Tuberculoma – a great mimicker: can diffusion tensor imaging and tractography help?

2021 ◽  
pp. 028418512110636
Author(s):  
Beenish Khan ◽  
Rashmi Dixit ◽  
Anjali Prakash ◽  
Sunita Aggarwal

Background Central nervous system (CNS) tuberculomas often mimic tumors on conventional imaging, differentiation of which may not be possible without invasive tissue sampling. Diffusion tensor imaging (DTI), owing to its unrivalled property of characterizing molecular diffusion, may help in better lesion characterization and tractography may help understand the pattern of white matter involvement by tuberculomas. Purpose To estimate qualitative and quantitative diffusion tensor changes in brain tuberculomas and to evaluate patterns of white matter involvement using 3D tractography. Material and Methods Thirty patients with brain tuberculomas were evaluated on a 3-T magnetic resonance scanner. Diffusion tensor images were acquired along 20 non-colinear encoding directions with two b-values (b = 0, b = 1000). Regions of interest (ROIs) were drawn on quantitative fractional anisotropy (FA) and apparent diffusion coefficient (ADC) maps in the center of the tuberculoma and perilesional area. Similar ROIs were placed in contralateral hemispheres for comparison. Tractography maps were also generated. Results Mean FA in the center and perilesional area of tuberculomas were 0.098 ± 0.041 and 0.311 ± 0.135, respectively. ADC values in corresponding regions were 0.920 ± 0.272 ×10−3 mm2/s and 1.157 ± 0.277 ×10−3 mm2/s. These values were significantly different compared to contralateral similar brain parenchyma. Tractography revealed interruption of white fibers in the center with deviation of fibers at the periphery in the majority of tuberculomas with none showing infiltration of white matter described in tumors. Conclusion Significant qualitative as well as quantitative DTI changes were seen in tuberculoma and perilesional areas compared to contralateral hemisphere with tractography showing a pattern different from that described in tumors. These findings may help to differentiate tuberculomas from infiltrating tumors.

2019 ◽  
Vol 130 (2) ◽  
pp. 550-558 ◽  
Author(s):  
Isabel Fragata ◽  
Marta Alves ◽  
Ana Luísa Papoila ◽  
Patrícia Ferreira ◽  
Ana Paiva Nunes ◽  
...  

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.


2004 ◽  
Vol 10 (2) ◽  
pp. 188-196 ◽  
Author(s):  
Emmanuelle Cassol ◽  
Jean-Philippe Ranjeva ◽  
Danielle Ibarrola ◽  
Claude Mékies ◽  
Claude Manelfe ◽  
...  

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.


Author(s):  
Piotr Podwalski ◽  
Krzysztof Szczygieł ◽  
Ernest Tyburski ◽  
Leszek Sagan ◽  
Błażej Misiak ◽  
...  

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.


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