Research on automatic recognition radiomics algorithm for early sacroiliac arthritis based on sacroiliac MRI imaging.

OBJECTIVE: To create an automated machine learning model using sacroiliac joint MRI imaging for early sacroiliac arthritis detection, aiming to enhance diagnostic accuracy. METHODS: We conducted a retrospective analysis involving 71 patients with early sacroiliac arthritis and 85 patients with normal sacroiliac joint MRI scans. Transverse T1WI and T2WI sequences were collected and subjected to radiomics analysis by two physicians. Patients were randomly divided into training and test groups at a 7:3 ratio. Initially, we extracted the region of interest on the sacroiliac joint surface using ITK-SNAP 3.6.0 software and extracted radiomic features. We retained features with an Intraclass Correlation Coefficient > 0.80, followed by filtering using max-relevance and min-redundancy (mRMR) and LASSO algorithms to establish an automatic identification model for sacroiliac joint surface injury. Receiver operating characteristic (ROC) curves were plotted, and the area under the ROC curve (AUC) was calculated. Model performance was assessed by accuracy, sensitivity, and specificity. RESULTS: We evaluated model performance, achieving an AUC of 0.943 for the SVM-T1WI training group, with accuracy, sensitivity, and specificity values of 0.878, 0.836, and 0.943, respectively. The SVM-T1WI test group exhibited an AUC of 0.875, with corresponding accuracy, sensitivity, and specificity values of 0.909, 0.929, and 0.875, respectively. For the SVM-T2WI training group, the AUC was 0.975, with accuracy, sensitivity, and specificity values of 0.933, 0.889, and 0.750. The SVM-T2WI test group produced an AUC of 0.902, with accuracy, sensitivity, and specificity values of 0.864, 0.889, and 0.800. In the SVM-bimodal training group, we achieved an AUC of 0.974, with accuracy, sensitivity, and specificity values of 0.921, 0.889, and 0.971, respectively. The SVM-bimodal test group exhibited an AUC of 0.964, with accuracy, sensitivity, and specificity values of 0.955, 1.000, and 0.875, respectively. CONCLUSION: The radiomics-based detection model demonstrates excellent automatic identification performance for early sacroiliitis.

RSU-Net: U-net based on residual and self-attention mechanism in the segmentation of cardiac magnetic resonance images.

BACKGROUND: Automated segmentation techniques for cardiac magnetic resonance imaging (MRI) are beneficial for evaluating cardiac functional parameters in clinical diagnosis. However, due to the characteristics of unclear image boundaries and anisotropic resolution anisotropy produced by cardiac magnetic resonance imaging technology, most of the existing methods still have the problems of intra-class uncertainty and inter-class uncertainty. However, due to the irregularity of the anatomical shape of the heart and the inhomogeneity of tissue density, the boundaries of its anatomical structures become uncertain and discontinuous. Therefore, fast and accurate segmentation of cardiac tissue remains a challenging problem in medical image processing. METHODOLOGY: We collected cardiac MRI data from 195 patients as training set and 35patients from different medical centers as external validation set. Our research proposed a U-net network architecture with residual connections and a self-attentive mechanism (Residual Self-Attention U-net, RSU-Net). The network relies on the classic U-net network, adopts the U-shaped symmetric architecture of the encoding and decoding mode, improves the convolution module in the network, introduces skip connections, and improves the network's capacity for feature extraction. Then for solving locality defects of ordinary convolutional networks. To achieve a global receptive field, a self-attention mechanism is introduced at the bottom of the model. The loss function employs a combination of Cross Entropy Loss and Dice Loss to jointly guide network training, resulting in more stable network training. RESULTS: In our study, we employ the Hausdorff distance (HD) and the Dice similarity coefficient (DSC) as metrics for assessing segmentation outcomes. Comparsion was made with the segmentation frameworks of other papers, and the comparison results prove that our RSU-Net network performs better and can make accurate segmentation of the heart. New ideas for scientific research. CONCLUSION: Our proposed RSU-Net network combines the advantages of residual connections and self-attention. This paper uses the residual links to facilitate the training of the network. In this paper, a self-attention mechanism is introduced, and a bottom self-attention block (BSA Block) is used to aggregate global information. Self-attention aggregates global information, and has achieved good segmentation results on the cardiac segmentation dataset. It facilitates the diagnosis of cardiovascular patients in the future.

Identification of Calculus Bovis and its mixed varieties by ultra-high-performance liquid chromatography/quadrupole time-of-flight mass spectrometry (UHPLC-Q/TOF-MS) combined with the principal component analysis (PCA) method.

