DUAL ENERGY COMPUTED TOMOGRAPHY FOR PROTON THERAPY TREATMENT PLANNING

Proton radiation therapy is gaining popularity because of the unique characteristics of its dose distribution, e.g., high dose-gradient at the distal end of the percentage-depth-dose curve (known as the Bragg peak). The high dose-gradient offers the possibility of delivering high dose to the target while still sparing critical organs distal to the target. However, the high dose-gradient is a double-edged sword: a small shift of the highly conformal high-dose area can cause the target to be substantially under-dosed or the critical organs to be substantially over-dosed. Because of that, large margins are required in treatment planning to ensure adequate dose coverage of the target, which prevents us from realizing the full potential of proton beams. Therefore, it is critical to reduce uncertainties in the proton radiation therapy. One major uncertainty in a proton treatment is the range uncertainty related to the estimation of proton stopping power ratio (SPR) distribution inside a patient. The SPR distribution inside a patient is required to account for tissue heterogeneities when calculating dose distribution inside the patient. In current clinical practice, the SPR distribution inside a patient is estimated from the patient’s treatment planning computed tomography (CT) images based on the CT number-to-SPR calibration curve. The SPR derived from a single CT number carries large uncertainties in the presence of human tissue composition variations, which is the major drawback of the current SPR estimation method. We propose to solve this problem by using dual energy CT (DECT) and hypothesize that the range uncertainty can be reduced by a factor of two from currently used value of 3.5%. A MATLAB program was developed to calculate the electron density ratio (EDR) and effective atomic number (EAN) from two CT measurements of the same object. An empirical relationship was discovered between mean excitation energies and EANs existing in human body tissues. With the MATLAB program and the empirical relationship, a DECT-based method was successfully developed to derive SPRs for human body tissues (the DECT method). The DECT method is more robust against the uncertainties in human tissues compositions than the current single-CT-based method, because the DECT method incorporated both density and elemental composition information in the SPR estimation. Furthermore, we studied practical limitations of the DECT method. We found that the accuracy of the DECT method using conventional kV-kV x-ray pair is susceptible to CT number variations, which compromises the theoretical advantage of the DECT method. Our solution to this problem is to use a different x-ray pair for the DECT. The accuracy of the DECT method using different combinations of x-ray energies, i.e., the kV-kV, kV-MV and MV-MV pair, was compared using the measured imaging uncertainties for each case. The kV-MV DECT was found to be the most robust against CT number variations. In addition, we studied how uncertainties propagate through the DECT calculation, and found general principles of selecting x-ray pairs for the DECT method to minimize its sensitivity to CT number variations. The uncertainties in SPRs estimated using the kV-MV DECT were analyzed further and compared to those using the stoichiometric method. The uncertainties in SPR estimation can be divided into five categories according to their origins: the inherent uncertainty, the DECT modeling uncertainty, the CT imaging uncertainty, the uncertainty in the mean excitation energy, and SPR variation with proton energy. Additionally, human body tissues were divided into three tissue groups – low density (lung) tissues, soft tissues and bone tissues. The uncertainties were estimated separately because their uncertainties were different under each condition. An estimate of the composite range uncertainty (2s) was determined for three tumor sites – prostate, lung, and head-and-neck, by combining the uncertainty estimates of all three tissue groups, weighted by their proportions along typical beam path for each treatment site. In conclusion, the DECT method holds theoretical advantages in estimating SPRs for human tissues over the current single-CT-based method. Using existing imaging techniques, the kV-MV DECT approach was capable of reducing the range uncertainty from the currently used value of 3.5% to 1.9%-2.3%, but it is short to reach our original goal of reducing the range uncertainty by a factor of two. The dominant source of uncertainties in the kV-MV DECT was the uncertainties in CT imaging, especially in MV CT imaging. Further reduction in beam hardening effect, the impact of scatter, out-of-field object etc. would reduce the Hounsfeld Unit variations in CT imaging. The kV-MV DECT still has the potential to reduce the range uncertainty further.

