University of British Columbia

RayStation’s Fallback Planning (FBP) uses dose mimicking to automatically generate a new radiotherapy plan from an existing plan using a different treatment modality, technique, or unit. This facilitates contingency planning in the event of a non-paired treat...

To predict the occurrence of clinically significant radiation pneumonitis in lung cancer patients using Raman spectroscopy on pre-treatment plasma samples.

Magnetic resonance imaging (MRI) is an important tool for visualizing tumor sites and organs at risk during spine radiation treatment planning. Some people with spinal metastasis require pedicle screw fixation to stabilize the spinal column which causes metal...

Total body irradiation (TBI) requires the entirety of the patient's body to be irradiated, and treatment methods vary greatly across treatment centres. For the majority of techniques, excluding intensity modulated TBI, little is known about the heterogeneity...

To quantify the efficacy of CBCT-guided external beam online adaptive radiotherapy (oART) compared to conventional cervical cancer treatment methods, and to determine the impact of intrafraction anatomical motion on dosimetry.

Accurate 177Lu SPECT quantification is essential for patient-specific dosimetry in radiopharmaceutical therapies. Monte Carlo (MC) based reconstruction uses comprehensive system modeling to stochastically simulate photon transport and detector interactions, p...

Physiologically based pharmacokinetic (PBPK) models used in radiopharmaceutical therapy (RPT) and theranostic digital twins are rapidly increasing in size and mechanistic detail, often containing tens to hundreds of parameters. While such models fit imaging a...

Head-and-neck radiotherapy inadvertently irradiates salivary glands, leading to radiation-induced xerostomia. Diffusion MRI provides sensitivity to radiation-induced microstructural tissue changes. We hypothesize that changes in intravoxel incoherent motion (...

The overarching goal is to develop a novel system for microdosimetry integrated with cellular molecular radiation response using Monte Carlo (MC) simulations, Raman spectroscopy (RS), and radiobiological assays. MC simulations of the system and initial invest...

To investigate internal treatment margins for targets undergoing cardiorespiratory motion with the use of dynamic tracking technology.

AI–based radiomics models for thyroid ultrasound often lack interpretability, limiting clinical trust. This study aims to develop and validate a fully interpretable radiomics framework for thyroid nodule classification by linking quantitative ultrasound featu...

To address the limited robustness of existing CT-based radiogenomic models, this study develops a multicenter framework for non-invasive dual prediction of EGFR and KRAS gene mutations in personalized management of non-small cell lung cancer (NSCLC), comparin...

To develop a Gaussian process regression (GPR) framework that treats along-core HDR prostate brachytherapy dose as a spatially correlated signal, in order to denoise voxel-level dose and dose-uncertainty summaries used for Monte Carlo biopsy dose quality assu...

The integration of radiosensitizing chemotherapeutics with radiotherapy represents a promising strategy to enhance tumor response. However, conventional systemic administration often results in limited tumor drug delivery, reducing radiosensitization while in...

To experimentally characterize low-energy helium-4 (⁴He⁺) ion beams at subclinical energies (0.5–1.5 MeV/u) at the newly commissioned ASPIRE facility at TRIUMF using radiochromic film dosimetry, and to validate the measured dose distributions through Monte Ca...

Radiation pneumonitis (RP) is a dose-limiting toxicity following thoracic radiotherapy. Existing RP prediction models have largely focused on clinical factors and conventional dose-volume histogram (DVH) metrics, with limited consideration of higher-order dos...

Radiopharmaceutical therapies (RPTs) effectively treat metastatic castration-resistant prostate cancer, yet injected radioactivities remain empirically prescribed. Although physiologically-based pharmacokinetic (PBPK) and pharmacodynamic (PD) models can separ...

Existing "one-size-fits-all" approaches in PSMA radiopharmaceutical therapies (RPTs) fail to account for critical inter-patient variabilities, risking under- or over-treatment. To address this, we are developing theranostic digital twins (TDTs) for reliable p...

To perform cohort-level probabilistic quality assurance of biopsy dose thresholds in HDR prostate brachytherapy under a fixed localization-uncertainty model and relate robustness to nominal distance from threshold.

Computational nuclear oncology (CNO) methods are advancing rapidly but often developed in isolated tools and workflows that are difficult to reproduce, compare, and share. This fragmentation limits virtual studies and slows translation of physiologically base...

Magnetic resonance (MR) imaging is routinely used to contour targets for stereotactic radiotherapy planning. However, MR images can suffer from susceptibility-induced geometric distortions, especially near air-tissue interfaces. The objective of this work is...

Lesion tracking establishes correspondence across imaging time points to assess disease evolution and treatment response. Despite registration-, graph-, and AI-based methods across CT, MR, PET, and PET/MR, robust correspondence in whole-body CT remains challe...

Theranostic digital twins (TDTs) are virtual representations of individual patients, that integrate clinical patient history, imaging, and physiologically based pharmacokinetic (PBPK) modeling to simulate radiopharmaceutical therapies (RPTs). Their validation...

Accurate quantitative assessment in positron emission tomography (PET) is essential for reliable lesion characterization and therapy response evaluation. Quantitative accuracy is conventionally investigated using physical phantoms or numerical simulations; ho...

To develop a Raman spectroscopy (RS)-based experimental microdosimetry system capable of read-out of a model system of cells cultured on a radiochromic film (RCF) dosimeter substrate that can measure energy deposited by ionizing radiation within individual ce...

Keynote Events

Automated quantification of tumor burden in PSMA PET/CT imaging is hampered by the low specificity of image-only AI models, which frequently misclassify physiological uptake as disease. This necessitates time-intensive manual corrections, limiting clinical ut...

Clinical Trials Specialty Program

To apply a multiparametric model selection strategy within a tensor radiomics paradigm, whereby different flavours of radiomics features are generated from multiple PET-CT image fusion strategies, to identify reliable and generalizable machine learning (ML) m...

To determine whether radiomic features extracted from normal endocrine organs, when combined with clinical variables, can capture systemic imaging signatures predictive of clinical progression in patients with PSMA-negative prostate cancer.

Assess whether current shielding methods for reducing scattered X-ray radiation in CT scans are appropriate for newer CT technologies, such as systems that use rapidly alternating X-ray tube voltage (fast kVp-switching), tin-filtered, or dual X-ray sources (d...

To develop and evaluate a radiomic phenotyping and multi-lesion aggregation scheme to derive patient-level biomarkers for identifying progressive disease and predicting time-to-progression (TTP) in diffuse large B-cell lymphoma (DLBCL).

To quantify treatment-associated immune density changes in prostate cancer following HDR brachytherapy, and to determine whether Raman spectroscopic signatures of tissue biochemistry may serve as potential biomarkers of immune response.