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Cardiovascular disease is one of the leading causes of death worldwide and, so far, echocardiography, nuclear cardiology, and catheterization are the gold standard techniques used for its detection. Cardiac magnetic resonance (CMR) can replace the invasive imaging modalities and provide a "one-stop shop" characterization of the cardiovascular system by measuring myocardial tissue structure, function and perfusion of the heart, as well as anatomy of and flow in the coronary arteries. In contrast to standard clinical magnetic resonance imaging (MRI) scanners, which are often operated at a field strength of 1.5 or 3 Tesla (T), a higher resolution and subsequent cardiac parameter quantification could potentially be achieved at ultra-high field, i.e., 7 T and above.
Unique insights into the pathophysiology of the heart are expected from ultra-high field MRI, which offers enhanced image quality in combination with novel contrast mechanisms, but suffers from spatio-temporal B0 magnetic field variations. Due to the resulting spatial misregistration and intra-voxel dephasing, these B0-field inhomogeneities generate a variety of undesired image artifacts, e.g., artificial image deformation. The resulting macroscopic field gradients lead to signal loss, because the effective transverse relaxation time T2* is shortened. This affects the accuracy of T2* measurements, which are essential for myocardial tissue characterization. When steady state free precession-based pulse sequences are employed for image acquisition, certain off-resonance frequencies cause signal voids. These banding artifacts complicate the proper marking of the myocardium and, subsequently, systematic errors in cardiac function measurements are inevitable. Clinical MR scanners are equipped with basic shim systems to correct for occurring B0-field inhomogeneities and resulting image artifacts, however, these are not sufficient for the advanced measurement techniques employed for ultra-high field MRI of the heart.
Therefore, this work focused on the development of advanced B0 shimming strategies for CMR imaging applications to correct the spatio-temporal B0 field variations present in the human heart at 7 T. A novel cardiac phase-specific shimming (CPSS) technique was set up, which featured a triggered B0 map acquisition, anatomy-matched selection of the shim-region-of-interest (SROI), and calibration-based B0 field modeling. The influence of technical limitations on the overall spherical harmonics (SH) shim was analyzed. Moreover, benefits as well as pitfalls of dynamic shimming were debated in this study. An advanced B0 shimming strategy was set up and applied in vivo, which was the first implementation of a heart-specific shimming approach in human UHF MRI at the time.
The spatial B0-field patterns which were measured in the heart throughout this study contained localized spots of strong inhomogeneities. They fluctuated over the cardiac cycle in both size and strength, and were ideally addressed using anatomy-matched SROIs. Creating a correcting magnetic field with one shim coil, however, generated eddy currents in the surrounding conducting structures and a resulting additional, unintended magnetic field. Taking these shim-to-shim interactions into account via calibration, it was demonstrated for the first time that the non-standard 3rd-order SH terms enhanced B0-field homogeneity in the human heart. However, they were attended by challenges for the shim system hardware employed in the presented work, which was indicated by the currents required to generate the optimal 3rd-order SH terms exceeding the dynamic range of the corresponding shim coils. To facilitate dynamic shimming updated over the cardiac cycle for cine imaging, the benefit of adjusting the oscillating CPSS currents was found to be vital. The first in vivo application of the novel advanced B0 shimming strategy mostly matched the simulations.
The presented technical developments are a basic requirement to quantitative and functional CMR imaging of the human heart at 7 T. They pave the way for numerous clinical studies about cardiac diseases, and continuative research on dedicated cardiac B0 shimming, e.g., adapted passive shimming and multi-coil technologies.
Acceleration is a central aim of clinical and technical research in magnetic resonance imaging (MRI) today, with the potential to increase robustness, accessibility and patient comfort, reduce cost, and enable entirely new kinds of examinations. A key component in this endeavor is image reconstruction, as most modern approaches build on advanced signal and image processing. Here, deep learning (DL)-based methods have recently shown considerable potential, with numerous publications demonstrating benefits for MRI reconstruction. However, these methods often come at the cost of an increased risk for subtle yet critical errors. Therefore, the aim of this thesis is to advance DL-based MRI reconstruction, while ensuring high quality and fidelity with measured data. A network architecture specifically suited for this purpose is the variational network (VN). To investigate the benefits these can bring to non-Cartesian cardiac imaging, the first part presents an application of VNs, which were specifically adapted to the reconstruction of accelerated spiral acquisitions. The proposed method is compared to a segmented exam, a U-Net and a compressed sensing (CS) model using qualitative and quantitative measures. While the U-Net performed poorly, the VN as well as the CS reconstruction showed good output quality. In functional cardiac imaging, the proposed real-time method with VN reconstruction substantially accelerates examinations over the gold-standard, from over 10 to just 1 minute. Clinical parameters agreed on average.
