Development and validation of models for predicting preterm birth and gestational latency following emergency cervical cerclage: A multicenter cohort study.

INTRODUCTION: Emergency cervical cerclage is a recognized method for preventing mid-trimester pregnancy loss and premature birth; however, its benefits remain controversial. This study aimed to establish preoperative models predicting preterm birth and gestational latency following emergency cervical cerclage in singleton pregnant patients with a high risk of preterm birth. MATERIAL AND METHODS: We retrospectively reviewed data from patients who received emergency cerclage between 2015 and 2023 in three institutions. Patients were grouped into a derivation cohort (n = 141) and an independent validation cohort (n = 61). Univariate and multivariate logistic and Cox regression analyses were used to identify independent predictive variables and establish the models. Harrell's C-index, time-dependent receiver operating characteristic curves and areas under the curves, calibration curve, and decision curve analyses were performed to assess the models. RESULTS: The models incorporated gestational weeks at cerclage placement, history of prior second-trimester loss and/or preterm birth, cervical dilation, and preoperative C-reactive protein level. The C-index of the model for predicting preterm birth before 28 weeks was 0.87 (95% CI: 0.82-0.93) in the derivation cohort and 0.82 (95% CI: 0.71-0.92) in the independent validation cohort; The C-index of the model for predicting gestational latency was 0.70 (95% CI: 0.66-0.75) and 0.78 (95% CI: 0.71-0.84), respectively. In the derivation set, the areas under the curves were 0.84, 0.81, and 0.84 for predicting 1-, 3- and 5-week pregnancy prolongation, respectively. The corresponding values for the external validation were 0.78, 0.78, and 0.79, respectively. Calibration curves showed a good homogeneity between the observed and predicted ongoing pregnant probabilities. Decision curve analyses revealed satisfactory clinical usefulness. CONCLUSIONS: These novel models provide reliable and valuable prognostic predictions for patients undergoing emergency cerclage. The models can assist clinicians and patients in making personalized clinical decisions before opting for the cervical cerclage.

Using artificial intelligence based imaging to predict lymph node metastasis in non-small cell lung cancer: a systematic review and meta-analysis.

Background: Lung cancer, especially non-small cell lung cancer (NSCLC), is one of the most-deadly malignancies worldwide. Lung cancer has a worse 5-year survival rate than many primary malignancies. Thus, the early detection and prognosis prediction of lung cancer are crucial. The early detection and prognosis prediction of lung cancer have improved with the widespread use of artificial intelligence (AI) technologies. This meta-analysis examined the accuracy and efficacy of AI-based models in predicting lymph node metastasis (LNM) in NSCLC patients using imaging data. Our findings could help clinicians predict patient prognosis and select alternative therapies. Methods: We searched the PubMed, Web of Science, Cochrane Library, and Embase databases for relevant articles published up to January 31, 2024. Two reviewers individually evaluated all the retrieved articles to assess their eligibility for inclusion in the meta-analysis. The systematic assessment and meta-analysis comprised articles that satisfied the inclusion criteria (e.g., randomized or non-randomized trials, and observational studies) and exclusion criteria (e.g., articles not published in English), and provided data for the quantitative synthesis. The quality of the included articles was assessed using the Quality Assessment of Diagnostic Accuracy Studies-2 (QUADAS-2). The pooled sensitivity, specificity, and area under the curve (AUC) were used to evaluate the ability of AI-based imaging models to predict LNM in NSCLC patients. Sources of heterogeneity were investigated using meta-regression. Covariates, including country, sample size, imaging modality, model validation technique, and model algorithm, were examined in the subgroup analysis. Results: The final meta-analysis comprised 11 retrospective studies of 6,088 NSCLC patients, of whom 1,483 had LNM. The pooled sensitivity, specificity, and AUC of the AI-based imaging model for predicting LNM in NSCLC patients were 0.87 [95% confidence interval (CI): 0.80-0.91], 0.85 (95% CI: 0.78-0.89), and 0.92 (95% CI: 0.90-0.94). Based on the QUADAS-2 results, a risk of bias was detected in the patient selection and diagnostic tests of the included articles. However, the quality of the included articles was generally acceptable. The pooled sensitivity and specificity were heterogeneous (I2>75%). The meta-regression and subgroup analyses showed that imaging modality [computed tomography (CT) or positron emission tomography (PET)/CT], and the neural network method model design significantly affected heterogeneity of this study. Models employing sample size data from a single center and the least absolute shrinkage and selection operator (LASSO) method had greater sensitivity than other techniques. Using the Deek' s funnel plot, no publishing bias was found. The results of the sensitivity analysis showed that deleting each article one by one did not change the findings. Conclusions: Imaging data models based on AI algorithms have good diagnostic accuracy in predicting LNM in patients with NSCLC and could be applied in clinical settings.

