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The Bloch-Siegert (B-S) B1+ mapping technique is a fast, phase-based method that is highly SAR limited especially at 7T, necessitating the use of long repetition times. Spiral and echo-planar readouts were incorporated in a gradient-echo based B-S sequence to reduce specific absoprtion rate (SAR) and improve its scan efficiency. A novel, numerically optimized 4 ms B-S off-resonant pulse at + 1960 Hz was used to increase sensitivity and further reduce SAR compared with the conventional 6 ms Fermi B-S pulse. Using echo-planar and spiral readouts, scan time reductions of 8-16 were achieved. By reducing the B-S pulse width by a factor of 1.5, SAR was reduced by a factor of 1.5 and overall sensitivity was increased by a factor of 1.33 due to the nearly halved resonance offset of the new B-S pulse. This was validated on phantoms and volunteers at 7 T. Magn Reson Med 70:1669-1673, 2013. © 2013 Wiley Periodicals, Inc. [ABSTRACT FROM AUTHOR]

The medial temporal lobe (MTL) is the first brain area to succumb to neurofibrillary tau pathology in Alzheimer's disease (AD). Postmortem human tissue evaluation suggests that this pathology propagates in an ordered manner, with the entorhinal cortex (ERC) and then CA1 stratum radiatum and stratum lacunosum-moleculare (CA1-SRLM)--two monosynaptically connected structures--exhibiting selective damage. Here, we hypothesized that, if ERC and CA1-SRLM share an early vulnerability to AD pathology, then atrophy should occur in a proportional manner between the two structures. We tested this hypothesis in living humans, using ultra-high field 7.0 T MRI to make fine measurements of MTL microstructure. Among a pool of age-matched healthy controls and patients with amnestic mild cognitive impairment and mild AD, we found a significant correlation between ERC and CA1-SRLM size that could not be explained by global atrophy affecting the MTL. Of the various structures that contribute axons or dendrites into the CA1-SRLM neuropil, only ERC emerged as a significant predictor of CA1-SRLM size in a linear regression analysis. In contrast, other synaptically connected elements of the MTL did not exhibit size correlations. CA1-SRLM and ERC structural covariance was significant for older controls and not patients, whereas the opposite pattern emerged for a correlation between CA1-SRLM and episodic memory performance. Interestingly, CA1-SRLM and ERC were the only MTL structures to atrophy in older controls relative to a younger comparison group. Together, these findings suggest that ERC and CA1-SRLM share vulnerability to both age and AD-associated atrophy. [ABSTRACT FROM AUTHOR]

Purpose To present a new method that can simultaneously and efficiently measure T1 and B1+ maps using reference region variable flip angle (RR-VFA) imaging. Methods Assuming T1 relaxation time in a reference region such as fat is well characterized, and the reference region sufficiently covers smoothly varying B1+ field inhomogeneity, B1+ maps can be measured from VFA images, conventionally used for T1 measurements. Fat-only images from two-point Dixon acquisitions were used to compute B1+ maps, and the B1+ maps were compared with ones using the double-angle method (DAM) in 22 breast MRI patients at 3T. Additionally, high spatial resolution VFA images were acquired to show T1 measurements with and without the RR-VFA B1+ correction in six patients. Results RR-VFA is able to generate reliable B1+ maps, similar to those using the conventional DAM. This simultaneous T1 and B1+ mapping can also be used to reduce T1 estimation errors, where T1 maps have more uniform fibroglandular tissue T1 and better depiction of heterogeneous T1 of breast masses. Conclusion A new method that can measure both T1 and B1+ maps based on Dixon VFA images is described, offering improved T1 quantification with no scan time penalty. Magn Reson Med, 70:954-961, 2013. © 2013 Wiley Periodicals, Inc. [ABSTRACT FROM AUTHOR]

