Neuroimaging at 7 Tesla: a pictorial narrative review

Neuroimaging using the 7-Tesla (7T) human magnetic resonance (MR) system is rapidly gaining popularity after being approved for clinical use in the European Union and the USA. This trend is the same for functional MR imaging (MRI). The primary advantages of 7T over lower magnetic fields are its higher signal-to-noise and contrast-to-noise ratios, which provide high-resolution acquisitions and better contrast, making it easier to detect lesions and structural changes in brain disorders. Another advantage is the capability to measure a greater number of neurochemicals by virtue of the increased spectral resolution. Many structural and functional studies using 7T have been conducted to visualize details in the white matter and layers of the cortex and hippocampus, the subnucleus or regions of the putamen, the globus pallidus, thalamus and substantia nigra, and in small structures, such as the subthalamic nucleus, habenula, perforating arteries, and the perivascular space, that are difficult to observe at lower magnetic field strengths. The target disorders for 7T neuroimaging range from tumoral diseases to vascular, neurodegenerative, and psychiatric disorders, including Alzheimer’s disease, Parkinson’s disease, multiple sclerosis, epilepsy, major depressive disorder, and schizophrenia. MR spectroscopy has also been used for research because of its increased chemical shift that separates overlapping peaks and resolves neurochemicals more effectively at 7T than a lower magnetic field. This paper presents a narrative review of these topics and an illustrative presentation of images obtained at 7T. We expect 7T neuroimaging to provide a new imaging biomarker of various brain disorders

The LONI QC System: A Semi-Automated, Web-Based and Freely-Available Environment for the Comprehensive Quality Control of Neuroimaging Data.

Quantifying, controlling, and monitoring image quality is an essential prerequisite for ensuring the validity and reproducibility of many types of neuroimaging data analyses. Implementation of quality control (QC) procedures is the key to ensuring that neuroimaging data are of high-quality and their validity in the subsequent analyses. We introduce the QC system of the Laboratory of Neuro Imaging (LONI): a web-based system featuring a workflow for the assessment of various modality and contrast brain imaging data. The design allows users to anonymously upload imaging data to the LONI-QC system. It then computes an exhaustive set of QC metrics which aids users to perform a standardized QC by generating a range of scalar and vector statistics. These procedures are performed in parallel using a large compute cluster. Finally, the system offers an automated QC procedure for structural MRI, which can flag each QC metric as being 'good' or 'bad.' Validation using various sets of data acquired from a single scanner and from multiple sites demonstrated the reproducibility of our QC metrics, and the sensitivity and specificity of the proposed Auto QC to 'bad' quality images in comparison to visual inspection. To the best of our knowledge, LONI-QC is the first online QC system that uniquely supports the variety of functionality where we compute numerous QC metrics and perform visual/automated image QC of multi-contrast and multi-modal brain imaging data. The LONI-QC system has been used to assess the quality of large neuroimaging datasets acquired as part of various multi-site studies such as the Transforming Research and Clinical Knowledge in Traumatic Brain Injury (TRACK-TBI) Study and the Alzheimer's Disease Neuroimaging Initiative (ADNI). LONI-QC's functionality is freely available to users worldwide and its adoption by imaging researchers is likely to contribute substantially to upholding high standards of brain image data quality and to implementing these standards across the neuroimaging community

B(1) inhomogeneity correction of RARE MRI with transceive surface radiofrequency probes

