Flexible, dense and porous chitosan and alginate membranes containing the standardized extract of Arrabidaea chica Verlot for the treatment of skin lesions.

The combination of chitosan (C) with alginate (A) has been explored for the production of dressings due to the positive results on wound healing. CA films can show a dense or porous flexible structure, with characteristics tunable for different applications. Porosity and flexibility can be achieved, respectively, by the addition of surfactants such as Kolliphor® P188 (P) and silicone-based compounds as Silpuran® 2130 A/B (S). Furthermore, composite matrices of these polysaccharides have potential applications as devices for releasing bioactive compounds to skin lesions. The purpose of this study was to evaluate the physicochemical and biological characteristics of flexible dense and porous CA membranes incorporating the standardized extract of Arrabidaea chica Verlot (A. chica), and also to analyze the release mechanism of the extract from different membrane formulations. The results show that the inclusion of P in the formulation allows obtaining porous matrices, promotes greater homogeneity of the mixture of the silicone gel with the suspension of polysaccharides, and increases the swelling of the polymer matrix. All formulations presented high stability, reaching a maximum mass loss of 18% after seven days. The formulations with S showed the best performance in terms of flexibility and strain at break. The presence of A. chica standardized extract did not affect negatively the characteristics of the membranes. Incorporation efficiencies of the bioactive compound above 87% were achieved, and the addition of P and S to the membrane formulation changed the release of the A. chica extract kinetics. In addition, the developed formulations did not significantly affect Vero cells proliferation.

Lifespan Trajectories of White Matter Changes in Rhesus Monkeys.

Progress in neurodevelopmental brain research has been achieved through the use of animal models. Such models not only help understanding biological changes that govern brain development, maturation and aging, but are also essential for identifying possible mechanisms of neurodevelopmental and age-related chronic disorders, and to evaluate possible interventions with potential relevance to human disease. Genetic relationship of rhesus monkeys to humans makes those animals a great candidate for such models. With the typical lifespan of 25 years, they undergo cognitive maturation and aging that is similar to this observed in humans. Quantitative structural neuroimaging has been proposed as one of the candidate in vivo biomarkers for tracking white matter brain maturation and aging. While lifespan trajectories of white matter changes have been mapped in humans, such knowledge is not available for nonhuman primates. Here, we analyze and model lifespan trajectories of white matter microstructure using in vivo diffusion imaging in a sample of 44 rhesus monkeys. We report quantitative parameters (including slopes and peaks) of lifespan trajectories for 8 individual white matter tracts. We show different trajectories for cellular and extracellular microstructural imaging components that are associated with white matter maturation and aging, and discuss similarities and differences between those in humans and rhesus monkeys, the importance of our findings, and future directions for the field. Significance Statement: Quantitative structural neuroimaging has been proposed as one of the candidate in vivo biomarkers for tracking brain maturation and aging. While lifespan trajectories of structural white matter changes have been mapped in humans, such knowledge is not available for rhesus monkeys. We present here results of the analysis and modeling of the lifespan trajectories of white matter microstructure using in vivo diffusion imaging in a sample of 44 rhesus monkeys (age 4-27). We report and anatomically map lifespan changes related to cellular and extracellular microstructural components that are associated with white matter maturation and aging.

Inter-site and inter-scanner diffusion MRI data harmonization.

