Possible confounding factors on cerebral diffusion tensor imaging measurements

Background Diffusion tensor imaging (DTI) is prone to numerous systemic confounding factors that should be acknowledged to avoid false conclusions. Purpose To investigate the possible effects of age, gender, smoking, alcohol consumption, and education on cerebral DTI parameters in a generally healthy homogenous sample with no neurological or psychiatric diseases. Material and Methods Forty ( n = 40) subjects (mean age, 40.3 years; SD, 12.3) underwent brain DTI with 3 T magnetic resonance imaging (MRI). At enrolment, all the subjects were interviewed with respect to general health, education, history of smoking, and alcohol consumption. Studied DTI parameters included: (i) fractional anisotropy (FA); and (ii) apparent diffusion coefficient (ADC). Region-of-interest (ROI)-based measurements were estimated at 13 anatomical locations bilaterally on the axial images, except for the corpus callosum in which the ROIs were placed on the sagittal images. Circular ROI measurements were mainly used. Freehand ROI method was used with the forceps minor, uncinate fasciculus, and thalamus. Intra-observer variability and repeatability were assessed. Results The most consistent finding was that aging decreased FA values in the frontal brain regions. Regarding the other confounding factors, the results were discontinuous and no concrete conclusions could be drawn from these findings. In general, intra-observer repeatability of the DTI measurement was considered relatively good. Conclusion Age should be noted as considerable confounding factors in ROI-based DTI analysis. More research on the effects of gender, smoking, alcohol consumption, and education is needed.

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Diffusion tensor imaging reveals microstructural differences between subtypes of trigeminal neuralgia

Journal of Neurosurgery ◽

10.3171/2019.4.jns19299 ◽

2020 ◽

Vol 133 (2) ◽

pp. 573-579 ◽

Cited By ~ 1

Author(s):

Matthew S. Willsey ◽

Kelly L. Collins ◽

Erin C. Conrad ◽

Heather A. Chubb ◽

Parag G. Patil

Keyword(s):

Diffusion Coefficient ◽

Diffusion Tensor Imaging ◽

Trigeminal Neuralgia ◽

Apparent Diffusion Coefficient ◽

Diffusion Tensor ◽

Statistical Significance ◽

Region Of Interest ◽

Pain Syndrome ◽

Radial Diffusivity ◽

Apparent Diffusion

OBJECTIVETrigeminal neuralgia (TN) is an uncommon idiopathic facial pain syndrome. To assist in diagnosis, treatment, and research, TN is often classified as type 1 (TN1) when pain is primarily paroxysmal and episodic or type 2 (TN2) when pain is primarily constant in character. Recently, diffusion tensor imaging (DTI) has revealed microstructural changes in the symptomatic trigeminal root and root entry zone of patients with unilateral TN. In this study, the authors explored the differences in DTI parameters between subcategories of TN, specifically TN1 and TN2, in the pontine segment of the trigeminal tract.METHODSThe authors enrolled 8 patients with unilateral TN1, 7 patients with unilateral TN2, and 23 asymptomatic controls. Patients underwent DTI with parameter measurements in a region of interest within the pontine segment of the trigeminal tract. DTI parameters were compared between groups.RESULTSIn the pontine segment, the radial diffusivity (p = 0.0049) and apparent diffusion coefficient (p = 0.023) values in TN1 patients were increased compared to the values in TN2 patients and controls. The DTI measures in TN2 were not statistically significant from those in controls. When comparing the symptomatic to asymptomatic sides in TN1 patients, radial diffusivity was increased (p = 0.025) and fractional anisotropy was decreased (p = 0.044) in the symptomatic sides. The apparent diffusion coefficient was increased, with a trend toward statistical significance (p = 0.066).CONCLUSIONSNoninvasive DTI analysis of patients with TN may lead to improved diagnosis of TN subtypes (e.g., TN1 and TN2) and improve patient selection for surgical intervention. DTI measurements may also provide insights into prognosis after intervention, as TN1 patients are known to have better surgical outcomes than TN2 patients.

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Meyer’s Loop Anatomy Demonstrated Using Diffusion Tensor MR Imaging and Fiber Tractography at 3T

Acta Medica Marisiensis ◽

10.2478/amma-2014-0045 ◽

2014 ◽

Vol 60 (5) ◽

pp. 215-222 ◽

Cited By ~ 1

Author(s):

Cristina Goga ◽

Zeynep Firat ◽

Klara Brinzaniuc ◽

Is Florian

Keyword(s):

