Browsing by Subject "TRACTOGRAPHY"

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  • Salo, Raimo A.; Belevich, Ilya; Jokitalo, Eija; Gröhn, Olli; Sierra, Alejandra (2021)
    Validation and interpretation of diffusion magnetic resonance imaging (dMRI) requires detailed understanding of the actual microstructure restricting the diffusion of water molecules. In this study, we used serial block-face scanning electron microscopy (SBEM), a three-dimensional electron microscopy (3D-EM) technique, to image seven white and grey matter volumes in the rat brain. SBEM shows excellent contrast of cellular membranes, which are the major components restricting the diffusion of water in tissue. Additionally, we performed 3D structure tensor (3D-ST) analysis on the SBEM volumes and parameterised the resulting orientation distributions using Watson and angular central Gaussian (ACG) probability distributions as well as spherical harmonic (SH) decomposition. We analysed how these parameterisations described the underlying orientation distributions and compared their orientation and dispersion with corresponding parameters from two dMRI methods, neurite orientation dispersion and density imaging (NODDI) and constrained spherical deconvolution (CSD). Watson and ACG parameterisations and SH decomposition captured well the 3D-ST orientation distributions, but ACG and SH better represented the distributions due to its ability to model asymmetric dispersion. The dMRI parameters corresponded well with the 3D-ST parameters in the white matter volumes, but the correspondence was less evident in the more complex grey matter. SBEM imaging and 3D-ST analysis also revealed that the orientation distributions were often not axially symmetric, a property neatly captured by the ACG distribution. Overall, the ability of SBEM to image diffusion barriers in intricate detail, combined with 3D-ST analysis and parameterisation, provides a step forward toward interpreting and validating the dMRI signals in complex brain tissue microstructure.
  • the PIPARI Study Group; Lahti, Katri; Saunavaara, Virva; Munck, Petriina; Uusitalo, Karoliina; Koivisto, Mari; Parkkola, Riitta; Haataja, Leena (2020)
    Abstract Aim Very preterm children born less than 32 weeks of gestation are at risk for motor difficulties such as cerebral palsy and developmental coordination disorder. This study explores the association between diffusion tensor imaging metrics at term and motor outcomes at 11 years of age. Methods A cohort of 37 very preterm infants (mean gestational age 29 4/7, SD 2 0/7) born in 2004-2006 in Turku University Hospital underwent diffusion tensor imaging at term. A region-of-interest analysis of fractional anisotropy and mean diffusivity was performed. Motor outcomes at 11 years of age were measured with the Movement Assessment Battery for Children ? Second Edition. Results The diffusion metrics of the corpus callosum (genu p=0.005, splenium p=0.049), the left corona radiata (p=0.035) and the right optic radiation (p=0.017) were related to later motor performance. Mean diffusivity decreased and fractional anisotropy increased in proportion to the improving performance. Conclusion The diffusion metrics of the genu and splenium of the corpus callosum, the left corona radiata and the right optic radiation at term were associated with motor skills at 11 years of age. Diffusion tensor imaging should be further studied as a potential tool in recognising children at risk for motor impairment.
  • Sairanen, Viljami; Ocampo-Pineda, Mario; Granziera, Cristina; Schiavi, Simona; Daducci, Alessandro (2022)
    A B S T R A C T The white matter structures of the human brain can be represented using diffusion-weighted MRI tractography. Unfortunately, tractography is prone to find false-positive streamlines causing a severe decline in its specificity and limiting its feasibility in accurate structural brain connectivity analyses. Filtering algorithms have been pro-posed to reduce the number of invalid streamlines but the currently available filtering algorithms are not suitable to process data that contains motion artefacts which are typical in clinical research. We augmented the Con-vex Optimization Modelling for Microstructure Informed Tractography (COMMIT) algorithm to adjust for these signals drop-out motion artefacts. We demonstrate with comprehensive Monte-Carlo whole brain simulations and in vivo infant data that our robust algorithm is capable of properly filtering tractography reconstructions despite these artefacts. We evaluated the results using parametric and non-parametric statistics and our results demonstrate that if not accounted for, motion artefacts can have severe adverse effects in human brain structural connectivity analyses as well as in microstructural property mappings. In conclusion, the usage of robust filtering methods to mitigate motion related errors in tractogram filtering is highly beneficial, especially in clinical stud-ies with uncooperative patient groups such as infants. With our presented robust augmentation and open-source implementation, robust tractogram filtering is readily available.
