Animal experiment (rabbit) to demonstrate changes in trabecular bone mechanical properties over time using finite element analysis.

Decreased strength of trabecular bone is a direct effect of osteoporosis, which can be evaluated by finite element analysis. However, computational limitations have restricted previous trabecular bone analyses primarily to the linear domain. In addition, previous work was largely invasive and the corresponding finite element models were typically homogeneous. Nonlinear heterogeneous finite element analysis was used to calculate trabecular bone apparent strength directly from in vivo micro computational tomography (micro-CT) scans. Through a series of validation experiments, it was shown that this nonlinear modeling is more accurate in evaluating trabecular bone mechanics in osteoporosis than previous work. A parameter driven set of material properties was employed in the finite element models using gray levels in the form of Hounsfield units as the independent variable. This enabled the finite element models to capture the variations of material properties of trabecular bone. The methods and techniques for converting the micro-CT scans into finite element models, defining the finite element models (element type, material properties characteristics) and solving the models are discussed in detail. In addition, the techniques developed for image preprocessing, such as image registration and image degradation, are also provided in this dissertation. The scanning, image processing and modeling methods and techniques were applied to two groups of rabbits, an ovariectomy group and a control group, to evaluate the time-course of trabecular bone osteoporosis. Our experiment showed that ovariectomy significantly slows the normal bone strength increase over time observed in the control group. The strength increase over time was due to a combination of increased bone architecture indices such as volume fraction and trabecular thickness as well as increased material properties due to greater bone tissue density. Compared to heterogeneous models, the homogeneous models reflected less strength increase over time because they lack the capability to capture tissue level material property variations. Volume fraction analysis alone resulted in even lower predicted increases in bone strength because it could only monitor the bone apparent level density variation. Thus the nonlinear heterogeneous models, with parameter driven material definitions, are more accurate than other types of models or methods

Automation Process for Morphometric Analysis of Volumetric CT Data from Pulmonary Vasculature in Rats

With advances in medical imaging scanners, it has become commonplace to generate large multidimensional datasets. These datasets require tools for a rapid, thorough analysis. To address this need, we have developed an automated algorithm for morphometric analysis incorporating A Visualization Workshop computational and image processing libraries for three-dimensional segmentation, vascular tree generation and structural hierarchical ordering with a two-stage numeric optimization procedure for estimating vessel diameters. We combine this new technique with our mathematical models of pulmonary vascular morphology to quantify structural and functional attributes of lung arterial trees. Our physiological studies require repeated measurements of vascular structure to determine differences in vessel biomechanical properties between animal models of pulmonary disease. Automation provides many advantages including significantly improved speed and minimized operator interaction and biasing. The results are validated by comparison with previously published rat pulmonary arterial micro-CT data analysis techniques, in which vessels were manually mapped and measured using intense operator intervention

An open environment CT-US fusion for tissue segmentation during interventional guidance.

Therapeutic ultrasound (US) can be noninvasively focused to activate drugs, ablate tumors and deliver drugs beyond the blood brain barrier. However, well-controlled guidance of US therapy requires fusion with a navigational modality, such as magnetic resonance imaging (MRI) or X-ray computed tomography (CT). Here, we developed and validated tissue characterization using a fusion between US and CT. The performance of the CT/US fusion was quantified by the calibration error, target registration error and fiducial registration error. Met-1 tumors in the fat pads of 12 female FVB mice provided a model of developing breast cancer with which to evaluate CT-based tissue segmentation. Hounsfield units (HU) within the tumor and surrounding fat pad were quantified, validated with histology and segmented for parametric analysis (fat: -300 to 0 HU, protein-rich: 1 to 300 HU, and bone: HU>300). Our open source CT/US fusion system differentiated soft tissue, bone and fat with a spatial accuracy of ∼1 mm. Region of interest (ROI) analysis of the tumor and surrounding fat pad using a 1 mm(2) ROI resulted in mean HU of 68±44 within the tumor and -97±52 within the fat pad adjacent to the tumor (p<0.005). The tumor area measured by CT and histology was correlated (r(2) = 0.92), while the area designated as fat decreased with increasing tumor size (r(2) = 0.51). Analysis of CT and histology images of the tumor and surrounding fat pad revealed an average percentage of fat of 65.3% vs. 75.2%, 36.5% vs. 48.4%, and 31.6% vs. 38.5% for tumors <75 mm(3), 75-150 mm(3) and >150 mm(3), respectively. Further, CT mapped bone-soft tissue interfaces near the acoustic beam during real-time imaging. Combined CT/US is a feasible method for guiding interventions by tracking the acoustic focus within a pre-acquired CT image volume and characterizing tissues proximal to and surrounding the acoustic focus

