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Edward H Herskovits

Publications and source records attributed to Edward H Herskovits.

17 recordsLinked to original sources
PubMed2005

Network analysis of mild cognitive impairment.

We present a network analysis of a cross-sectional study of mild cognitive impairment (MCI). Network analysis, as opposed to univariate analysis, accounts for interactions among brain structures in explaining a clinical outcome. In this context, we analyze structural magnetic resonance (MR) data based on a Bayesian network representation of variables in the problem domain. The Bayesian network resulting from this analysis reveals complex, nonlinear multivariate associations among morphological changes in the left hippocampus and in the right thalamus and the presence of mild cognitive impairment. This Bayesian network could be used to predict the presence of mild cognitive impairment from structural MR scans.

Aged↗
PubMed2005

Anatomy of spatial attention: insights from perfusion imaging and hemispatial neglect in acute stroke.

The site of lesion responsible for left hemispatial neglect after stroke has been intensely debated recently. Some studies provide evidence that right angular lesions are most likely to cause left neglect, whereas others indicate that right superior temporal lesions are most likely to cause neglect. We examine two potential accounts of the conflicting results: (1) neglect could result from cortical dysfunction beyond the structural lesion in some studies; and (2) different forms of neglect with separate neural correlates have been included in different proportions in separate studies. To evaluate these proposals, we studied 50 patients with acute right subcortical infarcts using tests of hemispatial neglect and magnetic resonance diffusion-weighted and perfusion-weighted imaging performed within 48 h of onset of symptoms. Left "allocentric" neglect (errors on the left sides of individual stimuli, regardless of location with respect to the viewer) was most strongly associated with hypoperfusion of right superior temporal gyrus (Fisher's exact test; p < 0.0001), whereas left "egocentric" neglect (errors on the left of the viewer) was most strongly associated with hypoperfusion of the right angular gyrus (p < 0.0001). Patients without cortical hypoperfusion showed no hemispatial neglect. Because the patients did not have cortical infarcts, our data show that neglect can be caused by hypoperfused dysfunctional tissue not detectable by structural magnetic resonance imaging. Moreover, different forms of neglect were associated with different sites of cortical hypoperfusion. Results help explain conflicting results in the literature and contribute to the understanding of spatial attention and representation in the human brain.

Adult↗
PubMed2005

Graphical-Model-based Morphometric Analysis.

We propose a novel method for voxel-based morphometry (VBM), which we call Graphical-Model-based Morphometric Analysis (GAMMA), to identify morphological abnormalities automatically, and to find complex probabilistic associations among voxels in magnetic-resonance images and clinical variables. GAMMA is a fully automatic, nonparametric morphometric-analysis algorithm, with high sensitivity and specificity. It uses a Bayesian network to represent the associations among voxels and the function variable, and uses a contextual-clustering method based on a Markov random field to find clusters in which all voxels have similar associations with the function variable. We use loopy belief propagation to infer the unobserved label field and belief map. As opposed to voxel-based morphometric methods based on general linear models, GAMMA is capable of identifying nonlinear associations among the function variable and voxels. Compared with our previous approach, a Bayesian morphometry algorithm, GAMMA has greater sensitivity, specificity, and computational efficiency.

Algorithms↗
PubMed2005

Uterine fibroids: diffusion-weighted MR imaging for monitoring therapy with focused ultrasound surgery--preliminary study.