Alcohol use disorder (AUD) is widely associated with cerebellar dysfunction and altered cerebro-cerebellar functional connectivity (FC) that lead to cognitive impairments. Evidence for this association comes from resting-state functional magnetic resonance imaging (rsfMRI) studies that assess time-averaged measures of FC across the duration of a typical scan. This approach, however, precludes the assessment of potentially FC dynamics happening at faster timescales. In this study, using rsfMRI data, we aim at exploring cerebro-cerebellar FC dynamics in AUD patients (N = 18) and age- and sex-matched controls (N = 18). In particular, we quantified group-level differences in the temporal variability of FC between the posterior cerebellum and large-scale cognitive systems, and we investigated the role of the cerebellum in large-scale brain dynamics in terms of the temporal flexibility and integration of its regions. We found that, relative to controls, the AUD group exhibited significantly greater FC variability between the cerebellum and both the frontoparietal executive control (F1,31 = 7.01, p(FDR) = 0.028) and ventral attention (F1,31 = 7.35, p(FDR) = 0.028) networks. Moreover, the AUD group exhibited significantly less flexibility (F1,31 = 8.61, p(FDR) = 0.028) and greater integration (F1,31 = 9.11, p(FDR) = 0.028) in the cerebellum. Finally, in an exploratory analysis, we found distributed changes in the dynamics of canonical large-scale networks in AUD. Overall, this study brings evidence of AUD-related alterations in dynamic FC within major cerebro-cerebellar networks. This pattern has implications for explaining the development and maintenance of this disorder and improving our understating of the cerebellum's involvement in addiction. [ABSTRACT FROM AUTHOR]

To develop a fast and accurate convolutional neural network based method for segmentation of thalamic nuclei. A cascaded multi-planar scheme with a modified residual U-Net architecture was used to segment thalamic nuclei on conventional and white-matter-nulled (WMn) magnetization prepared rapid gradient echo (MPRAGE) data. A single network was optimized to work with images from healthy controls and patients with multiple sclerosis (MS) and essential tremor (ET), acquired at both 3 T and 7 T field strengths. WMn-MPRAGE images were manually delineated by a trained neuroradiologist using the Morel histological atlas as a guide to generate reference ground truth labels. Dice similarity coefficient and volume similarity index (VSI) were used to evaluate performance. Clinical utility was demonstrated by applying this method to study the effect of MS on thalamic nuclei atrophy. Segmentation of each thalamus into twelve nuclei was achieved in under a minute. For 7 T WMn-MPRAGE, the proposed method outperforms current state-of-the-art on patients with ET with statistically significant improvements in Dice for five nuclei (increase in the range of 0.05–0.18) and VSI for four nuclei (increase in the range of 0.05–0.19), while performing comparably for healthy and MS subjects. Dice and VSI achieved using 7 T WMn-MPRAGE data are comparable to those using 3 T WMn-MPRAGE data. For conventional MPRAGE, the proposed method shows a statistically significant Dice improvement in the range of 0.14–0.63 over FreeSurfer for all nuclei and disease types. Effect of noise on network performance shows robustness to images with SNR as low as half the baseline SNR. Atrophy of four thalamic nuclei and whole thalamus was observed for MS patients compared to healthy control subjects, after controlling for the effect of parallel imaging, intracranial volume, gender, and age (p < 0.004). The proposed segmentation method is fast, accurate, performs well across disease types and field strengths, and shows great potential for improving our understanding of thalamic nuclei involvement in neurological diseases. [ABSTRACT FROM AUTHOR]

The thalamus consists of several histologically and functionally distinct nuclei increasingly implicated in brain pathology and important for treatment, motivating the need for development of fast and accurate thalamic parcellation. The contrast between thalamic nuclei as well as between the thalamus and surrounding tissues is poor in T1- and T2-weighted magnetic resonance imaging (MRI), inhibiting efforts to date to segment the thalamus using standard clinical MRI. Automatic parcellation techniques have been developed to leverage thalamic features better captured by advanced MRI methods, including magnetization prepared rapid acquisition gradient echo (MP-RAGE), diffusion tensor imaging (DTI), and resting-state functional MRI (fMRI). Despite operating on fundamentally different image contrasts, these methods claim a high degree of agreement with the Morel stereotactic atlas of the thalamus. However, no comparison has been undertaken to compare the results of these disparate parcellation methods. We have implemented state-of-the-art structural-, diffusion-, and functional imaging-based thalamus parcellation techniques and used them on a single set of subjects. We present the first systematic qualitative and quantitative comparison of these methods. The results show that DTI parcellation agrees more with structural parcellation in the larger thalamic nuclei, while rsfMRI parcellation agrees more with structural parcellation in the smaller nuclei. Structural parcellation is the most accurate in the delineation of small structures such as the habenular, antero-ventral, and medial geniculate nuclei. [ABSTRACT FROM AUTHOR]