The method of ultra-high-performance liquid chromatography/quadrupole time-of-flight mass spectrometry (UHPLC-Q/TOF-MS) was established and combined with principal component analysis (PCA) to identify natural Calculus Bovis, in vitro cultured Calculus Bovis and artificial Calculus Bovis. PCA, which was particularly powerful in dealing with multicollinearity and variables that outnumber the samples, was used to analyze the UHPLC-MS data of the processed samples, and potential markers were analyzed and described based on orthogonal partial least-squares discriminant analysis. According to the results in this study, the approach of combining UHPLC-QTOF-MS with PCA was proven to be credible and could be used to identify Calculus Bovis from in vitro cultured Calculus Bovis and artificial Calculus Bovis and to determine if there is Calculus Bovis in patented Chinese medicines that should contained Calculus Bovis medicinal materials.

The Role of Dual-Source Computed Tomography Angiography in Evaluating the Aortic Arch Vessels in Acute Type A Aortic Dissection: A Retrospective Study of 42 Patients.

BACKGROUND This study aimed to investigate the role of dual-source computed tomography angiography (DSCTA) to evaluate the anatomy of the aortic arch vessels in patients with acute Type A aortic dissection (AD). MATERIAL AND METHODS A retrospective clinical study included 42 patients with acute Type A AD who underwent DSCTA and were treated in our hospital between January 2018 and December 2018. The findings were compared with a control group of 45 healthy individuals with hypertension and without aortic arch lesions. RESULTS The diagnostic accuracy of DSCTA in patients with acute Type A AD was almost 100%. The innominate artery was most frequently affected. The mean DSCTA imaging measurements for the root of the innominate artery, the left common carotid artery, and the left subclavian artery, in the coronal plane of the aortic arch, were 17.7±3.7 mm, 17.7±3.7 mm, and 12.9±3.1 mm, respectively. The angles formed by the origin of the three aortic arch branches vessels and the aortic arch were 70.5±10.2°, 58.5±15.5°, and 90.2±22.7°, respectively. In the transverse plane of the aortic arch, the mean angles were 110.5±22.3°, 100.3±15.2°, and 95.4±10.6°, respectively. These DSCTA imaging findings were significantly different in the patient group compared with the control group. CONCLUSIONS DCTA demonstrated that patients with Type A AD showed anatomic differences in the aortic arch vessels. These findings may help surgeons to develop treatment strategies and select the most appropriate vascular grafts and stents.

Identification of velvet antler and its mixed varieties by UPLC-QTOF-MS combined with principal component analysis.

Many species of velvet antler have been used as traditional medicine for thousands of years; however, as medicinal materials, velvet antler derived from different animals have different clinical effects. To distinguish the differences and homologies, ultra-performance liquid chromatography-quadruple-time of flight mass spectrometry (UPLC-QTOF-MS) coupled with principal component analysis (PCA) was developed and applied to identify these antler samples derived from Cervus nippon Temminck, Cervus elaphus Linnaeus and Rangifer tarandus Linnaeus, which were first tested and compared at the molecular level of protein. The UPLC-MS data of the trypsin digested samples were subjected to PCA, and the potential markers based on peptide were depicted to illustrate their differences. With the integrated strategy combining UPLC-QTOF-MS with PCA, the results from this study indicated that the proposed methods could be successfully applied to distinguish reindeer antler from sika deer antler and red deer antler, which were prescribed in the Chinese Pharmacopoeia (2015 edition).

Posaconazole-associated severe hyperbilirubinemia in acute myeloid leukemia following chemotherapy: A case report.

BACKGROUND: Posaconazole is a widely used azole antifungal agent, and posaconazole-associated severe hyperbilirubinemia is usually rare in clinical practice. We herein report a 58-year-old male with acute myeloid leukemia, who developed fungal infection following chemotherapy. CASE SUMMARY: After administration of posaconazole oral suspension, the patient developed severe hyperbilirubinemia and jaundice (Common Terminology Criteria for Adverse Events, CTCAE -Grade 3) with a serum total bilirubin (T-BIL) peak level of 170 µmol/L, alkaline phosphatase level of 739 U/L, alanine aminotransferase level of 99 U/L, and gamma-glutamyl transpeptidase level of 638 U/L. After posaconazole withdrawal and symptomatic treatment with liver-protective agents, the level of T-BIL and other laboratory data decreased gradually, and related symptoms disappeared. After medication analysis and literature review, we consider that the patient had a cholestatic type of posaconazole-induced liver injury, which was related to intracellular mitochondrial DNA damage. The case demonstrates that when patients with hematological malignancy develop severe infection following chemotherapy, combination of anti-infective drugs may contribute to a higher risk of severe drug-induced liver injury. CONCLUSION: This is the first thoroughly documented case report of posaconazole-associated severe hyperbilirubinemia. Therefore, in order to avoid severe adverse events, liver and renal function should be monitored closely before and during the administration of posaconazole.