scholarly journals Quantitative diffusion tensor imaging analysis does not distinguish pediatric canines with mucopolysaccharidosis I from control canines

2017 ◽  
Vol 30 (5) ◽  
pp. 454-460
Author(s):  
Dana M Middleton ◽  
Jonathan Y Li ◽  
Steven D Chen ◽  
Leonard E White ◽  
Patricia I Dickson ◽  
...  

Purpose We compared fractional anisotropy and radial diffusivity measurements between pediatric canines affected with mucopolysaccharidosis I and pediatric control canines. We hypothesized that lower fractional anisotropy and higher radial diffusivity values, consistent with dysmyelination, would be present in the mucopolysaccharidosis I cohort. Methods Six canine brains, three affected with mucopolysaccharidosis I and three unaffected, were euthanized at 7 weeks and imaged using a 7T small-animal magnetic resonance imaging system. Average fractional anisotropy and radial diffusivity values were calculated for four white-matter regions based on 100 regions of interest per region per specimen. A 95% confidence interval was calculated for each mean value. Results No difference was seen in fractional anisotropy or radial diffusivity values between mucopolysaccharidosis affected and unaffected brains in any region. In particular, the 95% confidence intervals for mucopolysaccharidosis affected and unaffected canines frequently overlapped for both fractional anisotropy and radial diffusivity measurements. In addition, in some brain regions a large range of fractional anisotropy and radial diffusivity values were seen within the same cohort. Conclusion The fractional anisotropy and radial diffusivity values of white matter did not differ between pediatric mucopolysaccharidosis affected canines and pediatric control canines. Possible explanations include: (a) a lack of white matter tissue differences between mucopolysaccharidosis affected and unaffected brains at early disease stages; (b) diffusion tensor imaging does not detect any existing differences; (c) inflammatory processes such as astrogliosis produce changes that offset the decreased fractional anisotropy values and increased radial diffusivity values that are expected in dysmyelination; and (d) our sample size was insufficient to detect differences. Further studies correlating diffusion tensor imaging findings to histology are warranted.

2017 ◽  
Vol 30 (4) ◽  
pp. 324-329 ◽  
Author(s):  
Dana M Middleton ◽  
Jonathan Y Li ◽  
Hui J Lee ◽  
Steven Chen ◽  
Patricia I Dickson ◽  
...  

Purpose The purpose of this study was to investigate a novel tensor shape plot analysis technique of diffusion tensor imaging data as a means to assess microstructural differences in brain tissue. We hypothesized that this technique could distinguish white matter regions with different microstructural compositions. Methods Three normal canines were euthanized at seven weeks old. Their brains were imaged using identical diffusion tensor imaging protocols on a 7T small-animal magnetic resonance imaging system. We examined two white matter regions, the internal capsule and the centrum semiovale, each subdivided into an anterior and posterior region. We placed 100 regions of interest in each of the four brain regions. Eigenvalues for each region of interest triangulated onto tensor shape plots as the weighted average of three shape metrics at the plot's vertices: CS, CL, and CP. Results The distribution of data on the plots for the internal capsule differed markedly from the centrum semiovale data, thus confirming our hypothesis. Furthermore, data for the internal capsule were distributed in a relatively tight cluster, possibly reflecting the compact and parallel nature of its fibers, while data for the centrum semiovale were more widely distributed, consistent with the less compact and often crossing pattern of its fibers. This indicates that the tensor shape plot technique can depict data in similar regions as being alike. Conclusion Tensor shape plots successfully depicted differences in tissue microstructure and reflected the microstructure of individual brain regions. This proof of principle study suggests that if our findings are reproduced in larger samples, including abnormal white matter states, the technique may be useful in assessment of white matter diseases.


2017 ◽  
Vol 31 (1) ◽  
pp. 90-94 ◽  
Author(s):  
Dana M Middleton ◽  
Jonathan Y Li ◽  
Steven D Chen ◽  
Leonard E White ◽  
Patricia Dickson ◽  
...  

Purpose We investigated fractional anisotropy (FA) and radial diffusivity (RD) in a canine model of mucopolysaccharidosis (MPS). We hypothesized that canines affected with MPS would exhibit decreased FA and increased RD values when compared to unaffected canines, a trend that has been previously described in humans with white matter diseases. Methods Four unaffected canines and two canines with MPS were euthanized at 18 weeks of age. Their brains were imaged using high-resolution diffusion tensor imaging (DTI) on a 7T small-animal magnetic resonance imaging system. One hundred regions of interest (ROIs) were placed in each of four white matter regions: anterior and posterior regions of the internal capsule (AIC and PIC, respectively) and anterior and posterior regions of the centrum semiovale (ACS and PCS, respectively). For each specimen, average FA and RD values and associated 95% confidence intervals were calculated from 100 ROIs for each brain region. Results For each brain region, the FA values in MPS brains were consistently lower than in unaffected dogs, and the RD values in MPS dogs were consistently higher, supporting our hypothesis. The confidence intervals for affected and unaffected canines did not overlap in any brain region. Conclusion FA and RD values followed the predicted trend in canines affected with MPS, a trend that has been described in humans with lysosomal storage and dysmyelinating diseases. These findings suggest that the canine model parallels MPS in humans, and further indicates that quantitative DTI analysis of such animals may be suitable for future study of disease progression and therapeutic response in MPS.