PURPOSE: To prospectively determine the feasibility of using diffusion-weighted (DW) imaging and apparent diffusion coefficient (ADC) mapping before (baseline) and after treatment and at 6-month follow-up to monitor magnetic resonance (MR) image-guided focused ultrasound surgical ablation of uterine fibroids. MATERIALS AND METHODS: Informed consent was obtained from patients before treatment with our study protocol, as approved by the institutional review board, and the study complied with the Health Insurance Portability and Accountability Act. Fourteen patients (mean age, 46 years +/- 5 [standard deviation]) who underwent DW imaging were enrolled in this study, and 12 of 14 completed the inclusive MR examination with DW imaging at 6-month follow-up. Treatment was performed by one radiologist with a modified MR image-guided focused ultrasound surgical system coupled with a 1.5-T MR imager. Pre- and posttreatment and 6-month follow-up MR images were obtained by using phase-sensitive T1-weighted fast spoiled gradient-recalled acquisition, T1-weighted contrast material-enhanced, and DW imaging sequences. Total treatment time was 1-3 hours. Trace ADC maps were constructed for quantitative analysis. Regions of interest localized to areas of hyperintensity on DW images were drawn on postcontrast images, and quantitative statistics were obtained from treated and nontreated uterine tissue before and after treatment and at 6-month follow-up. Statistical analysis was performed with analysis of variance. Differences with P < .05 were considered statistically significant. RESULTS: T1-weighted contrast-enhancing fibroids selected for treatment had no hyperintense or hypointense signal intensity changes on the DW images or ADC maps before treatment. Considerably increased signal intensity changes that were localized within the treated areas were noted on DW images. Mean baseline ADC value in fibroids was 1504 mm(-6)/sec2 +/- 290. Posttreatment ADC values for nontreated fibroid tissue (1685 mm(-6)/sec2 +/- 468) differed from posttreatment ADC values for fibroid tissue (1078 mm(-6)/sec2 +/- 293) (P = .001). A significant difference (P < .001) between ADC values for treated (1905 mm(-6)/sec2 +/- 446) and nontreated (1437 mm(-6)/sec2 +/- 270) fibroid tissue at 6-month follow-up was observed. CONCLUSION: DW imaging and ADC mapping are feasible for identification of ablated tissue after focused ultrasound treatment of uterine fibroids.

Adult↗
PubMed2004

Neuroimaging correlates of anxiety after pediatric traumatic brain injury.

BACKGROUND: Anxiety disorders are common after traumatic brain injury (TBI). Data on the neural correlates of these conditions are lacking. This study examines the relationship between brain damage, particularly to the orbitofrontal cortex (OFC) and temporal lobe, and anxiety symptoms and disorders. METHODS: Ninety-five children and adolescents were followed for one year postinjury. Preinjury and one-year postinjury anxiety status were obtained from the parent. Magnetic resonance imaging was performed to evaluate brain lesions. The primary analysis used regression models to determine relationships between brain lesions and anxiety outcomes. As a secondary analysis, previously reported posttraumatic stress disorder (PTSD) data were reanalyzed using similar methods for purposes of comparison. RESULTS: The primary analysis showed that greater volume and number of OFC lesions correlated with decreased risk for anxiety, whereas lesions in other brain areas did not correlate with anxiety. Consistent with prior data, the secondary analysis showed an inverse correlation between OFC damage and PTSD; temporal lobe damage was positively correlated with PTSD. CONCLUSIONS: After pediatric TBI, greater damage to the OFC is associated with decreased risk for anxiety outcomes. Similar to adult data, these findings implicate OFC dysfunction in childhood anxiety. Temporal lobe damage did not correlate with anxiety, in contrast to the findings for PTSD.

Adolescent↗
PubMed2004

Optimized prostate biopsy via a statistical atlas of cancer spatial distribution.

A methodology is presented for constructing a statistical atlas of spatial distribution of prostate cancer from a large patient cohort, and it is used for optimizing needle biopsy. An adaptive-focus deformable model is used for the spatial normalization and registration of 100 prostate histological samples, which were provided by the Center for Prostate Disease Research of the US Department of Defense, resulting in a statistical atlas of spatial distribution of prostate cancer. Based on this atlas, a statistical predictive model was developed to optimize the needle biopsy sites, by maximizing the probability of detecting cancer. Experimental results using cross-validation show that the proposed method can detect cancer with a 99% success rate using seven needles, in these samples.

