Radiation therapy needs to balance between delivering a high dose to targets and the lowest possible dose to the organs at risk. Dose-volume histograms (DVHs) summarize the distribution of radiation doses in the irradiated structures. The interpretation can however be a challenge when the number of structures is high. We propose the use of a simple summary metric. We define the mean absolute dose deviation (MADD) as the average of absolute differences between a DVH and a reference dose. The properties are evaluated through numerical analysis. Calculus trivially shows the identity of the MADD and the area between curves, between DVH and reference dose. Computation of the MADD is the same regardless of structures' designation, whether organ at risk or target, on the same dose scale. Basic calculus properties open the perspective of applying the MADD to the evaluation of treatment plans.
Download full-text PDF |
Source |
|---|---|
| http://dx.doi.org/10.1016/j.meddos.2019.10.004 | DOI Listing |
Publication Analysis
Top Keywords
Similar Publications
High-throughput screening to identify endocrine disruptors: Contribution of low-resolution tandem MS and high-resolution MS.
Anal Chim Acta
February 2025
Univ Rennes, Inserm, EHESP, Irset (Institut de recherche en santé, environnement et travail) - UMR_S 1085, F-35000, Rennes, France.
Background: Considering the large diversity of chemicals present in the environment and the need to study their effects (alone or as mixtures), the development of high-throughput in vitro assays in line with the Replacement, Reduction, Refinement (3R) strategy is essential for chemical risk assessments.
Results: We developed a robust analytical workflow based on both low resolution tandem mass spectrometry (MS/MS) and high-resolution mass spectrometry (HRMS) to quantify 13 steroids in NCI-H295R cell culture medium, human plasma and serum. The workflow was validated by screening media from the NCI-H295R cell line exposed in dose-response experiments to 5 endocrine disruptors (EDs) such as bisphenol A, prochloraz, ketoconazole, atrazine and forskolin.
AI-based automatic patient positioning in a digital-BGO PET/CT scanner: efficacy and impact.
EJNMMI Phys
January 2025
Department of Nuclear Medicine, Rambam Health Care Campus, P.O.B. 9602, 3109601, Haifa, Israel.
Background: A recently released digital solid-state positron emission tomography/x-ray CT (PET/CT) scanner with bismuth germanate (BGO) scintillators provides an artificial intelligence (AI) based system for automatic patient positioning. The efficacy of this digital-BGO system in patient placement at the isocenter and its impact on image quality and radiation exposure was evaluated.
Method: The digital-BGO PET/CT with AI-based auto-positioning was compared (χ, Mann-Whitney tests) to a solid-state lutetium-yttrium oxyorthosilicate (digital-LYSO) PET/CT with manual patient positioning (n = 432 and 343 studies each, respectively), with results split into groups before and after the date of a recalibration of the digital-BGO auto-positioning camera.
Abdominal synthetic CT generation for MR-only radiotherapy using structure-conserving loss and transformer-based cycle-GAN.
Front Oncol
January 2025
Department of Radiation Oncology, Yonsei Cancer Center, Heavy Ion Therapy Research Institute, Yonsei University College of Medicine, Seoul, Republic of Korea.
Purpose: Recent deep-learning based synthetic computed tomography (sCT) generation using magnetic resonance (MR) images have shown promising results. However, generating sCT for the abdominal region poses challenges due to the patient motion, including respiration and peristalsis. To address these challenges, this study investigated an unsupervised learning approach using a transformer-based cycle-GAN with structure-preserving loss for abdominal cancer patients.
View Article and Find Full Text PDFTherapeutic dose prediction using score-based diffusion model for pretreatment patient-specific quality assurance.
Front Oncol
January 2025
Department of Radiation Oncology, Jiangxi Cancer Hospital & Institute, Jiangxi Clinical Research Center for Cancer, The Second Affiliated Hospital of Nanchang Medical College, Nanchang, China.
Objectives: Implementing pre-treatment patient-specific quality assurance (prePSQA) for cancer patients is a necessary but time-consuming task, imposing a significant workload on medical physicists. Currently, the prediction methods used for prePSQA fall under the category of supervised learning, limiting their generalization ability and resulting in poor performance on new data. In the context of this work, the limitation of traditional supervised models was broken by proposing a conditional generation method utilizing unsupervised diffusion model.
View Article and Find Full Text PDFIn Vivo Gastroprotective Upshots of the Novel Schiff Base CdCl2 (C14H21N3O2) Compound by Bax/HSP-70 Signaling and Inflammatory Cytokines.
Cureus
December 2024
Department of Biology, College of Education, Salahaddin University-Erbil, Erbil, IRQ.
Background: Synthesis of the original Schiff base CdCl (CHNO) compound (Schiff base complex) displays an extensive range of bioactivities and was predictably utilized to treat several syndromes.
Purpose: The goal of the existing experiment is to evaluate the gastroprotective effects of a novel Schiff base CdCl₂ (C14H21N3O2) compound in alcohol-induced gastric ulcers in rats by examining its antioxidant activity, anti-inflammatory effects, and modulation of key molecular markers, including heat shock protein-70 (HSP-70) and Bcl-2-associated X protein (Bax) proteins.
Methods: Five groups of rats were utilized in the current study.
Want AI Summaries of new PubMed Abstracts delivered to your In-box?
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!