The physical and biological basis of quantitative parameters derived from diffusion MRI

Diffusion magnetic resonance imaging is a quantitative imaging technique that measures the underlying molecular diffusion of protons. Diffusion-weighted imaging (DWI) quantifies the apparent diffusion coefficient (ADC) which was first used to detect early ischemic stroke. However this does not take account of the directional dependence of diffusion seen in biological systems (anisotropy).Diffusion tensor imaging (DTI) provides a mathematical model of diffusion anisotropy and is widely used. Parameters, including fractional anisotropy (FA), mean diffusivity (MD), parallel and perpendicular diffusivity can be derived to provide sensitive, but non-specific, measures of altered tissue structure. They are typically assessed in clinical studies by voxel-based or region-of-interest based analyses.The increasing recognition of the limitations of the diffusion tensor model has led to more complex multi-compartment models such as CHARMED, AxCaliber or NODDI being developed to estimate microstructural parameters including axonal diameter, axonal density and fiber orientations. However these are not yet in routine clinical use due to lengthy acquisition times.In this review, I discuss how molecular diffusion may be measured using diffusion MRI, the biological and physical bases for the parameters derived from DWI and DTI, how these are used in clinical studies and the prospect of more complex tissue models providing helpful micro-structural information

Memory fMRI predicts verbal memory decline after anterior temporal lobe resection.

To develop a clinically applicable memory functional MRI (fMRI) method of predicting postsurgical memory outcome in individual patients

Automated hippocampal segmentation in patients with epilepsy: Available free online

Hippocampal sclerosis, a common cause of refractory focal epilepsy, requires hippocampal volumetry for accurate diagnosis and surgical planning. Manual segmentation is time-consuming and subject to interrater/intrarater variability. Automated algorithms perform poorly in patients with temporal lobe epilepsy. We validate and make freely available online a novel automated method

Structural correlates of impaired working memory in hippocampal sclerosis

PURPOSE: Temporal lobe epilepsy (TLE) has been considered to impair long-term memory, whilst not affecting working memory, but recent evidence suggests that working memory is compromised. Functional MRI (fMRI) studies demonstrate that working memory involves a bilateral frontoparietal network the activation of which is disrupted in hippocampal sclerosis (HS). A specific role of the hippocampus to deactivate during working memory has been proposed with this mechanism faulty in patients with HS. Structural correlates of disrupted working memory in HS have not been explored. METHODS: We studied 54 individuals with medically refractory TLE and unilateral HS (29 left) and 28 healthy controls. Subjects underwent 3T structural MRI, a visuospatial n-back fMRI paradigm and diffusion tensor imaging (DTI). Working memory capacity assessed by three span tasks (digit span backwards, gesture span, motor sequences) was combined with performance in the visuospatial paradigm to give a global working memory measure. Gray and white matter changes were investigated using voxel-based morphometry and voxel-based analysis of DTI, respectively. KEY FINDINGS: Individuals with left or right HS performed less well than healthy controls on all measures of working memory. fMRI demonstrated a bilateral frontoparietal network during the working memory task with reduced activation of the right parietal lobe in both patient groups. In left HS, gray matter loss was seen in the ipsilateral hippocampus and parietal lobe, with maintenance of the gray matter volume of the contralateral parietal lobe associated with better performance. White matter integrity within the frontoparietal network, in particular the superior longitudinal fasciculus and cingulum, and the contralateral temporal lobe, was associated with working memory performance. In right HS, gray matter loss was also seen in the ipsilateral hippocampus and parietal lobe. Working memory performance correlated with the gray matter volume of both frontal lobes and white matter integrity within the frontoparietal network and contralateral temporal lobe. SIGNIFICANCE: Our data provide further evidence that working memory is disrupted in HS and impaired integrity of both gray and white matter is seen in functionally relevant areas. We suggest this forms the structural basis of the impairment of working memory, indicating widespread and functionally significant structural changes in patients with apparently isolated HS

Voxel-based magnetic resonance image postprocessing in epilepsy

OBJECTIVE: Although the general utility of voxel-based processing of structural magnetic resonance imaging (MRI) data for detecting occult lesions in focal epilepsy is established, many differences exist among studies, and it is unclear which processing method is preferable. The aim of this study was to compare the ability of commonly used methods to detect epileptogenic lesions in magnetic resonance MRI-positive and MRI-negative patients, and to estimate their diagnostic yield. METHODS: We identified 144 presurgical focal epilepsy patients, 15 of whom had a histopathologically proven and MRI-visible focal cortical dysplasia; 129 patients were MRI negative with a clinical hypothesis of seizure origin, 27 of whom had resections. We applied four types of voxel-based morphometry (VBM), three based on T1 images (gray matter volume, gray matter concentration, junction map [JM]) and one based on normalized fluid-attenuated inversion recovery (nFSI). Specificity was derived from analysis of 50 healthy controls. RESULTS: The four maps had different sensitivity and specificity profiles. All maps showed detection rates for focal cortical dysplasia patients (MRI positive and negative) of >30% at a strict threshold of p 60% with a liberal threshold of p < 0.0001 (uncorrected), except for gray matter volume (14% and 27% detection rate). All maps except nFSI showed poor specificity, with high rates of false-positive findings in controls. In the MRI-negative patients, absolute detection rates were lower. A concordant nFSI finding had a significant positive odds ratio of 7.33 for a favorable postsurgical outcome in the MRI-negative group. Spatial colocalization of JM and nFSI was rare, yet showed good specificity throughout the thresholds. SIGNIFICANCE: All VBM variants had specific diagnostic properties that need to be considered for an adequate interpretation of the results. Overall, structural postprocessing can be a useful tool in presurgical diagnostics, but the low specificity of some maps has to be taken into consideration

Optic radiation tractography and vision in anterior temporal lobe resection.