Case report: A suspected case of chronic pulmonary sparganosis characterized by migrating cavities and tunnel sign.

A 20-year-old male patient with a 15-month history of recurrent cough and hemoptysis presented at our hospital with suspected pulmonary sparganosis. Computed Tomography (CT) revealed migratory and variable lesions ranging from patchy shadows to nodular and cavernous foci. Additionally, the location and morphology of the cavities changed rapidly. The patient's peripheral blood eosinophil count remained within the normal range throughout the course of the infection, and antibiotics (moxifloxacin) alleviated the symptoms. At the early stage of admission, there was a slight increase in neutrophil and basophil counts. Initial treatment with a standard dose of praziquantel led to a significant improvement in symptoms, but the symptoms soon relapsed. However, doubling the dose 4 months later eventually cured the disease. The migratory nature of the CT lesion and the presence of tunnel signs were key to diagnosing a parasitic infection. The variability and rapid changes in the lesion further facilitated the differentiation of the disease, which rarely manifests as a granulomatous cavity.

Multimodality Imaging Evaluation of Nasal Rhabdomyosarcoma in Adults: A Case Report and Literature Review.

BACKGROUND: Alveolar rhabdomyosarcoma (ARMS) predominantly affects adolescents aged 10-15 years and is distinguished by its high aggressiveness and adverse prognosis compared with other sarcomas. It exhibits a pronounced tendency for lymphatic and hematogenous metastases at early stages. ARMS commonly manifests in the limbs and genitourinary system, with occurrences in the head and neck region being relatively uncommon. The role of CT, MRI, and 18F-FDG positron emission tomography combined with computed tomography (PET/CT) in the diagnostic process of ARMS is yet to be fully established. CASE REPORT: We report the case of a 49-year-old woman who presented with hematological nasal discharge for one month. CT imaging revealed a soft tissue mass in the left nasal cavity. MRI demonstrated a marginally hypo- to isointense signal on T1-weighted images, a hyperintense signal on T2-weighted images, and heterogeneous enhancement post-contrast. 18F-FDG PET/CT identified a hypermetabolic lesion located within the left nasal cavity. Surgical intervention entailed the excision of the left intranasal mass and the skull base lesion. Postoperative pathological analysis indicated ARMS. CONCLUSION: Sinus ARMS is notably malignant and associated with a dismal prognosis. Accurate diagnosis depends on histopathological and immunohistochemical evaluation, complemented by genetic analysis for specific chromosomal translocations and fusion genes. Imaging techniques, including CT, MRI, and PET/CT, are crucial for assessing lesion extent and metastasis, supporting disease diagnosis, informing treatment choices, facilitating surgical planning, and monitoring response to therapy.

Comparison of two emergency cervical cerclage techniques in twin pregnancies: A retrospective cohort study matched with cervical dilation.

