Farshid Sepehrband

Quantitative Comparison of Reconstruction Methods for Intra-Voxel Fiber Recovery From Diffusion MRI

Validation is arguably the bottleneck in the diffusion magnetic resonance imaging (MRI) community. This paper evaluates and compares 20 algorithms for recovering the local intra-voxel fiber structure from diffusion MRI data and is based on the results of the “HARDI reconstruction challenge” organized in the context of the “ISBI 2012” conference. Evaluated methods encompass a mixture of classical techniques well known in the literature such as diffusion tensor, Q-Ball and diffusion spectrum imaging, algorithms inspired by the recent theory of compressed sensing and also brand new approaches proposed for the first time at this contest. To quantitatively compare the methods under controlled conditions, two datasets with known ground-truth were synthetically generated and two main criteria were used to evaluate the quality of the reconstructions in every voxel: correct assessment of the number of fiber populations and angular accuracy in their orientation. This comparative study investigates the behavior of every algorithm with varying experimental conditions and highlights strengths and weaknesses of each approach. This information can be useful not only for enhancing current algorithms and develop the next generation of reconstruction methods, but also to assist physicians in the choice of the most adequate technique for their studies.

Brain tissue compartment density estimated using diffusion-weighted MRI yields tissue parameters consistent with histology

We examined whether quantitative density measures of cerebral tissue consistent with histology can be obtained from diffusion magnetic resonance imaging (MRI). By incorporating prior knowledge of myelin and cell membrane densities, absolute tissue density values were estimated from relative intracellular and intraneurite density values obtained from diffusion MRI. The NODDI (neurite orientation distribution and density imaging) technique, which can be applied clinically, was used. Myelin density estimates were compared with the results of electron and light microscopy in ex vivo mouse brain and with published density estimates in a healthy human brain. In ex vivo mouse brain, estimated myelin densities in different subregions of the mouse corpus callosum were almost identical to values obtained from electron microscopy (diffusion MRI: 42 ± 6%, 36 ± 4%, and 43 ± 5%; electron microscopy: 41 ± 10%, 36 ± 8%, and 44 ± 12% in genu, body and splenium, respectively). In the human brain, good agreement was observed between estimated fiber density measurements and previously reported values based on electron microscopy. Estimated density values were unaffected by crossing fibers. Hum Brain Mapp 36:3687–3702, 2015.

Towards higher sensitivity and stability of axon diameter estimation with diffusion-weighted MRI

Diffusion‐weighted MRI is an important tool for in vivo and non‐invasive axon morphometry. The ActiveAx technique utilises an optimised acquisition protocol to infer orientationally invariant indices of axon diameter and density by fitting a model of white matter to the acquired data. In this study, we investigated the factors that influence the sensitivity to small‐diameter axons, namely the gradient strength of the acquisition protocol and the model fitting routine. Diffusion‐weighted ex. vivo images of the mouse brain were acquired using 16.4‐T MRI with high (Gmax of 300 mT/m) and ultra‐high (Gmax of 1350 mT/m) gradient strength acquisitions. The estimated axon diameter indices of the mid‐sagittal corpus callosum were validated using electron microscopy. In addition, a dictionary‐based fitting routine was employed and evaluated. Axon diameter indices were closer to electron microscopy measures when higher gradient strengths were employed. Despite the improvement, estimated axon diameter indices (a lower bound of ~ 1.8 μm) remained higher than the measurements obtained using electron microscopy (~1.2 μm). We further observed that limitations of pulsed gradient spin echo (PGSE) acquisition sequences and axonal dispersion could also influence the sensitivity with which axon diameter indices could be estimated. Our results highlight the influence of acquisition protocol, tissue model and model fitting, in addition to gradient strength, on advanced microstructural diffusion‐weighted imaging techniques.

Complement C5aR1 Signaling Promotes Polarization and Proliferation of Embryonic Neural Progenitor Cells through PKCζ.

