Random noise in Diffusion Tensor Imaging, its Destructive Impact and Some Corrections

The empirical origin of random noise is described, its influence on DTI variables is illustrated by a review of numerical and in vivo studies supplemented by new simulations investigating high noise levels. A stochastic model of noise propagation is presented to structure noise impact in DTI. Finally, basics of voxelwise and spatial denoising procedures are presented. Recent denoising procedures are reviewed and consequences of the stochastic model for convenient denoising strategies are discussed

Diffusion Tensor Imaging: Structural adaptive smoothing

Diffusion Tensor Imaging (DTI) data is characterized by a high noise level. Thus, estimation errors of quantities like anisotropy indices or the main diffusion direction used for fiber tracking are relatively large and may significantly confound the accuracy of DTI in clinical or neuroscience applications. Besides pulse sequence optimization, noise reduction by smoothing the data can be pursued as a complementary approach to increase the accuracy of DTI. Here, we suggest an anisotropic structural adaptive smoothing procedure, which is based on the Propagation-Separation method and preserves the structures seen in DTI and their different sizes and shapes. It is applied to artificial phantom data and a brain scan. We show that this method significantly improves the quality of the estimate of the diffusion tensor and hence enables one either to reduce the number of scans or to enhance the input for subsequent analysis such as fiber tracking

Diffusion Tensor Imaging as a Diagnostic and Research Tool: A Study on Preterm Infants

Diffusion tensor imaging (DTI) is an advanced magnetic resonance imaging (MRI) technique. DTI is based on free thermal motion (diffusion) of water molecules. The properties of diffusion can be represented using parameters such as fractional anisotropy, mean diffusivity, axial diffusivity, and radial diffusivity, which are calculated from DTI data. These parameters can be used to study the microstructure in fibrous structure such as brain white matter. The aim of this study was to investigate the reproducibility of region-of-interest (ROI) analysis and determine associations between white matter integrity and antenatal and early postnatal growth at term age using DTI. Antenatal growth was studied using both the ROI and tract-based spatial statistics (TBSS) method and postnatal growth using only the TBSS method. The infants included to this study were born below 32 gestational weeks or birth weight less than 1,501 g and imaged with a 1.5 T MRI system at term age. Total number of 132 infants met the inclusion criteria between June 2004 and December 2006. Due to exclusion criteria, a total of 76 preterm infants (ROI) and 36 preterm infants (TBSS) were accepted to this study. The ROI analysis was quite reproducible at term age. Reproducibility varied between white matter structures and diffusion parameters. Normal antenatal growth was positively associated with white matter maturation at term age. The ROI analysis showed associations only in the corpus callosum. Whereas, TBSS revealed associations in several brain white matter areas. Infants with normal antenatal growth showed more mature white matter compared to small for gestational age infants. The gestational age at birth had no significant association with white matter maturation at term age. It was observed that good early postnatal growth associated negatively with white matter maturation at term age. Growth-restricted infants seemed to have delayed brain maturation that was not fully compensated at term, despite catchup growth.Diffuusiotensorikuvaus diagnostisena ja tutkimustyökaluna keskostutkimuksessa Diffuusiotensorikuvaus (DTI) on magneettikuvauksen erikoistekniikka. DTI perustuu veden vapaaseen lämpöliikkeeseen (diffuusioon). Diffuusion ominaisuuksia voidaan esittää DTI-datasta laskettavien parametrien avulla. Tällaisia parametreja ovat esimerkiksi fraktionaalinen anisotropia, keskimääräinen diffusiviteetti, aksiaalinen ja radiaalinen diffusiviteetti. Näitä parametrejä voidaan käyttää säikeisten rakenteiden esimerkiksi aivojen valkoisen aineen tutkimiseen. Tässä tutkimuksessa selvitettiin keskosten aivojen diffuusiotensorikuvista tehtyjen mielenkiintoalueisiin (ROI) perustuvien mittausten toistettavuutta sekä tutkittiin valkoisen aineen kypsyyden ja raskauden aikaisen sekä varhaisen postnataalisen kasvun välistä yhteyttä. Raskauden aikaisen kasvun vaikutusta tutkittiin käyttäen sekä ROI- että TBSS-tekniikoita. Postnataalista kasvua tarkasteltiin ainoastaan TBSS-tekniikalla. Tähän tutkimukseen otettiin mukaan keskoset, jotka syntyivät ennen 32 raskausviikkoa tai joiden syntymäpaino oli alle 1,501 g sekä MRI kuvaus oli tehty lasketunajan kohdalla. Tutkimukseen hyväksyttiin kesäkuun 2004 ja joulukuun 2006 välillä 132 keskosta. Poissulkukriteerien takia 76 keskosta (ROI) ja 36 (TBSS) hyväksyttiin tähän tutkimukseen. ROI-analyysi osoittautui melko toistettavaksi lasketun ajan iässä. Toistettavuus vaihteli sekä valkoisen aineen rakenteiden että diffuusioparametrien välillä. Normaali raskauden aikainen kasvu liittyi hyvään valkoisen aineen kehitykseen lasketunajan kohdalla. ROI-tekniikalla yhteys havaittiin corpus callosumin alueella. TBSS-menetelmä puolestaan näytti yhteyden usealla eri valkoisen aineen alueella. Syntymähetken gestaatioiällä ei havaittu yhteyttä valkoisen aineen kehitysasteeseen lasketun ajan kohdalla. Hyvän varhaisen vaiheen postnataalisen kasvun havaittiin liittyvän heikompaan valkoisen aineen kehitysasteeseen lasketunajan kohdalla. Saavutuskasvu ei ollut korjannut raskauden aikaisen kasvuhäiriön vaikutusta aivojen kypsyyteen laskettuun aikaan mennessä.Siirretty Doriast

