Because the imaging characteristics of many malignant superficial soft-tissue lesions overlap with those of benign ones, inadequate surgical resection due to misinterpretation of MRI often occurs. Adding DWI to conventional MRI yields greater diagnostic performances [area under the receiver-operating characteristic curve (AUC), 0.83-0.99] than does the use of conventional MRI alone (AUC, 0.71-0.93) in the evaluation of malignant superficial masses by inexperienced readers.
WHAT IS ALREADY KNOWN ABOUT THIS SUBJECT
• The only existing study of CYP2D6*10‐associated alterations in flecainide pharmacokinetics was retrospective.
• Paroxetine has been known as a strong inhibitor of CYP2D6.
WHAT THIS STUDY ADDS
• This study reports that the extent of drug interaction between flecainide and paroxetine is influenced by the CYP2D6*10 allele in healthy subjects, which is frequent in Asians.
AIMS
The objectives were to evaluate the effect of CYP2D6 genetic polymorphism on the pharmacokinetics of flecainide, and also on the extent of drug interaction with paroxetine as a CYP2D6 inhibitor after a single oral administration in healthy subjects.
METHODS
An open‐label, two‐period, single‐sequence, cross‐over study was performed in 21 healthy Korean male volunteers (seven for CYP2D6*1/*1 or *1/*2, group 1; seven for CYP2D6*1/*10, group 2; seven for CYP2D6*10/*10 or *10/*36, group 3). Subjects were administered 200 mg of flecainide on day 1. After a 7‐day wash‐out period, subjects were administered 20 mg of paroxetine from day 8 to 14, and 200 mg of flecainide on day 15. Blood sampling was performed up to 72 h after flecainide administration.
RESULTS
Terminal elimination half‐life and mean residence time (MRT) were significantly different among three genotype groups after a single oral administration of flecainide (P = 0.021, 0.011, respectively). Area under the concentration–time curve, terminal elimination half‐life and MRT increased significantly after paroxetine co‐administration only in groups 1 and 2.
CONCLUSIONS
This study reports that the extent of drug interaction between flecainide and paroxetine is influenced by the CYP2D6*10 allele in healthy subjects, which is frequent in Asians.
Vertebral compression fracture is a deformity of vertebral bodies found on lateral spine images. To diagnose vertebral compression fracture, accurate measurement of vertebral compression ratio is required. Therefore, rapid and accurate segmentation of vertebra is important for measuring the vertebral compression ratio. In this study, we used 339 data of lateral thoracic and lumbar vertebra images for training and testing a deep learning model for segmentation. The result of segmentation by the model was compared with the manual measurement, which is performed by a specialist. As a result, the average sensitivity of the dataset was 0.937, specificity was 0.995, accuracy was 0.992, and dice similarity coefficient was 0.929, area under the curve of receiver operating characteristic curve was 0.987, and the precision recall curve was 0.916. The result of correlation analysis shows no statistical difference between the manually measured vertebral compression ratio and the vertebral compression ratio using the data segmented by the model in which the correlation coefficient was 0.929. In addition, the Bland–Altman plot shows good equivalence in which VCR values are in the area within average ± 1.96. In conclusion, vertebra segmentation based on deep learning is expected to be helpful for the measurement of vertebral compression ratio.
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