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This paper presents an open, multi-vendor, multi-field strength magnetic resonance (MR) T1-weighted volumetric brain imaging dataset, named Calgary-Campinas-359 (CC-359). The dataset is composed of images of older healthy adults (29–80 years) acquired on scanners from three vendors (Siemens, Philips and General Electric) at both 1.5 T and 3 T. CC-359 is comprised of 359 datasets, approximately 60 subjects per vendor and magnetic field strength. The dataset is approximately age and gender balanced, subject to the constraints of the available images. It provides consensus brain extraction masks for all volumes generated using supervised classification. Manual segmentation results for twelve randomly selected subjects performed by an expert are also provided. The CC-359 dataset allows investigation of 1) the influences of both vendor and magnetic field strength on quantitative analysis of brain MR; 2) parameter optimization for automatic segmentation methods; and potentially 3) machine learning classifiers with big data, specifically those based on deep learning methods, as these approaches require a large amount of data. To illustrate the utility of this dataset, we compared to the results of a supervised classifier, the results of eight publicly available skull stripping methods and one publicly available consensus algorithm. A linear mixed effects model analysis indicated that vendor (p−value<0.001) and magnetic field strength (p−value<0.001) have statistically significant impacts on skull stripping results. •A public multi-vendor, multi-field-strength brain MR dataset is proposed and it is now available for download at http://miclab.fee.unicamp.br/tools.•Consensus masks are used as “silver-standards” to assess agreement between different skull stripping methods.•Influences of scanner magnetic field strength and scanner vendor on skull stripping results are analyzed.

The thalamus and its nuclei are largely indistinguishable on standard T1 or T2 weighted MRI. While diffusion tensor imaging based methods have been proposed to segment the thalamic nuclei based on the angular orientation of the principal diffusion tensor, these are based on echo planar imaging which is inherently limited in spatial resolution and suffers from distortion. We present a multi-atlas segmentation technique based on white-matter-nulled MP-RAGE imaging that segments the thalamus into 12 nuclei with computation times on the order of 10 min on a desktop PC; we call this method THOMAS (THalamus Optimized Multi Atlas Segmentation). THOMAS was rigorously evaluated on 7T MRI data acquired from healthy volunteers and patients with multiple sclerosis by comparing against manual segmentations delineated by a neuroradiologist, guided by the Morel atlas. Segmentation accuracy was very high, with uniformly high Dice indices: at least 0.85 for large nuclei like the pulvinar and mediodorsal nuclei and at least 0.7 even for small structures such as the habenular, centromedian, and lateral and medial geniculate nuclei. Volume similarity indices ranged from 0.82 for the smaller nuclei to 0.97 for the larger nuclei. Volumetry revealed that the volumes of the right anteroventral, right ventral posterior lateral, and both right and left pulvinar nuclei were significantly lower in MS patients compared to controls, after adjusting for age, sex and intracranial volume. Lastly, we evaluated the potential of this method for targeting the Vim nucleus for deep brain surgery and focused ultrasound thalamotomy by overlaying the Vim nucleus segmented from pre-operative data on post-operative data. The locations of the ablated region and active DBS contact corresponded well with the segmented Vim nucleus. Our fast, direct structural MRI based segmentation method opens the door for MRI guided intra-operative procedures like thalamotomy and asleep DBS electrode placement as well as for accurate quantification of thalamic nuclear volumes to follow progression of neurological disorders. •White-matter nulled MP-RAGE sequence provides improved intra-thalamic contrast.•THOMAS exploits this improved contrast to segment 12 thalamic nuclei with excellent accuracy as measured by Dice against manual segmentation.•Volumetry results using THOMAS revealed atrophy of select nuclei in multiple sclerosis patients.•THOMAS can also be used to accurately predict the ventralis intermedius nucleus for deep brain stimulation targeting.

