Atlas-Based Segmentation of Brain Tumor Images Using a Markov Random Field-Based Tumor Growth Model and Non-Rigid Registration

We propose a new and clinically oriented approach to perform atlas-based segmentation of brain tumor images. A mesh-free method is used to model tumor-induced soft tissue deformations in a healthy brain atlas image with subsequent registration of the modified atlas to a pathologic patient image. The atlas is seeded with a tumor position prior and tumor growth simulating the tumor mass effect is performed with the aim of improving the registration accuracy in case of patients with space-occupying lesions. We perform tests on 2D axial slices of five different patient data sets and show that the approach gives good results for the segmentation of white matter, grey matter, cerebrospinal fluid and the tumor.

Computed tomography angiography (CTA) to prove circulatory arrest for the diagnosis of brain death in the context of organ transplantation

For the determination of brain death (BD) in potential organ donors, confirmatory tests that show cessation of cerebral circulation are used in many countries. Conventional angiography is considered the golden standard among these ancillary examinations. In recent years other angiographic techniques such as CT angiography (CTA) have been increasingly employed to establish the diagnosis of BD. We report our experience with CTA in this setting.

Fully Automatic Segmentation of Brain Tumor Images using Support Vector Machine Classiffication in Combination with Hierarchical Conditional Random Field Regularization

Delineating brain tumor boundaries from magnetic resonance images is an essential task for the analysis of brain cancer. We propose a fully automatic method for brain tissue segmentation, which combines Support Vector Machine classification using multispectral intensities and textures with subsequent hierarchical regularization based on Conditional Random Fields. The CRF regularization introduces spatial constraints to the powerful SVM classification, which assumes voxels to be independent from their neighbors. The approach first separates healthy and tumor tissue before both regions are subclassified into cerebrospinal fluid, white matter, gray matter and necrotic, active, edema region respectively in a novel hierarchical way. The hierarchical approach adds robustness and speed by allowing to apply different levels of regularization at different stages. The method is fast and tailored to standard clinical acquisition protocols. It was assessed on 10 multispectral patient datasets with results outperforming previous methods in terms of segmentation detail and computation times.

Multi-Scale Modeling for Image Analysis of Brain Tumor Studies

Image-based modeling of tumor growth combines methods from cancer simulation and medical imaging. In this context, we present a novel approach to adapt a healthy brain atlas to MR images of tumor patients. In order to establish correspondence between a healthy atlas and a pathologic patient image, tumor growth modeling in combination with registration algorithms is employed. In a first step, the tumor is grown in the atlas based on a new multi-scale, multi-physics model including growth simulation from the cellular level up to the biomechanical level, accounting for cell proliferation and tissue deformations. Large-scale deformations are handled with an Eulerian approach for finite element computations, which can operate directly on the image voxel mesh. Subsequently, dense correspondence between the modified atlas and patient image is established using nonrigid registration. The method offers opportunities in atlasbased segmentation of tumor-bearing brain images as well as for improved patient-specific simulation and prognosis of tumor progression.

Segmentation of brain tumor images based on atlas-registration combined with a Markov-Random-Field lesion growth model

We present an automatic method to segment brain tissues from volumetric MRI brain tumor images. The method is based on non-rigid registration of an average atlas in combination with a biomechanically justified tumor growth model to simulate soft-tissue deformations caused by the tumor mass-effect. The tumor growth model, which is formulated as a mesh-free Markov Random Field energy minimization problem, ensures correspondence between the atlas and the patient image, prior to the registration step. The method is non-parametric, simple and fast compared to other approaches while maintaining similar accuracy. It has been evaluated qualitatively and quantitatively with promising results on eight datasets comprising simulated images and real patient data.

Comparison of C-11 methionine and C-11 choline for PET imaging of brain metastases: a prospective pilot study

The aim of the study was the comparison of C-11 methionine (MET) and C-11 choline (CHO) in the positron emission tomography (PET) imaging of brain metastases in correlation to the histopathology findings in stereotactic biopsy.

Comparison of brain PrPd distribution in ovine BSE and scrapie

Scrapie and bovine spongiform encephalopathy (BSE) are both prion diseases affecting ruminants, and these diseases do not share the same public health concerns. Surveillance of the BSE agent in small ruminants has been a great challenge, and the recent identification of diverse prion diseases in ruminants has led to the development of new methods for strain typing. In our study, using immunohistochemistry (IHC), we assessed the distribution of PrP(d) in the brains of 2 experimentally BSE-infected sheep with the ARQ/ARQ genotype. Distribution of PrP(d) in the brain, from the spinal cord to the frontal cortex, was remarkably similar in the 2 sheep despite different inoculation routes and incubation periods. Comparatively, overall PrP(d) brain distribution, evaluated by IHC, in 19 scrapie cases with the ARQ/ARQ, ARQ/VRQ, and VRQ/VRQ genotypes, in some cases showed similarities to the experimentally BSE-infected sheep. There was no exclusive neuroanatomical site with a characteristic and specific PrP(d) type of accumulation induced by the BSE agent. However, a detailed analysis of the topography, types, and intensity of PrP(d) deposits in the frontal cortex, striatum, piriform cortex, hippocampus, mesencephalon, and cerebellum allowed the BSE-affected sheep group to be distinguished from the 19 scrapie cases analyzed in our study. These results strengthen and emphasize the potential interest of PrP(d) brain mapping to help in identifying prion strains in small ruminants.

