European journal of radiology
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In this study, we used magnetic resonance imaging (MRI) to investigate the anatomical alterations of cerebral cortex in children with Tourette syndrome (TS) and explore whether such deficits were related with their clinical symptoms. ⋯ The results of this study revealed that cortical thickness, sulcus, cortical curvature and LGI were changed in multiple brain regions for children with TS.
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To develop and externally validate an MR-based radiomics nomogram from retrospective multicenter datasets for pretreatment prediction of early relapse (≤ 1 year) in osteosarcoma after surgical resection. ⋯ The proposed MRI-based radiomics nomogram could provide a non-invasive tool to predict early relapse of osteosarcoma, which has the potential to improve personalized pretreatment management of osteosarcoma.
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Randomized Controlled Trial
The effect of injection volume on long-term outcomes of US-guided subacromial bursa injections.
Limited data exist on the efficacy of high- compared to low-volume US-guided corticosteroid injections (CI) in the subacromial-subdeltoid (SA-SD) bursa. Our purpose was to compare the short- and long-term efficacy of low- and high-volume injections, by using a capacity reference of SA-SD bursa volume, as assessed on cadaveric specimens. ⋯ High-compared to low-volume US-guided CI are superior for achieving early pain recovery.
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Comparative Study
Image quality of the CAIPIRINHA-Dixon-TWIST-VIBE technique for ultra-fast breast DCE-MRI: Comparison with the conventional GRE technique.
The aim of this study was to evaluate image quality of the CAIPIRINHA-Dixon-TWIST-Volume-Interpolated Breath-hold Examination (CDT-VIBE) technique for ultra-fast breast dynamic contrast enhanced (DCE) MRI with respect to conventional Gradient-Recalled Echo (GRE) technique. ⋯ The CDT-VIBE sequence provides excellent spatial resolution and adequate image quality in ultra-fast breast DCE-MRI. Further improvement in PAT noise and internal structure blurriness may be necessary.
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Adenocarcinoma (ADC) is the most common histological subtype of lung cancers in non-small cell lung cancer (NSCLC) in which ground glass opacifications (GGOs) found on computed tomography (CT) scans are the most common lesions. However, the presence of a micropapillary or a solid component is identified as an independent predictor of prognosis, suggesting a more extensive resection. The purpose of our study is to explore imaging phenotyping using a method combining radiomics with deep learning (RDL) to predict high-grade patterns within lung ADC. ⋯ High-grade lung ADC based on histologic pattern spectrum in GGO lesions might be predicted by the framework combining radiomics with deep learning, which reveals advantage over radiomics alone.