European radiology
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To determine the diagnostic accuracy and interobserver concordance of whole-body (WB)-MRI, vs. 99mTc bone scintigraphy (BS) and 18fluoro-ethyl-choline (18F-choline) PET/CT for the primary staging of intermediate/high-risk prostate cancer. ⋯ • A whole-body MRI protocol comprising unenhanced mDixon and diffusion-weighted imaging provides high levels of diagnostic accuracy for the primary staging of intermediate- and high-risk prostate cancer. • The diagnostic accuracy of whole-body MRI is much higher than that of bone scintigraphy, as currently recommended for clinical use. • Staging using WB-MRI, rather than bone scintigraphy, could result in better patient stratification and treatment delivery than is currently provided to patients worldwide.
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Asthma is a heterogeneous disease with diverse clinical phenotypes that have been identified via cluster analyses. However, the classification of phenotypes based on quantitative CT (qCT) is poorly understood. The study was conducted to investigate CT determination of uncontrolled asthma phenotypes. ⋯ • Obvious air trapping and proximal airway remodeling were present in patients with severe uncontrolled asthma. • CT air trapping indices showed a good correlation with disease duration, total IgE, atopy, and OCS and ICS doses, and were even more strongly correlated with clinical lung function. • Three CT-determined uncontrolled asthma phenotypes were identified, which might reflect underlying mechanisms of disease in patient stratification and in the different stages of disease development.
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To investigate the value of machine learning (ML)-based high-dimensional quantitative texture analysis (qTA) on T2-weighted magnetic resonance imaging (MRI) in predicting response to somatostatin analogues (SA) in acromegaly patients with growth hormone (GH)-secreting pituitary macroadenoma, and to compare the qTA with quantitative and qualitative T2-weighted relative signal intensity (rSI) and immunohistochemical evaluation. ⋯ • Machine learning-based texture analysis of T2-weighted MRI can correctly classify response to somatostatin analogues in more than four fifths of the patients. • Machine learning-based texture analysis performs better than qualitative and quantitative evaluation of relative T2 signal intensity and immunohistochemical evaluation. • About one third of the texture features may not be excellently reproducible, indicating that a reliability analysis is necessary before model development.
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This study was conducted in order to investigate the value of magnetic resonance imaging (MRI)-based radiomics signatures for the preoperative prediction of hepatocellular carcinoma (HCC) grade. ⋯ • The radiomics signature based on non-contrast-enhanced MR images was significantly associated with the pathological grade of HCC. • The radiomics signatures based on T1WI or T2WI images performed similarly at predicting the pathological grade of HCC. • Combining the radiomics signature and clinical factors (including age, sex, tumour size, AFP level, history of hepatitis B, hepatocirrhosis, portal vein tumour thrombosis, portal hypertension and pseudocapsule) may be helpful for the preoperative prediction of HCC grade.
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To investigate the structural connectivity of the motor subnetwork in multiple system atrophy with cerebellar features (MSA-C), a distinct subtype of MSA, characterized by predominant cerebellar symptoms. ⋯ • Structural connectivity of the motor subnetwork was explored in patients with multiple system atrophy with cerebellar features (MSA-C) using probabilistic tractography. • The motor subnetwork in MSA-C has significant alterations in both basal ganglia and cerebellar connectivity, with a higher extent of abnormality in the cerebellum. • These findings may be causally implicated for the motor features of cerebellar dysfunction and parkinsonism observed in MSA-C.