Quantification of image texture in X-ray phase-contrast-enhanced projection images of in vivo mouse lungs observed at varied inflation pressures

To date, there are very limited noninvasive, regional assays of in vivo lung microstructure near the alveolar level. It has been suggested that x-ray phase-contrast enhanced imaging reveals information about the air volume of the lung; however, the image texture information in these images remains underutilized. Projection images of in vivo mouse lungs were acquired via a tabletop, propagation-based, X-ray phase-contrast imaging system. Anesthetized mice were mechanically ventilated in an upright position. Consistent with previously published studies, a distinct image texture was observed uniquely within lung regions. Lung regions were automatically identified using supervised machine learning applied to summary measures of the image texture data. It was found that an unsupervised clustering within predefined lung regions colocates with expected differences in anatomy along the cranial-caudal axis in upright mice. It was also found that specifically selected inflation pressures-here, a purposeful surrogate of distinct states of mechanical expansion-can be predicted from the lung image texture alone, that the prediction model itself varies from apex to base and that prediction is accurate regardless of overlap with nonpulmonary structures such as the ribs, mediastinum, and heart. Cross-validation analysis indicated low inter-animal variation in the image texture classifications. Together, these results suggest that the image texture observed in a single X-ray phase-contrast-enhanced projection image could be used across a range of pressure states to study regional variations in regional lung function

Validation of 3\u27-deoxy-3\u27-[18F]-fluorothymidine positron emission tomography for image-guidance in biologically adaptive radiotherapy

Accelerated tumor cell repopulation during radiation therapy is one of the leading causes for low survival rates of head-and-neck cancer patients. The therapeutic effectiveness of radiotherapy could be improved by selectively targeting proliferating tumor subvolumes with higher doses of radiation. Positron emission tomography (PET) imaging with 3´-deoxy-3´-[18F]-fluorothymidine (FLT) has shown great potential as a non-invasive approach to characterizing the proliferation status of tumors. This thesis focuses on histopathological validation of FLT PET imaging specifically for image-guidance applications in biologically adaptive radiotherapy. The lack of experimental data supporting the use of FLT PET imaging for radiotherapy guidance is addressed by developing a novel methodology for histopathological validation of PET imaging. Using this new approach, the spatial concordance between the intratumoral pattern of FLT uptake and the spatial distribution of cell proliferation is demonstrated in animal tumors. First, a two-dimensional analysis is conducted comparing the microscopic FLT uptake as imaged with autoradiography and the distribution of active cell proliferation markers imaged with immunofluorescent microscopy. It was observed that when tumors present a pattern of cell proliferation that is highly dispersed throughout the tumor, even high-resolution imaging modalities such as autoradiography could not accurately determine the extent and spatial distribution of proliferative tumor subvolumes. While microscopic spatial coincidence between high FLT uptake regions and actively proliferative subvolumes was demonstrated in tumors with highly compartmentalized/aggregated features of cell proliferation, there were no conclusive results across the entire set of utilized tumor specimens. This emphasized the need for addressing the limited resolution of FLT PET when imaging microscopic patterns of cell proliferation. This issue was emphasized in the second part of the thesis where the spatial concordance between volumes segmented on FLT simulated FLT PET images and the three dimensional spatial distribution of cell proliferation markers was analyzed

