Brain tissue segmentation based on MP2RAGE multi-contrast images in 7 T MRI

Cylindrical TGR as early radiological predictor of RLT progression in GEPNETs: a proof of concept

This study aims to assess the predictive capability of cylindrical Tumor Growth Rate (cTGR) in the prediction of early progression of well-differentiated gastro-entero-pancreatic tumours after Radio Ligand Therapy (RLT), compared to the conventional TGR. Fifty-eight patients were included and three CT scans per patient were collected at baseline, during RLT, and follow-up. RLT response, evaluated at follow-up according to RECIST 1.1, was calculated as a percentage variation of lesion diameters over time (continuous values) and as four different RECIST classes. TGR between baseline and interim CT was computed using both conventional (approximating lesion volume to a sphere) and cylindrical (called cTGR, approximating lesion volume to an elliptical cylinder) formulations. Receiver Operating Characteristic (ROC) curves were employed for Progressive Disease class prediction, revealing that cTGR outperformed conventional TGR (area under the ROC equal to 1.00 and 0.92, respectively). Multivariate analysis confirmed the superiority of cTGR in predicting continuous RLT response, with a higher coefficient for cTGR (1.56) compared to the conventional one (1.45). This study serves as a proof of concept, paving the way for future clinical trials to incorporate cTGR as a valuable tool for assessing RLT response.

Connectome-based schizophrenia prediction using structural connectivity - Deep Graph Neural Network(sc-DGNN)

Background

Connectome is understanding the complex organization of the human brain's structural and functional connectivity is essential for gaining insights into cognitive processes and disorders.

Objective

To improve the prediction accuracy of brain disorder issues, the current study investigates dysconnected subnetworks and graph structures associated with schizophrenia.

Method

By using the proposed structural connectivity-deep graph neural network (sc-DGNN) model and compared with machine learning (ML) and deep learning (DL) models.This work attempts to focus on eighty-eight subjects of diffusion magnetic resonance imaging (dMRI), three classical ML, and five DL models.

Result

The structural connectivity-deep graph neural network (sc-DGNN) model is proposed to effectively predict dysconnectedness associated with schizophrenia and exhibits superior performance compared to traditional ML and DL (GNNs) methods in terms of accuracy, sensitivity, specificity, precision, F1-score, and Area under receiver operating characteristic (AUC).

Conclusion

The classification task on schizophrenia using structural connectivity matrices and experimental results showed that linear discriminant analysis (LDA) performed 72% accuracy rate in ML models and sc-DGNN performed at a 93% accuracy rate in DL models to distinguish between schizophrenia and healthy patients.

Pushing MP2RAGE boundaries: Ultimate time-efficient parameterization combined with exhaustive T1 synthetic contrasts

PURPOSE

MP2RAGE parameter optimization is redefined to allow more time-efficient MR acquisitions, whereas the T1 -based synthetic imaging framework is used to obtain on-demand T1 -weighted contrasts. Our aim was to validate this concept on healthy volunteers and patients with multiple sclerosis, using plug-and-play parallel-transmission brain imaging at 7 T.

METHODS

A "time-efficient" MP2RAGE sequence was designed with optimized parameters including TI and TR set as small as possible. Extended phase graph formalism was used to set flip-angle values to maximize the gray-to-white-matter contrast-to-noise ratio (CNR). Several synthetic contrasts (UNI, EDGE, FGATIR, FLAWSMIN , FLAWSHCO ) were generated online based on the acquired T1 maps. Experimental validation was performed on 4 healthy volunteers at various spatial resolutions. Clinical applicability was evaluated on 6 patients with multiple sclerosis, scanned with both time-efficient and conventional MP2RAGE parameterizations.

RESULTS

The proposed time-efficient MP2RAGE protocols reduced acquisition time by 40%, 30%, and 19% for brain imaging at (1 mm)3 , (0.80 mm)3 and (0.65 mm)3 , respectively, when compared with conventional parameterizations. They also provided all synthetic contrasts and comparable contrast-to-noise ratio on UNI images. The flexibility in parameter selection allowed us to obtain a whole-brain (0.45 mm)3 acquisition in 19 min 56 s. On patients with multiple sclerosis, a (0.67 mm)3 time-efficient acquisition enhanced cortical lesion visualization compared with a conventional (0.80 mm)3 protocol, while decreasing the scan time by 15%.

