Publications

2014

Savadjiev P, Whitford TJ, Hough ME, von Hohenberg CC, Bouix S, Westin CF, Shenton ME, Crow TJ, A J, Kubicki M. Sexually Dimorphic White Matter Geometry Abnormalities in Adolescent Onset Schizophrenia. Cereb Cortex. 2014;24(5):1389–96.

The normal human brain is characterized by a pattern of gross anatomical asymmetry. This pattern, known as the "torque", is associated with a sexual dimorphism: The male brain tends to be more asymmetric than that of the female. This fact, along with well-known sex differences in brain development (faster in females) and onset of psychosis (earlier with worse outcome in males), has led to the theory that schizophrenia is a disorder in which sex-dependent abnormalities in the development of brain torque, the correlate of the capacity for language, cause alterations in interhemispheric connectivity, which are causally related to psychosis (Crow TJ, Paez P, Chance SE. 2007. Callosal misconnectivity and the sex difference in psychosis. Int Rev Psychiatry. 19(4):449-457.). To provide evidence toward this theory, we analyze the geometry of interhemispheric white matter connections in adolescent-onset schizophrenia, with a particular focus on sex, using a recently introduced framework for white matter geometry computation in diffusion tensor imaging data (Savadjiev P, Kindlmann GL, Bouix S, Shenton ME, Westin CF. 2010. Local white geometry from diffusion tensor gradients. Neuroimage. 49(4):3175-3186.). Our results reveal a pattern of sex-dependent white matter geometry abnormalities that conform to the predictions of Crow’s torque theory and correlate with the severity of patients’ symptoms. To the best of our knowledge, this is the first study to associate geometrical differences in white matter connectivity with torque in schizophrenia.

This tutorial demonstrates how to prepare data for 3D printing using the open source software 3D Slicer. The following topics are highlighted in the tutorial: introduction to the 3D Slicer interface, loading data into 3D Slicer, volume rendering, cropping image volumes, creating label maps, creating surface models, and saving data in file formats appropriate for 3D printing.