We propose a novel method to harmonize diffusion MRI data acquired from multiple sites and scanners, which is imperative for joint analysis of the data to significantly increase sample size and statistical power of neuroimaging studies. Our method incorporates the following main novelties: i) we take into account the scanner-dependent spatial variability of the diffusion signal in different parts of the brain; ii) our method is independent of compartmental modeling of diffusion (e.g., tensor, and intra/extra cellular compartments) and the acquired signal itself is corrected for scanner related differences; and iii) inter-subject variability as measured by the coefficient of variation is maintained at each site. We represent the signal in a basis of spherical harmonics and compute several rotation invariant spherical harmonic features to estimate a region and tissue specific linear mapping between the signal from different sites (and scanners). We validate our method on diffusion data acquired from seven different sites (including two GE, three Philips, and two Siemens scanners) on a group of age-matched healthy subjects. Since the extracted rotation invariant spherical harmonic features depend on the accuracy of the brain parcellation provided by Freesurfer, we propose a feature based refinement of the original parcellation such that it better characterizes the anatomy and provides robust linear mappings to harmonize the dMRI data. We demonstrate the efficacy of our method by statistically comparing diffusion measures such as fractional anisotropy, mean diffusivity and generalized fractional anisotropy across multiple sites before and after data harmonization. We also show results using tract-based spatial statistics before and after harmonization for independent validation of the proposed methodology. Our experimental results demonstrate that, for nearly identical acquisition protocol across sites, scanner-specific differences can be accurately removed using the proposed method.

Multi-shell diffusion signal recovery from sparse measurements.

For accurate estimation of the ensemble average diffusion propagator (EAP), traditional multi-shell diffusion imaging (MSDI) approaches require acquisition of diffusion signals for a range of b-values. However, this makes the acquisition time too long for several types of patients, making it difficult to use in a clinical setting. In this work, we propose a new method for the reconstruction of diffusion signals in the entire q-space from highly undersampled sets of MSDI data, thus reducing the scan time significantly. In particular, to sparsely represent the diffusion signal over multiple q-shells, we propose a novel extension to the framework of spherical ridgelets by accurately modeling the monotonically decreasing radial component of the diffusion signal. Further, we enforce the reconstructed signal to have smooth spatial regularity in the brain, by minimizing the total variation (TV) norm. We combine these requirements into a novel cost function and derive an optimal solution using the Alternating Directions Method of Multipliers (ADMM) algorithm. We use a physical phantom data set with known fiber crossing angle of 45° to determine the optimal number of measurements (gradient directions and b-values) needed for accurate signal recovery. We compare our technique with a state-of-the-art sparse reconstruction method (i.e., the SHORE method of Cheng et al. (2010)) in terms of angular error in estimating the crossing angle, incorrect number of peaks detected, normalized mean squared error in signal recovery as well as error in estimating the return-to-origin probability (RTOP). Finally, we also demonstrate the behavior of the proposed technique on human in vivo data sets. Based on these experiments, we conclude that using the proposed algorithm, at least 60 measurements (spread over three b-value shells) are needed for proper recovery of MSDI data in the entire q-space.

Gray matter alterations in early aging: a diffusion magnetic resonance imaging study.

Many studies have observed altered neurofunctional and structural organization in the aging brain. These observations from functional neuroimaging studies show a shift in brain activity from the posterior to the anterior regions with aging (PASA model), as well as a decrease in cortical thickness, which is more pronounced in the frontal lobe followed by the parietal, occipital, and temporal lobes (retrogenesis model). However, very little work has been done using diffusion MRI (dMRI) with respect to examining the structural tissue alterations underlying these neurofunctional changes in the gray matter. Thus, for the first time, we propose to examine gray matter changes using diffusion MRI in the context of aging. In this work, we propose a novel dMRI based measure of gray matter "heterogeneity" that elucidates these functional and structural models (PASA and retrogenesis) of aging from the viewpoint of diffusion MRI. In a cohort of 85 subjects (all males, ages 15-55 years), we show very high correlation between age and "heterogeneity" (a measure of structural layout of tissue in a region-of-interest) in specific brain regions. We examine gray matter alterations by grouping brain regions into anatomical lobes as well as functional zones. Our findings from dMRI data connects the functional and structural domains and confirms the "retrogenesis" hypothesis of gray matter alterations while lending support to the neurofunctional PASA model of aging in addition to showing the preservation of paralimbic areas during healthy aging.

Sexually dimorphic white matter geometry abnormalities in adolescent onset schizophrenia.

