5 resultados para Biological imaging
em Duke University
Resumo:
Luminescent semiconductor nanocrystals, also known as quantum dots (QDs), have advanced the fields of molecular diagnostics and nanotherapeutics. Much of the initial progress for QDs in biology and medicine has focused on developing new biosensing formats to push the limit of detection sensitivity. Nevertheless, QDs can be more than passive bio-probes or labels for biological imaging and cellular studies. The high surface-to-volume ratio of QDs enables the construction of a "smart" multifunctional nanoplatform, where the QDs serve not only as an imaging agent but also a nanoscaffold catering for therapeutic and diagnostic (theranostic) modalities. This mini review highlights the emerging applications of functionalized QDs as fluorescence contrast agents for imaging or as nanoscale vehicles for delivery of therapeutics, with special attention paid to the promise and challenges towards QD-based theranostics.
Resumo:
The ability of diffuse reflectance spectroscopy to extract quantitative biological composition of tissues has been used to discern tissue types in both pre-clinical and clinical cancer studies. Typically, diffuse reflectance spectroscopy systems are designed for single-point measurements. Clinically, an imaging system would provide valuable spatial information on tissue composition. While it is feasible to build a multiplexed fiber-optic probe based spectral imaging system, these systems suffer from drawbacks with respect to cost and size. To address these we developed a compact and low cost system using a broadband light source with an 8-slot filter wheel for illumination and silicon photodiodes for detection. The spectral imaging system was tested on a set of tissue mimicking liquid phantoms which yielded an optical property extraction accuracy of 6.40 +/- 7.78% for the absorption coefficient (micro(a)) and 11.37 +/- 19.62% for the wavelength-averaged reduced scattering coefficient (micro(s)').
Resumo:
BACKGROUND: The bioluminescence technique was used to quantify the local glucose concentration in the tissue surrounding subcutaneously implanted polyurethane material and surrounding glucose sensors. In addition, some implants were coated with a single layer of adipose-derived stromal cells (ASCs) because these cells improve the wound-healing response around biomaterials. METHODS: Control and ASC-coated implants were implanted subcutaneously in rats for 1 or 8 weeks (polyurethane) or for 1 week only (glucose sensors). Tissue biopsies adjacent to the implant were immediately frozen at the time of explant. Cryosections were assayed for glucose concentration profile using the bioluminescence technique. RESULTS: For the polyurethane samples, no significant differences in glucose concentration within 100 μm of the implant surface were found between bare and ASC-coated implants at 1 or 8 weeks. A glucose concentration gradient was demonstrated around the glucose sensors. For all sensors, the minimum glucose concentration of approximately 4 mM was found at the implant surface and increased with distance from the sensor surface until the glucose concentration peaked at approximately 7 mM at 100 μm. Then the glucose concentration decreased to 5.5-6.5 mM more than 100 μmm from the surface. CONCLUSIONS: The ASC attachment to polyurethane and to glucose sensors did not change the glucose profiles in the tissue surrounding the implants. Although most glucose sensors incorporate a diffusion barrier to reduce the gradient of glucose and oxygen in the tissue, it is typically assumed that there is no steep glucose gradient around the sensors. However, a glucose gradient was observed around the sensors. A more complete understanding of glucose transport and concentration gradients around sensors is critical.
Resumo:
Magnetic resonance imaging is a research and clinical tool that has been applied in a wide variety of sciences. One area of magnetic resonance imaging that has exhibited terrific promise and growth in the past decade is magnetic susceptibility imaging. Imaging tissue susceptibility provides insight into the microstructural organization and chemical properties of biological tissues, but this image contrast is not well understood. The purpose of this work is to develop effective approaches to image, assess, and model the mechanisms that generate both isotropic and anisotropic magnetic susceptibility contrast in biological tissues, including myocardium and central nervous system white matter.
This document contains the first report of MRI-measured susceptibility anisotropy in myocardium. Intact mouse heart specimens were scanned using MRI at 9.4 T to ascertain both the magnetic susceptibility and myofiber orientation of the tissue. The susceptibility anisotropy of myocardium was observed and measured by relating the apparent tissue susceptibility as a function of the myofiber angle with respect to the applied magnetic field. A multi-filament model of myocardial tissue revealed that the diamagnetically anisotropy α-helix peptide bonds in myofilament proteins are capable of producing bulk susceptibility anisotropy on a scale measurable by MRI, and are potentially the chief sources of the experimentally observed anisotropy.
