16 resultados para Magneto-optical imaging techniques

em DigitalCommons@The Texas Medical Center


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Olfactory glomeruli are the loci where the first odor-representation map emerges. The glomerular layer comprises exquisite local synaptic circuits for the processing of olfactory coding patterns immediately after their emergence. To understand how an odor map is transferred from afferent terminals to postsynaptic dendrites, it is essential to directly monitor the odor-evoked glomerular postsynaptic activity patterns. Here we report the use of a transgenic mouse expressing a Ca(2+)-sensitive green fluorescence protein (GCaMP2) under a Kv3.1 potassium-channel promoter. Immunostaining revealed that GCaMP2 was specifically expressed in mitral and tufted cells and a subpopulation of juxtaglomerular cells but not in olfactory nerve terminals. Both in vitro and in vivo imaging combined with glutamate receptor pharmacology confirmed that odor maps reported by GCaMP2 were of a postsynaptic origin. These mice thus provided an unprecedented opportunity to analyze the spatial activity pattern reflecting purely postsynaptic olfactory codes. The odor-evoked GCaMP2 signal had both focal and diffuse spatial components. The focalized hot spots corresponded to individually activated glomeruli. In GCaMP2-reported postsynaptic odor maps, different odorants activated distinct but overlapping sets of glomeruli. Increasing odor concentration increased both individual glomerular response amplitude and the total number of activated glomeruli. Furthermore, the GCaMP2 response displayed a fast time course that enabled us to analyze the temporal dynamics of odor maps over consecutive sniff cycles. In summary, with cell-specific targeting of a genetically encoded Ca(2+) indicator, we have successfully isolated and characterized an intermediate level of odor representation between olfactory nerve input and principal mitral/tufted cell output.

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Apoptosis, a form of programmed cell death, is critical to homoeostasis, normal development, and physiology. Dysregulation of apoptosis can lead to the accumulation of unwanted cells, such as occurs in cancer, and the removal of needed cells or disorders of normal tissues, such as heart, neurodegenerative, and autoimmune diseases. Noninvasive detection of apoptosis may play an important role in the evaluation of disease states and response to therapeutic intervention for a variety of diseases. It is desirable to have an imaging method to accurately detect and monitor this process in patients. In this study, we developed annexin A5-conjugated polymeric micellar nanoparticles dual-labeled with a near-infrared fluorescence fluorophores (Cy7) and a radioisotope (111In), named as 111In-labeled annexin A5-CCPM. In vitro studies demonstrated that annexin A5-CCPM could strongly and specifically bind to apoptotic cells. In vivo studies showed that apoptotic tissues could be clearly visualized by both single photon emission computed tomography (SPECT) and fluorescence molecular tomography (FMT) after intravenous injection of 111In-labeled Annexin A5-CCPM in 6 different apoptosis models. In contrast, there was little signal in respective healthy tissues. All the biodistribution data confirmed imaging results. Moreover, histological analysis revealed that radioactivity count correlated with fluorescence signal from the nanoparticles, and both signals co-localized with the region of apoptosis. In sum, 111In-labeled annexin A5-CCPM allowed visualization of apoptosis by both nuclear and optical imaging techniques. The complementary information acquired with multiple imaging techniques should be advantageous in improving diagnostics and management of patients.

