Correction to: Diagnostic Value of Bone SPECT/CT Using 99mTc-Methylene Diphosphonate in Patients with Unspecified Chest Wall PainNuklearmedizin 2022; 61(01): 16-24DOI: 10.1055/a-1549-5910
Determination of the bioequivalence of 2 pravastatin tablet formulations manufactured in Korea.Twenty-three healthy male Korean volunteers received each of the 2 pravastatin formulations at a dose of 20 mg in a 2 x 2 crossover study. There was a 1-week washout period between doses. Plasma concentrations of pravastatin were monitored using high-performance liquid chromatography over a period of 8 hours after administration. AUC(0-8h) (the area under the plasma concentration-time curve from time zero to the last measured time in plasma, 8 h) was calculated using the linear-log trapezoidal method. Cmax (maximum plasma drug concentration) and tmax (time to reach Cmax) were compiled from the plasma concentration-time data. Analysis of variance was carried out using logarithmically transformed AUC(0-8h) and Cmax and untransformed tmax.The point estimates and 90% confidence intervals for AUC(0-8h) (parametric) and Cmax (parametric) were 1.067 (0.968 to approximately 1.176) and 1.074 (0.999 to approximately 1.155), respectively, satisfying the bioequivalence criteria of the European Committee for Proprietary Medicinal Products and the US Food and Drug Administration guidelines. The corresponding value of tmax was 0.000 (-0.250 to approximately 0.250).These results indicate that the 2 medications of pravastatin are bioequivalent and, thus, may be prescribed interchangeably.
Purpose:We aimed to compare the effects of a fast shock wave rate (120 shocks per minute) and a slow shock wave rate (60 shocks per minute) on the shock wave lithotripsy (SWL) success rate, patient's pain tolerance, and complications.Materials and Methods: A total of 165 patients with radiopaque renal pelvis or upper ureter stones were included in the study.Patients were classified by use of a random numbers table.Group I (81 patients) received 60 shock waves per minute and group II (84 patients) received 120 shock waves per minute.For each session, the success rate, pain measurement, and complication rate were recorded.Results: No statistically significant differences were observed in the patients according to age, sex, body mass index, stone size, side, location, total energy level, or number of shocks.The success rate of the first session was greater in group I than in group II (p=0.002).The visual analogue pain scale was lower in group I than in group II (p=0.001).The total number of sessions to success and the complication rate were significantly lower in group I than in group II (p=0.001). Conclusions:The success rate of SWL is dependent on the interval between the shock waves.If the time between the shock waves is short, the rate of lithotripsy success decreases, and the pain measurement score and complications increase.We conclude slow SWL is the optimal shock wave rate.
Persistent left superior vena cava is a rare but well-recognised condition. We describe a case of persistent left superior vena cava draining directly into the left atrium, with a fixed anatomical right-to-left shunt and paradoxical embolic events causing recurrent brain abscess. Surgical ligation was curative.
We explored the prediction of programmed cell death ligand 1 (PD-L1) expression level in non-small cell lung cancer using a machine learning approach with positron emission tomography/computed tomography (PET/CT)-based radiomics.A total of 312 patients (189 adenocarcinomas, 123 squamous cell carcinomas) who underwent F-18 fluorodeoxyglucose PET/CT were retrospectively analysed. Imaging biomarkers with 46 CT and 48 PET radiomic features were extracted from segmented tumours on PET and CT images using the LIFEx package. Radiomic features were ranked, and the top five best feature subsets were selected using the Gini index based on associations with PD-L1 expression in at least 50% of tumour cells. The areas under the receiver operating characteristic curves (AUCs) of binary classifications afforded by several machine learning algorithms (random forest, neural network, Naïve Bayes, logistic regression, adaptive boosting, stochastic gradient descent, support vector machine) were compared. The model performances were tested by 10-fold cross validation.We developed and validated a PET/CT-based radiomic model predicting PD-L1 expression levels in lung cancer. Long run high grey-level emphasis, homogeneity, mean Hounsfield unit, long run emphasis from CT, and maximum standardised uptake value from PET were the five best feature subsets for positive PD-L1 expression. The Naïve Bayes model (AUC=0.712), with a sensitivity of 75.3% and specificity of 58.2%, outperformed all other classifiers. It was followed by the neural network model (AUC=0.711), random forest (AUC=0.700), logistic regression (AUC=0.673) and adaptive boosting (AUC=0.604).PET/CT-based radiomic features may help clinicians identify tumours with positive PD-L1 expression in a non-invasive manner using machine learning algorithms.
A 30-year-old male admitted to our hospital with sudden onset shortness of breath, general weakness, dysuria, frequency, oligouria and fever. Abdominal and chest computed tomography revealed septic pulmonary embolism, multiple thrombi along right common iliac, internal iliac and femoral vein and large size prostatic abscess (right lobe >5 cm, left lobe >3.5 cm). We, therefore, diagnosed septic pulmonary embolism secondary to prostate abscess. Abscess was drained by transurethral resection of prostate with appropriate antibiotics therapy. There were no postoperative complications with complete abscess resolution. Septic pulmonary embolism originated from urinary tract infection is rare. So we present a case report and the review of relevant literatures.
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