University of Calgary

To quantify the geometric accuracy of an automatic applicator anchor point placement framework for cervical cancer (CC) high-dose-rate (HDR) brachytherapy implemented in Oncentra Brachy (Elekta).

HyperArc is an automated planning and delivery technique for single and multiple-target stereotactic radiosurgery (SRS) treatments that creates highly conformal plans and has potential for saving time. This study evaluates whether HyperArc SRS plans have a no...

To optimize a curve-fitting model for quantitative T1-mapping via inversion recovery (IR) sequences considering varying numbers of data points. For clinical applications, higher resolution and shorter scan times are desired.

To investigate dose calculations in low-density media and identify potential clinical impacts on lung stereotactic body radiation therapy (SBRT) patients.

Professional

MRI-based radiomics can provide a PET-free way to estimate amyloid burden using MRI data alone. However, variability in radiomics feature stability and model performance poses technical challenges. This study examines the stability, reliability, and clinical...

To develop a novel CEST-based MRI technique at 3T for robust Z-spectrum imaging enabling quantitative pH sensitivity in a brain tissue-like phantom.

Geometric distortions in MRI increase with distance from the magnetic isocenter and may impact spatial accuracy in gynecological interstitial brachytherapy (ISBT). This is particularly relevant for ISBT techniques, such as the Syed-Neblett template, where nee...

Craniospinal irradiation (CSI) can be delivered using a multi-isocentre technique. This requires a time-consuming alignment process using kV orthogonal imaging followed by cone-beam CT (CBCT) to ensure alignment accuracy across multiple anatomical regions. Su...

To demonstrate feasibility of three-dimensional ultrasound (3DUS) for the detection of oral squamous cell carcinoma (OSCC) and to evaluate its potential as a pre-clinical screening tool.

To determine if Artificial Intelligence (AI) deep learning models can infer patient ethnicity from screening mammograms, and to identify the image features enabling this inference.

To improve lung-sparing for multi-isocentric total body irradiation (TBI) in adult-sized patients while preserving target coverage, and to determine mean lung dose (MLD) and target maximum dose (PTV D1cc) as a function of body dimensions.

To optimize diffusion-kurtosis imaging (DKI) MRI acquisitions for improved time efficiency while preserving quantitative data fidelity, enabling the future integration of DKI into cancer-care workflows for RT treatment planning and disease tracking.

To evaluate the relationship between quantitative MRI relaxation parameters (T1, T2, T*2, and T'2) at 3T and hypoxia level in three-dimensional (3D) cancer cell spheroids under controlled in-vitro conditions, using western blot measurements as biological grou...

To optimize a Fricke xylenol orange (FXO) gel formulation for high-sensitivity readout using optical computed tomography (optical CT) and magnetic resonance imaging (MRI), and to quantitatively demonstrate that MRI-based readout provides three-dimensional (3D...

Over the past two decades Radiation Therapy has become increasingly reliant on complex software systems, locally developed scripts and spreadsheets. Recent advances in AI technology suggest that this reliance will only increase in the future. While software e...