The commissioning data indicated good consistency among the three TB-LINAC units. The commissioning data provided us valuable insights and reliable evaluations on the characteristics of the new treatment system. The systematically measured data might be useful for future reference.

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A Bayesian method is presented for simultaneously segmenting and reconstructing emission computed tomography (ECT) images and for incorporating high-resolution, anatomical information into those reconstructions. The anatomical information is often available from other imaging modalities such as computed tomography (CT) or magnetic resonance imaging (MRI). The Bayesian procedure models the ECT radiopharmaceutical distribution as consisting of regions, such that radiopharmaceutical activity is similar throughout each region. It estimates the number of regions, the mean activity of each region, and the region classification and mean activity of each voxel. Anatomical information is incorporated by assigning higher prior probabilities to ECT segmentations in which each ECT region stays within a single anatomical region. This approach is effective because anatomical tissue type often strongly influences radiopharmaceutical uptake. The Bayesian procedure is evaluated using physically acquired single-photon emission computed tomography (SPECT) projection data and MRI for the three-dimensional (3-D) Hoffman brain phantom. A clinically realistic count level is used. A cold lesion within the brain phantom is created during the SPECT scan but not during the MRI to demonstrate that the estimation procedure can detect ECT structure that is not present anatomically.

A compact, dedicated cadmium zinc telluride (CZT) gamma camera coupled with a fully three-dimensional (3-D) acquisition system may serve as a secondary diagnostic tool for volumetric molecular imaging of breast cancers, particularly in cases when mammographic findings are inconclusive. The developed emission mammotomography system comprises a medium field-of-view, quantized CZT detector and 3-D positioning gantry. The intrinsic energy resolution, sensitivity and spatial resolution of the detector are evaluated with Tc-99m (140 keV) filled flood sources, capillary line sources, and a 3-D frequency-resolution phantom. To mimic realistic human pendant, uncompressed breast imaging, two different phantom shapes of an average sized breast, and three different lesion diameters are imaged to evaluate the system for 3-D mammotomography. Acquisition orbits not possible with conventional emission, or transmission, systems are designed to optimize the viewable breast volume while improving sampling of the breast and anterior chest wall. Complications in camera positioning about the patient necessitate a compromise in these two orbit design criteria. Image quality is evaluated with signal-to-noise ratios and contrasts of the lesions, both with and without additional torso phantom background. Reconstructed results indicate that 3-D mammotomography, incorporating a compact CZT detector, is a promising, dedicated breast imaging technique for visualization of tumors < 1 cm in diameter. Additionally, there are no outstanding trajectories that consistently yield optimized quantitative lesion imaging parameters. Qualitatively, imaging breasts with realistic torso backgrounds (out-of-field activity) substantially alters image characteristics and breast morphology unless orbits which improve sampling are utilized. In practice, the sampling requirement may be less strict than initially anticipated.

In recent years, many investigators have proposed Gibbs prior models to regularize images reconstructed from emission computed tomography data. Unfortunately, hyperparameters used to specify Gibbs priors can greatly influence the degree of regularity imposed by such priors and, as a result, numerous procedures have been proposed to estimate hyperparameter values from observed image data. Many of these procedures attempt to maximize the joint posterior distribution on the image scene. To implement these methods, approximations to the joint posterior densities are required, because the dependence of the Gibbs partition function on the hyperparameter values is unknown. In this paper, we use recent results in Markov chain Monte Carlo (MCMC) sampling to estimate the relative values of Gibbs partition functions and using these values, sample from joint posterior distributions on image scenes. This allows for a fully Bayesian procedure which does not fix the hyperparameters at some estimated or specified value, but enables uncertainty about these values to be propagated through to the estimated intensities. We utilize realizations from the posterior distribution for determining credible regions for the intensity of the emission source. We consider two different Markov random field (MRF) models-the power model and a line-site model. As applications we estimate the posterior distribution of source intensities from computer simulated data as well as data collected from a physical single photon emission computed tomography (SPECT) phantom.

Cell therapies are potential alternatives to organ transplantation for liver failure or dysfunction but are compromised by inefficient engraftment, cell dispersal to ectopic sites, and emboli formation. Grafting strategies have been devised for transplantation of human hepatic stem cells (hHpSCs) embedded into a mix of soluble signals and extracellular matrix biomaterials (hyaluronans, type III collagen, laminin) found in stem cell niches. The hHpSCs maintain a stable stem cell phenotype under the graft conditions. The grafts were transplanted into the livers of immuno-compromised murine hosts with and without carbon tetrachloride treatment to assess the effects of quiescent versus injured liver conditions. Grafted cells remained localized to the livers resulting in a larger bolus of engrafted cells in the host livers under quiescent conditions and with potential for more rapid expansion under injured liver conditions. By contrast, transplantation by direct injection or via a vascular route resulted in inefficient engraftment and cell dispersal to ectopic sites. Transplantation by grafting is proposed as a preferred strategy for cell therapies for solid organs such as liver.

Dual-energy CBCT imaging techniques were implemented to synthesize VM CBCT and LM CBCTs. VM CBCT was effective at achieving metal artifact reduction. Depending on the dose-partitioning scheme, LM CBCT demonstrated the potential to improve CNR for low contrast objects compared to single-energy CBCT acquired with equivalent dose.

The primary goal of this work has been to develop a processing method for gated cardiac emission computed tomography (ECT) that simultaneously reconstructs the pixel intensities of the gated images and estimates the motion of the cardiac wall. The simultaneous reconstruction and motion estimation is achieved using conjugate gradient optimization with an objective function that is dependent on the gated reconstructed images at two time frames and the estimated motion of the object between the two frames. The method was evaluated on simulated phantom data both with and without Poisson noise. With noise-free data, the accuracy of the motion estimate and the quality of the reconstructed images were found to be dependent on the hyperparameter selection. With noisy data, the simultaneous method produced reconstructed images with smaller squared error compared with images reconstructed without motion estimation. In a patient gated myocardial perfusion study, the estimated motion between two frames agreed with subjective assessment of wall motion.