The normal human brain is characterized by a pattern of gross anatomical asymmetry. This pattern, known as the "torque", is associated with a sexual dimorphism: The male brain tends to be more asymmetric than that of the female. This fact, along with well-known sex differences in brain development (faster in females) and onset of psychosis (earlier with worse outcome in males), has led to the theory that schizophrenia is a disorder in which sex-dependent abnormalities in the development of brain torque, the correlate of the capacity for language, cause alterations in interhemispheric connectivity, which are causally related to psychosis (Crow TJ, Paez P, Chance SE. 2007. Callosal misconnectivity and the sex difference in psychosis. Int Rev Psychiatry. 19(4):449-457.). To provide evidence toward this theory, we analyze the geometry of interhemispheric white matter connections in adolescent-onset schizophrenia, with a particular focus on sex, using a recently introduced framework for white matter geometry computation in diffusion tensor imaging data (Savadjiev P, Kindlmann GL, Bouix S, Shenton ME, Westin CF. 2010. Local white geometry from diffusion tensor gradients. Neuroimage. 49(4):3175-3186.). Our results reveal a pattern of sex-dependent white matter geometry abnormalities that conform to the predictions of Crow's torque theory and correlate with the severity of patients' symptoms. To the best of our knowledge, this is the first study to associate geometrical differences in white matter connectivity with torque in schizophrenia.

Prediction of live birth in frozen-thawed single blastocyst transfer cycles by pre-freeze and post-thaw morphology.

STUDY QUESTION: What pre-freeze and post-thaw morphological parameters can be used to predict live birth outcomes after frozen-thawed blastocyst transfer cycles? SUMMARY ANSWER: Pre-freeze blastocoele expansion and trophectoderm (TE) grade and post-thaw degree of re-expansion are the most significant predictors of live birth in frozen-thawed blastocyst transfer cycles. WHAT IS KNOWN ALREADY: Currently, blastocoele re-expansion after thawing is used to indicate blastocyst cryosurvival and reproductive potential. The predictive roles of other pre-freeze and post-thaw morphological parameters are neglected. STUDY DESIGN, SIZE, DURATION: This was a retrospective study of all the patients who received a frozen-thawed single blastocyst transfer (n = 1089) at our clinic between March 2008 and October 2011. PARTICIPANTS/MATERIALS, SETTING, METHODS: Pre-freeze morphological parameters analyzed for all blastocysts included grade of blastocoele expansion, inner cell mass and TE. A group of blastocysts (n = 243) were also graded for post-thaw parameters: degree of blastocoele re-expansion, viability and cell contour. Univariate and multivariate generalized estimating equations (GEEs) models were used to identify the confounders that statistically significantly affected live birth outcomes and to investigate the independent effect of significant pre-freeze and post-thaw morphological parameters. Stepwise logistic regression analysis was used to select the best independent morphological predictors of live birth. Pearson correlations and linear regression analyses were performed to determine the relationship between morphological parameters and possible covariates. MAIN RESULTS AND THE ROLE OF CHANCE: Multivariate GEE models estimated that the odds of live birth increased by ∼36% for each grade of expansion (P = 0.0061) and decreased by 29% for blastocysts with grade B TE compared with grade A TE (P = 0.0099). Furthermore, the odds of live birth increased by ∼39% (P = 0.0042) for each 10% increase in degree of re-expansion. Blastocoele expansion and TE grade were selected as the most significant pre-freeze morphological predictors of live birth and degree of re-expansion was selected as the best post-thaw parameter for prediction of live birth. LIMITATIONS, REASONS FOR CAUTION: Blastocysts with poorer grades of morphology were not cryopreserved or transferred, limiting the ability to generalize our findings for grades of morphology not included in this study. WIDER IMPLICATIONS OF THE FINDINGS: Blastocysts with higher pre-freeze grades of expansion and TE, irrespective of day of cryopreservation, should be given priority when thawing. Subsequently, re-expanding blastocysts, assessed within 2-4 h, with >60% viability should be transferred. STUDY FUNDING/COMPETING INTEREST(S): No external funding was obtained for this study. There was no competing interest. TRIAL REGISTRATION NUMBER: not applicable.

