Magnetic susceptibility is an intrinsic physical quantity which describes the relationship between material magnetization and applied external magnetic field. Quantitative susceptibility mapping (QSM) is an MRI technology which can quantify the buck magnetic susceptibility of tissue in vivo. It is particularly effective at elucidating anatomy with paramagnetic or diamagnetic components. QSM technology is a method for solving the ill-pose problem of un-conventional de-convolution of the measured tissue magnetic field with the unit magnetic dipole field to obtain the susceptibility source map. Many multi orientation scan based QSM and clinically acceptable single orientation QSM methods have been proposed to solve this ill-posed problem. In this paper, the QSM concept is introduced and the various QSM methods are systematically categorized and discussed. The aim of this paper is to summarize the current research progress of QSM, popularize the knowledge of QSM and promote the improvements and the rational application of QSM in clinical field.
Magnetic induction method aims at the noninvasive detection of liver iron overload by measuring the hepatic magnetic susceptibility. To solve the difficulty that eddy current effects interfere with the measurement of magnetic susceptibility, we proposed an improved coil system based on the static field magnetization principle in this study. We used a direct current excitation to eliminate the eddy current effect, and a rotary receiver coil to get the induced voltage. The magnetic field for a cylindrical object due to the magnetization effect was calculated and the relative change of maximum induced voltage was derived. The correlation between magnetic susceptibility of object and maximum magnetic flux, maximum induced voltage and relative change of maximum induced voltage of the receiver coil were obtained by simulation experiments, and the results were compared with those of the theory calculation. The contrast shows that the simulation results fit the theory results well, which proves our method can eliminate the eddy current effect effectively.
Objective To investigate the relationship between p53 codon 72 polymorphism and susceptibility to keloid. Methods The p53 genotypes were detected by polymerase chain reactionreverse dot blot(PCRRDB) and DNA direct sequencing among 15 healthy controls and 15 patients with keloid. Results The frequency of the Proallele(P=0.035) and Pro/Pro genotype(P=0.030) in patients was significantly higher than that in the controlls. There was no significant difference in the frequency of Pro/Arg and Arg/Arg genotypes between patients and controls. Conclusion The p53 gene codon 72 polymorphism may play a role in susceptibility to keloid.
Objective To analyze the human leukocyte antigen (HLA) gene polymorphism and haplotype frequency and distribution in Han patients with end stage renal disease (ESRD) in Sichuan province, and explore the correlation of HLA gene polymorphism and haplotype with the susceptibility to ESRD in Sichuan Han patients. Methods Polymerase chain reaction-sequence specific oligonucleotide probe hybridization typing technique was used to detect the HLA-A, -B, -DRB1, and -DQB1 genotypes of Han patients with ESRD and healthy participants. The allele and haplotype frequencies in the ESRD group and the control group were analyzed using SPSS 25.0 and Arlequin 3.5.2.2 softwares. Results A total of 756 ESRD patients and 1118 healthy participants were enrolled. In the four loci of HLA-A, -B, -DRB1, and -DQB1, the frequency of HLA-B*39 allele in the ESRD group was higher than that in the control group [3.37% vs. 2.19%; χ2=4.850, P=0.028, odds ratio (OR)=1.558, 95% confidence interval (CI) (1.047, 2.319)], the frequency of HLA-DQB1*06 allele in the ESRD group was lower than that in the control group [17.39% vs. 21.20%; χ2=8.264, P=0.004, OR=0.783, 95%CI (0.662, 0.925)], and the frequency of HLA-DQB1*04 allele in the ESRD group was higher than that in the control group [7.41% vs. 5.46%; χ2=5.867, P=0.015, OR=1.386, 95%CI (1.063, 1.807)]. The frequencies of 10 haplotypes, including HLA-A*11-B*39, HLA-DRB1*15-DQB1*06, and HLA-DRB1*04-DQB1*04, were significantly different between the ESRD group and the control group (P<0.05), among which 9 haplotypes were possibly susceptible to ESRD and 1 haplotype was possibly protective. Conclusions HLA gene polymorphism is closely related to the susceptibility to ESRD. HLA-B*39 and HLA-DQB1*04 may be susceptible genes for ESRD in Sichuan Han patients, while HLA-DQB1*06 may be a protective gene. In addition, 10 HLA haplotypes are possibly associated with the susceptibility to ESRD in Sichuan Han patients.
Objective To summarize the advancement of hereditary thrombophilia. Methods Relevant literatures about hereditary thrombophilia published recently domestic and abroad were reviewed and analyzed. Results The hereditary risk factors of venous thromboembolism were different among different races. In western population, the main risk factors were activated protein C resistance (APC-R) and mutation of factor V Leiden, methylene tetrahydrofolate reductase polymorphism (C677T) and prothrombin G20210A. While in Chinese population, the disorder of protein C system and hyperhomocysteinemia were the major genetic risk factor. The existence of multiple genetic risk factors increased the incidence of primary and recurrent venous thromboembolism. Conclusion Further study on the relations between the hereditary risk factors and thrombophilia will be very important for prediction and prevention of the venous thromboembolism.
Cryptococcosis, mainly caused by Cryptococcus neoformans/gattii species complexes, is a lethal infection in both immunosuppressive and immunocompetent populations. With the upgrade of detection methods and the increase of clinical knowledge, the incidence rate of cryptococcosis is increasing, and it has become one of the most important fungi threatening human health. In recent years, great progress has been made in this field, including the taxonomy and nomenclature of Cryptococcus spp., laboratory diagnostic methods and antifungal susceptibility tests, as well as the characteristics and treatments of cryptococcosis. This article reviews the above contents, in order to improve the clinical and laboratory understanding of the Cryptococcus spp., and realize the timely diagnosis and early treatment of cryptococcosis.
