European radiology
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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.
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To evaluate predictive values of sarcopenia and visceral obesity measured from preoperative CT/MRIs for postoperative pancreatic fistula (POPF) after pancreaticoduodenectomy in patients with periampullary malignancies. ⋯ • Sarcopenic obesity might be predictive for postoperative pancreatic fistula after pancreaticoduodenectomy. • The vascular resection during pancreaticoduodenectomy might be predictive of major complications. • Body morphometric analysis might be helpful for identifying high-risk patients.
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Multicenter Study
Multicenter validation of the magnetic resonance T2* technique for quantification of pancreatic iron.
To assess the transferability of the magnetic resonance imaging (MRI) multislice multiecho T2* technique for pancreatic iron overload assessment. ⋯ • The gradient-echo T2* MRI technique is an accurate and reproducible means for the quantification of pancreatic iron. • The gradient-echo T2* MRI technique for the quantification of pancreatic iron may be transferred among MRI scanners by different vendors in several centers. • Pancreatic iron might serve as an early predictor of cardiac siderosis and is the strongest overall predictor of glucose dysregulation.