The process of storing recently encoded episodic mnestic traces so that they are available for subsequent retrieval is accompanied by specific brain functional connectivity (FC) changes. In this fMRI study, we examined the early processing of memories in twenty-eight healthy participants performing an episodic memory task interposed between two resting state sessions. Memory performance was assessed through a forced-choice recognition test after the scanning sessions. We investigated resting state system configuration changes via Independent Component Analysis by cross-modeling baseline resting state spatial maps onto the post-encoding resting state, and post-encoding resting state spatial maps onto baseline. We identified both persistent and plastic components of the overall brain functional configuration between baseline and post-encoding. While FC patterns within executive, default mode, and cerebellar circuits persisted from baseline to post-encoding, FC within the visual circuit changed. A significant session × performance interaction characterized medial temporal lobe and prefrontal cortex FC with the visual circuit, as well as thalamic FC within the executive control system. Findings reveal early-stage FC changes at the system-level subsequent to a learning experience and associated with inter-individual variation in memory performance. [ABSTRACT FROM AUTHOR]

Sleep disturbances and drug-resistant seizures significantly impact people with idiopathic generalized epilepsy (IGE). Thalamic deep brain stimulation (DBS) offers potential treatment, but its effect on sleep and seizure control needs clarification. In this study, we combined wearable sleep monitoring with electroencephalogram (EEG) confirmation to investigate the impact of nocturnal centromedian nucleus (CM) DBS parameters in a patient with drug-resistant IGE. We found that high-frequency (125 Hz) CM stimulation during sleep severely disrupted sleep macro architecture and exacerbated seizures. Conversely, switching to low-frequency (10 Hz) stimulation enhanced both sleep quality and seizure control. This study underscores the critical need to personalize DBS settings, tailoring them to individual patients' sleep patterns to maximize therapeutic benefits. While larger-scale trials are needed, our findings pave the way for patient-centric approaches to thalamic neuromodulation, offering a transformative path to improve treatment outcomes and quality of life for those with refractory epilepsy., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2024 Suresh, Chaitanya, Kachhvah, Vashin, Saranathan and Pati.)

Accurate segmentation of thalamic nuclei, crucial for understanding their role in healthy cognition and in pathologies, is challenging to achieve on standard T1-weighted (T1w) magnetic resonance imaging (MRI) due to poor image contrast. White-matter-nulled (WMn) MRI sequences improve intrathalamic contrast but are not part of clinical protocols or extant databases. In this study, we introduce histogram-based polynomial synthesis (HIPS), a fast preprocessing transform step that synthesizes WMn-like image contrast from standard T1w MRI using a polynomial approximation for intensity transformation. HIPS was incorporated into THalamus Optimized Multi-Atlas Segmentation (THOMAS) pipeline, a method developed and optimized for WMn MRI. HIPS-THOMAS was compared to a convolutional neural network (CNN)-based segmentation method and THOMAS modified for the use of T1w images (T1w-THOMAS). The robustness and accuracy of the three methods were tested across different image contrasts (MPRAGE, SPGR, and MP2RAGE), scanner manufacturers (PHILIPS, GE, and Siemens), and field strengths (3 T and 7 T). HIPS-transformed images improved intra-thalamic contrast and thalamic boundaries, and HIPS-THOMAS yielded significantly higher mean Dice coefficients and reduced volume errors compared to both the CNN method and T1w-THOMAS. Finally, all three methods were compared using the frequently travelling human phantom MRI dataset for inter- and intra-scanner variability, with HIPS displaying the least inter-scanner variability and performing comparably with T1w-THOMAS for intra-scanner variability. In conclusion, our findings highlight the efficacy and robustness of HIPS in enhancing thalamic nuclei segmentation from standard T1w MRI., (© 2024. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

