcortex is accompanied by an increasing number of parcellation procedures to identify deep brain structures in magnetic resonance imaging (MRI) contrasts. Manual procedures continue to form the gold standard for parcellating brain structures and is used for the validation of automated approaches. Performing manual parcellations is a tedious process which requires a systematic and reproducible approach. For this purpose, we created a series of protocols for the anatomical delineation of 21 individual subcortical structures. The intelligibility of the protocols was assessed by calculating Dice similarity coefficients for ten healthy volunteers. In addition, dilated Dice coefficients showed that manual parcellations created using these protocols can provide high-quality training data for automated algorithms. Here, we share the protocols, together with three example MRI datasets and the created manual delineations. The protocols can be applied to create high-quality training data for automated parcellation procedures, as well as for further validation of existing procedures and are shared without restrictions with the research community.Action Contro