Model-based segmentation methods have the advantage of incorporating a priori shape information into the segmentation process but suffer from the drawback that the model must be initialized sufficiently close to the target. We propose a novel approach for initializing an active shape model (ASM) and apply it to 3D lung segmentation in CT scans. Our method constructs an atlas consisting of a set of representative lung features and an average lung shape. The ASM pose parameters are found by transforming the average lung shape based on an affine transform computed from matching features between the new image and representative lung features. Our evaluation on a diverse set of 190 images showed an average dice coefficient of 0.746 ± 0.068 for initialization and 0.974 ± 0.017 for subsequent segmentation, based on an independent reference standard. The mean absolute surface distance error was 0.948 ± 1.537 mm. The initialization as well as segmentation results showed a statistically significant improvement compared to four other approaches. The proposed initialization method can be generalized to other applications employing ASM-based segmentation.
Horky LL, Gerbaudo VH, Zaitsev A, Plesniak W, Hainer J, Govindarajulu U, Kikinis R, Dietrich J. Systemic chemotherapy decreases brain glucose metabolism. Ann Clin Transl Neurol. 2014;1(10):788–98.
OBJECTIVE: Cancer patients may experience neurologic adverse effects, such as alterations in neurocognitive function, as a consequence of chemotherapy. The mechanisms underlying such neurotoxic syndromes remain poorly understood. We here describe the temporal and regional effects of systemically administered platinum-based chemotherapy on glucose metabolism in the brain of cancer patients. METHODS: Using sequential FDG-PET/CT imaging prior to and after administration of chemotherapy, we retrospectively characterized the effects of intravenously administered chemotherapy on brain glucose metabolism in a total of 24 brain regions in a homogenous cohort of 10 patients with newly diagnosed non-small-cell lung cancer. RESULTS: Significant alterations of glucose metabolism were found in response to chemotherapy in all gray matter structures, including cortical structures, deep nuclei, hippocampi, and cerebellum. Metabolic changes were also notable in frontotemporal white matter (WM) network systems, including the corpus callosum, subcortical, and periventricular WM tracts. INTERPRETATION: Our data demonstrate a decrease in glucose metabolism in both gray and white matter structures associated with chemotherapy. Among the affected regions are those relevant to the maintenance of brain plasticity and global neurologic function. This study potentially offers novel insights into the spatial and temporal effects of systemic chemotherapy on brain metabolism in cancer patients.
Gao Y, Zhu L, Norton I, Agar NYR, Tannenbaum A. Reconstruction and Feature Selection for Desorption Electrospray Ionization Mass Spectroscopy Imagery. Proc SPIE Int Soc Opt Eng. 2014;9036:90360D.
Desorption electrospray ionization mass spectrometry (DESI-MS) provides a highly sensitive imaging technique for differentiating normal and cancerous tissue at the molecular level. This can be very useful, especially under intra-operative conditions where the surgeon has to make crucial decision about the tumor boundary. In such situations, the time it takes for imaging and data analysis becomes a critical factor. Therefore, in this work we utilize compressive sensing to perform the sparse sampling of the tissue, which halves the scanning time. Furthermore, sparse feature selection is performed, which not only reduces the dimension of data from about 10(4) to less than 50, and thus significantly shortens the analysis time. This procedure also identifies biochemically important molecules for pathological analysis. The methods are validated on brain and breast tumor data sets.
Gao Y, Zhu LJ, Bouix S, Tannenbaum A. Interpolation of Longitudinal Shape and Image Data via Optimal Mass Transport. Proc SPIE Int Soc Opt Eng. 2014;9034:90342X.
Longitudinal analysis of medical imaging data has become central to the study of many disorders. Unfortunately, various constraints (study design, patient availability, technological limitations) restrict the acquisition of data to only a few time points, limiting the study of continuous disease/treatment progression. Having the ability to produce a sensible time interpolation of the data can lead to improved analysis, such as intuitive visualizations of anatomical changes, or the creation of more samples to improve statistical analysis. In this work, we model interpolation of medical image data, in particular shape data, using the theory of optimal mass transport (OMT), which can construct a continuous transition from two time points while preserving "mass" (e.g., image intensity, shape volume) during the transition. The theory even allows a short extrapolation in time and may help predict short-term treatment impact or disease progression on anatomical structure. We apply the proposed method to the hippocampus-amygdala complex in schizophrenia, the heart in atrial fibrillation, and full head MR images in traumatic brain injury.
Huang S, Rossi S, Hämäläinen M, Ahveninen J. Auditory conflict resolution correlates with medial-lateral frontal theta/alpha phase synchrony. PLoS One. 2014;9(10):e110989.
When multiple persons speak simultaneously, it may be difficult for the listener to direct attention to correct sound objects among conflicting ones. This could occur, for example, in an emergency situation in which one hears conflicting instructions and the loudest, instead of the wisest, voice prevails. Here, we used cortically-constrained oscillatory MEG/EEG estimates to examine how different brain regions, including caudal anterior cingulate (cACC) and dorsolateral prefrontal cortices (DLPFC), work together to resolve these kinds of auditory conflicts. During an auditory flanker interference task, subjects were presented with sound patterns consisting of three different voices, from three different directions (45° left, straight ahead, 45° right), sounding out either the letters "A" or "O". They were asked to discriminate which sound was presented centrally and ignore the flanking distracters that were phonetically either congruent (50%) or incongruent (50%) with the target. Our cortical MEG/EEG oscillatory estimates demonstrated a direct relationship between performance and brain activity, showing that efficient conflict resolution, as measured with reduced conflict-induced RT lags, is predicted by theta/alpha phase coupling between cACC and right lateral frontal cortex regions intersecting the right frontal eye fields (FEF) and DLPFC, as well as by increased pre-stimulus gamma (60-110 Hz) power in the left inferior fontal cortex. Notably, cACC connectivity patterns that correlated with behavioral conflict-resolution measures were found during both the pre-stimulus and the pre-response periods. Our data provide evidence that, instead of being only transiently activated upon conflict detection, cACC is involved in sustained engagement of attentional resources required for effective sound object selection performance.
Echlin PS, Johnson AM, Holmes JD, Tichenoff A, Gray S, Gatavackas H, Walsh J, Middlebro T, Blignaut A, MacIntyre M, Anderson C, Fredman E, Mayinger M, Skopelja EN, Sasaki T, Bouix S, Pasternak O, Helmer KG, Koerte IK, Shenton ME, Forwell LA. The Sport Concussion Education Project. A brief report on an educational initiative: from concept to curriculum. J Neurosurg. 2014;121(6):1331–6.
Current research on concussion is primarily focused on injury identification and treatment. Prevention initiatives are, however, important for reducing the incidence of brain injury. This report examines the development and implementation of an interactive electronic teaching program (an e-module) that is designed specifically for concussion education within an adolescent population. This learning tool and the accompanying consolidation rubric demonstrate that significant engagement occurs in addition to the knowledge gained among participants when it is used in a school curriculum setting.