In 1962, Gross and Lapiere described collagenolytic activity in the degradation of tadpole tails during amphibian metamorphosis. This activity was later attributed to a collagenase enzyme belonging to the matrix metalloproteinase family. Over the past 49 years, steady growth in the field of metalloproteinase biology has uncovered that degradation of extracellular matrix components represents only a fraction of the functions performed by these enzymes. The regulatory roles of these enzymes in numerous aspects of mammalian biology remains poorly understood. This thesis investigates the metalloproteinase ADAM17 and its natural inhibitor TIMP3 in acute and chronic inflammation. My work describes the generation of new murine experimental systems of compartmentalized ADAM17 or TIMP3 deficiency and their applications in acute liver inflammation (i.e. fulminant hepatitis and T-cell mediated autoimmune hepatitis) and atopic dermatitis. Loss of Timp3 protected mice against fulminant hepatic failure caused by activation of the death receptor Fas. We determined that TIMP3 simultaneously promotes pro-apoptotic signaling through TNFR1 while suppressing anti-apoptotic EGFR activation in the liver. Mechanistically, we identified that ADAM17 is critical in shedding TNFR1 and EGFR ligands (e.g. Amphiregulin, HB-EGF, TGF) and extended this finding to clinically relevant drug-induced hepatitis. Adult TIMP3 deficient mice also exhibited spontaneous accumulation of CD4+ T cells in the liver. Consequently, polyclonal T cell activation with the lectin Concanavalin A (con A) in a model of autoimmune hepatitis resulted in accelerated liver injury. We identified that this immunopathology relied on TNF bioavailability as mice lacking both Timp3 and Tnf were resistant to con A. Using bone marrow chimeras we established that non-hematopoietic tissues were the physiologically relevant source of TIMP3 in vivo, thereby highlighting an immunosuppressive role for this stromal metalloproteinase inhibitor in cellular immunity. Finally, we investigated epithelial:immune crosstalk in the epidermis by generating tissue-specific ADAM17 deficiency in basal keratinocytes. These mice developed spontaneous inflammatory skin disease that was physiologically consistent with atopic dermatitis. Focused investigation of keratinocyte-specific signaling deregulated by ADAM17 deficiency revealed its requirement for tonic Notch activation, which in turn antagonized transcriptional activity of AP-1 transcription factors on the promoters of epithelial cytokines TSLP and G-CSF. In summary, these works identify cellular mechanisms governing cytokine-mediated communication between epithelial and immune cells to modulate inflammation. The findings that TIMP3 and ADAM17 act as regulators of key inflammatory, proliferative and developmental pathways provide impetus to expand our understanding of this important family of enzymes in mammalian signal transduction.

BOLD fMRI (Blood-Oxygenation Level Dependent functional Magnetic Resonance Imaging) measures the haemodynamic correlates of brain function, with research and clinical applications. However, fMRI is limited by relatively weak signal, and large, complex noise sources. A variety of preprocessing algorithms have been developed to remove artifacts and improve signal detection, but there is no literature consensus on optimal preprocessing strategies. Furthermore, it is not well understood how fMRI experimental design choices interact with preprocessing steps. This thesis develops a statistical framework for selecting the set of preprocessing choices (“pipelines”), using data-driven metrics of (R) reproducibility of brain maps, and (P) prediction of experimental stimuli. These metrics were used to evaluate standard pipeline steps on data from young healthy subjects, who performed a set of brief tasks in an fMRI cognitive assessment battery. It is shown that (1) preprocessing choices have significant, consistent effects on the detection of brain networks in fMRI. However, (2) optimizing pipelines on a subject- and task-specific basis, compared to the standard fMRI approach of applying a single fixed set of preprocessing choices, improves (P, R) and independent test measures of between-subject activation overlap. This indicates that signal detection in standard fMRI may be limited by sub-optimal pipeline choices. Even after optimizing standard pipeline choices, physiological noise is a major confound in fMRI analysis; this includes BOLD signal changes due to respiration and pulsatile blood flow. As a potential solution, the PHYCAA (PHYsiological correction using Canonical Autocorrelation Analysis) algorithm is developed. This multivariate, data-driven model estimates physiological noise, without respiratory and cardiac measurements. The estimated noise has a spatial distribution consistent with non-neuronal tissues, and its dimensionality is correlated with cardiac and respiratory variability. Removing this physiological noise increases (P, R) of analysis results. The PHYCAA model provides novel information about the structure of physiological noise in fMRI, and a principled method of removing physiological artifact. The results of this thesis were obtained using data from a prototype fMRI cognitive assessment battery, designed for clinical use. The datasets involve brief scanning sessions with complex cognitive tasks. These findings are therefore relevant for clinical implementation of fMRI.

