The detection and significance of subtle changes in mixed-signal brain lesions by serial MRI scan matching and spatial normalization

Automatic change detection in multimodal serial MRI: application to multiple sclerosis lesion evolution

The automatic analysis of subtle changes between MRI scans is an important tool for assessing disease evolution over time. Manual labeling of evolutions in 3D data sets is tedious and error prone. Automatic change detection, however, remains a challenging image processing problem. A variety of MRI artifacts introduce a wide range of unrepresentative changes between images, making standard change detection methods unreliable. In this study we describe an automatic image processing system that addresses these issues. Registration errors and undesired anatomical deformations are compensated using a versatile multiresolution deformable image matching method that preserves significant changes at a given scale. A nonlinear intensity normalization method is associated with statistical hypothesis test methods to provide reliable change detection. Multimodal data is optionally exploited to reduce the false detection rate. The performance of the system was evaluated on a large database of 3D multimodal, MR images of patients suffering from relapsing remitting multiple sclerosis (MS). The method was assessed using receiver operating characteristics (ROC) analysis, and validated in a protocol involving two neurologists. The automatic system outperforms the human expert, detecting many lesion evolutions that are missed by the expert, including small, subtle changes.

Improving tissue segmentation of human brain MRI through preprocessing by the Gegenbauer reconstruction method

The Gegenbauer image reconstruction method, previously shown to improve the quality of magnetic resonance images, is utilized in this study as a segmentation preprocessing step. It is demonstrated that, for all simulated and real magnetic resonance images used in this study, the Gegenbauer reconstruction method improves the accuracy of segmentation. Although it is more desirable to use the k-space data for the Gegenbauer reconstruction method, only information acquired from MR images is necessary for the reconstruction, making the procedure completely self-contained and viable for all human brain segmentation algorithms.

Automatic segmentation of the brain and intracranial cerebrospinal fluid in T1-weighted volume MRI scans of the head, and its application to serial cerebral and intracranial volumetry

A new fully automatic algorithm for the segmentation of the brain and total intracranial cerebrospinal fluid (CSF) from T(1)-weighted volume MRI scans of the head, called Exbrain v.2, is described. The algorithm was developed in the context of serial intracranial volumetry. A brain mask obtained using a previous version of the algorithm forms the basis of the CSF segmentation. Improved brain segmentation is then obtained by iterative tracking of the brain-CSF interface. Gray matter (GM), white matter (WM), and intracranial CSF volumes and probability maps are calculated based on a model of intensity probability distribution (IPD) that includes two partial volume classes: GM-CSF and GM-WM. Accuracy was assessed using the Montreal Neurological Institute's (MNI) digital phantom scan. Reproducibility was assessed using scan pairs from 24 controls and 10 patients with epilepsy. Segmentation overlap with the gold standard was 98% for the brain and 95%, 96%, and 97% for the GM, WM, and total intracranial contents, respectively; CSF overlap was 86%. In the controls, the Bland and Altman coefficient of reliability (CR) was 35.2 cm(3) for the total brain volume (TBV) and 29.0 cm(3) for the intracranial volume (ICV). Scan-matching reduced CR to 25.2 cm(3) and 17.1 cm(3) for the TBV and ICV, respectively. For the patients, similar CR values were obtained for the ICV.

Clinical application of neuroimaging in epilepsy

OBJECTIVE

To evaluate the use of neuroimaging in clinical practice and to assess the prevalence of detected structural abnormalities in epilepsy patients in a clinical set up.

METHODS

919 outpatients were identified and the scan results reviewed. A total of 677 patients had chronic active epilepsy (88 had idiopathic generalised epilepsy (IGE), 588 had localisation related epilepsy, one had symptomatic generalised epilepsy), 57 had a single epileptic seizure, 46 were in remission, and 139 had non-epileptic attacks.

RESULTS

391 patients had no scan (53 patients in this group had IGE, 182 had localisation related epilepsy, one had generalised symptomatic epilepsy, 18 had single epileptic attacks, 21 were in remission, 116 had non-epileptic attacks). Altogether 528 patients had a scan, the results were not available in 33, 163 had x ray computed tomography (CT) only, 178 had standard magnetic resonance imaging (MRI) (slice thickness 5 mm), and 154 had high resolution MRI (including a T1 weighted sequence with 1.5 mm thick slices). Some 252 of 495 scans (51%) were abnormal. Abnormalities were hippocampal sclerosis (n=128), atrophy or non-specific white matter lesions (n=35), vascular abnormalities (n=27), tumours (n=25), brain damage (n=24), malformations of cortical development (n=13). Excluding atrophy and non-specific white matter lesions the prevalence of detected abnormalities was 54% in localisation related epilepsy, 18% in single seizure patients, 16% in epilepsy in remission, and 0% in IGE and non-epileptic attacks.

