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This study reports FDG-PET findings in Wernicke-Korsakoff patients. Twelve patients suffering amnesia arising from the Korsakoff syndrome were compared with 10 control subjects without alcohol-related disability. Subjects received [18F]-fluorodeoxyglucose (FDG-PET) imaging as well as neuropsychological assessment and high-resolution MR imaging with volumetric analysis. Volumetric MRI analysis had revealed thalamic and mamillary body atrophy in the patient group as well as frontal lobe atrophy with relative sparing of medial temporal lobe structures. Differences in regional metabolism were identified using complementary region of interest (ROI) and statistical parametric mapping (SPM) approaches employing either absolute methods or a reference region approach to increase statistical power. In general, we found relative hypermetabolism in white matter and hypometabolism in subcortical grey matter in Korsakoff patients. When FDG uptake ratios were examined with occipital lobe metabolism as covariate reference region, Korsakoff patients showed widespread bilateral white matter hypermetabolism on both SPM and ROI analysis. When white matter metabolism was the reference covariate; Korsakoff patients showed relative hypometabolism in the diencephalic grey matter, consistent with their known underlying neuropathology, and medial temporal and retrosplenial hypometabolism, interpreted as secondary metabolic effects within the diencephalic-limbic memory circuits. There was also evidence of a variable degree of more general frontotemporal neocortical hypometabolism on some, but not all, analyses.

There are many controversies concerning the structural basis of retrograde amnesia (RA). One view is that memories are held briefly within a medial temporal store ("hippocampal complex") before being "consolidated" or reorganised within temporal neocortex and/or networks more widely distributed within the cerebral cortex. An alternative view is that the medial temporal lobes are always involved in the storage and retrieval (reactivation) of autobiographical memories (multiple trace theory). The present study used quantitative magnetic resonance imaging (MRI) in 40 patients with focal pathology/volume loss in different sites, to examine the correlates of impairment on three different measures of RA. The findings supported the view that widespread neural networks are involved in the storage and retrieval of autobiographical and other remote memories. Brain volume measures in critical structures could account for 60% of variance on autobiographical memory measures (for incidents and facts) in diencephalic patients and for 60-68% of variance in patients with frontal lesions. Significant correlations with medial temporal lobe volume were found only in the diencephalic group, in whom they were thought to reflect thalamic changes, but not in patients with herpes encephalitis or hypoxia in whom the temporal lobes were particularly implicated. The latter finding fails to support one of the main predictions of multiple trace theory, as presently expounded.

This paper presents a fully automated algorithm for segmentation of multiple sclerosis (MS) lesions from multispectral magnetic resonance (MR) images. The method performs intensity-based tissue classification using a stochastic model for normal brain images and simultaneously detects MS lesions as outliers that are not well explained by the model. It corrects for MR field inhomogeneities, estimates tissue-specific intensity models from the data itself, and incorporates contextual information in the classification using a Markov random field. The results of the automated method are compared with lesion delineations by human experts, showing a high total lesion load correlation. When the degree of spatial correspondence between segmentations is taken into account, considerable disagreement is found, both between expert segmentations, and between expert and automatic measurements.

The study of hepatic haemodynamics is of importance in understanding both hepatic physiology and disease processes as well as assessing the effects of portosystemic shunting and liver transplantation. The liver has the most complicated circulation of any organ and many physiological and pathological processes can affect it1,2. This review surveys the methods available for assessing liver blood flow, examines the different parameters being measured and outlines problems of applicability and interpretation for each technique.The classification of these techniques is to some extent arbitrary and several so called “different” methods may share certain common principles. The methods reviewed have been classified into two groups (Table 1): those primarily reflecting flow through discrete vessels or to the whole organ and those used to assess local microcirculatory blood flow. All techniques have their advantages and disadvantages and in some situations a combination may provide the most information. In addition, because of the many factors affecting liver blood flow and sinusoidal perfusion, readings in a single subject may vary depending on positioning, recent food intake, anxiety, anaesthesia and drug therapy. This must be borne in mind if different studies are to be meaningfully compared.

Traditional neuropathological examination provides information about neurological disease or injury of a patient at a high-resolution level. Correlating this type of post mortemdiagnosis with in vivoimage data of the same patient acquired by non-invasive tomographic scans greatly complements the interpretation of any disease or injury. We present the validation of a registration method for correlating macroscopic pathological images with MR images of the same patient. This also allows for 3-D mapping of the distribution of pathological changes throughout the brain. As the validation deals with datasets of widely differing sampling, we propose a method using smooth curvilinear anatomical features in the brain which allows interpolation between wide-spaced samples. Curvilinear features are common anatomically, and if selected carefully have the potential to allow determination of the accuracy of co-registration across large areas of a volume of interest.

