All conference submissions

Amid ongoing war, Ukraine continues to maintain and modernize radiation therapy (RT) services. Between 2023 and 2025, 24 linacs were installed to replace aging, non-rechargeable cobalt units. While linacs offer clinical advantage...

This study aims to estimate prostate cancer cell survival following Ac-225-PSMA targeted radionuclide therapy by integrating physiologically based pharmacokinetic (PBPK) modeling, Monte Carlo simulations, and the two-lesion kinet...

To exploit differences in J-coupling evolution of the ≈2 ppm fat allylic protons (neighbor the two ends of the double bond chain) to estimate relative linolenic acid content at 3 T. Oleic (mono-unsaturated), linoleic (di-unsatura...

To quantify the systematic uncertainty introduced to pre-configured beam data if the Effective Point of Measurement (EPOM) proposed in AAPM TG-51 Report-374 is implemented.

To develop and evaluate a data-driven strategy that optimally combines the full set of virtual monoenergetic images (VMIs) from dual-energy CT to construct an optimal image pair for estimating electron density and proton stopping...

Conventional radiotherapy dose (Gy) quantifies deposited energy, but response is influenced by the local radiochemical environment driving indirect DNA damage. Superoxide is a comparatively long-lived paramagnetic radical species...

Deep learning-based image quality assessment (DL-IQA) models are commonly trained using radiologist ratings and may provide a more objective approach to CT image quality evaluation. However, clinical deployment may be limited by...

To evaluate a protocol-agnostic machine learning (PlanAI) (Sun Nuclear, Mirion Medical Company, Florida, USA)1 model for automated treatment planning in external-beam radiotherapy for thoracic cancer.

Understanding chemoradiation resistance remains a major barrier to improving outcomes in head and neck cancer. We developed a multiscale framework linking tumor architecture, cellular network topology, and immune context to thera...

Accurate radiation documentation is essential for assessing patient risk during fluoroscopically guided procedures. Radiation Dose sheets are commonly used but may omit exposure details while DICOM Radiation-Dose-Structured-Repor...

To evaluate the feasibility of using a 4.2 MV imaging beam for simultaneous guidance and biologically enhanced delivery of preoperative stereotactic ablative radiotherapy (SABR) to intact breast tumors loaded with gold nanopartic...

To investigate the inter- and intra-fractional morphological and dosimetric variations in precision radiotherapy for bladder cancer using Fan Beam CT (FBCT) and Electronic Portal Imaging Device (EPID), providing evidence for moti...

RapidArc Dynamic (RAD) introduces static-angle modulated ports (STAMPs) and a rotating collimator. It also incorporates a deterministic optimizer. This study aims to evaluate the independent effects of the optimizer versus these...

Accurate prediction of overall survival (OS) in glioblastoma (GBM) remains challenging in clinical practice. Recently developed foundation models trained on large-scale medical imaging datasets offer a promising strategy to impro...

Surface-guided radiation therapy (SGRT) is increasingly used for high-precision patient setup and intrafraction motion management in radiotherapy clinics, including DIBH workflows. Respiratory signals acquired at simulation may b...

To assess correlations between pediatric radiation exposure rates and commonly used body size surrogates, anteroposterior (AP) or lateral (LAT) thickness, weight, height, body mass index (BMI), body surface area (BSA), and age—fo...

To assess dose calculation accuracy on cone-beam computed tomography (CBCT) images relative to the RayStation CBCT correction framework (CBCTcorr) across multiple CBCT platforms, anatomical sites, and clinical scenarios.

Current automated offline triggers for adaptive radiotherapy often function as black boxes and fail to provide the reasoning behind a decision. Vision Language Models (VLM) offer a novel solution by providing a clear path toward...

To evaluate the motion measurement accuracy of transverse and coronal 3D stack-of-stars MR sequences relative to 4D-CT and physical ground truth, using a phantom undergoing hysteretic and non-hysteretic 3D sinusoidal motion.

To evaluate the feasibility and accuracy of a hyperspectral plastic scintillation detector (PSD) system (Medscint HYPERSCINT QA-200 with PRB-0019 probe)—commonly used for brachytherapy dosimetry—for Gamma Knife (GK) small-field d...

To evaluate the clinical accuracy and utility of a commercial deep learning-based auto-segmentation tool by Siemens for delineating brain metastases (GTV) and organs-at-risk (OAR) on contrast-enhanced MRI.

To examine the subjective and objective image quality (IQ) of a deep learning image reconstruction algorithm (Precise Image Quality Engine (PIQE)) in abdominal CT.

In MRI-only radiotherapy treatment pathways, synthetic CT (sCT) images can be used for dose calculation, but achieving adequate bony detail in the pelvic region remains challenging. This study aimed to evaluate the performance of...

Stereotactic planning for ocular tumors is limited by long optimization times, inter-planner variability, and patient-specific requirements for fractionation, beam energy, and machine configuration. Knowledge-based planning (KBP)...