Biomedical subjects

T Cizadlo

Publications and source records attributed to T Cizadlo.

28 records · Page 2Linked to original sources

PubMed1995

Remembering the past: two facets of episodic memory explored with positron emission tomography.

OBJECTIVE: This study used positron emission tomography to examine two kinds of personal memory that are used in psychiatric evaluation: focused episodic memory (recall of past experience, employed in "taking a history") and random episodic memory (uncensored thinking about experience, examined during analytic therapy using free association). For comparison, a third memory task was used to tap impersonal memory that represents general information about the world ("semantic memory"). METHOD: Thirteen subjects were studied using the [15O]H2O method to obtain quantitative measurements of cerebral blood flow. The three conditions were subtracted and their relative relationships examined. RESULTS: The random episodic condition produced activations in widely distributed association cortex (right and left frontal, parietal, angular/supramarginal, and posterior inferior temporal regions). Focused episodic memory engaged a network that included the medial inferior frontal regions, precuneus/retrosplenial cingulate, anterior cingulate, thalamus, and cerebellum. The use of medial frontal regions and the precuneus/retrosplenial cingulate was common to both focused and random episodic memory. The major difference between semantic and episodic memory was activation of Broca's area and the left frontal operculum by semantic memory. CONCLUSIONS: These results indicate that free-ranging mental activity (random episodic memory) produces large activations in association cortex and may reflect both active retrieval of past experiences and planning of future experiences. Focused episodic memory shares some components of this circuit (inferior frontal and precuneus), which may reflect the time-linked components of both aspects of episodic memory, and which permit human beings to experience personal identity, consciousness, and self-awareness.

Adult↗

PubMed1995

A comparison of approaches to the statistical analysis of [15O]H2O PET cognitive activation studies.

This study compares two of the most widely used statistical techniques for analyzing data obtained from [15O]H2O PET studies of brain function. The Friston method (SPM94) and the Worsley (Montreal) method were applied to a single data set of 33 subjects who were studied in a paradigm designed to evaluate memory for word lists. Neither of these methods emerged as either strikingly different or strikingly preferable, although the occasional differences may be important in some experiments. In general, the two methods were found to produce similar results in identifying brain regions active during long-term memory: frontal, parietal, cingulate, and cerebellar. Underlying assumptions of the two methods, as well as their strengths and weaknesses, are discussed.

Arousal↗

PubMed1994

Thalamic abnormalities in schizophrenia visualized through magnetic resonance image averaging.

Schizophrenia is a complex illness characterized by multiple types of symptoms involving many aspects of cognition and emotion. Most efforts to identify its underlying neural substrates have focused on a strategy that relates a single symptom to a single brain region. An alternative hypothesis, that the variety of symptoms could be explained by a lesion in midline neural circuits mediating attention and information processing, is explored. Magnetic resonance images from patients and controls were transformed with a "bounding box" to produce an "average schizophrenic brain" and an "average normal brain." After image subtraction of the two averages, the areas of difference were displayed as an effect size map. Specific regional abnormalities were observed in the thalamus and adjacent white matter. An abnormality in the thalamus and related circuitry explains the diverse symptoms of schizophrenia parsimoniously because they could all result from a defect in filtering or gating sensory input, which is one of the primary functions of the thalamus in the human brain.

Brain↗

PubMed1994

Techniques for measuring sulcal/gyral patterns in the brain as visualized through magnetic resonance scanning: BRAINPLOT and BRAINMAP.

A method for measuring sulcal and gyral patterns, using data derived from magnetic resonance (MR) scanning, is described. This method can be applied through two newly developed computer programs, BRAINPLOT and BRAINMAP. These programs provide quantitative measures of brain surface pattern. The method has been validated with postmortem brains, phantoms, and human MR data. The method is robust to detecting differences in brain surface anatomy between atrophic and nonatrophic brains. It appears to offer an efficient, fully automated, and accurate method for analyzing the large amounts of information generated through in vivo neuroimaging techniques.

