Prospective characterization of incident hepatic steatosis in pediatric and adolescent patients after total pancreatectomy with islet autotransplantation

BackgroundHepatic steatosis has been described as a common finding in adults following total pancreatectomy with islet autotransplantation (TPIAT) but it is unknown if this occurs in children and adolescents.ObjectivesTo define the frequency of post-TPIAT hepatic steatosis in a sample of children and adolescents and to identify clinical predictors of incident steatosis post-TPIAT.MethodsIn this prospective study, consecutive participants at least 1-month post-TPIAT underwent a liver MRI with proton density fat fraction (PDFF) and blood draw at our pediatric academic medical center between April 2021 and January 2022. Comparison clinical pre-TPIAT liver MRI or ultrasound and insulin use and graft function data were extracted from the medical record. T-tests were used for the comparison of means across continuous variables between participants with and without post-TPIAT steatosis.ResultsA total of 20 participants (mean: 13 ± 4 years; 12 female) were evaluated. Mean liver PDFF at research MRI was 7.4 ± 6.2% (range: 2–25%). Seven participants (35%) had categorical hepatic steatosis (PDFF>5%) post-TPIAT, five of whom had pre-TPIAT steatosis, reflecting a 13% (2/15; 95% CI: 2–40%) incidence of post-TPIAT steatosis. Participant characteristics were not significantly different between subgroups with and without post-TPIAT steatosis. Mean PDFF at research MRI was not different between graft function subgroups (7.5% optimal/good vs. 7.3% marginal/failure; p = .96).ConclusionOur study shows a moderate prevalence but low incidence of hepatic steatosis in a small sample of children and adolescents post-TPIAT. This study raises questions about a causal relationship between TPIAT and hepatic steatosis.     

儿童1型糖尿病骨密度变化及影响因素分析

目的 测定儿童1型糖尿病(T1DM)患者骨密度(BMD),分析探讨骨密度变化的影响因素。方法 选取于2018年1月—2021年6月于我院收治的儿童1型糖尿病患者76例,收集性别、年龄、发病年龄、身高、体重、BMI、病程等基本资料,检测空腹血糖、空腹C肽、糖化血红蛋白(HbA1c)、血碳酸氢根(HCO3-)、血清碱性磷酸酶(ALP),应用双能X线吸收测定法测定骨密度,获取Z值。结果 76例儿童1型糖尿病患者骨密度Z值为-0.93±2.14。HbA1c、病程与骨密度Z值呈负相关,差异具有统计学意义(分别B=-0.334,P<0.001;B=-0.191,P=0.017)。结论 儿童1型糖尿病患者骨密度低于健康儿童,血糖控制不良、病程长是1型糖尿病儿童骨密度减低的危险因素。     

Preoperative comprehensive malignancy risk estimation for thyroid nodules: Development and verification of a network-based prediction model

BackgroundIn order to avoid excessive treatment of thyroid nodules in the clinic, it is necessary to find a simple and practical analysis method to comprehensively and accurately reflect benign or malignant thyroid nodules. This study aimed to construct and validate a comprehensive and reliable network-based predictive model using a variety of imaging and laboratory criteria for thyroid nodules to stratify the risk of malignancy prior to surgery.MethodsWe retrospectively analyzed data from patients who underwent surgical treatment for thyroid nodules at the Thyroid and Breast Diagnosis and Treatment Center of Weifang Hospital of Traditional Chinese Medicine between January 2018 and December 2020. Binary logical regression analysis was performed to predict whether nodules were malignant or benign. The developmental dataset included 457 patients (January 2018–December 2020). The validation set included separate data points (n = 225, January 2018–December 2020).ResultsIn this study, criteria that showed significant predictive value for malignant nodules included TI-RADS: 4b (p = 0.065); Bethesda IV, Bethesda V, Bethesda VI (P < 0.0001); BRAF^V600E mutation (P < 0.0001); Calcitonin>5 pg/ml (p = 0.0037); and FNA-Tg>30 ng/ml (p = 0.0003). A 10-grade risk scoring system was developed. The risk of malignancy risk ranged from 2.06% to 100% and was positively associated with increasing risk grade. The areas under the receiver-operating characteristic curve of the development and validation sets were 0.972 and 0.946, respectively.ConclusionA simple, comprehensive and reliable web-based predictive model was designed using a variety of imaging and laboratory criteria to stratify thyroid nodules by probability of malignancy.     

Valvuloplasty of fetal pulmonary atresia with intact ventricular septum and hypoplastic right heart: Mid-term follow-up results

ObjectiveThis study aimed to analyze and evaluate the results of mid-term follow-up after fetal pulmonary valvuloplasty (FPV) in fetuses with pulmonary atresia with intact ventricular septum (PA/IVS).MethodsFrom August 31, 2018, to May 31, 2019, seven fetuses with PA/IVS and hypoplastic right heart were included in this study. All underwent echocardiography by the same specialist and were operated on by the same team. Intervention and echocardiography data were collected, and changes in the associated indices noted during follow-up were analyzed.ResultsAll seven fetuses successfully underwent FPV. The median gestational age at FPV was 27.54 weeks. The average FPV procedural time was 6 ?min. Persistent bradycardia requiring treatment occurred in 4/7 procedures. Finally, five pregnancies were successfully delivered, and the other two were aborted. Compared to data before fetal cardiac interventions (FCI), tricuspid valve annulus diameter/mitral valve annulus diameter (TV/MV) and right ventricle diameter/left ventricle diameter (RV/LV) of all fetuses had progressively improved. The maximum tricuspid regurgitation velocity decreased from 4.60 ?m/s to 3.64 ?m/s. The average follow-up time was 30.40 ?± ?2.05 months. During the follow-up period, the diameter of the tricuspid valve ring in five children continued to improve, and the development rate of the tricuspid valve was relatively obvious from 6 months to 1 year after birth. However, the development of the right ventricle after birth was relatively slow. It was discovered that there were individual variations in the development of the right ventricle during follow-up.ConclusionThe findings support the potential for the development of the right ventricle and tricuspid valve in fetuses with PA/IVS who underwent FCI. Development of the right ventricle and tricuspid valve does not occur synchronously during pregnancy. The right ventricle develops rapidly in utero, but the development of tricuspid valve is more apparent after birth than in utero.     

