98%
921
2 minutes
20
Prompt gamma (PG) radiation generated from nuclear reactions between protons and tissue nuclei can be employed for range verification in proton therapy. A typical clinical workflow for PG range verification compares the detected PG profile with a predicted one. Recently, a novel analytical PG prediction algorithm based on the so-called filtering formalism has been proposed and implemented in a research version of RayStation (RaySearch Laboratories AB), which is a widely adopted treatment planning system. This work validates the performance of the filtering PG prediction approach.The said algorithm is validated against experimental data and benchmarked with another well-established PG prediction algorithm implemented in a MATLAB-based software REGGUI. Furthermore, a new workflow based on several PG profile quality criteria and analytical methods is proposed for data selection. The workflow also calculates sensitivity and specificity information, which can help practitioners to decide on irradiation course interruption during treatment and monitor spot selection at the treatment planning stage. With the proposed workflow, the comparison can be performed on a limited number of selected high-quality irradiation spots without neighbouring-spot aggregation.The mean shifts between the experimental data and the predicted PG detection (PGD) profiles (ΔPGD) by the two algorithms are estimated to be1.5±2.1mm and-0.6±2.2mm for the filtering and REGGUI prediction methods, respectively. The ΔPGD difference between two algorithms is observed to be consistent with the beam model difference within uncertainty. However, the filtering approach requires a much shorter computation time compared to the REGGUI approach.The novel filtering approach is successfully validated against experimental data and another widely used PG prediction algorithm. The workflow designed in this work selects spots with high-quality PGD shift calculation results, and performs sensitivity and specificity analyses to assist clinical decisions.
Download full-text PDF |
Source |
---|---|
http://dx.doi.org/10.1088/1361-6560/ad6116 | DOI Listing |
Biomed Chromatogr
October 2025
Department of Rehabilitation, Nan'ao People's Hospital, Shenzhen, China.
Chrysotobibenzyl, a bioactive ingredient from Dendrobium chrysotoxum, exhibits potent anti-tumor activity. However, its metabolic profiles remain unelucidated. This study aimed to disclose the metabolic fates of chrysotobibenzyl using human liver fractions.
View Article and Find Full Text PDFAnn Thorac Surg
September 2025
Department of Surgery, St. Louis University, St. Louis, MO.
Background: The use of artificial intelligence (AI) in medicine has increased dramatically. Its utilization will expand in cardiothoracic (CT) surgery, altering current practice. We surveyed CT surgeons to gain insight into their beliefs, hopes, and fears regarding AI.
View Article and Find Full Text PDFJ Neurosci Methods
September 2025
Department of Computer Science and Engineering, IIT (ISM) Dhanbad, Dhanbad, 826004, Jharkhand, India. Electronic address:
Background: Interpretation of motor imagery (MI) in brain-computer interface (BCI) applications is largely driven by the use of electroencephalography (EEG) signals. However, precise classification in stroke patients remains challenging due to variability, non-stationarity, and abnormal EEG patterns.
New Methods: To address these challenges, an integrated architecture is proposed, combining multi-domain feature extraction with evolutionary optimization for enhanced EEG-based MI classification.
Comput Methods Programs Biomed
September 2025
eXiT Research Group, Universitat de Girona (UdG), EPS - Edifici P-IV, Carrer Universitat de Girona, 6, Girona, 17003, Catalunya, Spain.
Background And Objective: Hybrid forecasting methods aim to overcome the limitations of classical statistical approaches and deep learning models. While statistical methods provide interpretability, they often lack predictive power. Conversely, deep learning models achieve high accuracy but act as "black boxes.
View Article and Find Full Text PDFMicrobiol Spectr
September 2025
United States Department of Agriculture, Agricultural Research Service (USDA-ARS), Southeast Poultry Research Laboratories, US National Poultry Research Center, Athens, Georgia, USA.
Infectious bursal disease (IBD), a highly contagious viral disease in young chickens, poses significant economic losses due to high mortality and immunosuppression. While IBD virus (IBDV) virulence is influenced by multiple genes, whole-genome sequencing (WGS) of IBDV is crucial for defining the strain pathotype and clinical profile. Flinders Technology Associates (FTA) cards are convenient for field sample collection, but their filter paper matrix can hinder nucleic acid recovery, impacting sequencing efficiency.
View Article and Find Full Text PDF