The contributions of the hippocampal formation, perirhinal cortex and areas TH/TF to object, spatial and contextual recognition memory in primates

Adult monkeys (Macaca mulatta) with lesions of the hippocampal formation, perirhinal cortex, areas TH/TF, as well as controls were tested on tasks of object, spatial and contextual recognition memory. ^ Using a visual paired-comparison (VPC) task, all experimental groups showed a lack of object recognition relative to controls, although this impairment emerged at 10 sec with perirhinal lesions, 30 sec with areas TH/TF lesions and 60 sec with hippocampal lesions. In contrast, only perirhinal lesions impaired performance on delayed nonmatching-to-sample (DNMS), another task of object recognition memory. All groups were tested on DNMS with distraction (dDNMS) to examine whether the use of active cognitive strategies during the delay period could enable good performance on DNMS in spite of impaired recognition memory (revealed by the VPC task). Distractors affected performance of animals with perirhinal lesions at the 10-sec delay (the only delay in which their DNMS performance was above chance). They did not affect performance of animals with areas TH/TF lesions. Hippocampectomized animals were impaired at the 600-sec delay (the only delay at which prevention of active strategies would likely affect their behavior). ^ While lesions of areas TH/TF impaired spatial location memory and object-in-place memory, hippocampal lesions impaired only object-in-place memory. The pattern of results for perirhinal cortex lesions on the different task conditions indicated that this cortical area is not critical for spatial memory. ^ Finally, all three lesions impaired contextual recognition memory processes. The pattern of impairment appeared to result from the formation of only a global representation of the object and background, and suggests that all three areas are recruited for associating information across sources. ^ These results support the view that (1) the perirhinal cortex maintains storage of information about object and the context in which it is learned for a brief period of time, (2) areas TH/TF maintain information about spatial location and form associations between objects and their spatial relationship (a process that likely requires additional time) and (3) the hippocampal formation mediates associations between objects, their spatial relationship and the general context in which these associations are formed (an integrative function that requires additional time). ^

Spatial modulation of primate inferotemporal responses by eye position.

BACKGROUND: A key aspect of representations for object recognition and scene analysis in the ventral visual stream is the spatial frame of reference, be it a viewer-centered, object-centered, or scene-based coordinate system. Coordinate transforms from retinocentric space to other reference frames involve combining neural visual responses with extraretinal postural information. METHODOLOGY/PRINCIPAL FINDINGS: We examined whether such spatial information is available to anterior inferotemporal (AIT) neurons in the macaque monkey by measuring the effect of eye position on responses to a set of simple 2D shapes. We report, for the first time, a significant eye position effect in over 40% of recorded neurons with small gaze angle shifts from central fixation. Although eye position modulates responses, it does not change shape selectivity. CONCLUSIONS/SIGNIFICANCE: These data demonstrate that spatial information is available in AIT for the representation of objects and scenes within a non-retinocentric frame of reference. More generally, the availability of spatial information in AIT calls into questions the classic dichotomy in visual processing that associates object shape processing with ventral structures such as AIT but places spatial processing in a separate anatomical stream projecting to dorsal structures.

Thoracic radiotherapy treatment planning with cine PET/CT

Purpose: Respiratory motion causes substantial uncertainty in radiotherapy treatment planning. Four-dimensional computed tomography (4D-CT) is a useful tool to image tumor motion during normal respiration. Treatment margins can be reduced by targeting the motion path of the tumor. The expense and complexity of 4D-CT, however, may be cost-prohibitive at some facilities. We developed an image processing technique to produce images from cine CT that contain significant motion information without 4D-CT. The purpose of this work was to compare cine CT and 4D-CT for the purposes of target delineation and dose calculation, and to explore the role of PET in target delineation of lung cancer. Methods: To determine whether cine CT could substitute 4D-CT for small mobile lung tumors, we compared target volumes delineated by a physician on cine CT and 4D-CT for 27 tumors with intrafractional motion greater than 1 cm. We assessed dose calculation by comparing dose distributions calculated on respiratory-averaged cine CT and respiratory-averaged 4D-CT using the gamma index. A threshold-based PET segmentation model of size, motion, and source-to-background was developed from phantom scans and validated with 24 lung tumors. Finally, feasibility of integrating cine CT and PET for contouring was assessed on a small group of larger tumors. Results: Cine CT to 4D-CT target volume ratios were (1.05±0.14) and (0.97±0.13) for high-contrast and low-contrast tumors respectively which was within intraobserver variation. Dose distributions on cine CT produced good agreement (< 2%/1 mm) with 4D-CT for 71 of 73 patients. The segmentation model fit the phantom data with R2 = 0.96 and produced PET target volumes that matched CT better than 6 published methods (-5.15%). Application of the model to more complex tumors produced mixed results and further research is necessary to adequately integrate PET and cine CT for delineation. Conclusions: Cine CT can be used for target delineation of small mobile lesions with minimal differences to 4D-CT. PET, utilizing the segmentation model, can provide additional contrast. Additional research is required to assess the efficacy of complex tumor delineation with cine CT and PET. Respiratory-averaged cine CT can substitute respiratory-averaged 4D-CT for dose calculation with negligible differences.