Generally in MRI reconstruction, the assessment of image quality is complex, in particular for modern non-linear methods. Therefore, advanced techniques for precise evaluation of quality were subsequently demonstrated.
With two distinct methods, resolution and amplification or suppression of noise are quantified locally in each pixel of a reconstruction. Using these, local maps of resolution and noise in parallel imaging (GRAPPA), CS, U-Net and VN reconstructions were determined for MR images of the brain. In the tested images, GRAPPA delivers uniform and ideal resolution, but amplifies noise noticeably. The other methods adapt their behavior to image structure, where different levels of local blurring were observed at edges compared to homogeneous areas, and noise was suppressed except at edges. Overall, VNs were found to combine a number of advantageous properties, including a good trade-off between resolution and noise, fast reconstruction times, and high overall image quality and fidelity of the produced output. Therefore, this network architecture seems highly promising for MRI reconstruction.
This work deals with the acceleration of cardiovascular MRI for the assessment
of functional information in steady-state contrast and for viability assessment
during the inversion recovery of the magnetization. Two approaches
are introduced and discussed in detail. MOCO-MAP uses an exponential
model to recover dynamic image data, IR-CRISPI, with its low-rank plus
sparse reconstruction, is related to compressed sensing.
MOCO-MAP is a successor to model-based acceleration of parametermapping
(MAP) for the application in the myocardial region. To this end, it
was augmented with a motion correction (MOCO) step to allow exponential
fitting the signal of a still object in temporal direction. Iteratively, this
introduction of prior physical knowledge together with the enforcement of
consistency with the measured data can be used to reconstruct an image
series from distinctly shorter sampling time than the standard exam (< 3 s
opposed to about 10 s). Results show feasibility of the method as well as
detectability of delayed enhancement in the myocardium, but also significant
discrepancies when imaging cardiac function and artifacts caused already by
minor inaccuracy of the motion correction.
IR-CRISPI was developed from CRISPI, which is a real-time protocol
specifically designed for functional evaluation of image data in steady-state
contrast. With a reconstruction based on the separate calculation of low-rank
and sparse part, it employs a softer constraint than the strict exponential
model, which was possible due to sufficient temporal sampling density via
spiral acquisition. The low-rank plus sparse reconstruction is fit for the use on
dynamic and on inversion recovery data. Thus, motion correction is rendered
unnecessary with it.
IR-CRISPI was equipped with noise suppression via spatial wavelet filtering.
A study comprising 10 patients with cardiac disease show medical
applicability. A comparison with performed traditional reference exams offer
insight into diagnostic benefits. Especially regarding patients with difficulty
to hold their breath, the real-time manner of the IR-CRISPI acquisition provides
a valuable alternative and an increase in robustness.
In conclusion, especially with IR-CRISPI in free breathing, a major acceleration
of the cardiovascular MR exam could be realized. In an acquisition
of less than 100 s, it not only includes the information of two traditional
protocols (cine and LGE), which take up more than 9.6 min, but also allows
adjustment of TI in retrospect and yields lower artifact level with similar
image quality.
X-ray dark-field imaging allows to resolve the conflict between the demand for centimeter scaled fields of view and the spatial resolution required for the characterization of fibrous materials structured on the micrometer scale. It draws on the ability of X-ray Talbot interferometers to provide full field images of a sample's ultra small angle scattering properties, bridging a gap of multiple orders of magnitude between the imaging resolution and the contrasted structure scale. The correspondence between shape anisotropy and oriented scattering thereby allows to infer orientations within a sample's microstructure below the imaging resolution. First demonstrations have shown the general feasibility of doing so in a tomographic fashion, based on various heuristic signal models and reconstruction approaches. Here, both a verified model of the signal anisotropy and a reconstruction technique practicable for general imaging geometries and large tensor valued volumes is developed based on in-depth reviews of dark-field imaging and tomographic reconstruction techniques.
