A 3-D CT assisted Monte Carlo evaluation of intracavitary brachytherapy implants

Intracavitary brachytherapy (ICB) combined with external beam irradiation for treatment of cervical cancer is highly successful in achieving local control. The M.D. Anderson Cancer Center employs Fletcher Suit Delclos (FSD) applicators. FSD applicators contain shields to limit dose to critical structures. Dosimetric evaluation of ICB implants is limited to assessing dose at reference points. These points serve as surrogates for treatment intensity and critical structure dose. Several studies have mentioned that the ICRU38 reference points inadequately characterize the dose distribution. Also, the ovoid shields are rarely considered in dosimetry. ^ The goal of this dissertation was to ascertain the influence of the ovoid shields on patient dose distributions. Monte Carlo dosimetry (MCD) was applied to patient computed tomography(CT) scans. These data were analyzed to determine the effect of the shields on dose to standard reference points and the bladder and rectum. The hypothesis of this work is that the ICRU38 bladder and rectal points computed conventionally are not clinically acceptable surrogates for the maximum dose points as determined by MCD. ^ MCD was applied to the tandem and ovoids. The FSD ovoids and tandem were modeled in a single input file that allowed dose to be calculated for any patient. Dose difference surface histograms(DDSH) were computed for the bladder and rectum. Reference point doses were compared between shielded and unshielded ovoids, and a commercial treatment planning system. ^ The results of this work showed the tandem tip screw caused a 33% reduction in dose. The ovoid shields reduced the dose by a maximum of 48.9%. DDSHs revealed on average 5% of the bladder surface area was spared 53 cGy and 5% of the rectal surface area was spared 195 cGy. The ovoid shields on average reduced the dose by 18% for the bladder point and 25% for the rectal point. The Student's t-test revealed the ICRU38 bladder and rectal points do not predict the maximum dose for these organs. ^ It is concluded that modeling the tandem and ovoid internal structures is necessary for accurate dose calculations, the bladder shielding segments may not be necessary, and that the ICRU38 bladder point is irrelevant. ^

Structural studies of proteinase entrapment by human alpha 2-macroglobulin using 3-D electron microscopy

Human a2 -macroglobulin ( a2 M; homotetramer, Mr 720 kDa) is an essential scavenger of proteinases in the serum. Each of its four subunits has a ‘bait region’, with cleavage sequences for almost all endo-proteinases, an unusual thiol ester moiety and a receptor-binding domain (RBD). Bait region cleavage in native a2 M ( a2 M-N) by a proteinase results in rapid thiol ester breakage, with a large-scale structural transformation, in which a2 M uniquely entraps the proteinase in a cage-like structure and exposes receptor-binding domains for rapid endocytosis. Transformed a2 M ( a2 M-TR) contains up to two proteinases, which remain active to small substrates. 3-D electron microscopy is optimally suited to study this unusual structural change at resolutions near (1/30) Å−1. ^ The structural importance of the thiol esters was demonstrated by a genetically-engineered a2 M, with the cysteines involved in thiol ester formation mutated to serines, which appeared structurally homologous to a2 M-TR. This demonstrates that the four highly labile thiol esters alone maintain the a2 M-N structure, while the ‘closed trap’ formed by a2 M-TR is a more stable structural form. ^ Half-transformed a2 M ( a2 M-HT), with cleaved bait regions and thiol esters in only two of its four subunits, provides an important structural link between a2 M-N and a2 M-TR. A comparison with a2 M-N showed the two proteinase-entrapping domains were above and below the plane bisecting the long axis. Both a2 M-N and a2 M-TR consist of two dense, oppositely twisted strands with significant interconnections, indicating that the structural change involves a rotation of these strands. In a2 M-HT these strands were partially untwisted with large central openings, revealing the manner in which the proteinase enters the internal cavity of a2 M. ^ In reconstructions of a2 M-N, a2 M-HT and a2 M-TR labeled with a monoclonal Fab, the Fabs were located on distal ends of each constitutive strand, demonstrating an anti-parallel arrangement of the subunits. Separation between the top and bottom pairs of Fabs was nearly the same on all structures, but the pairs were rotated about the long axis. Taken together, these results indicate that upon proteinase cleavage the two strands in a2 M-N separate. The proteinase enters the structure, while the strands re-twist to encage it. In a2 M-TR, which displays receptor-binding arms, more than two subunits are transformed as strands in the transformed half of a2 M-HT were not separated. ^

