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Background: F-FDG positron emission tomography (PET) plays a crucial part in the evaluation for pediatric epileptic patients prior to therapy. Short-term scanning holds significant importance, especially for pediatrics epileptic individuals who exhibited involuntary movements. The aim was to evaluate the effects of short acquisition time on image quality and lesion detectability in pediatric epileptic patients using total-body (TB) PET/CT. A total of 25 pediatric patients who underwent TB PET/CT using uEXPLORER scanner with an F-FDG administered dose of 3.7 MBq/kg and an acquisition time of 600 s were retrospectively enrolled. Short acquisition times (60 s, 150 and 300 s) were simulated by truncating PET data in list mode to reduce count density. Subjective image quality was scored on a 5-point scale. Regions of interest analysis of suspected epileptogenic zones (EZs), corresponding locations contralateral to EZs, and healthy cerebellar cortex were used to compare the semi-quantitative uptake indices of short-time images and then were compared with 600 s images. The comparison of EZs detectability based on time-dependent PET images was performed.
Results: Our study demonstrated that a short acquisition time of 150 s is sufficient to maintain subjective image quality and lesion significance. Statistical analysis revealed no significant difference in subjective PET image quality between imaging at 300 s and 150 s (P > 0.05). The overall impression scores of image quality and lesion conspicuity in G60s were both greater than 3 (overall quality, 3.21 ± 0.46; lesion conspicuity, 4.08 ± 0.74). As acquisition time decreased, the changes of SUVmax and SD in the cerebellar cortex gradually increased (P < 0.01). There was no significant difference in asymmetry index (AI) difference between the groups and the AIs of EZs were > 15% in all groups. In 26 EZs of 25 patients, the lesion detection rate was still 100% when the time was reduced to 60 s.
Conclusions: This study proposed that TB PET/CT acquisition time could be reduced to 60 s with acceptable lesion detectability. Furthermore, it was suggested that a 150 s acquisition time would be sufficient to achieve diagnostic performance and image quality for children with epilepsy.
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http://dx.doi.org/10.1186/s13550-024-01081-x | DOI Listing |
Autophagy
September 2025
Department of Biochemistry and Molecular Biology, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan.
Macroautophagy/autophagy is an evolutionarily conserved process through which cells degrade cytoplasmic substances via autophagosomes. During the initiation of autophagosome formation, the ULK/Atg1 complex serves as a scaffold that recruits and regulates downstream ATG/Atg proteins and ATG9/Atg9-containing vesicles. Despite the essential role of the ULK/Atg1 complex, its components have changed during evolution; the ULK complex in mammals consists of ULK1 (or ULK2), RB1CC1, ATG13, and ATG101, whereas the Atg1 complex in the yeast lacks Atg101 but instead has Atg29 and Atg31 along with Atg17.
View Article and Find Full Text PDFHealth Commun
September 2025
Department of Communication, University of Illinois Urbana-Champaign.
This study took a lab-based approach to test both the drivers and effects of information seeking, in the context of meningitis. Participants ( = 107) answered a survey where they indicated their actual knowledge, perceived knowledge insufficiency (i.e.
View Article and Find Full Text PDFMagn Reson Med
September 2025
Centre for Integrative Neuroimaging, FMRIB Division, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK.
Purpose: To develop a deep learning-based reconstruction method for highly accelerated 3D time-of-flight MRA (TOF-MRA) that achieves high-quality reconstruction with robust generalization using extremely limited acquired raw data, addressing the challenge of time-consuming acquisition of high-resolution, whole-head angiograms.
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Drugs Aging
September 2025
Dalla Lana School of Public Health, University of Toronto, V1 06, 2075 Bayview Avenue, Toronto, ON, M4N 3M5, Canada.
Background And Objectives: Older adults living with dementia are a heterogeneous group, which can make studying optimal medication management challenging. Unsupervised machine learning is a group of computing methods that rely on unlabeled data-that is, where the algorithm itself is discovering patterns without the need for researchers to label the data with a known outcome. These methods may help us to better understand complex prescribing patterns in this population.
View Article and Find Full Text PDFRev Sci Instrum
September 2025
National Centre for Physics (NCP), Islamabad, Pakistan.
Time-resolved data acquisition is crucial for compositional analysis using Laser-Induced Breakdown Spectroscopy (LIBS). It can be managed by adjusting the delay time and gate width of the spectrometer. This study describes the compositional analysis of molybdenum (Mo) ore utilizing charge coupled device (CCD) and intensified charge-coupled device (ICCD) based LIBS systems.
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