All conference submissions

The escalating global burden of cancer necessitates reliable and broadly generalizable automated treatment planning (ATP) systems. Current data-driven ATP approaches often exhibit insufficient generalization when applied to diver...

To survey current clinical practice, assess priorities, and identify resource gaps related to environmental sustainability in medical imaging physics.

While transrectal ultrasound (TRUS) is the primary modality for guidance and planning in high-dose-rate prostate brachytherapy (HDR-BT), magnetic resonance imaging (MRI) is required for identifying and targeting the dominant intr...

While PET-CT imaging holds promise for simulation-free radiotherapy workflows, its inherent image resolution limits its use for accurate tumor and organ-at-risk (OAR) contouring. This study aims to enhance the spatial resolution...

Accurate prediction of radiotherapy toxicity requires integrating heterogeneous data, including 3D dose distributions, patient anatomy, and unstructured clinical text. We developed a multimodal pipeline that couples deep learning...

Standard Cone-Beam CT (CBCT) has limited utility in longitudinal lung tumor response assessment due to the presence of motion artifacts. Our proposed method of motion-compensated Simultaneous Algebraic Reconstruction Technique (m...

Deformable image registration (DIR) in medical imaging remains inherently ill-conditioned due to structural ambiguities and weak anatomical constraints. Although foundation models (FMs) have shown strong promise for unsupervised...

This study proposes a transformer-based deep learning framework for markerless lung tumor tracking that improves localization accuracy, robustness, and computational efficiency of real-time intrafraction motion management for sea...

To develop a Monte Carlo (MC)-based approach for generating transit dosimetry prediction images for volumetric modulated arc therapy (VMAT) online adaptive radiotherapy (OART) on a ring gantry linac featuring an advanced cone bea...

Phase II and III clinical trials establish standards of care in radiation oncology; however, achieving equivalent clinical outcomes in routine practice depends on the reproducible implementation of trial protocols. We systematica...

Interrupted patient treatments that are split into multiple partially delivered trajectory log files for a given field may be most susceptible to Linac delivery errors. The AAPM TG-100 recommends independent QA checks to prevent...

To develop and evaluate a treatment planning and optimization framework for internal boron neutron capture therapy (internal BNCT) using a miniaturized neutron tube for the treatment of glioblastoma, and to quantify its dosimetri...

Stereotactic radiosurgery (SRS) plan optimization requires balancing high-quality dosimetry and treatment efficiency. This study compares treatment plan quality between the recently launched Zap-Axon optimizer and the Leksell Gam...

To evaluate the dosimetric accuracy of plans calculated on the Varian TrueBeam HyperSight cone beam CT (CTHS) imager upgrade compared to current fan beam simulation CT (CTSim) solutions towards online adaptive radiotherapy.

Knowledge-based planning tools like RapidPlan (RP) estimate dose-volume histograms (DVH) for organs-at-risk based on anatomical features and historical data. DVH estimates can then be used to guide treatment planning. However, pl...

The HyperSight 6-second rapid scan has been used clinically for internal-target-volume(ITV) definition. However, limited temporal sampling may lead to ITV underestimation, particularly for irregular motion. Using a joint dynamic...

Model the therapeutic effects of chemotherapy, radiotherapy, and chemoradiotherapy to study the heterogeneous responses of pancreatic cancer patient-derived tumor organoids (PDTOs).

Conventional methods for testing proton pencil-beams require multiple quality assurance tools that lack efficiency and spatiotemporal resolutions. Here, we used our efficient ultra-high-resolution scintillation imaging system to...

To determine the Type-B uncertainty of dose calculations using a Monte-Carlo model of a clinical linac and to quantify the contributions of different sources of uncertainty.

To develop and characterize a lost-cost, 3D-printed, patient-specific electron cutout filled with steel ball bearings (BBs) for use with Elekta linear accelerators, and to assess current electron radiotherapy (ERT) practices and...

To use ultrasonic methods to measure FLASH-beam dose distributions within irradiated water, thereby to validate ultrasonic phase-shift methods for FLASH dosimetry and, ultimately, to differentiate regions where FLASH thresholds a...

In image-guided radiation therapy (IGRT), cone-beam CT (CBCT) reconstruction typically requires 300–600 projections to achieve acceptable image quality, which contributes to imaging dose and acquisition time. This study investiga...

To evaluate the prognostic value of deep learning–derived spatial uncertainty in locoregionally advanced nasopharyngeal carcinoma (LA-NPC).

Multiscale treatment response prediction in advanced NSCLC enables spatially informed dose painting, yet prediction point estimates alone do not convey the uncertainty required for adaptive therapy decision support. We developed...