CONCLUSIONS

Abnormalities were detected in more than half of all patients with localisation related epilepsy, and in about one in five patients with single seizures or epilepsy in remission. Many patients had no scan or only CT or standard MRI. The true prevalence of structural abnormalities may be have been higher. Scanning did not add any information in patients with IGE or non-epileptic attacks.

Progressive neocortical damage in epilepsy

Our objective was to determine the pattern and extent of generalized and focal neocortical atrophy that develops in patients with epilepsy and the factors associated with such changes. As part of a prospective, longitudinal follow-up study of 122 patients with chronic epilepsy, 68 newly diagnosed patients, and 90 controls, serial magnetic resonance imaging scans were obtained 3.5 years apart. Image subtraction was used to identify diffuse and focal neocortical change that was quantified with a regional brain atlas and a fully automated segmentation algorithm. New focal or generalized neocortical volume losses were identified in 54% of patients with chronic epilepsy, 39% of newly diagnosed patients and 24% of controls. Patients with chronic epilepsy were significantly more likely to develop neocortical atrophy than control subjects. The increased risk of cerebral atrophy in epilepsy was not related to a history of documented seizures. Risk factors for neocortical atrophy were age and multiple antiepileptic drug exposure. Focal and generalized neocortical atrophy commonly develops in chronic epilepsy. Neocortical changes seen in a quarter of our control group over 3.5 years were likely to reflect physiological changes. Our results show that ongoing cerebral atrophy may be widespread and remote from the putative epileptic focus, possibly reflecting extensive networks and interconnections between cortical regions.

Subvoxel image registration of multislice (2D) magnetic resonance images in patients with high-grade gliomas of the brain

AIMS

To implement a multislice two-dimensional (2D) T2-weighted sequence suitable for subvoxel image registration and to assess its usefulness in detecting change in high-grade intracranial gliomas.

MATERIALS AND METHODS

Twenty patients with high-grade gliomas were studied on two or more occasions. T2-weighted multislice pulse sequences with a Gaussian slice profile, 50% overlapping slices and nearly isotropic voxels were acquired. The images were registered and subtraction images were produced. The images were compared with three-dimensional (3D) T1-weighted registered images and conventional unregistered T2-weighted images. All images were scored for changes in the lesions and ventricular system.

RESULTS

The 2D and 3D registered subtraction images were the most sensitive for detecting changes in both the lesions and other regions in the brain. The mean rank scores were significantly higher for the lesions (chi2=86.742; df=5, n=38, P<0.0001) and for the ventricles (chi2=63.837; df=5, n=35, P<0.0001) compared with the unregistered and registered anatomical images. The subtraction images were also most sensitive for detecting signal intensity changes irrespective of the direction of change.

CONCLUSION

Rigid body subvoxel registration can be successfully performed with both multislice 2D and 3D imaging. In principle, virtually all forms of clinical MR images of the brain can be accurately registered and subtracted.

Automated histogram-based brain segmentation in T1-weighted three-dimensional magnetic resonance head images

Current semiautomated magnetic resonance (MR)-based brain segmentation and volume measurement methods are complex and not sufficiently accurate for certain applications. We have developed a simpler, more accurate automated algorithm for whole-brain segmentation and volume measurement in T(1)-weighted, three-dimensional MR images. This histogram-based brain segmentation (HBRS) algorithm is based on histograms and simple morphological operations. The algorithm's three steps are foreground/background thresholding, disconnection of brain from skull, and removal of residue fragments (sinus, cerebrospinal fluid, dura, and marrow). Brain volume was measured by counting the number of brain voxels. Accuracy was determined by applying HBRS to both simulated and real MR data. Comparing the brain volume rendered by HBRS with the volume on which the simulation is based, the average error was 1.38%. By applying HBRS to 20 normal MR data sets downloaded from the Internet Brain Segmentation Repository and comparing them with expert segmented data, the average Jaccard similarity was 0.963 and the kappa index was 0.981. The reproducibility of brain volume measurements was assessed by comparing data from two sessions (four total data sets) with human volunteers. Intrasession variability of brain volumes for sessions 1 and 2 was 0.55 +/- 0.56 and 0.74 +/- 0.56%, respectively; the mean difference between the two sessions was 0.60 +/- 0.46%. These results show that the HBRS algorithm is a simple, fast, and accurate method to determine brain volume with high reproducibility. This algorithm may be applied to various research and clinical investigations in which brain segmentation and volume measurement involving MRI data are needed.