BAYESIAN STATISTICAL METHODS IN GENE-ENVIRONMENT AND GENE-GENE INTERACTION STUDIES

Complex diseases such as cancer result from multiple genetic changes and environmental exposures. Due to the rapid development of genotyping and sequencing technologies, we are now able to more accurately assess causal effects of many genetic and environmental factors. Genome-wide association studies have been able to localize many causal genetic variants predisposing to certain diseases. However, these studies only explain a small portion of variations in the heritability of diseases. More advanced statistical models are urgently needed to identify and characterize some additional genetic and environmental factors and their interactions, which will enable us to better understand the causes of complex diseases. In the past decade, thanks to the increasing computational capabilities and novel statistical developments, Bayesian methods have been widely applied in the genetics/genomics researches and demonstrating superiority over some regular approaches in certain research areas. Gene-environment and gene-gene interaction studies are among the areas where Bayesian methods may fully exert its functionalities and advantages. This dissertation focuses on developing new Bayesian statistical methods for data analysis with complex gene-environment and gene-gene interactions, as well as extending some existing methods for gene-environment interactions to other related areas. It includes three sections: (1) Deriving the Bayesian variable selection framework for the hierarchical gene-environment and gene-gene interactions; (2) Developing the Bayesian Natural and Orthogonal Interaction (NOIA) models for gene-environment interactions; and (3) extending the applications of two Bayesian statistical methods which were developed for gene-environment interaction studies, to other related types of studies such as adaptive borrowing historical data. We propose a Bayesian hierarchical mixture model framework that allows us to investigate the genetic and environmental effects, gene by gene interactions (epistasis) and gene by environment interactions in the same model. It is well known that, in many practical situations, there exists a natural hierarchical structure between the main effects and interactions in the linear model. Here we propose a model that incorporates this hierarchical structure into the Bayesian mixture model, such that the irrelevant interaction effects can be removed more efficiently, resulting in more robust, parsimonious and powerful models. We evaluate both of the 'strong hierarchical' and 'weak hierarchical' models, which specify that both or one of the main effects between interacting factors must be present for the interactions to be included in the model. The extensive simulation results show that the proposed strong and weak hierarchical mixture models control the proportion of false positive discoveries and yield a powerful approach to identify the predisposing main effects and interactions in the studies with complex gene-environment and gene-gene interactions. We also compare these two models with the 'independent' model that does not impose this hierarchical constraint and observe their superior performances in most of the considered situations. The proposed models are implemented in the real data analysis of gene and environment interactions in the cases of lung cancer and cutaneous melanoma case-control studies. The Bayesian statistical models enjoy the properties of being allowed to incorporate useful prior information in the modeling process. Moreover, the Bayesian mixture model outperforms the multivariate logistic model in terms of the performances on the parameter estimation and variable selection in most cases. Our proposed models hold the hierarchical constraints, that further improve the Bayesian mixture model by reducing the proportion of false positive findings among the identified interactions and successfully identifying the reported associations. This is practically appealing for the study of investigating the causal factors from a moderate number of candidate genetic and environmental factors along with a relatively large number of interactions. The natural and orthogonal interaction (NOIA) models of genetic effects have previously been developed to provide an analysis framework, by which the estimates of effects for a quantitative trait are statistically orthogonal regardless of the existence of Hardy-Weinberg Equilibrium (HWE) within loci. Ma et al. (2012) recently developed a NOIA model for the gene-environment interaction studies and have shown the advantages of using the model for detecting the true main effects and interactions, compared with the usual functional model. In this project, we propose a novel Bayesian statistical model that combines the Bayesian hierarchical mixture model with the NOIA statistical model and the usual functional model. The proposed Bayesian NOIA model demonstrates more power at detecting the non-null effects with higher marginal posterior probabilities. Also, we review two Bayesian statistical models (Bayesian empirical shrinkage-type estimator and Bayesian model averaging), which were developed for the gene-environment interaction studies. Inspired by these Bayesian models, we develop two novel statistical methods that are able to handle the related problems such as borrowing data from historical studies. The proposed methods are analogous to the methods for the gene-environment interactions on behalf of the success on balancing the statistical efficiency and bias in a unified model. By extensive simulation studies, we compare the operating characteristics of the proposed models with the existing models including the hierarchical meta-analysis model. The results show that the proposed approaches adaptively borrow the historical data in a data-driven way. These novel models may have a broad range of statistical applications in both of genetic/genomic and clinical studies.

Intact flagellar motor of Borrelia burgdorferi revealed by cryo-electron tomography: evidence for stator ring curvature and rotor/C-ring assembly flexion.

