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Contrast Media & Molecular Imaging is an exciting journal in the area of contrast agents and molecular imaging, covering all areas of imaging technologies with a special emphasis on MRI and PET.
Chief Editor, Professor Zimmer, focuses on the development and use of PET radiotracers for new applications of PET/MRI imaging in neuroscience and pharmacology.
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Detection of Changes in CEA and ProGRP Levels in BALF of Patients with Peripheral Lung Cancer and the Relationship with CT Signs
Objective. To investigate the relationship between the detection of changes in the levels of carcinoembryonic antigen (CEA) and progastrin-releasing peptide (ProGRP) in bronchoalveolar lavage fluid (BALF) and CT signs in patients with peripheral lung cancer. Methods. Retrospective analysis of 108 patients with perihilar lung cancer who attended our hospital from January 2019 to January 2022, 54 cases were randomly selected as the observation group and 50 cases as the control group. Patients in both groups received CT examination and BALF test at the same time to observe and compare the differences in serum levels, the relationship between CT signs and serum indices, and the diagnostic value of peripheral lung cancer between the two groups. Results. The serum levels of ProGrp, CEA, CA211, and NSE in the observation group were significantly higher than those in the control group, and the difference was statistically significant ( < 0.05). The morphology, density, mass enhancement pattern, bronchial morphology, obstructive signs, and lymph node fusion of CT signs were compared between the observation group and the control group, indicating that CT signs were more helpful for the localization, diagnosis, and staging of lung cancer. The results of ROC curve analysis showed that the AUC value of low-dose CT combined with serum ProGrp, CEA, CA211, and NSE was 0.892, sensitivity was 96.21%, and specificity of 90.05%, which were significantly higher than those of the single tests, respectively. The positive likelihood ratio was 84.41% and the negative likelihood ratio was 87.11%. Conclusion. The combination of CT signs and serum tumour markers helps to improve the detection rate, sensitivity, and specificity of lung cancer, which has a high diagnostic rate for lung cancer and may provide evidence for the early diagnosis of lung cancer.
Perioperative Fast-Track Surgery Nursing Intervention for Patients with Kidney Stone Disease under Computed Tomography Imaging
This research aims to analyze the clinical intervention effect of perioperative fast-track surgery (FTS) nursing on patients with kidney stone disease (KSD) under computed tomography (CT) imaging. One-hundred KSD patients were selected as research objects and grouped after CT examination. These objects were randomly divided into a research group (FTS nursing intervention, n = 50) and a control group (general routine nursing intervention, n = 50). The preoperative psychological status of patients was compared between the two groups, using Self-rating Anxiety Scale and Self-rating Depression Scale. The hunger and thirst situations were compared using Numerical Rating Scale; postoperative recovery time, incidence of complications, and nursing satisfaction were also compared. The high-density shadow could be clearly observed in the right kidney of the patients in the CT imaging examination. The nursing outcomes suggested that there was no notable difference in hunger between the two groups, and anxiety, depression, and thirst in the research group were highly better than those in the control group (). The time of the first exhaust, the time of body temperature returning to normal, the time of getting out of bed, and the length of hospital stay in the research group were all shorter than those in the control group (). The total postoperative satisfaction of the research group (98.00%) was greatly better than the 88.00% in the control group (). As the FTS concept was applied in the perioperative nursing of KSD patients under CT imaging, the preoperative and postoperative negative emotions of patients could be improved. Thereby, the postoperative recovery rate of patients was promoted, postoperative complications and patients’ pain were reduced, and the postoperative quality of life of patients was also improved.
The Diagnostic and Prognostic Value of Cardiac Magnetic Resonance Strain Analysis in Heart Failure with Preserved Ejection Fraction
Background. Strain analysis of cardiac magnetic resonance (CMR) is critical for the diagnosis and prognosis of heart failure (HF) with preserved ejection fraction (HFpEF). Our study aimed to identify the diagnostic and prognostic value of strain analysis revealed by CMR in HFpEF. Methods. Participants in HFpEF and control were recruited according to the guideline. Baseline information, clinical parameters, blood samples were collected, and echocardiography and CMR examination were performed. Various parameters, including global longitudinal strain, global circumferential strain (GCS) and global radial strain in left ventricle (LV), right ventricle (RV), and left atrium, were measured from CMR. Receiver operator curve (ROC) was established to evaluate the diagnostic and prognostic value of strains in HFpEF. Results. Seven strains, with the exception of RVGCS, were employed to generate ROC curves after t-test. All strains had significant diagnostic value for HFpEF. The area under curve (AUC) of LV strains was greater than 0.7 and the AUC of the combined analysis of LV strains was 0.858 (95% confidence interval (CI): 0.798–0.919, sensitivity: 0.713, specificity: 0.875, ), indicating that they had a higher diagnostic value than individual LV strains. However, individual strains had no predictive value in identifying end-point events in HFpEF, the AUC of coanalysis of LV strains was 0.722 (95% CI: 0.573–0.872, sensitivity: 0.500, specificity: 0.959, ), indicating its prognostic relevance. Conclusion. Individual strain analysis in CMR may be useful for diagnosing HFpEF, the combination of LV strain analysis had the highest diagnostic value. Moreover, the prognostic value of individual strain analysis in predicting HFpEF outcome was not satisfactory while the combined usage of LV strain analysis was prognostically valuable in HFpEF outcome prediction.
