Biomedical subjects

D Louis Collins

Publications and source records attributed to D Louis Collins.

17 recordsLinked to original sources

PubMed2006

Automated cortical thickness measurements from MRI can accurately separate Alzheimer's patients from normal elderly controls.

We investigated the potential of fully automated measurements of cortical thickness to reproduce the clinical diagnosis in Alzheimer's Disease (AD) using 19 patients and 17 healthy controls. Thickness maps were analyzed using three different discriminant techniques to separate patients from controls. All analyses were performed using leave-one-out cross-validation to avoid overtraining of the discriminants. The results show regionally variant patterns of discrimination ability, with over 90% accuracy obtained in the medial temporal lobes and other limbic structures. Multivariate discriminant analysis produced 100% accuracy with six different combinations, all involving the parahippocampal gyrus. We therefore propose automated measurements of cortical thickness as a tool to improve the clinical diagnosis of probable AD, as well as a research method to gain unique insight into the etiology of cortical pathology in the disease.

Aged↗

PubMed2006

Genetic contributions to human brain morphology and intelligence.

Variation in gray matter (GM) and white matter (WM) volume of the adult human brain is primarily genetically determined. Moreover, total brain volume is positively correlated with general intelligence, and both share a common genetic origin. However, although genetic effects on morphology of specific GM areas in the brain have been studied, the heritability of focal WM is unknown. Similarly, it is unresolved whether there is a common genetic origin of focal GM and WM structures with intelligence. We explored the genetic influence on focal GM and WM densities in magnetic resonance brain images of 54 monozygotic and 58 dizygotic twin pairs and 34 of their siblings. For genetic analyses, we used structural equation modeling and voxel-based morphometry. To explore the common genetic origin of focal GM and WM areas with intelligence, we obtained cross-trait/cross-twin correlations in which the focal GM and WM densities of each twin are correlated with the psychometric intelligence quotient of his/her cotwin. Genes influenced individual differences in left and right superior occipitofrontal fascicle (heritability up to 0.79 and 0.77), corpus callosum (0.82, 0.80), optic radiation (0.69, 0.79), corticospinal tract (0.78, 0.79), medial frontal cortex (0.78, 0.83), superior frontal cortex (0.76, 0.80), superior temporal cortex (0.80, 0.77), left occipital cortex (0.85), left postcentral cortex (0.83), left posterior cingulate cortex (0.83), right parahippocampal cortex (0.69), and amygdala (0.80, 0.55). Intelligence shared a common genetic origin with superior occipitofrontal, callosal, and left optical radiation WM and frontal, occipital, and parahippocampal GM (phenotypic correlations up to 0.35). These findings point to a neural network that shares a common genetic origin with human intelligence.

Adolescent↗

PubMed2006

Gray and white matter density changes in monozygotic and same-sex dizygotic twins discordant for schizophrenia using voxel-based morphometry.

Global gray matter brain tissue volume decreases in schizophrenia have been associated to disease-related (possibly nongenetic) factors. Global white matter brain tissue volume decreases were related to genetic risk factors for the disease. However, which focal gray and white matter brain regions best reflect the genetic and environmental risk factors in the brains of patients with schizophrenia remains unresolved. 1.5-T MRI brain scans of 11 monozygotic and 11 same-sex dizygotic twin-pairs discordant for schizophrenia were compared to 11 monozygotic and 11 same-sex dizygotic healthy control twin-pairs using voxel-based morphometry. Linear regression analysis was done in each voxel for the average and difference in gray and white matter density separately, in each twin-pair, with group (discordant, healthy) and zygosity (monozygotic, dizygotic) as between subject variables, and age, sex and handedness as covariates. The t-maps (critical threshold value mid R:tmid R: > 6.0, P < 0.05) revealed a focal decrease in gray matter density accompanied by a focal increase in white matter density in the left medial orbitofrontal gyrus and a focal decrease in white matter density in the left sensory motor gyrus in twin-pairs discordant for schizophrenia as compared to healthy twin-pairs. Focal changes in left medial (orbito)frontal and left sensory motor gyri may reflect the increased genetic risk to develop schizophrenia. Focal changes in the left anterior hemisphere may therefore be particularly relevant as endophenotype in genetic studies of schizophrenia.

Brain↗

PubMed2006

The creation of a brain atlas for image guided neurosurgery using serial histological data.