The bacterial flagellar motor is a remarkable nanomachine that provides motility through flagellar rotation. Prior structural studies have revealed the stunning complexity of the purified rotor and C-ring assemblies from flagellar motors. In this study, we used high-throughput cryo-electron tomography and image analysis of intact Borrelia burgdorferi to produce a three-dimensional (3-D) model of the in situ flagellar motor without imposing rotational symmetry. Structural details of B. burgdorferi, including a layer of outer surface proteins, were clearly visible in the resulting 3-D reconstructions. By averaging the 3-D images of approximately 1,280 flagellar motors, a approximately 3.5-nm-resolution model of the stator and rotor structures was obtained. flgI transposon mutants lacked a torus-shaped structure attached to the flagellar rod, establishing the structural location of the spirochetal P ring. Treatment of intact organisms with the nonionic detergent NP-40 resulted in dissolution of the outermost portion of the motor structure and the C ring, providing insight into the in situ arrangement of the stator and rotor structures. Structural elements associated with the stator followed the curvature of the cytoplasmic membrane. The rotor and the C ring also exhibited angular flexion, resulting in a slight narrowing of both structures in the direction perpendicular to the cell axis. These results indicate an inherent flexibility in the rotor-stator interaction. The FliG switching and energizing component likely provides much of the flexibility needed to maintain the interaction between the curved stator and the relatively symmetrical rotor/C-ring assembly during flagellar rotation.

Chronic spontaneous activity generated in the somata of primary nociceptors is associated with pain-related behavior after spinal cord injury.

Mechanisms underlying chronic pain that develops after spinal cord injury (SCI) are incompletely understood. Most research on SCI pain mechanisms has focused on neuronal alterations within pain pathways at spinal and supraspinal levels associated with inflammation and glial activation. These events might also impact central processes of primary sensory neurons, triggering in nociceptors a hyperexcitable state and spontaneous activity (SA) that drive behavioral hypersensitivity and pain. SCI can sensitize peripheral fibers of nociceptors and promote peripheral SA, but whether these effects are driven by extrinsic alterations in surrounding tissue or are intrinsic to the nociceptor, and whether similar SA occurs in nociceptors in vivo are unknown. We show that small DRG neurons from rats (Rattus norvegicus) receiving thoracic spinal injury 3 d to 8 months earlier and recorded 1 d after dissociation exhibit an elevated incidence of SA coupled with soma hyperexcitability compared with untreated and sham-treated groups. SA incidence was greatest in lumbar DRG neurons (57%) and least in cervical neurons (28%), and failed to decline over 8 months. Many sampled SA neurons were capsaicin sensitive and/or bound the nociceptive marker, isolectin B4. This intrinsic SA state was correlated with increased behavioral responsiveness to mechanical and thermal stimulation of sites below and above the injury level. Recordings from C- and Aδ-fibers revealed SCI-induced SA generated in or near the somata of the neurons in vivo. SCI promotes the entry of primary nociceptors into a chronic hyperexcitable-SA state that may provide a useful therapeutic target in some forms of persistent pain.

Development of a SPECT -based three-dimensional treatment planner for radionuclide therapy with iodine -131

Accurate calculation of absorbed dose to target tumors and normal tissues in the body is an important requirement for establishing fundamental dose-response relationships for radioimmunotherapy. Two major obstacles have been the difficulty in obtaining an accurate patient-specific 3-D activity map in-vivo and calculating the resulting absorbed dose. This study investigated a methodology for 3-D internal dosimetry, which integrates the 3-D biodistribution of the radionuclide acquired from SPECT with a dose-point kernel convolution technique to provide the 3-D distribution of absorbed dose. Accurate SPECT images were reconstructed with appropriate methods for noise filtering, attenuation correction, and Compton scatter correction. The SPECT images were converted into activity maps using a calibration phantom. The activity map was convolved with an $\sp{131}$I dose-point kernel using a 3-D fast Fourier transform to yield a 3-D distribution of absorbed dose. The 3-D absorbed dose map was then processed to provide the absorbed dose distribution in regions of interest. This methodology can provide heterogeneous distributions of absorbed dose in volumes of any size and shape with nonuniform distributions of activity. Comparison of the activities quantitated by our SPECT methodology to true activities in an Alderson abdominal phantom (with spleen, liver, and spherical tumor) yielded errors of $-$16.3% to 4.4%. Volume quantitation errors ranged from $-$4.0 to 5.9% for volumes greater than 88 ml. The percentage differences of the average absorbed dose rates calculated by this methodology and the MIRD S-values were 9.1% for liver, 13.7% for spleen, and 0.9% for the tumor. Good agreement (percent differences were less than 8%) was found between the absorbed dose due to penetrating radiation calculated from this methodology and TLD measurement. More accurate estimates of the 3-D distribution of absorbed dose can be used as a guide in specifying the minimum activity to be administered to patients to deliver a prescribed absorbed dose to tumor without exceeding the toxicity limits of normal tissues. ^