Author(s):  
Shawn D’Souza ◽  
Lisa Hirt ◽  
David R Ormond ◽  
John A Thompson

Abstract Gliomas are neoplasms that arise from glial cell origin and represent the largest fraction of primary malignant brain tumours (77%). These highly infiltrative malignant cell clusters modify brain structure and function through expansion, invasion and intratumoral modification. Depending on the growth rate of the tumour, location and degree of expansion, functional reorganization may not lead to overt changes in behaviour despite significant cerebral adaptation. Studies in simulated lesion models and in patients with stroke reveal both local and distal functional disturbances, using measures of anatomical brain networks. Investigations over the last two decades have sought to use diffusion tensor imaging tractography data in the context of intracranial tumours to improve surgical planning, intraoperative functional localization, and post-operative interpretation of functional change. In this study, we used diffusion tensor imaging tractography to assess the impact of tumour location on the white matter structural network. To better understand how various lobe localized gliomas impact the topology underlying efficiency of information transfer between brain regions, we identified the major alterations in brain network connectivity patterns between the ipsilesional versus contralesional hemispheres in patients with gliomas localized to the frontal, parietal or temporal lobe. Results were indicative of altered network efficiency and the role of specific brain regions unique to different lobe localized gliomas. This work draws attention to connections and brain regions which have shared structural susceptibility in frontal, parietal and temporal lobe glioma cases. This study also provides a preliminary anatomical basis for understanding which affected white matter pathways may contribute to preoperative patient symptomology.


2021 ◽  
Vol 10 (2) ◽  
pp. 205846012199347
Author(s):  
Romulo V de Oliveira ◽  
João S Pereira

Background Diffusion tensor imaging has emerged as a promising tool for quantitative analysis of neuronal damage in Parkinson disease, with potential value for diagnostic and prognostic evaluation. Purpose The aim of this study was to examine Parkinson disease-associated alterations in specific brain regions revealed by diffusion tensor imaging and how such alterations correlate with clinical variables. Material and Methods Diffusion tensor imaging was performed on 42 Parkinson disease patients and 20 healthy controls with a 1.5-T scanner. Manual fractional anisotropy measurements were performed for the ventral, intermediate, and dorsal portions of the substantia nigra, as well as for the cerebral peduncles, putamen, thalamus, and supplementary motor area. The correlation analysis between these measurements and the clinical variables was performed using χ2 variance and multiple linear regression. Results Compared to healthy controls, Parkinson disease patients had significantly reduced fractional anisotropy values in the substantia nigra ( P < .05). Some fractional anisotropy measurements in the substantia nigra correlated inversely with duration of Parkinson disease and Parkinson disease severity scores. Reduced fractional anisotropy values in the substantia nigra were also correlated inversely with age variable. fractional anisotropy values obtained for the right and left putamen varied significantly between males and females in both groups. Conclusion Manual fractional anisotropy measurements in the substantia nigra were confirmed to be feasible with a 1.5-T scanner. Diffusion tensor imaging data can be used as a reliable biomarker of Parkinson disease that can be used to support diagnosis, prognosis, and progression/treatment monitoring.


Neurology ◽  
2018 ◽  
Vol 92 (1) ◽  
pp. e30-e39 ◽  
Author(s):  
Meher R. Juttukonda ◽  
Giulia Franco ◽  
Dario J. Englot ◽  
Ya-Chen Lin ◽  
Kalen J. Petersen ◽  
...  

ObjectiveTo assess white matter integrity in patients with essential tremor (ET) and Parkinson disease (PD) with moderate to severe motor impairment.MethodsSedated participants with ET (n = 57) or PD (n = 99) underwent diffusion tensor imaging (DTI) and fractional anisotropy, mean diffusivity, axial diffusivity, and radial diffusivity values were computed. White matter tracts were defined using 3 well-described atlases. To determine candidate white matter regions that differ between ET and PD groups, a bootstrapping analysis was applied using the least absolute shrinkage and selection operator. Linear regression was applied to assess magnitude and direction of differences in DTI metrics between ET and PD populations in the candidate regions.ResultsFractional anisotropy values that differentiate ET from PD localize primarily to thalamic and visual-related pathways, while diffusivity differences localized to the cerebellar peduncles. Patients with ET exhibited lower fractional anisotropy values than patients with PD in the lateral geniculate body (p < 0.01), sagittal stratum (p = 0.01), forceps major (p = 0.02), pontine crossing tract (p = 0.03), and retrolenticular internal capsule (p = 0.04). Patients with ET exhibited greater radial diffusivity values than patients with PD in the superior cerebellar peduncle (p < 0.01), middle cerebellar peduncle (p = 0.05), and inferior cerebellar peduncle (p = 0.05).ConclusionsRegionally, distinctive white matter microstructural values in patients with ET localize to the cerebellar peduncles and thalamo-cortical visual pathways. These findings complement recent functional imaging studies in ET but also extend our understanding of putative physiologic features that account for distinctions between ET and PD.