MRI studies. Do seizures damage the brain?

Methods to assess the development of cerebral damage need to be quantitative, reliable, reproducible and safe. They must be acceptable to patients and to a healthy control group, for repeated use and the acquisition and analytical methods must be stable over years. Longitudinal studies are necessary to determine whether secondary cerebral damage occurs as a consequence to the epilepsies. The principal aim of longitudinal studies is to detect physical evidence of brain damage when it occurs. Patient groups will be heterogeneous in this regard and analysis will need to be not only of changes in group means, but also of the number of patients who show significant changes in imaging parameters, that exceed the limits of test-retest reliability. MRI is attractive as a tool to evaluate the presence and development of cerebral damage in patients with epilepsy. MRI is readily available and non-invasive, making it acceptable to patients and controls. MRI volumetry is reliable and reproducible, but the sensitivity of the method to detect subtle abnormalities has not yet been established. Longitudinal studies are ongoing in patients with newly diagnosed and chronic epilepsy, with an inter-scan interval of 3.5 years, using complementary voxel-based and region-based methods that can detect changes in hippocampal and cerebellar volumes of 3% and neocortical volume changes of 1.6%. MR spectroscopy may be more sensitive for detecting abnormalities, but the test-retest reliability is less good. Other MRI tools, such as diffusion tensor imaging, may be useful methods for evaluating secondary cerebral damage acutely and chronically.

Automatic detection and segmentation of evolving processes in 3D medical images: Application to multiple sclerosis

The study of temporal series of medical images can be helpful for physicians to perform pertinent diagnoses and to help them in the follow-up of a patient: in some diseases, lesions, tumors or anatomical structures vary over time in size, position, composition, etc., either because of a natural pathological process or under the effect of a drug or a therapy. It is a laborious and subjective task to visually and manually analyze such images. Thus the objective of this work was to automatically detect regions with apparent local volume variation with a vector field operator applied to the local displacement field obtained after a non-rigid registration between two successive temporal images. On the other hand, quantitative measurements, such as the volume variation of lesions or segmentation of evolving lesions, are important. By studying the information of apparent shrinking areas in the direct and reverse displacement fields between images, we are able to segment evolving lesions. Then we propose a method to segment lesions in a whole temporal series of images. In this article we apply this approach to automatically detect and segment multiple sclerosis lesions that evolve in time series of MRI scans of the brain. At this stage, we have only applied the approach to a few experimental cases to demonstrate its potential. A clinical validation remains to be done, which will require important additional work.

Neuroimaging methods to evaluate the etiology and consequences of epilepsy

Magnetic resonance imaging (MRI) is widely available and is generally the imaging method of first choice for identifying the structural basis of seizure disorders, having both sensitivity and specificity. Positron emission tomography (PET) and single photon emission computed tomography (SPECT) scans may be more sensitive in some patients when MRI is unremarkable, but do not confer specificity of etiological diagnosis. Methods to assess the consequences of epilepsy on the brain need to be quantitative, reliable, reproducible and safe. They must be acceptable to patients and to a healthy control group for repeated use, and the acquisition and analytical methods must be stable over years. Longitudinal studies are necessary to determine whether secondary cerebral damage occurs as a consequence to the epilepsies. Patient groups will be heterogeneous in this regard and analysis will need to be not only of changes in group means, but also of the number of patients who show significant changes in imaging parameters, that exceed the limits of test-retest reliability and of changes in age-matched controls. MRI is an attractive tool to evaluate the presence and development of cerebral damage in patients with epilepsy as it is readily available, non-invasive, and acceptable to patients and controls. MRI volumetry is reliable and reproducible, but the sensitivity of the method to detect subtle abnormalities has not yet been established. Preliminary analysis of longitudinal studies of patients with newly diagnosed and chronic active epilepsy suggests that 10% of newly diagnosed patients and 25% of those with chronic active epilepsy develop significant cerebral, hippocampal or cerebellar atrophy over 3.5 years. MR spectroscopy may be more sensitive for detecting abnormalities, but the test-retest reliability is less good. Other MRI tools such as diffusion tensor imaging (DTI) may be useful methods for evaluating secondary cerebral damage acutely and chronically.

