One algorithm is designed to implement longitudinal auto-tracking of the the detector on X-ray in the digital radiography system (DR) with manual collimator. In this study, when the longitudinal length of field of view (LFOV) on the detector is coincided with the longitudinal effective imaging size of the detector, the collimator half open angle (Ψ), the maximum centric distance (emax) between the center of X-ray field of view and the projection center of the focal spot, and the detector moving distance for auto-traking can be calculated automatically. When LFOV is smaller than the longitudinal effective imaging size of the detector by reducing Ψ, the emax can still be used to calculate the detector moving distance. Using this auto-tracking algorithm in DR with manual collimator, the tested results show that the X-ray projection is totally covered by the effective imaging area of the detector, although the center of the field of view is not aligned with the center of the effective imaging area of the detector. As a simple and low-cost design, the algorithm can be used for longitudinal auto-tracking of the detector on X-ray in the manual collimator DR.
This study proposed a method to calibrate tube focus spot and the center plane of rotation in computed tomography system. In the method, the tube was rotated to 0° and 180° respectively, and then one metal jig with symmetric windows A and B was scanned at each position under the tube cool and static condition. According to the geometry of tube focus spot, aperture center of the collimator and jig, the distance between tube focus spot and the center plane of rotation were calculated with the X ray transmittance data after denoising, mean value and normalization. To verify the practicability and validity of the method, the tube focus spot in a 16 slices CT system (Brivo CT385, GE, China) was calibrated, and the result after calibration was validated by scanning a polaroid film. The validation result showed that the deviation between tube focal spot and center plane of rotation was 0.02 mm and was in the error range within ± 0.1 mm. The results of this study showed that, as a simple and low-cost design, the method could be used for fast calibration between tube focus spot and the center plane of rotation.
ObjectiveTo investigate the causal relationship between gut microbiota and idiopathic pulmonary fibrosis (IPF). MethodsGenome-wide association studies (GWAS) data of gut microbiota and IPF were obtained from MiBioGen and Finngen databases, respectively. Instrumental variables were screened by means of significance, linkage disequilibrium, weak instrumental variable screening, and removal of confounding factors (genetics, smoking, host characteristics). Inverse variance weighted (IVW) was used as the main Mendelian randomization (MR) analysis method, and the weighted median, simple mode, MR-Egger, and weighted mode were used to perform MR to reveal the causal effect of gut microbiota and IPF. The Cochrane's Q, leave-one-out, MR-Egger-intercept, and Mendelian randomization pleiotropy residual sum and outlier (MR-PRESSO) and Steiger tests were used to analyze the heterogeneity, horizontal pleiotropy, outliers, and directionality, respectively. ResultsIVW analysis results showed that Actinomycetes [OR=1.773, 95%CI (1.323, 2.377), P<0.001], Erysipelatoclostridium [OR=2.077, 95%CI (1.107, 3.896), P=0.023], and Streptococcus [OR=1.35, 95%CI (1.100, 1.657), P=0.004] could increase the risk of IPF. Bifidobacterium [OR=0.668, 95%CI (0.620, 0.720), P<0.001], Ruminococcus [OR=0.434, 95%CI (0.222,0.848), P=0.015], and Tyzzerella [OR=0.479, 95%CI (0.304, 0.755), P=0.001] could reduce the risk of IPF. No significant heterogeneity, horizontal pleiotropy, outliers, and reverse causality were found. ConclusionActinobacteria, Erysipelatoclostridium and Streptococcus may increase the risk of IPF, while Bifidobacterium, Ruminococcus and Tyzzerella may reduce the risk of IPF. Regulation of the above gut microbiota may become a new direction in the study of the pathogenesis of IPF.