PURPOSE: The use of surface radiofrequency (RF) coils is common practice to boost sensitivity in (pre)clinical MRI. The number of transceive surface RF coils is rapidly growing due to the surge in cryogenically cooled RF technology and ultrahigh‐field MRI. Consequently, there is an increasing need for effective correction of the excitation field (B(1)(+)) inhomogeneity inherent in these coils. Retrospective B(1) correction permits quantitative MRI, but this usually requires a pulse sequence‐specific analytical signal intensity (SI) equation. Such an equation is not available for fast spin‐echo (Rapid Acquisition with Relaxation Enhancement, RARE) MRI. Here we present, test, and validate retrospective B(1) correction methods for RARE. METHODS: We implemented the commonly used sensitivity correction and developed an empirical model‐based method and a hybrid combination of both. Tests and validations were performed with a cryogenically cooled RF probe and a single‐loop RF coil. Accuracy of SI quantification and T(1) contrast were evaluated after correction. RESULTS: The three described correction methods achieved dramatic improvements in B(1) homogeneity and significantly improved SI quantification and T(1) contrast, with mean SI errors reduced from >40% to >10% following correction in all cases. Upon correction, images of phantoms and mouse heads demonstrated homogeneity comparable to that of images acquired with a volume resonator. This was quantified by SI profile, SI ratio (error 80% in vivo and ex vivo compared to PIU > 87% with the reference RF coil). CONCLUSIONS: This work demonstrates the efficacy of three B(1) correction methods tailored for transceive surface RF probes and RARE MRI. The corrected images are suitable for quantification and show comparable results between the three methods, opening the way for T(1) measurements and X‐nuclei quantification using surface transceiver RF coils. This approach is applicable to other MR techniques for which no analytical SI exists

Invest Radiol

The magnetization-prepared 2 rapid acquisition gradient echo (MP2RAGE) sequence provides quantitative T1 maps in addition to high-contrast morphological images. Advanced acceleration techniques such as compressed sensing (CS) allow its acquisition time to be compatible with clinical applications. To consider its routine use in future neuroimaging protocols, the repeatability of the segmented brain structures was evaluated and compared with the standard morphological sequence (magnetization-prepared rapid gradient echo [MPRAGE]). The repeatability of the T1 measurements was also assessed. Thirteen healthy volunteers were scanned either 3 or 4 times at several days of interval, on a 3 T clinical scanner, with the 2 sequences (CS-MP2RAGE and MPRAGE), set with the same spatial resolution (0.8-mm isotropic) and scan duration (6 minutes 21 seconds). The reconstruction time of the CS-MP2RAGE outputs (including the 2 echo images, the MP2RAGE image, and the T1 map) was 3 minutes 33 seconds, using an open-source in-house algorithm implemented in the Gadgetron framework.Both precision and variability of volume measurements obtained from CAT12 and VolBrain were assessed. The T1 accuracy and repeatability were measured on phantoms and on humans and were compared with literature.Volumes obtained from the CS-MP2RAGE and the MPRAGE images were compared using Student t tests (P < 0.05 was considered significant). The CS-MP2RAGE acquisition provided morphological images of the same quality and higher contrasts than the standard MPRAGE images. Similar intravolunteer variabilities were obtained with the CS-MP2RAGE and the MPRAGE segmentations. In addition, high-resolution T1 maps were obtained from the CS-MP2RAGE. T1 times of white and gray matters and several deep gray nuclei are consistent with the literature and show very low variability (<1%). The CS-MP2RAGE can be used in future protocols to rapidly obtain morphological images and quantitative T1 maps in 3-dimensions while maintaining high repeatability in volumetry and relaxation times.Translational Research and Advanced Imaging LaboratoryDéveloppement de l'IRM ultra-rapide pour la mesure des temps de relaxation : Apllication à la thérapide guidée par IR

MAGNIMS recommendations for harmonization of MRI data in MS multicenter studies

Harmonization; MRI; Multiple sclerosisHarmonització; Ressonància magnètica; Esclerosi múltipleArmonización; Resonancia magnética; Esclerosis múltipleThere is an increasing need of sharing harmonized data from large, cooperative studies as this is essential to develop new diagnostic and prognostic biomarkers. In the field of multiple sclerosis (MS), the issue has become of paramount importance due to the need to translate into the clinical setting some of the most recent MRI achievements. However, differences in MRI acquisition parameters, image analysis and data storage across sites, with their potential bias, represent a substantial constraint. This review focuses on the state of the art, recent technical advances, and desirable future developments of the harmonization of acquisition, analysis and storage of large-scale multicentre MRI data of MS cohorts. Huge efforts are currently being made to achieve all the requirements needed to provide harmonized MRI datasets in the MS field, as proper management of large imaging datasets is one of our greatest opportunities and challenges in the coming years. Recommendations based on these achievements will be provided here. Despite the advances that have been made, the complexity of these tasks requires further research by specialized academical centres, with dedicated technical and human resources. Such collective efforts involving different professional figures are of crucial importance to offer to MS patients a personalised management while minimizing consumption of resources

Relationship between neuromelanin and dopamine terminals within the Parkinson's nigrostriatal system.