To this end, a wide interdisciplinary field of imaging and reconstruction methodologies is revisited. To begin with, a novel introduction to the mathematical description of perspective projections provides essential insights into the relations between the tangible real space properties of cone beam imaging geometries and their technically relevant description in terms of homogeneous coordinates and projection matrices. Based on these fundamentals, a novel auto-calibration approach is developed, facilitating the practical determination of perspective imaging geometries with minimal experimental constraints. A corresponding generalized formulation of the widely employed Feldkamp algorithm is given, allowing fast and flexible volume reconstructions from arbitrary tomographic imaging geometries. Iterative reconstruction techniques are likewise introduced for general projection geometries, with a particular focus on the efficient evaluation of the forward problem associated with tomographic imaging. A highly performant 3D generalization of Joseph's classic linearly interpolating ray casting algorithm is developed to this end and compared to typical alternatives. With regard to the anisotropic imaging modality required for tensor tomography, X-ray dark-field contrast is extensively reviewed. Previous literature is brought into a joint context and nomenclature and supplemented by original work completing a consistent picture of the theory of dark-field origination. Key results are explicitly validated by experimental data with a special focus on tomography as well as the properties of anisotropic fibrous scatterers. In order to address the pronounced susceptibility of interferometric images to subtle mechanical imprecisions, an efficient optimization based evaluation strategy for the raw data provided by Talbot interferometers is developed. Finally, the fitness of linear tensor models with respect to the derived anisotropy properties of dark-field contrast is evaluated, and an iterative scheme for the reconstruction of tensor valued volumes from projection images is proposed. The derived methods are efficiently implemented and applied to fiber reinforced plastic samples, imaged at the ID19 imaging beamline of the European Synchrotron Radiation Facility. The results represent unprecedented demonstrations of X-ray dark-field tensor tomography at a field of view of 3-4cm, revealing local fiber orientations of both complex shaped and low-contrast samples at a spatial resolution of 0.1mm in 3D. The results are confirmed by an independent micro CT based fiber analysis.
In this work, accelerated non-Cartesian Magnetic Resonance Imaging (MRI) methods were established and applied to cardiovascular imaging (CMR) at different magnetic field strengths (3T and 7T).
To enable rapid data acquisition, highly efficient spiral k-space trajectories were created. In addition, hybrid sampling patterns such as the twisting radial lines (TWIRL) k-space trajectory were studied.
Imperfections of the dynamic gradient system of a MR scanner result in k-space sampling errors. Ultimately, these errors can lead to image artifacts in non-Cartesian acquisitions.
Among other reasons such as an increased reconstruction complexity, they cause the lack of spiral sequences in clinical routine compared to standard Cartesian imaging.
Therefore, the Gradient System Transfer Functions (GSTFs) of both scanners were determined and used for k-space trajectory correction in post-correction as well as in terms of a pre-emphasis.
The GSTF pre-emphasis was implemented as a fully automatic procedure, which enabled a precise correction of arbitrary gradient waveforms for double-oblique slice orientations.
Consequently, artifacts due to trajectory errors could be mitigated, which resulted in high image quality in non-Cartesian MRI.
Additionally, the GSTF correction was validated by measuring pre-emphasized spiral gradient outputs, which showed high agreement with the theoretical gradient waveforms.
Furthermore, it could be demonstrated that the performance of the GSTF correction is superior to a simple delay compensation approach.
The developed pulse sequences were applied to gated as well as real-time CMR. Special focus lied on the implementation of a spiral imaging protocol to resolve the beating heart of animals and humans in real time and free breathing.
In order to achieve real-time CMR with high spatiotemporal resolution, k-space undersampling was performed. For this reason, efficient sampling strategies were developed with the aim to facilitate compressed sensing (CS) during image reconstruction.
The applied CS approach successfully removed aliasing artifacts and yielded high-resolution cardiac image series. Image reconstruction was performed offline in all cases such that the images were not available immediately after acquisition at the scanner.
Spiral real-time CMR could be performed in free breathing, which led to an acquisition time of less than 1 minute for a whole short-axis stack.
At 3T, the results were compared to the gold standard of electrocardiogram-gated Cartesian CMR in breath hold, which revealed similar values for important cardiovascular functional and volumetric parameters.
This paves the way to an application of the developed framework in clinical routine of CMR.
