A tract-specific approach to assessing white matter in preterm infants.

Diffusion-weighted imaging (DWI) is becoming an increasingly important tool for studying brain development. DWI analyses relying on manually-drawn regions of interest and tractography using manually-placed waypoints are considered to provide the most accurate characterisation of the underlying brain structure. However, these methods are labour-intensive and become impractical for studies with large cohorts and numerous white matter (WM) tracts. Tract-specific analysis (TSA) is an alternative WM analysis method applicable to large-scale studies that offers potential benefits. TSA produces a skeleton representation of WM tracts and projects the group's diffusion data onto the skeleton for statistical analysis. In this work we evaluate the performance of TSA in analysing preterm infant data against results obtained from native space tractography and tract-based spatial statistics. We evaluate TSA's registration accuracy of WM tracts and assess the agreement between native space data and template space data projected onto WM skeletons, in 12 tracts across 48 preterm neonates. We show that TSA registration provides better WM tract alignment than a previous protocol optimised for neonatal spatial normalisation, and that TSA projects FA values that match well with values derived from native space tractography. We apply TSA for the first time to a preterm neonatal population to study the effects of age at scan on WM tracts around term equivalent age. We demonstrate the effects of age at scan on DTI metrics in commissural, projection and association fibres. We demonstrate the potential of TSA for WM analysis and its suitability for infant studies involving multiple tracts

Structural MRI predicts clinical progression in presymptomatic genetic frontotemporal dementia: findings from the GENetic Frontotemporal dementia Initiative (GENFI) cohort

Abstract Biomarkers that can predict disease progression in individuals with genetic frontotemporal dementia are urgently needed. We aimed to identify whether baseline MRI-based grey and white matter abnormalities are associated with different clinical progression profiles in presymptomatic mutation carriers in the GENetic Frontotemporal dementia Initiative. 387 mutation carriers were included (160 GRN, 160 C9orf72, 67 MAPT), together with 240 non-carrier cognitively normal controls. Cortical and subcortical grey matter volumes were generated using automated parcellation methods on volumetric 3 T T1-weighted MRI scans, while white matter characteristics were estimated using diffusion tensor imaging. Mutation carriers were divided into two disease stages based on their global CDR®+NACC-FTLD score: presymptomatic (0 or 0.5) and fully symptomatic (1 or greater). W-scores in each grey matter volumes and white matter diffusion measures were computed to quantify the degree of abnormality compared to controls for each presymptomatic carrier, adjusting for their age, sex, total intracranial volume, and scanner type. Presymptomatic carriers were classified as “normal” or “abnormal” based on whether their grey matter volume and white matter diffusion measure w-scores were above or below the cut point corresponding to the 10th percentile of the controls. We then compared the change in disease severity between baseline and one year later in both the “normal” and “abnormal” groups within each genetic subtype, as measured by the CDR®+NACC-FTLD sum-of-boxes score and revised Cambridge Behavioural Inventory total score. Overall, presymptomatic carriers with normal regional w-scores at baseline did not progress clinically as much as those with abnormal regional w-scores. Having abnormal grey or white matter measures at baseline was associated with a statistically significant increase in the CDR®+NACC-FTLD of up to 4 points in C9orf72 expansion carriers, and 5 points in the GRN group as well as a statistically significant increase in the revised Cambridge Behavioural Inventory of up to 11 points in MAPT, 10 points in GRN, and 8 points in C9orf72 mutation carriers. Baseline regional brain abnormalities on MRI in presymptomatic mutation carriers are associated with different profiles of clinical progression over time. These results may be helpful to inform stratification of participants in future trials

PopTract: Population-Based Tractography

White matter fiber tractography plays a key role in the in vivo understanding of brain circuitry. For tract-based comparison of a population of images, a common approach is to first generate an atlas by averaging, after spatial normalization, all images in the population, and then perform tractography using the constructed atlas. The reconstructed fiber trajectories form a common geometry onto which diffusion properties of each individual subject can be projected based on the corresponding locations in the subject native space. However, in the case of high angular resolution diffusion imaging (HARDI), where modeling fiber crossings is an important goal, the above-mentioned averaging method for generating an atlas results in significant error in the estimation of local fiber orientations and causes a major loss of fiber crossings. These limitatitons have significant impact on the accuracy of the reconstructed fiber trajectories and jeopardize subsequent tract-based analysis. As a remedy, we present in this paper a more effective means of performing tractography at a population level. Our method entails determining a bipolar Watson distribution at each voxel location based on information given by all images in the population, giving us not only the local principal orientations of the fiber pathways, but also confidence levels of how reliable these orientations are across subjects. The distribution field is then fed as an input to a probabilistic tractography framework for reconstructing a set of fiber trajectories that are consistent across all images in the population. We observe that the proposed method, called PopTract, results in significantly better preservation of fiber crossings, and hence yields better trajectory reconstruction in the atlas space

Methodological considerations on tract-based spatial statistics (TBSS)