Tracking the Flow of Information through the Hippocampal Formation in the Rat

The hippocampus receives input from upper levels of the association cortex and is implicated in many mnemonic processes, but the exact mechanisms by which it codes and stores information is an unresolved topic. This work examines the flow of information through the hippocampal formation while attempting to determine the computations that each of the hippocampal subfields performs in learning and memory. The formation, storage, and recall of hippocampal-dependent memories theoretically utilize an autoassociative attractor network that functions by implementing two competitive, yet complementary, processes. Pattern separation, hypothesized to occur in the dentate gyrus (DG), refers to the ability to decrease the similarity among incoming information by producing output patterns that overlap less than the inputs. In contrast, pattern completion, hypothesized to occur in the CA3 region, refers to the ability to reproduce a previously stored output pattern from a partial or degraded input pattern. Prior to addressing the functional role of the DG and CA3 subfields, the spatial firing properties of neurons in the dentate gyrus were examined. The principal cell of the dentate gyrus, the granule cell, has spatially selective place fields; however, the behavioral correlates of another excitatory cell, the mossy cell of the dentate polymorphic layer, are unknown. This report shows that putative mossy cells have spatially selective firing that consists of multiple fields similar to previously reported properties of granule cells. Other cells recorded from the DG had single place fields. Compared to cells with multiple fields, cells with single fields fired at a lower rate during sleep, were less likely to burst, and were more likely to be recorded simultaneously with a large population of neurons that were active during sleep and silent during behavior. These data suggest that single-field and multiple-field cells constitute at least two distinct cell classes in the DG. Based on these characteristics, we propose that putative mossy cells tend to fire in multiple, distinct locations in an environment, whereas putative granule cells tend to fire in single locations, similar to place fields of the CA1 and CA3 regions. Experimental evidence supporting the theories of pattern separation and pattern completion comes from both behavioral and electrophysiological tests. These studies specifically focused on the function of each subregion and made implicit assumptions about how environmental manipulations changed the representations encoded by the hippocampal inputs. However, the cell populations that provided these inputs were in most cases not directly examined. We conducted a series of studies to investigate the neural activity in the entorhinal cortex, dentate gyrus, and CA3 in the same experimental conditions, which allowed a direct comparison between the input and output representations. The results show that the dentate gyrus representation changes between the familiar and cue altered environments more than its input representations, whereas the CA3 representation changes less than its input representations. These findings are consistent with longstanding computational models proposing that (1) CA3 is an associative memory system performing pattern completion in order to recall previous memories from partial inputs, and (2) the dentate gyrus performs pattern separation to help store different memories in ways that reduce interference when the memories are subsequently recalled.

Evaluation of deformable image registration for improved 4D CT-derived ventilation for image guided radiotherapy

