55,694 research outputs found
T2 Mapping from Super-Resolution-Reconstructed Clinical Fast Spin Echo Magnetic Resonance Acquisitions
Get PDFRelaxometry studies in preterm and at-term newborns have provided insight into brain microstructure, thus opening new avenues for studying normal brain development and supporting diagnosis in equivocal neurological situations. However, such quantitative techniques require long acquisition times and therefore cannot be straightforwardly translated to in utero brain developmental studies. In clinical fetal brain magnetic resonance imaging routine, 2D low-resolution T2-weighted fast spin echo sequences are used to minimize the effects of unpredictable fetal motion during acquisition. As super-resolution techniques make it possible to reconstruct a 3D high-resolution volume of the fetal brain from clinical low-resolution images, their combination with quantitative acquisition schemes could provide fast and accurate T2 measurements. In this context, the present work demonstrates the feasibility of using super-resolution reconstruction from conventional T2-weighted fast spin echo sequences for 3D isotropic T2 mapping. A quantitative magnetic resonance phantom was imaged using a clinical T2-weighted fast spin echo sequence at variable echo time to allow for super-resolution reconstruction at every echo time and subsequent T2 mapping of samples whose relaxometric properties are close to those of fetal brain tissue. We demonstrate that this approach is highly repeatable, accurate and robust when using six echo times (total acquisition time under 9 minutes) as compared to gold-standard single-echo spin echo sequences (several hours for one single 2D slice)
Motion robust acquisition and reconstruction of quantitative T2* maps in the developing brain
Get PDFThe goal of the research presented in this thesis was to develop methods for quantitative T2* mapping of the developing brain. Brain maturation in the early period of life involves complex structural and physiological changes caused by synaptogenesis, myelination and growth of cells. Molecular structures and biological processes give rise to varying levels of T2* relaxation time, which is an inherent contrast mechanism in magnetic resonance imaging. The knowledge of T2* relaxation times in the brain can thus help with evaluation of pathology by establishing its normative values in the key areas of the brain. T2* relaxation values are a valuable biomarker for myelin microstructure and iron concentration, as well as an important guide towards achievement of optimal fMRI contrast. However, fetal MR imaging is a significant step up from neonatal or adult MR imaging due to the complexity of the acquisition and reconstruction techniques that are required to provide high quality artifact-free images in the presence of maternal respiration and unpredictable fetal motion. The first contribution of this thesis, described in Chapter 4, presents a novel acquisition method for measurement of fetal brain T2* values. At the time of publication, this was the first study of fetal brain T2* values. Single shot multi-echo gradient echo EPI was proposed as a rapid method for measuring fetal T2* values by effectively freezing intra-slice motion. The study concluded that fetal T2* values are higher than those previously reported for pre-term neonates and decline with a consistent trend across gestational age. The data also suggested that longer than usual echo times or direct T2* measurement should be considered when performing fetal fMRI in order to reach optimal BOLD sensitivity. For the second contribution, described in Chapter 5, measurements were extended to a higher field strength of 3T and reported, for the first time, both for fetal and neonatal subjects at this field strength. The technical contribution of this work is a fully automatic segmentation framework that propagates brain tissue labels onto the acquired T2* maps without the need for manual intervention. The third contribution, described in Chapter 6, proposed a new method for performing 3D fetal brain reconstruction where the available data is sparse and is therefore limited in the use of current state of the art techniques for 3D brain reconstruction in the presence of motion. To enable a high resolution reconstruction, a generative adversarial network was trained to perform image to image translation between T2 weighted and T2* weighted data. Translated images could then be served as a prior for slice alignment and super resolution reconstruction of 3D brain image.Open Acces
EchoFusion: Tracking and Reconstruction of Objects in 4D Freehand Ultrasound Imaging without External Trackers
Get PDFUltrasound (US) is the most widely used fetal imaging technique. However, US
images have limited capture range, and suffer from view dependent artefacts
such as acoustic shadows. Compounding of overlapping 3D US acquisitions into a
high-resolution volume can extend the field of view and remove image artefacts,
which is useful for retrospective analysis including population based studies.
However, such volume reconstructions require information about relative
transformations between probe positions from which the individual volumes were
acquired. In prenatal US scans, the fetus can move independently from the
mother, making external trackers such as electromagnetic or optical tracking
unable to track the motion between probe position and the moving fetus. We
provide a novel methodology for image-based tracking and volume reconstruction
by combining recent advances in deep learning and simultaneous localisation and
mapping (SLAM). Tracking semantics are established through the use of a
Residual 3D U-Net and the output is fed to the SLAM algorithm. As a proof of
concept, experiments are conducted on US volumes taken from a whole body fetal
phantom, and from the heads of real fetuses. For the fetal head segmentation,
we also introduce a novel weak annotation approach to minimise the required
manual effort for ground truth annotation. We evaluate our method
qualitatively, and quantitatively with respect to tissue discrimination
accuracy and tracking robustness.Comment: MICCAI Workshop on Perinatal, Preterm and Paediatric Image analysis
(PIPPI), 201
Glycolipidomics of human cerebellum in development and aging by ion mobility tandem mass spectrometry
Get PDFIn this study ion mobility separation (IMS) mass spectrometry (MS) was for the first time introduced in human cerebellum ganglioside research. The work was focused on a comprehensive mapping and structural characterization of human cerebellar gangliosides and determination of the specific changes induced in their expression by brain development and aging. We have carried out a comparative IMS MS mapping of the native ganglioside mixtures extracted from fetal cerebellum in the second trimester of pregnancy vs. near-term fetus vs. aged cerebellum, followed by IMS CID MS/MS fragmentation analysis
MR imaging–derived oxygen-hemoglobin dissociation curves and fetal-placental oxygen-hemoglobin affinities
Get PDFPURPOSE: To generate magnetic resonance (MR) imaging–derived, oxygen-hemoglobin dissociation curves and to map fetal-placental oxygen-hemoglobin affinity in pregnant mice noninvasively by combining blood oxygen level–dependent (BOLD) T2* and oxygen-weighted T1 contrast mechanisms under different respiration challenges. MATERIALS AND METHODS: All procedures were approved by the Weizmann Institutional Animal Care and Use Committee. Pregnant mice were analyzed with MR imaging at 9.4 T on embryonic days 14.5 (eight dams and 58 fetuses; imprinting control region ICR strain) and 17.5 (21 dams and 158 fetuses) under respiration challenges ranging from hyperoxia to hypoxia (10 levels of oxygenation, 100%–10%; total imaging time, 100 minutes). A shorter protocol with normoxia to hyperoxia was also performed (five levels of oxygenation, 20%–100%; total imaging time, 60 minutes). Fast spin-echo anatomic images were obtained, followed by sequential acquisition of three-dimensional gradient-echo T2*- and T1-weighted images. Automated registration was applied to align regions of interest of the entire placenta, fetal liver, and maternal liver. Results were compared by using a two-tailed unpaired Student t test. R1 and R2* values were derived for each tissue. MR imaging–based oxygen-hemoglobin dissociation curves were constructed by nonlinear least square fitting of 1 minus the change in R2*divided by R2*at baseline as a function of R1 to a sigmoid-shaped curve. The apparent P50 (oxygen tension at which hemoglobin is 50% saturated) value was derived from the curves, calculated as the R1 scaled value (x) at which the change in R2* divided by R2*at baseline scaled (y) equals 0.5. RESULTS: The apparent P50 values were significantly lower in fetal liver than in maternal liver for both gestation stages (day 14.5: 21% ± 5 [P = .04] and day 17.5: 41% ± 7 [P < .0001]). The placenta showed a reduction of 18% ± 4 in mean apparent P50 values from day 14.5 to day 17.5 (P = .003). Reproduction of the MR imaging–based oxygen-hemoglobin dissociation curves with a shorter protocol that excluded the hypoxic periods was demonstrated. CONCLUSION: MR imaging–based oxygen-hemoglobin dissociation curves and oxygen-hemoglobin affinity information were derived for pregnant mice by using 9.4-T MR imaging, which suggests a potential to overcome the need for direct sampling of fetal or maternal blood. Online supplemental material is available for this article
Optimizing automated preprocessing streams for brain morphometric comparisons across multiple primate species
Get PDFINTRODUCTION