Amygdala pathology in psychosis of epilepsy: A magnetic resonance imaging study in patients with temporal lobe epilepsy

Psychosis of epilepsy (POE) has been recognized as a severe complication of chronic intractable epilepsy for more than a century. Most of the clinical symptoms of POE are reminiscent of schizophrenia. Nevertheless, there is general agreement that the phenomenology of POE differs from classical schizophrenia. The temporal lobe hypothesis of schizophrenia put forward in the 1960s notes that episodes with paranoid psychoses are more prevalent in temporal lobe epilepsy (TLE). However, the aetiology and pathogenesis of POE are poorly understood. One of the strongest biological findings in schizophrenia is volume loss of temporal lobe structures and the hippocampus in particular. In order to test the hypothesis that atrophy of the hippocampus and the amygdala is found in patients with TLE and POE, we performed a retrospective study of all patients with TLE who were admitted to the assessment unit of the Chalfont Centre for Epilepsy from 1995 until 1999. Twenty-six (2.6%) of these 1008 patients fulfilled inclusion criteria and were compared with 24 patients with TLE without psychopathology and 20 healthy volunteers. All patients underwent extensive MRI investigations, including volumetric data sets and quantitative T(2 )relaxometry. We found that patients with TLE and POE differed from patients with TLE alone and healthy volunteers in that the total brain volumes were significantly smaller. While there were no differences in hippocampal volumes between the three study groups, there was a significant 16-18% enlargement of the amygdala on both sides in patients with POE. Our findings support the notion that POE is a distinct nosologic entity differing from schizophrenia not only in clinical details but also in neurobiological aspects. The finding of amygdala enlargement agrees with the observation of an association between dysphoric disorders of epilepsy and POE described nearly 100 years ago.

MR image-based measurement of rates of change in volumes of brain structures. Part I: method and validation

A detailed analysis procedure is described for evaluating rates of volumetric change in brain structures based on structural magnetic resonance (MR) images. In this procedure, a series of image processing tools have been employed to address the problems encountered in measuring rates of change based on structural MR images. These tools include an algorithm for intensity non-uniformity correction, a robust algorithm for three-dimensional image registration with sub-voxel precision and an algorithm for brain tissue segmentation. However, a unique feature in the procedure is the use of a fractional volume model that has been developed to provide a quantitative measure for the partial volume effect. With this model, the fractional constituent tissue volumes are evaluated for voxels at the tissue boundary that manifest partial volume effect, thus allowing tissue boundaries be defined at a sub-voxel level and in an automated fashion. Validation studies are presented on key algorithms including segmentation and registration. An overall assessment of the method is provided through the evaluation of the rates of brain atrophy in a group of normal elderly subjects for which the rate of brain atrophy due to normal aging is predictably small. An application of the method is given in Part II where the rates of brain atrophy in various brain regions are studied in relation to normal aging and Alzheimer's disease.

A longitudinal quantitative MRI study of community-based patients with chronic epilepsy and newly diagnosed seizures: methodology and preliminary findings

Experimental and human data suggest that progressive cerebral damage may result from the cumulative effect of brief recurrent seizures. Longitudinal studies addressing this fundamental question, however, are lacking. We have addressed this need with a large prospective community-based observational study, which aims to rescan 154 patients with chronic active epilepsy and 90 patients with newly diagnosed seizures, after an interval of 3.5 years. Here, we describe the quantitative magnetic resonance methods used to identify subtle volume changes in hippocampal, cerebellar, and neocortical structures over time and report preliminary findings. Using this methodology, we have previously shown that we can reliably detect individual hippocampal volume (HV) and cerebellar volume (CBV) changes greater than 3.1 and 3.0%, respectively (Lemieux et al, 2000). Analysis of the first 53 subjects (24 patients with chronic active epilepsy, 9 patients with newly diagnosed seizures, and 20 controls) has demonstrated significant HV losses in 4 individuals. Automated and semiautomated calculation has detected significant reductions in CBV, total brain volume, and gray matter volume in 2, 3, and 1 subject, respectively. There were no significant white matter volume losses detected. Data collected from rescanning the entire cohorts will help to provide further information on the relationship between recurrent seizures and secondary brain damage.