Recent treatment planning studies have demonstrated the use of physiologic images in radiation therapy treatment planning to identify regions for functional avoidance. This image-guided radiotherapy (IGRT) strategy may reduce the injury and/or functional loss following thoracic radiotherapy. 4D computed tomography (CT), developed for radiotherapy treatment planning, is a relatively new imaging technique that allows the acquisition of a time-varying sequence of 3D CT images of the patient's lungs through the respiratory cycle. Guerrero et al. developed a method to calculate ventilation imaging from 4D CT, which is potentially better suited and more broadly available for IGRT than the current standard imaging methods. The key to extracting function information from 4D CT is the construction of a volumetric deformation field that accurately tracks the motion of the patient's lungs during the respiratory cycle. The spatial accuracy of the displacement field directly impacts the ventilation images; higher spatial registration accuracy will result in less ventilation image artifacts and physiologic inaccuracies. Presently, a consistent methodology for spatial accuracy evaluation of the DIR transformation is lacking. Evaluation of the 4D CT-derived ventilation images will be performed to assess correlation with global measurements of lung ventilation, as well as regional correlation of the distribution of ventilation with the current clinical standard SPECT. This requires a novel framework for both the detailed assessment of an image registration algorithm's performance characteristics as well as quality assurance for spatial accuracy assessment in routine application. Finally, we hypothesize that hypo-ventilated regions, identified on 4D CT ventilation images, will correlate with hypo-perfused regions in lung cancer patients who have obstructive lesions. A prospective imaging trial of patients with locally advanced non-small-cell lung cancer will allow this hypothesis to be tested. These advances are intended to contribute to the validation and clinical implementation of CT-based ventilation imaging in prospective clinical trials, in which the impact of this imaging method on patient outcomes may be tested.

The Dissociation of Location and Object Working Memory using fMRI and MEG

Visual working memory (VWM) involves maintaining and processing visual information, often for the purpose of making immediate decisions. Neuroimaging experiments of VWM provide evidence in support of a neural system mainly involving a fronto-parietal neuronal network, but the role of specific brain areas is less clear. A proposal that has recently generated considerable debate suggests that a dissociation of object and location VWM occurs within the prefrontal cortex, in dorsal and ventral regions, respectively. However, re-examination of the relevant literature presents a more robust distribution suggestive of a general caudal-rostral dissociation from occipital and parietal structures, caudally, to prefrontal regions, rostrally, corresponding to location and object memory, respectively. The purpose of the present study was to identify a dissociation of location and object VWM across two imaging methods (magnetoencephalography, MEG, and functional magnetic imaging, fMRI). These two techniques provide complimentary results due the high temporal resolution of MEG and the high spatial resolution of fMRI. The use of identical location and object change detection tasks was employed across techniques and reported for the first time. Moreover, this study is the first to use matched stimulus displays across location and object VWM conditions. The results from these two imaging methods provided convergent evidence of a location and object VWM dissociation favoring a general caudal-rostral rather than the more common prefrontal dorsal-ventral view. Moreover, neural activity across techniques was correlated with behavioral performance for the first time and provided convergent results. This novel approach of combining imaging tools to study memory resulted in robust evidence suggesting a novel interpretation of location and object memory. Accordingly, this study presents a novel context within which to explore the neural substrates of WM across imaging techniques and populations.

Structural equation modeling of the medical outcome study: Short Form 36 (SF-36)

The factorial validity of the SF-36 was evaluated using confirmatory factor analysis (CFA) methods, structural equation modeling (SEM), and multigroup structural equation modeling (MSEM). First, the measurement and structural model of the hypothesized SF-36 was explicated. Second, the model was tested for the validity of a second-order factorial structure, upon evidence of model misfit, determined the best-fitting model, and tested the validity of the best-fitting model on a second random sample from the same population. Third, the best-fitting model was tested for invariance of the factorial structure across race, age, and educational subgroups using MSEM.^ The findings support the second-order factorial structure of the SF-36 as proposed by Ware and Sherbourne (1992). However, the results suggest that: (a) Mental Health and Physical Health covary; (b) general mental health cross-loads onto Physical Health; (c) general health perception loads onto Mental Health instead of Physical Health; (d) many of the error terms are correlated; and (e) the physical function scale is not reliable across these two samples. This hierarchical factor pattern was replicated across both samples of health care workers, suggesting that the post hoc model fitting was not data specific. Subgroup analysis suggests that the physical function scale is not reliable across the "age" or "education" subgroups and that the general mental health scale path from Mental Health is not reliable across the "white/nonwhite" or "education" subgroups.^ The importance of this study is in the use of SEM and MSEM in evaluating sample data from the use of the SF-36. These methods are uniquely suited to the analysis of latent variable structures and are widely used in other fields. The use of latent variable models for self reported outcome measures has become widespread, and should now be applied to medical outcomes research. Invariance testing is superior to mean scores or summary scores when evaluating differences between groups. From a practical, as well as, psychometric perspective, it seems imperative that construct validity research related to the SF-36 establish whether this same hierarchical structure and invariance holds for other populations.^ This project is presented as three articles to be submitted for publication. ^