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The binding of immune inhibitory receptor Programmed Death 1 (PD-1) on T cells to its ligand PD-L1 has been implicated as a major contributor to tumor induced immune suppression. Clinical trials of PD-L1 blockade have proven effective in unleashing therapeutic anti-tumor immune responses in a subset of patients with advanced melanoma, yet current response rates are low for reasons that remain unclear. Hypothesizing that the PD-1/PD-L1 pathway regulates T cell surveillance within the tumor microenvironment, we employed intravital microscopy to investigate the in vivo impact of PD-L1 blocking antibody upon tumor-associated immune cell migration. However, current analytical methods of intravital dynamic microscopy data lack the ability to identify cellular targets of T cell interactions in vivo, a crucial means for discovering which interactions are modulated by therapeutic intervention. By developing novel imaging techniques that allowed us to better analyze tumor progression and T cell dynamics in the microenvironment; we were able to explore the impact of PD-L1 blockade upon the migratory properties of tumor-associated immune cells, including T cells and antigen presenting cells, in lung tumor progression. Our results demonstrate that early changes in tumor morphology may be indicative of responsiveness to anti-PD-L1 therapy. We show that immune cells in the tumor microenvironment as well as tumors themselves express PD-L1, but immune phenotype alone is not a predictive marker of effective anti-tumor responses. Through a novel method in which we quantify T cell interactions, we show that T cells are largely engaged in interactions with dendritic cells in the tumor microenvironment. Additionally, we show that during PD-L1 blockade, non-activated T cells are recruited in greater numbers into the tumor microenvironment and engage more preferentially with dendritic cells. We further show that during PD-L1 blockade, activated T cells engage in more confined, immune synapse-like interactions with dendritic cells, as opposed to more dynamic, kinapse-like interactions with dendritic cells when PD-L1 is free to bind its receptor. By advancing the contextual analysis of anti-tumor immune surveillance in vivo, this study implicates the interaction between T cells and tumor-associated dendritic cells as a possible modulator in targeting PD-L1 for anti-tumor immunotherapy.

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EphB4 receptors, a member of the largest family of receptor tyrosine kinases, are found over-expressed in a variety of tumors cells including glioma cells as well as angiogenic blood vessels. Noninvasive imaging of EphB4 could potentially increase early detection rates, monitor response to therapy directed against EphB4, and improve patient outcomes. Targeted delivery of EphB4 receptor specific peptide conjugated hollow gold nanoshells (HAuNS) into tumors has great potential in cancer imaging and photothermal therapy. In this study, we developed an EphB4 specific peptide named TNYL-RAW and labeled with radioisotope 64Cu and Cy5.5 dye. We also conjugate this specific peptide with hollow gold nanoshells (HAuNS) to evaluate targeted photothermal therapy of cancers. In vitro, 64Cu-DOTA-TNYL- RAW specifically bind to CT26 and PC-3M cells but not to A549 cells. In vivo, Small-animal PET/CT clearly showed the significant uptake of 64Cu-DOTA-TNYL-RAW in CT26 and PC-3M tumors but not in A549 tumors. Furthermore, µPET/CT and near-infrared optical imaging clearly showed the uptake of the dual labeled TNYL-RAW peptide in both U251 and U87 tumors in the brains of nude mice. In U251 tumors, Cy5.5-labeled peptide can bind to EphB4-expressing tumor blood vessels and tumors cells. But in U87 models, dual labeled peptide only could bind to tumor associated blood vessels. Also, Irradiation of PC-3M and CT-26 cell treated with TNYL-PEG-HAuNS nanopatilces with near-infrared (NIR) laser resulted in selective destruction of these cells in vitro. EphB4 targeted TNYL-PEG-HAuNS showed more photothermal killing effect on CT26 tumor model than PEG-HAuNS did. In summary, tumors with overexpression of EphB4 receptors can be noninvasively visualized by micro PET/CT with 64Cu labeled or dual labeled TNYL-RAW peptide. Targeted delivery of TNYL-RAW conjugated HAuNS into tumors can greatly improve the treatment effect of photothermal therapy. The information acquired with this study should be advantageous in improving diagnostics and future applications in photothermal ablation therapy in clinical.

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We have developed an empirically based simulation system to create images equivalent in SNR and SPR to those that would be acquired with various possible SEDR configurations. This system uses a collection of spot collimated full-field images (SCFFIs) of an anthropomorphic chest phantom, taken at high exposure levels and rescaled in noise and intensity, then digitally collimated and combined to produce the simulated SEDR images. This system allows for the study of design trade-offs between different equalization feedback schemes and scatter rejection geometries in addition to estimating the clinical benefits of SEDR over traditional imaging techniques. Data from this simulation system has demonstrated that SEDR techniques offer potential significant improvements over currently used digital radiography techniques for chest imaging. ^

