scholarly journals Correlations between DTI-derived metrics and MRS metabolites in tumour regions of glioblastoma: a pilot study

2020 ◽  
Vol 0 (0) ◽  
Author(s):  
Eduardo Flores-Alvarez ◽  
Edgar Anselmo Rios Piedra ◽  
Griselda-Adriana Cruz-Priego ◽  
Coral Durand-Muñoz ◽  
Sergio Moreno-Jimenez ◽  
...  
Keyword(s):  
Anisotropic Diffusion ◽  
Retrospective Cohort ◽  
Diffusion Tensor ◽  
Mean Diffusivity ◽  
Resonance Spectroscopy ◽  
Radial Diffusivity ◽  
Isotropic Diffusion ◽  
Normal Appearing White Matter ◽  
Total Magnitude ◽  
Diffusion Tensor Imaging Dti

AbstractIntroductionSpecific correlations among diffusion tensor imaging (DTI)-derived metrics and magnetic resonance spectroscopy (MRS) metabolite ratios in brains with glioblastoma are still not completely understood.Patients and methodsWe made retrospective cohort study. MRS ratios (choline-to-N-acetyl aspartate [Cho/NAA], lipids and lactate to creatine [LL/Cr], and myo-inositol/creatine [mI/Cr]) were correlated with eleven DTI biomarkers: mean diffusivity (MD), fractional anisotropy (FA), pure isotropic diffusion (p), pure anisotropic diffusion (q), the total magnitude of the diffusion tensor (L), linear tensor (Cl), planar tensor (Cp), spherical tensor (Cs), relative anisotropy (RA), axial diffusivity (AD) and radial diffusivity (RD) at the same regions: enhanced rim, peritumoral oedema and normal-appearing white matter. Correlational analyses of 546 MRS and DTI measurements used Spearman coefficient.ResultsAt the enhancing rim we found four significant correlations: FA ⇔ LL/Cr, Rs = -.364, p = .034; Cp ⇔ LL/Cr, Rs = .362, p = .035; q ⇔ LL/Cr, Rs = -.349, p = .035; RA ⇔ LL/Cr, Rs = -.357, p = .038. Another ten pairs of significant correlations were found in the peritumoral edema: AD ⇔ LL/Cr, AD ⇔ mI/Cr, MD ⇔ LL/Cr, MD ⇔ mI/Cr, p ⇔ LL/Cr, p ⇔ mI/ Cr, RD ⇔ mI/Cr, RD ⇔ mI/Cr, L ⇔ LL/Cr, L ⇔ mI/Cr.ConclusionsDTI and MRS biomarkers answer different questions; peritumoral oedema represents the biggest challenge with at least ten significant correlations between DTI and MRS that need additional studies. The fact that DTI and MRS measures are not specific of one histologic type of tumour broadens their application to a wider variety of intracranial pathologies.

scholarly journals Discrimination of epileptogenic lesions and perilesional white matter using diffusion tensor magnetic resonance imaging

2018 ◽  
Vol 32 (1) ◽  
pp. 10-16
Author(s):  
Alexander Rau ◽  
Elias Kellner ◽  
Niels A Foit ◽  
Niklas Lützen ◽  
Dieter H Heiland ◽  
...  
Keyword(s):  
White Matter ◽  
Fractional Anisotropy ◽  
Diffusion Tensor ◽  
Focal Cortical Dysplasia ◽  
Mean Diffusivity ◽  
Area Under The Curve ◽  
P Value ◽  
Radial Diffusivity ◽  
Normal Appearing White Matter ◽  
Diffusion Parameters

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.

scholarly journals Characteristics of mental health implications and plasma metabolomics in patients recently recovered from COVID-19

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Lian Yang ◽  
Mei Zhou ◽  
Lingli Li ◽  
Ping Luo ◽  
Wenliang Fan ◽  
...  
Keyword(s):  
Mental Health ◽  
Metabolic Profiling ◽  
Diffusion Tensor ◽  
Demographic Data ◽  
Mean Diffusivity ◽  
Brain Regions ◽  
Cerebral White Matter ◽  
Radial Diffusivity ◽  
Amine Metabolism ◽  
Diffusion Tensor Imaging Dti