Human middle longitudinal fascicle: variations in patterns of anatomical connections.

Based on high-resolution diffusion tensor magnetic resonance imaging (DTI) tractographic analyses in 39 healthy adult subjects, we derived patterns of connections and measures of volume and biophysical parameters, such as fractional anisotropy (FA) for the human middle longitudinal fascicle (MdLF). Compared to previous studies, we found that the cortical connections of the MdLF in humans appear to go beyond the superior temporal (STG) and angular (AG) gyri, extending to the temporal pole (TP), superior parietal lobule (SPL), supramarginal gyrus, precuneus and the occipital lobe (including the cuneus and lateral occipital areas). Importantly, the MdLF showed a striking lateralized pattern with predominant connections between the TP, STG and AG on the left and TP, STG and SPL on the right hemisphere. In light of the results of the present study, and of the known functional role of the cortical areas interconnected by the MdLF, we suggested that this fiber pathway might be related to language, high order auditory association, visuospatial and attention functions.

DIFFEOMORPHIC POINT SET REGISTRATION USING NON-STATIONARY MIXTURE MODELS.

This paper investigates a diffeomorphic point-set registration based on non-stationary mixture models. The goal is to improve the non-linear registration of anatomical structures by representing each point as a general non-stationary kernel that provides information about the shape of that point. Our framework generalizes work done by others that use stationary models. We achieve this by integrating the shape at each point when calculating the point-set similarity and transforming it according to the calculated deformation. We also restrict the non-rigid transform to the space of symmetric diffeomorphisms. Our algorithm is validated in synthetic and human datasets in two different applications: fiber bundle and lung airways registration. Our results shows that non-stationary mixture models are superior to Gaussian mixture models and methods that do not take into account the shape of each point.

A review of magnetic resonance imaging and diffusion tensor imaging findings in mild traumatic brain injury.

Mild traumatic brain injury (mTBI), also referred to as concussion, remains a controversial diagnosis because the brain often appears quite normal on conventional computed tomography (CT) and magnetic resonance imaging (MRI) scans. Such conventional tools, however, do not adequately depict brain injury in mTBI because they are not sensitive to detecting diffuse axonal injuries (DAI), also described as traumatic axonal injuries (TAI), the major brain injuries in mTBI. Furthermore, for the 15 to 30 % of those diagnosed with mTBI on the basis of cognitive and clinical symptoms, i.e., the "miserable minority," the cognitive and physical symptoms do not resolve following the first 3 months post-injury. Instead, they persist, and in some cases lead to long-term disability. The explanation given for these chronic symptoms, i.e., postconcussive syndrome, particularly in cases where there is no discernible radiological evidence for brain injury, has led some to posit a psychogenic origin. Such attributions are made all the easier since both posttraumatic stress disorder (PTSD) and depression are frequently co-morbid with mTBI. The challenge is thus to use neuroimaging tools that are sensitive to DAI/TAI, such as diffusion tensor imaging (DTI), in order to detect brain injuries in mTBI. Of note here, recent advances in neuroimaging techniques, such as DTI, make it possible to characterize better extant brain abnormalities in mTBI. These advances may lead to the development of biomarkers of injury, as well as to staging of reorganization and reversal of white matter changes following injury, and to the ability to track and to characterize changes in brain injury over time. Such tools will likely be used in future research to evaluate treatment efficacy, given their enhanced sensitivity to alterations in the brain. In this article we review the incidence of mTBI and the importance of characterizing this patient population using objective radiological measures. Evidence is presented for detecting brain abnormalities in mTBI based on studies that use advanced neuroimaging techniques. Taken together, these findings suggest that more sensitive neuroimaging tools improve the detection of brain abnormalities (i.e., diagnosis) in mTBI. These tools will likely also provide important information relevant to outcome (prognosis), as well as play an important role in longitudinal studies that are needed to understand the dynamic nature of brain injury in mTBI. Additionally, summary tables of MRI and DTI findings are included. We believe that the enhanced sensitivity of newer and more advanced neuroimaging techniques for identifying areas of brain damage in mTBI will be important for documenting the biological basis of postconcussive symptoms, which are likely associated with subtle brain alterations, alterations that have heretofore gone undetected due to the lack of sensitivity of earlier neuroimaging techniques. Nonetheless, it is noteworthy to point out that detecting brain abnormalities in mTBI does not mean that other disorders of a more psychogenic origin are not co-morbid with mTBI and equally important to treat. They arguably are. The controversy of psychogenic versus physiogenic, however, is not productive because the psychogenic view does not carefully consider the limitations of conventional neuroimaging techniques in detecting subtle brain injuries in mTBI, and the physiogenic view does not carefully consider the fact that PTSD and depression, and other co-morbid conditions, may be present in those suffering from mTBI. Finally, we end with a discussion of future directions in research that will lead to the improved care of patients diagnosed with mTBI.