Background: Previous studies have shown that thalamic and hippocampal neurodegeneration is associated with clinical decline in Multiple Sclerosis (MS). However, contributions of the specific thalamic nuclei and hippocampal subfields require further examination., Objective: Using 7 Tesla (7T) magnetic resonance imaging (MRI), we investigated the cross-sectional associations between functionally grouped thalamic nuclei and hippocampal subfields volumes and T1 relaxation times (T1-RT) and subsequent clinical outcomes in MS., Methods: High-resolution T1-weighted and T2-weighted images were acquired at 7T (n=31), preprocessed, and segmented using the Thalamus Optimized Multi Atlas Segmentation (THOMAS, for thalamic nuclei) and the Automatic Segmentation of Hippocampal Subfields (ASHS, for hippocampal subfields) packages. We calculated Pearson correlations between hippocampal subfields and thalamic nuclei volumes and T1-RT and subsequent multi-modal rater-determined and patient-reported clinical outcomes (∼2.5 years after imaging acquisition), correcting for confounders and multiple tests., Results: Smaller volume bilaterally in the anterior thalamus region correlated with worse performance in gait function, as measured by the Patient Determined Disease Steps (PDDS). Additionally, larger volume in most functional groups of thalamic nuclei correlated with better visual information processing and cognitive function, as measured by the Symbol Digit Modalities Test (SDMT). In bilateral medial and left posterior thalamic regions, there was an inverse association between volumes and T1-RT, potentially indicating higher tissue degeneration in these regions. We also observed marginal associations between the right hippocampal subfields (both volumes and T1-RT) and subsequent clinical outcomes, though they did not survive correction for multiple testing., Conclusion: Ultrahigh field MRI identified markers of structural damage in the thalamic nuclei associated with subsequently worse clinical outcomes in individuals with MS. Longitudinal studies will enable better understanding of the role of microstructural integrity in these brain regions in influencing MS outcomes., Competing Interests: Declaration of competing interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: Tamer S. Ibrahim reports financial support was provided by National Institutes of Health. Zongqi Xia reports financial support was provided by National Institutes of Health. Tales Santini reports financial support was provided by Coordination of Higher Education Personnel Improvement. If there are other authors, they declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier B.V. All rights reserved.)

Background and Objectives: Thalamic atrophy can be used as a proxy for neurodegeneration in multiple sclerosis (MS). Some data point toward thalamic nuclei that could be affected more than others. However, the dynamic of their changes during MS evolution and the mechanisms driving their differential alterations are still uncertain., Methods: We paired a large cohort of 1,123 patients with MS with the same number of healthy controls, all scanned with conventional 3D-T1 MRI. To highlight the main atrophic regions at the thalamic nuclei level, we validated a segmentation strategy consisting of deep learning-based synthesis of sequences, which were used for automatic multiatlas segmentation. Then, through a lifespan-based approach, we could model the dynamics of the 4 main thalamic nuclei groups., Results: All analyses converged toward a higher rate of atrophy for the posterior and medial groups compared with the anterior and lateral groups. We also demonstrated that focal MS white matter lesions were associated with atrophy of groups of nuclei when specifically located within the associated thalamocortical projections. The volumes of the most affected posterior group, but also of the anterior group, were better associated with clinical disability than the volume of the whole thalamus., Discussion: These findings point toward the thalamic nuclei adjacent to the third ventricle as more susceptible to neurodegeneration during the entire course of MS through potentiation of disconnection effects by regional factors. Because this information can be obtained even from standard T1-weighted MRI, this paves the way toward such an approach for future monitoring of patients with MS.

