Publications

PURPOSE: To report the use of a semiburied curvilinear distraction device, with a 3-dimensional (3D) computed tomography treatment planning system, for correction of mandibular deformities. MATERIALS AND METHODS: This was a retrospective evaluation of 13 consecutive patients, with syndromic and nonsyndromic micrognathia, who underwent correction by curvilinear distraction osteogenesis. A 3D computed tomography scan was obtained for each patient and imported into a 3D treatment planning system (Slicer/Osteoplan). Surgical guides were constructed to localize the osteotomy and to drill holes to secure the distractor’s proximal and distal footplates to the mandible. Postoperatively, patients were followed by clinical examination and plain radiographs to ensure the desired vector of movement. At end distraction, when possible, a 3D computed tomography scan was obtained to document the final mandibular position.

We have compared the three-dimensional (3D) morphology of stubby and spiny neurons derived from the human small intestine. After immunohistochemical triple staining for leu-enkephalin (ENK), vasoactive intestinal peptide (VIP) and neurofilament (NF), neurons were selected and scanned based on their immunoreactivity, whether ENK (stubby) or VIP (spiny). For the 3D reconstruction, we focused on confocal data pre-processing with intensity drop correction, non-blind deconvolution, an additional compression procedure in z-direction, and optimizing segmentation reliability. 3D Slicer software enabled a semi-automated segmentation based on an objective threshold (interrater and intrarater reliability, both 0.99). We found that most dendrites of stubby neurons emerged only from the somal circumference, whereas in spiny neurons, they also emerged from the luminal somal surface. In most neurons, the nucleus was positioned abluminally in its soma. The volumes of spiny neurons were significantly larger than those of stubby neurons (total mean of stubbies 806 +/- 128 mum(3), of spinies 2,316 +/- 545 mum(3)), and spiny neurons had more dendrites (26.3 vs. 11.3). The ratios of somal versus dendritic volumes were 1:1.2 in spiny and 1:0.3 in stubby neurons. In conclusion, 3D reconstruction revealed new differences between stubby and spiny neurons and allowed estimations of volumetric data of these neuron populations.

We present a method for controlling a dynamical system using real-time fMRI. The objective for the subject in the MR scanner is to balance an inverted pendulum by activating the left or right hand or resting. The brain activity is classified each second by a neural network and the classification is sent to a pendulum simulator to change the force applied to the pendulum. The state of the inverted pendulum is shown to the subject in a pair of VR goggles. The subject was able to balance the inverted pendulum during several minutes, both with real activity and imagined activity. In each classification 9000 brain voxels were used and the response time for the system to detect a change of activity was on average 2-4 seconds. The developments here have a potential to aid people with communication disabilities, such as locked in people. Another future potential application can be to serve as a tool for stroke and Parkinson patients to be able to train the damaged brain area and get real-time feedback for more efficient training.

BACKGROUND: White matter fiber tracts, especially those interconnecting the frontal and temporal lobes, are likely implicated in pathophysiology of schizophrenia. Very few studies, however, have focused on the fornix, a compact bundle of white matter fibers, projecting from the hippocampus to the septum, anterior nucleus of the thalamus and the mamillary bodies. Diffusion Tensor Imaging (DTI), and a new post-processing method, fiber tractography, provides a unique opportunity to visualize and to quantify entire trajectories of fiber bundles, such as the fornix, in vivo. We applied these techniques to quantify fornix diffusion anisotropy in schizophrenia. METHODS: DTI images were used to evaluate the left and the right fornix in 36 male patients diagnosed with chronic schizophrenia and 35 male healthy individuals, group matched on age, parental socioeconomic status, and handedness. Regions of interest were drawn manually, blind to group membership, to guide tractography, and fractional anisotropy (FA), a measure of fiber integrity, was calculated and averaged over the entire tract for each subject. The Doors and People test (DPT) was used to evaluate visual and verbal memory, combined recall and combined recognition.

We examined the status of the neural network mediating the default mode of brain function, which typically exhibits greater activation during rest than during task, in patients in the early phase of schizophrenia and in young first-degree relatives of persons with schizophrenia. During functional MRI, patients, relatives, and controls alternated between rest and performance of working memory (WM) tasks. As expected, controls exhibited task-related suppression of activation in the default network, including medial prefrontal cortex (MPFC) and posterior cingulate cortex/precuneus. Patients and relatives exhibited significantly reduced task-related suppression in MPFC, and these reductions remained after controlling for performance. Increased task-related MPFC suppression correlated with better WM performance in patients and relatives and with less psychopathology in all 3 groups. For WM task performance, patients and relatives had greater activation in right dorsolateral prefrontal cortex (DLPFC) than controls. During rest and task, patients and relatives exhibited abnormally high functional connectivity within the default network. The magnitudes of default network connectivity during rest and task correlated with psychopathology in the patients. Further, during both rest and task, patients exhibited reduced anticorrelations between MPFC and DLPFC, a region that was hyperactivated by patients and relatives during WM performance. Among patients, the magnitude of MPFC task suppression negatively correlated with default connectivity, suggesting an association between the hyperactivation and hyperconnectivity in schizophrenia. Hyperactivation (reduced task-related suppression) of default regions and hyperconnectivity of the default network may contribute to disturbances of thought in schizophrenia and risk for the illness.