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Introduction. Investigations into the shortcomings of current intracavitary brachytherapy (ICBT) technology has lead us to design an Anatomically Adaptive Applicator (A3). The goal of this work was to design and characterize the imaging and dosimetric capabilities of this device. The A3 design incorporates a single shield that can both rotate and translate within the colpostat. We hypothesized that this feature, coupled with specific A3 component construction materials and imaging techniques, would facilitate artifact-free CT and MR image acquisition. In addition, by shaping the delivered dose distribution via the A3 movable shield, dose delivered to the rectum will be less compared to equivalent treatments utilizing current state-of-the-art ICBT applicators. ^ Method and materials. A method was developed to facilitate an artifact-free CT imaging protocol that used a "step-and-shoot" technique: pausing the scanner midway through the scan and moving the A 3 shield out of the path of the beam. The A3 CT imaging capabilities were demonstrated acquiring images of a phantom that positioned the A3 and FW applicators in a clinically-applicable geometry. Artifact-free MRI imaging was achieved by utilizing MRI-compatible ovoid components and pulse-sequences that minimize susceptibility artifacts. Artifacts were qualitatively compared, in a clinical setup. For the dosimetric study, Monte-Carlo (MC) models of the A3 and FW (shielded and unshielded) applicators were validated. These models were incorporated into a MC model of one cervical cancer patient ICBT insertion, using 192Ir (mHDR v2 source). The A3 shield's rotation and translation was adjusted for each dwell position to minimize dose to the rectum. Superposition of dose to rectum for all A3 dwell sources (4 per ovoid) was applied to obtain a comparison of equivalent FW treatments. Rectal dose-volume histograms (absolute and HDR/PDR biologically effective dose (BED)) and BED to 2 cc (BED2cc ) were determined for all applicators and compared. ^ Results. Using a "step-and-shoot" CT scanning method and MR compliant materials and optimized pulse-sequences, images of the A 3 were nearly artifact-free for both modalities. The A3 reduced BED2cc by 18.5% and 7.2% for a PDR treatment and 22.4% and 8.7% for a HDR treatment compared to treatments delivered using an uFW and sFW applicator, respectively. ^ Conclusions. The novel design of the A3 facilitated nearly artifact-free image quality for both CT and MR clinical imaging protocols. The design also facilitated a reduction in BED to the rectum compared to equivalent ICBT treatments delivered using current, state-of-the-art applicators. ^

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High Angular Resolution Diffusion Imaging (HARDI) techniques, including Diffusion Spectrum Imaging (DSI), have been proposed to resolve crossing and other complex fiber architecture in the human brain white matter. In these methods, directional information of diffusion is inferred from the peaks in the orientation distribution function (ODF). Extensive studies using histology on macaque brain, cat cerebellum, rat hippocampus and optic tracts, and bovine tongue are qualitatively in agreement with the DSI-derived ODFs and tractography. However, there are only two studies in the literature which validated the DSI results using physical phantoms and both these studies were not performed on a clinical MRI scanner. Also, the limited studies which optimized DSI in a clinical setting, did not involve a comparison against physical phantoms. Finally, there is lack of consensus on the necessary pre- and post-processing steps in DSI; and ground truth diffusion fiber phantoms are not yet standardized. Therefore, the aims of this dissertation were to design and construct novel diffusion phantoms, employ post-processing techniques in order to systematically validate and optimize (DSI)-derived fiber ODFs in the crossing regions on a clinical 3T MR scanner, and develop user-friendly software for DSI data reconstruction and analysis. Phantoms with a fixed crossing fiber configuration of two crossing fibers at 90° and 45° respectively along with a phantom with three crossing fibers at 60°, using novel hollow plastic capillaries and novel placeholders, were constructed. T2-weighted MRI results on these phantoms demonstrated high SNR, homogeneous signal, and absence of air bubbles. Also, a technique to deconvolve the response function of an individual peak from the overall ODF was implemented, in addition to other DSI post-processing steps. This technique greatly improved the angular resolution of the otherwise unresolvable peaks in a crossing fiber ODF. The effects of DSI acquisition parameters and SNR on the resultant angular accuracy of DSI on the clinical scanner were studied and quantified using the developed phantoms. With a high angular direction sampling and reasonable levels of SNR, quantification of a crossing region in the 90°, 45° and 60° phantoms resulted in a successful detection of angular information with mean ± SD of 86.93°±2.65°, 44.61°±1.6° and 60.03°±2.21° respectively, while simultaneously enhancing the ODFs in regions containing single fibers. For the applicability of these validated methodologies in DSI, improvement in ODFs and fiber tracking from known crossing fiber regions in normal human subjects were demonstrated; and an in-house software package in MATLAB which streamlines the data reconstruction and post-processing for DSI, with easy to use graphical user interface was developed. In conclusion, the phantoms developed in this dissertation offer a means of providing ground truth for validation of reconstruction and tractography algorithms of various diffusion models (including DSI). Also, the deconvolution methodology (when applied as an additional DSI post-processing step) significantly improved the angular accuracy of the ODFs obtained from DSI, and should be applicable to ODFs obtained from the other high angular resolution diffusion imaging techniques.