Simulating Developmental Cardiac Morphology in Virtual Reality Using a Deformable Image Registration Approach

While virtual reality (VR) has potential in enhancing cardiovascular diagnosis and treatment, prerequisite labor-intensive image segmentation remains an obstacle for seamlessly simulating 4-dimensional (4-D, 3-D + time) imaging data in an immersive, physiological VR environment. We applied deformable image registration (DIR) in conjunction with 3-D reconstruction and VR implementation to recapitulate developmental cardiac contractile function from light-sheet fluorescence microscopy (LSFM). This method addressed inconsistencies that would arise from independent segmentations of time-dependent data, thereby enabling the creation of a VR environment that fluently simulates cardiac morphological changes. By analyzing myocardial deformation at high spatiotemporal resolution, we interfaced quantitative computations with 4-D VR. We demonstrated that our LSFM-captured images, followed by DIR, yielded average dice similarity coefficients of 0.92 ± 0.05 (n = 510) and 0.93 ± 0.06 (n = 240) when compared to ground truth images obtained from Otsu thresholding and manual segmentation, respectively. The resulting VR environment simulates a wide-angle zoomed-in view of motion in live embryonic zebrafish hearts, in which the cardiac chambers are undergoing structural deformation throughout the cardiac cycle. Thus, this technique allows for an interactive micro-scale VR visualization of developmental cardiac morphology to enable high resolution simulation for both basic and clinical science

The accuracy of cone beam computed tomography (CBCT) to determine newly formed bone within grafted maxillary sinus in sheep

Grafting of the maxillary sinus floor has become a common surgical intervention to increase bone volume for implant placement (Wallace and Froum, 2003); the procedure can be performed either as an 1-stage procedure with simultaneous implant placement or as a 2-stage procedure before implant placement (Bruggenkate and Bergh, 1998). In a 2-stage procedure, the chosen graft material is placed into the sinus floor and the graft material is left to consolidate with newly formed bone. This consolidation should preferably occur before implant placement. However, currently there is no clinical tool to assess healing within the grafted sinus. A trephine bone biopsy can be harvested for histological assessment but this is invasive and not clinically useful. The current clinical guideline is to wait between six to twelve months after maxillary sinus grafting before implant placement (Rodriguez et al., 2003) CBCT (Cone beam computed tomography) is a clinical 3-D (three-dimensional) radiographic tool for assessment of mineralised tissue (Ehrhart et al., 2008; Estrela et al., 2008) and may be used for assessment of graft healing within maxillary sinus. However, there are a limited number of studies looking at the use of CBCT in bone-density measurements (Benavides et al., 2012). Micro-computed tomography (µCT) is a 3-D radiographic tool mainly used for in vitro studies. Specimens with a volume of approximately 5cm3 can be scanned with up to a 1µm voxel resolution producing high-resolution radiographic images for mineralised tissues. There is growing evidence to suggest that µCT can be used as a substitute method for histology to measure mineralised tissue, particularly trabecular bone (Thomsen et al., 2000; Thomsen et al., 2005). With no clinical tool available for assessment of graft healing within the sinus, the purpose of this study was to assess whether CBCT can be used to measure the amount of newly formed bone in grafted maxillary sinus in sheep. To validate this, CBCT was compared with two reference standards; micro-computed tomography (µCT) and histology. Aim: To assess the effectiveness of CBCT for quantifying newly formed bone within grafted sinus sites, using an animal model. Method: Maxillary sinus grafting in six sheep with bovine xenograft (Endobon®) was evaluated after a sixteen-week healing period. Specimens from each animal were analysed using three imaging techniques: CBCT, µCT and resin-embedded histological sections. Two-dimensional "virtual" CBCT sections were matched with corresponding 2-D µCT sections and digitised histological sections. µCT and CBCT images were calibrated using known-density radiographic calibration standards. Using image analysis software (Image J, NIH, USA), % new bone (%NB), % residual graft (%RG), % mineralised tissue (%MT) were measured for matched regions of interest across each imaging technique and compared statistically (p<0.05). Results: CBCT measured %NB and %RG significantly higher than µCT and histology. µCT measured %NB significantly higher than histology. %RG measurements of µCT and histology were not significantly different. CBCT measured %MT significantly higher than both µCT and histology. %MT measurements of µCT and histology were statistically different but were very similar. Conclusion: Micro-computed tomography (µCT) measurements of residual graft and new bone were affected as the radiodensities of residual graft (Endobon®) and new bone were similar. µCT however appeared to be capable of measuring the combined area of graft and new bone (i.e., mineralised tissue) similar to histomorphometry. Cone-beam computerised tomography (CBCT) markedly overestimated new bone, residual graft and the total mineralised tissue. CBCT lacks the resolution to accurately determine newly formed bone after maxillary sinus grafting, an important step before definitive implant placement

