Improving Radiotherapy Targeting for Cancer Treatment Through Space and Time

Radiotherapy is a common medical treatment in which lethal doses of ionizing radiation are preferentially delivered to cancerous tumors. In external beam radiotherapy, radiation is delivered by a remote source which sits several feet from the patient\u27s surface. Although great effort is taken in properly aligning the target to the path of the radiation beam, positional uncertainties and other errors can compromise targeting accuracy. Such errors can lead to a failure in treating the target, and inflict significant toxicity to healthy tissues which are inadvertently exposed high radiation doses. Tracking the movement of targeted anatomy between and during treatment fractions provides valuable localization information that allows for the reduction of these positional uncertainties. Inter- and intra-fraction anatomical localization data not only allows for more accurate treatment setup, but also potentially allows for 1) retrospective treatment evaluation, 2) margin reduction and modification of the dose distribution to accommodate daily anatomical changes (called `adaptive radiotherapy\u27), and 3) targeting interventions during treatment (for example, suspending radiation delivery while the target it outside the path of the beam). The research presented here investigates the use of inter- and intra-fraction localization technologies to improve radiotherapy to targets through enhanced spatial and temporal accuracy. These technologies provide significant advancements in cancer treatment compared to standard clinical technologies. Furthermore, work is presented for the use of localization data acquired from these technologies in adaptive treatment planning, an investigational technique in which the distribution of planned dose is modified during the course of treatment based on biological and/or geometrical changes of the patient\u27s anatomy. The focus of this research is directed at abdominal sites, which has historically been central to the problem of motion management in radiation therapy

Development, Validation and Applications of MRI-Only Treatment Planning in Radiotherapy

Magnetic resonance imaging (MRI) has superior soft tissue visualization to guide radiotherapy treatment planning but does not provide the electron density information required for the dose calculation. Thus, MRI has been used in a complementary way, registering to the gold standard computed tomography (CT) scan. Development of methods to allow accurate planning from the MRI images would remove the requirement for additional (CT) scans as well as improve clinical workflow and remove potential registration errors. Various methods have been reported to generate datasets with electron density information from MRI data, with these being termed substitute, synthetic or pseudo CT (sCT) datasets. This thesis explores the potential variation in planning and optimization error from MRI-only treatment planning for a range of situations. sCT generation was explored with a deep learning methodology applied to a set of retrospective H&N patient data. A lung MRI sequence was investigated for its potential application for sCT generation, with various methods trialed and assessed for clinical suitability. For an existing sCT generation method used clinically for prostate cancer treatment planning, a time-reduced MRI sequence was investigated, optimizing scan parameters for this by initial assessment in a volunteer cohort, followed by clinical validation in a patient cohort. A pancreas MRI volunteer study was also conducted to investigate internal organ motion effects on treatment planning and potential treatment delivery to assess the suitability of treatment regimes for pancreatic cancer patients. This work provides evidence that MRI-only treatment planning is achievable and acceptably accurate. This has led to current and future implementations of findings into clinical practice locally, and potentially more widely. MRI-only treatment planning in radiotherapy could lead to improved patient outcomes, via both better target delineation and reduced normal tissue toxicity