Aims: The magnitude of upper abdominal organ motion in children may be overestimated by current planning target volumes (PTV). A four-dimensional computed tomography (4DCT) - derived internal target volume (ITV) is frequently used in adult radiotherapy to take respiratory-related organ motion into account. In this study, the dosimetric consequences for target coverage and organs at risk from the use of an ITV approach compared to standard PTV margins in children with high-risk neuroblastoma were investigated.
Materials And Methods: 14 patients, median age 4.1 years, range 1.5 - 18.9 years, (9 midline targets, 5 lateralised) each had two dual arc volumetric modulated arc therapy (VMAT) plans (14 ×1.5 Gy) generated. One used an ITV-approach; motion information derived from 4DCT (PTV_itv) with a 5mm ITV to PTV expansion, and the other a PTV margin of 10mm from CTV to PTV (PTV_standard). Differences in absolute PTV volume and organ at risk doses are described.
Results: The ITV approach resulted in a highly significant reduction in PTV size of 38% (p<0.0001). For midline targets, an ITV approach resulted in a small but statistically significant reduction in combined mean kidney dose of 0.8Gy, p 0.01. Mean heart and lung dose were reduced by an average of 1 Gy with an ITV approach. Non-PTV integral dose from 30.4 Gy L to 27.8 Gy L using an ITV approach.
Conclusion: An ITV-approach to respiratory related organ motion management in children can significantly reduce absolute PTV volumes, maintain target coverage and reduce dose delivered to normal tissue in proximity to the target. This is an essential step to maximising the benefits of highly conformal radiotherapy techniques including VMAT for this patient group, and in the future with Proton Therapy.
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http://dx.doi.org/10.1016/j.clon.2024.08.009 | DOI Listing |
Struct Dyn
November 2024
Second Target Station, Oak Ridge National Laboratory, Oak Ridge, Tennessee 37831, USA.
We introduce a computational framework that integrates artificial intelligence (AI), machine learning, and high-performance computing to enable real-time steering of neutron scattering experiments using an edge-to-exascale workflow. Focusing on time-of-flight neutron event data at the Spallation Neutron Source, our approach combines temporal processing of four-dimensional neutron event data with predictive modeling for multidimensional crystallography. At the core of this workflow is the Temporal Fusion Transformer model, which provides voxel-level precision in predicting 3D neutron scattering patterns.
View Article and Find Full Text PDFJ Autism Dev Disord
December 2024
School of Information Science and Engineering, Yanshan University, Qinhuangdao, 066004, China.
Autism spectrum disorder (ASD) has been reported to exhibit altered local functional consistency. However, previous studies mainly focused on male samples and explored the temporal consistency in the ASD brain ignoring the spatial consistency. In this study, FOur-dimensional Consistency of local neural Activities (FOCA) analysis was used to investigate the sex differences of local spatiotemporal consistency of spontaneous brain activity in ASD.
View Article and Find Full Text PDFFront Endocrinol (Lausanne)
December 2024
Department of Endocrine Surgery, University College London Hospital, London, United Kingdom.
Background: Surgery is the preferred treatment for primary hyperparathyroidism. Minimally invasive parathyroidectomy is only feasible with accurate preoperative localisation. Virtual 3D anatomical models can be constructed from patient-specific CT scans using segmentation software.
View Article and Find Full Text PDFQuant Imaging Med Surg
December 2024
Anhui Province Key Laboratory of Medical Physics and Technology, Institute of Health and Medical Technology, Hefei Institutes of Physical Science, Hefei Cancer Hospital, Chinese Academy of Sciences, Hefei, China.
Background: Robust registration of thoracic computed tomography (CT) images is strongly impacted by motion during acquisition, high-density objects, and noise, particularly in lower-dose acquisitions. Despite the enhanced registration speed achieved by popular deep learning (DL) methods, their robustness is often neglected. This study aimed to develop a robust thoracic CT image registration algorithm to address the aforementioned issues.
View Article and Find Full Text PDFInt J Mol Sci
December 2024
State Key Laboratory of Animal Biotech Breeding, Beijing Key Laboratory for Animal Genetic Improvement, College of Animal Science and Technology, China Agricultural University, Beijing 100193, China.
Antlers are the sole mammalian organs capable of continuous regeneration. This distinctive feature has evolved into various biomedical models. Research on mechanisms of antler growth, development, and ossification provides valuable insights for limb regeneration, cartilage-related diseases, and cancer mechanisms.
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