CONCLUSION

The proposed optimization, associated with T1 -based synthetic contrasts, enabled substantial decrease of the acquisition time or higher spatial resolution scans for a given time budget, while generating all typical brain contrasts derived from MP2RAGE.

Magnetoencephalography Atlas Viewer for Dipole Localization and Viewing

Magnetoencephalography (MEG) is a noninvasive neuroimaging technique widely recognized for epilepsy and tumor mapping. MEG clinical reporting requires a multidisciplinary team, including expert input regarding each dipole's anatomic localization. Here, we introduce a novel tool, the "Magnetoencephalography Atlas Viewer" (MAV), which streamlines this anatomical analysis. The MAV normalizes the patient's Magnetic Resonance Imaging (MRI) to the Montreal Neurological Institute (MNI) space, reverse-normalizes MNI atlases to the native MRI, identifies MEG dipole files, and matches dipoles' coordinates to their spatial location in atlas files. It offers a user-friendly and interactive graphical user interface (GUI) for displaying individual dipoles, groups, coordinates, anatomical labels, and a tri-planar MRI view of the patient with dipole overlays. It evaluated over 273 dipoles obtained in clinical epilepsy subjects. Consensus-based ground truth was established by three neuroradiologists, with a minimum agreement threshold of two. The concordance between the ground truth and MAV labeling ranged from 79% to 84%, depending on the normalization method. Higher concordance rates were observed in subjects with minimal or no structural abnormalities on the MRI, ranging from 80% to 90%. The MAV provides a straightforward MEG dipole anatomic localization method, allowing a nonspecialist to prepopulate a report, thereby facilitating and reducing the time of clinical reporting.

Characterizing upper extremity fine motor function in the presence of white matter hyperintensities: A 7 T MRI cross-sectional study in older adults

BACKGROUND

White matter hyperintensities (WMH) are a prevalent radiographic finding in the aging brain studies. Research on WMH association with motor impairment is mostly focused on the lower-extremity function and further investigation on the upper-extremity is needed. How different degrees of WMH burden impact the network of activation recruited during upper limb motor performance could provide further insight on the complex mechanisms of WMH pathophysiology and its interaction with aging and neurological disease processes.

METHODS

40 healthy elderly subjects without a neurological/psychiatric diagnosis were included in the study (16F, mean age 69.3 years). All subjects underwent ultra-high field 7 T MRI including structural and finger tapping task-fMRI. First, we quantified the WMH lesion load and its spatial distribution. Secondly, we performed a data-driven stratification of the subjects according to their periventricular and deep WMH burdens. Thirdly, we investigated the distribution of neural recruitment and the corresponding activity assessed through BOLD signal changes among different brain regions for groups of subjects. We clustered the degree of WMH based on location, numbers, and volume into three categories; ranging from mild, moderate, and severe. Finally, we explored how the spatial distribution of WMH, and activity elicited during task-fMRI relate to motor function, measured with the 9-Hole Peg Test.

RESULTS

Within our population, we found three subgroups of subjects, partitioned according to their periventricular and deep WMH lesion load. We found decreased activity in several frontal and cingulate cortex areas in subjects with a severe WMH burden. No statistically significant associations were found when performing the brain-behavior statistical analysis for structural or functional data.

CONCLUSION

WMH burden has an effect on brain activity during fine motor control and the activity changes are associated with varying degrees of the total burden and distributions of WMH lesions. Collectively, our results shed new light on the potential impact of WMH on motor function in the context of aging and neurodegeneration.