Autopsy↗

PubMed1994

Evaluating and validating two methods for estimating brain structure volumes: tessellation and simple pixel counting.

Developments in imaging technology have made three-dimensional visualization of internal brain structures possible with excellent resolution. Since improved visualization implies improved measurement, these advances hold promise to more accurately measure the volumes of internal structures. As new technologies and techniques emerge, evaluating the relative benefits of measurement methods becomes necessary. We compared and evaluated two methods of estimating volumes from images of brain structures. One method counted pixels within a region of interest, while the other method tessellated the surface between tracings on adjacent slices. Our study assessed both measurement error for true phantom volumes and method disparity for in vivo structures in a randomly selected sample of subjects (n = 100). For our comparisons, we focused on the temporal lobe, ventricular system, and hippocampus. Bias, independence of measurement errors and maximal discrimination of individual differences are properties that are relevant to validating and evaluating measurements of cerebral structure. Pixel counting proved to be the more robust of the two methods, being less sensitive to nuisance-interactions between size of object, shape, and slice thickness. Clinical and research applications of imaging techniques may have distinctive but overlapping needs when evaluating and validating new developments in imaging.

Adult↗

PubMed1993

Voxel processing techniques for the antemortem study of neuroanatomy and neuropathology using magnetic resonance imaging.

BRAINBLAST, a program that uses voxel processing, was developed in order to produce high-fidelity three-dimensional reconstructions of the brain. Four steps were used to produce images: washing away cerebrospinal fluid (via histogramming), dissecting away the blood vessels (via a connectivity heuristic), highlighting the sulci and gyri (via a lighting model), and resampling the interior contents of the brain. After reconstruction, the images can be resampled, rotated, written on, measured, or redissected. The technique has a variety of applications: study of individual variation in sulcal and gyral patterns, evaluation of structure/function relationships, measurement of volumes or subregions using anatomically defined landmarks, and teaching of neuroanatomy.

Brain↗

PubMed1992

Image processing for the study of brain structure and function: problems and programs.

Fundamental problems in the analysis of functional and structural imaging data include data transport, boundary identification (including manual tracing, edge detection, and tissue segmentation), volume estimation, three-dimensional reconstruction and display, surface and volume rendering, shape analysis, and image overlay. These problems require that research investigators have access to suitable methods of image analysis, implemented on a set of software programs, in order to conduct neuroimaging research. The authors describe a group of software programs designed to provide a comprehensive solution for these problems.

Brain↗

PubMedDate not supplied

Comparison of inversion recovery asymmetrical spin-echo EPI and gradient-echo EPI for brain motor activation study.

An inversion recovery asymmetric spin-echo (IR-ASE) echo-planar imaging (EPI) sequence has been developed for functional studies of the brain. This technique uses an 180 degrees inversion pulse with a long inversion time (TI) to suppress the pulsatile cerebrospinal fluid and an asymmetric spin-echo readout to obtain activation signals from brain capillaries. Because gradient-echo sequences are most sensitive to large vessels, motor cortex activation studies using a gradient-echo technique also were conducted for comparison with the IR-ASE method. The results suggest that the IR-ASE pulse sequence may be a useful complement to the gradient-echo technique for the study of neuronal activity of the human brain.

Brain Mapping↗

PubMedDate not supplied

Automatic atlas-based volume estimation of human brain regions from MR images.