  • Shams, Boshra; Wang, Ziqian; Roine, Timo; Aydogan, Dogu Baran; Vajkoczy, Peter; Lippert, Christoph; Picht, Thomas; Fekonja, Lucius S. (2022)
    Shams et al. report that glioma patients' motor status is predicted accurately by diffusion MRI metrics along the corticospinal tract based on support vector machine method, reaching an overall accuracy of 77%. They show that these metrics are more effective than demographic and clinical variables. Along tract statistics enables white matter characterization using various diffusion MRI metrics. These diffusion models reveal detailed insights into white matter microstructural changes with development, pathology and function. Here, we aim at assessing the clinical utility of diffusion MRI metrics along the corticospinal tract, investigating whether motor glioma patients can be classified with respect to their motor status. We retrospectively included 116 brain tumour patients suffering from either left or right supratentorial, unilateral World Health Organization Grades II, III and IV gliomas with a mean age of 53.51 +/- 16.32 years. Around 37% of patients presented with preoperative motor function deficits according to the Medical Research Council scale. At group level comparison, the highest non-overlapping diffusion MRI differences were detected in the superior portion of the tracts' profiles. Fractional anisotropy and fibre density decrease, apparent diffusion coefficient axial diffusivity and radial diffusivity increase. To predict motor deficits, we developed a method based on a support vector machine using histogram-based features of diffusion MRI tract profiles (e.g. mean, standard deviation, kurtosis and skewness), following a recursive feature elimination method. Our model achieved high performance (74% sensitivity, 75% specificity, 74% overall accuracy and 77% area under the curve). We found that apparent diffusion coefficient, fractional anisotropy and radial diffusivity contributed more than other features to the model. Incorporating the patient demographics and clinical features such as age, tumour World Health Organization grade, tumour location, gender and resting motor threshold did not affect the model's performance, revealing that these features were not as effective as microstructural measures. These results shed light on the potential patterns of tumour-related microstructural white matter changes in the prediction of functional deficits.
  • Fekonja, Lucius S.; Wang, Ziqian; Cacciola, Alberto; Roine, Timo; Aydogan, D. Baran; Mewes, Darius; Vellmer, Sebastian; Vajkoczy, Peter; Picht, Thomas (2022)
    Tumors and their location distinctly alter both local and global brain connectivity within the ipsilesional hemisphere of glioma patients. Gliomas that infiltrate networks and systems, such as the motor system, often lead to substantial functional impairment in multiple systems. Network-based statistics (NBS) allow to assess local network differences and graph theoretical analyses enable investigation of global and local network properties. Here, we used network measures to characterize glioma-related decreases in structural connectivity by comparing the ipsi- with the contralesional hemispheres of patients and correlated findings with neurological assessment. We found that lesion location resulted in differential impairment of both short and long connectivity patterns. Network analysis showed reduced global and local efficiency in the ipsilesional hemisphere compared to the contralesional hemispheric networks, which reflect the impairment of information transfer across different regions of a network.
  • Salo, Raimo A.; Belevich, Ilya; Manninen, Eppu; Jokitalo, Eija; Gröhn, Olli; Sierra, Alejandra (2018)
    Diffusion tensor imaging (DTI) reveals microstructural features of grey and white matter non-invasively. The contrast produced by DTI, however, is not fully understood and requires further validation. We used serial block-face scanning electron microscopy (SBEM) to acquire tissue metrics, i.e., anisotropy and orientation, using three-dimensional Fourier transform-based (3D-FT) analysis, to correlate with fractional anisotropy and orientation in DTI. SBEM produces high-resolution 3D data at the mesoscopic scale with good contrast of cellular membranes. We analysed selected samples from cingulum, corpus callosum, and perilesional cortex of sham-operated and traumatic brain injury (TBI) rats. Principal orientations produced by DTI and 3D-FT in all samples were in good agreement. Anisotropy values showed similar patterns of change in corresponding DTI and 3D-FT parameters in sham-operated and TBI rats. While DTI and 3D-FT anisotropy values were similar in grey matter, 3D-FT anisotropy values were consistently lower than fractional anisotropy values from DTI in white matter. We also evaluated the effect of resolution in 3D-FT analysis. Despite small angular differences in grey matter samples, lower resolution datasets provided reliable results, allowing for analysis of larger fields of view. Overall, 3D SBEM allows for more sophisticated validation studies of diffusion imaging contrast from a tissue microstructural perspective.
