Magnetic Resonance Imaging (MRI)

The lack of relevant pre-clinical animal models incorporating the clinical scenario of Glioblastoma multiforme (GBM) resection and recurrence has contributed significantly to the inability to successfully treat GBM. A multi-modality imaging approach that allows real-time assessment of tumor resection during surgery and non-invasive detection of post-operative tumor volumes is urgently needed.

Several imaging modalities are suitable for in vivo molecular neuroimaging, but the blood-brain barrier (BBB) limits their utility by preventing brain delivery of most targeted molecular probes. We prepared biodegradable nanocarrier systems made up of poly(n-butyl cyanoacrylate) dextran polymers coated with polysorbate 80 (PBCA nanoparticles) to deliver BBB-impermeable molecular imaging probes into the brain for targeted molecular neuroimaging.

Spatial unwrapping of the phase component of time varying electromagnetic fields has important implications in a range of disciplines including synthetic aperture radar (SAR) interferometry, MRI, optical confocal microscopy, and microwave tomography. This paper presents a fundamental framework based on the phase unwrapping integral, especially in the complex case where phase singularities are enclosed within the closed path integral.

RATIONALE AND OBJECTIVES: We have developed a microwave tomography system for experimental breast imaging.

The magnetic resonance imaging (MRI)-detectable T1 contrast agent manganese (Mn2+) has recently been introduced as a neural tracer in rodents, birds, and monkeys. We have tested to what extent this in vivo method is useful for three-dimensional (3-D) survey of connectivity patterns in the rat somatosensory system. A commonly available 3 T human clinical MRI scanner was used to trace neural pathways following focal injection of manganese chloride (MnCl2) in the somatosensory cortex.

Recent advances in brain imaging have improved the measure of neural processes related to perceptual, cognitive and affective functions, yet the relation between brain activity and subjective experience remains poorly characterized. In part, it is a challenge to obtain reliable accounts of participant's experience in such studies. Here we addressed this limitation by utilizing experienced meditators who are expert in introspection.

This work presents a method that permits the characterization, quantification, and 3D visualization of white matter structural information contained within diffusion tensor MR imaging (DT-MRI) data. In this method, regions within the brain are defined as possessing linear, planar, or spherical diffusion. Visualization of this diffusion metric data is realized by generating streamtube and streamsurface models to represent regions of linear and planar diffusion.

A novel cellular automaton model of proliferative brain tumor growth has been developed. This model is able to simulate Gompertzian tumor growth over nearly three orders of magnitude in radius using only four microscopic parameters. The predicted composition and growth rates are in agreement with a test case pooled from the available medical literature. The model incorporates several new features, improving previous models, and also allows ready extension to study other important properties of tumor growth, such as clonal competition.

We have developed a novel and versatile three-dimensional cellular automaton model of brain tumor growth. We show that macroscopic tumor behavior can be realistically modeled using microscopic parameters. Using only four parameters, this model simulates Gompertzian growth for a tumor growing over nearly three orders of magnitude in radius. It also predicts the composition and dynamics of the tumor at selected time points in agreement with medical literature.