AbstractThis study aimed to explore the associations between cerebral white matter (WM) alterations, mental health status, and metabolism in recovered COVID-19 patients. We included 28 recovered COVID-19 patients and 27 healthy controls between April 2020 and June 2020. Demographic data, the mental health scores, diffusion-tensor imaging (DTI) data, and plasma metabolomics were collected and compared between the two groups. Tract-based spatial statistics and graph theory approaches were used for DTI data analysis. Untargeted metabolomics analysis of the plasma was performed. Correlation analyses were performed between these characteristics. Recovered COVID-19 patients showed decreased fractional anisotropy, increased mean diffusivity and radial diffusivity values in widespread brain regions, and significantly lower global efficiency, longer shortest path length, and less nodal local efficiency in superior occipital gyrus (all, P < 0.05, Bonferroni corrected). Our results also demonstrated significantly different plasma metabolic profiling in recovered COVID-19 patients even at 3 months after their hospital discharge, which was mainly related to purine pathways, amino acids, lipids, and amine metabolism. Certain regions with cerebral WM alterations in the recovered patients showed significant correlations with different metabolites and the mental health scores. We observed multiple alterations in both WM integrity and plasma metabolomics that may explain the deteriorated mental health of recovered COVID-19 patients. These findings may provide potential biomarkers for the mental health evaluation for the recovered COVID-19 patients and potential targets for novel therapeutics.

scholarly journals White matter differences between essential tremor and Parkinson disease

Neurology ◽  
2018 ◽  
Vol 92 (1) ◽  
pp. e30-e39 ◽  
Author(s):  
Meher R. Juttukonda ◽  
Giulia Franco ◽  
Dario J. Englot ◽  
Ya-Chen Lin ◽  
Kalen J. Petersen ◽  
...  
Keyword(s):  
White Matter ◽  
Parkinson Disease ◽  
Essential Tremor ◽  
Fractional Anisotropy ◽  
Diffusion Tensor ◽  
Mean Diffusivity ◽  
Superior Cerebellar Peduncle ◽  
Radial Diffusivity ◽  
Cerebellar Peduncles ◽  
Cerebellar Peduncle

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.

Diffusion tensor imaging in multiple sclerosis: a tool for monitoring changes in normal-appearing white matter

2004 ◽  
Vol 10 (2) ◽  
pp. 188-196 ◽  
Author(s):  
Emmanuelle Cassol ◽  
Jean-Philippe Ranjeva ◽  
Danielle Ibarrola ◽  
Claude Mékies ◽  
Claude Manelfe ◽  
...  
Keyword(s):  
Multiple Sclerosis ◽  
Diffusion Tensor Imaging ◽  
White Matter ◽  
Diffusion Tensor ◽  
Lesion Load ◽  
Normal Appearing White Matter ◽  
Relapsing Remitting ◽  
One Year ◽  
Diffusion Tensor Imaging Dti

Our objectives were to determine the reproducibility of diffusion tensor imaging (DTI) in volunteers and to evaluate the ability of the method to monitor longitudinal changes occurring in the normal-appearing white matter (NAWM) of patients with multiple sclerosis (MS). DTI was performed three-mo nthly for one year in seven MS patients: three relapsing-remitting (RRMS), three secondary progressive (SPMS) and one relapsing SP. They were selected with a limited cerebral lesion load. Seven age- and sex-matched controls also underwent monthly examinations for three months. Diffusivity and anisotropy were quantified over the segmented whole supratentorial white matter, with the indices of trace (Tr) and fractional anisotropy (FA). Results obtained in volunteers show the reproducibility of the method. Patients had higher trace and lower anisotropy than matched controls (P B-0.0001). O ver the follow-up, both Tr and FA indicated a recovery after the acute phase in RRMS and a progressive shift towards abnormal values in SPMS. A lthough this result is not statistically significant, it suggests that DTI is sensitive to microscopic changes occurring in tissue of normal appearance in conventional images and could be useful for monitoring the course of the disease, even though it was unable to clearly distinguish between the various physiopathological processes involved.