A novel treatment planning methodology for high dose 166Ho-DOTMP therapy in patients with multiple myeloma

Bone marrow ablation, i.e., the complete sterilization of the active bone marrow, followed by bone marrow transplantation (BMT) is a comment treatment of hematological malignancies. The use of targeted bone-seeking radiopharmaceuticals to selectively deliver radiation to the adjacent bone marrow cavities while sparing normal tissues is a promising technique. Current radiopharmaceutical treatment planning methods do not properly compensate for the patient-specific variable distribution of radioactive material within the skeleton. To improve the current method of internal dosimetry, novel methods for measuring the radiopharmaceutical distribution within the skeleton were developed. 99mTc-MDP was proven as an adequate surrogate for measuring 166Ho-DOTMP skeletal uptake and biodistribution, allowing these measures to be obtained faster, safer, and with higher spatial resolution. This translates directly into better measurements of the radiation dose distribution within the bone marrow. The resulting bone marrow dose-volume histograms allow prediction of the patient disease response where conventional organ scale dosimetry failed. They indicate that complete remission is only achieved when greater than 90% of the bone marrow receives at least 30 Gy. ^ Comprehensive treatment planning requires combining target and non-target organ dosimetry. Organs in the urinary tract were of special concern. The kidney dose is primarily dependent upon the mean transit time of 166 Ho-DOTMP through the kidney. Deconvolution analysis of renograms predicted a mean transit time of 2.6 minutes for 166Ho-DOTMP. The radiation dose to the urinary bladder wall is dependent upon numerous factors including patient hydration and void schedule. For beta-emitting isotopes such as 166Ho, reduction of the bladder wall dose is best accomplished through good patient hydration and ensuring a partially full bladder at the time of injection. Encouraging the patient to void frequently, or catheterizing the patient without irrigation, will not significantly reduce the bladder wall dose. ^ The results from this work will produce the most advanced treatment planning methodology for bone marrow ablation therapy using radioisotopes currently available. Treatments can be tailored specifically for each patient, including the addition of concomitant total body irradiation for patients with unfavorable dose distributions, to deliver a desired patient disease response, while minimizing the dose or toxicity to non-target organs. ^

A coalescent analysis for modeling the mutation process in colorectal cancer

Colorectal cancer is the forth most common diagnosed cancer in the United States. Every year about a hundred forty-seven thousand people will be diagnosed with colorectal cancer and fifty-six thousand people lose their lives due to this disease. Most of the hereditary nonpolyposis colorectal cancer (HNPCC) and 12% of the sporadic colorectal cancer show microsatellite instability. Colorectal cancer is a multistep progressive disease. It starts from a mutation in a normal colorectal cell and grows into a clone of cells that further accumulates mutations and finally develops into a malignant tumor. In terms of molecular evolution, the process of colorectal tumor progression represents the acquisition of sequential mutations. ^ Clinical studies use biomarkers such as microsatellite or single nucleotide polymorphisms (SNPs) to study mutation frequencies in colorectal cancer. Microsatellite data obtained from single genome equivalent PCR or small pool PCR can be used to infer tumor progression. Since tumor progression is similar to population evolution, we used an approach known as coalescent, which is well established in population genetics, to analyze this type of data. Coalescent theory has been known to infer the sample's evolutionary path through the analysis of microsatellite data. ^ The simulation results indicate that the constant population size pattern and the rapid tumor growth pattern have different genetic polymorphic patterns. The simulation results were compared with experimental data collected from HNPCC patients. The preliminary result shows the mutation rate in 6 HNPCC patients range from 0.001 to 0.01. The patients' polymorphic patterns are similar to the constant population size pattern which implies the tumor progression is through multilineage persistence instead of clonal sequential evolution. The results should be further verified using a larger dataset. ^

