Registration of low-SNR high-resolution diffusion-weighted images

This paper introduces a novel, high-speed scheme for intrasubject registration and segmentation of high-resolution multi-shot diffusion-weighted images. Compared to single-shot sequences, multi-shot have advantages in terms of improved spatial resolution and reduced eddy-current and susceptibility artifacts. However, these sequences have prolonged scan times increasing the risk of subject motion, and, a lower signal to noise ratio (SNR) with smaller voxel volumes. The proposed registration algorithm comprises a hybrid thresholding expectation-maximization segmentation method that can cope with the low-SNR, and registers diffusion-weighted to B0 images through fast detection and matching of features found in edge images derived from floating and reference images. We performed validations of the entire pipeline, including assessment of visual appearance by experts, consistency error computations, and analysis of the segmentation, using volunteer images, and found its performance to be comparable with, or exceeding, that of established solutions

Basal ganglia correlates of fatigue in young adults

Although the prevalence of chronic fatigue is approximately 20% in healthy individuals, there are no studies of brain structure that elucidate the neural correlates of fatigue outside of clinical subjects. We hypothesized that fatigue without evidence of disease might be related to changes in the basal ganglia and prefrontal cortex and be implicated in fatigue with disease. We aimed to identify the white matter structures of fatigue in young subjects without disease using magnetic resonance imaging (MRI). Healthy young adults (n = 883; 489 males and 394 females) were recruited. As expected, the degrees of fatigue and motivation were associated with larger mean diffusivity (MD) in the right putamen, pallidus and caudate. Furthermore, the degree of physical activity was associated with a larger MD only in the right putamen. Accordingly, motivation was the best candidate for widespread basal ganglia, whereas physical activity might be the best candidate for the putamen. A plausible mechanism of fatigue may involve abnormal function of the motor system, as well as areas of the dopaminergic system in the basal ganglia that are associated with motivation and reward

In vivo Diffusion Tensor Magnetic Resonance Tractography of the Sheep Brain : An Atlas of the Ovine White Matter Fiber Bundles

Diffusion Tensor Magnetic Resonance Imaging (DTI) allows to decode the mobility of water molecules in cerebral tissue, which is highly directional along myelinated fibers. By integrating the direction of highest water diffusion through the tissue, DTI Tractography enables a non-invasive dissection of brain fiber bundles. As such, this technique is a unique probe for in vivo characterization of white matter architecture. Unraveling the principal brain texture features of preclinical models that are advantageously exploited in experimental neuroscience is crucial to correctly evaluate investigational findings and to correlate them with real clinical scenarios. Although structurally similar to the human brain, the gyrencephalic ovine model has not yet been characterized by a systematic DTI study. Here we present the first in vivo sheep (ovis aries) tractography atlas, where the course of the main white matter fiber bundles of the ovine brain has been reconstructed. In the context of the EU's Horizon EDEN2020 project, in vivo brain MRI protocol for ovine animal models was optimized on a 1.5T scanner. High resolution conventional MRI scans and DTI sequences (b-value = 1,000 s/mm2, 15 directions) were acquired on ten anesthetized sheep o. aries, in order to define the diffusion features of normal adult ovine brain tissue. Topography of the ovine cortex was studied and DTI maps were derived, to perform DTI tractography reconstruction of the corticospinal tract, corpus callosum, fornix, visual pathway, and occipitofrontal fascicle, bilaterally for all the animals. Binary masks of the tracts were then coregistered and reported in the space of a standard stereotaxic ovine reference system, to demonstrate the consistency of the fiber bundles and the minimal inter-subject variability in a unique tractography atlas. Our results determine the feasibility of a protocol to perform in vivo DTI tractography of the sheep, providing a reliable reconstruction and 3D rendering of major ovine fiber tracts underlying different neurological functions. Estimation of fiber directions and interactions would lead to a more comprehensive understanding of the sheep's brain anatomy, potentially exploitable in preclinical experiments, thus representing a precious tool for veterinaries and researchers