Triangulating brain alterations in anorexia nervosa: a multimodal investigation of magnetic resonance spectroscopy, morphometry and blood-based biomarkers

The acute state of anorexia nervosa (AN) is associated with widespread reductions in cortical gray matter (GM) thickness and white matter (WM) volume, suspected changes in myelin content and elevated levels of the neuronal damage marker neurofilament light (NF-L), but the underlying mechanisms remain largely unclear. To gain a deeper understanding of brain changes in AN, we applied a multimodal approach combining advanced neuroimaging methods with analysis of blood-derived biomarkers. In addition to standard measures of cortical GM thickness and WM volume, we analyzed tissue-specific profiles of brain metabolites using multivoxel proton magnetic resonance spectroscopy, T1 relaxation time as a proxy of myelin content leveraging advanced quantitative MRI methods and serum NF-L concentrations in a sample of 30 female, predominately adolescent patients with AN and 30 age-matched female healthy control participants. In patients with AN, we found a reduction in GM cortical thickness and GM total N-acetyl aspartate. The latter predicted higher NF-L levels, which were elevated in AN. Furthermore, GM total choline was elevated. In WM, there were no group differences in either imaging markers, choline levels or N-acetyl aspartate levels. The current study provides evidence for neuronal damage processes as well as for increased membrane lipid catabolism and turnover in GM in acute AN but no evidence for WM pathology. Our results illustrate the potential of multimodal research including tissue-specific proton magnetic resonance spectroscopy analyses to shed light on brain changes in psychiatric and neurological conditions, which may ultimately lead to better treatments.

Reinforcement learning with associative or discriminative generalization across states and actions: fMRI at 3 T and 7 T

The model-free algorithms of "reinforcement learning" (RL) have gained clout across disciplines, but so too have model-based alternatives. The present study emphasizes other dimensions of this model space in consideration of associative or discriminative generalization across states and actions. This "generalized reinforcement learning" (GRL) model, a frugal extension of RL, parsimoniously retains the single reward-prediction error (RPE), but the scope of learning goes beyond the experienced state and action. Instead, the generalized RPE is efficiently relayed for bidirectional counterfactual updating of value estimates for other representations. Aided by structural information but as an implicit rather than explicit cognitive map, GRL provided the most precise account of human behavior and individual differences in a reversal-learning task with hierarchical structure that encouraged inverse generalization across both states and actions. Reflecting inference that could be true, false (i.e., overgeneralization), or absent (i.e., undergeneralization), state generalization distinguished those who learned well more so than action generalization. With high-resolution high-field fMRI targeting the dopaminergic midbrain, the GRL model's RPE signals (alongside value and decision signals) were localized within not only the striatum but also the substantia nigra and the ventral tegmental area, including specific effects of generalization that also extend to the hippocampus. Factoring in generalization as a multidimensional process in value-based learning, these findings shed light on complexities that, while challenging classic RL, can still be resolved within the bounds of its core computations.

Application of Clustering-Based Analysis in MRI Brain Tissue Segmentation

The segmentation of brain tissue by MRI not only contributes to the study of the function and anatomical structure of the brain, but it also offers a theoretical foundation for the diagnosis and treatment of brain illnesses. When discussing the anatomy of the brain in a clinical setting, the terms “white matter,” “gray matter,” and “cerebrospinal fluid” are the ones most frequently used (CSF). However, due to the fact that the human brain is highly complicated in its structure and that there are many different types of brain tissues, the human brain structure of each individual has its own set of distinctive qualities. Because of these several circumstances, the process of segmenting brain tissue will be challenging. In this article, several different clustering algorithms will be discussed, and their performance and effects will be compared to one another. The goal of this comparison is to determine which algorithm is most suited for segmenting MRI brain tissue. Based on the clustering method, the primary emphasis of this research is placed on the segmentation approach that is appropriate for medical brain imaging. The qualitative and quantitative findings of the experiment reveal that the FCM algorithm has more steady performance and better universality, but it is necessary to include the additional auxiliary conditions in order to achieve more ideal outcomes.