The complement system, typically associated with innate immunity, is emerging as a key controller of nonimmune systems including in development, with recent studies linking complement mutations with neurodevelopmental disease. A key effector of the complement response is the activation fragment C5a, which, through its receptor C5aR1, is a potent driver of inflammation. Surprisingly, C5aR1 is also expressed during early mammalian embryogenesis; however, no clearly defined function is ascribed to C5aR1 in development. Here we demonstrate polarized expression of C5aR1 on the apical surface of mouse embryonic neural progenitor cells in vivo and on human embryonic stem cell-derived neural progenitors. We also show that signaling of endogenous C5a during mouse embryogenesis drives proliferation of neural progenitor cells within the ventricular zone and is required for normal brain histogenesis. C5aR1 signaling in neural progenitors was dependent on atypical protein kinase C ζ, a mediator of stem cell polarity, with C5aR1 inhibition reducing proliferation and symmetric division of apical neural progenitors in human and mouse models. C5aR1 signaling was shown to promote the maintenance of cell polarity, with exogenous C5a increasing the retention of polarized rosette architecture in human neural progenitors after physical or chemical disruption. Transient inhibition of C5aR1 during neurogenesis in developing mice led to behavioral abnormalities in both sexes and MRI-detected brain microstructural alterations, in studied males, demonstrating a requirement of C5aR1 signaling for appropriate brain development. This study thus identifies a functional role for C5a–C5aR1 signaling in mammalian neurogenesis and provides mechanistic insight into recently identified complement gene mutations and brain disorders. SIGNIFICANCE STATEMENT The complement system, traditionally known as a controller of innate immunity, now stands as a multifaceted signaling family with a broad range of physiological actions. These include roles in the brain, where complement activation is associated with diseases, including epilepsy and schizophrenia. This study has explored complement regulation of neurogenesis, identifying a novel relationship between the complement activation peptide C5a and the neural progenitor proliferation underpinning formation of the mammalian brain. C5a was identified as a regulator of cell polarity, with inhibition of C5a receptors during embryogenesis leading to abnormal brain development and behavioral deficits. This work demonstrates mechanisms through which dysregulation of complement causes developmental disease and highlights the potential risk of complement inhibition for therapeutic purposes in pregnancy.

Simple lossless and near-lossless medical image compression based on enhanced DPCM transformation

Medical images include information about human body which are used for different purposes such as surgical and diagnostic plans. Compression of medical images is used in some applications such as profiling patients data and transmission systems. Regard to importance of medical images information, lossless or near-lossless compression is preferred. Lossless JPEG, JPEG-LS and lossless version of JPEG2000 are few well-known methods for lossless compression. JPEG2000 is one of the latest and provides good compression ratio, however, it is complex [1]. In real time application which needs hardware implementation, low complex algorithm accelerates compression process. In this paper, a lossless and near-lossless compression method is introduced which is efficient due to its high compression ratio and simplicity. The method is consists of a new transformation method called Enhanced DPCM Transformation (EDT) which has a good energy compaction and a suitable Huffman encoding. After introducing the compression method, it is applied on different test cases and the results are evaluated.

Tissue Classification for PET/MRI Attenuation Correction Using Conditional Random Field and Image Fusion

Photon attenuation correction is a challenging task in the emerging hybrid PET/MRI medical imaging techniques because of the missing link between tissue attenuation coefficient and MRI signal. MRI-based tissue classification methods for attenuation correction have difficulties caused by the significantly different abilities of photon absorption in tissues with similar MRI signal, such as bone and air. We proposed a novel method of integrating the information from MRI and PET emission data to increase the tissue classification accuracy. A classifier based on conditional random field was trained using features extracted from fused MRI and uncorrected PET images. The efficacy of the proposed method was validated quantitatively on synthetic datasets. It was found that the inclusion of PET data improved the classifiers performance in terms of classification accuracy and PET image reconstruction quality.

