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BackgroundSudden unexpected death in epilepsy (SUDEP) is common among young people with epilepsy. Individuals who are at high risk of SUDEP exhibit regional brain structural and functional connectivity (FC) alterations compared with low-risk patients. However, less is known about network-based FC differences among critical cortical and subcortical autonomic regulatory brain structures in temporal lobe epilepsy (TLE) patients at high risk of SUDEP.Methods32 TLE patients were risk-stratified according to the following clinical criteria: age of epilepsy onset, duration of epilepsy, frequency of generalized tonic-clonic seizures, and presence of nocturnal seizures, resulting in 14 high-risk and 18 low-risk cases. Resting-state functional magnetic resonance imaging (rs-fMRI) signal time courses were extracted from 11 bilateral cortical and subcortical brain regions involved in autonomic and other regulatory processes. After computing all pairwise correlations, FC matrices were analyzed using the network-based statistic. FC strength among the 11 brain regions was compared between the high- and low-risk patients. Increases and decreases in FC were sought, using high-risk > low-risk and low-risk > high-risk contrasts (with covariates age, gender, lateralization of epilepsy, and presence of hippocampal sclerosis).ResultsHigh-risk TLE patients showed a subnetwork with significantly reduced FC (t = 2.5, p = 0.029) involving the thalamus, brain stem, anterior cingulate, putamen and amygdala, and a second subnetwork with significantly elevated FC (t = 2.1, p = 0.031), which extended to medial/orbital frontal cortex, insula, hippocampus, amygdala, subcallosal cortex, brain stem, thalamus, caudate, and putamen.ConclusionTLE patients at high risk of SUDEP showed widespread FC differences between key autonomic regulatory brain regions compared to those at low risk. The altered FC revealed here may help to shed light on the functional correlates of autonomic disturbances in epilepsy and mechanisms involved in SUDEP. Furthermore, these findings represent possible objective biomarkers which could help to identify high-risk patients and enhance SUDEP risk stratification via the use of non-invasive neuroimaging, which would require validation in larger cohorts, with extension to patients with other epilepsies and subjects who succumb to SUDEP.

Purpose: To develop a new sequence to simultaneously acquire Cartesian sodium (23Na) MRI and accelerated Cartesian single (SQ) and triple quantum (TQ) sodium MRI of in vivo human brain at 7 T by leveraging two dedicated low‐rank reconstruction frameworks. Theory and Methods: The Double Half‐Echo technique enables short echo time Cartesian 23Na MRI and acquires two k‐space halves, reconstructed by a low‐rank coupling constraint. Additionally, three‐dimensional (3D) 23Na Multi‐Quantum Coherences (MQC) MRI requires multi‐echo sampling paired with phase‐cycling, exhibiting a redundant multidimensional space. Simultaneous Autocalibrating and k‐Space Estimation (SAKE) were used to reconstruct highly undersampled 23Na MQC MRI. Reconstruction performance was assessed against five‐dimensional (5D) CS, evaluating structural similarity index (SSIM), root mean squared error (RMSE), signal‐to‐noise ratio (SNR), and quantification of tissue sodium concentration and TQ/SQ ratio in silico, in vitro, and in vivo. Results: The proposed sequence enabled the simultaneous acquisition of fully sampled 23Na MRI while leveraging prospective undersampling for 23Na MQC MRI. SAKE improved TQ image reconstruction regarding SSIM by 6% and reduced RMSE by 35% compared to 5D CS in vivo. Thanks to prospective undersampling, the spatial resolution of 23Na MQC MRI was enhanced from 8×8×15$$ 8\times 8\times 15 $$ mm3 to 8×8×8$$ 8\times 8\times 8 $$ mm3 while reducing acquisition time from 2×31$$ 2\times 31 $$ min to 2×23$$ 2\times 23 $$ min. Conclusion: The proposed sequence, coupled with low‐rank reconstructions, provides an efficient framework for comprehensive whole‐brain sodium MRI, combining TSC, T2*, and TQ/SQ ratio estimations. Additionally, low‐rank matrix completion enables the reconstruction of highly undersampled 23Na MQC MRI, allowing for accelerated acquisition or enhanced spatial resolution. [ABSTRACT FROM AUTHOR]