3-Dimensional Fluid and White Matter Suppression Magnetic Resonance Imaging Sequence Accelerated With Compressed Sensing Improves Multiple Sclerosis Cervical Spinal Cord Lesion Detection Compared With Standard 2-Dimensional Imaging

OBJECTIVES

Fluid and white matter suppression (FLAWS) is a recently proposed magnetic resonance sequence derived from magnetization-prepared 2 rapid acquisition gradient-echo providing 2 coregistered datasets with white matter- and cerebrospinal fluid-suppressed signal, enabling synthetic imaging with amplified contrast. Although these features are high potential for brain multiple sclerosis (MS) imaging, spinal cord has never been evaluated with this sequence to date. The objective of this work was therefore to assess diagnostic performance and self-confidence provided by compressed-sensing (CS) 3-dimensional (3D) FLAWS for cervical MS lesion detection on a head scan that includes the cervical cord without changing standard procedures.

MATERIALS AND METHODS

Prospective 3 T scans (MS first diagnosis or follow-up) acquired between 2019 and 2020 were retrospectively analyzed. All patients underwent 3D CS-FLAWS (duration: 5 minutes 40 seconds), axial T2 turbo spin echo covering cervical spine from cervicomedullary junction to the same inferior level as FLAWS, and sagittal cervical T2/short tau inversion recovery imaging. Two readers performed a 2-stage double-blind reading, followed by consensus reading. Wilcoxon tests were used to compare the number of detected spinal cord lesions and the reader's diagnostic self-confidence when using FLAWS versus the reference 2D T2-weighted imaging.

RESULTS

Fifty-eight patients were included (mean age, 40 ± 13 years, 46 women, 7 ± 6 years mean disease duration). The CS-FLAWS detected significantly more lesions than the reference T2-weighted imaging (197 vs 152 detected lesions, P < 0.001), with a sensitivity of 98% (T2-weighted imaging sensitivity: 90%) after consensual reading. Considering the subgroup of patients who underwent sagittal T2 + short tau inversion recovery imaging (Magnetic Resonance Imaging for Multiple Sclerosis subgroup), +250% lesions were detected with FLAWS (63 vs 25 lesions detected, P < 0.001). Mean reading self-confidence was significantly better with CS-FLAWS (median, 5 [interquartile range, 1] [no doubt for diagnosis] vs 4 [interquartile range, 1] [high confidence]; P < 0.001).

CONCLUSIONS

Imaging with CS-FLAWS provides an improved cervical spinal cord exploration for MS with increased self-confidence compared with conventional T2-weighted imaging, in a clinically acceptable time.

Volumetric 23Na Single and Triple-Quantum Imaging at 7T: 3D-CRISTINA

PURPOSE

To measure multi-quantum coherence (MQC) ²³Na signals for noninvasive cell physiological information in the whole-brain, the 2D-CRISTINA method was extended to 3D. This experimental study investigated the use and results of a new sequence, 3D-CRISTINA, on a phantom and healthy volunteers.

METHODS

The 3D Cartesian single and triple-quantum imaging of ²³Na (3D-CRISTINA) was developed and implemented at 7T, favoring a non-selective volume excitation for increased signal-to-noise ratio (SNR) and lower energy deployment than its 2D counterpart. Two independent phase cycles were used in analogy to the 2D method. A comparison of 6-steps cycles and 12-steps cycles was performed. We used a phantom composed of different sodium and agarose concentrations, 50mM to 150mM Na+, and 0-5% agarose for sequence validation. Four healthy volunteers were scanned at 7T for whole brain MQC imaging. The sequence 3D-CRISTINA was developed and tested at 7T.

RESULTS

At 7T, the 3D-CRISTINA acquisition allowed to reduce the TR to 230ms from the previous 390ms for 2D, resulting in a total acquisition time of 53min for a 3D volume of 4×4×8mm resolution. The phase cycle evaluation showed that the 7T acquisition time could be reduced by 4-fold with moderate single and triple-quantum signals SNR loss. The healthy volunteers demonstrated clinical feasibility at 7T and showed a difference in the MQC signals ratio of White Matter (WM) and Grey Matter (GM).

CONCLUSION

Volumetric CRISTINA multi-quantum imaging allowed whole-brain coverage. The non-selective excitation enabled a faster scan due to a decrease in energy deposition which enabled a lower repetition time. Thus, it should be the preferred choice for future in vivo multi-quantum applications compared to the 2D method. A more extensive study is warranted to explore WM and GM MQC differences.