scholarly journals Magnetic resonance diffusion tensor imaging in psychiatry: a narrative review of its potential role in diagnosis

2020 ◽  
Author(s):  
Piotr Podwalski ◽  
Krzysztof Szczygieł ◽  
Ernest Tyburski ◽  
Leszek Sagan ◽  
Błażej Misiak ◽  
...  
Keyword(s):  
Diffusion Tensor Imaging ◽  
White Matter ◽  
Magnetic Resonance ◽  
Potential Role ◽  
Diffusion Tensor ◽  
Mean Diffusivity ◽  
Water Molecules ◽  
Mental Diseases ◽  
The Brain ◽  
Diffusion Tensor Imaging Dti

Abstract Diffusion tensor imaging (DTI) is an imaging technique that uses magnetic resonance. It measures the diffusion of water molecules in tissues, which can occur either without restriction (i.e., in an isotropic manner) or limited by some obstacles, such as cell membranes (i.e., in an anisotropic manner). Diffusion is most often measured in terms of, inter alia, fractional anisotropy (FA), mean diffusivity (MD), radial diffusivity (RD), and axial diffusivity (AD). DTI allows us to reconstruct, visualize, and evaluate certain qualities of white matter. To date, many studies have sought to associate various changes in the distribution of diffusion within the brain with mental diseases and disorders. A better understanding of white matter integrity disorders can help us recognize the causes of diseases, as well as help create objective methods of psychiatric diagnosis, identify biomarkers of mental illness, and improve pharmacotherapy. The aim of this work is to present the characteristics of DTI as well as current research on its use in schizophrenia, affective disorders, and other mental disorders.

scholarly journals Converging evidence points towards a role of insulin signaling in regulating compulsive behavior

2019 ◽  
Vol 9 (1) ◽  
Author(s):  
Ilse I. G. M. van de Vondervoort ◽  
Houshang Amiri ◽  
Muriel M. K. Bruchhage ◽  
Charlotte A. Oomen ◽  
Nitin Rustogi ◽  
...  
Keyword(s):  
Insulin Signaling ◽  
Diffusion Tensor ◽  
Structural Connectivity ◽  
Mean Diffusivity ◽  
Repetitive Behaviors ◽  
Anterior Cingulate ◽  
Resonance Spectroscopy ◽  
Compulsive Disorder ◽  
Dorsomedial Striatum

Abstract Obsessive–compulsive disorder (OCD) is a neuropsychiatric disorder with childhood onset, and is characterized by intrusive thoughts and fears (obsessions) that lead to repetitive behaviors (compulsions). Previously, we identified insulin signaling being associated with OCD and here, we aim to further investigate this link in vivo. We studied TALLYHO/JngJ (TH) mice, a model of type 2 diabetes mellitus, to (1) assess compulsive and anxious behaviors, (2) determine neuro-metabolite levels by 1 H magnetic resonance spectroscopy (MRS) and brain structural connectivity by diffusion tensor imaging (DTI), and (3) investigate plasma and brain protein levels for molecules previously associated with OCD (insulin, Igf1, Kcnq1, and Bdnf) in these subjects. TH mice showed increased compulsivity-like behavior (reduced spontaneous alternation in the Y-maze) and more anxiety (less time spent in the open arms of the elevated plus maze). In parallel, their brains differed in the white matter microstructure measures fractional anisotropy (FA) and mean diffusivity (MD) in the midline corpus callosum (increased FA and decreased MD), in myelinated fibers of the dorsomedial striatum (decreased FA and MD), and superior cerebellar peduncles (decreased FA and MD). MRS revealed increased glucose levels in the dorsomedial striatum and increased glutathione levels in the anterior cingulate cortex in the TH mice relative to their controls. Igf1 expression was reduced in the cerebellum of TH mice but increased in the plasma. In conclusion, our data indicates a role of (abnormal) insulin signaling in compulsivity-like behavior.

scholarly journals Loss of corticospinal tract integrity in early MS disease stages