Image Reconstruction of the Speed of Sound and Initial Pressure Distributions in Ultrasound Computed Tomography and Photoacoustic Computed Tomography

Ultrasound computed tomography (USCT) and photoacoustic computed tomography (PACT) are two emerging imaging modalities that have a wide range of potential applications from pre-clinical small animal imaging to cancer screening in human subjects. USCT is typically employed to measure acoustic contrasts, including the speed of sound (SOS) distribution, while PACT typically measures optical contrasts or some related quantity such as the initial pressure distribution. Their complementary contrasts and similar implementations make USCT and PACT a natural fit for a hybrid imaging system. Still, much work remains to realize this promise. First, USCT image reconstruction methods based on the acoustic wave equation, known as waveform inversion methods, are computationally burdensome, limiting their widespread use. Instead, image reconstruction methods based on geometric acoustics are often employed. These methods do not model higher-order diffraction effects and consequentially have poor resolution. In this dissertation, use of a novel stochastic optimization method, which overcomes much of the computational burden of waveform inversion, is proposed. Second, most traditional PACT image reconstruction algorithms assume a constant SOS distribution. For many biological applications, this is a poor assumption that can result in reduced resolution, reduced contrast, and an increase in the number of imaging artifacts. More recent image reconstruction algorithms can compensate for a known heterogeneous SOS distribution; however, in practice, the SOS distribution is not known. Further, in general, the joint reconstruction (JR) of the SOS and initial pressure distributions from PACT measurements is unstable. Two methods are proposed to overcome this problem. In the first, a parameterized JR method is employed. Under this approach, the SOS distribution is assumed to have a known low-dimensional representation. By constraining the form of the SOS distribution, the JR problem can be made more stable. In the second method, few-view USCT measurements are added to the PACT data, and the initial pressure and SOS distributions are jointly estimated from the combined measurements. This approach effectively exploits acoustic information present in the PACT data, allowing both the initial pressure and SOS distributions to be more accurately reconstructed

Quantitative characterization of pore structure of several biochars with 3D imaging

Pore space characteristics of biochars may vary depending on the used raw material and processing technology. Pore structure has significant effects on the water retention properties of biochar amended soils. In this work, several biochars were characterized with three-dimensional imaging and image analysis. X-ray computed microtomography was used to image biochars at resolution of 1.14 $\mu$m and the obtained images were analysed for porosity, pore-size distribution, specific surface area and structural anisotropy. In addition, random walk simulations were used to relate structural anisotropy to diffusive transport. Image analysis showed that considerable part of the biochar volume consist of pores in size range relevant to hydrological processes and storage of plant available water. Porosity and pore-size distribution were found to depend on the biochar type and the structural anisotopy analysis showed that used raw material considerably affects the pore characteristics at micrometre scale. Therefore attention should be paid to raw material selection and quality in applications requiring optimized pore structure.Comment: 16 pages, 4 figures. The final publication is available at Springer via http://dx.doi.org/10.1007/s11356-017-8823-