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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.

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DCE-MRI is an important technique in the study of small animal cancer models because its sensitivity to vascular changes opens the possibility of quantitative assessment of early therapeutic response. However, extraction of physiologically descriptive parameters from DCE-MRI data relies upon measurement of the vascular input function (VIF), which represents the contrast agent concentration time course in the blood plasma. This is difficult in small animal models due to artifacts associated with partial volume, inflow enhancement, and the limited temporal resolution achievable with MR imaging. In this work, the development of a suite of techniques for high temporal resolution, artifact resistant measurement of the VIF in mice is described. One obstacle in VIF measurement is inflow enhancement, which decreases the sensitivity of the MR signal to the presence of contrast agent. Because the traditional techniques used to suppress inflow enhancement degrade the achievable spatiotemporal resolution of the pulse sequence, improvements can be achieved by reducing the time required for the suppression. Thus, a novel RF pulse which provides spatial presaturation contemporaneously with the RF excitation was implemented and evaluated. This maximizes the achievable temporal resolution by removing the additional RF and gradient pulses typically required for suppression of inflow enhancement. A second challenge is achieving the temporal resolution required for accurate characterization of the VIF, which exceeds what can be achieved with conventional imaging techniques while maintaining adequate spatial resolution and tumor coverage. Thus, an anatomically constrained reconstruction strategy was developed that allows for sampling of the VIF at extremely high acceleration factors, permitting capture of the initial pass of the contrast agent in mice. Simulation, phantom, and in vivo validation of all components were performed. Finally, the two components were used to perform VIF measurement in the murine heart. An in vivo study of the VIF reproducibility was performed, and an improvement in the measured injection-to-injection variation was observed. This will lead to improvements in the reliability of quantitative DCE-MRI measurements and increase their sensitivity.

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In a challenging case of carotid occlusion with slowly evolving stroke, we used brain imaging to facilitate endovascular revascularization resulting in the relief of the patient's symptoms. Patients with carotid occlusion and continued neurological worsening or fluctuations present enormous treatment challenges. These patients may present "slow" strokes with subacute infarcts that present significant challenges and risks during attempts at revascularization of the occluded artery. We present such a case in which we used multimodal imaging techniques, including MR-perfusion, to facilitate endovascular revascularization. Our approach of delayed but cautious intra-arterial thrombolytic therapy, guided by brain imaging, and followed by stent placement across the residual stenosis, enabled revascularization of the occluded artery without overt in-hospital complications.

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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.

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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.

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With the recognition of the importance of evidence-based medicine, there is an emerging need for methods to systematically synthesize available data. Specifically, methods to provide accurate estimates of test characteristics for diagnostic tests are needed to help physicians make better clinical decisions. To provide more flexible approaches for meta-analysis of diagnostic tests, we developed three Bayesian generalized linear models. Two of these models, a bivariate normal and a binomial model, analyzed pairs of sensitivity and specificity values while incorporating the correlation between these two outcome variables. Noninformative independent uniform priors were used for the variance of sensitivity, specificity and correlation. We also applied an inverse Wishart prior to check the sensitivity of the results. The third model was a multinomial model where the test results were modeled as multinomial random variables. All three models can include specific imaging techniques as covariates in order to compare performance. Vague normal priors were assigned to the coefficients of the covariates. The computations were carried out using the 'Bayesian inference using Gibbs sampling' implementation of Markov chain Monte Carlo techniques. We investigated the properties of the three proposed models through extensive simulation studies. We also applied these models to a previously published meta-analysis dataset on cervical cancer as well as to an unpublished melanoma dataset. In general, our findings show that the point estimates of sensitivity and specificity were consistent among Bayesian and frequentist bivariate normal and binomial models. However, in the simulation studies, the estimates of the correlation coefficient from Bayesian bivariate models are not as good as those obtained from frequentist estimation regardless of which prior distribution was used for the covariance matrix. The Bayesian multinomial model consistently underestimated the sensitivity and specificity regardless of the sample size and correlation coefficient. In conclusion, the Bayesian bivariate binomial model provides the most flexible framework for future applications because of its following strengths: (1) it facilitates direct comparison between different tests; (2) it captures the variability in both sensitivity and specificity simultaneously as well as the intercorrelation between the two; and (3) it can be directly applied to sparse data without ad hoc correction. ^