Structural assessment of thalamus morphology in brain disorders: A review and recommendation of thalamic nucleus segmentation and shape analysis

The thalamus is a central brain structure crucially involved in cognitive, emotional, sensory, and motor functions and is often reported to be involved in the pathophysiology of neurological and psychiatric disorders. The functional subdivision of the thalamus warrants morphological investigation on the level of individual subnuclei. In addition to volumetric measures, the investigation of other morphological features may give additional insights into thalamic morphology. For instance, shape features offer a higher spatial resolution by revealing small, regional differences that are left undetected in volumetric analyses. In this review, we discuss the benefits and limitations of recent advances in neuroimaging techniques to investigate thalamic morphology in vivo, leading to our proposed methodology. This methodology consists of available pipelines for volume and shape analysis, focussing on the morphological features of volume, thickness, and surface area. We demonstrate this combined approach in a Parkinson's disease cohort to illustrate their complementarity. Considering our findings, we recommend a combined methodology as it allows for more sensitive investigation of thalamic morphology in clinical populations.

High-resolution Structural Magnetic Resonance Imaging and Quantitative Susceptibility Mapping

High-resolution 7-T imaging and quantitative susceptibility mapping produce greater anatomic detail compared with conventional strengths because of improvements in signal/noise ratio and contrast. The exquisite anatomic details of deep structures, including delineation of microscopic architecture using advanced techniques such as quantitative susceptibility mapping, allows improved detection of abnormal findings thought to be imperceptible on clinical strengths. This article reviews caveats and techniques for translating sequences commonly used on 1.5 or 3 T to high-resolution 7-T imaging. It discusses for several broad disease categories how high-resolution 7-T imaging can advance the understanding of various diseases, improve diagnosis, and guide management.

Whole brain and deep gray matter structure segmentation: Quantitative comparison between MPRAGE and MP2RAGE sequences

Objective

T1-weighted MRI images are commonly used for volumetric assessment of brain structures. Magnetization prepared 2 rapid gradient echo (MP2RAGE) sequence offers superior gray (GM) and white matter (WM) contrast. This study aimed to quantitatively assess the agreement of whole brain tissue and deep GM (DGM) volumes obtained from MP2RAGE compared to the widely used MP-RAGE sequence.

Methods

Twenty-nine healthy participants were included in this study. All subjects underwent a 3T MRI scan acquiring high-resolution 3D MP-RAGE and MP2RAGE images. Twelve participants were re-scanned after one year. The whole brain, as well as DGM segmentation, was performed using CAT12, volBrain, and FSL-FAST automatic segmentation tools based on the acquired images. Finally, contrast-to-noise ratio between WM and GM (CNR_WG), the agreement between the obtained tissue volumes, as well as scan-rescan variability of both sequences were explored.

Results

Significantly higher CNR_WG was detected in MP2RAGE vs. MP-RAGE (Mean ± SD = 0.97 ± 0.04 vs. 0.8 ± 0.1 respectively; p<0.0001). Significantly higher total brain GM, and lower cerebrospinal fluid‏ volumes were obtained from MP2RAGE vs. MP-RAGE based on all segmentation methods (p<0.05 in all cases). Whole-brain voxel-wise comparisons revealed higher GM tissue probability in the thalamus, putamen, caudate, lingual gyrus, and precentral gyrus based on MP2RAGE compared with MP-RAGE. Moreover, significantly higher WM probability was observed in the cerebellum, corpus callosum, and frontal-and-temporal regions in MP2RAGE vs. MP-RAGE. Finally, MP2RAGE showed a higher mean percentage of change in total brain GM compared to MP-RAGE. On the other hand, MP-RAGE demonstrated a higher overtime percentage of change in WM and DGM volumes compared to MP2RAGE.

Conclusions

Due to its higher CNR, MP2RAGE resulted in reproducible brain tissue segmentation, and thus is a recommended method for volumetric imaging biomarkers for the monitoring of neurological diseases.

