Relevant Degree Programs
Graduate Student Supervision
Doctoral Student Supervision (Jan 2008 - May 2019)
Introduction: Stereotactic Radiosurgery is the delivery of a large, highly focused radiation dose to well defined targets. This thesis explores linac-based inverse planning algorithms that can be implemented to improve the dosimetric and delivery performance of volumetric modulated arc therapy treatments for these indications.Methods: In this work, algorithms for couch-gantry and collimator-gantry trajectory optimization were developed. Treatment plans calculated with these algorithms were compared dosimetrically to conventional methods used for treatment planning. Additionally, the clinical feasibility of the methods developed were tested by performing end-to-end patient-specific quality assurance on prospective treatments and by developing machine specific quality assurance for the intra-treatment movement of the couch and collimator.Results: This thesis introduces a robust method for optimizing the trajectory of the couch by delivering treatments along patient generalized trajectories. These treatments were able to dosimetrically outperform dynamic conformal arcs, and had higher delivery efficiency than multi-arc volumetric modulated arc therapy. Similarly, collimator trajectory optimization was shown to reduce the dose bath when compared with the clinical standard of care. These methods were shown to be safe for delivery using phantom verification studies.Conclusion: This thesis outlines methods for stereotactic radiosurgery which showdosimetric improvement over previous methodology and are clinically feasible.
Cancers treated with radiotherapy must be adequately irradiated to suppress growth at the site of origin. To achieve doses high enough to attain ‘local control’ and inhibit growth of metastases, surrounding normal tissues are selectively co-irradiated. Current clinical practice for head-and-neck cancers involves salivary gland irradiation. Threshold doses that minimize adverse induced toxicities are currently based on whole-organ mean dose. Modern radiation delivery techniques are able to sculpt the dose profile to accommodate sub-organ irradiation, but knowledge of the relative importance of sub-organ structures remains unknown. As tissue-sparing techniques improve, assessment of the normal tissue toxicity risk becomes increasingly important. Loss of salivary function and xerostomia (subjective dry mouth) are common normal tissue toxicities in head-and-neck cancer patients. Radiotherapy-induced dysfunction and xerostomia can drastically reduce oral hygiene and health and may negatively impact the ability to eat, speak, sleep, or swallow. These pervasive toxicities detract from overall quality of life and can be permanent, perpetuating the negative impact. The purpose of this work is to quantify the relative importance of spatial regions within the major salivary glands for late salivary function (i.e., ‘regional effects’). The ultimate aim is to improve knowledge of toxicity risk. Broad regional effects have been noted in rat parotid, and it has recently been claimed that a localized ‘critical region’ has been located in human parotid glands. Furthermore, a morphological dependence on the dose profile has been noted for subjective xerostomia. Clinical trials involving lobe and region sparing are underway, yet comprehensive quantification of the importance of sub-organ structures remains unknown. To this end, the association between radiation dose delivered to regions within the largest salivary glands and measurements of whole-mouth salivary flow is quantified. Independent analysis procedures are developed that are capable of quantifying the relative importance of sub-segments. Evidence is found that sub-segments are inhomogeneously important for maintenance of late salivary flow, with the caudal parotid aspects having greatest importance. An imaging protocol is developed which may help pinpoint specific tissues or functional units residing within these regions.
In the radiation therapy of high-grade gliomas, T1-weighted magnetic resonance imaging (MRI) with contrast enhancement does not accurately represent the extent of the tumour. Functional imaging techniques, such as positron emission tomography (PET) and diffusion tensor imaging (DTI), can potentially be used to improve tumour localization and for biologically-based treatment planning. This project investigated tumour localization using 3,4-dihydroxy-6-[¹⁸F]fluoro-L-phenylalanine (¹⁸F-FDOPA) PET and interhemispheric difference images obtained from DTI, and determined whether radiation therapy of high-grade gliomas using dose painting was feasible with volumetric modulated arc therapy (VMAT). First, radiation therapy target volumes obtained from five observers using ¹⁸F-FDOPA PET and MRI were compared with the location of recurrences following radiotherapy. It was demonstrated with simultaneous truth and performance level estimation that high-grade glioma radiation therapy target volumes obtained with PET had similar interobserver agreement to MRI-based volumes. Although PET target volumes were significantly larger than volumes obtained using MRI, treatment planning using the PET-based volumes may not have yielded better treatment outcomes since all but one central recurrence extended beyond the PET abnormality. The second study characterized the distribution of fractional anisotropy (FA) and mean diffusivity (MD) values obtained from DTI, as well as FA and MD interhemispheric differences. It was demonstrated that FA, MD, and interhemispheric differences approached those of contralateral normal brain as the distance from the tumour increased, consistent with the expectation of a gradual and decreasing presence of tumour cells. Lastly, a treatment planning study compared VMAT for high-grade gliomas obtained from dose painting using ¹⁸F-FDOPA PET images. Dose constraints for each contour were specified by a radiobiological model. VMAT planning using dose painting for high-grade gliomas was achieved using biologically-guided thresholds of ¹⁸F-FDOPA uptake with no significant change in the dose delivered to critical structures.
Master's Student Supervision (2010 - 2018)
Tumour tissue is highly heterogeneous with disordered vasculature that is characteristically highly permeable relative to other normal tissue bloodvessels. Non-invasive investigation of tumour vasculature may be achieved using Dynamic Contrast Enhanced MRI (DCE-MRI). Pharmacokinetic modelling of contrast agent uptake can provide information about blood flow and vessel permeability, but modelling is limited due to the ability of typical contrast agents such as Gd-DTPA to extravasate and accumulate in tumour tissue. The hypothesis motivating this work is that DCE-MRI measurements with both high and low molecular weight contrast agent uptake will allow for improved interpretation of the tumour micro-environment. A new high molecular weight contrast agent comprised of hyperbranched polyglycerol (HPG) molecules doubly labelled with gadolinium and a fluorescent marker is characterized, and used along side a standard low molecular weight contrast agent, Gadovist (Bayer Healthcare). Histological data reveals that HPG extravasates slowly from vasculature, and remains near blood vessels over the time-frame of a DCE-MRI experiment. HPG was also found to accumulate in tumour tissue over days, peaking at 2-4 days. HPG was found to be inappropriate for pharmacokinetic modelling, due to relatively low enhancement in the DCE-MRI data. Parameter maps showing bolus arrival time of HPG throughout the tumour show increased sensitivity to necrosis relative to Gadovist. Initial area under the HPG-concentration time curve was found to be correlated with vascular density. Modelling of DCE-MRI data should be performed with a model appropriate to the tissue, contrast agent, and data available. While simpler models are not able to distinguish blood flow from permeability, data quality is not necessarily sufficient to justify the use of a more complex model. This problem is addressed in this work by modelling contrast agent uptake with system of increasingly complex models, and the Akaike information criterion was used to determine that a general two compartment exchange model was more appropriate than the extended Tofts model for pharmacokinetic modelling of DCE-MRI with a standard contrast agent.