Design and Optimization of Four-dimensional Cone-beam Computed Tomography in Image-guided Radiation Therapy

The influence of respiratory motion on patient anatomy poses a challenge to accurate radiation therapy, especially in lung cancer treatment. Modern radiation therapy planning uses models of tumor respiratory motion to account for target motion in targeting. The tumor motion model can be verified on a per-treatment session basis with four-dimensional cone-beam computed tomography (4D-CBCT), which acquires an image set of the dynamic target throughout the respiratory cycle during the therapy session. 4D-CBCT is undersampled if the scan time is too short. However, short scan time is desirable in clinical practice to reduce patient setup time. This dissertation presents the design and optimization of 4D-CBCT to reduce the impact of undersampling artifacts with short scan times. This work measures the impact of undersampling artifacts on the accuracy of target motion measurement under different sampling conditions and for various object sizes and motions. The results provide a minimum scan time such that the target tracking error is less than a specified tolerance. This work also presents new image reconstruction algorithms for reducing undersampling artifacts in undersampled datasets by taking advantage of the assumption that the relevant motion of interest is contained within a volume-of-interest (VOI). It is shown that the VOI-based reconstruction provides more accurate image intensity than standard reconstruction. The VOI-based reconstruction produced 43% fewer least-squares error inside the VOI and 84% fewer error throughout the image in a study designed to simulate target motion. The VOI-based reconstruction approach can reduce acquisition time and improve image quality in 4D-CBCT.

DEVELOPMENT OF A BEAM-SPECIFIC PLANNING TARGET VOLUME AND A ROBUST PLAN ANALYSIS TOOL FOR PROTON THERAPY

Proton therapy is growing increasingly popular due to its superior dose characteristics compared to conventional photon therapy. Protons travel a finite range in the patient body and stop, thereby delivering no dose beyond their range. However, because the range of a proton beam is heavily dependent on the tissue density along its beam path, uncertainties in patient setup position and inherent range calculation can degrade thedose distribution significantly. Despite these challenges that are unique to proton therapy, current management of the uncertainties during treatment planning of proton therapy has been similar to that of conventional photon therapy. The goal of this dissertation research was to develop a treatment planning method and a planevaluation method that address proton-specific issues regarding setup and range uncertainties. Treatment plan designing method adapted to proton therapy: Currently, for proton therapy using a scanning beam delivery system, setup uncertainties are largely accounted for by geometrically expanding a clinical target volume (CTV) to a planning target volume (PTV). However, a PTV alone cannot adequately account for range uncertainties coupled to misaligned patient anatomy in the beam path since it does not account for the change in tissue density. In order to remedy this problem, we proposed a beam-specific PTV (bsPTV) that accounts for the change in tissue density along the beam path due to the uncertainties. Our proposed method was successfully implemented, and its superiority over the conventional PTV was shown through a controlled experiment.. Furthermore, we have shown that the bsPTV concept can be incorporated into beam angle optimization for better target coverage and normal tissue sparing for a selected lung cancer patient. Treatment plan evaluation method adapted to proton therapy: The dose-volume histogram of the clinical target volume (CTV) or any other volumes of interest at the time of planning does not represent the most probable dosimetric outcome of a given plan as it does not include the uncertainties mentioned earlier. Currently, the PTV is used as a surrogate of the CTV’s worst case scenario for target dose estimation. However, because proton dose distributions are subject to change under these uncertainties, the validity of the PTV analysis method is questionable. In order to remedy this problem, we proposed the use of statistical parameters to quantify uncertainties on both the dose-volume histogram and dose distribution directly. The robust plan analysis tool was successfully implemented to compute both the expectation value and its standard deviation of dosimetric parameters of a treatment plan under the uncertainties. For 15 lung cancer patients, the proposed method was used to quantify the dosimetric difference between the nominal situation and its expected value under the uncertainties.