Diffusion Tensor Imaging ◽

Diffusion Tensor ◽

Region Of Interest ◽

Fiber Tractography ◽

Brain Images ◽

3 Dimensional ◽

Software Release ◽

Magnetic Resonance Imaging Mri ◽

Meyer’S Loop

Abstract Objective: The ultimate anatomy of the Meyer’s loop continues to elude us. Diffusion tensor imaging (DTI) and diffusion tensor tractography (DTT) may be able to demonstrate, in vivo, the anatomy of the complex network of white matter fibers surrounding the Meyer’s loop and the optic radiations. This study aims at exploring the anatomy of the Meyer’s loop by using DTI and fiber tractography. Methods: Ten healthy subjects underwent magnetic resonance imaging (MRI) with DTI at 3 T. Using a region-of-interest (ROI) based diffusion tensor imaging and fiber tracking software (Release 2.6, Achieva, Philips), sequential ROI were placed to reconstruct visual fibers and neighboring projection fibers involved in the formation of Meyer’s loop. The 3-dimensional (3D) reconstructed fibers were visualized by superimposition on 3-planar MRI brain images to enhance their precise anatomical localization and relationship with other anatomical structures. Results: Several projection fiber including the optic radiation, occipitopontine/parietopontine fibers and posterior thalamic peduncle participated in the formation of Meyer’s loop. Two patterns of angulation of the Meyer’s loop were found. Conclusions: DTI with DTT provides a complimentary, in vivo, method to study the details of the anatomy of the Meyer’s loop.

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Increased muscle fiber fractional anisotropy value using diffusion tensor imaging after compression without fiber injury

Acta Radiologica ◽

10.1177/02841851211058282 ◽

2021 ◽

pp. 028418512110582

Author(s):

Takumi Yokohama ◽

Motoyuki Iwasaki ◽

Daisuke Oura ◽

Sho Furuya ◽

Yoshimasa Niiya

Keyword(s):

Diffusion Tensor Imaging ◽

Fractional Anisotropy ◽

Muscle Tissue ◽

Diffusion Tensor ◽

Longitudinal Direction ◽

Diffusion Parameters ◽

Apparent Diffusion ◽

The Mean ◽

Magnetic Resonance Imaging Mri ◽

Age Range

Background Recent studies have indicated that injuries such as muscle tears modify the microstructural integrity of muscle, leading to substantial alterations in measured diffusion parameters. Therefore, the fractional anisotropy (FA) value decreases. However, we hypothesized that soft tissue, such as muscle tissue, undergoes reversible changes under conditions of compression without fiber injury. Purpose To evaluate the FA change due to compression in muscle tissue without fiber injury. Material and Methods Diffusion tensor imaging (DTI) was performed on both feet of 10 healthy volunteers (mean age = 35.0 ± 10.39 years; age range = 23–52 years) using a 3.0-T magnetic resonance imaging (MRI) scanner with an eight-channel phased array knee coil. An MRI-compatible sphygmomanometer was applied to the individuals’ lower legs and individuals were placed in a compressed state. Then, rest intervals of 5 min were set in re-rest state after compression. The FA value, apparent diffusion coefficient (ADC), and eigenvalues (λ1, λ2, λ3) of the gastrocnemius and soleus muscle were measured at each state. Results The mean FA values increased in all muscles in a compressed state, while the mean λ3 decreased. In all muscles, significant differences were found between the rest and compressed states in terms of mean FA and λ3 ( P < 0.0001). Conclusion We confirmed the reversibility of the DTI metrics, which suggests that there was no muscle injury during this study. In cases of compression without fiber injury, the FA value increases, because fibers are strongly aligned in the longitudinal direction.

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Diffusion Tensor Imaging and Fiber Tractography

Handbook of Research on Advanced Techniques in Diagnostic Imaging and Biomedical Applications ◽

10.4018/978-1-60566-314-2.ch015 ◽

2009 ◽

pp. 229-246

Author(s):

Evanthia E. Tripoliti ◽

Dimitrios I. Fotiadis ◽

Konstantia Veliou

Keyword(s):

Diffusion Tensor Imaging ◽

White Matter ◽

Diffusion Tensor ◽

Brain Regions ◽

Cerebral White Matter ◽

Tissue Microstructure ◽

Diffusion Weighted Images ◽

Fiber Tracts ◽

Diffusion Weighted ◽

Magnetic Resonance Imaging Mri

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.

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Prediction of clinical outcome in subacute subarachnoid hemorrhage using diffusion tensor imaging

Journal of Neurosurgery ◽

10.3171/2017.10.jns171793 ◽

2019 ◽

Vol 130 (2) ◽

pp. 550-558 ◽

Cited By ~ 2

Author(s):

Isabel Fragata ◽

Marta Alves ◽

Ana Luísa Papoila ◽

Patrícia Ferreira ◽

Ana Paiva Nunes ◽

...