Sparse multi-shell diffusion imaging.

Diffusion magnetic resonance imaging (dMRI) is an important tool that allows non-invasive investigation of neural architecture of the brain. The data obtained from these in-vivo scans provides important information about the integrity and connectivity of neural fiber bundles in the brain. A multi-shell imaging (MSI) scan can be of great value in the study of several psychiatric and neurological disorders, yet its usability has been limited due to the long acquisition times required. A typical MSI scan involves acquiring a large number of gradient directions for the 2 (or more) spherical shells (several b-values), making the acquisition time significantly long for clinical application. In this work, we propose to use results from the theory of compressive sampling and determine the minimum number of gradient directions required to attain signal reconstruction similar to a traditional MSI scan. In particular, we propose a generalization of the single shell spherical ridgelets basis for sparse representation of multi shell signals. We demonstrate its efficacy on several synthetic and in-vivo data sets and perform quantitative comparisons with solid spherical harmonics based representation. Our preliminary results show that around 20-24 directions per shell are enough for robustly recovering the diffusion propagator.

Trophectoderm morphology: an important parameter for predicting live birth after single blastocyst transfer.

BACKGROUND: In order to select the best blastocyst for transfer, in humans, three morphological parameters have routinely been used, i.e. degree of blastocoele expansion and appearance of both the trophectoderm (TE) and the inner cell mass (ICM). Although it has been shown that blastocysts with highest scores for all three parameters achieve highest implantation rates, their independent ability to predict pregnancy outcome remains unclear. METHOD: This study is a retrospective analysis of 1117 fresh day 5 single blastocyst transfers and their live birth outcome related to each morphological parameter. RESULTS: All three parameters had a significant effect on live birth however, once adjusted for known significant confounders, it was shown that TE was the only statistically significant independent predictor of live birth outcome. CONCLUSIONS: This study has shown, for the first time, the predictive strength of TE grade over ICM for selecting the best blastocyst for embryo replacement. It may be that, even though ICM is important, a strong TE layer is essential at this stage of embryo development, allowing successful hatching and implantation.

A diffusion tensor imaging study of the anterior limb of the internal capsule in schizophrenia.