Digital and print brain atlases have been used with success to help in the planning of neurosurgical interventions. In this paper, a technique presented for the creation of a brain atlas of the basal ganglia and the thalamus derived from serial histological data. Photographs of coronal histological sections were digitized and anatomical structures were manually segmented. A slice-to-slice nonlinear registration technique was used to correct for spatial distortions introduced into the histological data set at the time of acquisition. Since the histological data were acquired without any anatomical reference (e.g., block-face imaging, post-mortem MRI), this registration technique was optimized to use an error metric which calculates a nonlinear transformation minimizing the mean distance between the segmented contours between adjacent pairs of slices in the data set. A voxel-by-voxel intensity correction field was also estimated for each slice to correct for lighting and staining inhomogeneity. The reconstructed three-dimensional (3D) histological volume can be viewed in transverse and sagittal directions in addition to the original coronal. Nonlinear transformations used to correct for spatial distortions of the histological data were applied to the segmented structure contours. These contours were then tessellated to create three-dimensional geometric objects representing the different anatomic regions in register with the histological volumes. This yields two alternate representations (one histological and one geometric) of the atlas. To register the atlas to a standard reference MR volume created from the average of 27 T1-weighted MR volumes, a pseudo-MRI was created by setting the intensity of each anatomical region defined in the geometric atlas to match the intensity of the corresponding region of the reference MR volume. This allowed the estimation of a 3D nonlinear transformation using a correlation based registration scheme to fit the atlas to the reference MRI. The result of this procedure is a contiguous 3D histological volume, a set of 3D objects defining the basal ganglia and thalamus, both of which are registered to a standard MRI data set, for use for neurosurgical planning.

Algorithms↗

PubMed2006

Twenty new digital brain phantoms for creation of validation image data bases.

Simulations provide a way of generating data where ground truth is known, enabling quantitative testing of image processing methods. In this paper, we present the construction of 20 realistic digital brain phantoms that can be used to simulate medical imaging data. The phantoms are made from 20 normal adults to take into account intersubject anatomical variabilities. Each digital brain phantom was created by registering and averaging four T1, T2, and proton density (PD)-weighted magnetic resonance imaging (MRI) scans from each subject. A fuzzy minimum distance classification was used to classify voxel intensities from T1, T2, and PD average volumes into grey-matter, white matter, cerebro-spinal fluid, and fat. Automatically generated mask volumes were required to separate brain from nonbrain structures and ten fuzzy tissue volumes were created: grey matter, white matter, cerebro-spinal fluid, skull, marrow within the bone, dura, fat, tissue around the fat, muscles, and skin/muscles. A fuzzy vessel class was also obtained from the segmentation of the magnetic resonance angiography scan of the subject. These eleven fuzzy volumes that describe the spatial distribution of anatomical tissues define the digital phantom, where voxel intensity is proportional to the fraction of tissue within the voxel. These fuzzy volumes can be used to drive simulators for different modalities including MRI, PET, or SPECT. These phantoms were used to construct 20 simulated T1-weighted MR scans. To evaluate the realism of these simulations, we propose two approaches to compare them to real data acquired with the same acquisition parameters. The first approach consists of comparing the intensities within the segmented classes in both real and simulated data. In the second approach, a whole brain voxel-wise comparison between simulations and real T1-weighted data is performed. The first comparison underlines that segmented classes appear to properly represent the anatomy on average, and that inside these classes, the simulated and real intensity values are quite similar. The second comparison enables the study of the regional variations with no a priori class. The experiments demonstrate that these variations are small when real data are corrected for intensity nonuniformity.

Adult↗

PubMed2005

Hippocampal shape analysis using medial surfaces.

In magnetic resonance imaging (MRI) research, significant attention has been paid to the analysis of the hippocampus (HC) within the medial temporal lobe because of its importance in memory and learning, and its role in neurodegenerative diseases. Manual segmentation protocols have established a volume decline in the HC in conjunction with Alzheimer's disease, epilepsy, post-traumatic stress disorder, and depression. Furthermore, recent studies have investigated age-related changes of HC volume which show an interaction with gender; in early adulthood, volume reduction of the HC is found in men but not in women. In this paper, we investigated gender differences in normal subjects in young adulthood by employing a shape analysis of the HC using medial surfaces. For each subject, the most prominent medial manifold of the HC was extracted and flattened. The flattened sheets were then registered using both a rigid and a non-rigid alignment technique, and the medial surface radius was expressed as a height function over them. This allowed for an investigation of the association between subject variables and the local width of the HC. With regard to the effects of age and gender, it could be shown that the previously observed gender differences were mostly due to volume loss in males in the lateral areas of the HC head and tail. We suggest that the analysis of HC shape using medial surfaces might thus serve as a complimentary technique to investigate group differences to the established segmentation protocols for volume quantification in MRI.

Adolescent↗

PubMed2005

Predicting clinical variable from MRI features: application to MMSE in MCI.