Keyword(s):

Diffusion Tensor Imaging ◽

Subarachnoid Hemorrhage ◽

Clinical Outcome ◽

Diffusion Tensor ◽

Brain Regions ◽

Poor Clinical Outcome ◽

Poor Outcome ◽

Apparent Diffusion ◽

Adc Values ◽

Diffusion Tensor Imaging Dti

OBJECTIVEClinical outcome in nontraumatic subarachnoid hemorrhage (SAH) is multifactorial and difficult to predict. Diffusion tensor imaging (DTI) findings are a prognostic marker in some diseases such as traumatic brain injury. The authors hypothesized that DTI parameters measured in the subacute phase of SAH can be associated with a poor clinical outcome.METHODSDiffusion tensor imaging was prospectively performed in 54 patients at 8–10 days after nontraumatic SAH. Logistic regression analysis was performed to evaluate the association of fractional anisotropy (FA) and apparent diffusion coefficient (ADC) values with a poor clinical outcome (modified Rankin Scale score ≥ 3) at 3 months.RESULTSAt 8–10 days post-SAH, after adjusting for other variables associated with a poor outcome, an increased ADC at the frontal centrum semiovale was associated with a poor prognosis (OR estimate 1.29, 95% CI 1.04–1.60, p = 0.020). Moreover, an increase of 0.1 in the FA value at the corpus callosum at 8–10 days after SAH corresponded to 66% lower odds of having a poor outcome (p = 0.002).CONCLUSIONSDecreased FA and increased ADC values in specific brain regions were independently associated with a poor clinical outcome after SAH. This preliminary exploratory study supports a potential role for DTI in predicting the outcome of SAH.

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Comparison of Region-of-Interest Delineation Methods for Diffusion Tensor Imaging in Patients with Cervical Spondylotic Radiculopathy

10.21203/rs.3.rs-1023507/v1 ◽

2021 ◽

Author(s):

Penghuan Wu ◽

Chengyan Huang ◽

Benchao Shi ◽

Anmin Jin

Keyword(s):

Diffusion Tensor Imaging ◽

Diffusion Tensor ◽

Region Of Interest ◽

Cervical Radiculopathy ◽

Nerve Roots ◽

Intra Class Correlation ◽

Cervical Spondylotic Radiculopathy ◽

Apparent Diffusion ◽

The Impact ◽

Intra Class Correlation Coefficient

Abstract Background Diffusion tensor imaging is a promising technique for determining the responsible lesion of cervical radiculopathy, but the selection and delineation of the region of interest (ROI) affects the results. To explore the impact of different ROI sketching methods on the repeatability and consistency of DTI measurement values in patients with cervical spondylotic radiculopathy (CSR). Methods This was a retrospective study that included CSR patients who underwent DTI imaging. The images were analyzed independently by two radiologists. Four delineation methods were used: free-hand method, maximum roundness, quadrilateral method, and multi-point averaging method. They re-examined the images 6 weeks later. To investigate the consistency between the two measurements and the reproducibility between two radiologists, the intra-class correlation coefficient (ICC) was used. Results A total of 42 CSR patients were enrolled in this study. The distribution of compressed nerve roots was five C4, eight C5, sixteen C6, eleven C7, and two C8. No difference was found among the four methods in fractional anisotropy (FA) or apparent diffusion coefficient (ADC), irrespective of radiologists. (all P>0.05). Similar results were observed between the first and second measurements (all P>0.05), but some significant differences were observed for radiologist 2 for the four-small rounds method (P=0.033). Between the two measurements and the two radiologists, the free-hand and single largest circle methods were the two methods with the highest ICC (all ICC >0.90). Conclusion For the delineation of DTI ROI in patients with CSR, the free-hand and single largest circle methods were the most consistent methods.

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Retrospective analysis of hemispheric structural network change as a function of location and size of glioma

Brain Communications ◽

10.1093/braincomms/fcaa216 ◽

2020 ◽

Author(s):

Shawn D’Souza ◽

Lisa Hirt ◽

David R Ormond ◽

John A Thompson

Keyword(s):

Diffusion Tensor Imaging ◽

White Matter ◽

Temporal Lobe ◽

Diffusion Tensor ◽

Brain Regions ◽

Structural Network ◽

Tumour Location ◽

The Impact ◽

Tractography Data ◽

Diffusion Tensor Imaging Tractography

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.

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

The Neuroradiology Journal ◽

10.1177/1971400917718844 ◽

2017 ◽

Vol 30 (5) ◽

pp. 454-460

Author(s):

Dana M Middleton ◽

Jonathan Y Li ◽

Steven D Chen ◽

Leonard E White ◽

Patricia I Dickson ◽

...

Keyword(s):

Diffusion Tensor Imaging ◽

White Matter ◽

Fractional Anisotropy ◽

Imaging System ◽

Diffusion Tensor ◽

Brain Regions ◽

Magnetic Resonance Imaging System ◽

Radial Diffusivity ◽

Mucopolysaccharidosis I ◽

Diffusivity Measurements

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.

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