Frontal-subcortical cognitive and limbic feedback loops modulate higher cognitive functioning. The final step in these feedback loops is the thalamo-cortical projection through the anterior limb of the internal capsule (AL-IC). Using diffusion tensor imaging (DTI), we evaluated abnormalities in the AL-IC fiber tract in schizophrenia. Participants comprised 16 chronic schizophrenia patients and 19 male, normal controls, who were group matched for handedness, age, and parental socioeconomic status, and underwent DTI on a 1.5 Tesla GE system. We measured the diffusion indices, fractional anisotropy (FA), mean diffusivity (MD), radial diffusivity (RD), and axial diffusivity (AD), and manually segmented, based on FA maps, AL-IC volume, normalized for intracranial contents (ICC). The results showed a significant reduction in the ICC-corrected volume of the AL-IC in schizophrenia, but did not show diffusion measure group differences in the AL-IC in FA, MD, RD or AD. In addition, in the schizophrenia patients, AL-IC FA correlated positively with performance on measures of spatial and verbal declarative/episodic memory, and right AL-IC ICC-corrected volume correlated positively with more perseverative responses on the Wisconsin Card Sort Test (WCST). We found a reduction in AL-IC ICC-corrected volume in schizophrenia, without FA, MD, RD or AD group differences, implicating the presence of a structural abnormality in schizophrenia in this subcortical white matter region which contains important cognitive, and limbic feedback pathways that modulate prefrontal cortical function. Despite not demonstrating a group difference in FA, we found that AL-IC FA was a good predictor of spatial and verbal declarative/episodic memory performance in schizophrenia.

Obstetric outcomes after transfer of vitrified blastocysts.

BACKGROUND: It has been claimed that the risks to the child resulting from vitrification as compared with the slow-freezing technique, may be higher owing to the high concentrations of potentially toxic cryoprotectants. We therefore retrospectively compared the obstetric and neonatal outcomes in a cohort of children born after transfer of vitrified blastocysts, fresh blastocysts and slow-frozen early cleavage stage embryos. METHODS: All children born after transfer of vitrified blastocysts (n = 106), fresh blastocysts (n = 207) and slow-frozen early cleavage stage embryos (n = 206) during the period January 2006 to May 2008 at Fertility Center Scandinavia were included. Data on obstetric and neonatal outcomes were obtained from medical records from the antenatal and delivery clinics. RESULTS: For singletons, there were no significant differences between the groups in gestational age, mortality or birth defects. After adjustment for parity and BMI, birthweight was significantly higher in singletons born after transfer of vitrified blastocysts as compared with after transfer of fresh blastocysts (median 3560 versus 3510 g, P = 0.0311). More singletons born after transfer of fresh blastocysts were small for gestational age compared with singletons born after transfer of vitrified blastocysts (12.1 versus 3.0%, P = 0.0085). A higher rate of major post-partum haemorrhage was observed in the vitrified blastocyst group as compared with the other two groups (25.0 versus 6.0 and 7.5%). CONCLUSIONS: No adverse neonatal outcomes were observed in children born after transfer of vitrified, as compared with fresh blastocysts or after transfer of slow-frozen early cleavage stage embryos.

Re-analysis of 166 embryos not transferred after PGS with advanced reproductive maternal age as indication.

BACKGROUND: In a randomized controlled study aiming to test the effectiveness of preimplantation genetic screening (PGS) in women of advanced maternal age, embryos diagnosed as chromosomally abnormal and those with no diagnosis were fixed for reanalysis. The aim of this study was to determine how well the chromosomal constitution of one biopsied blastomere reflects the status of the entire embryo. METHODS: One hundred and seventy-three embryos diagnosed as chromosomally abnormal, 22 with no PGS result and four degenerated embryos originally diagnosed as normal were fixed and reanalysed by fluorescence in situ hybridization. RESULTS: In total, 199 embryos were fixed, of which 166 were successfully reanalysed. One hundred and sixty embryos were found to be chromosomally abnormal; 48 of the reanalysed embryos with an initial diagnosis (149) had at least one cell with exactly the same chromosomal constitution shown in the first PGS analysis (34.2%). The reanalysis confirmed the initial overall chromosomally abnormal status of the embryo in 95.9% of the cases. Of all chromosomally abnormal embryos, 4.1% were diagnosed as false positive. The risk for false negative rate was at least 4.1%. CONCLUSIONS: PGS seems to be a good method for selecting against chromosomally abnormal embryos but not for determining an embryo's exact chromosomal constitution.