Collaborative patch-based super-resolution for diffusion-weighted images

In this paper, a new single image acquisition super-resolution method is proposed to increase image resolution of diffusion weighted (DW) images. Based on a nonlocal patch-based strategy, the proposed method uses a non-diffusion image (b0) to constrain the reconstruction of DW images. An extensive validation is presented with a gold standard built on averaging 10 high-resolution DW acquis itions. A comparison with classical interpo- lation methods such as trilinear and B-spline demonstrates the competitive results of our proposed approach in termsofimprovementsonimagereconstruction,fractiona lanisotropy(FA)estimation,generalizedFAandangular reconstruction for tensor and high angular resolut ion diffusion imaging (HARDI) models. Besides, fi rst results of reconstructed ultra high resolution DW images are presented at 0.6 × 0.6 × 0.6 mm 3 and0.4×0.4×0.4mm 3 using our gold standard based on the average of 10 acquisitions, and on a single acquisition. Finally, fi ber tracking results show the potential of the proposed super-resolution approach to accurately analyze white matter brain architecture.We thank the reviewers for their useful comments that helped improve the paper. We also want to thank the Pr Louis Collins for proofreading this paper and his fruitful comments. Finally, we want to thank Martine Bordessoules for her help during image acquisition of DWI used to build the phantom. This work has been supported by the French grant "HR-DTI" ANR-10-LABX-57 funded by the TRAIL from the French Agence Nationale de la Recherche within the context of the Investments for the Future program. This work has been also partially supported by the French National Agency for Research (Project MultImAD; ANR-09-MNPS-015-01) and by the Spanish grant TIN2011-26727 from the Ministerio de Ciencia e Innovacion. This work benefited from the use of FSL (http://fsl.fmrib.ox.ac.uk/fsl/fslwiki/), FiberNavigator (code.google.com/p/fibernavigator/), MRtrix software (http://www. brain.org.au/software/mrtrix/) and ITKsnap (www.itk.org).Coupé, P.; Manjón Herrera, JV.; Chamberland, M.; Descoteaux, M.; Hiba, B. (2013). Collaborative patch-based super-resolution for diffusion-weighted images. NeuroImage. 83:245-261. https://doi.org/10.1016/j.neuroimage.2013.06.030S2452618

Магнитно-резонансная трактография: возможности и ограничения метода, современный подход к обработке данных

Purpose: systematization of the knowledge about diffusion tensor magnetic resonance tomography; analysis of literature related to current limitations of this method and possibilities of overcoming these limitations.Materials and methods. We have analyzed 74 publications (6 Проанализировано 74 публикации (6 Russian, 68 foreign), published in the time period from 1986 to 2021years.  More, than half of these articles were published in the last ten years, 19 studies-in the time period from 2016 to 2021years.Results. In this article we  represent the physical basis of diffusion weighted techniques of magnetic resonance tomography, principles of obtaining diffusion weighted images and diffusion tensor, cover the specific features of the probabilistic and deterministic approaches of the diffusion tensor MRI data processing, describe methods of evaluation of the diffusion characteristics of tissues in clinical practice. Article provides a thorough introduction to the reasons of existing limitations of diffusion tensor MRI and systematization the main developed approaches of overcoming these limitations, such as multi-tensor model, high angular resolution diffusion imaging, diffusion kurtosis visualization. The article consistently reviews the stages of data processing of diffusion tensor magnetic resonance tomography (preprocessing, processing and post processing). We also describe the special aspects of the main approaches to the quantitative data analysis of diffusion tensor magnetic resonance tomography (such as analysis of the region of interest, analysis of the total data amount, quantitative tractography).Conclusion. Magnetic resonance tractography is a unique technique for noninvasive in vivo visualization of brain white matter tracts and assessment of the structural integrity of their constituent axons. In the meantime this technique, which has found applications in numerous pathologies of central nervous system, has a number of significant limitations, and the main of them are the inability to adequately visualize the crossing fibers and the relatively low reproducibility of the results. Standardization of the data postprocessing algorithms, further upgrading of the magnetic resonance scanners and implementation of the alternative tractography methods have the potential of partially reducing of the current limitations.Цель исследования. Систематизация знаний о диффузионной тензорной магнитно-резонансной томографии; анализ литературы, касающейся существующих на сегодняшний момент ограничений метода и возможностей их преодоления.Материал и методы. Проанализировано 74 публикации (6 отечественных, 68 зарубежных), вышедших в свет в период с 1986 по 2021 год. Более половины работ было опубликовано в последнее десятилетие, 19 работ – в период с 2016 по 2021 год.Результаты. В статье изложены физические основы диффузионных методик магнитно-резонансной томографии, принципы получения диффузионно-взвешенных изображений и диффузионного тензора, отражены особенности вероятностного и детерминистского подходов к обработке данных диффузионной тензорной МРТ, а также методы оценки диффузионных характеристик тканей в клинической практике. Подробно рассмотрены причины имеющихся ограничений диффузионной тензорной МРТ, а также систематизированы основные разработанные приемы преодоления этих ограничений, таких как мультитензорная модель, диффузионная визуализация высокого углового разрешения, диффузионная спектральная визуализация, диффузионная куртозисная визуализация. Последовательно рассмотрены этапы обработки данных диффузионной тензорной магнитно-резонансной томографии (препроцессинг, процессинг и постпроцессинг). Отражены особенности основных подходов к количественному анализу данных диффузионной тензорной магнитно-резонансной томографии (таких как анализ области интереса, анализ всего объема данных, количественная трактография).Заключение. Магнитно-резонансная трактография – уникальная методика неинвазивной прижизненной визуализации проводящих путей головного мозга и оценки структурной целостности составляющих их аксонов, нашедшая применение при многих заболеваниях центральной нервной системы. В то же время эта методика имеет ряд существенных ограничений, основными из которых являются невозможность адекватной визуализации перекрещивающихся волокон и относительно низкая воспроизводимость результатов. Стандартизация алгоритмов постпроцессинга данных, дальнейшее совершенствование магнитнорезонансных томографов и внедрение альтернативных методов трактографии потенциально способны частично нивелировать имеющиеся в настоящее время недостатки