In addition, the spiral real-time protocol was transferred to swallowing and speech imaging at 3T, and first images were presented.
The results were of high quality and confirm the straightforward utilization of the spiral sequence in other fields of MRI.
In general, the GSTF correction yielded high-quality images at both field strengths, 3T and 7T.
Off-resonance related blurring was mitigated by applying non-Cartesian readout gradients of short duration. At 7T, however, B1-inhomogeneity led to image artifacts in some cases.
All in all, this work demonstrated great advances in accelerating the MRI process by combining efficient, undersampled non-Cartesian k-space coverage with CS reconstruction.
Trajectory correction using the GSTF can be implemented at any scanner model and enables non-Cartesian imaging with high image quality.
Especially MRI of dynamic processes greatly benefits from the presented rapid imaging approaches.
The SNR spectra model and measurement method developed in this work yield reliable application-specific optima for image quality. This optimization can either be used to understand image quality, find out how to build a good imaging device or to (automatically) optimize the parameters of an existing setup.
SNR spectra are here defined as a fraction of power spectra instead of a product of device properties. In combination with the newly developed measurement method for this definition, a close correspondence be- tween theory and measurement is achieved. Prior approaches suffer from a focus on theoretical definitions without fully considering if the defined quantities can be measured correctly. Additionally, discrepancies between assumptions and reality are common.
The new approach is more reliable and complete, but also more difficult to evaluate and interpret. The signal power spectrum in the numerator of this fraction allows to model the image quality of different contrast mechanisms that are used in high-resolution x-ray imaging. Superposition equations derived for signal and noise enable understanding how polychromaticity (or superposition in general) affects the image quality.
For the concept of detection energy weighting, a quantitative model for how it affects im- age quality was found. It was shown that—depending on sample properties—not detecting x-ray photons can increase image quality. For optimal computational energy weighting, more general formula for the optimal weight was found. In addition to the signal strength, it includes noise and modulation transfer.
The novel method for measuring SNR spectra makes it possible to experimentally optimize image quality for different contrast mechanisms. This method uses one simple measurement to obtain a measure for im- age quality for a specific experimental setup. Comparable measurement methods typically require at least three more complex measurements, where the combination may then give a false result. SNR spectra measurements can be used to:
• Test theoretical predictions about image quality optima.
• Optimize image quality for a specific application.
• Find new mechanisms to improve image quality.
The last item reveals an important limitation of x- ray imaging in general: The achievable image quality is limited by the amount of x-ray photons interacting with the sample, not by the amount incident per detector area (see section 3.6). If the rest of the imaging geometry is fixed, moving the detector only changes the field of view, not the image quality. A practical consequence is that moving the sample closer to the x-ray source increases image quality quadratically.
The results of a SNR spectra measurement represent the image quality only on a relative scale, but very reliable. This relative scale is sufficient for an optimization problem. Physical effects are often already clearly identifiable by the shape of the functional relationship between input parameter and measurement result.
SNR spectra as a quantity are not well suited for standardization, but instead allow a reliable optimization. Not satisfying the requirements of standardization allows to use methods which have other advantages. In this case, the SNR spectra method describes the image quality for a specific application. Consequently, additional physical effects can be taken into account. Additionally, the measurement method can be used to automate the setting of optimal machine parameters.
The newly proposed image quality measure detection effectiveness is better suited for standardization or setup comparison. This quantity is very similar to measures from other publications (e.g. CNR(u)), when interpreted monochromatically. Polychromatic effects can only be modeled fully by the DE(u). The measurement processes of both are different and the DE(u) is fundamentally more reliable.
Information technology and digital data processing make it possible to determine SNR spectra from a mea- sured image series. This measurement process was designed from the ground up to use these technical capabilities. Often, information technology is only used to make processes easier and more exact. Here, the whole measurement method would be infeasible without it. As this example shows, using the capabilities of digital data processing much more extensively opens many new possibilities. Information technology can be used to extract information from measured data in ways that analog data processing simply cannot.
The original purpose of the SNR spectra optimization theory and methods was to optimize high resolution x-ray imaging only. During the course of this work, it has become clear that some of the results of this work affect x-ray imaging in general. In the future, these results could be applied to MI and NDT x-ray imaging. Future work on the same topic will also need to consider the relationship between SNR spectra or DE(u) and sufficient image quality.This question is about the minimal image quality required for a specific measurement task.