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Standard treatment strategies for cancer patients include surgery, radiation therapy, and chemotherapy. Although these strategies have been proven effective, they also have associated limitations. An attractive and innovative approach that can be used alone or in combination with the above modalities is based on the systemic or topical administration of a nanomaterial-based photoactive compound. Interaction with light in the near infrared (NIR) region results in either emission of fluorescence, which can be used for photodetection, or absorption of light which results in phototherapy. Nanomaterials have the advantage of providing multi-functional and unique properties in a single device that cannot be readily acquired with conventional small molecular weight compounds. ^ In this study, three different novel nanocarrier systems were designed and evaluated in mediating photodetection and phototherapy in the NIR. The first compound synthesized was a dual-labeled magnetic resonance/optical imaging agent for sentinel lymph node mapping and biopsy. This dual-labeled agent combines the high resolution of magnetic resonance imaging with the highly sensitive detection of optical imaging. The second imaging agent was an activatable optical imaging agent used to monitor cathepsin B activity in vivo and to probe the degradation of poly(L-glutamic acid). This polymeric nanocarrier offers highly sensitive technique for the detection of enzymatic activity, with is not yet possible with small molecular weight compounds. The third agent was a C225-conjugated hollow nanoshell that is targeted to epidermal growth factor receptors. This targeting agent has been demonstrated to mediate photothermal therapy both in vitro and in vivo. ^ These nanocarrier systems are an invaluable tool for the detection of cancer and many other diseases. With improved targeted delivery of these agents, the ability to diagnose diseases will become more sensitive and more specific. Finally, when designed properly, these agents would allow concurrent diagnosis and treatment of patients of various diseases. ^

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Lung damage is a common side effect of chemotherapeutic drugs such as bleomycin. This study used a bleomycin mouse model which simulates the lung damage observed in humans. Noninvasive, in vivo cone-beam computed tomography (CBCT) was used to visualize and quantify fibrotic and inflammatory damage over the entire lung volume of mice. Bleomycin was used to induce pulmonary damage in vivo and the results from two CBCT systems, a micro-CT and flat panel CT (fpCT), were compared to histologic measurements, the standard method of murine lung damage quantification. Twenty C57BL/6 mice were given either 3 U/kg of bleomycin or saline intratracheally. The mice were scanned at baseline, before the administration of bleomycin, and then 10, 14, and 21 days afterward. At each time point, a subset of mice was sacrificed for histologic analysis. The resulting CT images were used to assess lung volume. Percent lung damage (PLD) was calculated for each mouse on both the fpCT (PLDfpcT) and the micro-CT (PLDμCT). Histologic PLD (PLDH) was calculated for each histologic section at each time point (day 10, n = 4; day 14, n = 4; day 21, n = 5; control group, n = 5). A linear regression was applied to the PLDfpCT vs. PLDH, PLDμCT vs. PLDH and PLDfpCT vs. PLDμCT distributions. This study did not demonstrate strong correlations between PLDCT and PLDH. The coefficient of determination, R, was 0.68 for PLDμCT vs. PLDH and 0.75 for the PLD fpCT vs. PLDH. The experimental issues identified from this study were: (1) inconsistent inflation of the lungs from scan to scan, (2) variable distribution of damage (one histologic section not representative of overall lung damage), (3) control mice not scanned with each group of bleomycin mice, (4) two CT systems caused long anesthesia time for the mice, and (5) respiratory gating did not hold the volume of lung constant throughout the scan. Addressing these issues might allow for further improvement of the correlation between PLDCT and PLDH. ^