High-dose-rate (HDR) Magnetic Resonance (MR) guided brachytherapy (BT) is rapidly becoming the standard for treatment of locally advanced cervical cancer, globally. MR is an integral aspect of this treatment, enabling the level of soft tissue visualization required for precise delineation of organ and target contours with respect to the BT applicator or needles during treatment planning. The optimal slice thickness for MR datasets, and the role of super-resolved datasets are questions
yet to be investigated. A digital phantom-based study assessed the impact of slice thickness on volumetric and geometric uncertainties in traditional MR datasets and estimated the resultant dosimetric uncertainty. Datasets with traditional slice thicknesses produced uncertainties up to 27% of the imaged structure volume, and contour uncertainty up to one third of the slice thickness This resulted in the exceeding of the American Association of Physicists in Medicine’s (AAPM) recommended dosimetric uncertainty in HDR BT. Trilinearly interpolated datasets reduced these uncertainties substantially, allowing imaging with 2.7 mm coarser slices while conferring an imaging time reduction of 6 minutes. The results of this thesis demonstrate that the recommended range of slice thicknesses introduces uncertainties on a level known to impact dosimetry more than 9%. Trilinearly interpolated datasets may thus confer benefit in this clinical setting.