PURPOSE: To validate the performance of an analysis method for fMRI data based on restricted canonical correlation analysis (rCCA) and adaptive filtering, and to increase the usability of the method by introducing a new technique for significance estimation of rCCA maps. MATERIALS AND METHODS: Activation data from a language task and also a resting state fMRI data were collected from eight volunteers. Data was analyzed using both the rCCA method and the General Linear Model (GLM). A modified Receiver Operating Characteristic (ROC) method was used to evaluate the performance of the different analysis methods. The area under a fraction of the ROC curve was used as a measure of performance. On resting state data the fraction of voxels above certain significance thresholds were used to evaluate the significance estimation method. RESULTS: The rCCA method scored significantly higher on the area under the ROC curve than the GLM. The fraction of activated voxels determined by thresholding according to the introduced significance estimation technique showed good agreement with the thresholds selected. CONCLUSION: The rCCA method is an effective analysis tool for fMRI data and its usability is increased with the introduced significance estimation method.

BACKGROUND: The goal of the study was to examine mismatch negativity (MMN) in schizotypal personality disorder (SPD) individuals. Abnormal MMN has been a consistent finding in chronic schizophrenia and there also have been reports of reduced duration MMN in first episode schizophrenia patients [Umbricht, D., Krljes, S., Mismatch negativity in schizophrenia: a meta-analysis. Schizophrenia Research (2005); 76(1):1-23], with some studies finding no pitch MMN amplitude differences [Salisbury, D.F., Shenton, M.E., Griggs, C.B., Bonner-Jackson, A., McCarley, R.W., Mismatch negativity n chronic schizophrenia and first-episode schizophrenia. Archives of General Psychiatry (2002); 59(8):686-694.], while others reporting a modest reduction [Umbricht, D.S., Bates, J.A., Lieberman, J.A., Kane, J.M., Javitt, D.C., Electrophysiological indices of automatic and controlled auditory information processing in first-episode, recent-onset and chronic schizophrenia. Biological Psychiatry (2006); 59(8):762-772], in recent onset schizophrenia patients. To our knowledge no reports exist of MMN in SPD individuals. METHODS: Twenty six normal (14 females) control and 23 SPD (12 females) individuals were tested using the pitch MMN paradigm. Normal control (NC) and SPD individuals were recruited from the general population and assessed using DSM-IV. SPD individuals were included if they met 5 or more criteria for SPD disorder. The subjects listened to 2000 frequent 1 kHz pure tones and 100 rare 1.2 kHz pure tones while reading a magazine article. MMN was measured from a difference waveform within the latency window of 175-276 ms. RESULTS: Reduced MMN amplitude was found in SPD relative to NC subjects (p

BACKGROUND: A critical challenge in neuroscience is organizing, managing, and accessing the explosion in neuroscientific knowledge, particularly anatomic knowledge. We believe that explicit knowledge-based approaches to make neuroscientific knowledge computationally accessible will be helpful in tackling this challenge and will enable a variety of applications exploiting this knowledge, such as surgical planning. RESULTS: We developed ontology-based models of neuroanatomy to enable symbolic lookup, logical inference and mathematical modeling of neural systems. We built a prototype model of the motor system that integrates descriptive anatomic and qualitative functional neuroanatomical knowledge. In addition to modeling normal neuroanatomy, our approach provides an explicit representation of abnormal neural connectivity in disease states, such as common movement disorders. The ontology-based representation encodes both structural and functional aspects of neuroanatomy. The ontology-based models can be evaluated computationally, enabling development of automated computer reasoning applications. CONCLUSION: Neuroanatomical knowledge can be represented in machine-accessible format using ontologies. Computational neuroanatomical approaches such as described in this work could become a key tool in translational informatics, leading to decision support applications that inform and guide surgical planning and personalized care for neurological disease in the future.

Efficiently obtaining a reliable coronary artery centerline from computed tomography angiography data is relevant in clinical practice. Whereas numerous methods have been presented for this purpose, up to now no standardized evaluation methodology has been published to reliably evaluate and compare the performance of the existing or newly developed coronary artery centerline extraction algorithms. This paper describes a standardized evaluation methodology and reference database for the quantitative evaluation of coronary artery centerline extraction algorithms. The contribution of this work is fourfold: (1) a method is described to create a consensus centerline with multiple observers, (2) well-defined measures are presented for the evaluation of coronary artery centerline extraction algorithms, (3) a database containing 32 cardiac CTA datasets with corresponding reference standard is described and made available, and (4) 13 coronary artery centerline extraction algorithms, implemented by different research groups, are quantitatively evaluated and compared. The presented evaluation framework is made available to the medical imaging community for benchmarking existing or newly developed coronary centerline extraction algorithms.