All conference submissions

To investigate the dosimetric and radiobiological advantages of repurposing a standard kilovoltage (kV) X-ray source for the treatment of nonmelanoma skin cancer. This study assessed the kV X-ray beam character and plan quality i...

Objective assessment of radiotherapy plans is challenging because expert assessment relies on complex, multidimensional tradeoffs that are not fully captured by predefined dose-volume constraints. This study aims to quantitativel...

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...

Accurate delineation of the gross tumor volume of the primary lesion (GTVp) during radiotherapy is essential for ART, particularly in head-and-neck cancer where tumor regression and anatomical deformation occur during treatment....

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...

To implement a full abdominal motion model that combines respiration with gastrointestinal (GI) motility and quantify its interplay impact in pencil-beam scanning (PBS) proton therapy.

To introduce and evaluate a rotational phantom that enables full‑angle patient‑specific QA (PSQA) in proton therapy using a standard, commercially available ion‑chamber‑based detector. The focus of this work is to develop an angl...

To propose a full-range dose automatic Phantom-less QCT bone mineral density (BMD) calibration algorithm, aiming to address the increased BMD measurement error caused by non-linear changes in CT values under different CT scan dos...

To develop and validate a contour-regulated automated registration framework for correcting motion artifacts and aligning time-resolved scans in liver CT perfusion (CTp) series.

Size-specific dose estimates (SSDE) are essential for personalized CT dose management; however, implementation in routine clinical workflows remains challenging. Existing automated approaches based on axial CT images are often co...

VMAT planning for prostate cancer in Elekta Monaco can be slow and variable due to differences in planner experience. Existing automation tools often depend on external prediction models or provide limited optimization support. W...

To evaluate the dosimetric benefit of incorporating MR-based functional dose objectives into liver stereotactic body radiation therapy (SBRT) planning.

This study investigates correction factors commonly used in calculating peak skin dose (PSD) from IR procedures. Specifically, it examines 1- effect of patient-induced compression of the table/pad on transmission factors and, 2-...

To improve immobilization of Gamma Knife patients' heads by limiting pronation motion through dental fixation, thereby enabling shorter treatment times, more accurate dose delivery, and enhanced patient comfort.

Monte Carlo particle transport simulations are essential in medical physics, including radiotherapy, nuclear imaging, detector development, and radiobiology. However, traditional Monte Carlo workflows remain difficult to scale, a...

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...

Radiotherapy in patients with temporomandibular joint reconstruction (TMJR) prostheses introduces unique dosimetric challenges due to the interaction between the radiation beam and high-density implant materials. Different eTMJR...

Deep learning–based dose prediction models have demonstrated high accuracy in multi-institutional challenges; however, their performance under real-world institutional domain shift remains unclear. This study evaluates the genera...

Augment immunogenic photothermal therapy (PTT) with a novel near-infrared (NIR) plasmonic nanoparticle platform to investigate photothermal immunotherapy treatment schemes. By leveraging the photothermal stability and biocompatib...

To generate physiologically plausible 4D medical image sequences from extremely sparse inputs by integrating external breathing signals, overcoming the limitation of requiring dense supervision in current spatiotemporal interpola...

Inferior CBCT quality from artifacts or incomplete data can compromise anatomy visualization during Image-Guided Radiotherapy (IGRT), increasing uncertainty in target localization and organ-at-risk positioning. Improving CBCT rec...

Proton pencil beam scanning (PBS) spot profiles are traditionally modeled using orthogonal X and Y profiles. In-air measurements may exhibit asymmetry and rotation. This study evaluates whether rotation-aware elliptical spot char...

To demonstrate an automated workflow for fiducial marker tracking using online daily CBCT data and to characterize the geometric limitations of utilizing offline CT-sim fiducial centroids for the Varian TrueBeam triggered-imaging...

This study evaluates a commercial web-based AI model for auto-segmentation of pelvic sites by comparing its contours to expert ground truth and an alternative AI model, emphasizing its accuracy and clinical relevance for radiothe...