@article {954, title = {Moment-based representation of the diffusion inside the brain from reduced DMRI acquisitions: Generalized AMURA}, journal = {Medical Image Analysis}, volume = {77}, year = {2022}, pages = {102356}, abstract = {

AMURA (Apparent Measures Using Reduced Acquisitions) was originally proposed as a method to infer micro-structural information from single-shell acquisitions in diffusion MRI. It reduces the number of samples needed and the computational complexity of the estimation of diffusion properties of tissues by assuming the diffusion anisotropy is roughly independent on the b-value. This simplification allows the computation of simplified expressions and makes it compatible with standard acquisition protocols commonly used even in clinical practice. The present work proposes an extension of AMURA that allows the calculation of general moments of the diffusion signals that can be applied to describe the diffusion process with higher accuracy. We provide simplified expressions to analytically compute a set of scalar indices as moments of arbitrary orders over either the whole 3-D space, particular directions, or particular planes. The existing metrics previously proposed for AMURA (RTOP, RTPP and RTAP) are now special cases of this generalization. An extensive set of experiments is performed on public data and a clinical clase acquired with a standard type acquisition. The new metrics provide additional information about the diffusion processes inside the brain.

}, keywords = {AMURA, Diffusion anisotropy, Fast acquisition, diffusion MRI, white matter}, issn = {1361-8415}, doi = {https://doi.org/10.1016/j.media.2022.102356}, url = {https://www.sciencedirect.com/science/article/pii/S1361841522000093}, author = {Aja-Fern{\'a}ndez, Santiago and Pieciak, Tomasz and Mart{\'\i}n-Mart{\'\i}n, Carmen and {\'A}lvaro Planchuelo-G{\'o}mez and de Luis-Garc{\'\i}a, Rodrigo and Trist{\'a}n-Vega, Antonio} } @article {943, title = {Medium-term changes in patients with epilepsy during the COVID-19 pandemic}, journal = {Acta Neurologica Scandinavica}, volume = {144}, year = {2021}, pages = {450-459}, abstract = {

Objectives: The novel coronavirus disease (COVID-19) pandemic has led to social distancing measures and impaired medical care of chronic neurological diseases, including epilepsy, which may have adversely affected well-being and quality of life of patients with epilepsy (PWE). The objective of this study is to evaluate the impact of the COVID-19 pandemic in the levels of anxiety, depression, somnolence, and quality of life using validated scales in PWE in real-life clinical practice.

Materials \& Methods: Self-administered scales of anxiety disorders (GAD-7), depression (NDDI-E), somnolence (Epworth Sleepiness Scale; ESS), and quality of life (QOLIE-31-P) in PWE treated in a Refractory Epilepsy Unit were longitudinally analyzed. Data were collected before the beginning (December 2019-March 2020) and during the COVID-19 pandemic (September 2020-January 2021).

Results: 158 patients (85 from the first round and 73 from the second round) 45.0 +- 17.3 years of age, 43.2\% women, epilepsy duration 23.0 +- 14.9 years, number of antiepileptic drugs 2.1 +- 1.4, completed the survey. Significant longitudinal reduction of QOLIE-31-P (from 58.9 +- 19.7 to 56.2 +- 16.2, p = 0.035) and GAD-7 scores (from 8.8 +- 6.2 to 8.3 +- 5.9, corrected p = .024) was identified. No statistically significant longitudinal changes in the number of seizures (from 0.9 +- 1.9 to 2.5 +- 6.2, p = .125) or NDDI-E scores (from 12.3 +- 4.3 to 13.4 +- 4.4, p = .065) were found. Significant longitudinal increase of ESS (from 4.9 +- 3.7 to 7.4 +- 4.9, p = .001) was found.

Conclusions: During the COVID-19 pandemic, quality of life and anxiety levels were lower in PWE, and sleepiness levels were raised, without seizure change.

}, keywords = {Anxiety, COVID-19, Sleep, epilepsy, pandemic, quality of life}, doi = {https://doi.org/10.1111/ane.13481}, url = {https://onlinelibrary.wiley.com/doi/abs/10.1111/ane.13481}, author = {Gonzalez-Martinez, Alicia and {\'A}lvaro Planchuelo-G{\'o}mez and Vieira Campos, Alba and Mart{\'\i}nez-Dubarbie, Francisco and Vivancos, Jos{\'e} and De Toledo-Heras, Mar{\'\i}a} } @article {907, title = {Multimodal fusion analysis of structural connectivity and gray matter morphology in migraine}, journal = {Human Brain Mapping}, volume = {42}, year = {2021}, pages = {908-921}, abstract = {

No specific migraine biomarkers have been found in single-modality MRI studies. We aimed at establishing biomarkers for episodic and chronic migraine using diverse MRI modalities. We employed canonical correlation analysis and joint independent component analysis to find structural connectivity abnormalities that are related to gray matter morphometric alterations. The number of streamlines (trajectories of estimated fiber-tracts from tractography) was employed as structural connectivity measure, while cortical curvature, thickness, surface area, and volume were used as gray matter parameters. These parameters were compared between 56 chronic and 54 episodic migraine patients, and 50 healthy controls. Cortical curvature alterations were associated with abnormalities in the streamline count in episodic migraine patients compared to controls, with higher curvature values in the frontal and temporal poles being related to a higher streamline count. Lower streamline count was found in migraine compared to controls in connections between cortical regions within each of the four lobes. Higher streamline count was found in migraine in connections between subcortical regions, the insula, and the cingulate and orbitofrontal cortex, and between the insula and the temporal region. The connections between the caudate nucleus and the orbitofrontal cortex presented worse connectivity in chronic compared to episodic migraine. The hippocampus was involved in connections with higher and lower number of streamlines in chronic migraine. Strengthening of structural networks involving pain processing and subcortical regions coexists in migraine with weakening of cortical networks within each lobe. The multimodal analysis offers a new insight about the association between brain structure and connectivity.

}, keywords = {Brain, Magnetic Resonance Imaging, connectome, diffusion magnetic resonance imaging, migraine disorders}, doi = {https://doi.org/10.1002/hbm.25267}, url = {https://onlinelibrary.wiley.com/doi/abs/10.1002/hbm.25267}, author = {{\'A}lvaro Planchuelo-G{\'o}mez and Garc{\'\i}a-Azor{\'\i}n, David and {\'A}ngel L. Guerrero and Santiago Aja-Fern{\'a}ndez and Rodr{\'\i}guez, Margarita and Rodrigo de Luis-Garc{\'\i}a} }