Anterior temporal lobe resection (ATLR) is an effective treatment for refractory temporal lobe epilepsy but may result in a contralateral superior visual field deficit (VFD) that precludes driving in the seizure-free patient. Diffusion tensor imaging (DTI) tractography can delineate the optic radiation preoperatively and stratify risk. It would be advantageous to incorporate display of tracts into interventional magnetic resonance imaging (MRI) to guide surgery

Memory network plasticity after temporal lobe resection: a longitudinal functional imaging study

Anterior temporal lobe resection can control seizures in up to 80% of patients with temporal lobe epilepsy. Memory decrements are the main neurocognitive complication. Preoperative functional reorganization has been described in memory networks, but less is known of postoperative reorganization. We investigated reorganization of memory-encoding networks preoperatively and 3 and 12 months after surgery. We studied 36 patients with unilateral medial temporal lobe epilepsy (19 right) before and 3 and 12 months after anterior temporal lobe resection. Fifteen healthy control subjects were studied at three equivalent time points. All subjects had neuropsychological testing at each of the three time points. A functional magnetic resonance imaging memory-encoding paradigm of words and faces was performed with subsequent out-of-scanner recognition assessments. Changes in activations across the time points in each patient group were compared to changes in the control group in a single flexible factorial analysis. Postoperative change in memory across the time points was correlated with postoperative activations to investigate the efficiency of reorganized networks. Left temporal lobe epilepsy patients showed increased right anterior hippocampal and frontal activation at both 3 and 12 months after surgery relative to preoperatively, for word and face encoding, with a concomitant reduction in left frontal activation 12 months postoperatively. Right anterior hippocampal activation 12 months postoperatively correlated significantly with improved verbal learning in patients with left temporal lobe epilepsy from preoperatively to 12 months postoperatively. Preoperatively, there was significant left posterior hippocampal activation that was sustained 3 months postoperatively at word encoding, and increased at face encoding. For both word and face encoding this was significantly reduced from 3 to 12 months postoperatively. Patients with right temporal lobe epilepsy showed increased left anterior hippocampal activation on word encoding from 3 to 12 months postoperatively compared to preoperatively. On face encoding, left anterior hippocampal activations were present preoperatively and 12 months postoperatively. Left anterior hippocampal and orbitofrontal cortex activations correlated with improvements in both design and verbal learning 12 months postoperatively. On face encoding, there were significantly increased left posterior hippocampal activations that reduced significantly from 3 to 12 months postoperatively. Postoperative changes occur in the memory-encoding network in both left and right temporal lobe epilepsy patients across both verbal and visual domains. Three months after surgery, compensatory posterior hippocampal reorganization that occurs is transient and inefficient. Engagement of the contralateral hippocampus 12 months after surgery represented efficient reorganization in both patient groups, suggesting that the contralateral hippocampus contributes to memory outcome 12 months after surgery

Quantitative Susceptibility Mapping (QSM) is Sensitive to Hippocampal and Subcortical Gray Matter Changes in Temporal Lobe Epilepsy

Although temporal lobe epilepsy (TLE) results in widespread changes in MRI measures of tissue volume, diffusion and functional connectivity, changes in tissue composition in TLE have not been investigated with MRI. Quantitative susceptibility mapping (QSM) is sensitive to changes in tissue composition, in particular to iron and myelin. Here, we show for the first time that QSM is sensitive to gray matter abnormalities in 31patients with temporal lobe epilepsy (TLE) compared to 23 healthy controls, and showed significant susceptibility changes in the hippocampus in left TLE patients, and in the bilateral thalamus in both left and right TLE

The impact of epilepsy surgery on the structural connectome and its relation to outcome

BACKGROUND: Temporal lobe surgical resection brings seizure remission in up to 80% of patients, with long-term complete seizure freedom in 41%. However, it is unclear how surgery impacts on the structural white matter network, and how the network changes relate to seizure outcome. METHODS: We used white matter fibre tractography on preoperative diffusion MRI to generate a structural white matter network, and postoperative T1-weighted MRI to retrospectively infer the impact of surgical resection on this network. We then applied graph theory and machine learning to investigate the properties of change between the preoperative and predicted postoperative networks. RESULTS: Temporal lobe surgery had a modest impact on global network efficiency, despite the disruption caused. This was due to alternative shortest paths in the network leading to widespread increases in betweenness centrality post-surgery. Measurements of network change could retrospectively predict seizure outcomes with 79% accuracy and 65% specificity, which is twice as high as the empirical distribution. Fifteen connections which changed due to surgery were identified as useful for prediction of outcome, eight of which connected to the ipsilateral temporal pole. CONCLUSIONS: Our results suggest that the use of network change metrics may have clinical value for predicting seizure outcome. This approach could be used to prospectively predict outcomes given a suggested resection mask using preoperative data only