2018 ◽  
Vol 32 (1) ◽  
pp. 10-16
Author(s):  
Alexander Rau ◽  
Elias Kellner ◽  
Niels A Foit ◽  
Niklas Lützen ◽  
Dieter H Heiland ◽  
...  

The aim of this study was to evaluate whether ganglioglioma (GGL), dysembryoplastic neuroepithelial tumour (DNET) and FCD (focal cortical dysplasia) are distinguishable through diffusion tensor imaging. Additionally, it was investigated whether the diffusion measures differed in the perilesional (pNAWM) and in the contralateral normal appearing white matter (cNAWM). Six GGLs, eight DNETs and seven FCDs were included in this study. Quantitative diffusion measures, that is, axial, radial and mean diffusivity and fractional anisotropy, were determined in the lesion identified on isotropic T2 or FLAIR-weighted images and in pNAWM and cNAWM, respectively. DNET differed from FCD in mean diffusivity, and GGL from FCD in radial diffusivity. Both types of glioneuronal tumours were different from pNAWM in fractional anisotropy and radial diffusivity. For identifying the tumour edges, threshold values for tumour-free tissue were investigated with receiver operating characteristic analyses: tumour could be separated from pNAWM at a threshold ≤ 0.32 (fractional anisotropy) or ≥ 0.56 (radial diffusivity) *10–3 mm2/s (area under the curve 0.995 and 0.990 respectively). While diffusion parameters of FCDs differed from cNAWM (radial diffusivity (*10–3 mm/s2): 0.74 ± 0.19 vs. 0.43 ± 0.05; corrected p-value < 0.001), the pNAWM could not be differentiated from the FCD.


Author(s):  
Evanthia E. Tripoliti ◽  
Dimitrios I. Fotiadis ◽  
Konstantia Veliou

Diffusion Tensor Imaging (DTI) is a magnetic resonance imaging (MRI) modality which can significantly improve our understanding of the brain structures and neural connectivity. DTI measures are thought to be representative of brain tissue microstructure and are particularly useful for examining organized brain regions, such as white matter tract areas. DTI measures the water diffusion tensor using diffusion weighted pulse sequences which are sensitive to microscopic random water motion. The resulting diffusion weighted images (DWI) display and allow quantification of how water diffuses along axes or diffusion encoding directions. This can help to measure and quantify the tissue’s orientation and structure, making it an ideal tool for examining cerebral white matter and neural fiber tracts. In this chapter the authors discuss the theoretical aspects of DTI, the information that can be extracted from DTI data, and the use of the extracted information for the reconstruction of fiber tracts and the diagnosis of a disease. In addition, a review of known fiber tracking algorithms is presented.


2020 ◽  
Vol 8 (1) ◽  
pp. e926
Author(s):  
Maija Saraste ◽  
Svetlana Bezukladova ◽  
Markus Matilainen ◽  
Jouni Tuisku ◽  
Eero Rissanen ◽  
...  

ObjectiveTo evaluate to which extent serum neurofilament light chain (NfL) increase is related to diffusion tensor imaging–MRI measurable diffuse normal-appearing white matter (NAWM) damage in MS.MethodsSeventy-nine patients with MS and 10 healthy controls underwent MRI including diffusion tensor sequences and serum NfL determination by single molecule array (Simoa). Fractional anisotropy and mean, axial, and radial diffusivities were calculated within the whole and segmented (frontal, parietal, temporal, occipital, cingulate, and deep) NAWM. Spearman correlations and multiple regression models were used to assess the associations between diffusion tensor imaging, volumetric MRI data, and NfL.ResultsElevated NfL correlated with decreased fractional anisotropy and increased mean, axial, and radial diffusivities in the entire and segmented NAWM (for entire NAWM ρ = −0.49, p = 0.005; ρ = 0.49, p = 0.005; ρ = 0.43, p = 0.018; and ρ = 0.48, p = 0.006, respectively). A multiple regression model examining the effect of diffusion tensor indices on NfL showed significant associations when adjusted for sex, age, disease type, the expanded disability status scale, treatment, and presence of relapses. In the same model, T2 lesion volume was similarly associated with NfL.ConclusionsOur findings suggest that elevated serum NfL in MS results from neuroaxonal damage both within the NAWM and focal T2 lesions. This pathologic heterogeneity ought to be taken into account when interpreting NfL findings at the individual patient level.


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