Normalized accurate measurement of longitudinal brain change

PURPOSE

Quantitative measurement of change in brain size and shape (e.g., to estimate atrophy) is an important current area of research. New methods of change analysis attempt to improve robustness, accuracy, and extent of automation. A fully automated method has been developed that achieves high estimation accuracy.

METHOD

A fully automated method of longitudinal change analysis is presented here, which automatically segments brain from nonbrain in each image, registers the two brain images while using estimated skull images to constrain scaling and skew, and finally estimates brain surface motion by tracking surface points to subvoxel accuracy.

RESULTS AND CONCLUSION

The method described has been shown to be accurate ( approximately 0.2% brain volume change error) and to achieve high robustness (no failures in several hundred analyses over a range of different data sets).

Automated registration of dynamic MR images for the quantification of myocardial perfusion

Cardiac dynamic magnetic resonance imaging (MRI) after contrast media injection suffers from motion induced by free breathing during acquisition. This work presents an automated approach for motion correction of the heart. The registration is based on the multipass/multiresolution iterative minimizing of intrinsic differences between each image and a reference image coupled to a two-dimensional/3 parameters rigid body correction. The efficiency of this correction method was evaluated with anatomical landmarks, various cost functions, and for a compartment model fit of the data with 2 parameters: K1, the blood to myocardium transfer coefficient; and Vd, the distribution volume of the contrast media. The variability of K1 and Vd, derived from the fit of the registered images (using the manual correction as a gold standard), was significantly reduced by comparison with the variability obtained from the uncorrected images (P < 0.04). This motion correction method also clearly improves the analysis of dynamic cardiac MRI after contrast media injection in comparison to manual correction.

Medical image registration

Radiological images are increasingly being used in healthcare and medical research. There is, consequently, widespread interest in accurately relating information in the different images for diagnosis, treatment and basic science. This article reviews registration techniques used to solve this problem, and describes the wide variety of applications to which these techniques are applied. Applications of image registration include combining images of the same subject from different modalities, aligning temporal sequences of images to compensate for motion of the subject between scans, image guidance during interventions and aligning images from multiple subjects in cohort studies. Current registration algorithms can, in many cases, automatically register images that are related by a rigid body transformation (i.e. where tissue deformation can be ignored). There has also been substantial progress in non-rigid registration algorithms that can compensate for tissue deformation, or align images from different subjects. Nevertheless many registration problems remain unsolved, and this is likely to continue to be an active field of research in the future.

Extrahippocampal temporal lobe atrophy in temporal lobe epilepsy and mesial temporal sclerosis

Visual inspection and volumetric analysis of MRIs allow mesial temporal sclerosis (MTS) to be reliably identified in patients with temporal lobe epilepsy. The presence of unilateral MTS ipsilateral to the side of habitual seizure onset is an indicator for the prognosis of good outcome after temporal lobe resection. There is evidence to suggest that widespread temporal lobe pathology, leading to atrophy, may be associated with MTS and such abnormal tissue may play an important role in epileptogenesis. We have analysed quantitatively the volumes of the mesial and lateral temporal lobe substructures in MRIs from 62 patients with intractable mesial temporal lobe epilepsy and in 20 normal controls. We found significant atrophy in these structures in patients, ranging from 8.3 to 18.4% compared with controls. The degree of atrophy in the extrahippocampal structures correlated with the degree of hippocampal atrophy, suggesting that a common process may be responsible. There was no correlation between the degree of atrophy in the extrahippocampal structures and the duration of epilepsy, a history of febrile convulsions or of generalized seizures. These findings suggest that there may be widespread pathological abnormalities in the temporal lobe associated with MTS. The importance of extrahippocampal atrophy to surgical outcome and whether it occurs in temporal lobe epilepsy not associated with MTS remain to be investigated.

Topology preserving deformable image matching using constrained hierarchical parametric models

In this paper, we address the issue of topology preservation in deformable image matching. A novel constrained hierarchical parametric approach is presented, that ensures that the mapping is globally one-to one and thus preserves topology in the deformed image. The transformation between the source and target images is parameterized at different scales, using a decomposition of the deformation vector field over a sequence of nested (multiresolution) subspaces. The Jacobian of the mapping is controlled over the continuous domain of the transformation, ensuring actual topology preservation on the whole image support. The resulting fast nonlinear constrained optimization algorithm enables to track large nonlinear deformations while preserving the topology. Experimental results are presented both on simulated data and on real medical images.

