Water diffusion in the human hippocampus in epilepsy

Wieshmann, Udo; lark, Chris A.C; Symms, Mark R.; Barker, Gareth J.; Birnie, K; Shorvon, Simon

doi:10.1016/s0730-725x(98)00153-2

Cited by 115 publications

(74 citation statements)

References 38 publications

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“…Changes in MD and FA values have been reported in neurological conditions such as stroke (during transition from acute to subacute to chronic stroke, MD decreases and FA increases in acute phase, then renormalizes and then increase in MD with a decrease in FA was found during the chronic stroke) [28], increase in MD with a decrease in FA has been observed in the sclerotic hippocampi of chronic epilepsy patients [29]. In the case of brain tumor patients an increase in MD values with a decrease in FA was observed in cystic or necrotic areas [30].…”

Section: Dti Metrics (Derived From the Eigenvalues) And Their Interprmentioning

confidence: 94%

A Basic Introduction to Diffusion Tensor Imaging Mathematics and Image Processing Steps

Rajagopalan¹,

Jiang²,

Yue³

et al. 2017

Brain Disord Ther

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Diffusion tensor imaging (DTI) is one of the most powerful magnetic resonance imaging (MRI) techniques developed in the twentieth century. In spite of the fact that DTI has been in use for more than two decades, it is still hard to find publications that simplify mathematics behind DTI for DTI users without extensive mathematical background. We believe that this may prevent some researchers from using DTI technique to its fullest extent. To the best of our knowledge, there are no published reviews which have tried to clarify the methods of DTI measurement and analysis. In this article, we attempted to explain the mathematics of DTI in simple terms with the goal of providing DTI users, with a better understanding of this technique and its usage. In addition, we have also described the DTI processing steps and explained the reasons behind each step.

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Section: Dti Metrics (Derived From the Eigenvalues) And Their Interprmentioning

confidence: 94%

A Basic Introduction to Diffusion Tensor Imaging Mathematics and Image Processing Steps

Rajagopalan¹,

Jiang²,

Yue³

et al. 2017

Brain Disord Ther

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“…For details and the specific parameters related to collection and analysis of each image modality, see Osipowicz et al 32 and Tracy et al 40 and Supplemental Data. 43 During the task, the participant must generate members of the category "four-legged animals" for 1 minute, with the total number generated used as the variable of interest. The task requires semantic processing and lexical access of common nouns.…”

Section: Scanning Parametersmentioning

confidence: 99%

Functional MRI, resting state fMRI, and DTI for predicting verbal fluency outcome following resective surgery for temporal lobe epilepsy

Osipowicz

Sperling²,

Sharan

et al. 2016

JNS

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929cliNical article J Neurosurg 124:929-937, 2016 P redicting outcome following resective brain surgery remains a high-priority goal in neurology and neurosurgery. Recently, a need for classifying surgical outcome on the basis of functional status, such as cognition, rather than just seizure control, has been articulated. 44 A number of neuroimaging techniques give us insight into the neuroanatomical correlates of cognition. These techniques are increasingly being used as part of presurgical planning algorithms, 11,19,20,28 providing an opportunity to not only gain insights into the functional neuroanatomy of "at-risk" cognition and how it relates to the underlying pathology, but also use such insights to predict cognitive outcome following surgery, such as anterior temporal lobectomy (ATL) for epilepsy.The predictive power and the combined clinical utility of 3 major MRI techniques (functional MRI [fMRI], resting state fMRI [rsfMRI], and diffusion tensor imaging [DTI]) are unknown and untested. These 3 modalities can be conceptually combined to obtain a more complete view of the neural modules and connectivity networks implementing cognition and driving adaptive or maladaptive neuroplasticity responses in the brain. Functional MRI can be used to define an active network implementing a key function that might be "at risk" with temporal lobe surgery (e.g., verbal fluency), although the validity of this approach needs to be established in prospective studies.5 Preoperative fMRI has been shown to be sensitive to language and verbal memory laterality 9 and is a known predictor of cogabbreviatioNs ATL = anterior temporal lobectomy; DTI = diffusion tensor imaging; fMRI = functional MRI; RCI = Reliable Change Index; rsfMRI = resting state fMRI; TLE = temporal lobe epilepsy. obJective Predicting cognitive function following resective surgery remains an important clinical goal. Each MRI neuroimaging technique can potentially provide unique and distinct insight into changes that occur in the structural or functional organization of "at-risk" cognitive functions. The authors tested for the singular and combined power of 3 imaging techniques (functional MRI [fMRI], resting state fMRI, diffusion tensor imaging) to predict cognitive outcome following left (dominant) anterior temporal lobectomy for intractable epilepsy. methods The authors calculated the degree of deviation from normal, determined the rate of change in this measure across the pre- and postsurgical imaging sessions, and then compared these measures for their ability to predict verbal fluency changes following surgery. results The data show that the 3 neuroimaging techniques, in a combined model, can reliably predict cognitive outcome following anterior temporal lobectomy for medically intractable temporal lobe epilepsy. coNclusioNs These findings suggest that these 3 imaging modalities can be used effectively, in an additive fashion, to predict functional reorganization and cognitive outcome following anterior temporal lobectomy.

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“…Magnetic resonance imaging (MRI) has played a key role in the evaluation of TLE, by allowing sensitive in vivo characterization and detection of HS across multiple contrasts. Hippocampal atrophy on T1-weighted MRI 1 , increased signal on T2-weighted images 2 , and chronic increases in tissue diffusivity 3 are established markers of HS (TLE-HS), and their individual or combined analysis is highly effective in patient lateralization and surgical target definition. 4 Although HS represents the most frequent pathological finding in TLE, analysis of surgical specimens has also consistently identified a subgroup of patients who present with no apparent cell loss but rather isolated gliosis (TLE-G).…”

mentioning

confidence: 99%

The spectrum of structural and functional imaging abnormalities in temporal lobe epilepsy

Bernhardt

Bernasconi

Liu

et al. 2016

Annals of Neurology

141

119

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Water diffusion in the human hippocampus in epilepsy

Cited by 115 publications

References 38 publications

A Basic Introduction to Diffusion Tensor Imaging Mathematics and Image Processing Steps

A Basic Introduction to Diffusion Tensor Imaging Mathematics and Image Processing Steps

Functional MRI, resting state fMRI, and DTI for predicting verbal fluency outcome following resective surgery for temporal lobe epilepsy

The spectrum of structural and functional imaging abnormalities in temporal lobe epilepsy

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