2017 ◽  
Vol 4 (6) ◽  
pp. e399 ◽  
Author(s):  
Marc Pawlitzki ◽  
Jens Neumann ◽  
Jörn Kaufmann ◽  
Jan Heidel ◽  
Erhard Stadler ◽  
...  
Keyword(s):  
Corticospinal Tract ◽  
Diffusion Tensor ◽  
Mean Diffusivity ◽  
Group Differences ◽  
Disability Score ◽  
Brain Volumes ◽  
Disability Status ◽  
Relapsing Remitting ◽  
Disease Stages ◽  
Diffusion Tensor Imaging Dti

Objective:We investigated corticospinal tract (CST) integrity in the absence of white matter (WM) lesions using diffusion tensor imaging (DTI) in early MS disease stages.Methods:Our study comprised 19 patients with clinically isolated syndrome (CIS), 11 patients with relapsing-remitting MS (RRMS), and 32 age- and sex-matched healthy controls, for whom MRI measures of CST integrity (fractional anisotropy [FA], mean diffusivity [MD]), T1- and T2-based lesion load, and brain volumes were available. The mean (SD) disease duration was 3.5 (2.1) months, and disability score was low (median Expanded Disability Status Scale 1.5) at the time of the study.Results:Patients with CIS and RRMS had significantly lower CST FA and higher CST MD values compared with controls. These findings were present, irrespective of whether WM lesions affected the CST. However, no group differences in the overall gray or WM volume were identified.Conclusions:In early MS disease stages, CST integrity is already affected in the absence of WM lesions or brain atrophy.

scholarly journals Spatial Gradient of Microstructural Changes in Normal-Appearing White Matter in Tracts Affected by White Matter Hyperintensities in Older Age

2018 ◽  
Author(s):  
Susana Muñoz Maniega ◽  
Rozanna Meijboom ◽  
Francesca M. Chappell ◽  
Maria C. Valdés Hernández ◽  
John M. Starr ◽  
...  
Keyword(s):  
White Matter ◽  
White Matter Hyperintensities ◽  
Diffusion Tensor ◽  
Mean Diffusivity ◽  
Pathological Process ◽  
Spatial Gradient ◽  
Microstructural Changes ◽  
Normal Appearing White Matter ◽  
Brain White Matter ◽  
Lothian Birth Cohort

AbstractBrain white matter hyperintensities (WMH), common in older adults, may contribute to cortical disconnection and cognitive dysfunction. The presence of WMH within white matter (WM) tracts indicates underlying microstructural WM changes that may also affect the normal-appearing WM (NAWM) of a tract. We performed an exploratory study using diffusion magnetic resonance imaging of 52 healthy participants from the Lothian Birth Cohort 1936 (age 72.2 ± 0.7 years) selected to include a range of WMH burden, to quantify microstructural changes of tracts intersecting WMH. We reconstructed tracts using automated tractography and identified intersections with WMH. Tissue volumes and water diffusion tensor parameters (mean diffusivity (MD) and fractional anisotropy (FA)) were established for tract-WMH and tract-NAWM. MD and FA were also measured for tract-NAWM at 2 mm incremental distances from the tract-WMH edge, and from the edge of nearby, non-intersecting, WMH. We observed microstructural changes in tract-WMH suggestive of tissue damage. Tract-NAWM also showed a spatial gradient of FA and MD abnormalities, which diminished with distance from the tract-WMH. Nearby WMH lesions, not directly crossed by the tract, also affected tract microstructure with a similar pattern. Additionally, both FA and MD changes in tract-NAWM were predicted by FA and MD changes respectively in tract-WMH. FA was also predicted by tract-WMH overlap volume, whereas MD was better predicted by whole-brain WMH load. These results suggest that tract-NAWM microstructure is affected by the pathological process underlying WMH, when WMH are either within or near to the tract. The changes in NAWM tract tissue may indicate future lesion progression and may play an important role in cognitive ageing.

scholarly journals Diffusion tensor imaging in differentiation metastatic from reactive axillary lymph nodes in patients with breast cancer