Identification of Key MicroRNAs and Genes between Colorectal Adenoma and Colorectal Cancer via Deep Learning on GEO Databases and Bioinformatics
Background. Deep learning techniques are gaining momentum in medical research. Colorectal adenoma (CRA) is a precancerous lesion that may develop into colorectal cancer (CRC) and its etiology and pathogenesis are unclear. This study aims to identify transcriptome differences between CRA and CRC via deep learning on Gene Expression Omnibus (GEO) databases and bioinformatics in the Chinese population. Methods. In this study, three microarray datasets from the GEO database were used to identify the differentially expressed genes (DEGs) and differentially expressed miRNAs (DEMs) in CRA and CRC. The FunRich software was performed to predict the targeted mRNAs of DEMs. The targeted mRNAs were overlapped with DEGs to determine the key DEGs. Molecular mechanisms of CRA and CRC were evaluated using enrichment analysis. Cytoscape was used to construct protein–protein interaction (PPI) and miRNA–mRNA regulatory networks. We analyzed the expression of key DEMs and DEGs, their prognosis, and correlation with immune infiltration based on the Kaplan–Meier plotter, UALCAN, and TIMER databases. Results. A total of 38 DEGs are obtained after the intersection, including 11 upregulated genes and 27 downregulated genes. The DEGs were involved in the pathways, including epithelial-to-mesenchymal transition, sphingolipid metabolism, and intrinsic pathway for apoptosis. The expression of has-miR-34c (), hsa-miR-320a (), and has-miR-338 () was correlated with the prognosis of CRC patients. The expression levels of BCL2, PPM1L, ARHGAP44, and PRKACB in CRC tissues were significantly lower than normal tissues (), while the expression levels of TPD52L2 and WNK4 in CRC tissues were significantly higher than normal tissues (). These key genes are significantly associated with the immune infiltration of CRC. Conclusion. This preliminary study will help identify patients with CRA and early CRC and establish prevention and monitoring strategies to reduce the incidence of CRC.
Computed Tomography Imaging Features of Lung Cancer under Artificial Intelligence Algorithm and Its Correlation with Pathology
This study aims to investigate the relationship between the detection performance of an artificial intelligence (AI) algorithm and pathology in chest computed tomography (CT) images. In this study, a new pulmonary nodule (PN) detection algorithm was designed and developed on the three-dimensional (3D) connected domain algorithm. The appropriate grayscale threshold of CT images was selected, the CT images were converted into black-and-white images, and the useless images were removed. Then, the remaining lung images were formed into a 3D black-and-white pixel matrix. Labeling statistics was carried out, and the size, property, and location of PN could be measured and determined. A self-built database of PNs undergoing chest multislice spiral CT examination was retrospectively selected, and 150 cases were randomly selected by SPSS 22.0. Image processing was performed according to the algorithm and compared with the PN detected by radiologists; finally, the detection results were counted. There were 560 benign and malignant PNs, 312 malignant, and 248 benign. The algorithm detected 498 cases, of which 478 cases were detected accurately, and the sensitivity was 95.98%. The radiologist detected 424 cases, 364 cases were accurate, and the sensitivity was 85.85%. Compared with the detection results of radiologists, the algorithm detection results of nodules in solid nodules and ground glass nodules were more accurate. The detection results of nodules in the pleural connection type, peripheral type, central type, and hilar type were more accurate and statistically significant (). The malignancy, size, property, and location of different nodules could be accurately determined through CT images under this algorithm. It provided important support for the pathological research of lung cancer and prejudged the future development of PN in patients more accurately.
Dynamic Total-Body PET/CT Imaging Reveals Kinetic Distribution of 68Ga-DOTATATE in Normal Organs
Objective. To investigate the biodistribution and kinetic constants of 68Ga-DOTATATE in normal organs through dynamic total-body positron emission tomography/computed tomography (PET/CT). Methods. Seven patients who experienced endoscopic resection of gastric neuroendocrine tumor were enrolled. Dynamic total-body PET/CT scans over 60 min were performed. Time-activity curves were obtained by drawing regions of interest in normal organs. Rate constants, including K1, k2, k3, and vB, were computed using a two-tissue compartment model. Factor analysis was used to compare the rate constants among subjects and regions. Hierarchical cluster analysis was performed to identify organs with similar kinetic characteristics. Results. The highest uptake of 68Ga-DOTATATE was observed in the spleen followed by kidneys, adrenals, liver, pituitary gland, pancreas head, prostate, pancreas body, and thyroid, parotid, and submandibular glands. Low background level of 68Ga-DOTATATE uptake was observed in the nasal mucosa, bone, blood pool, and cerebrum. In addition, the uptake in the pancreas head was noted to be higher than the pancreas body () on the basis of each time point of dynamic PET. There were differences of rate constants among different organs. The mean K1 ranged from 0.0507 min−1 in the left nasal mucosa to 1.21 min−1 in the left kidney, and mean k2 ranged from 0.0174 min−1 in the spleen to 4.4487 min−1 in the left cerebrum. The mean k3 ranged from 0.0563 min−1 in the right cerebrum to 4.6309 min−1 in the left adrenal, and mean vB ranged from 0.0001 in the left cerebrum to 0.2489 in the right adrenal. However, none of the rate constants was significantly different among subjects or among different sites within a single organ. Three groups of organs with similar kinetic characteristics were identified: (1) cerebrum; (2) pituitary gland, liver, adrenal, and prostate; and (3) nasal mucosa, parotid and submandibular glands, thyroid, spleen, pancreas, kidney, and bone. Conclusion. Uptake and clearance of 68Ga-DOTATATE, in terms of kinetic constants, were different in different organs. The kinetic parameters of 68Ga-DOTATATE in different organs provide a reference for future dynamic PET imaging.