To better use the phase information to compensate the influence of blood flow, the phase unwrapping problem in susceptibility weighted imaging (SWI) is studied in this paper. In order to improve the accuracy of unwrapping, this paper proposes a magnitude image-guided phase unwrapping algorithm of SWI. The basic idea is as follows: (1) reduce the influence of noise by improving the rotational invariant non-local principal component analysis method (PRI-NL-PCA); (2) extract the corresponding solid region in the phase image to avoid the influence of the background noise on the phase unwrapping method; (3) use the phase compensation method to constrain the phase image reconstructed by the K-space. Finally, the reliability of the unwrapping method is evaluated by using four kinds of statistics as quantification index: the number, mean (M), variance (Var), and positive percentage (Pos) and negative percentage (Neg) of phasic error points. By comparing the simulated data with 226 sets of true head SWI data, the results show that the proposed algorithm has high accuracy compared with the classical branch cut method and the least squares method.
More and more medical devices can capture different features of human body and form three dimensional (3D) images. In clinical applications, usually it is required to fuse multiple source images containing different and crucial information into one for the purpose of assisting medical treatment. However, traditional image fusion methods are normally designed for two dimensional (2D) images and will lead to loss of the third dimensional information if directly applied to 3D data. Therefore, a novel 3D magnetic image fusion method was proposed based on the combination of newly invented beyond wavelet transform, called 3D band limited shearlet transformand (BLST), and four groups of traditional fusion rules. The proposed method was then compared with the 2D and 3D wavelet and dual-tree complex wavelet transform fusion methods through 4 groups of human brain T2* and quantitative susceptibility mapping (QSM) images. The experiments indicated that the performance of the method based on 3D transform was generally superior to the existing methods based on 2D transform. Taking advantage of direction representation, shearlet transform could effectively improve the performance of conventional fusion method based on 3D transform. It is well concluded, therefore, that the proposed method is the best among the methods based on 2D and 3D transforms.
Inappropriate and irrational prescription of antimicrobial agents has led to increasing bacterial resistance, which has become a major concern around the world. Clinical microbiology service provides a basis and guarantee for the rational application of antimicrobial agents and an important technical support for antimicrobial stewardship, and plays an important role in promoting the rational use of antimicrobial agents. This paper summarizes and evaluates the specific role and technical requirements of clinical microbiology service in the diagnosis of infectious diseases, rational application of antimicrobial agents, hospital infection control and training of medical staff, so as to provide a technical guidance for clinical microbiology service in the antimicrobial stewardship.
Objective To investigate the pathogen distribution and drug resistance in ICU patients, provide reference for prevention of severe infection and empirical antibacterial treatment. Methods The patients admitted in ICU between January 2013 and December 2014 were retrospectively analyzed. The pathogenic data were collected including bacterial and fungal culture results, the flora distribution and drug resistance of pathogenic bacteria. Results A total of 2088 non-repeated strains were isolated, including 1403 (67.2%) strains of Gram-positive bacteria, 496 (23.8%) strains of Gram-negative bacteria, and 189 (9.0%) strains of fungus. There were 1324 (63.42%) strains isolated from sputum or other respiratory specimens, 487 (23.33%) strains from blood specimens, 277 (13.27%) strains from other specimens. The bacteria included Acinetobacter baumannii (17.2%), Klebsiella pneumoniae (14.8%), Pseudomonas aeruginosa (9.9%), C. albicans (6.3%), E. coli (5.6%), E. cloacae (5.4%), Epidermis staphylococcus (5.0%) and Staphylococcus aureus (4.7%). There were 15 strains of penicillium carbon resistant enterobacteriaceae bacteria (CRE) accounting for 2.3%, including 5 strains of Pneumonia klebsiella, 4 strains of E. cloacae. In 117 strains of E. coli, drug-resistant strains accounted for 86.4% including 85.5% of multiple drug-resistant strains (MDR) and 0.9% of extremely-drug resistant (XDR) strains. In 359 strains of Acinetobacter baumannii, drug-resistant strains accounted for 75.2% including 72.1% of XDR strains and 3.1% of MDR strains. MDR strains accounted for 10.6% in Pseudomonas aeruginosa. Detection rate of methicillin resistant Staphylococcus aureus (MRSA) and methicillin resistant coagulase-negative Staphylococci (MRCNS) was 49.0% and 95.5%, respectively. There were 4 strains of vancomycin resistant Enterococcus faecalis. There were 131 (69.3%) strains of C. albicans, 23 (12.2%) strains of smooth candida. C. albicans was sensitive to amphotericin and 5-fluorine cytosine, and the resistance rate was less than 1% to other antifungle agents. The resistance rate of smooth ball candida was higher than C. albicans and nearly smooth candida, but still less than 15%. Conclusions The predominant pathogens in ICU was gram-negative bacteria. The top eight pathogenic bacteria were Acinetobacter baumanni, Klebsiella pneumoniae, Pseudomonas aeruginosa, C. albicans, E. coli, E. cloacae, Epidermis staphylococcus and S. aureus. Sputum and blood are common specimens. CRE accounts for 2.3%. Drug-resistant strains are most common in E. coli mainly by MDR, followed by Acinetobacter baumannii mainly by XDR, and least in Pseudomonas aeruginosa. C. albicans is the most common fungus with low drug resitance.