scholarly journals Test-retest reliability and long-term stability of 3-tissue constrained spherical deconvolution methods for analyzing diffusion MRI data

2019 ◽  
Author(s):  
Benjamin T. Newman ◽  
Thijs Dhollander ◽  
Kristen A. Reynier ◽  
Matthew B. Panzer ◽  
T. Jason Druzgal
Keyword(s):  
White Matter ◽  
Grey Matter ◽  
Tissue Microstructure ◽  
Term Stability ◽  
Long Term Stability ◽  
Constrained Spherical Deconvolution ◽  
Spherical Deconvolution ◽  
Brain Microstructure ◽  
Tissue Compartments

AbstractPurposeSeveral recent studies have utilized a 3-tissue constrained spherical deconvolution pipeline to obtain quantitative metrics of brain tissue microstructure from diffusion-weighted MRI data. The three tissue compartments, comprising white matter-, grey matter-, and CSF-like (free water) signals, are potentially useful in the evaluation of brain microstructure in a range of pathologies. However, the reliability and long-term stability of these metrics has not yet been evaluated.MethodsThis study examined estimates of whole brain microstructure for the three tissue compartments, in three separate test-retest cohorts. Each cohort has different lengths of time between baseline and retest, ranging from within the same scanning session in the shortest interval to three months in the longest interval. Each cohort was also collected with different acquisition parameters.ResultsThe CSF-like compartment displayed the greatest reliability across all cohorts, with intraclass correlation coefficient (ICC) values being above 0.95 in each cohort. White matter-like and grey matter-like compartments both demonstrated very high reliability in the immediate cohort (both ICC>0.90), however this declined in the 3 month interval cohort to both compartments having ICC>0.80. Regional CSF-like signal fraction was examined in bilateral hippocampus and had an ICC>0.80 in each cohort.ConclusionThe 3-tissue CSD techniques provide reliable and stable estimates of tissue microstructure composition, up to 3 months longitudinally in a control population. This forms an important basis for further investigations utilizing 3-tissue CSD techniques to track changes in microstructure across a variety of brain pathologies.

scholarly journals Evaluating the performance of 3-tissue constrained spherical deconvolution pipelines for within-tumor tractography

2019 ◽  
Author(s):  
Hannelore Aerts ◽  
Thijs Dhollander ◽  
Daniele Marinazzo
Keyword(s):  
White Matter ◽  
Tumor Tissue ◽  
Diffusion Tensor ◽  
Orientation Distribution ◽  
Constrained Spherical Deconvolution ◽  
Spherical Deconvolution ◽  
Fiber Orientation Distribution ◽  
Tissue Compartments ◽  
Diffusion Tensor Imaging Dti ◽  
Single Shell

AbstractThe use of diffusion MRI (dMRI) for assisting in the planning of neurosurgery has become increasingly common practice, allowing to non-invasively map white matter pathways via tractography techniques. Limitations of earlier pipelines based on the diffusion tensor imaging (DTI) model have since been revealed and improvements were made possible by constrained spherical deconvolution (CSD) pipelines. CSD allows to resolve a full white matter (WM) fiber orientation distribution (FOD), which can describe so-called “crossing fibers”: complex local geometries of WM tracts, which DTI fails to model. This was found to have a profound impact on tractography results, with substantial implications for presurgical decision making and planning. More recently, CSD itself has been extended to allow for modeling of other tissue compartments in addition to the WM FOD, typically resulting in a 3-tissue CSD model. It seems likely this may improve the capability to resolve WM FODs in the presence of infiltrating tumor tissue. In this work, we evaluated the performance of 3-tissue CSD pipelines, with a focus on within-tumor tractography. We found that a technique named single-shell 3-tissue CSD (SS3T-CSD) successfully allowed tractography within infiltrating gliomas, without increasing existing single-shell dMRI acquisition requirements.

Individual differences in white and grey matter structure associated with verbal habits of thought

2019 ◽  
Author(s):  
Justin C. Hayes ◽  
Katherine L Alfred ◽  
Rachel Pizzie ◽  
Joshua S. Cetron ◽  
David J. M. Kraemer
Keyword(s):  
Individual Differences ◽  
White Matter ◽  
Cognitive Processing ◽  
Grey Matter ◽  
Structural Changes ◽  
Structural Integrity ◽  
Diffusion Tensor ◽  
Self Report ◽  
White Matter Tracts

Modality specific encoding habits account for a significant portion of individual differences reflected in functional activation during cognitive processing. Yet, little is known about how these habits of thought influence long-term structural changes in the brain. Traditionally, habits of thought have been assessed using self-report questionnaires such as the visualizer-verbalizer questionnaire. Here, rather than relying on subjective reports, we measured habits of thought using a novel behavioral task assessing attentional biases toward picture and word stimuli. Hypothesizing that verbal habits of thought are reflected in the structural integrity of white matter tracts and cortical regions of interest, we used diffusion tensor imaging and volumetric analyses to assess this prediction. Using a whole-brain approach, we show that word bias is associated with increased volume in several bilateral language regions, in both white and grey matter parcels. Additionally, connectivity within white matter tracts within an a priori speech production network increased as a function of word bias. These results demonstrate long-term structural and morphological differences associated with verbal habits of thought.

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