The growing use of paramagnetic contrast agents in magnetic susceptibility imaging motivated a series of investigations regarding the effect of these exogenous agents on susceptibility imaging in the brain, heart, and kidney. In each of these organs, gadolinium increases susceptibility contrast and anisotropy, though the enhancements depend on the tissue type, compartmentalization of contrast agent, and complex multi-pool relaxation. In the brain, the introduction of paramagnetic contrast agents actually makes white matter tissue regions appear more diamagnetic relative to the reference susceptibility. Gadolinium-enhanced MRI yields tensor-valued susceptibility images with eigenvectors that more accurately reflect the underlying tissue orientation.
Despite the boost gadolinium provides, tensor-valued susceptibility image reconstruction is prone to image artifacts. A novel algorithm was developed to mitigate these artifacts by incorporating orientation-dependent tissue relaxation information into susceptibility tensor estimation. The technique was verified using a numerical phantom simulation, and improves susceptibility-based tractography in the brain, kidney, and heart. This work represents the first successful application of susceptibility-based tractography to a whole, intact heart.
The knowledge and tools developed throughout the course of this research were then applied to studying mouse models of Alzheimer’s disease in vivo, and studying hypertrophic human myocardium specimens ex vivo. Though a preliminary study using contrast-enhanced quantitative susceptibility mapping has revealed diamagnetic amyloid plaques associated with Alzheimer’s disease in the mouse brain ex vivo, non-contrast susceptibility imaging was unable to precisely identify these plaques in vivo. Susceptibility tensor imaging of human myocardium specimens at 9.4 T shows that susceptibility anisotropy is larger and mean susceptibility is more diamagnetic in hypertrophic tissue than in normal tissue. These findings support the hypothesis that myofilament proteins are a source of susceptibility contrast and anisotropy in myocardium. This collection of preclinical studies provides new tools and context for analyzing tissue structure, chemistry, and health in a variety of organs throughout the body.
Resumo:
Scatter in medical imaging is typically cast off as image-related noise that detracts from meaningful diagnosis. It is therefore typically rejected or removed from medical images. However, it has been found that every material, including cancerous tissue, has a unique X-ray coherent scatter signature that can be used to identify the material or tissue. Such scatter-based tissue-identification provides the advantage of locating and identifying particular materials over conventional anatomical imaging through X-ray radiography. A coded aperture X-ray coherent scatter spectral imaging system has been developed in our group to classify different tissue types based on their unique scatter signatures. Previous experiments using our prototype have demonstrated that the depth-resolved coherent scatter spectral imaging system (CACSSI) can discriminate healthy and cancerous tissue present in the path of a non-destructive x-ray beam. A key to the successful optimization of CACSSI as a clinical imaging method is to obtain anatomically accurate phantoms of the human body. This thesis describes the development and fabrication of 3D printed anatomical scatter phantoms of the breast and lung.
The purpose of this work is to accurately model different breast geometries using a tissue equivalent phantom, and to classify these tissues in a coherent x-ray scatter imaging system. Tissue-equivalent anatomical phantoms were designed to assess the capability of the CACSSI system to classify different types of breast tissue (adipose, fibroglandular, malignant). These phantoms were 3D printed based on DICOM data obtained from CT scans of prone breasts. The phantoms were tested through comparison of measured scatter signatures with those of adipose and fibroglandular tissue from literature. Tumors in the phantom were modeled using a variety of biological tissue including actual surgically excised benign and malignant tissue specimens. Lung based phantoms have also been printed for future testing. Our imaging system has been able to define the location and composition of the various materials in the phantom. These phantoms were used to characterize the CACSSI system in terms of beam width and imaging technique. The result of this work showed accurate modeling and characterization of the phantoms through comparison of the tissue-equivalent form factors to those from literature. The physical construction of the phantoms, based on actual patient anatomy, was validated using mammography and computed tomography to visually compare the clinical images to those of actual patient anatomy.