  • Sihvonen, Aleksi J.; Virtala, Paula; Thiede, Anja; Laasonen, Marja; Kujala, Teija (2021)
    Current views on the neural network subserving reading and its deficits in dyslexia rely largely on evidence derived from functional neuroimaging studies. However, understanding the structural organization of reading and its aberrations in dyslexia requires a hodological approach, studies of which have not provided consistent findings. Here, we adopted a whole brain hodological approach and investigated relationships between structural white matter connectivity and reading skills and phonological processing in a cross-sectional study of 44 adults using individual local connectome matrix from diffusion MRI data. Moreover, we performed quantitative anisotropy aided differential tractography to uncover structural white matter anomalies in dyslexia (23 dyslexics and 21 matched controls) and their correlation to reading-related skills. The connectometry analyses indicated that reading skills and phonological processing were both associated with corpus callosum (tapetum), forceps major and minor, as well as cerebellum bilaterally. Furthermore, the left dorsal and right thalamic pathways were associated with phonological processing. Differential tractography analyses revealed structural white matter anomalies in dyslexics in the left ventral route and bilaterally in the dorsal route compared to the controls. Connectivity deficits were also observed in the corpus callosum, forceps major, vertical occipital fasciculus and corticostriatal and thalamic pathways. Altered structural connectivity in the observed differential tractography results correlated with poor reading skills and phonological processing. Using a hodological approach, the current study provides novel evidence for the extent of the reading-related connectome and its aberrations in dyslexia. The results conform current functional neuroanatomical models of reading and developmental dyslexia but provide novel network-level and tract-level evidence on structural connectivity anomalies in dyslexia, including the vertical occipital fasciculus.
  • Roine, T.; Roine, U.; Tokola, A.; Balk, M. H.; Mannerkoski, M.; Åberg, Laura E.; Lönnqvist, T.; Autti, T. (2019)
    BACKGROUND AND PURPOSE: We used diffusion MR imaging to investigate the structural brain connectivity networks in juvenile neuronal ceroid lipofuscinosis, a neurodegenerative lysosomal storage disease of childhood. Although changes in conventional MR imaging are typically not visually apparent in children aged
  • Sihvonen, Aleksi J.; Ripolles, Pablo; Särkämö, Teppo; Leo, Vera; Rodriguez-Fornells, Antoni; Saunavaara, Jani; Parkkola, Riitta; Soinila, Seppo (2017)
    Acquired amusia provides a unique opportunity to investigate the fundamental neural architectures of musical processing due to the transition from a functioning to defective music processing system. Yet, the white matter (WM) deficits in amusia remain systematically unexplored. To evaluate which WM structures form the neural basis for acquired amusia and its recovery, we studied 42 stroke patients longitudinally at acute, 3-month, and 6-month post-stroke stages using DTI [tract-based spatial statistics (TBSS) and deterministic tractography (DT)] and the Scale and Rhythm subtests of the Montreal Battery of Evaluation of Amusia (MBEA). Non-recovered amusia was associated with structural damage and subsequent degeneration in multiple WM tracts including the right inferior fronto-occipital fasciculus (IFOF), arcuate fasciculus (AF), inferior longitudinal fasciculus (ILF), uncinate fasciculus (UF), and frontal aslant tract (FAT), as well as in the corpus callosum (CC) and its posterior part (tapetum). In a linear regression analysis, the volume of the right IFOF was the main predictor of MBEA performance across time. Overall, our results provide a comprehensive picture of the large-scale deficits in intra- and interhemispheric structural connectivity underlying amusia, and conversely highlight which pathways are crucial for normal music perception.