Daina Burnes

Development of a clinical research tool to track variation in metastatic tumor density in the spine.

Primary breast cancer commonly metastasizes to the vertebrae, forming osteolytic and/or blastic lesions. Osteolytic lesions de-calcify bone, depicted as a lowered density volume within the bone. Blastic tumor calcifies bone, recognized as volumes of high density within the vertebrae. Computed Tomography (CT) is the conventional imaging technology used to monitor the tumor variation within bone. Monitoring the disease progression commonly involves the qualitative assessment of two-dimensional axial CT slices taken through the diseased vertebrae. Previous studies motivated the need to develop a quantitative method to assess the progression or regression of the disease. The objective of this study was to develop a clinical research tool to serially track tumor involvement in vertebrae with metastatic disease by quantifying changes in CT attenuation. A program was developed to semi-automatically segment the total vertebral body and tumor volume alone from CT scans of metastatically involved vertebrae. Image registration through user-defined landmarks and surface matching was used to spatially align serial scans, and the initial segmentation was superimposed with the aligned scans. Changes within the segmentation between CT scans were tracked using mean density and a voxel distribution histogram. A cadaveric vertebra with a simulated tumor was scanned at 5 orientations with 20 degree offsets to determine the accuracy of the methods. Error primarily resulted from unavoidable re-sampling during alignment of the scans. The vertebral body segmentation was more accurate at tracking tumor involvement (voxel distribution histogram: 96.8% +/- 0.75% accuracy, mean density error: 4.7% +/- 0.8%) than segmenting the tumor volume alone (voxel distribution histogram: 86.1% +/- 3.6% accuracy, mean density error: 14.1% +/- 4.8%). Segmentation of the vertebral body and analysis of the voxel distribution within the region provides the most accurate method of quantifying changes in tumor involvement for the metastatic spine. A quantitative method to assess the progression or regression of disease may improve clinical decision-making and treatment options for patients with spinal metastases.

Doppler Optical Coherence Tomography (DOCT) is a non-invasive imaging modality that provides subsurface images with high spatial resolution (~20mm) and velocity sensitivity (~20mm/s). The technology is used to detect and quantify vascular blood flow for various applications including abnormal retinal and esophageal vascularization. The study of dynamic vascular flow is not fully realized due to the complex nature of blood flow in elastic, branching and tapering geometries. Although the laws governing conventional fluid dynamics are well characterized, correlation to microvascularization is difficult due to intermittent deviations. To address this problem, two tissue- mimicking flow phantoms were designed with known geometries to aid DOCT signal interpretation. Two flow arrangements were examined; a straight flow path to simulate parabolic laminar flow and an occluded flow path to model vessel narrowing. The DOCT system produced two-dimensional image data sets that were stacked sequentially to yield three dimensional reconstructions of microstructure and perfusion-level blood flow. These experiments validated the capacity of DOCT to detect flow velocities of 1.7 mm/s and 5.7 mm/s in the 450 micron and 250 micron diameter model vessels. The three-dimensional reconstructions allowed the investigation of internal flow patterns, including the pressure drop across an abrupt occlusion. This research was designed to guide image interpretation of in-vivo DOCT studies, including treatment response monitoring in animal tumors and endoscopic assessment of the human GI tract. Quantification of abnormal vascularization has several important applications including characterizing angiogenesis, tissue microcirculation and tumor vascular response to therapy.

The most common clinical appearance of vision loss associated with macular degeneration is age related macular degeneration (AMD). Type I AMD causes vision loss due to abnormal choroidal neovascularization (CNV) leading to blood leakage in the choroid of the retina. The standard method for the diagnosis and monitoring of type I AMD is color fundus photography (CFP) and fluorescein angiography (FA). These technologies provide information about the en-face location of macular abnormalities but do not offer depth information throughout the macular region of the retina and choroid. Conventional spectral domain optical coherence tomography operating at a spectral range of 850nm provides adequate depth resolution to visualize the retina, but does not sufficiently resolve structures at or below the choroid. The purpose of this project was to assess the application of ophthalmic optical frequency domain imaging (OFDI) at 1050 nm in combination with post-image processing methods for the detection of CNV in Type I AMD. An OFDI system consisting of a swept laser with a bandwidth of 64nm centered at 1050nm was developed. The system demonstrated an improved depth range of 2-2.4mm compared to conventional 850nm systems. Three-dimensional image datasets can be acquired and post-processed to identify and obtain volumetric measurements of distinct structures representing AMD. The efficacy of this technology was assessed as a clinical tool to monitor AMD before and after treatment. Patients were imaged before treatment with ranibizumab, a monoclonal antibody that binds and inhibits vascular endothelial growth factor A (VEGF-A). Patients were subsequently imaged following 4-8 treatments. The subretinal fluid, intra-retinal edema and CNV volumes were segmented by the design of advanced image processing techniques. Enface images from the OFDI cross sections were co-registered with CFP and FA, in addition to compiling CNV thickness maps. In post treatment scans, the technology could detect a reduction or absence of subretinal fluid and retinal edema volumes, as well as a diminution of the CNV volume. The CNV thickness maps correlated to the areas corresponding to CNV detected by FA. There was no complete loss of type I CNV identified in any patient treated with ranibizumab, providing a potential explanation to the regression seen in patients when taken off the drug. The significance of this technology is its potential for early non-invasive diagnosis and post-treatment monitoring of AMD.