In Magnetic Resonance Imaging (MRI), acquisition of dynamic data may be highly complex due to rapid changes occurred in the object to be imaged. For clinical diagnostic, dynamic MR images require both high spatial and temporal resolution. The speed in the acquisition is a crucial factor to capture optimally dynamics of the objects to obtain accurate diagnosis. In the 90’s, partially parallel MRI (pMRI) has been introduced to shorten scan times reducing the amount of acquired data. These approaches use multi-receiver coil arrays to acquire independently and simultaneously the data.
Reduction in the amount of acquired data results in images with aliasing artifacts. Dedicated methods as such Sensitivity Encoding (SENSE) and Generalized Autocalibrating Partially Parallel Acquisition (GRAPPA) were the basis of a series of algorithms in pMRI.
Nevertheless, pMRI methods require extra spatial or temporal information in order to optimally reconstruct the data. This information is typically obtained by an extra scan or embedded in the accelerated acquisition applying a variable density acquisition scheme.
In this work, we were able to reduce or totally eliminate the acquisition of the training data for kt-SENSE and kt-PCA algorithms obtaining accurate reconstructions with high temporal fidelity.
For dynamic data acquired in an interleaved fashion, the temporal average of accelerated data can generate an artifact-free image used to estimate the coil sensitivity maps avoiding the need of extra acquisitions. However, this temporal average contains errors from aliased components, which may lead to signal nulls along the spectra of reconstructions when methods like kt-SENSE are applied. The use of a GRAPPA filter applied to the temporal average reduces these errors and subsequently may reduce the null components in the reconstructed data. In this thesis the effect of using temporal averages from radial data was investigated. Non-periodic artifacts performed by undersampling radial data allow a more accurate estimation of the true temporal average and thereby avoiding undesirable temporal filtering in the reconstructed images. kt-SENSE exploits not only spatial coil sensitivity variations but also makes use of spatio-temporal correlations in order to separate the aliased signals. Spatio-temporal correlations in kt-SENSE are learnt using a training data set, which consists of several central k-space lines acquired in a separate scan. The scan of these extra lines results in longer acquisition times even for low resolution images. It was demonstrate that limited spatial resolution of training data set may lead to temporal filtering effects (or temporal blurring) in the reconstructed data.
In this thesis, the auto-calibration for kt-SENSE was proposed and its feasibility was tested in order to completely eliminate the acquisition of training data. The application of a prior TSENSE reconstruction produces the training data set for the kt-SENSE algorithm. These training data have full spatial resolution. Furthermore, it was demonstrated that the proposed auto-calibrating method reduces significantly temporal filtering in the reconstructed images compared to conventional kt-SENSE reconstructions employing low resolution training images. However, the performance of auto-calibrating kt-SENSE is affected by the Signal-to-Noise Ratio (SNR) of the first pass reconstructions that propagates to the final reconstructions.
Another dedicated method used in dynamic MRI applications is kt-PCA, that was first proposed for the reconstruction of MR cardiac data. In this thesis, kt-PCA was employed for the generation of spatially resolved M0, T1 and T2 maps from a single accelerated IRTrueFISP or IR-Snapshot FLASH measurement. In contrast to cardiac dynamic data, MR relaxometry experiments exhibit signal at all temporal frequencies, which makes their reconstruction more challenging. However, since relaxometry measurements can be represented by only few parameters, the use of few principal components (PC) in the kt-PCA algorithm can significantly simplify the reconstruction. Furthermore, it was found that due to high redundancy in relaxometry data, PCA can efficiently extract the required information from just a single line of training data.
It has been demonstrated in this thesis that auto-calibrating kt-SENSE is able to obtain high temporal fidelity dynamic cardiac reconstructions from moderate accelerated data avoiding the extra acquisition of training data. Additionally, kt-PCA has been proved to be a suitable method for the reconstruction of highly accelerated MR relaxometry data.
Furthermore, a single central training line is necessary to obtain accurate reconstructions. Both reconstruction methods are promising for the optimization of training data acquisition and seem to be feasible for several clinical applications.
