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Justin Chunjoo Park
Mayo Clinic
A Clinical Dose Prescription System for Proton Radiotherapy Based on Microdosimetric Spectral Information
Clinical proton dose prescription uses a fixed relative biological effectiveness (RBE) factor of 1.1 despite preclinical and clinical evidence that RBE varies with dose, radiation quality and tissue radiosensitivity, particularly near the distal edge of treat...
Poster Program · Therapy Physics
Development of an Ultra Fast and Setup Robust Deep Learning Rbe Dose Engine for Carbon Ion Therapy Using a Conditional Mednext
Accurate voxel-wise RBE modeling for carbon ion radiation therapy (CIRT), such as the Mayo Clinic Florida Microdosimetric Kinetic Model (MCF-MKM), is computationally prohibitive for time-constrained clinical workflows. Monte Carlo (MC) calculations can requir...
Poster Program · Therapy Physics
DIM-Free Monte-Carlo–Integrated Planning Optimization Using Randomized-Gradient-Free-Method (RGFM) for MCF Mkm Rbe Dose In Carbon Ion Therapy
The Mayo Clinic Florida microdosimetric kinetic model (MCF MKM) provides highly accurate relative biological effectiveness (RBE) calculations for carbon ion radiation therapy (CIRT), but its clinical use is limited by extreme memory and computational demands...
Poster Program · Therapy Physics
Predictive Smart-Spill Scheduling: Minimizing Dead Time In Synchrotron-Based Spot Scanning Via Look-Ahead Energy Management
Synchrotron-based proton spot scanning includes non-productive dead time from layer switching and spill change/reinjection. In dose-driven continuous scanning, spill changes are commonly triggered only after beam exhaustion, causing sequential overheads. We p...
Poster Program · Therapy Physics
Preliminary Monte Carlo Benchmarking of the First U.S. Carbon TPS: Range, Voxel-Wise Differences, and Microdosimetry
To present preliminary validation results for the first carbon treatment planning system (TPS) in the United States and to benchmark its GPU Monte Carlo dose engine using depth-resolved dose and microdosimetric metrics.
Poster Program · Therapy Physics
Real-Time Diffusion-Quality Synthetic CT Generation Via Reliability-Aware Vision Transformers for Online Adaptive Radiotherapy
While Denoising Diffusion Probabilistic Models (DDPMs) have set new benchmarks for synthetic CT (sCT) image quality, their prohibitive inference times hinder integration into online adaptive radiation therapy (ART) workflows. This study introduces HQ-PatchNet...
Poster Program · Therapy Physics
Toxicity Prediction In Prostate Radiotherapy Using Multimodal Features with 3D Mednext and Large Language Models
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–based dose prediction (3D Med...
Poster Program · Therapy Physics