Algorithms↗
PubMed2004

A Bayesian morphometry algorithm.

Most methods for structure-function analysis of the brain in medical images are usually based on voxel-wise statistical tests performed on registered magnetic resonance (MR) images across subjects. A major drawback of such methods is the inability to accurately locate regions that manifest nonlinear associations with clinical variables. In this paper, we propose Bayesian morphological analysis methods, based on a Bayesian-network representation, for the analysis of MR brain images. First, we describe how Bayesian networks (BNs) can represent probabilistic associations among voxels and clinical (function) variables. Second, we present a model-selection framework, which generates a BN that captures structure-function relationships from MR brain images and function variables. We demonstrate our methods in the context of determining associations between regional brain atrophy (as demonstrated on MR images of the brain), and functional deficits. We employ two data sets for this evaluation: the first contains MR images of 11 subjects, where associations between regional atrophy and a functional deficit are almost linear; the second data set contains MR images of the ventricles of 84 subjects, where the structure-function association is nonlinear. Our methods successfully identify voxel-wise morphological changes that are associated with functional deficits in both data sets, whereas standard statistical analysis (i.e., t-test and paired t-test) fails in the nonlinear-association case.

Aged↗
PubMed2003

Application of a data-mining method based on Bayesian networks to lesion-deficit analysis.

Although lesion-deficit analysis (LDA) has provided extensive information about structure-function associations in the human brain, LDA has suffered from the difficulties inherent to the analysis of spatial data, i.e., there are many more variables than subjects, and data may be difficult to model using standard distributions, such as the normal distribution. We herein describe a Bayesian method for LDA; this method is based on data-mining techniques that employ Bayesian networks to represent structure-function associations. These methods are computationally tractable, and can represent complex, nonlinear structure-function associations. When applied to the evaluation of data obtained from a study of the psychiatric sequelae of traumatic brain injury in children, this method generates a Bayesian network that demonstrates complex, nonlinear associations among lesions in the left caudate, right globus pallidus, right side of the corpus callosum, right caudate, and left thalamus, and subsequent development of attention-deficit hyperactivity disorder, confirming and extending our previous statistical analysis of these data. Furthermore, analysis of simulated data indicates that methods based on Bayesian networks may be more sensitive and specific for detecting associations among categorical variables than methods based on chi-square and Fisher exact statistics.

Algorithms↗
PubMed2003

Benign and malignant breast lesions: diagnosis with multiparametric MR imaging.

PURPOSE: To both develop and use a tissue signature method for the identification and classification of breast lesions and healthy breast tissue with magnetic resonance (MR) imaging. MATERIALS AND METHODS: Thirty-six patients underwent breast MR imaging (T1- and T2-weighted imaging and three-dimensional T1-weighted imaging with and without contrast material enhancement), followed by biopsy or mastectomy and histopathologic analysis. Tissue cluster analysis was performed by using the iterative self-organizing data technique to identify glandular, adipose, and lesion tissue signature vectors. Glandular and lesion tissue vectors were characterized by angular separation from the reference adipose tissue vector. Differences in angular separation of histologically proved benign and malignant lesion groups were evaluated with an independent t test. The usefulness of the angular separation model for distinguishing benign from malignant lesions was evaluated with nonparametric receiver operating characteristic curve analysis. RESULTS: The model enabled successful identification and characterization of breast lesion tissue clusters in all patients; 18 lesions were benign, and 18 were malignant. Angular separation +/- SD was 17.8 degrees +/- 6.1 degrees between adipose tissue and malignant lesions and 29.0 degrees +/- 11.2 degrees between adipose tissue and benign lesions. Angular separations of benign lesions and malignant lesions were significantly different (P =.002), with a specificity of 78% and sensitivity of 89% at a cutoff value of 21 degrees. Significant differences in angular separation from adipose tissue also were found between glandular tissue and lesion tissue (P <.001) and, in glandular tissue, between patients with benign lesions and those with malignant lesions (P =.04). The area under the receiver operating characteristic curve was 0.84. CONCLUSION: Multispectral analysis of conventional breast MR images based on the iterative self-organizing data model and on measurement of angular separation between tissue signature vectors may enable automated lesion identification and classification.