OBJECTIVES: This retrospective cohort study aimed to assess the efficacy of emergency cervical cerclage (ECC) performed with the combined McDonald-Shirodkar technique in twin pregnancies between 18 and 26 weeks of pregnancy with painless cervical dilation 1 to 6 cm. METHODS: A retrospective cohort study matched with the degree of cervical dilation was conducted. The study group (case group) included women with twin pregnancies undergoing combined McDonald-Shirodkar approach with cervical dilation ≥1 cm between 18 to 26 weeks of gestation at four institutions, from December 2015 to December 2022. To minimize confounding factors, we elucidated the causality structure using a directed acyclic graph and performed 1:1 case-control matching. A control group underwent the McDonald approach. The primary outcome was gestational age (GA) at delivery. The secondary outcomes were pregnancy latency; the rates of spontaneous preterm birth at <28, <30, <32, and <34 weeks; and neonatal outcomes. Additional subanalysis was performed by dividing the patients into two subgroups of women with cervical dilation ≥3 cm and <3 cm. RESULTS: A total of 84 twin pregnancies were managed with either the combined McDonald-Shirodkar approach (case group: n = 42) or the McDonald approach (control group: n = 42). Demographic characteristics were not significantly different in the two groups (P > 0.05). After adjusting for confounders that were represented by a directed acyclic graph, median GA at delivery was significantly higher (30.5 vs 27 weeks; Bate: 3.40 [95% confidence interval (CI), 2.13-4.67], P < 0.001) and median pregnancy latency was significantly longer (56 vs 28 days; Bate: 24.04 [95% CI, 13.31-34.78], P < 0.001) in the case group compared with the control group. Rates of spontaneous preterm birth at <28, <30, <32, and <34 weeks were significantly lower in the case group than in the control group. For neonatal outcomes, there was higher birth weight (1543.75 vs 980 g; Bate: 420.08 [95% CI, 192.18-647.98], P < 0.001) and significantly lower overall perinatal mortality (7.1% vs 31%; adjusted odds ratio, 0.16 [95% CI, 0.04-0.70], P = 0.014) in the case group compared with the control group. When cervical dilation was ≥3 cm, the combined McDonald-Shirodkar procedure can significantly reduce perinatal mortality (8.3% vs 46.7%; adjusted odds ratio, 0.09 [95% CI, 0.01-0.77], P = 0.028), significantly decrease the risk of delivery at <28 and <30 weeks, and prolong GA at delivery and pregnancy latency compared with the McDonald procedure. CONCLUSIONS: ECC performed with the combined McDonald-Shirodkar procedure in women with twin pregnancies who have cervical dilation 1 to 6 cm in midtrimester pregnancy may reduce the rate of spontaneous preterm birth and improve perinatal and neonatal outcomes compared with the McDonald procedure, especially for twin pregnancies in women with cervical dilation of 3 to 6 cm and prolapsed membranes.

Fungibility, accessibility and clinical utility of remote electronic fetal monitoring in improving maternal emotional status compared with traditional method: A multicenter prospective cohort analysis.

OBJECTIVE: Supported by remote signal processing techniques and wireless communication technology, remote electronic fetal monitoring (REFM) has emerged as a promising alternative to traditional electronic fetal monitoring (TEFM) in clinical practice. The aim of this study was to evaluate the comparability, accessibility, and clinical utility of REFM in contrast to TEFM. METHODS: This was a multicenter prospective cohort study. A cohort of 2900 pregnant women were enrolled from three medical centers between June 1, 2021 and June 31, 2022. Among them, 800 utilized REFM, with 760 of them completing the self-rating anxiety scale (SAS) and self-rating depression scale (SDS) assessments using the devices for 1 month. The control group comprised 2100 pregnant women who did not use REFM. Additionally, 80 pregnant women concurrently employed both REFM and TEFM, and their respective curve coincidence rates were determined through curve fitting. Primary outcomes encompassed pregnancy outcomes in both groups, average curve coincidence rates between REFM and TEFM, as well as SDS and SAS scores. RESULTS: Among the 760 pregnant women who completed SAS and SDS assessments, their average SAS scores before and after 1 month of REFM usage were 43.09 ± 8.04 and 41.58 ± 6.59, respectively. Concurrently, the average SDS scores before and after 1 month of REFM usage were 45.45 ± 9.60 and 44.80 ± 9.17, respectively. A statistically significant decrease was observed in SAS scores (P = 0.005), whereas no significant difference was noted in SDS scores (P = 0.340). Furthermore, a statistically significant difference in the rate of adverse pregnancy outcomes (neonatal asphyxia) emerged between the two groups, those who employed REFM and those who did not (P = 0.021). In the subset of 80 pregnant women employing both REFM and TEFM, all 80 results showed precise congruence between the two methods. The average coincidence rate was determined to be 79.45% ± 12.64%. CONCLUSION: REFM contributes to improved pregnancy outcomes and exhibits a high level of concordance with TEFM, thereby accurately reflecting the quality of fetal heart monitoring. Additionally, REFM effectively mitigates pregnant women's anxiety. Thus, REFM demonstrates comparability, accessibility, and clinical utility.