BOLD fMRI (Blood-Oxygenation Level Dependent functional Magnetic Resonance Imaging) measures the haemodynamic correlates of brain function, with research and clinical applications. However, fMRI is limited by relatively weak signal, and large, complex noise sources. A variety of preprocessing algorithms have been developed to remove artifacts and improve signal detection, but there is no literature consensus on optimal preprocessing strategies. Furthermore, it is not well understood how fMRI experimental design choices interact with preprocessing steps. This thesis develops a statistical framework for selecting the set of preprocessing choices (“pipelines”), using data-driven metrics of (R) reproducibility of brain maps, and (P) prediction of experimental stimuli. These metrics were used to evaluate standard pipeline steps on data from young healthy subjects, who performed a set of brief tasks in an fMRI cognitive assessment battery. It is shown that (1) preprocessing choices have significant, consistent effects on the detection of brain networks in fMRI. However, (2) optimizing pipelines on a subject- and task-specific basis, compared to the standard fMRI approach of applying a single fixed set of preprocessing choices, improves (P, R) and independent test measures of between-subject activation overlap. This indicates that signal detection in standard fMRI may be limited by sub-optimal pipeline choices. Even after optimizing standard pipeline choices, physiological noise is a major confound in fMRI analysis; this includes BOLD signal changes due to respiration and pulsatile blood flow. As a potential solution, the PHYCAA (PHYsiological correction using Canonical Autocorrelation Analysis) algorithm is developed. This multivariate, data-driven model estimates physiological noise, without respiratory and cardiac measurements. The estimated noise has a spatial distribution consistent with non-neuronal tissues, and its dimensionality is correlated with cardiac and respiratory variability. Removing this physiological noise increases (P, R) of analysis results. The PHYCAA model provides novel information about the structure of physiological noise in fMRI, and a principled method of removing physiological artifact. The results of this thesis were obtained using data from a prototype fMRI cognitive assessment battery, designed for clinical use. The datasets involve brief scanning sessions with complex cognitive tasks. These findings are therefore relevant for clinical implementation of fMRI.

Shear wave (SW) imaging is an ultrasound elastogrpahy technique for estimating the elastic properties of biological tissues. Increasing the frequency would improve both the confinement of the radiation force generating the shear wave, and the imaging spatial resolution. The objectives of the study were to realize a simple high frequency (HF) system for the generation and detection of SW propagation and to implement this system to develop and characterize tissue-mimicking gelatin phantoms (TMGP) for HF SWI with elastic properties in the range of those encountered in biological tissue. A 5 MHz and 10 MHz focused transducer were used to induced SW’s in TMGP ranging from 4% to 12% gelatin with 3% silica for scattering and a 25 MHz single-element focused transducer recorded pulse-echo signals in order to capture the SW. The shear wave speeds in the TMGP were found to range linearly from 1.59-4.59 m/s in the 4% to 12% gelatin samples.

Shear wave (SW) imaging is an ultrasound elastogrpahy technique for estimating the elastic properties of biological tissues. Increasing the frequency would improve both the confinement of the radiation force generating the shear wave, and the imaging spatial resolution. The objectives of the study were to realize a simple high frequency (HF) system for the generation and detection of SW propagation and to implement this system to develop and characterize tissue-mimicking gelatin phantoms (TMGP) for HF SWI with elastic properties in the range of those encountered in biological tissue. A 5 MHz and 10 MHz focused transducer were used to induced SW’s in TMGP ranging from 4% to 12% gelatin with 3% silica for scattering and a 25 MHz single-element focused transducer recorded pulse-echo signals in order to capture the SW. The shear wave speeds in the TMGP were found to range linearly from 1.59-4.59 m/s in the 4% to 12% gelatin samples.