The folding pattern of the cerebral cortex and its relation to functional areas is notoriously variable and there is a need to identify more consistent 3-dimensional (3D) topographical cortical features. We analyzed magnetic resonance brain images of 96 normal adult human volunteers using automated 3D image analysis methods. We examined the deeper parts of the sulci because they generally show less interindividual variability than more superficial parts, especially in monozygotic twins, and deepest parts of primary sulci are the first to develop embryologically and change least as the cortex expands. Along the length of each sulcus we found that there is generally one well-defined zone where depth is maximal, which we term the sulcal pit. Long sulci may have 2 or 3 pits. The spatial arrangement of pits is strikingly regular, forming alternating chains of deeper and shallower pits. We hypothesize that the pits are encoded in the protomap described in Rakic (1988. Specification of cerebral cortical areas. Science. 241:170–176) and are under closer genetic control than the rest of the cortex and are likely to have a more consistent relationship to functional areas.

There is considerable controversy concerning the theoretical basis of retrograde amnesia (R.A.). In the present paper, we compare medial temporal, medial plus lateral temporal, and frontal lesion patients on a new autobiographical memory task and measures of the more semantic aspects of memory (famous faces and news events). Only those patients with damage extending beyond the medial temporal cortex into the lateral temporal regions showed severe impairment on free recall remote memory tasks, and this held for both the autobiographical and the more semantic memory tests. However, ont-test analysis, the medial temporal group was impaired in retrieving recent autobiographical memories. Within the medial temporal group, those patients who had combined hippocampal and parahippocampal atrophy (H+) on quantified MRI performed somewhat worse on the semantic tasks than those with atrophy confined to the hippocampi (H−), but scores were very similar on autobiographical episodic recall. Correlational analyses with regional MRI volumes showed that lateral temporal volume was correlated significantly with performance on all three retrograde amnesia tests. The findings are discussed in terms of consolidation, reconsolidation, and multiple trace theory: We suggest that a widely distributed network of regions underlies the retrieval of past memories, and that the extent of lateral temporal damage appears to be critical to the emergence of a severe remote memory impairment.

In this paper, we present a systematic investigation of the variability of the human cortical folding using a generic gyral model (GGM). The GGM consists of a fixed number of vertices that can be registered non-linearly to an individual anatomy so that for each individual we have a clearly defined set of landmarks that is spread across the cortex. This allows us to obtain a regionalized estimation of inter-subject variability. Since the GGM is stratified into different levels of depth, it also allows us to estimate variability as a function of depth. As another application of a polygonal line representation underlying the generic gyral model, we present a cortical parcellation scheme that can be used to regionalize cortical measurements.

Because of the complex shape of human cortical gyri and great variation between individuals, development of effective representation schemes which allow establishment of correspondence between individuals, extraction of average structure of a population, and coregistration has proved very difficult. We introduce an approach which extracts line representations of gyri at different depths from high resolution MRI, labels main gyri semi-automatically, and extracts a template from a population using non-linear principal component analysis. The method has been tested on data from 96 healthy human volunteers. The model captures the most salient shape features of all major cortical gyri, and can be used for inter-subject registration, for investigating regionalized inter-subject variability, and for inter-hemispheric comparisons.

Accurate co-registration of MR images of the brain with pathological data from the same patient is required for many applications, including validation of in-vivo MRI processing. We present preliminary results from a 2-D optical to 3-D MRI registration process, which depends on initialisation using an initial 3-D reconstruction of post-mortem whole-brain or hemisphere slices from independent 2D images followed by 3-D to 3-D registration. Our overall approach progressively models the acquisition process, and the final stages account for variations in slice thickness and other errors that can occur as a result of the specimen preparation and earlier processing. Our method can be used in most neuropathology laboratories where thick slices are cut. Alternative approaches depend on sectioning by macrocryotomes, which are not generally available and have limited applicability in conditions such as CJD where infectivity risks are high.