The ability to predict a clinical variable from automated analysis of single, cross-sectional T1-weighted (T1w) MR scans stands to improve the management of patients with neurological diseases. We present a methodology for predicting yearly Mini-Mental Score Examination (MMSE) changes in Mild Cognitive Impairment (MCI) patients. We begin by generating a non-pathological, multidimensional reference space from a group of 152 healthy volunteers by Principal Component Analyses of (i) T1w MR intensity of linearly registered Volumes of Interest (VOI); and (ii) trace of the deformation fields of nonlinearly registered VOIs. We use multiple regression to build linear models from eigenvectors where the projection eigencoordinates of patient data in the reference space are highly correlated with the clinical variable of interest. In our cohort of 47 MCI patients, composed of 16 decliners, 26 stable and 5 improvers (based on MMSE at 1 yr follow-up), there was a significant difference (P = 0.0003) for baseline MMSE scores between decliners and improvers, but no other differences based on age or sex. First, we classified our three groups using leave-one-out, forward stepwise linear discriminant analyses of the projection eigencoordinates with 100% accuracy. Next, we compared various linear models by computing F-statistics on the residuals of predicted vs actual values. The best model was based on 10 eigenvectors + baseline MMSE, with predicted yearly changes highly correlated (r = 0.6955) with actual data. Prospective study of an independent cohort of patients is the next logical step towards establishing this promising technique for clinical use.

Artificial Intelligence↗

PubMed2005

Maximum a posteriori local histogram estimation for image registration.

Image similarity measures for registration can be considered within the general context of joint intensity histograms, which consist of bin count parameters estimated from image intensity samples. Many approaches to estimation are ML (maximum likelihood), which tends to be unstable in the presence sparse data, resulting in registration that is driven by spurious noisy matches instead of valid intensity relationships. We propose instead a method of MAP (maximum a posteriori) estimation, which is well-defined for sparse data, or even in the absence of data. This estimator can incorporate a variety of prior assumptions, such as global histogram characteristics, or use a maximum entropy prior when no such assumptions exist. We apply our estimation method to deformable registration of MR (magnetic resonance) and US (ultrasound) images for an IGNS (image-guided guided neurosurgery) application, where our MAP estimation method results in more stable and accurate registration than a traditional ML approach.

Algorithms↗

PubMed2005

Anatomical and electrophysiological validation of an atlas for neurosurgical planning.

Digital brain atlases can be used in conjunction with magnetic resonance imaging (MRI) and computed tomography (CT) for planning and guidance during neurosurgery. Digital atlases are advantageous, since they can be warped nonlinearly to fit each patient's unique anatomy. Two atlas-to-patient warping techniques are compared in this paper. The first technique uses an MRI template as an intermediary to estimate a nonlinear atlas-to-patient transformation. The second, is novel, and uses a pseudo-MRI volume, derived from the voxel-label-atlas, to estimate the atlas-to-patient transformation directly. Manual segmentations and functional data are used to validate the two methods.

Brain↗

PubMed2005

A review of calibration techniques for freehand 3-D ultrasound systems.

Three-dimensional (3-D) ultrasound (US) is an emerging new technology with numerous clinical applications. Ultrasound probe calibration is an obligatory step to build 3-D volumes from 2-D images acquired in a freehand US system. The role of calibration is to find the mathematical transformation that converts the 2-D coordinates of pixels in the US image into 3-D coordinates in the frame of reference of a position sensor attached to the US probe. This article is a comprehensive review of what has been published in the field of US probe calibration for 3-D US. The article covers the topics of tracking technologies, US image acquisition, phantom design, speed of sound issues, feature extraction, least-squares minimization, temporal calibration, calibration evaluation techniques and phantom comparisons. The calibration phantoms and methods have also been classified in tables to give a better overview of the existing methods.

Algorithms↗

PubMed2004

Tuning and comparing spatial normalization methods.

Spatial normalization is a key process in cross-sectional studies of brain structure and function using MRI, fMRI, PET and other imaging techniques. A wide range of 2D surface and 3D image deformation algorithms have been developed, all of which involve design choices that are subject to debate. Moreover, most have numerical parameters whose value must be specified by the user. This paper proposes a principled method for evaluating design choices and choosing parameter values. This method can also be used to compare competing spatial normalization algorithms. We demonstrate the method through a performance analysis of a nonaffine registration algorithm for 3D images and a registration algorithm for 2D cortical surfaces.

Algorithms↗

PubMed2004

Focal white matter density changes in schizophrenia: reduced inter-hemispheric connectivity.