MR techniques have delivered images of brains from a wide array of species, ranging from invertebrates to birds to elephants and whales. However, their potential to serve as a basis for comparative brain morphometric investigations has rarely been tapped so far (Christidis and Cox, 2006; Van Essen & Dierker, 2007), which also hampers a deeper understanding of the mechanisms behind structural alterations in neurodevelopmental disorders (Kochunov et al., 2010). One of the reasons for this is the lack of computational tools suitable for morphometrci comparisons across multiple species. In this work, we aim to characterize this gap, taking primates as an example.

METHODS

Using a legacy dataset comprising MR scans from eleven species of haplorhine primates acquired on the same scanner (Rilling & Insel, 1998), we tested different automated processing streams, focusing on denoising and brain segmentation. Newer multi-species datasets are not currently available, so our experiments with this decade-old dataset (which had a very low signal-to-noise ratio by contemporary standards) can serve to highlight the lower boundary of the current possibilities of automated processing pipelines. After manual orientation into Talairach space, an automated bias correction was performed using CARET (Van Essen et al., 2001) before the brains were extracted with FSL BET (Smith, 2002; Fig. 1) and either smoothed by an isotropic Gaussian Kernel, FSL SUSAN (Smith, 1996), an anisotropic diffusion filter (Perona & Malik, 1990), an optimized Rician non-local means filter (Gaser & Coupé, 2010), or not at all (Fig. 2 & 3). Segmentation of the brains (Fig. 2 & 4) was performed separately by either FSL FAST (Zhang, 2001) without atlas priors, or using an Adaptive Maximum A Posteriori Approach (Rajapakse et al., 1997). Finally, the white matter surface was extracted with CARET, and inspected for anatomical and topological correctness. 