The deep grey matter structures of the brain have been reported to show MR hyperintensity in the sporadic form of Creutzfeldt-Jakob disease (sCJD), but the criteria for visual judgment of this are not well defined. We carried out a quantitative study of T2 weighted and proton density scans comparing 10 sCJD patients with 10 non-CJD dementia controls (NCD) and also with 11 patients suffering from the new variant form of CJD (vCJD). Scans were acquired in a clinical context and came from many hospitals. Absolute intensities varied widely and did not allow any useful discrimination. In all groups the putamen had a gradient of reducing intensity from anterior to posterior on T2 scans. In both s- and v- CJD patients this gradient was increased. Sensitivity and specificity (SS (2) intensities of deep grey matter structures vary systematically and intensity-based segmentation methods used in patients and normals should take account of this.

BACKGROUND If they are to be replicable, MRI volume measurements require explicit definitions of structures and of criteria for delineating these structures on MRI. Previously published volumes in healthy subjects show considerable differences in measurements across different studies, including a fourfold variation in estimates of hippocampal volume. Previous neuroimaging reports in patients with Korsakoff syndrome have generally found widespread or non-specific change, whereas in patients with herpes encephalitis the extent of pathological involvement reported beyond the temporal lobes has varied. METHOD In the present study, a clear set of anatomical criteria and detailed MRI segmentation procedures were applied to measure whole brain, frontal and temporal lobe, and anterolateral and medial temporal volumes, as well as thalamic areas in patients with organic amnesia (from Korsakoff9s syndrome, herpes encephalitis, and focal frontal lesions) as well as healthy controls. RESULTS Patients with Korsakoff9s syndrome showed decreased thalamic measurements but no significant changes in the medial temporal lobes, whereas patients with herpes encephalitis showed severe medial temporal but not thalamic atrophy. In the patients with known frontal lobe lesions, quantitative analysis on MRI showed reduced frontal lobe volume but no significant temporal lobe or thalamic atrophy. CONCLUSION Quantified MRI can be a useful technique with which to examine brain-cognitive relations, provided that detailed techniques are explicitly described. In particular, specific patterns of volume change can be found in vivo in patients with Korsakoff9s syndrome and those with herpes encephalitis.

BACKGROUND: Cognitive-MRI correlations have often been studied in disorders in which there are multiple cognitive deficits and widespread cortical atrophy, such as Alzheimer's dementia. In such circumstances, the interpretation of any single cognitive-structural correlation is equivocal. Only by measuring differing cognitive functions and a wide range of brain structures in patients with a varying distribution of lesions or atrophy can specific brain-cognitive relations be determined in neurological disorder. METHOD: In the present study, a clear set of anatomical criteria and detailed MRI segmentation procedures were applied to measure whole brain, and left and right frontal, temporal lobe, anterolateral and medial temporal volumes, as well as thalamic cross sectional areas in 40 patients with organic amnesia (from various diseases) and 10 healthy controls. RESULTS: Within the total patient group, anterograde memory measures correlated significantly with medial temporal, hippocampal, and thalamic measurements. A spatial memory measure correlated significantly with hippocampal volume, and temporal context memory with frontal volume. After a factor analysis of the cognitive measures, the association between anterograde memory and hippocampal volume was corroborated. Forgetting rates and subjective memory evaluations did not show any significant MR correlations and, of executive tests employed, only card sorting categories correlated significantly with frontal volume. CONCLUSION: Loss of volume in key brain structures (for example, hippocampus, thalamus) is detectable on quantitative MRI, and this loss of volume correlates significantly with impaired performance on measures of anterograde memory function. Correlations with hippocampal volume did not indicate a specific role in either recall or verbal memory, as opposed to recognition or visual memory.

We present a method for registration of macroscopic optical images with MR images of the same patient. This forms a key part of a series of procedures to allow post mortem findings to be accurately registered with MR images, and more generally provides a method for 3D mapping of the distribution of pathological changes throughout the brain. The first stage of the method involves a 3D reconstruction of 2D brain slices and was presented in a previous paper [2]. In the current paper, we focus on the registration of the reconstructed volume with corresponding MR images.

We present a method for reconstruction of macroscopic optical images of post-mortem brain slices to form a 3-D volume. This forms a key part of a series of procedures to allow post mortem findings to be accurately registered with MR images, and more generally provides a method for 3-D mapping of the distribution of pathological changes throughout the brain. In this preliminary work, four brains from a study of Creutzfeldt-Jakob disease were examined. After brain fixation, the pathologist cut coronal slices several mm thick through the brain. The anterior and posterior faces of each slice were photographed. We show that the 2-D co-registration of each such pair of images was most effectively obtained if the slice was placed in a jig before photographing. Fiducials on the jig were detected automatically and point-based rigid registration computed. For co-registration between slices, i.e., across a single cut, an intensity-based method for 2-D non-rigid registration is used which provided satisfactory results. By propagating the 2-D registrations through the volume and using the known slice thickness, the 3-D volume was reconstructed.