Alzheimer's disease (AD) is the most common cause of dementia worldwide. Increasing evidence points to the thalamus as an important hub in the clinical symptomatology of the disease, with the 'limbic thalamus' been described as especially vulnerable. In this work, we examined thalamic atrophy in early-onset AD (EOAD) and late-onset AD (LOAD) compared to young and old healthy controls (YHC and OHC, respectively) using a recently developed cutting-edge thalamic nuclei segmentation method. A deep learning variant of Thalamus Optimized Multi Atlas Segmentation (THOMAS) was used to parcellate 11 thalamic nuclei per hemisphere from T1-weighted MRI in 88 biomarker-confirmed AD patients (49 EOAD and 39 LOAD) and 58 healthy controls (41 YHC and 17 OHC) with normal AD biomarkers. Nuclei volumes were compared among groups using MANCOVA. Further, Pearson's correlation coefficient was computed between thalamic nuclear volume and cortical-subcortical regions, CSF tau levels, and neuropsychological scores. The results showed widespread thalamic nuclei atrophy in EOAD and LOAD compared to their respective healthy control groups, with EOAD showing additional atrophy in the centromedian and ventral lateral posterior nuclei compared to YHC. In EOAD, increased thalamic nuclei atrophy was associated with posterior parietal atrophy and worse visuospatial abilities, while LOAD thalamic nuclei atrophy was preferentially associated with medial temporal atrophy and worse episodic memory and executive function. Our findings suggest that thalamic nuclei may be differentially affected in AD according to the age at symptoms onset, associated with specific cortical-subcortical regions, CSF total tau and cognition., Competing Interests: The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: Albert Llado reports financial support was provided by 10.13039/501100004587Carlos III Health Institute. Mircea Balasa reports financial support was provided by 10.13039/501100004587Carlos III Health Institute. Michael Hornberger reports financial support was provided by Alzheimer's Research UK, Wellcome Trust. Neus Falgas reports financial support was provided by 10.13039/501100004587Carlos III Health Institute. Nuria Guillen reports financial support was provided by 10.13039/501100004587Carlos III Health Institute., (© 2023 The Authors.)

Objectives: Investigating differential vulnerability of thalamic nuclei in multiple sclerosis (MS)., Methods: In a secondary analysis of prospectively collected datasets, we pooled 136 patients with MS or clinically isolated syndrome and 71 healthy controls all scanned with conventional 3D-T1 and white-matter-nulled magnetization-prepared rapid gradient echo (WMn-MPRAGE) and tested for cognitive performance. T1-based thalamic segmentation was compared with the reference WMn-MPRAGE method. Volumes of thalamic nuclei were compared according to clinical phenotypes and cognitive profile., Results: T1- and WMn-MPRAGE provided comparable segmentations (0.84 ± 0.13 < volume-similarity-index < 0.95 ± 0.03). Medial and posterior thalamic groups were significantly more affected than anterior and lateral groups. Cognitive impairment related to volume loss of the anterior group., Conclusion: Thalamic nuclei closest to the third ventricle are more affected, with cognitive consequences.

