Publications by authors named "A Fredriksson"
The advent of ultra-high dose rate irradiation, known as FLASH radiation therapy, has shown promising potential in reducing toxicity while maintaining tumor control. However, the clinical translation of these benefits necessitates efficient treatment planning strategies. This study introduces a novel approach to optimize proton therapy for FLASH effects using traveling salesperson problem (TSP) heuristics.
View Article and Find Full Text PDFObjective: To evaluate the effects of customized corneal collagen cross-linking (CXL) on higher-order aberrations (HOAs) in keratoconus (KC): vertical coma (VC), horizontal coma (HC), spherical aberration (SA), trefoil (TF) and astigmatism, compared with the same effects in healthy eyes undergoing CXL for low-grade myopia.
Methods: This mixed-designed study included 38 eyes of 38 patients with KC, treated and followed prospectively, who received customized epi-on CXL in high oxygen, and a retrospective control group of 23 eyes from 23 patients who underwent central 4-mm CXL treatment for low-grade myopia. VC, HC, SA, TF and keratometry values were obtained from Pentacam HR® measurements at baseline and at 1, 6, 12 and 24 months post-treatment.
Article Synopsis
- ProtOnART is a technique that improves proton therapy for esophageal cancer by adapting to changes in patient anatomy during treatment, focusing on effective autodelineation methods for target and risk areas.
- A study of 15 patients compared various autodelineation methods and their effectiveness in creating adaptive treatment plans, finding that deformation techniques yielded better results for organs at risk and clinical target volumes.
- The results showed that while most adaptive treatment plans met initial evaluation goals, significant challenges remained in ensuring adequate coverage of clinical targets, necessitating manual intervention for clinical acceptance.
To demonstrate the feasibility of integrating fully-automated online adaptive proton therapy strategies (OAPT) within a commercially available treatment planning system and underscore what limits their clinical implementation. These strategies leverage existing deformable image registration (DIR) algorithms and state-of-the-art deep learning (DL) networks for organ segmentation and proton dose prediction.Four OAPT strategies featuring automatic segmentation and robust optimization were evaluated on a cohort of 17 patients, each undergoing a repeat CT scan.
View Article and Find Full Text PDFBackground: Robotic radiosurgery treatments allow for precise non-coplanar beam delivery by utilizing a robot equipped with a linac that traverses through a set of predetermined nodes. High quality treatment plans can be produced but treatment times can grow large, with one substantial component being the robot traversal time.
Purpose: The aim of this study is to reduce the treatment time for robotic radiosurgery treatments by introducing algorithms for reducing the robot traversal time.