Gray matter changes have been demonstrated in several regions in schizophrenia. Particularly, the frontal and temporal cortices and amygdala-hippocampal region have been found decreased in volume and density in magnetic resonance imaging (MRI) studies. These abnormalities may reflect an aberrant neuronal network in schizophrenia, suggesting that white matter fibers connecting these regions may also be affected. However, it is unclear if particular white matter areas are (progressively) affected in schizophrenia and if these are related to the gray matter changes. Focal white matter changes in schizophrenia were studied in whole brain magnetic resonance images acquired from 159 patients with schizophrenia or schizophreniform disorder and 158 healthy comparison subjects using voxel-based morphometry. White matter density changes in the patients with schizophrenia were correlated to gray matter density changes and to illness severity. In the patients with schizophrenia, significant decreases in white matter density were found in the genu and truncus of the corpus callosum in the left and right hemisphere, in the right anterior internal capsule and in the right anterior commissure. No interactions between diagnosis and age were found. Increased illness severity was correlated with low density of the corpus callosum and anterior commissure. Decreased corpus callosum density correlated with decreased density of thalamus, lateral inferior frontal and insular gray matter in patients and controls and with decreased density of medial orbitofrontal and superior temporal gyri in patients. Decreased internal capsule and anterior commissure density correlated with increased caudate, and globus pallidus density in patients and controls. These findings suggest aberrant inter-hemispheric connectivity of anterior cortical and sub-cortical brain regions in schizophrenia, reflecting decreased hemispheric specialisation in schizophrenia.

Adult↗

PubMed2004

Automatic non-linear MRI-ultrasound registration for the correction of intra-operative brain deformations.

OBJECTIVE: Movements of brain tissue during neurosurgical procedures reduce the effectiveness of using pre-operative images for intra-operative surgical guidance. In this paper, we explore the use of acquiring intra-operative ultrasound (US) images for the quantification of and correction for non-linear brain deformations. MATERIALS AND METHODS: We will present a multi-modal registration strategy that automatically matches pre-operative images (e.g., MRI) to intra-operative US to correct for these deformations. The strategy involves using the predicted appearance of neuroanatomical structures in US images to build "pseudo ultrasound" images based on pre-operative segmented MRI. These images can then be non-linearly registered to intra-operative US using cross-correlation measurements within the ANIMAL package. The feasibility of the theory is demonstrated through its application to clinical patient data acquired during 12 neurosurgical procedures. RESULTS: Results of applying the method to 12 surgical cases, including those with brain tumors and selective amygdalo-hippocampectomies, indicate that our strategy significantly recovers from non-linear brain deformations occurring during surgery. Quantitative results at tumor boundaries indicate up to 87% correction for brain shift. CONCLUSIONS: Qualitative and quantitative examination of the results indicate that the system is able to correct for non-linear brain deformations in clinical patient data.

Automation↗

PubMed2003

Automated detection of focal cortical dysplasia lesions using computational models of their MRI characteristics and texture analysis.

Focal cortical dysplasia (FCD), a malformation of cortical development, is a frequent cause of pharmacologically intractable epilepsy. FCD is characterized on Tl-weighted MRI by cortical thickening, blurring of the gray-matter/white-matter interface, and gray-level hyperintensity. We have previously used computational models of these characteristics to enhance visual lesion detection. In the present study we seek to improve our methods by combining these models with features derived from texture analysis of MRI, which allows measurement of image properties not readily accessible by visual analysis. These computational models and texture features were used to develop a two-stage Bayesian classifier to perform automated FCD lesion detection. Eighteen patients with histologically confirmed FCD and 14 normal controls were studied. On the MRI volumes of the 18 patients, 20 FCD lesions were manually labeled by an expert observer. Three-dimensional maps of the computational models and texture features were constructed for all subjects. A Bayesian classifier was trained on the computational models to classify voxels as cerebrospinal fluid, gray-matter, white-matter, transitional, or lesional. Voxels classified as lesional were subsequently reclassified based on the texture features. This process produced a 3D lesion map, which was compared to the manual lesion labels. The automated classifier identified 17/20 manually labeled lesions. No lesions were identified in controls. Thus, combining models of the T1-weighted MRI characteristics of FCD with texture analysis enabled successful construction of a classifier. This computer-based, automated method may be useful in the presurgical evaluation of patients with severe epilepsy related to FCD.

Adult↗

PubMed2002

Computational models of MRI characteristics of focal cortical dysplasia improve lesion detection.