Sequential anisotropic multichannel Wiener filtering with Rician bias correction applied to 3D regularization of DWI data.

It has been shown that the tensor calculation is very sensitive to the presence of noise in the acquired images, yielding to very low quality Diffusion Tensor Images (DTI) data. Recent investigations have shown that the noise present in the Diffusion Weighted Images (DWI) causes bias effects on the DTI data which cannot be corrected if the noise characteristic is not taken into account. One possible solution is to increase the minimum number of acquired measurements (which is 7) to several tens (or even several hundreds). This has the disadvantage of increasing the acquisition time by one (or two) orders of magnitude, making the process inconvenient for a clinical setting. We here proposed a turn-around procedure for which the number of acquisitions is maintained but, the DWI data are filtered prior to determining the DTI. We show a significant reduction on the DTI bias by means of a simple and fast procedure which is based on linear filtering; well-known drawbacks of such filters are circumvented by means of anisotropic neighborhoods and sequential application of the filter itself. Information of the first order probability density function of the raw data, namely, the Rice distribution, is also included. Results are shown both for synthetic and real datasets. Some error measurements are determined in the synthetic experiments, showing how the proposed scheme is able to reduce them. It is worth noting a 50% increase in the linear component for real DTI data, meaning that the bias in the DTI is considerably reduced. A novel fiber smoothness measure is defined to evaluate the resulting tractography for real DWI data. Our findings show that after filtering, fibers are considerably smoother on the average. Execution times are very low as compared to other reported approaches which allows for a real-time implementation.

Diffusion tractography of the fornix in schizophrenia.

BACKGROUND: White matter fiber tracts, especially those interconnecting the frontal and temporal lobes, are likely implicated in pathophysiology of schizophrenia. Very few studies, however, have focused on the fornix, a compact bundle of white matter fibers, projecting from the hippocampus to the septum, anterior nucleus of the thalamus and the mamillary bodies. Diffusion Tensor Imaging (DTI), and a new post-processing method, fiber tractography, provides a unique opportunity to visualize and to quantify entire trajectories of fiber bundles, such as the fornix, in vivo. We applied these techniques to quantify fornix diffusion anisotropy in schizophrenia. METHODS: DTI images were used to evaluate the left and the right fornix in 36 male patients diagnosed with chronic schizophrenia and 35 male healthy individuals, group matched on age, parental socioeconomic status, and handedness. Regions of interest were drawn manually, blind to group membership, to guide tractography, and fractional anisotropy (FA), a measure of fiber integrity, was calculated and averaged over the entire tract for each subject. The Doors and People test (DPT) was used to evaluate visual and verbal memory, combined recall and combined recognition. RESULTS: Analysis of variance was performed and findings demonstrated a difference between patients with schizophrenia and controls for fornix FA (p=0.006). Protected post-hoc independent sample t-tests demonstrated a bilateral FA decrease in schizophrenia, compared with control subjects (left side: p=0.048; right side p=0.006). Higher fornix FA was statistically significantly correlated with DPT and measures of combined visual memory (r=0.554, p=0.026), combined verbal memory (r=0.647, p=0.007), combined recall (r=0.516, p=0.041), and combined recognition (r=0.710, p=0.002) for the control group. No such statistically significant correlations were found in the patient group. CONCLUSIONS: Our findings show the utility of applying DTI and tractography to study white matter fiber tracts in vivo in schizophrenia. Specifically, we observed a bilateral disruption in fornix integrity in schizophrenia, thus broadening our understanding of the pathophysiology of this disease.

Signal LMMSE estimation from multiple samples in MRI and DT-MRI.

A method to estimate the magnitude MR data from several noisy samples is presented. It is based on the Linear Minimum Mean Squared Error (LMMSE) estimator for the Rician noise model when several scanning repetitions are available. This method gives a closed-form analytical solution that takes into account the probability distribution of the data as well as the existing level of noise, showing a better performance than methods such as the average or the median.