Adolescent↗
PubMed2003

Defining thresholds for changes in size of simulated T2-hyperintense brain lesions on the basis of qualitative comparisons.

OBJECTIVE: Our purpose was to define thresholds below which trained reviewers cannot detect changes in the size of T2-hyperintense brain lesions. MATERIALS AND METHODS: We generated T2-weighted brain MR images (TR/TE, 4000/80) with simulated hyperintense lesions derived from a real multiple sclerosis plaque. The size of the original multiple sclerosis lesion was varied by scaling up or down the lesion using a bicubic interpolation method. Three hundred seventy-eight composite images, in which two T2-weighted images containing lesions were paired, were presented to three equally trained neuroradiologists to define thresholds below which changes in original lesion size could not be detected. Stepwise logistic regression was used to evaluate the dependency of size thresholds on the original size of the lesion. RESULTS: Thresholds ranged from a 5% to 15% increase in the original lesion diameter. For increases greater than 15%, all three reviewers detected the change in lesion size irrespective of the diameter of the original lesion. There was a dependency of the threshold on the diameter of the original lesion (p = 0.02). CONCLUSION: Using an MR simulator, we can define thresholds below which changes in original lesion size cannot be reliably detected. These results may guide the design of clinical trials that rely on trained reviewers to assess change in lesion burden.

Brain↗
PubMed2003

The surgical bed after BCNU polymer wafer placement for recurrent glioma: serial assessment on CT and MR imaging.

OBJECTIVE: The objective of our study was to describe the CT and MR imaging appearances of the surgical bed in the brains of patients receiving biodegradable polymers impregnated with N, N'1, 3-Bis-(2-chloroethyl)-N-nitrosourea (BCNU) for recurrent glioma and to determine whether patients receiving placebos could be differentiated from those receiving BCNU based on the pattern and growth kinetics of tumor recurrence. MATERIALS AND METHODS: The CT and MR images of 20 patients who underwent surgery for resection of recurrent high-grade gliomas and placement of intratumoral wafers (11 received BCNU polymer wafers, nine received control wafers) were analyzed for wafer appearance, volume of gas in the tumor bed, and volume of enhancement on serial scans. RESULTS: Wafers appeared as linear hyperdense structures on CT and as linear low-signal-intensity structures on MR imaging and caused no significant enhancement. In the BCNU polymer group, gas volume was 4.0 +/- 3.4 cm(3) (mean +/- SD), whereas gas volume was 1.6 +/- 3.0 cm(3) for the placebo group (Mann-Whitney test, p = 0.03). A trend toward linear rather than exponential recurrent tumor growth was identified for the BCNU polymer group but not for the placebo group. CONCLUSION: BCNU polymer wafers have a specific appearance on CT and MR imaging with which radiologists should be familiar: gas in the surgical bed is an expected transient finding, and tumor regrowth in patients receiving BCNU polymer wafers appeared to occur at a slower rate than in those receiving the placebo.

Adult↗
PubMed2002

Impact of pager notification on report verification times.