The relation of structural integrity and task-related functional connectivity in the aging brain

The relations among structural integrity, functional connectivity (FC), and cognitive performance in the aging brain are still understudied. Here, we used multimodal and multivariate approaches to specifically examine age-related changes in task-related FC, gray-matter volumetrics, white-matter integrity, and performance. Our results are two-fold, showing (i) age-related differences in FC of the working memory network and (ii) age-related recruitment of a compensatory network associated with better accuracy on the task. Increased connectivity in the compensatory network correlates positively with preserved white-matter integrity in bilateral frontoparietal tracks and with larger gray-matter volume of right inferior parietal lobule. These findings demonstrate the importance of structural integrity and FC in working memory performance associated with healthy aging.

Parametric Probability Distribution Functions for Axon Diameters of Corpus Callosum.

Axon diameter is an important neuroanatomical characteristic of the nervous system that alters in the course of neurological disorders such as multiple sclerosis. Axon diameters vary, even within a fiber bundle, and are not normally distributed. An accurate distribution function is therefore beneficial, either to describe axon diameters that are obtained from a direct measurement technique (e.g., microscopy), or to infer them indirectly (e.g., using diffusion-weighted MRI). The gamma distribution is a common choice for this purpose (particularly for the inferential approach) because it resembles the distribution profile of measured axon diameters which has been consistently shown to be non-negative and right-skewed. In this study we compared a wide range of parametric probability distribution functions against empirical data obtained from electron microscopy images. We observed that the gamma distribution fails to accurately describe the main characteristics of the axon diameter distribution, such as location and scale of the mode and the profile of distribution tails. We also found that the generalized extreme value distribution consistently fitted the measured distribution better than other distribution functions. This suggests that there may be distinct subpopulations of axons in the corpus callosum, each with their own distribution profiles. In addition, we observed that several other distributions outperformed the gamma distribution, yet had the same number of unknown parameters; these were the inverse Gaussian, log normal, log logistic and Birnbaum-Saunders distributions.

Lens shape and refractive index distribution in type 1 diabetes

PURPOSE To compare lens dimensions and refractive index distributions in type 1 diabetes and age-matched control groups. METHODS There were 17 participants with type 1 diabetes, consisting of two subgroups (7 young [23 ± 4 years] and 10 older [54 ± 4 years] participants), with 23 controls (13 young, 24 ± 4 years; 10 older, 55 ± 4 years). For each participant, one eye was tested with relaxed accommodation. A 3T clinical magnetic resonance imaging scanner was used to image the eye, employing a multiple spin echo (MSE) sequence to determine lens dimensions and refractive index profiles along the equatorial and axial directions. RESULTS The diabetes group had significantly smaller lens equatorial diameters and larger lens axial thicknesses than the control group (diameter mean ± 95% confidence interval [CI]: diabetes group 8.65 ± 0.26 mm, control group 9.42 ± 0.18 mm; axial thickness: diabetes group 4.33 ± 0.30 mm, control group 3.80 ± 0.14 mm). These differences were also significant within each age group. The older group had significantly greater axial thickness than the young group (older group 4.35 ± 0.26 mm, young group 3.70 ± 0.25 mm). Center refractive indices of diabetes and control groups were not significantly different. There were some statistically significant differences between the refractive index fitting parameters of young and older groups, but not between diabetes and control groups of the same age. CONCLUSIONS Smaller lens diameters occurred in the diabetes groups than in the age-matched control groups. Differences in refractive index distribution between persons with and without diabetes are too small to have important effects on instruments measuring axial thickness.

lop-DWI: A Novel Scheme for Pre-Processing of Diffusion-Weighted Images in the Gradient Direction Domain.

We describe and evaluate a pre-processing method based on a periodic spiral sampling of diffusion-gradient directions for high angular resolution diffusion magnetic resonance imaging. Our pre-processing method incorporates prior knowledge about the acquired diffusion-weighted signal, facilitating noise reduction. Periodic spiral sampling of gradient direction encodings results in an acquired signal in each voxel that is pseudo-periodic with characteristics that allow separation of low-frequency signal from high frequency noise. Consequently, it enhances local reconstruction of the orientation distribution function used to define fiber tracks in the brain. Denoising with periodic spiral sampling was tested using synthetic data and in vivo human brain images. The level of improvement in signal-to-noise ratio and in the accuracy of local reconstruction of fiber tracks was significantly improved using our method.