Quantitative analysis of MR images is becoming increasingly important as a surrogate marker in clinical trials in multiple sclerosis (MS). This paper describes a fully automated model-based method for segmentation of MS lesions from multi-channel MR images. The method simultaneously corrects for MR field inhomogeneities, estimates tissue class distribution parameters and classifies the image voxels. MS lesions are detected as voxels that are not well explained by the model. The results of the automated method are compared with the lesions delineated by human experts, showing a significant total lesion load correlation and an average overall spatial correspondence similar to that between the experts.

Segmentation of objects of interest in magnetic resonance imaging is a necessary procedure for volumetric calculations. However, these direct measurements tend to be inaccurate due to the intrinsic MRI partial volume effects. In this paper, a general method for correcting these effects based on the geometry and grey level intensity of the segmented objects is presented. This method is independent of the segmentation strategy used to extract the objects of interest. An evaluation for three different segmentation methods is presented and it is shown that the proposed partial volume correction can improve the volume estimation of all three methods.

This paper presents a new methodology for the automatic segmentation and characterization of object changes in time series of three-dimensional data sets. The purpose of the analysis is a detection and characterization of objects based on their dynamic changes. The technique was inspired by procedures developed for the analysis of functional MRI data sets. After precise registration of serial volume data sets to 4-D data, we applied a new time series analysis taking into account the characteristic time function of variable lesions. The images were preprocessed with a correction of image field inhomogeneities and a normalization of the brightness function over the whole time series. This leads to the hypothesis that static regions remain unchanged over time, whereas local changes in tissue characteristics cause typical functions in the voxel’s time series. A set of features are derived from the time series and their derivatives, expressing probabilities for membership to the sought structures. These multiple sources of uncertain evidence were combined to a single evidence value using Dempster Shafer’s theory. Individual processing of a series of 3-D data sets is therefore replaced by a fully 4-D processing. To explore the sensitivity of time information, active lesions are segmented solely based on time fluctuation, neglecting absolute intensity information.

The evaluation of spatial correspondence between binary objects resulting from a segmentation step performed by two different observers or methods is a critical part of the validation of a segmentation criterion or technique. Several global measures of correspondence have been previously proposed, but all of them assume a one-to-one correspondence between objects, thus failing to address local problems such as the splitting of an object by one of the observers. Moreover, such global measures do not distinguish between the reference and the observed objects and most of them lack a solid theoretical foundation. In this paper, we introduce a set of spatial correspondence indices that can evaluate global (many-to-many), local (many-to-one) and individual (one-to-one) spatial correspondence between observed and reference objects and vice versa. The proposed measures, derived from applying information theory concepts to the problem of spatial correspondence, are shown to be well-behaved and suitable to be used in medical imaging applications.

Segmentation of objects of interest in magnetic resonance imaging is a necessary procedure for volumetric calculations. However, these direct measurements tend to be inaccurate due to the intrinsic MRI partial volume effects. In this paper, a generalised method for correcting these effects based on the geometry and grey level intensity of the segmented objects is presented. This method is independent of the segmentation strategy used to extract the objects of interest. An evaluation is presented for three different segmentation methods and it is shown that the proposed generalised partial volume correction can improve the volume estimation of all three methods.

International audience; The VISLAN system is based on one of the newest developments in optical localiser tracking, where the localiser reflects light shone on it (passive illumination) rather than emitting light. In experiments with a CT-compatible skull phantom we evaluated the VISLAN system in comparison with a widely used stereotactic system, the Cosman-Roberts-Wells frame (Radionics lnc). The mean Euclidean difference in localising points initially defined in CT images was 2.5mm across a wide range of target positions. We estimated the accuracy of the VISLAN system with the same phantom set up but independently of the stereotactic frame, and showed a mean Euclidean error of 1.0mm. We concluded that the majority of the discrepancy between the two systems was accounted for by the inaccuracy of the CRW frame. It would be inappropriate to regard the frame based systems as a satisfactory gold standard for estimating the accuracy of VISLAN. However, frame-based and frameless guidance may be needed in the same operation, and it is important for such systems to be compared.

