Improving Image Quality and Diagnostic Performance of CCTA in Patients with Challenging Heart Rate Conditions Using a Deep Learning-Based Motion Correction Algorithm.

OBJECTIVE: Challenging HR conditions, such as elevated Heart Rate (HR) and Heart Rate Variability (HRV), are major contributors to motion artifacts in Coronary Computed Tomography Angiography (CCTA). This study aims to assess the impact of a deep learning-based motion correction algorithm (MCA) on motion artifacts in patients with challenging HR conditions, focusing on image quality and diagnostic performance of CCTA. MATERIALS AND METHODS: This retrospective study included 240 patients (mean HR: 88.1 ± 14.5 bpm; mean HRV: 32.6 ± 45.5 bpm) who underwent CCTA between June, 2020 and December, 2020. CCTA images were reconstructed with and without the MCA. The signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) were measured to assess objective image quality. Subjective image quality was evaluated by two radiologists using a 5-point scale regarding vessel visualization, diagnostic confidence, and overall image quality. Moreover, all vessels with scores ≥ 3 were considered clinically interpretable. The diagnostic performance of CCTA with and without MCA for detecting significant stenosis (≥ 50%) was assessed in 34 patients at both per-vessel and per-patient levels, using invasive coronary angiography as the reference standard. RESULTS: The MCA significantly improved subjective image quality, increasing the vessel interpretability from 89.9% (CI: 0.88-0.92) to 98.8% (CI: 0.98-0.99) (p < 0.001). The use of MCA resulted in significantly higher diagnostic performance in both patient-based (AUC: 0.83 vs. 0.58, p = 0.04) and vessel-based (AUC: 0.92 vs. 0.81, p < 0.001) analyses, with the vessel-based accuracy notably increased from 79.4% (CI: 0.72-0.86) to 91.2% (CI: 0.85-0.95) (p = 0.01). There were no significant differences in objective image quality between the two reconstructions. The mean effective dose in this study was 2.8 ± 1.1 mSv. CONCLUSION: The use of MCA allows for obtaining high-quality CCTA images and superior diagnostic performance with low radiation exposure in patients with elevated HR and HRV.

CONUT score is associated with short-term prognosis in patients with severe acute pancreatitis: a propensity score matching cohort study.

Background: The Controlling Nutritional Status (CONUT) score was designed to assess the immune-nutritional status in patients. This study aimed to investigate the role of the CONUT score in the short-term prognosis of severe acute pancreatitis. Methods: This was a retrospective cohort study. 488 patients with severe acute pancreatitis at the Department of Critical Care Medicine of the West China Hospital of Sichuan University (Chengdu, China) were enrolled in the study. Baseline data were collected from the West China Hospital of Sichuan University database. The primary outcome during follow-up was all-cause mortality. The secondary outcomes were 28 day mortality, renal insufficiency, length of stay (LOS) in the ICU, and length of stay (LOS) in the hospital. Patients were divided into two groups based on a median CONUT score of 7, and baseline differences between the two groups were eliminated by propensity matching. Univariate Cox regression analyses were performed to estimate the association between CONUT score and outcomes. The Kaplan-Meier method was used to estimate the survival rate of patients. Results: CONUT score was an independent predictor of all-cause mortality (hazard ratio [HR]:2.093; 95%CI: 1.342-3.263; p < 0.001) and 28 day mortality (hazard ratio [HR]:1.813; 95%CI: 1.135-2.896; p < 0.013). CONUT score was not statistically significant in predicting the incidence of renal insufficiency. The high CONUT group had significantly higher all-cause mortality (p < 0.001), and 28 day mortality (p < 0.011) than the low CONUT group. Conclusion: The CONUT score is an independent predictor of short-term prognosis in patients with severe acute pancreatitis, and timely nutritional support is required to reduce mortality in patients with severe acute pancreatitis.

The Comparison of PCR Kits for the Detection of Erythrocytic Parasites on Filter Paper.

Dried blood spot (DBS) based PCR was considered an inexpensive and feasible method for detecting pathogens in the blood. The DBS carrier filter paper and PCR kits are crucial for accurate diagnosis. We evaluated 4 types of filter papers and 20 PCR kits for DBS samples. The PCR detecting Plasmodium results showed that the minimum detection limit of the 4 filter papers was 1 × 102 parasites/µL, and the positive rates of 20 PCR kits ranged from 0% to 100%. PCR results were satisfactory for detecting Plasmodium falciparum (P. falciparum) and Plasmodium. vivax (P. vivax) in archived DBS samples and Babesia gibsoni (B. gibsoni) in fresh pet DBS samples. Our results provided a useful reference for the detection of blood pathogens with DBS samples and direct PCR, especially for screening the cost-efficacy combination of filter paper and PCR kit in resource-limited areas.

The complete mitochondrial genome of major malaria vector Anopheles anthropophagus (Diptera: Culicidae) in China.

Anopheles anthropophagus (Xu and Feng 1975) is the major vector of malaria in Eastern and Southern China. The species An. anthropophagus is considered a synonym of An. lesteri (Baisas & Hu, 1936), although they differ in several key biological characteristics. Here, we report the complete mitochondrial genome of An. anthropophagus for the first time. The mitogenome of An. anthropophagus is a typical circular, double-stranded molecule with a total length of 15,413 base pairs, and contains 13 protein-coding genes, 22 transfer RNA genes, two ribosomal RNA genes, and an AT-rich control region. A phylogenetic analysis of the complete mitogenomes of 16 species of Anopheles (Culicidae) revealed that An. anthropophagus is closely related to An. sinensis (Wiedemann 1828), in the family Culicidae. The An. anthropophagus mitogenome provides new data for further taxonomic and phylogenetic studies of the genus Anopheles.