Prediction of CD3 T cells and CD8 T cells expression levels in non-small cell lung cancer based on radiomic features of CT images.

Background: In this work, radiomics characteristics based on CT scans were used to build a model for preoperative evaluation of CD3 and CD8 T cells expression levels in patients with non-small cell lung cancer (NSCLC). Methods: Two radiomics models for evaluating tumor-infiltrating CD3 and CD8 T cells were created and validated using computed tomography (CT) images and pathology information from NSCLC patients. From January 2020 to December 2021, 105 NSCLC patients with surgical and histological confirmation underwent this retrospective analysis. Immunohistochemistry (IHC) was used to determine CD3 and CD8 T cells expression, and all patients were classified into groups with high and low CD3 T cells expression and high and low CD8 T cells expression. The CT area of interest had 1316 radiomic characteristics that were retrieved. The minimal absolute shrinkage and selection operator (Lasso) technique was used to choose components from the IHC data, and two radiomics models based on CD3 and CD8 T cells abundance were created. Receiver operating characteristic (ROC), calibration curve, and decision curve analyses were used to examine the models' ability to discriminate and their clinical relevance (DCA). Results: A CD3 T cells radiomics model with 10 radiological characteristics and a CD8 T cells radiomics model with 6 radiological features that we created both demonstrated strong discrimination in the training and validation cohorts. The CD3 radiomics model has an area under the curve (AUC) of 0.943 (95% CI 0.886-1), sensitivities, specificities, and accuracy of 96%, 89%, and 93%, respectively, in the validation cohort. The AUC of the CD8 radiomics model was 0.837 (95% CI 0.745-0.930) in the validation cohort, with sensitivity, specificity, and accuracy values of 70%, 93%, and 80%, respectively. Patients with high levels of CD3 and CD8 expression had better radiographic results than patients with low levels of expression in both cohorts (p<0.05). Both radiomic models were therapeutically useful, as demonstrated by DCA. Conclusions: When making judgments on therapeutic immunotherapy, CT-based radiomic models can be utilized as a non-invasive way to evaluate the expression of tumor-infiltrating CD3 and CD8 T cells in NSCLC patients.

Study on the dynamic change law and correlation between CT imaging manifestations and cellular immunity of 2019 novel coronavirus disease.

PURPOSE: To explore the dynamic changes and correlation between CT imaging manifestations and cellular immunity of COVID-19. MATERIALS AND METHODS: This retrospective review analyzed 23 patients with COVID-19, including 13 males and 10 females aged 27-70 years, with an average age of 48 years. Patients were divided into two groups: group A with 11 critical-severe patients, and group B with 12 common-mild patients. Clinical, laboratory, and radiological data were collected and analyzed. RESULTS: LYM, LYM (%), CD3+, CD4+, and CD8+ decreased, while NEU (%), CRP, and CT scores increased in all patients, WBC in group A increased. In group A, on day 10-12 after disease onset, CT scores and CRP reached the highest point, and day 13-15 LYM, LYM (%) reached the lowest but NEU (%) and WBC reached the highest, CD3+, CD4+ and CD8+ were at the lowest on day 10-15. In group B, on day 7-9, CT scores, NEU (%) and CRP reached the peak, but LYM, LYM (%), CD3+, CD4+ and CD8+ reached the lowest. In all patients, CT scores had a significantly negative correlation with CD3+, CD4+, CD8+, LYM (%), and LYM (p = 0.001, r = - 0.797; p = 0.008, r = - 0.698; p = 0.002, r = - 0.775; p < 0.001, r = - 0.785; p = 0.021, r = - 0.571, respectively), and a significantly positive correlation with WBC and NEU (%) (p < 0.001, r = 0.785; p = 0.003, r = 0.691, respectively). CONCLUSION: Dynamic changes of CT manifestations and cellular immunity of patients with COVID-19 were regular and correlation was high between these two parameters.