Background and Purpose Digital angiography is the best established tool for assessing atheromatous disease of extracranial blood vessels. Advances in computer technology have now made it possible and practicable to extract quantitative information (length, width, cross-sectional area, and flow velocity) from good-quality clinical angiograms, allowing calculation of volume flow and pressure gradient. The technique of quantitative angiography (QA) is used for assessing coronary artery disease, but to date there has been no clinical application in patients with cerebrovascular disease. Summary of Report We have developed a computer program for off-line analysis of routine digital subtraction angiographic images. From biplanar images, the program reconstructs the angiogram in three dimensions and performs quantitative analysis of each vessel. From this data, the pressure drop from the aortic arch to the circle of Willis is then calculated. We assessed the clinical applicability of QA in five patients investigated for transient ischemic attack. The carotid artery ipsilateral to the symptomatic hemisphere was occluded in one patient and had minor plaque in another. In the remaining three patients, ipsilateral internal carotid artery stenosis was measured by QA as producing area reductions of 55%, 72%, and 88% (equivalent to diameter reductions of 33%, 48%, and 65%, respectively). In these patients, the quantitative stenosis pressure gradients were calculated as 1.2, 3.0, and 3.5 mm Hg, respectively. Further calculation showed that each stenosis contributed to 18%, 24%, and 60%, respectively, of the total carotid pressure gradient from the aortic arch to the circle of Willis. These carotid arteries carried 47%, 42%, and 26%, respectively, of the total cerebral flow. The results of quantitative analysis were validated by comparing, within each patient, the differences in pressure gradients between right and left carotid systems or between right and left vertebral arteries (overall mean difference in pressure gradient, 0.6±0.5 mm Hg; P =NS). Finally, comparison was made of pressure gradients across the circle of Willis between the carotid and vertebrobasilar circulations (mean difference in pressure gradient, 4.1±5.3 mm Hg; P =NS). Conclusions Quantitative angiography allows determination of the hemodynamic parameters of a vessel or stenosis. It has significant potential, both as a research tool and in routine clinical practice, for the investigation of cerebrovascular disease.

In the absence of a priori information on scales of interest vision systems should initially process in a scale invariant manner. The fact that any signal can only be sampled discretely further constrains the initial processing. The paper argues that a representation satisfying these requirements is an hierarchical segmentation of scalespace. An algorithm is presented to compute such representations. The algorithm has been designed so that its operation is scale invariant in the following sense: the addition of finer scale information only ever adds to the computed representation and never changes what was discoverable from coarser scales. It is noted that such a scheme has benefits even when the scales of interest are known.

In this paper we present the Delaunay/Voronoi selection graph (DVSG), an approach to the representation of the shape of 2-D objects which does not require a complete segmentation, merely a pattern of dots which are believed to lie on the edges of objects. The technique produces both a skeleton and boundary representation and, with subsequent processing, generates a hierarchical description of the topology of individual objects. We compare the DVSG to other methods used for obtaining information from dot-patterns, and show how this technique can be extended to 3-D.

A hierarchical model of the brain has been developed, based on the ARTTM system, in which nodes represent the structures of interest, and arcs represent 3-D topographical relationships between organs and part-of relationships. The nodes contain attributes of the organs which encode their expected shape and identifying features; they also attach to the recognition rules, which use the measured attributes and relationships to identify the structures. In this paper the image data is pre-processed to create a Laplacian Pyramid by using multiple Difference of Gaussian (DoG) filters (see Figure 2). Most of the reasoning used in the recognition rules is based on zero crossing features of the DoG images, which may be tracked between scales, or between images of adjacent slices.

Summary Sixty-five patients who had coronary artery graft surgery were subjected to detailed neuropsychometric assessment before operation and twice again within 7 days after operation. They were monitored continuously with a cerebral function analysing monitor during the operation. The results of the peroperative cerebral monitoring were compared on completion of the study with the neuropsychometric assessments. Seventy-six percent of the patients with a significant neuropsychometric deficit after operation also showed significant peroperative changes on the analysing monitor; the majority occurred immediately after the start of perfusion. Twenty-eight patients failed to demonstrate any evidence of neuropsychometric dejicit and six (21%) of these also showed significant peroperative changes. All patients whose traces demonstrated more than one significant change during the peroperative course had a significant neuropsychometric deficit afterwards.

Objective Quantitative analysis of MR images is becoming increasingly important in assessing the progression of multiple sclerosis (MS) and in monitoring the effect of a drug therapy. In clinical trials, manual analysis of the MR images by human experts is prohibitively time-consuming because of the large amounts of data typically involved. The interand mtra-observer variability associated with manual delineations. and the unclear decision making process when multi-spectral MR data are presented to a human expert. further complicate matters. The goal of our work is to develop a fast, fully-automated method for MS lesion segmentation that analysis multi-spectral MR data in an objective and reproducible way.