OBJECTIVE: MRI offers many opportunities for noninvasive in vivo measurement of structure-function relationships in the human brain. Although automated methods are now available for whole-brain measurements, an efficient and valid automatic method for volume estimation of subregions such as the frontal or temporal lobes is still needed. MATERIALS AND METHODS: We adapted the Talairach atlas to the study of brain subregions. We supplemented the atlas with additional boxes to include the cerebellum. We assigned all the boxes to 1 of 12 regions of interest (ROIs) (frontal, parietal, temporal, and occipital lobes, cerebellum, and subcortical regions on right and left sides of the brain). Using T1-weighted MR scans collected with an SPGR sequence (slice thickness = 1.5 mm), we manually traced these ROIs and produced volume estimates. We then transformed the scans into Talairach space and compared the volumes produced by the two methods ("traced" versus "automatic"). The traced measurements were considered to be the "gold standard" against which the automatic measurements were compared. RESULTS: The automatic method was found to produce measurements that were nearly identical to the traced method. We compared absolute measurements of volume produced by the two methods, as well as the sensitivity and specificity of the automatic method. We also compared the measurements of cerebral blood flow obtained through [15O]H2O PET studies in a sample of nine subjects. Absolute measurements of volume produced by the two methods were very similar, and the sensitivity and specificity of the automatic method were found to be high for all regions. The flow values were also found to be very similar by both methods. CONCLUSION: The automatic atlas-based method for measuring the volume of brain subregions produces results that are similar to manual techniques. The method is rapid, efficient, unbiased, and not subject to the problems of rater drift or potentially poor interrater reliability that plague manual methods. Consequently, this method may be very useful for the study of structure-function relationships in the human brain.

Anatomy, Artistic↗

PubMedDate not supplied

Improving tissue classification in MRI: a three-dimensional multispectral discriminant analysis method with automated training class selection.

PURPOSE: To improve the reliability, accuracy, and computational efficiency of tissue classification with multispectral sequences [T1, T2, and proton density (PD)], we developed an automated method for identifying training classes to be used in a discriminant function analysis. We compared it with a supervised operator-dependent method, evaluating its reliability and validity. We also developed a fuzzy (continuous) classification to correct for partial voluming. METHOD: Images were obtained on a 1.5 T GE Signa MR scanner using three pulse sequences that were co-registered. Training classes for the discriminant analysis were obtained in two ways. The operator-dependent method involved defining circular ROIs containing 5-15 voxels that represented "pure" samples of gray matter (GM), white matter (WM), and cerebrospinal fluid (CSF), using a total of 150-300 voxels for each tissue type. The automated method involved selecting a large number of samples of brain tissue with sufficiently low variance and randomly placed throughout the brain ("plugs"), partitioning these samples into GM, WM, and CSF, and minimizing the amount of variance within each partition of samples to optimize its "purity." The purity of the plug was estimated by calculating the variance of 8 voxels in all modalities (T1, T2, and PD). We also compared "sharp" (discrete) measurements (which classified tissue only as GM, WM, or CSF) and "fuzzy" (continuous) measurements (which corrected for partial voluming by weighting the classification based on the mixture of tissue types in each voxel). RESULTS: Reliability was compared for the operator-dependent and automated methods as well as for the fuzzy versus sharp classification. The automated sharp classifications consistently had the highest interrater and intrarater reliability. Validity was assessed in three ways: reproducibility of measurements when the same individuals were scanned on multiple occasions, sensitivity of the method to detecting changes associated with aging, and agreement between the automated segmentation values and those produced through expert manual segmentation. The sharp automated classification emerged as slightly superior to the other three methods according to each of these validators. Its reproducibility index (intraclass r) was 0.97, 0.98, and 0.98 for total CSF, total GM, and total WM, respectively. Its correlations with age were 0.54, -0.61, and -0.53, respectively. Its percent agreement with the expert manually segmented tissue for the three tissue types was 93, 90, and 94%, respectively. CONCLUSION: Automated identification of training classes for discriminant analysis was clearly superior to a method that required operator intervention. A sharp (discrete) classification into three tissue types was also slightly superior to one that used "fuzzy" classification to produce continuous measurements to correct for partial voluming. This multispectral automated discriminant analysis method produces a computationally efficient, reliable, and valid method for classifying brain tissue into GM, WM, and CSF. It corrects some of the problems with reliability and computational inefficiency previously observed for operator-dependent approaches to segmentation.

Adult↗