In many patients, focal cortical dysplasia (FCD) is characterized by minor structural changes that may go unrecognized by standard radiological analysis. We previously demonstrated that visual analysis of a composite map based on three simple models of MRI features of FCD increased the sensitivity of FCD lesion detection, compared to visual analysis of conventional MRI. Here we report on the use of improved methods for characterizing FCD which improve contrast in the composite maps: a Laplacian-based metric for measuring cortical thickness, a convolutional kernel to model blurring of the GM-WM interface, and an operator to measure hyperintense T1 signal. To validate these methods, we processed the MRIs of 14 FCD patients with our original set of image processing operators and an improved set of image processing operators. Comparison of the composite maps associated with the two sets of operators revealed that contrast between lesional tissue and nonlesional cortex was significantly increased in the composite maps associated with the set of improved operators. Increasing this contrast is an important step toward the goal of automated FCD lesion detection.

Brain Mapping↗

PubMed2002

Volumetry of temporopolar, perirhinal, entorhinal and parahippocampal cortex from high-resolution MR images: considering the variability of the collateral sulcus.

Researchers in clinical and basic neuroscience frequently target structures of the human medial temporal lobe (MTL) for volumetric analysis with magnetic resonance imaging (MRI). In neurodegenerative diseases, a precise volumetric analysis of MTL structures can assist in differential diagnosis and can be used in guiding early treatment. Also, in functional neuroimaging, exact localization is crucial for the correct interpretation of focal MTL activations with respect to specific memory functions. In presently available protocols, precise and consistent volumetric analysis of MTL structures is compromised in numerous ways. Most importantly, in order to cover all structures of the MTL, the researcher is presently forced to combine independently developed segmentation protocols for different structures from different laboratories. This approach limits anatomical precision because these protocols are based on different anatomical guidelines and descriptions that cannot easily be integrated. The segmentation approach presented in this paper was designed to address this issue by presenting segmentation guidelines for all major structures of the parahippocampal gyrus (PHG). It was developed directly to complement a volumetric protocol for hippocampus and amygdala (Pruessner et al., 2000, Cereb Cortex 10:433-442), thus allowing volumetric assessment of all major MTL structures in an integrated and consistent manner. Furthermore, it takes into consideration the neuroanatomical appearance of the collateral sulcus by presenting a method to correct the volumes of the surrounding cortices for the variability of this sulcus. The protocol was validated using MR images of 40 healthy normal control subjects (20 men and 20 women, age range 18-42 years). Intra- and interrater coefficients are presented, together with mean values for the volumes of all PHG structures, correlations with age and sex, and tests for hemispheric differences.

Adult↗

PubMed2002

Optimal location of thalamotomy lesions for tremor associated with Parkinson disease: a probabilistic analysis based on postoperative magnetic resonance imaging and an integrated digital atlas.

OBJECT: Renewed interest in stereotactic neurosurgery for movement disorders has led to numerous reports of clinical outcomes associated with different treatment strategies. Nevertheless, there is a paucity of autopsy and imaging data that can be used to describe the optimal size and location of lesions or the location of implantable stimulators. In this study the authors correlated the clinical efficacy of stereotactic thalamotomy for tremor with precise anatomical localization by using postoperative magnetic resonance (MR) imaging and an integrated deformable digital atlas of subcortical structures. METHODS: Thirty-one lesions were created by stereotactic thalamotomy in 25 patients with tremor-dominant Parkinson disease. Lesion volume and configuration were evaluated by reviewing early postoperative MR images and were correlated with excellent, good, or fair tremor outcome categories. To allow valid comparisons of configurations of lesions with respect to cytoarchitectonic thalamic boundaries, the MR image obtained in each patient was nonlinearly deformed into a standardized MR imaging space, which included an integrated atlas of the basal ganglia and thalamus. The volume and precise location of lesions associated with different clinical outcomes were compared using nonparametric statistical methods. Probabilistic maps of lesions in each tremor outcome category were generated and compared. Statistically significant differences in lesion location between excellent and good. and excellent and fair outcome categories were demonstrated. On average, lesions associated with excellent outcomes involved thalamic areas located more posteriorly than sites affected by lesions in the other two outcome groups. Subtraction analysis revealed that lesions correlated with excellent outcomes necessarily involved the interface of the nucleus ventralis intermedius (Vim; also known as the ventral lateral posterior nucleus [VLp]) and the nucleus ventrocaudalis (Vc; also known as the ventral posterior [VP] nucleus). Differences in lesion volume among outcome groups did not achieve statistical significance. CONCLUSIONS: Anatomical evaluation of lesions within a standardized MR image-atlas integrated reference space is a useful method for determining optimal lesion localization. The results of an analysis of probabilistic maps indicates that optimal relief of tremor is associated with lesions involving the Vim (VLp) and the anterior Vc (VP).

Aged↗