@conference {939, title = {Resting-state functional alterations in patients with persistent headache after COVID-19 infection: an exploratory study}, booktitle = {International Headache Congress 2021}, year = {2021}, month = {2021}, publisher = {International Headache Society \& European Headache Federation}, organization = {International Headache Society \& European Headache Federation}, address = {Virtual Congress}, abstract = {
Objective: To evaluate resting-state functional alterations in patients with persistent headache after COVID-19 resolution.
Methods: Exploratory case-control study. Highresolution brain resting-state functional Magnetic Resonance Imaging data were acquired in patients with
persistent headache after COVID-19 infection and healthy controls (HC). CONN toolbox (version 17) was employed to assess the resting-state functional connectivity between 84 cortical and subcortical gray matter regions of interest. Significant results were considered with p \< 0.05 (Family Discovery Rate and seed-level corrected).
Results: Ten patients with persistent headache after COVID-19 (mean age: 53.8 +- 7.8 years; nine women) and 10 HC balanced for age and sex (mean age: 51.9 +- 6.6 years; nine women) were included in the study. Statistically significant higher functional connectivity was observed in the patients with persistent headache compared to HC in 10 connections. These connections were composed of an occipital region and another region that included the isthmus cingulate gyrus, a frontal or a parietal area. In the patients, significant lower functional connectivity was found in 12 connections between the cingulate and hippocampal gyri, parietal, temporal and frontal regions.
Conclusions: Patients with persistent headache after COVID-19 infection present strengthened functional connectivity with occipital regions and weakened functional connectivity between frontal, temporal and parietal regions.
Diffusion-Weighted MRI (DW-MRI) often suffers from signal attenuation due to long TE, motion-related artefacts, dephasing due to concomitant gradients (CGs), and image distortions due to eddy currents (ECs). Further, the application of rapidly switching gradients may cause peripheral nerve stimulation (PNS). These challenges hinder the progress, application and interpretability of DW-MRI. Therefore, based on the Optimized Diffusion-weighting Gradient waveforms Design (ODGD) formulation, in this work we design optimal (minimum TE) nth-order moment-nulling diffusion-weighting gradient waveforms with or without CG-nulling able to reduce EC induced distortions and PNS-effects. We assessed the feasibility of these waveforms in simulations and phantom experiments.
}, author = {{\'O}scar Pe{\~n}a-Nogales and Yuxin Zhang and Rodrigo de Luis-Garc{\'\i}a and Santiago Aja-Fern{\'a}ndez and James H. Holmes and Diego Hernando} } @inbook {818, title = {Return-to-Axis Probability Calculation from Single-Shell Acquisitions}, booktitle = {Computational Diffusion MRI}, year = {2019}, pages = {29-41}, publisher = {Springer}, organization = {Springer}, isbn = {978-3-030-05830-2}, doi = {10.1007/978-3-030-05831-9_3}, author = {Santiago Aja-Fern{\'a}ndez and Antonio Trist{\'a}n-Vega and Molendowska, Malwina and Tomasz Pieciak and Luis-Garc{\'\i}a, Rodrigo} } @proceedings {759, title = {Return-to-the-origin probability calculation in single shell acquisitions}, year = {2018}, pages = {1414}, address = {Paris, France}, author = {Santiago Aja-Fern{\'a}ndez and Antonio Trist{\'a}n-Vega and Malwina Molendowska and Tomasz Pieciak and Rodrigo de Luis-Garc{\'\i}a} } @article {779, title = {Robust Estimation of the Apparent Diffusion Coefficient Invariant to Acquisition Noise and Physiological Motion}, journal = {Magnetic Resonance Imaging}, volume = {53}, year = {2018}, pages = {123-133}, abstract = {In this work we have proposed a methodology for the estimation of the apparent diffusion coefficient in the body from multiple breath hold diffusion weighted images, which is robust to two preeminent confounding factors: noise and motion during acquisition. We have extended a method for the joint groupwise multimodal registration and apparent diffusion coefficient estimation, previously proposed by the authors, in order to correct the bias that arises from the non-Gaussianity of the data and the registration procedure. Results show that the proposed methodology provides a statistically significant improvement both in robustness for displacement fields calculation and in terms of accuracy for the apparent diffusion coefficient estimation as compared with traditional sequential approaches. Reproducibility has also been measured on real data in terms of the distribution of apparent diffusion coefficient differences obtained from different b-values subsets. Our proposal has shown to be able to effectively correct the estimation bias by introducing additional computationally light procedures to the original method, thus providing robust apparent diffusion coefficient maps in the liver and allowing an accurate and reproducible analysis of the tissue.