2021 ◽  
Author(s):  
Ahmed Abdel Razek ◽  
Waleed Elnahas ◽  
Mahmoud Abd El-Latif
Keyword(s):  
Breast Cancer ◽  
Diffusion Tensor Imaging ◽  
Lymph Nodes ◽  
Diffusion Tensor ◽  
Mean Diffusivity ◽  
Final Diagnosis ◽  
Axillary Lymph Nodes ◽  
Axillary Lymph ◽  
Reactive N ◽  
Diffusion Tensor Imaging Dti

Purpose: To determine if diffusion tensor imaging (DTI) parameters can differentiate metastatic from reactive axillary lymph nodes (ALNs) in patients with breast cancer. Methods: Prospective study was done on 48 patients with breast cancer that were examined by DTI of the breast. The mean diffusivity (MD) and fractional anisotropy (FA) of ALNs were calculated by 2 observers. The final diagnosis was obtained by biopsy. Results: Metastatic nodes (n=50) had significantly lower MD (p = 0.001, 0.001) and higher FA (p = 0.002, 0.01) than reactive (n=20) nodes for both observers respectively. When threshed of MD (0.875, 0.815 X10-3 mm2/s) was used for differentiation of both entities revealed accuracy (80 %, 81.4 %) and had AUC of 0.920 and 0.918 by both observers respectively. When threshold FA (0.565, 0.645) was used for differentiation revealed an accuracy of 87.1%, 81.4% and had AUC of 0.860 and 0.870 by both observers respectively. Combined FA and MD had AUC 0.940, 0.950) with an accuracy of 91.4%, 92.9% for both observers respectively. Conclusion: Combined analysis DTI parameters FA may play a role in differentiation of metastatic from reactive ALNs in patients with breast cancer.

scholarly journals The role of diffusion tensor imaging metrics in machine learning-based characterisation of paediatric brain tumors and their practicality for multicentre clinical assessment

2021 ◽  
Vol 23 (Supplement_4) ◽  
pp. iv1-iv2
Author(s):  
Heather Rose ◽  
Huijun Li ◽  
Christopher D Bennett ◽  
Jan Novak ◽  
Yu Sun ◽  
...  
Keyword(s):  
Machine Learning ◽  
Brain Tumours ◽  
Anisotropic Diffusion ◽  
Diffusion Tensor ◽  
Mean Diffusivity ◽  
Imaging Biomarkers ◽  
Significant Difference ◽  
Mri Scans ◽  
Leave One Out ◽  
Paediatric Brain Tumours

Abstract Aims Magnetic resonance imaging (MRI) is a valuable tool for non-invasive diagnosis of paediatric brain tumours. The rarity of the disease dictates multi-centre studies and imaging biomarkers that are robust to protocol variability. We investigated diffusion tensor MRI (DT-MRI), combined with machine learning, as an aid to diagnosis and evaluated the robustness of the imaging metrics. Method A multi-centre cohort of 52 clinical DT-MRI scans (20 medulloblastomas (MB), 21 pilocytic astrocytomas (PA), 11 ependymomas (EP)) were analysed retrospectively. Histograms for regions of solid tumour for fractional anisotropy (FA), mean diffusivity (MD), pure anisotropic diffusion (q) and pure isotropic diffusion (p) were compared to assess diagnostic capability. Linear discriminate analysis (LDA) was used for classification and validated using leave-one-out-cross-validation (LOOCV). Results Histogram medians for FA, MD, q and p were all different between tumor groups (P&lt;.0001, Kruskal Wallis test). Median MD, p and q values were highest in PA, then EP and lowest in MB (P&lt;.0001, Pairwise Wilcox test). FA median was higher for EP than PA (P=.004) with no significant difference between EP and MB (P=.591). ROC analysis showed that median MD, q and p perform best as a diagnostic marker (AUC= 0.92 to 0.99). LOOCV showed an overall accuracy of the LDA classification, ranging between 67% - 87%. FA values were highly dependent on protocol parameters, whereas pure anisotropic diffusion, q, was not. Conclusion DT-MRI metrics from multi-centre acquisitions can classify paediatric brain tumours. FA is the least robust metric to protocol variability and q provides the most robust quantification of anisotropic behaviour.

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