Cancer Stem Cells and Circulatory Tumor Cells Promote Breast Cancer Metastasis

Breast cancer (BC) is a highly metastatic, pathological cancer that significantly affects women worldwide. The mortality rate of BC is related to its heterogeneity, aggressive phenotype, and metastasis. Recent studies have highlighted that the tumor microenvironment (TME) is critical for the interplay between metastasis mediators in BC. BC stem cells, tumor-derived exosomes, circulatory tumor cells (CTCs), and signaling pathways dynamically remodel the TME and promote metastasis. This review examines the cellular and molecular mechanisms governing the epithelial to mesenchymal transition (EMT) that facilitate metastasis. This review also discusses the role of cancer stem cells (CSCs), tumor-derived exosomes, and CTs in promoting BC metastasis. Furthermore, the review emphasizes major signaling pathways that mediate metastasis in BC. Finally, the interplay among CSCs, exosomes, and CTCs in mediating metastasis have been highlighted. Therefore, understanding the molecular cues that mediate the association of CSCs, exosomes, and CTCs in TME helps to optimize systemic therapy to target metastatic BC.     

Caractéristiques de l’atteinte cardiaque au cours de la granulomatose éosinophilique avec polyangéite

Aim of the studyOur study aimed to identify the characteristics of cardiac involvement in eosinophilic granulomatosis with polyangiitis (EGPA).MethodsWe conducted a retrospective analytic study including EGPA cases diagnosed between 2000 and 2019 in an internal medicine department. Diagnosis was made according to the 1990 American College of Rheumatology criteria and the 2012 Chapel Hill Concensus.ResultsEleven EGPA cases were included, 64% of patients were female. Median age at diagnosis was 52 years [42–58]. Heart damage revealed EGPA in 55% of cases with a significant predominance of women (p = 0.015). The main cardiac manifestations were myocarditis, ischemic cardiomyopathy due to small vessel vasculitis, cardiac tamponade and intracardiac thrombus. Cardiac magnetic resonance imaging (MRI) mainly showed subendocardial hyposignal in early infusion and late enhancement in the same areas, nodular by locations, associated with impaired left ventricle function and micro-infarctions by distal vasculitis. Cardiac damage was associated to ANCA negativity in 83.3% of cases. The median Birmingham Vasculitis Activity Score version3 (BVAS v3) was 16 [10–17]. Under conventional treatment, no relapses had occurred. The median vasculitis damage index (VDI) was 2 [1–2.3] and the mortality rate was zero after a mean follow-up of 43 months.ConclusionCardiomyopathy is a frequent revealing mode of EGPA. A late onset asthma and hypereosinophilia should guide the diagnosis. As ANCA research often turns out to be negative, histological evidence is recommended in this context. The contribution of cardiac MRI in the diagnosis of EGPA remains to be defined.     

Comparing Radiomics features of tumour and healthy liver tissue in a limited CT dataset: A machine learning study

IntroductionLiver cancer lesions on Computed Tomography (CT) withholds a great amount of data, which is not visible to the radiologists and radiographer. Radiomics features can be extracted from the lesions and used to train Machine Learning (ML) algorithms to predict between tumour and liver tissue. The purpose of this study was to investigate and classify Radiomics features extracted from liver tumours and normal liver tissue in a limited CT dataset.MethodsThe Liver Tumour Segmentation Benchmark (LiTS) dataset consisting of 131 CT scans of the liver with segmentations of tumour tissue and healthy liver was used to extract Radiomic features. Extracted Radiomic features included size, shape, and location extracted with morphological and statistical techniques according to the International Symposium on Biomedical Imaging manual. Relevant features was selected with chi2 correlation and principal component analysis (PCA) with tumour and healthy liver tissue as outcome according to a consensus between three experienced radiologists. Logistic regression, random forest and support vector machine was used to train and validate the dataset with a 10-fold cross-validation method and the Grid Search as hyper-parameter tuning. Performance was evaluated with sensitivity, specificity and accuracy.ResultsThe performance of the ML algorithms achieved sensitivities, specificities and accuracy ranging from 96.30% (95% CI: 81.03%–99.91%) to 100.00% (95% CI: 86.77%–100.00%), 91.30% (95% CI: 71.96%–98.93%) to 100.00% (95% CI: 83.89%–100.00%)and 94.00% (95% CI: 83.45%–98.75%) to 100.00% (95% CI: 92.45%–100.00%), respectively.ConclusionML algorithms classifies Radiomics features extracted from healthy liver and tumour tissue with perfect accuracy. The Radiomics signature allows for a prognostic biomarker for hepatic tumour screening on liver CT.Implications for practiceDifferentiation between tumour and liver tissue with Radiomics ML algorithms have the potential to increase the diagnostic accuracy, assist in the decision-making of supplementary multiphasic enhanced medical imaging, as well as for developing novel prognostic biomarkers for liver cancer patients.