RESULTS

Figure 3 shows that noise reduction was generally necessary but, at least for these noisy data, anisotropic filtering (SUSAN, diffusion filter, Rician filter) provided little improvement over simple isotropic filtering. While several segmentations worked well in individual species, our focus was on cross-species optimization of the processing pipeline, and none of the tested segmentations performed uniformly well in all 11 species. The performance could be improved by some of the denoising approaches and by deviating systematically from the default parameters recommended for processing human brains (cf. Fig. 4). Depending on the size of the brains and on the processing path, it took a double-core 2.4GHz iMac from about two minutes (squirrel monkeys) to half an hour (humans) to generate the white matter surface from the T1 image. Nonetheless, the resulting surfaces always necessitated topology correction and - often considerable - manual cleanup. 


CONCLUSIONS

Automated processing pipelines for surface-based morphometry still require considerable adaptations to reach optimal performance across brains of multiple species, even within primates (cf. Fig. 5). However, most contemporary datasets have a better signal-to-noise ratio than the ones used here, which provides for better segmentations and cortical surface reconstructions. Considering further that cross-scanner variability is well below within-species differences (Stonnington, 2008), the prospects look good for comparative evolutionary analyses of cortical parameters, and gyrification in particular. In order to succeed, however, computational efforts on comparative morphometry depend on high-quality imaging data from multiple species being more widely available.

ACKNOWLEDGMENTS

D.M, R.D, & C.G are supported by the German BMBF grant 01EV0709.


REFERENCES

Christidis, P & Cox, RW (2006), A Step-by-Step Guide to Cortical Surface Modeling of the Nonhuman Primate Brain Using FreeSurfer, Proc Human Brain Mapping Annual Meeting, http://afni.nimh.nih.gov/sscc/posters/file.2006-06-01.4536526043 .
Gaser, C & Coupé, P (2010), Impact of Non-local Means filtering on Brain Tissue Segmentation, OHBM 2010, Abstract 1770.
Kochunov, P & al. (2010), Mapping primary gyrogenesis during fetal development in primate brains: high-resolution in utero structural MRI study of fetal brain development in pregnant baboons, Frontiers in Neurogenesis, in press, DOI: 10.3389/fnins.2010.00020.
Perona, P & Malik J (1990), Scale space and edge detection using anisotropic diffusion, IEEE Trans Pattern Anal Machine Intell, vol. 12, no. 7, pp. 629-639.
Rajapakse, JC & al. (1997), Statistical approach to segmentation of single-channel cerebral MR images, IEEE Trans Med Imaging, vol. 16, no. 2, pp. 176-186.
Rilling, JK & Insel TR (1998), Evolution of the cerebellum in primates: differences in relative volume among monkeys, apes and humans. Brain Behav. Evol. 52, 308-314 doi:10.1159/000006575. Dataset available at http://www.fmridc.org/f/fmridc/77.html .
Smith, SM (1996), Flexible filter neighbourhood designation, Proc. 13th Int. Conf. on Pattern Recognition, vol. 1, pp. 206-212.
Smith, SM (2002), Fast robust automated brain extraction, Hum Brain Mapp, vol. 17, no. 3, pp. 143-155.
Stonnington, CM & al. (2008), Interpreting scan data acquired from multiple scanners: a study with Alzheimers disease, Neuroimage, vol. 39, no. 3, pp. 1180-1185.
Van Essen, DC & al. (2001), An Integrated Software System for Surface-based Analyses of Cerebral Cortex, J Am Med Inform Assoc, vol. 8, no. 5, pp. 443-459.
Van Essen, DC & Dierker DL (2007), Surface-based and probabilistic atlases of primate cerebral cortex, Neuron, vol. 56, no. 2, pp. 209-225.
Zhang, Y & al. (2001), Segmentation of brain MR images through a hidden Markov random field model and the expectation maximization algorithm, IEEE Trans Med Imaging, vol. 20, no. 1, pp. 45-57.

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Chromatin establishes an immature version of neuronal protocadherin selection during the naive-to-primed conversion of pluripotent stem cells.
Get PDFIn the mammalian genome, the clustered protocadherin (cPCDH) locus provides a paradigm for stochastic gene expression with the potential to generate a unique cPCDH combination in every neuron. Here we report a chromatin-based mechanism that emerges during the transition from the naive to the primed states of cell pluripotency and reduces, by orders of magnitude, the combinatorial potential in the human cPCDH locus. This mechanism selectively increases the frequency of stochastic selection of a small subset of cPCDH genes after neuronal differentiation in monolayers, 10-month-old cortical organoids and engrafted cells in the spinal cords of rats. Signs of these frequent selections can be observed in the brain throughout fetal development and disappear after birth, except in conditions of delayed maturation such as Down's syndrome. We therefore propose that a pattern of limited cPCDH-gene expression diversity is maintained while human neurons still retain fetal-like levels of maturation
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