Thalamic nuclei have been implicated in several neurological diseases. Thalamic nuclei parcellation from structural MRI is challenging due to poor intra-thalamic nuclear contrast while methods based on diffusion and functional MRI are affected by limited spatial resolution and image distortion. Existing multi-atlas based techniques are often computationally intensive and time-consuming. In this work, we propose a 3D convolutional neural network (CNN) based framework for thalamic nuclei parcellation using T1-weighted Magnetization Prepared Rapid Gradient Echo (MPRAGE) images. Transformation of images to an efficient representation has been proposed to improve the performance of subsequent classification tasks especially when working with limited labeled data. We investigate this by transforming the MPRAGE images to White-Matter-nulled MPRAGE (WMn-MPRAGE) contrast, previously shown to exhibit good intra-thalamic nuclear contrast, prior to the segmentation step. We trained two 3D segmentation frameworks using MPRAGE images (n = 35 subjects): (a) a native contrast segmentation (NCS) on MPRAGE images and (b) a synthesized contrast segmentation (SCS) where synthesized WMn-MPRAGE representation generated by a contrast synthesis CNN were used. Thalamic nuclei labels were generated using THOMAS, a multi-atlas segmentation technique proposed for WMn-MPRAGE images. The segmentation accuracy and clinical utility were evaluated on a healthy cohort (n = 12) and a cohort (n = 45) comprising of healthy subjects and patients with alcohol use disorder (AUD), respectively. Both the segmentation CNNs yielded comparable performances on most thalamic nuclei with Dice scores greater than 0.84 for larger nuclei and at least 0.7 for smaller nuclei. However, for some nuclei, the SCS CNN yielded significant improvements in Dice scores (medial geniculate nucleus, P = 0.003, centromedian nucleus, P = 0.01) and percent volume difference (ventral anterior, P = 0.001, ventral posterior lateral, P = 0.01) over NCS. In the AUD cohort, the SCS CNN demonstrated a significant atrophy in ventral lateral posterior nucleus in AUD patients compared to healthy age-matched controls (P = 0.01), agreeing with previous studies on thalamic atrophy in alcoholism, whereas the NCS CNN showed spurious atrophy of the ventral posterior lateral nucleus. CNN-based segmentation of thalamic nuclei provides a fast and automated technique for thalamic nuclei prediction in MPRAGE images. The transformation of images to an efficient representation, such as WMn-MPRAGE, can provide further improvements in segmentation performance., (© 2021. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.)

The extant literature supports the involvement of the thalamus in the cognitive and motor impairment associated with chronic alcohol consumption, but clear structure/function relationships remain elusive. Alcohol effects on specific nuclei rather than the entire thalamus may provide the basis for differential cognitive and motor decline in Alcohol Use Disorder (AUD). This functional MRI (fMRI) study was conducted in 23 abstinent individuals with AUD and 27 healthy controls to test the hypothesis that functional connectivity between anterior thalamus and hippocampus would be compromised in those with an AUD diagnosis and related to mnemonic deficits. Functional connectivity between 7 thalamic structures [5 thalamic nuclei: anterior ventral (AV), mediodorsal (MD), pulvinar (Pul), ventral lateral posterior (VLP), and ventral posterior lateral (VPL); ventral thalamus; the entire thalamus] and 14 "functional regions" was evaluated. Relative to controls, the AUD group exhibited different VPL-based functional connectivity: an anticorrelation between VPL and a bilateral middle temporal lobe region observed in controls became a positive correlation in the AUD group; an anticorrelation between the VPL and the cerebellum was stronger in the AUD than control group. AUD-associated altered connectivity between anterior thalamus and hippocampus as a substrate of memory compromise was not supported; instead, connectivity differences from controls selective to VPL and cerebellum demonstrated a relationship with impaired balance. These preliminary findings support substructure-level evaluation in future studies focused on discerning the role of the thalamus in AUD-associated cognitive and motor deficits., (Copyright © 2021 Elsevier B.V. All rights reserved.)

The Bloch-Siegert (B-S) B1 (+) mapping technique is a fast, phase-based method that is highly SAR limited especially at 7T, necessitating the use of long repetition times. Spiral and echo-planar readouts were incorporated in a gradient-echo based B-S sequence to reduce specific absoprtion rate (SAR) and improve its scan efficiency. A novel, numerically optimized 4 ms B-S off-resonant pulse at + 1960 Hz was used to increase sensitivity and further reduce SAR compared with the conventional 6 ms Fermi B-S pulse. Using echo-planar and spiral readouts, scan time reductions of 8-16 were achieved. By reducing the B-S pulse width by a factor of 1.5, SAR was reduced by a factor of 1.5 and overall sensitivity was increased by a factor of 1.33 due to the nearly halved resonance offset of the new B-S pulse. This was validated on phantoms and volunteers at 7 T., (Copyright © 2013 Wiley Periodicals, Inc.)