Magnetic Resonance Imaging (MRI) is crucial for detailed visualization of brain structure and function. However, conventional supine imaging limits the exploration of how posture impacts brain morphology. While recent advancements in upright MRI systems have enabled studies of postural effects on various body systems, investigations into posture's impact on brain anatomy remain limited. This study investigated volumetric differences between upright and supine positions to establish a baseline for future investigations into how posture influenced brain structure. Thirty-one healthy volunteers underwent scans using a rotatable cryogen-free 1.5T MRI scanner in supine and upright postures. The 3D T1-weighted MP-RAGE brain images were segmented into 109 regions, and volume changes across these regions were analyzed. Volumetric analysis across 109 brain regions in both supine and upright postures shows minimal changes, with most regions displaying variations within a ±5% range. The coefficient of variation (COV) indicated that posture-induced volume changes are even smaller than the measurement precision of the method. These findings provide a solid groundwork for future studies on the effects of posture on brain structure. The majority of brain regions exhibited no significant volumetric differences between supine and upright positions, suggesting that brain structure remains consistent and stable across different postures. These findings offer valuable insights for future research on the postural influences on brain morphology.

At high magnetic field, MR images exhibit large, undesirable signal intensity variations commonly referred to as “intensity field bias”. Such inhomogeneities mostly originate from heterogeneous RF coil B1 profiles and, with no appropriate correction, are further pronounced when utilizing rooted sum of square reconstruction with receive coil arrays. These artifacts can significantly alter whole brain high resolution T1-weighted (T1w) images that are extensively utilized for clinical diagnosis, for gray/white matter segmentation as well as for coregistration with functional time series. In T1 weighted 3D-MPRAGE sequences, it is possible to preserve a bulk amount of T1 contrast through space by using adiabatic inversion RF pulses that are insensitive to transmit B1 variations above a minimum threshold. However, large intensity variations persist in the images, which are significantly more difficult to address at very high field where RF coil B1 profiles become more heterogeneous. Another characteristic of T1w MPRAGE sequences is their intrinsic sensitivity to Proton Density and T2⁎ contrast, which cannot be removed with post-processing algorithms utilized to correct for receive coil sensitivity. In this paper, we demonstrate a simple technique capable of producing normalized, high resolution T1w 3D-MPRAGE images that are devoid of receive coil sensitivity, Proton Density and T2⁎ contrast. These images, which are suitable for routinely obtaining whole brain tissue segmentation at 7 T, provide higher T1 contrast specificity than standard MPRAGE acquisitions. Our results show that removing the Proton Density component can help in identifying small brain structures and that T2⁎ induced artifacts can be removed from the images. The resulting unbiased T1w images can also be used to generate Maximum Intensity Projection angiograms, without additional data acquisition, that are inherently registered with T1w structural images. In addition, we introduce a simple technique to reduce residual signal intensity variations induced by transmit B1 heterogeneity. Because this approach requires two 3D images, one divided with the other, head motion could create serious problems, especially at high spatial resolution. To alleviate such inter-scan motion problems, we developed a new sequence where the two contrast acquisitions are interleaved within a single scan. This interleaved approach however comes with greater risk of intra-scan motion issues because of a longer single scan time. Users can choose between these two trade offs depending on specific protocols and patient populations. We believe that the simplicity and the robustness of this double contrast based approach to address intensity field bias at high field and improve T1 contrast specificity, together with the capability of simultaneously obtaining angiography maps, advantageously counter balance the potential drawbacks of the technique, mainly a longer acquisition time and a moderate reduction in signal to noise ratio.