Hippocampal and cerebellar volumetry in serially acquired MRI volume scans

In this work, we describe methodologies for serial volumetric measurements of hippocampi and cerebella. Serial scans were co-registered and intensity matched prior to the volumetric measurements. Manual drawing was used to define the boundaries of the hippocampi. For the cerebellar volumetric measurements, the brain was automatically segmented from the co-registered scans; manual drawing was used to define the boundary between the cerebellum and the cerebrum and brainstem. The operator was blinded to the nature of the subject (patient or normal control) and the chronological order of the scans. The coefficient of reliability of hippocampal volume measurements in a group of 20 controls was 0.078 cm(3) (3.1% of the mean baseline volume); for the cerebellum, the value was 3.8 cm(3) (3.0% of the mean baseline volume). We conclude that the methods presented are valid and that the software provides a useful integrated tool for the quantitative analysis of structural changes in serially acquired volume MRI data in prospective, blinded studies.

Association between brain size and abstinence from alcohol

Brain shrinkage with chronic alcoholism is well acknowledged. We have shown, with quantitative analysis of serial scans, an increase in hippocampal, cerebral, and cerebellar volume after abstinence from alcohol.

Automatic measurement of changes in brain volume on consecutive 3D MR images by segmentation propagation

This article presents a technique to automatically measure changes in the volume of a structure of interest in successive 3D magnetic resonance (MR) images and its application in the study of the brain and lateral cerebral ventricles. The only manual step is a segmentation of the structure of interest in the first image. The analysis comprises, first, precise rigid co-registration of the time series of images; second, computation of residual deformations between pairs of images; third, automatic quantification of the volume change, obtained by propagation of the segmentation of the structure of interest through the series of MR images. This approach has been applied to monitor changes in the volume of the brain and lateral cerebral ventricles in a healthy subject and a patient with primary progressive aphasia (PPA). Results are consistent with those obtained by application of the boundary shift integral (BSI) and by stereology in the same subjects.

Voxel similarity measures for 3-D serial MR brain image registration

We have evaluated eight different similarity measures used for rigid body registration of serial magnetic resonance (MR) brain scans. To assess their accuracy we used 33 clinical three-dimensional (3-D) serial MR images, with deformable extradural tissue excluded by manual segmentation and simulated 3-D MR images with added intensity distortion. For each measure we determined the consistency of registration transformations for both sets of segmented and unsegmented data. We have shown that of the eight measures tested, the ones based on joint entropy produced the best consistency. In particular, these measures seemed to be least sensitive to the presence of extradural tissue. For these data the difference in accuracy of these joint entropy measures, with or without brain segmentation, was within the threshold of visually detectable change in the difference images.

Affective aggression in patients with temporal lobe epilepsy: a quantitative MRI study of the amygdala

Recurrent episodes with interictal affective aggression are a rare but well-recognized problem in patients with temporal lobe epilepsy. They are referred to as episodic dyscontrol or, more precisely, as intermittent explosive disorder (IED). The amygdala play a crucial role in the affective evaluation of multimodal sensory input and the neurobiological mediation of aggressive behaviour. With hippocampal sclerosis, in the context of mesial temporal lobe sclerosis, being the most common cause of temporal lobe epilepsy, we hypothesized that the amygdala might be affected by the same pathogenic process in aggressive patients. We investigated 50 patients with temporal lobe epilepsy: 25 with and 25 without a history of IED. Data from clinical, electrophysiological, neuropsychological and psychometric investigations were obtained, as well as MRI scans for the quantitative assessment of possible amygdala pathology. We found no evidence of a higher prevalence of amygdala sclerosis in the aggressive patients. Hippocampal sclerosis was significantly less common in patients with temporal lobe epilepsy and IED. However, a significant subgroup of patients (20%) with temporal lobe epilepsy and aggressive behaviour had severe amygdala atrophy in the context of a history of encephalitis. Another subgroup of aggressive patients (28%) had different left temporal lesions affecting either the amygdala or periamygdaloid structures. IED was associated with left-sided or bilateral EEG and MRI abnormalities, low IQ and high scores in depression and anxiety.

Amygdala enlargement in dysthymia--a volumetric study of patients with temporal lobe epilepsy

BACKGROUND

Previous studies indicated an important role of the amygdala for emotional information processing. We investigated a possible relationship between amygdala volumes, aggressive behavior, and dysthymia, in patients with temporal lobe epilepsy (TLE).