RATIONALE AND OBJECTIVES: The purpose of this study was to assess the impact on times of verification (TOVs) by a pager notification system (PNS) that informs physicians when reports are available for signature. MATERIALS AND METHODS: An automated PNS was implemented in the authors' department in November 2000. Monthly report verification times of each physician were collected for 3 months in the years before and after initiation of the PNS. Radiologists enrolled in the PNS and those who were not were assigned into two groups for analysis. Mean TOVs for the two sets of 3 months and for the two groups were calculated and differences recorded. Two-tailed t tests were used to assess for statistical differences between the groups. RESULTS: Twenty-nine of 37 radiologists voluntarily enrolled in the PNS (group 1). Mean TOV was 26.75 hours (standard deviation [SD] = 17.76) for these physicians before and 14.48 hours (SD = 11.86) after the PNS was employed (P < .01). For those physicians who did not enroll in the PNS, mean TOV was 11.53 hours (SD = 5.55) before and 9.77 hours (SD = 9.86) after the PNS was employed (P = .33). Both the absolute and percentage reductions in TOVs were significantly greater for those physicians enrolled in the PNS than for those who were not (P = .035). Twenty-three of 29 (79%) physicians who used the PNS showed a reduction in their report turnaround times. CONCLUSION: Linking the PNS with the radiology information system to notify physicians of unsigned reports was effective in reducing report verification times.

Humans↗
PubMed2002

Effect of emergency department CT on neuroimaging case volume and positive scan rates.

RATIONALE AND OBJECTIVES: The authors performed this study to determine the effect a computed tomographic (CT) scanner in the emergency department (ED) has on neuroimaging case volume and positive scan rates. MATERIALS AND METHODS: The total numbers of ED visits and neuroradiology CT scans requested from the ED were recorded for 1998 and 2000, the years before and after the installation of a CT unit in the ED. For each examination type (brain, face, cervical spine), studies were graded for major findings (those that affected patient care), minor findings, and normal findings. The CT utilization rates and positive study rates were compared for each type of study performed for both years. RESULTS: There was a statistically significant increase in the utilization rate after installation of the CT unit (P < .001). The fractions of studies with major findings, minor findings, and normal findings changed significantly after installation of the CT unit for facial examinations (P = .002) but not for brain (P = .12) or cervical spine (P = .24) examinations. In all types of studies, the percentage of normal examinations increased. In toto, there was a significant decrease in the positive scan rate after installation of the CT scanner (P = .004). CONCLUSION: After installation of a CT scanner in the ED, there was increased utilization and a decreased rate of positive neuroradiologic examinations, the latter primarily due to lower positive rates for facial CT scans.

Cervical Vertebrae↗
PubMed2002

Is the spatial distribution of brain lesions associated with closed-head injury in children predictive of subsequent development of posttraumatic stress disorder?

PURPOSE: To determine whether there is an association between the spatial distributions of lesions detected at magnetic resonance (MR) imaging of the brain in children, adolescents, and young adults after closed-head injury (CHI) and development of the reexperiencing symptoms of posttraumatic stress disorder (PTSD). MATERIALS AND METHODS: Data obtained in 94 subjects without a history of PTSD as determined by parental interview were analyzed. MR images were obtained 3 months after CHI. Lesions were manually delineated and registered to the Talairach coordinate system. Mann-Whitney analysis of lesion distribution and PTSD status at 1 year (again, as determined by parental interview) was performed, consisting of an analysis of lesion distribution versus the major symptoms of PTSD: reexperiencing, hyperarousal, and avoidance. RESULTS: Of the 94 subjects, 41 met the PTSD reexperiencing criterion and nine met all three PTSD criteria. Subjects who met the reexperiencing criterion had fewer lesions in limbic system structures (eg, the cingulum) on the right than did subjects who did not meet this criterion (Mann-Whitney, P =.003). CONCLUSION: Lesions induced by CHI in the limbic system on the right may inhibit subsequent manifestation of PTSD reexperiencing symptoms in children, adolescents, and young adults.

Adolescent↗
PubMed2002

Spatial normalization of spine MR images for statistical correlation of lesions with clinical symptoms.

An image analysis method was developed for spatial normalization of spine magnetic resonance images. A deformable shape model of the spine is first constructed, and it is subsequently used by an automated algorithm to find a shape transformation that places patient data into a stereotactic space. Very good agreement with manual segmentations was observed. The main application of this method is in lesion-deficit analysis for determining associations between structural damage and clinical symptoms.

Algorithms↗