T1-Based Synthetic Magnetic Resonance Contrasts Improve Multiple Sclerosis and Focal Epilepsy Imaging at 7 T

OBJECTIVES

Ultra-high field magnetic resonance imaging (MRI) (≥7 T) is a unique opportunity to improve the clinical diagnosis of brain pathologies, such as multiple sclerosis or focal epilepsy. However, several shortcomings of 7 T MRI, such as radiofrequency field inhomogeneities, could degrade image quality and hinder radiological interpretation. To address these challenges, an original synthetic MRI method based on T1 mapping achieved with the magnetization-prepared 2 rapid acquisition gradient echo (MP2RAGE) sequence was developed. The radiological quality of on-demand T1-based contrasts generated by this technique was evaluated in multiple sclerosis and focal epilepsy imaging at 7 T.

MATERIALS AND METHODS

This retrospective study was carried out from October 2017 to September 2019 and included 21 patients with different phenotypes of multiple sclerosis and 35 patients with focal epilepsy who underwent MRI brain examinations using a whole-body investigative 7 T magnetic resonance system. The quality of 2 proposed synthetic contrast images were assessed and compared with conventional images acquired at 7 T using the MP2RAGE sequence by 4 radiologists, evaluating 3 qualitative criteria: signal homogeneity, contrast intensity, and lesion visualization. Statistical analyses were performed on reported quality scores using Wilcoxon rank tests and further multiple comparisons tests. Intraobserver and interobserver reliabilities were calculated as well.

RESULTS

Radiological quality scores were reported higher for synthetic images when compared with original images, regardless of contrast, pathologies, or raters considered, with significant differences found for all 3 criteria (P < 0.0001, Wilcoxon rank test). None of the 4 radiologists ever rated a synthetic image "markedly worse" than an original image. Synthetic images were rated slightly less satisfying for only 3 epileptic patients, without precluding lesion identification.

CONCLUSION

T1-based synthetic MRI with the MP2RAGE sequence provided on-demand contrasts and high-quality images to the radiologist, facilitating lesion visualization in multiple sclerosis and focal epilepsy, while reducing the magnetic resonance examination total duration by removing an additional sequence.

Methodological Considerations for Neuroimaging in Deep Brain Stimulation of the Subthalamic Nucleus in Parkinson's Disease Patients

Deep brain stimulation (DBS) of the subthalamic nucleus is a neurosurgical intervention for Parkinson's disease patients who no longer appropriately respond to drug treatments. A small fraction of patients will fail to respond to DBS, develop psychiatric and cognitive side-effects, or incur surgery-related complications such as infections and hemorrhagic events. In these cases, DBS may require recalibration, reimplantation, or removal. These negative responses to treatment can partly be attributed to suboptimal pre-operative planning procedures via direct targeting through low-field and low-resolution magnetic resonance imaging (MRI). One solution for increasing the success and efficacy of DBS is to optimize preoperative planning procedures via sophisticated neuroimaging techniques such as high-resolution MRI and higher field strengths to improve visualization of DBS targets and vasculature. We discuss targeting approaches, MRI acquisition, parameters, and post-acquisition analyses. Additionally, we highlight a number of approaches including the use of ultra-high field (UHF) MRI to overcome limitations of standard settings. There is a trade-off between spatial resolution, motion artifacts, and acquisition time, which could potentially be dissolved through the use of UHF-MRI. Image registration, correction, and post-processing techniques may require combined expertise of traditional radiologists, clinicians, and fundamental researchers. The optimization of pre-operative planning with MRI can therefore be best achieved through direct collaboration between researchers and clinicians.

