Related papers: Adaptive Proton Therapy Using CBCT-Guided Digital …

Despite best efforts, various challenges remain in the creation and maintenance processes of digital twins (DTs). One of those primary challenges is the constant, continuous and omnipresent evolution of systems, their user's needs and their…

Recent studies suggest that 4DCT is unable to accurately measure respiratory-induced pancreatic tumor motion. In this work, we assessed the daily motion of pancreatic tumors treated with SBRT, and developed adaptive strategies to predict…

Accurately modeling the spatiotemporal evolution of tumor morphology from baseline imaging is a pre-requisite for developing digital twin frameworks that can simulate disease progression and treatment response. Most existing approaches…

Purpose: Organ-at-risk (OAR) delineation is a key step for cone-beam CT (CBCT) based adaptive radiotherapy planning that can be a time-consuming, labor-intensive, and subject-to-variability process. We aim to develop a fully automated…

Background: FLASH radiation therapy (FLASH-RT) uses ultra-high dose rates to induce the FLASH effect, enhancing normal tissue sparing. In proton Bragg peak FLASH-RT, this effect is confined to high-dose regions near the target at deep…

We present a novel application of Tensor Network methods in cancer treatment as a potential tool to solve the dose optimization problem in radiotherapy. In particular, the Intensity-Modulated Radiation Therapy (IMRT) technique - that allows…

We propose a fast beam orientation selection method, based on deep neural networks (DNN), capable of developing a plan comparable to those by the state-of-the-art column generation method. The novelty of Our model lies in its supervised…

Purpose: The importance of robust proton treatment planning to mitigate the impact of uncertainty is well understood. However, its computational cost grows with the number of uncertainty scenarios, prolonging the treatment planning process.…

Optimizing modern wireless networks is exceptionally challenging due to their high dynamism and complexity. While the agentic artificial intelligence (AI) powered by reinforcement learning (RL) offers a promising solution, its practical…

Heterogeneous treatment effect estimation in high-stakes applications demands models that simultaneously optimize precision, interpretability, and calibration. Many existing tree-based causal inference techniques, however, exhibit high…

Base station (BS) association and beam selection in multi-cell drone corridor networks present unique challenges due to the high altitude, mobility and three-dimensional movement of drones. These factors lead to frequent handovers and…

Computer tomography is one of the most promising new methods to image abnormal tissues inside the human body. Tomography is also used to position the patient accurately before radiation therapy. Hadron therapy for treating cancer has become…

Digital Twin (DT) technology has emerged as a transformative approach in healthcare, but its application in personalized patient care remains limited. This paper aims to present a practical implementation of DT in the management of chronic…

Dynamic treatment regimes (DTR) are sequential decision rules corresponding to several stages of intervention. Each rule maps patients' covariates to optional treatments. The optimal dynamic treatment regime is the one that maximizes the…

Background: Daily or weekly cone-beam computed tomography (CBCT) scans are commonly used for accurate patient positioning during the image-guided radiotherapy (IGRT) process, making it an ideal option for adaptive radiotherapy (ART)…

Objective: Radiotherapy treatment planning is a time-consuming and potentially subjective process that requires the iterative adjustment of model parameters to balance multiple conflicting objectives. Recent advancements in frontier…

Cone-beam CT (CBCT) is installed in the treatment room to facilitate online clinical applications, including image guidance in radiation and surgery. Half-fan and short-can are the commonly used modes in clinical applications to expand the…

Background: Accurate deformable image registration (DIR) is required for contour propagation and dose accumulation in MR-guided adaptive radiotherapy (MRgART). This study trained and evaluated a deep learning DIR method for domain invariant…

Treatment delivery is largely determined by capabilities of the beam delivery system (BDS), where faster delivery can have many potential benefits including improved dosimetric quality, utility, cost effectiveness, patient throughput and…

We present a nitrogen-targeting-Proton-Carbon-Alpha-Therapy method, abbreviated as Proton-CAT, which partially converts protons into carbon-12 and $\alpha$ particles through nuclear reactions between protons and nitrogen-15. Monte Carlo…