Dual-energy (DE) x-ray imaging of the chest decomposes two radiographs acquired at low- and high x-ray energies into 'soft-tissue' and 'bone' images, reducing the influence of background anatomical noise and providing increased conspicuity of subtle underlying structures compared to conventional radiography. This thesis derives a quantitative theoretical model of imaging performance in DE x-ray imaging and employs the resulting framework to system optimization in thoracic imaging. Fourier domain metrics of signal and noise performance - including the noise-power spectrum (NPS), modulation transfer function (MTF), detective quantum efficiency (DQE), and noise-equivalent quanta (NEQ) - were computed using cascaded systems analysis extended to DE imaging and combined with a quantitative model of imaging task to yield estimates of detectability across a broad range of DE image acquisition and decomposition techniques. Specifically, the detectability index provided an objective function for optimizing the selection of kVp pair, added filtration, allocation of dose between low- and high- energy views, and choice of decomposition algorithm and parameters therein. Theoretical calculations were validated in comparison to measurements of NPS, MTF, DQE, and NEQ performed on an experimental DE imaging system and through human observer studies for a variety of imaging tasks. Overall, the detectability index was found to provide a reliable predictor of human observer performance. Results identified optimal DE image acquisition and decomposition techniques that boost detectability beyond that achieved by conventional radiography or other DE imaging approaches, in many cases boosting conspicuity of subtle lesions from barely visible to highly conspicuous at fixed dose to the patient. The results are particularly encouraging, as such performance was achieved with the DE imaging dose equivalent to that of a single chest radiograph. The theoretical framework provided a valuable guide to optimization of a clinical prototype for high-performance DE chest imaging and may be extended to other DE imaging approaches, such as DE mammography and DE computed tomography.

Real-time feedback of absorbed dose at a point within a patient can help with radiological quality assurance and innovation. Two radiochromic materials from GafChromic MD-55 and EBT films have been investigated for applicability in real-time in vivo dosimetry of ionizing radiation. Both films were able to produce a real-time measurement of optical density from a small volume, allowing positioning onto a tip of an optical fibre in the future. The increase in optical density was linear with absorbed dose for MD-55, and non-linear for EBT. The non-linearity of EBT is associated with its increased sensitivity to ionizing radiation compared to MD-55, thus reaching optical saturation at a much lower dose. The radiochromic material in EBT film was also shown to polymerize and stabilize faster, decreasing dose rate dependence in real-time measurements in comparison to MD-55. The response of the two media was tested over 75 kVp – 18 MV range of x-ray beams. The optical density measured for EBT was constant within 3% throughout the entire range, while MD-55 exhibited a nearly 40% decrease at low energies. Both materials were also shown to be temperature sensitive, with the change in optical density generally decreasing when the temperature increased from ~22°C to ~37°C. This was accompanied by a shift in the peak absorbance wavelength. It was illustrated that some of this decrease can be corrected for by tracking the peak position and then multiplying the optical density by a correction factor based on the predicted temperature. Overall, the radiochromic material in GafChromic EBT film was found to be a better candidate for in vivo real-time dosimetry than the material in GafChromic MD-55. A novel mathematical model was proposed linking absorbance to physical parameters and processes of the radiochromic materials. The absorbance at every wavelength in the spectrum was represented as a sum of absorbances from multiple absorbers, where absorbance is characterized by its absorption coefficient, initiation constant, and polymerization constant. Preliminary fits of this model to experimental data assuming two absorbers suggested that there is a trade-off between EBT’s greater sensitivity and its dose linearity characteristics. This was confirmed by experimental results.