In this work, a model-based acceleration of parameter mapping (MAP) for the determination of the tissue parameter T1 using magnetic resonance imaging (MRI) is introduced. The iterative reconstruction uses prior knowledge about the relaxation behavior of the longitudinal magnetization after a suitable magnetization preparation to generate a series of fully sampled k-spaces from a strongly undersampled acquisition. A Fourier transform results in a spatially resolved time course of the longitudinal relaxation process, or equivalently, a spatially resolved map of the longitudinal relaxation time T1.
In its fastest implementation, the MAP algorithm enables the reconstruction of a T1 map from a radial gradient echo dataset acquired within only a few seconds after magnetization preparation, while the acquisition time of conventional T1 mapping techniques typically lies in the range of a few minutes. After validation of the MAP algorithm for two different types of magnetization preparation (saturation recovery & inversion recovery), the developed algorithm was applied in different areas of preclinical and clinical MRI and possible advantages and disadvantages were evaluated.
The present cumulative dissertation comprises three neuroimaging studies using different techniques, functional tasks and experimental variables of diverse nature to investigate human prefrontal cortex (PFC) (dys)function as well as methodological aspects of functional near-infrared spectroscopy (fNIRS). (1) Both dopamine (DA) availability (“inverted U-model”) and excitatory versus inhibitory DA receptor stimulation (“dual-state theory”) have been linked to PFC processing and cognitive control function. Electroencephalography (EEG) was recorded during a Go/NoGo response inhibition task in 114 healthy controls and 181 adult patients with attention-deficit/hyperactivity disorder (ADHD). As a neural measure of prefrontal cognitive response control the anteriorization of the P300 centroid in NoGo- relative to Go-trials (NoGo anteriorization, NGA) was investigated for the impact of genetic polymorphisms modulating catechol-O-methyltransferase efficiency (COMT, Val158Met) in degrading prefrontal DA and inhibitory DA receptor D4 sensitivity (DRD4, 48bp VNTR). Single genes and ADHD diagnosis showed no significant impact on the NGA or behavioral measures. However, a significant COMT×DRD4 interaction was revealed as subjects with relatively increased D4-receptor function (DRD4: no 7R-alleles) displayed an “inverted U”-relationship between the NGA and increasing COMT-dependent DA levels, whereas subjects with decreased D4-sensitivity (7R) showed a U-relationship. This interaction was supported by 7R-allele dose-effects and also reflected by an impact on task behavior, i.e. intraindividual reaction time variability. Combining previous theories of PFC DA function, neural stability at intermediate DA levels may be accompanied by the risk of overly decreased neural flexibility if inhibitory DA receptor function is additionally decreased. The findings of COMT×DRD4 epistasis might help to disentangle the genetic basis of dopaminergic mechanisms underlying prefrontal (dys)function. (2) While progressive neurocognitive impairments are associated with aging and Alzheimer's disease (AD), cortical reorganization might delay difficulties in effortful word retrieval, which is one of the earliest cognitive signs of AD. Therefore, cortical hemodynamic responses were measured with fNIRS during phonological and semantic verbal fluency, and investigated in 325 non-demented, healthy subjects (age: 51-82 years). The predictive value of age, sex, verbal fluency performance and years of education for the cortical hemodynamics was assessed using multiple regression analyses. Age predicted bilaterally reduced inferior frontal junction (IFJ) and increased middle frontal and supramarginal gyri activity in both task conditions. Years of education as well as sex (IFJ activation in females > males) partly predicted opposite effects on activation compared to age, while task performance was not a significant predictor. All predictors showed small effect sizes (-.24 < β < .22). Middle frontal and supramarginal gyri activity may compensate for an aging-related decrease in IFJ recruitment during verbal fluency. The findings of aging-related (compensatory) cortical reorganization of verbal fluency processing might, in combination with other (risk) factors and using longitudinal observations, help to identify neurodegenerative processes of Alzheimer's disease, while individuals are still cognitively healthy. (3) Individual anatomical or systemic physiological sources of variance may hamper the interpretation of fNIRS signals as neural correlates of cortical functions and their association with individual personality traits. Using simultaneous fNIRS and functional magnetic resonance imaging (fMRI) of hemodynamic responses elicited by an intertemporal choice task in 20 healthy subjects, variability in crossmodal correlations and divergence in associations of the activation with trait "sensitivity to reward" (SR) was investigated. Moreover, an impact of interindividual anatomy and scalp fMRI signal fluctuations on fNIRS signals and activation-trait associations was studied. Both methods consistently detected activation within right inferior/middle frontal gyrus, while fNIRS-fMRI correlations showed wide variability between subjects. Up to 41% of fNIRS channel activation variance was explained by gray matter volume (simulated to be) traversed by near-infrared light, and up to 20% by scalp-cortex distance. Extracranial fMRI and fNIRS time series showed significant temporal correlations at the temple. Trait SR was negatively correlated with fMRI but not fNIRS activation elicited by immediate rewards of choice within right inferior/middle frontal gyrus. Higher trait SR increased the correlation between extracranial fMRI signal fluctuations and fNIRS signals, suggesting that task-evoked systemic arousal-effects might be trait-dependent. Task-related fNIRS signals might be impacted by regionally and individually weighted sources of anatomical and systemic physiological error variance. Traitactivation correlations might be affected or biased by systemic physiological arousal-effects, which should be accounted for in future fNIRS studies of interindividual differences.