One of the promises of Ultra High Field (UHF) MRI scanners is to bring finer spatial resolution in the human brain images due to an increased signal to noise ratio. However, at such field strengths, the spatial non-uniformity of the Radio Frequency (RF) transmit profiles challenges the applicability of most MRI sequences, where the signal and contrast levels strongly depend on the flip angle (FA) homogeneity. In particular, the MP-RAGE sequence, one of the most commonly employed 3D sequences to obtain T1-weighted anatomical images of the brain, is highly sensitive to these spatial variations. These cause deterioration in image quality and complicate subsequent image post-processing such as automated tissue segmentation at UHF. In this work, we evaluate the potential of parallel-transmission (pTx) to obtain high-quality MP-RAGE images of the human brain at 7T. To this end, non-selective transmit-SENSE pulses were individually tailored for each of 8 subjects under study, and applied to an 8-channel transmit-array. Such RF pulses were designed both for the low-FA excitation train and the 180° inversion preparation involved in the sequence, both utilizing the recently introduced kT-point trajectory. The resulting images were compared with those obtained from the conventional method and from subject-specific RF-shimmed excitations. In addition, four of the volunteers were scanned at 3T for benchmarking purposes (clinical setup without pTx). Subsequently, automated tissue classification was performed to provide a more quantitative measure of the final image quality. Results indicated that pTx could already significantly improve image quality at 7T by adopting a suitable RF-Shim. Exploiting the full potential of the pTx-setup, the proposed kT-point method provided excellent inversion fidelity, comparable to what is commonly only achievable at 3T with energy intensive adiabatic pulses. Furthermore, the cumulative energy deposition was simultaneously reduced by over 40% compared to the conventional adiabatic inversions. Regarding the low-FA kT-point based excitations, the FA uniformity achieved at 7T surpassed what is typically obtained at 3T. Subsequently, automated white and gray matter segmentation not only confirmed the expected improvements in image quality, but also suggests that care should be taken to properly account for the strong local susceptibility effects near cranial cavities. Overall, these findings indicate that the kT-point-based pTx solution is an excellent candidate for UHF 3D imaging, where patient safety is a major concern due to the increase of specific absorption rates. ► We explore the potential of parallel-transmission for human brain MRI at high field. ► Different transmission methods at 7T are compared to the standard MP-RAGE at 3T. ► Parallel transmission improves image quality while reducing energy deposition. ► Contrast losses due to RF inhomogeneities vanish with kT-point tailored pulses. ► KT-points applied in MP-RAGE at 7T produce T1-contrasts equivalent to standard 3T.

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.

Intraplaque hemorrhage (IPH) is associated with atherosclerosis progression and subsequent cardiovascular events. We sought to develop a semi-automatic method with an optimized threshold for carotid IPH detection and quantification on MP-RAGE images using matched histology as the gold standard. Fourteen patients scheduled for carotid endarterectomy underwent 3D MP-RAGE cardiovascular magnetic resonance (CMR) preoperatively. Presence and area of IPH were recorded using histology. Presence and area of IPH were also recorded on CMR based on intensity thresholding using three references for intensity normalization: the sternocleidomastoid muscle (SCM), the adjacent muscle and the automatically generated local median value. The optimized intensity thresholds were obtained by maximizing the Youden's index for IPH detection. Using leave-one-out cross validation, the sensitivity and specificity for IPH detection based on our proposed semi-automatic method and the agreement with histology on IPH area quantification were evaluated. The optimized intensity thresholds for IPH detection were 1.0 times the SCM intensity, 1.6 times the adjacent muscle intensity and 2.2 times the median intensity. Using the semi-automatic method with the optimized intensity threshold, the following IPH detection and quantification performance was obtained: sensitivities up to 59, 68 and 80 %; specificities up to 85, 74 and 79 %; Pearson's correlation coefficients (IPH area measurement) up to 0.76, 0.93 and 0.90, respectively, using SCM, the adjacent muscle and the local median value for intensity normalization, after heavily calcified and small IPH were excluded. A semi-automatic method with good performance on IPH detection and quantification can be obtained in MP-RAGE CMR, using an optimized intensity threshold comparing to the adjacent muscle. The automatically generated reference of local median value provides comparable performance and may be particularly useful for developing automatic classifiers. Use of the SCM intensity as reference is not recommended without coil sensitivity correction when surface coils are used.

Funct. 218, 97–104. doi: 10.1007/s00429-012-0385-6 The magnetization-prepared rapid gradient-echo (MP-RAGE) T1-weighted high resolution structural MRI is a mainstay tool used to identify morphometric biomarkers of disease conditions, progression and treatment effects despite a critical limitation: the relaxation signal on which inferences are based is nearly indistinguishable for gray matter vs. blood flow (Lu et al., 2004; Wright et al., 2008). [...]apparent reported morphometric findings might be at least partially related to transient changes in blood flow or other physiological signals. The findings of altered gray matter induced by acute pharmacological manipulations highlighted above led us to hypothesize that cigarette smoking, which delivers the psychostimulant, nicotine, to the brain may transiently alter the MP-RAGE, based on the T1-weighted images. [...]we examined T1-weighted structural MRIs acquired in a within-subjects design in 39 otherwise healthy nicotine-dependent individuals. Nicotine's terminal half-life is approximately 2 h; thus, conservative estimates might place the onset of withdrawal symptomatology within the first 2 h after last smoking (Benowitz et al., 1982). [...]5 h of deprivation was chosen to ensure that the subjects would be experiencing withdrawal from nicotine. [...]these results show that the MP-RAGE should be acquired at the initiation of a scanning session, given the potential for it to be altered by subsequent activities (tasks, pharmacological manipulations) that occur over the course of scanning.