Modeling Techniques for the High-Resolution Interpretation of Cryo-Electron Microscopy Reconstructions

Essential biological processes are governed by organized, dynamic interactions between multiple biomolecular systems. Complexes are thus formed to enable the biological function and get dissembled as the process is completed. Examples of such processes include the translation of the messenger RNA into protein by the ribosome, the folding of proteins by chaperonins or the entry of viruses in host cells. Understanding these fundamental processes by characterizing the molecular mechanisms that enable then, would allow the (better) design of therapies and drugs. Such molecular mechanisms may be revealed trough the structural elucidation of the biomolecular assemblies at the core of these processes. Various experimental techniques may be applied to investigate the molecular architecture of biomolecular assemblies. High-resolution techniques, such as X-ray crystallography, may solve the atomic structure of the system, but are typically constrained to biomolecules of reduced flexibility and dimensions. In particular, X-ray crystallography requires the sample to form a three dimensional (3D) crystal lattice which is technically di‑cult, if not impossible, to obtain, especially for large, dynamic systems. Often these techniques solve the structure of the different constituent components within the assembly, but encounter difficulties when investigating the entire system. On the other hand, imaging techniques, such as cryo-electron microscopy (cryo-EM), are able to depict large systems in near-native environment, without requiring the formation of crystals. The structures solved by cryo-EM cover a wide range of resolutions, from very low level of detail where only the overall shape of the system is visible, to high-resolution that approach, but not yet reach, atomic level of detail. In this dissertation, several modeling methods are introduced to either integrate cryo-EM datasets with structural data from X-ray crystallography, or to directly interpret the cryo-EM reconstruction. Such computational techniques were developed with the goal of creating an atomic model for the cryo-EM data. The low-resolution reconstructions lack the level of detail to permit a direct atomic interpretation, i.e. one cannot reliably locate the atoms or amino-acid residues within the structure obtained by cryo-EM. Thereby one needs to consider additional information, for example, structural data from other sources such as X-ray crystallography, in order to enable such a high-resolution interpretation. Modeling techniques are thus developed to integrate the structural data from the different biophysical sources, examples including the work described in the manuscript I and II of this dissertation. At intermediate and high-resolution, cryo-EM reconstructions depict consistent 3D folds such as tubular features which in general correspond to alpha-helices. Such features can be annotated and later on used to build the atomic model of the system, see manuscript III as alternative. Three manuscripts are presented as part of the PhD dissertation, each introducing a computational technique that facilitates the interpretation of cryo-EM reconstructions. The first manuscript is an application paper that describes a heuristics to generate the atomic model for the protein envelope of the Rift Valley fever virus. The second manuscript introduces the evolutionary tabu search strategies to enable the integration of multiple component atomic structures with the cryo-EM map of their assembly. Finally, the third manuscript develops further the latter technique and apply it to annotate consistent 3D patterns in intermediate-resolution cryo-EM reconstructions. The first manuscript, titled An assembly model for Rift Valley fever virus, was submitted for publication in the Journal of Molecular Biology. The cryo-EM structure of the Rift Valley fever virus was previously solved at 27Å-resolution by Dr. Freiberg and collaborators. Such reconstruction shows the overall shape of the virus envelope, yet the reduced level of detail prevents the direct atomic interpretation. High-resolution structures are not yet available for the entire virus nor for the two different component glycoproteins that form its envelope. However, homology models may be generated for these glycoproteins based on similar structures that are available at atomic resolutions. The manuscript presents the steps required to identify an atomic model of the entire virus envelope, based on the low-resolution cryo-EM map of the envelope and the homology models of the two glycoproteins. Starting with the results of the exhaustive search to place the two glycoproteins, the model is built iterative by running multiple multi-body refinements to hierarchically generate models for the different regions of the envelope. The generated atomic model is supported by prior knowledge regarding virus biology and contains valuable information about the molecular architecture of the system. It provides the basis for further investigations seeking to reveal different processes in which the virus is involved such as assembly or fusion. The second manuscript was recently published in the of Journal of Structural Biology (doi:10.1016/j.jsb.2009.12.028) under the title Evolutionary tabu search strategies for the simultaneous registration of multiple atomic structures in cryo-EM reconstructions. This manuscript introduces the evolutionary tabu search strategies applied to enable a multi-body registration. This technique is a hybrid approach that combines a genetic algorithm with a tabu search strategy to promote the proper exploration of the high-dimensional search space. Similar to the Rift Valley fever virus, it is common that the structure of a large multi-component assembly is available at low-resolution from cryo-EM, while high-resolution structures are solved for the different components but lack for the entire system. Evolutionary tabu search strategies enable the building of an atomic model for the entire system by considering simultaneously the different components. Such registration indirectly introduces spatial constrains as all components need to be placed within the assembly, enabling the proper docked in the low-resolution map of the entire assembly. Along with the method description, the manuscript covers the validation, presenting the benefit of the technique in both synthetic and experimental test cases. Such approach successfully docked multiple components up to resolutions of 40Å. The third manuscript is entitled Evolutionary Bidirectional Expansion for the Annotation of Alpha Helices in Electron Cryo-Microscopy Reconstructions and was submitted for publication in the Journal of Structural Biology. The modeling approach described in this manuscript applies the evolutionary tabu search strategies in combination with the bidirectional expansion to annotate secondary structure elements in intermediate resolution cryo-EM reconstructions. In particular, secondary structure elements such as alpha helices show consistent patterns in cryo-EM data, and are visible as rod-like patterns of high density. The evolutionary tabu search strategy is applied to identify the placement of the different alpha helices, while the bidirectional expansion characterizes their length and curvature. The manuscript presents the validation of the approach at resolutions ranging between 6 and 14Å, a level of detail where alpha helices are visible. Up to resolution of 12 Å, the method measures sensitivities between 70-100% as estimated in experimental test cases, i.e. 70-100% of the alpha-helices were correctly predicted in an automatic manner in the experimental data. The three manuscripts presented in this PhD dissertation cover different computation methods for the integration and interpretation of cryo-EM reconstructions. The methods were developed in the molecular modeling software Sculptor (http://sculptor.biomachina.org) and are available for the scientific community interested in the multi-resolution modeling of cryo-EM data. The work spans a wide range of resolution covering multi-body refinement and registration at low-resolution along with annotation of consistent patterns at high-resolution. Such methods are essential for the modeling of cryo-EM data, and may be applied in other fields where similar spatial problems are encountered, such as medical imaging.