Replication-competent oncolytic viral therapies have shown great promise preclinically and in clinical trials for the treatment of various cancers. They are able to preferentially and selectively propagate in cancer cells, consequently destroying tumor tissue via cell lysis, while leaving noncancerous tissues unharmed. Currently, biopsy is the gold standard for monitoring of viral tumor colonization and oncolysis. This may be feasible in preclinical or early clinical trials; however, a noninvasive method facilitating ongoing monitoring of viral therapy is needed for human studies. The tracking of viral delivery could give clinicians the ability to assess the biodistribution of oncolytic viruses to ensure safety and correlation with treatment efficacy. This work centers on the construction and testing of a VACV strain, GLV-1h153, carrying the human sodium iodide symporter (hNIS) as a marker gene for non-invasive tracking of virus by imaging. Thus, this project aimed to help develop imaging techniques for use in clinical trials of oncolytic viral therapy. Further, the feasibility and effectiveness of virally induced targeted radiotherapy as an anti-cancer strategy was also investigated. hNIS is an intrinsic plasma membrane protein which mediates the active transport and concentration of iodide in the thyroid gland and some extra-thyroidal tissues. It is also one of several human genes currently being used as reporters in preclinical studies and has already been used in clinical studies for imaging viral replication in prostate cancer. hNIS gene transfer via viral vector may allow infected tumor cells to concentrate several carrier-free radionuclide probes such as Iodide-124 (124I), Iodide-131 (131I), and 99m-Technecium Pertechtenate (99mTcO4), which have long been approved for human use. hNIS also has the advantage of being of human origin thus minimizing immunogenicity, and its transporter based system allows intracellular signal amplification. GLV-1h153 was tested in pancreatic adenocarcinoma cell line PANC-1. GLV-1h153 infected, replicated within, and killed PANC-1 cells in cell culture as efficiently as GLV-1h68 and provided dose-dependent levels of hNIS transgene expression in infected cells. Immunofluorescence detected successful transport of the protein to the cell membrane prior to cell lysis, which enhanced dose and time-dependent intracellular uptake of 131I. In vivo, GLV-1h153 was as safe and effective as GLV-1h68 in regressing pancreatic cancer xenografts. Tumor infection by virus was confirmed via optical imaging and histology. GLV-1h153 further facilitated deep tissue imaging of virus replication in tumors via Iodide-124I positron emission tomography (PET) as well as 99mTcO4-mediated gamma scintigraphy. This was possible with both intratumoral and intravenous injection of the virus with radiouptake retained as long as 24 and 48 hours after radiotracer injection. PET image quantitation of radiouptake in tumors was found to correlate well with tissue radiouptake counts. Autoradiography of GLV-1h153-infected tumors revealed a need for presence of virus (visualized with green fluorescent protein expression), viable tissue, and adequate blood flow to enhance radiouptake in tumors. Dosimetric analysis of uptake in infected tumors displayed potential for therapeutic doses of radiotherapy to be delivered systemically to tumors. When GLV-1h153 was combined with 131I for treatment, a modest additive effect was seen as compared to GLV-1h153 alone. Therefore, GLV-1h153 is a promising new candidate for treating pancreatic cancer and noninvasively imaging viral therapy. These findings warrant further investigation into possible long term monitoring of viral therapy, as well as synergistic or additive effects of radioiodine combined with this novel treatment and imaging modality.