A novel method for the quantification of heterogeneity and spatial correlation in 3D MP-RAGE images of white matter is presented. The technique is based on the variogram, a tool commonly used in geosciences for the analysis of spatial data, and was tailored to the special requirements of MR image analysis. Influences from intensity non-uniformities, noise and arbitrary greyscale were quantified and considered in the calculations. The obtained variograms were fitted with spherical model functions to infer parameters that quantify heterogeneity and size of the correlation structures of the tissue. Numerically generated samples with well-defined correlation properties were employed to validate the estimation process and to provide an interpretation of the parameters obtained. It is shown that the method gives reliable results in an interval of correlation structures sized between 2mm and 20mm. The method was applied to 24 MP-RAGE datasets of healthy female volunteers ranging in age from 19 to 73years. White matter was found to have two prominent correlation structures with sizes of approximately 3mm and 23mm. The heterogeneity of the smaller structure increases significantly with age (r=0.83, p<10−6). [Display omitted] ► Variograms are employed to investigate spatial correlation in MR images. ► Numerical samples provide interpretation of variogram shapes. ► White matter obtained from MP-RAGE data of 24 healthy subjects is analysed. ► White matter is found to have 2 correlation structures, 3mm and 23mm in size. ► Inhomogeneity of the 3mm structure is significantly correlated with age.

The thickness of the human cerebral cortex, which provides valuable information in the studies of normal and abnormal neuroanatomy, is commonly estimated using high-resolution, volumetric magnetization-prepared rapid gradient echo (MP-RAGE) magnetic resonance imaging due to its strong T1-weighted contrast and high signal-to-noise ratio. However, the accuracy of cortical thickness estimates using MP-RAGE is potentially contaminated by susceptibility-induced signal loss particularly at regions in close proximity to air-filled cavities. The purpose of this work is to investigate the feasibility of susceptibility-resistant variable-flip-angle (VFA) three-dimensional turbo/fast spin echo imaging for reliable estimation of cortical thickness of the human brain, wherein 1) radio-frequency (RF) pulse refocuses susceptibility-induced spin de-phasing, 2) the VFA refocusing pulse train is applied for a tissue-specific prescribed signal evolution along the echo train, 3) the desired T1-weighted contrast is achieved by composite restore pulses at the end of the refocusing pulse train, and 4) blood signals are suppressed using the VFA scheme combined with increasing moments of flow-sensitizing gradients while dura mater signals are attenuated due to short T2 relaxation time, which alleviates potential failure in brain segmentation. Numerical simulations of the Bloch equation are performed in both MP-RAGE and the proposed method for comparison. In vivo studies are performed in 14 healthy volunteers at 3T. Image processing is then performed using the Freesurfer, resulting in mean and standard deviations of cortical thickness for the entire cortical surfaces. Statistical analysis demonstrates that particularly in the inferior prefrontal and temporal regions heavily affected by susceptibility-induced signal loss conventional MP-RAGE, if compared with the proposed method, significantly under-estimates cortical thickness. It is expected that the proposed pulse sequence, which is resistant to susceptibility-induced signal loss and attenuates the signal intensity of blood and dura mater, can be a potentially promising alternative to conventional MP-RAGE in reliably estimating cortical thickness for the entire brain. ► Susceptibility-resistant volumetric imaging for cortical thickness estimation. ► Inherent suppression of blood and dura mater for accurate brain segmentation ► Reliable estimation of cortical thickness particularly in prefrontal and temporal lobes.