European journal of radiology
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Artificial intelligence (AI) will continue to cause substantial changes within the field of radiology, and it will become increasingly important for clinicians to be familiar with several concepts behind AI algorithms in order to effectively guide their clinical implementation. This review aims to give medical professionals the basic information needed to understand AI development and research. The general concepts behind several AI algorithms, including their data requirements, training, and evaluation methods are explained. The potential legal implications of using AI algorithms in clinical practice are also discussed.
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Meta Analysis Comparative Study
Systematic review and meta-analysis of whole-body computed tomography compared to conventional radiological procedures of trauma patients.
The superior diagnostic accuracy of CT makes it an attractive tool for initial trauma imaging. This meta-analysis aimed to assess the evidence regarding the value of whole-body CT (WBCT) as part of the primary survey, in comparison to conventional radiological procedures. ⋯ This review demonstrates that WBCT markedly reduces time spent in ED. No significant differences in mortality rate are suggested. WBCT currently entails greater radiation dose and mechanical ventilation time. Further research is necessitated to address limitations of predominately retrospective observational data available.
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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.
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Background parenchymal enhancement (BPE) often affects interpretation of dynamic contrast-enhanced (DCE) MRI. There is limited evidence that reduced BPE is a feature of ultrafast DCE (UF-DCE) MRI. We aimed to evaluate the effect of BPE levels on lesion detectability on UF-DCE MRI in comparison with conventional DCE MRI. ⋯ Images with lower BPE can be achieved using UF-DCE MRI and may be advantageous when assessing breast lesions among patients with higher BPE or premenopausal women.
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Observational Study
Spectrum of chest computed tomographic (CT) findings in coronavirus disease-19 (COVID-19) patients in India.
To report the spectrum of chest computed tomographic (CT) imaging findings in coronavirus disease-19 (COVID-19) infected Indian patients. ⋯ In this study population predominantly with mild symptoms and few comorbidities, two-thirds of RT-PCR positive patients had a normal chest CT; whereas the remaining patients showed typical findings of predominant GGOs with a bilateral distribution and peripheral predominance.