Objective To investigate the value of artificial intelligence-assisted compressed sensing (ACS) technology for intravenous gadolinium contrast-enhanced magnetic resonance imaging of the inner ear using three-dimensional fluid-attenuated inversion recovery (3D-FLAIR) sequence. Methods The patients received gadolinium contrast-enhanced magnetic resonance imaging using ACS and united compressed sensing (uCS) 3D-FLAIR at Zhongshan Hospital, Fudan University from January to November 2024 were prospectively enrolled. The repetition time was 16 000 ms, and acquisition time was 6 min 40 s and 10 min 24 s in ACS 3D-FLAIR and uCS 3D-FLAIR, respectively. The images on the two sequences were evaluated independently by two radiologists. The image quality of the two sequences was subjectively evaluated and compared. The signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) were compared between the two sequences. The grading consistencies using two sequences and between the two doctors were analyzed. Results There was no statistically difference in subjective score of image quality between the two sequences. SNR and CNR of the ACS 3D-FLAIR sequence were significantly higher than those of the uCS 3D-FLAIR sequence (P＜0.001). The kappa values of grades of cochlear and vestibular endolymphatic hydrops were 0.942 and 0.888 using two sequences (P＜0.001). The kappa values of grades of cochlear and vestibular endolymphatic hydrops using the ACS 3D-FLAIR sequence between the two doctors were 0.784 and 0.831, respectively (P＜0.001); the kappa values of grades of cochlear and vestibular endolymphatic hydrops using uCS 3D-FLAIR sequence between the two doctors were 0.725 and 0.756, respectively (P＜0.001). Conclusions ACS 3D-FLAIR could provide higher SNR and CNR than uCS 3D-FLAIR, and is more suitable for intravenous gadolinium contrast-enhanced magnetic resonance imaging of the inner ear; the endolymphatic hydrops grades using ACS 3D-FLAIR is similar to use uCS 3D-FLAIR.

ObjectiveTo understand the seropositivity of neutralizing antibodies (NAb) and low-level NAb against SARS-CoV-2 infection in the community residents, and to explore the impact of COVID-19 vaccination and SARS-CoV-2 infection on the levels of NAb in human serum. MethodsOn the ground of surveillance cohort for acute infectious diseases in community populations in Shanghai, a proportional stratified sampling method was used to enroll the subjects at a 20% proportion for each age group (0‒14, 15‒24, 25‒59, and ≥60 years old). Blood samples collection and serum SARS-CoV-2 NAb concentration testing were conducted from March to April 2023. Low-level NAb were defined as below the 25^th percentile of NAb. ResultsA total of 2 230 participants were included, the positive rate of NAb was 97.58%, and the proportion of low-level NAb was 25.02% (558/2 230). Multivariate logistic regression analysis indicated that age, infection history and vaccination status were correlated with low-level NAb (all P<0.05). Individuals aged 60 years and above had the highest risk of low-level NAb. There was a statistically significant interaction between booster vaccination and one single infection (aOR=0.38, 95%CI: 0.19‒0.77). Compared to individuals without vaccination, among individuals infected with SARS-CoV-2 once, both primary immunization (aOR=0.23, 95%CI: 0.16‒0.35) and booster immunization (aOR=0.12, 95%CI: 0.08‒0.17) significantly reduced the risk of low-level NAb; among individuals without infections, only booster immunization (aOR=0.28, 95%CI: 0.14‒0.52) showed a negative correlation with the risk of low-level NAb. ConclusionsThe population aged 60 and above had the highest risk of low-level NAb. Regardless of infection history, a booster immunization could reduce the risk of low-level NAb. It is recommended that eligible individuals , especially the elderly, should get vaccinated in a timely manner to exert the protective role of NAb.

Background::Dual-energy computed tomography (DECT) is purported to accurately distinguish uric acid stones from non-uric acid stones. However, whether DECT can accurately discriminate ammonium urate stones from uric acid stones remains unknown. Therefore, we aimed to explore whether they can be accurately identified by DECT and to develop a radiomics model to assist in distinguishing them.Methods::This research included two steps. For the first purpose to evaluate the accuracy of DECT in the diagnosis of uric acid stones, 178 urolithiasis patients who underwent preoperative DECT between September 2016 and December 2019 were enrolled. For model construction, 93, 40, and 109 eligible urolithiasis patients treated between February 2013 and October 2022 were assigned to the training, internal validation, and external validation sets, respectively. Radiomics features were extracted from non-contrast CT images, and the least absolute shrinkage and selection operator (LASSO) algorithm was used to develop a radiomics signature. Then, a radiomics model incorporating the radiomics signature and clinical predictors was constructed. The performance of the model (discrimination, calibration, and clinical usefulness) was evaluated.Results::When patients with ammonium urate stones were included in the analysis, the accuracy of DECT in the diagnosis of uric acid stones was significantly decreased. Sixty-two percent of ammonium urate stones were mistakenly diagnosed as uric acid stones by DECT. A radiomics model incorporating the radiomics signature, urine pH value, and urine white blood cell count was constructed. The model achieved good calibration and discrimination {area under the receiver operating characteristic curve (AUC; 95% confidence interval [CI]), 0.944 (0.899–0.989)}, which was internally and externally validated with AUCs of 0.895 (95% CI, 0.796–0.995) and 0.870 (95% CI, 0.769–0.972), respectively. Decision curve analysis revealed the clinical usefulness of the model.Conclusions::DECT cannot accurately differentiate ammonium urate stones from uric acid stones. Our proposed radiomics model can serve as a complementary diagnostic tool for distinguishing them in vivo.

For Perihilar cholangiocarcinoma (pCCA), surgical resection is the only effective way to cure this disease. However, it has high postoperative mortality and high recurrence rate. Domestic and foreign scholars have constructed statistics-based evaluation methods to predict patients′ postoperative survival and complications, such as nomogram, scoring system and other prognostic models. Based on these methods, clinicians can better select patients who can benefit from surgery and choose the optimal? treatment for more severe patients. Through the adoption of other treatments or some ways to ameliorate some preoperative condition, to improve the patient′s mortality and survival. This article reviews the prognostic risk factors and prognostic models of pCCA in order to provide a reference for clinicians to predict the prognosis about the surgery.