METHODS

Patients with TLE with and without aggression or dysthymia and healthy volunteers were assessed using quantitative MRI. Amygdala volumes were measured in a blinded fashion and corrected for total brain volumes.

RESULTS

There was a highly significant enlargement of left and right amygdala volumes in patients with dysthymia (right side, p < .000; left side, p = .001). We found a significant positive correlation between left amygdala volumes (p = .02) and a trend towards positive correlation between right amygdala volumes and depression (p = .06), as measured with the Beck Depression Inventory. Amygdala volumes of females were significantly larger than those of males (left side: p = .005; right side: p = .06).

CONCLUSIONS

This is the second report of a relationship between amygdala volumes and depressed mood, confirming an earlier finding in patients with bipolar disease, and the first study reporting a correlation between amygdala volumes and depression. Increased processing of emotional information might increase amygdala blood flow and subsequently, result in amygdala enlargement.

Wallerian degeneration in the optic radiation after temporal lobectomy demonstrated in vivo with diffusion tensor imaging

PURPOSE

Diffusion tensor imaging allows the quantitative assessment of the microstructural organization of tracts in vivo (MR tractography). We used the new technique of MR tractography to demonstrate the effects of temporal lobectomy on the optic radiation.

METHODS

Spatially normalised maps encoding magnitude of the bias (anisotropy) of diffusion of three patients with temporal lobe resections were compared with spatially normalised diffusion maps of 22 control subjects. All three patients were operated on for the treatment of medically intractable temporal lobe epilepsy and had a normal neurologic examination before surgery. One patient had an amygdalocorticectomy. Two patients had standard en bloc resections, one of whom developed a homonymous hemianopia after surgery.

RESULTS

In the patient with hemianopia, a significant reduction of diffusion anisotropy (greater than mean+/-2 SD) consistent with wallerian degeneration was demonstrated in the optic radiation on the side of the temporal lobectomy, extending from the temporal to the occipital lobe. In the other patient with standard en bloc resection but clinically no hemianopia, the optic radiation was only marginally affected. In the third patient (amygdalocorticectomy), the diffusion anisotropy was within the normal range in the expected position of the optic radiation.

CONCLUSIONS

Our findings show that MR tractography may be a useful tool to demonstrate wallerian degeneration in the optic radiation after temporal lobectomy in patients with hemianopia. This is the first time that this new method has been applied in postoperative imaging; it enables us to visualise the morphologic correlate of dysfunctional pathways after epilepsy surgery in vivo. The potential for using MR tractography to study other aspects of epilepsy is discussed.

Analysis of temporal lobe resections in MR images

PURPOSE

The nature of the resection in surgery for intractable medial temporal lobe epilepsy is likely to be a principal factor determining seizure and neuropsychological outcome. However, there is no universally accepted system for describing the characteristics of individual resections to allow comparison between patients and patient groups treated at different institutions. We therefore developed a technique of volumetric analysis of temporal lobe resections.

METHODS

With comparison of coregistered pre- and postoperative, volumetric magnetic resonance imaging (MRI) scans in 10 subjects, the volumes of six temporal lobe substructures were determined by manual delineation in the pre- and post-operative images for each case, allowing the extent of resection to be determined.

RESULTS

The substructures and their extent of resection were measured with acceptable repeatability in each case.

CONCLUSIONS

We developed a reliable method for the quantitative description of temporal lobe resections. This will be of application in determining the relation between the anatomic nature of the resection in intractable epilepsy and the seizure and neuropsychological outcome.

Fast, accurate, and reproducible automatic segmentation of the brain in T1-weighted volume MRI data

A new fast automated algorithm has been developed to segment the brain from T1-weighted volume MR images. The algorithm uses automated thresholding and morphological operations. It is fully three-dimensional and therefore independent of scan orientation. The validity and the performance of the algorithm were evaluated by comparing the automatically calculated brain volume with semi-automated measurements in 10 subjects, by calculating the brain volume from repeated scans in another 10 subjects, and by visual inspection. The mean and standard deviation of the difference between semi-automated and automated measurements were 0.56% and 2.8% of the mean brain volume, respectively, which is within inter-observer variability of the semi-automated method. The mean and standard deviation of the difference between the total volumes calculated from repeated scans were 0.40% and 1.2% of the mean brain volume, respectively. Good results were also obtained from a scan of abnormal brains.