Chalcone JAI-51 improves efficacy of synchrotron microbeam radiation therapy of brain tumors

Microbeam radiation therapy (MRT), a preclinical form of radiosurgery, uses spatially fractionated micrometre-wide synchrotron-generated X-ray beams. As MRT alone is predominantly palliative for animal tumors, the effects of the combination of MRT and a newly synthesized chemotherapeutic agent JAI-51 on 9L gliosarcomas have been evaluated. Fourteen days (D14) after implantation (D0), intracerebral 9LGS-bearing rats received either MRT, JAI-51 or both treatments. JAI-51, alone or immediately after MRT, was administered three times per week. Animals were kept up to ∼20 weeks after irradiation or sacrificed at D16 or D28 after treatment for cell cycle analysis. MRT plus JAI-51 increased significantly the lifespan compared with MRT alone (p = 0.0367). JAI-51 treatment alone had no effect on rat survival. MRT alone or associated with JAI-51 induced a cell cycle blockade in G2/M (p < 0.01) while the combined treatment also reduced the proportion of G0/G1 cells. At D28 after irradiation, MRT and MRT/JAI-51 had a smaller cell blockade effect in the G2/M phase owing to a significant increase in tumor cell death rate (<2c) and a proportional increase of endoreplicative cells (>8c). The combination of MRT and JAI-51 increases the survival of 9LGS-bearing rats by inducing endoreduplication of DNA and tumor cell death; further, it slowed the onset of tumor growth resumption two weeks after treatment.

Early assessment of brain maturation by MR imaging segmentation in neonates and premature infants

PURPOSE: We evaluated the impact of premature extrauterine life on brain maturation. PATIENTS AND METHODS: Twelve neonates underwent MR imaging at 40 (39.64 +/- 0.98) weeks (full term). Fifteen premature infants underwent 2 MR imaging examinations, after birth (preterm at birth) and at 40 weeks (41.03 +/- 1.33) (preterm at term). A 3D MR imaging technique was used to measure brain volumes compared with intracranial volume: total brain volume, cortical gray matter, myelinated white matter, unmyelinated white matter, basal ganglia (BG), and CSF. RESULTS: The average absolute volume of intracranial volume (269.8 mL +/- 36.5), total brain volume (246.5 +/- 32.3), cortical gray matter (85.53 mL +/- 22.23), unmyelinated white matter (142.4 mL +/-14.98), and myelinated white matter (6.099 mL +/-1.82) for preterm at birth was significantly lower compared with that for the preterm at term: the average global volume of intracranial volume (431.7 +/- 69.98), total brain volume (391 +/- 66,1), cortical gray matter (179 mL +/- 41.54), unmyelinated white matter (185.3 mL +/- 30.8), and myelinated white matter (10.66 mL +/- 3.05). It was also lower compared with that of full-term infants: intracranial volume (427.4 mL +/- 53.84), total brain volume (394 +/- 49.22), cortical gray matter (181.4 +/- 29.27), unmyelinated white matter (183.4 +/- 27.37), and myelinated white matter (10.72 +/- 4.63). The relative volume of cortical gray matter (30.62 +/- 5.13) and of unmyelinated white matter (53.15 +/- 4.8) for preterm at birth was significantly different compared with the relative volume of cortical gray matter (41.05 +/- 5.44) and of unmyelinated white matter (43.22 +/- 5.11) for the preterm at term. Premature infants had similar brain tissue volumes at 40 weeks to full-term infants. CONCLUSION: MR segmentation techniques demonstrate that cortical neonatal maturation in moderately premature infants at term and term-born infants was similar.

Effects of local continuous release of brain derived neurotrophic factor (BDNF) on peripheral nerve regeneration in a rat model

The purpose of this study was to evaluate the effect of continuously released BDNF on peripheral nerve regeneration in a rat model. Initial in vitro evaluation of calcium alginate prolonged-release-capsules (PRC) proved a consistent release of BDNF for a minimum of 8 weeks. In vivo, a worst case scenario was created by surgical removal of a 20-mm section of the sciatic nerve of the rat. Twenty-four autologous fascia tubes were filled with calcium alginate spheres and sutured to the epineurium of both nerve ends. The animals were divided into 3 groups. In group 1, the fascial tube contained plain calcium alginate spheres. In groups 2 and 3, the fascial tube contained calcium alginate spheres with BDNF alone or BDNF stabilized with bovine serum albumin, respectively. The autocannibalization of the operated extremity was clinically assessed and documented in 12 additional rats. The regeneration was evaluated histologically at 4 weeks and 10 weeks in a blinded manner. The length of nerve fibers and the numbers of axons formed in the tube was measured. Over a 10-week period, axons have grown significantly faster in groups 2 and 3 with continuously released BDNF compared to the control. The rats treated with BDNF (groups 2 and 3) demonstrated significantly less autocannibalization than the control group (group 1). These results suggest that BDNF may not only stimulate faster peripheral nerve regeneration provided there is an ideal, biodegradable continuous delivery system but that it significantly reduces the neuropathic pain in the rat model.

Little strokes fill big oaks: a simple in vivo stain of brain cells

High-resolution functional imaging of neural activity in vivo relies on appropriate labeling methods. In this issue of Neuron, Nagayama et al. introduce a simple procedure for staining subsets of neurons with organic calcium indicator dyes via local electroporation. Neuronal populations are sparsely labeled, preserving the ability to resolve calcium signals in dendrites and synaptic structures.