Detection of Pathologic Changes Following Traumatic Brain Injury Using Magnetic Resonance Imaging

Background: Approximately two percent of Finns have sequels after traumatic brain injury (TBI), and many TBI patients are young or middle-aged. The high rate of unemployment after TBI has major economic consequences for society, and traumatic brain injury often has remarkable personal consequences, as well. Structural imaging is often needed to support the clinical TBI diagnosis. Accurate early diagnosis is essential for successful rehabilition and, thus, may also influence the patient’s outcome. Traumatic axonal injury and cortical contusions constitute the majority of traumatic brain lesions. Several studies have shown magnetic resonance imaging (MRI) to be superior to computed tomography (CT) in the detection of these lesions. However, traumatic brain injury often leads to persistent symptoms even in cases with few or no findings in conventional MRI. Aims and methods: The aim of this prospective study was to clarify the role of conventional MRI in the imaging of traumatic brain injury, and to investigate how to improve the radiologic diagnostics of TBI by using more modern diffusion-weighted imaging (DWI) and diffusion tensor imaging (DTI) techniques. We estimated, in a longitudinal study, the visibility of the contusions and other intraparenchymal lesions in conventional MRI at one week and one year after TBI. We used DWI-based measurements to look for changes in the diffusivity of the normal-appearing brain in a case-control study. DTI-based tractography was used in a case-control study to evaluate changes in the volume, diffusivity, and anisotropy of the long association tracts in symptomatic TBI patients with no visible signs of intracranial or intraparenchymal abnormalities on routine MRI. We further studied the reproducibility of different tools to identify and measure white-matter tracts by using a DTI sequence suitable for clinical protocols. Results: Both the number and extent of visible traumatic lesions on conventional MRI diminished significantly with time. Slightly increased diffusion in the normal-appearing brain was a common finding at one week after TBI, but it was not significantly associated with the injury severity. Fractional anisotropy values, that represent the integrity of the white-matter tracts, were significantly diminished in several tracts in TBI patients compared to the control subjects. Compared to the cross-sectional ROI method, the tract-based analyses had better reproducibility to identify and measure white-matter tracts of interest by means of DTI tractography. Conclusions: As conventional MRI is still applied in clinical practice, it should be carried out soon after the injury, at least in symptomatic patients with negative CT scan. DWI-related brain diffusivity measurements may be used to improve the documenting of TBI. DTI tractography can be used to improve radiologic diagnostics in a symptomatic TBI sub-population with no findings on conventional MRI. Reproducibility of different tools to quantify fibre tracts vary considerably, which should be taken into consideration in the clinical DTI applications.Siirretty Doriast

Correcting for Motion between Acquisitions in Diffusion MR Imaging

The diffusion tensor (DT) and other diffusion models assume that each voxel corresponds to the same anatomical location in all the measurements. Movements and distortions violate this assumption and typically the images are realigned before model fitting. We propose a set of model-based methods to improve motion correction and avoid the errors that the traditional method introduces. The new methods are based on a three-step procedure to register DWI datasets, and use different reference images for DWIs with different gradient directions for registration, so the registrations take into account the contrast differences of measurements. Performance of the model-based registration techniques depends critically on outlier rejection. We develop new methods for fitting the diffusion tensor to diffusion MRI measurements in the presence of outliers by drawing on the RANSAC algorithm from computer vision. We compareone popularly used outlier rejection method RESTORE in the diffusion MRI literature with our new method. Then, we combine outlier rejection methods with model-based registration schemes, and compare the performance of motion correction with other methods. After aligning the dataset, we also update diffusion gradients for the registered datasets from both traditional and our methods, according to the transformations used in registrations. We develop and discuss a variety of registration evaluation methods using both synthetic and human-brain diffusion MRI datasets. Experiments demonstrate both quantitative and qualitative improvements using our new model-based methods