Parkinson's disease is characterized by the progressive loss of pigmented dopaminergic neurons in the substantia nigra and associated striatal deafferentation. Neuromelanin content is thought to reflect the loss of pigmented neurons, but available data characterizing its relationship with striatal dopaminergic integrity are not comprehensive or consistent, and predominantly involve heterogeneous samples. In this cross-sectional study, we used neuromelanin-sensitive MRI and the highly specific dopamine transporter PET radioligand, 11C-PE2I, to assess the association between neuromelanin-containing cell levels in the substantia nigra pars compacta and nigrostriatal terminal density in vivo, in 30 patients with bilateral Parkinson's disease. Fifteen healthy control subjects also underwent neuromelanin-sensitive imaging. We used a novel approach taking into account the anatomical and functional subdivision of substantia nigra into dorsal and ventral tiers and striatal nuclei into pre- and post-commissural subregions, in accordance with previous animal and post-mortem studies, and consider the clinically asymmetric disease presentation. In vivo, Parkinson's disease subjects displayed reduced neuromelanin levels in the ventral (-30 ± 28%) and dorsal tiers (-21 ± 24%) as compared to the control group [F(1,43) = 11.95, P = 0.001]. Within the Parkinson's disease group, nigral pigmentation was lower in the ventral tier as compared to the dorsal tier [F(1,29) = 36.19, P < 0.001] and lower in the clinically-defined most affected side [F(1,29) = 4.85, P = 0.036]. Similarly, lower dopamine transporter density was observed in the ventral tier [F(1,29) = 76.39, P < 0.001] and clinically-defined most affected side [F(1,29) = 4.21, P = 0.049]. Despite similar patterns, regression analysis showed no significant association between nigral pigmentation and nigral dopamine transporter density. However, for the clinically-defined most affected side, significant relationships were observed between pigmentation of the ventral nigral tier with striatal dopamine transporter binding in pre-commissural and post-commissural striatal subregions known to receive nigrostriatal projections from this tier, while the dorsal tier correlated with striatal projection sites in the pre-commissural striatum (P < 0.05, Benjamini-Hochberg corrected). In contrast, there were no statistically significant relationships between these two measures in the clinically-defined least affected side. These findings provide important insights into the topography of nigrostriatal neurodegeneration in Parkinson's disease, indicating that the characteristics of disease progression may fundamentally differ across hemispheres and support post-mortem data showing asynchrony in the loss of neuromelanin-containing versus tyrosine hydroxylase positive nigral cells.The research leading to these results has received funding from the European Research Council under the European Union's Seventh Framework Programme (FP7/2007-2013) [FP7-242003], from the Medical Research Council (MRC) [MR/P025870/1] and from Parkinson’s UK [J-1204]. Infrastructure support for this research was provided by the NIHR Imperial Biomedical Research Centre (BRC) and NIHR Imperial CRF at Imperial College healthcare NHS trust. The views expressed are those of the authors and not necessarily those of the funder, the NHS, the NIHR, or the Department of Health. This work was also supported financially by a PhD studentship awarded to N.P.L-K from Parkinson’s UK

MAGNIMS recommendations for harmonization of MRI data in MS multicenter studies

There is an increasing need of sharing harmonized data from large, cooperative studies as this is essential to develop new diagnostic and prognostic biomarkers. In the field of multiple sclerosis (MS), the issue has become of paramount importance due to the need to translate into the clinical setting some of the most recent MRI achievements. However, differences in MRI acquisition parameters, image analysis and data storage across sites, with their potential bias, represent a substantial constraint. This review focuses on the state of the art, recent technical advances, and desirable future developments of the harmonization of acquisition, analysis and storage of large-scale multicentre MRI data of MS cohorts. Huge efforts are currently being made to achieve all the requirements needed to provide harmonized MRI datasets in the MS field, as proper management of large imaging datasets is one of our greatest opportunities and challenges in the coming years. Recommendations based on these achievements will be provided here. Despite the advances that have been made, the complexity of these tasks requires further research by specialized academical centres, with dedicated technical and human resources. Such collective efforts involving different professional figures are of crucial importance to offer to MS patients a personalised management while minimizing consumption of resource