Pencil -beam redefinition algorithm dose calculations for electron therapy treatment planning

The electron pencil-beam redefinition algorithm (PBRA) of Shiu and Hogstrom has been developed for use in radiotherapy treatment planning (RTP). Earlier studies of Boyd and Hogstrom showed that the PBRA lacked an adequate incident beam model, that PBRA might require improved electron physics, and that no data existed which allowed adequate assessment of the PBRA-calculated dose accuracy in a heterogeneous medium such as one presented by patient anatomy. The hypothesis of this research was that by addressing the above issues the PBRA-calculated dose would be accurate to within 4% or 2 mm in regions of high dose gradients. A secondary electron source was added to the PBRA to account for collimation-scattered electrons in the incident beam. Parameters of the dual-source model were determined from a minimal data set to allow ease of beam commissioning. Comparisons with measured data showed 3% or better dose accuracy in water within the field for cases where 4% accuracy was not previously achievable. A measured data set was developed that allowed an evaluation of PBRA in regions distal to localized heterogeneities. Geometries in the data set included irregular surfaces and high- and low-density internal heterogeneities. The data was estimated to have 1% precision and 2% agreement with accurate, benchmarked Monte Carlo (MC) code. PBRA electron transport was enhanced by modeling local pencil beam divergence. This required fundamental changes to the mathematics of electron transport (divPBRA). Evaluation of divPBRA with the measured data set showed marginal improvement in dose accuracy when compared to PBRA; however, 4% or 2mm accuracy was not achieved by either PBRA version for all data points. Finally, PBRA was evaluated clinically by comparing PBRA- and MC-calculated dose distributions using site-specific patient RTP data. Results show PBRA did not agree with MC to within 4% or 2mm in a small fraction (<3%) of the irradiated volume. Although the hypothesis of the research was shown to be false, the minor dose inaccuracies should have little or no impact on RTP decisions or patient outcome. Therefore, given ease of beam commissioning, documentation of accuracy, and calculational speed, the PBRA should be considered a practical tool for clinical use. ^