Noninvasive 7 tesla MRI of fatal craniocerebral gunshots - a glance into the future of radiologic wound ballistics

Compared to computed tomography (CT), magnetic resonance imaging (MRI) provides superior visualization of the soft tissue. Recently, the first 7 Tesla (7 T) MRI scanner was approved for clinical use, which will facilitate access to these ultra-high-field MRI scanners for noninvasive examinations and scientific studies on decedents. 7 T MRI has the potential to provide a higher signal-to-noise ratio (SNR), a characteristic that can be directly exploited to improve image quality and invest in attempts to increase resolution. Therefore, evaluating the diagnostic potential of 7 T MRI for forensic purposes, such as assessments of fatal gunshot wounds, was deemed essential. In this article, we present radiologic findings obtained for craniocerebral gunshot wounds in three decedents. The decedents were submitted to MRI examinations using a 7 T MRI scanner that has been approved for clinical use and a clinical 3 T MRI scanner for comparison. We focused on detecting tiny injuries beyond the wound tract caused by temporary cavitation, such as microbleeds. Additionally, 7 T T₂-weighted MRI highlighted a dark (hypo intense) zone beyond the permanent wound tract, which was attributed to increased amounts of paramagnetic blood components in damaged tissue. Microbleeds were also detected adjacent to the wound tract in the white matter on 7 T MRI. Based on the findings of radiologic assessments, the advantages and disadvantages of postmortem 7 T MRI compared to 3 T MRI are discussed with regard to investigations of craniocerebral gunshot wounds as well as the potential role of 7 T MRI in the future of forensic science.

Hippocampal-striatal functional connectivity supports processing of temporal expectations from associative memory

The hippocampus and dorsal striatum are both associated with temporal processing, but they are thought to play distinct roles. The hippocampus has been reported to contribute to storing temporal structure of events in memory, whereas the striatum contributes to temporal motor preparation and reward anticipation. Here, we asked whether the striatum cooperates with the hippocampus in processing the temporal context of memorized visual associations. In our task, participants were trained to implicitly form temporal expectations for one of two possible time intervals associated to specific cue-target associations, and subsequently were scanned using ultra-high-field 7T functional magnetic resonance imaging. During scanning, learned temporal expectations could be violated when the pairs were presented at either the associated or not-associated time intervals. When temporal expectations were met during testing trials, activity in left and right hippocampal subfields and right putamen decreased, compared to when temporal expectations were not met. Further, psycho-physiological interactions showed that functional connectivity between left hippocampal subfields and caudate decreased when temporal expectations were not met. Our results indicate that the hippocampus and striatum cooperate to process implicit temporal expectation from mnemonic associations. Our findings provide further support for a hippocampal-striatal network in temporal associative processing.

7T MPFLAIR versus MP2RAGE for Quantifying Lesion Volume in Multiple Sclerosis

BACKGROUND AND PURPOSE

Use of fluid-attenuated inversion recovery (FLAIR) scans to quantify multiple sclerosis (MS) lesion volume on 7 Tesla (7T) magnetic resonance imaging (MRI) has many downsides, including poor image homogeneity. There are little data about the relative benefit of alternative modalities. The purpose of this paper is to investigate if magnetization-prepared 2 rapid acquisition gradient echo (MP2RAGE) is a viable alternative to FLAIR for robust lesion volume measurement and disability correlations.

METHODS

Forty-seven participants with MS underwent annual brain 7T MRIs. Magnetization-prepared FLAIR (MPFLAIR) and MP2RAGE (both at .7 mm³ isotropic resolution) sequences from a total of 80 MRI scans from 47 subjects were reviewed. White matter lesion (WML) masks were manually constructed from MPFLAIR and T1 maps (from MP2RAGE). Lesion volumes (normalized to intracranial volume) were compared to clinical characteristics and disability scales scores by Pearson or Spearman correlation, as appropriate. Relative correlation strength was compared by Fisher r- to z-transformation.

RESULTS

Normalized lesion volume was greater in MPFLAIR masks (median .005 [range, .001-.030]) than from T1 maps (median .003 [range, .000-.015]). However, lesion volumes between MPFLAIR and T1 maps were highly correlated (rho = .87, P < .001). WML masks from both modalities correlated with most disability measures with no significant difference in the strength of correlation.

CONCLUSIONS

7T MPFLAIR and MP2RAGE T1 map-based WML volumes are highly intercorrelated and both correlate with disability. Thus, MP2RAGE may be a viable alternative to FLAIR-based methods for WML measurement on 7T MRI in MS research.