Increased glucose metabolism may occur in malignant tumours due to altered gene expression or a response to hypoxia. It has been shown that tumours with high levels of glycolysis, indicated by elevated lactate, are less responsive to radiotherapy. It is not clear whether this effect is caused by lactate itself or rather that high lactate is a surrogate for a radioresistant property such as hypoxia. Furthermore, we are not aware of studies that examine the manipulation of lactate production in tumours to alter radiation response. We propose a novel approach of metabolic targeting of HIF-1 to address these issues. HIF-1 is a major regulator of glycolysis and its inhibition would decrease malignant cell metabolism and could lead to a decrease in lactate production. The goal of this pre-clinical study was to evaluate metabolic targeting as a strategy of enhancing radiation response by inhibiting the HIF-1 transcription factor.

Real-time feedback of absorbed dose at a point within a patient can help with radiological quality assurance and innovation. Two radiochromic materials from GafChromic MD-55 and EBT films have been investigated for applicability in real-time in vivo dosimetry of ionizing radiation. Both films were able to produce a real-time measurement of optical density from a small volume, allowing positioning onto a tip of an optical fibre in the future. The increase in optical density was linear with absorbed dose for MD-55, and non-linear for EBT. The non-linearity of EBT is associated with its increased sensitivity to ionizing radiation compared to MD-55, thus reaching optical saturation at a much lower dose. The radiochromic material in EBT film was also shown to polymerize and stabilize faster, decreasing dose rate dependence in real-time measurements in comparison to MD-55. The response of the two media was tested over 75 kVp – 18 MV range of x-ray beams. The optical density measured for EBT was constant within 3% throughout the entire range, while MD-55 exhibited a nearly 40% decrease at low energies. Both materials were also shown to be temperature sensitive, with the change in optical density generally decreasing when the temperature increased from ~22°C to ~37°C. This was accompanied by a shift in the peak absorbance wavelength. It was illustrated that some of this decrease can be corrected for by tracking the peak position and then multiplying the optical density by a correction factor based on the predicted temperature. Overall, the radiochromic material in GafChromic EBT film was found to be a better candidate for in vivo real-time dosimetry than the material in GafChromic MD-55. A novel mathematical model was proposed linking absorbance to physical parameters and processes of the radiochromic materials. The absorbance at every wavelength in the spectrum was represented as a sum of absorbances from multiple absorbers, where absorbance is characterized by its absorption coefficient, initiation constant, and polymerization constant. Preliminary fits of this model to experimental data assuming two absorbers suggested that there is a trade-off between EBT’s greater sensitivity and its dose linearity characteristics. This was confirmed by experimental results.

Dual-energy (DE) x-ray imaging of the chest decomposes two radiographs acquired at low- and high x-ray energies into 'soft-tissue' and 'bone' images, reducing the influence of background anatomical noise and providing increased conspicuity of subtle underlying structures compared to conventional radiography. This thesis derives a quantitative theoretical model of imaging performance in DE x-ray imaging and employs the resulting framework to system optimization in thoracic imaging. Fourier domain metrics of signal and noise performance - including the noise-power spectrum (NPS), modulation transfer function (MTF), detective quantum efficiency (DQE), and noise-equivalent quanta (NEQ) - were computed using cascaded systems analysis extended to DE imaging and combined with a quantitative model of imaging task to yield estimates of detectability across a broad range of DE image acquisition and decomposition techniques. Specifically, the detectability index provided an objective function for optimizing the selection of kVp pair, added filtration, allocation of dose between low- and high- energy views, and choice of decomposition algorithm and parameters therein. Theoretical calculations were validated in comparison to measurements of NPS, MTF, DQE, and NEQ performed on an experimental DE imaging system and through human observer studies for a variety of imaging tasks. Overall, the detectability index was found to provide a reliable predictor of human observer performance. Results identified optimal DE image acquisition and decomposition techniques that boost detectability beyond that achieved by conventional radiography or other DE imaging approaches, in many cases boosting conspicuity of subtle lesions from barely visible to highly conspicuous at fixed dose to the patient. The results are particularly encouraging, as such performance was achieved with the DE imaging dose equivalent to that of a single chest radiograph. The theoretical framework provided a valuable guide to optimization of a clinical prototype for high-performance DE chest imaging and may be extended to other DE imaging approaches, such as DE mammography and DE computed tomography.