Having gained a tremendous amount of popularity since its introduction in 2006, tract-based spatial statistics (TBSS) can now be considered as the standard approach for voxel-based analysis (VBA) of diffusion tensor imaging (DTI) data. Aiming to improve the sensitivity, objectivity, and interpretability of multi-subject DTI studies, TBSS includes a skeletonization step that alleviates residual image misalignment and obviates the need for data smoothing. Although TBSS represents an elegant and user-friendly framework that tackles numerous concerns existing in conventional VBA methods, it has limitations of its own, some of which have already been detailed in recent literature. In this work, we present general methodological considerations on TBSS and report on pitfalls that have not been described previously. In particular, we have identified specific assumptions of TBSS that may not be satisfied under typical conditions. Moreover, we demonstrate that the existence of such violations can severely affect the reliability of TBSS results. With TBSS being used increasingly, it is of paramount importance to acquaint TBSS users with these concerns, such that a well-informed decision can be made as to whether and how to pursue a TBSS analysis. Finally, in addition to raising awareness by providing our new insights, we provide constructive suggestions that could improve the validity and increase the impact of TBSS drastically

Generalizations, extensions and applications for principal component analysis

Principal component analysis (PCA) is one of the most important dimension reduction technique. It is widely used in many applications including economics, finance and medical research. In this research, several novel generalizations of PCA are proposed to adapt the technique to more complicated scenarios. In the first project, we propose a principal surface model for manifold-like datasets in 3D space. In the second part, a new concept of graphical intra-class correlation coefficient (GICC) is defined and a Markov Chain Monte Carlo Expectation-Maximization (mcmcEM) algorithm is used for likelihood optimization. In the third part, we propose multilevel binary principal component analysis (MBPCA) models for finding the principal components of multilevel binary dataset. A variational expectation maximization algorithm is used for likelihood optimization

Statistical Techniques For Addressing The Clinico-Radiological Paradox In Multiple Sclerosis

Medical imaging technology has allowed for unparalleled insight into the structure and function of the human brain, giving clinicians powerful new tools for disease diagnosis and monitoring. Yet the complex and high-dimensional nature of imaging data makes computational analysis challenging. In multiple sclerosis (MS), this complexity is typically simplified by identifying regions of visible tissue damage and measuring spatial extent. However, many common radiological measures have been shown to be only weakly associated with clinical outcomes (a discovery that has been referred to as “the clinico-radiological paradox”). We attempt to bridge this gap by developing statistical methods capable of extracting clinically relevant information from MRI scans in MS. Here, we discuss three such techniques: a texture modeling approach to improve research on lesion dynamics; a biomarker detection algorithm to support diagnostic decision-making; and a flexible multi-modal group differences test to facilitate exploration of subtle disease processes. The performance of these methods is illustrated using simulated and real data, and the opportunities and obstacles for their clinical use are discussed

Development of maxilla and palate in patients with bilateral orofacial clefts after neonatal suture

Cíle: Časná neonatální cheiloplastika je nový modifikovaný operační postup, který se využívá k léčbě jedinců s oboustrannými rozštěpy rtu a patra (BCLP). Stěžejním cílem diplomové práce bylo zhodnotit růst a vývoj maxily a patra u jedinců s BCLP po podstoupení neonatální cheiloplastiky. Dalším cílem bylo popsat morfologické odlišnosti mezi jedinci s kompletním oboustranným rozštěpem rtu a patra (cBCLP) a oboustranným rozštěpem rtu a patra s kombinovaným mostem (BCLP + KM). Analyzován byl vliv velikosti premaxily na růst a vývoj horní čelisti a patra v prvním roce života. Materiál a metody: Padesát dentálních sádrových odlitků, získaných od 25 jedinců s BCLP, bylo analyzováno metodami klasické a geometrické morfometrie (metrická analýza, CPD- DCA, mnohorozměrná statistika). Analyzovány byly dva odlitky v odlišných věkových kategoriích. První byl získán před provedením neonatální cheiloplastiky (T0 průměrně 4,5 dne) a druhý před podstoupením palatoplastiky (T1 průměrně 11,5 měsíců). Výsledky: Dle výsledků klasické morfometrie došlo ke konvergenci maxilárních segmentů směrem k premaxile, přičemž rozštěpové štěrbiny se následkem toho zmenšily. Po podstoupení neonatální sutury rtu maxilární segmenty rostly do délky a nedocházelo k negativnímu zúžení dentoalveolárního oblouku. Velikost premaxily...Objectives: Early neonatal cheiloplasty is a new modified surgery protocol for treating patients with bilatelar cleft lip and palate (BCLP). Althought there are known a lot of benefits of this surgery, its influence on facial growth is still studied. Goals are to evaluate: (1) palatal morphology before and one year after neonatal cheiloplasty, (2) growth maxilla and palate using classic and geometric morphometry, (3) morphological differences between complete BCLP (cBCLP) and BCLP with combined bridge (BCLP+B), (4) effect of premaxillary size on the growth of maxilla and palate. Materials and methods: Fifty virtual dental models of 25 cBCLP and BCLP+B patients were analysed using metric analysis, a coherent point drift - dense correspondence analysis (CPD- DCA) and multivariate statistic. Two plaster casts were taken from each patient, the first before neonatal cheiloplasty (mean age 4,5 days) and the second before palatoplasty (mean age 11,5 months). Results: The upper jaw segments converge towards premaxilla. This fact leads to reduction of alveolar cleft widht but the upper jaw segments has grown in lenght direction. There is no decrease of the dentoalveolar arc after early neonatal cheiloplasty. The size of premaxilla affects dimensions of anterior parts of the upper jaw segments. According to...Katedra antropologie a genetiky člověkaDepartment of Anthropology and Human GeneticsPřírodovědecká fakultaFaculty of Scienc