Purpose: To propose a standardized comparison between state‐of‐the‐art open‐source fat‐water separation algorithms for proton density fat fraction (PDFF) and R2*$$ {R}_2^{\ast } $$ quantification using an open‐source multi‐language toolbox. Methods: Eight recent open‐source fat‐water separation algorithms were compared in silico, in vitro, and in vivo. Multi‐echo data were synthesized with varying fat‐fractions, B0 off‐resonance, SNR and TEs. Experimental evaluation was conducted using calibrated fat‐water phantoms acquired at 3T and multi‐site open‐source phantoms data. Algorithms' performances were observed on challenging in vivo datasets at 3T. Finally, reconstruction algorithms were investigated with different fat spectra to evaluate the importance of the fat model. Results: In silico and in vitro results proved most algorithms to be not sensitive to fat‐water swaps and B0$$ {\mathrm{B}}_0 $$ offsets with five or more echoes. However, two methods remained inaccurate even with seven echoes and SNR = 50, and two other algorithms' precision depended on the echo spacing scheme (p < 0.05). The remaining four algorithms provided reliable performances with limits of agreement under 2% for PDFF and 6 s−1 for R2*$$ {R}_2^{\ast } $$. The choice of fat spectrum model influenced quantification of PDFF mildly (<2% bias) and of R2*$$ {R}_2^{\ast } $$ more severely, with errors up to 20 s−1. Conclusion: In promoting standardized comparisons of MRI‐based fat and iron quantification using chemical‐shift encoded multi‐echo methods, this benchmark work has revealed some discrepancies between recent approaches for PDFF and R2*$$ {R}_2^{\ast } $$ mapping. Explicit choices and parameterization of the fat‐water algorithm appear necessary for reproducibility. This open‐source toolbox further enables the user to optimize acquisition parameters by predicting algorithms' margins of errors. [ABSTRACT FROM AUTHOR]

Purpose: The acquisition of accurate B1 maps is critical for parallel transmit techniques (pTx). The presaturated turboFLASH (satTFL) method has been widely used in combination with interferometric encoding to provide robust and fast B1 maps. However, typical encodings, mostly evaluated on brain, do not necessarily fit all coils and organs. In this work, we evaluated and improved the accuracy of the satTFL for cervical spine at 7 T, proposing a novel interferometric encoding optimization. The benefits of such improvements were investigated in an exploratory study of quantitative T1 mapping with pTx‐MP2RAGE. Methods: Global optimization of interferometric encoding was implemented by simulating the ability of the satTFL to reconstruct B1 maps, with varying encoding and inclusion of complex noise, inside a region of interest covering the cervical spine. The performance of satTFL before and after optimization was compared to actual flip angle imaging. Optimized and non‐optimized B1 maps were then used to calculate pTx pulses for MP2RAGE T1 mapping. Results: Interferometric encoding optimization resulted in satTFL closer to actual flip angle imaging, with substantial gain of signal in regions where non‐optimized satTFL could fail. T1 maps measured with non‐adiabatic pTx pulses were closer to standard non‐pTx results (which used adiabatic pulses) when using optimized‐satTFL, with substantially lower specific absorption rate. Conclusion: Optimization of the satTFL interferometric encoding improves B1 maps in the spinal cord, in particular in low SNR regions. A linear correction of the satTFL was additionally shown to be required. The method was successfully used for quantitative phantom and in vivo T1 mapping, showing improved results compared to non‐optimized satTFL thanks to improved pTx‐pulse generation. [ABSTRACT FROM AUTHOR]