Doctor of Philosophy

dissertationDiffusion tensor MRI (DT-MRI or DTI) has been proven useful for characterizing biological tissue microstructure, with the majority of DTI studies having been performed previously in the brain. Other studies have shown that changes in DTI parameters are detectable in the presence of cardiac pathology, recovery, and development, and provide insight into the microstructural mechanisms of these processes. However, the technical challenges of implementing cardiac DTI in vivo, including prohibitive scan times inherent to DTI and measuring small-scale diffusion in the beating heart, have limited its widespread usage. This research aims to address these technical challenges by: (1) formulating a model-based reconstruction algorithm to accurately estimate DTI parameters directly from fewer MRI measurements and (2) designing novel diffusion encoding MRI pulse sequences that compensate for the higher-order motion of the beating heart. The model-based reconstruction method was tested on undersampled DTI data and its performance was compared against other state-of-the-art reconstruction algorithms. Model-based reconstruction was shown to produce DTI parameter maps with less blurring and noise and to estimate global DTI parameters more accurately than alternative methods. Through numerical simulations and experimental demonstrations in live rats, higher-order motion compensated diffusion-encoding was shown to successfully eliminate signal loss due to motion, which in turn produced data of sufficient quality to accurately estimate DTI parameters, such as fiber helix angle. Ultimately, the model-based reconstruction and higher-order motion compensation methods were combined to characterize changes in the cardiac microstructure in a rat model with inducible arterial hypertension in order to demonstrate the ability of cardiac DTI to detect pathological changes in living myocardium

The functional anatomy of white matter pathways for visual configuration learning

The role of the medial temporal lobes (MTL) in visuo-spatial learning has been extensively studied and documented in the neuroscientific literature. Numerous animal and human studies have demonstrated that the parahippocampal place area (PPA), which sits at the confluence of the parahippocampal and lingual gyri, is particularly important for learning the spatial configuration of objects in visually presented scenes. In current visuo-spatial processing models, the PPA sits downstream from the parietal lobes which are involved in multiple facets of spatial processing. Yet, direct input to the PPA from early visual cortex (EVC) is rarely discussed and poorly understood. This thesis adopted a multimodal neuroimaging analysis approach to study the functional anatomy of these connections. First, the pattern of structural connectivity between EVC and the MTL was explored by means of surface-based ‘connectomes’ constructed from diffusion MRI tractography in a cohort of 200 healthy young adults from the Human Connectome Project. Through this analysis, the PPA emerged as a primary recipient of EVC connections within the MTL. Second, a data-driven clustering analysis of the PPA’s connectivity to an extended cortical region (including EVC, retrosplenial cortex, and other areas) revealed multiple clusters with different connectivity profiles within the PPA. The two main clusters were located in the posterior and anterior portions of the PPA, with the posterior cluster preferentially connected to EVC. Motivated by this result, virtual tractography dissections were used to delineate the medial occipital longitudinal tract (MOLT), the white matter bundle connecting the PPA with EVC. The properties of this bundle and its relation to visual configuration learning were verified in a different, cross-sectional adult cohort of 90 subjects. Finally, the role of the MOLT in the visuo-spatial learning domain was further confirmed in the case of a stroke patient who, after bilateral occipital injury, exhibited deficits confined to this domain. The results presented in this work suggest that the MOLT should be included in current visuo-spatial processing models as it offers additional insight into how the MTL acquires and processes information for spatial learning

Pronounced structural and functional damage in early adult pediatric-onset multiple sclerosis with no or minimal clinical disability

Pediatric-onset multiple sclerosis (POMS) may represent a model of vulnerability to damage occurring during a period of active maturation of the human brain. Whereas adaptive mechanisms seem to take place in the POMS brain in the short-medium term, natural history studies have shown that these patients reach irreversible disability, despite slower progression, at a significantly younger age than adult-onset MS (AOMS) patients. We tested for the first time whether significant brain alterations already occurred in POMS patients in their early adulthood and with no or minimal disability (n = 15) in comparison with age- and disability-matched AOMS patients (n = 14) and to normal controls (NC, n = 20). We used a multimodal MRI approach by modeling, using FSL, voxelwise measures of microstructural integrity of white matter tracts and gray matter volumes with those of intra- and internetwork functional connectivity (FC) (analysis of variance, p â\u89¤ 0.01, corrected for multiple comparisons across space). POMS patients showed, when compared with both NC and AOMS patients, altered measures of diffusion tensor imaging (reduced fractional anisotropy and/or increased diffusivities) and higher probability of lesion occurrence in a clinically eloquent region for physical disability such as the posterior corona radiata. In addition, POMS patients showed, compared with the other two groups, reduced long-range FC, assessed from resting functional MRI, between default mode network and secondary visual network, whose interaction subserves important cognitive functions such as spatial attention and visual learning. Overall, this pattern of structural damage and brain connectivity disruption in early adult POMS patients with no or minimal clinical disability might explain their unfavorable clinical outcome in the long term