Radiomics model based on preoperative gadoxetic acid-enhanced MRI for predicting liver failure

BACKGROUND Postoperative liver failure is the most severe complication in cirrhotic patients with hepatocellular carcinoma(HCC) after major hepatectomy. Current available clinical indexes predicting postoperative residual liver function are not sufficiently accurate.AIM To determine a radiomics model based on preoperative gadoxetic acid-enhanced magnetic resonance imaging for predicting liver failure in cirrhotic patients with HCC after major hepatectomy.METHODS For this retrospective study, a radiomics-based model was developed based on preoperative hepatobiliary phase gadoxetic acid-enhanced magnetic resonance images in 101 patients with HCC between June 2012 and June 2018. Sixty-one radiomic features were extracted from hepatobiliary phase images and selected by the least absolute shrinkage and selection operator method to construct a radiomics signature. A clinical prediction model, and radiomics-based model incorporating significant clinical indexes and radiomics signature were built using multivariable logistic regression analysis. The integrated radiomics-based model was presented as a radiomics nomogram. The performances of clinical prediction model, radiomics signature, and radiomics-based model for predicting post-operative liver failure were determined using receiver operating characteristics curve, calibration curve, and decision curve analyses.RESULTS Five radiomics features from hepatobiliary phase images were selected to construct the radiomics signature. The clinical prediction model, radiomics signature, and radiomics-based model incorporating indocyanine green clearance rate at 15 min and radiomics signature showed favorable performance for predicting postoperative liver failure(area under the curve: 0.809-0.894). The radiomics-based model achieved the highest performance for predicting liver failure(area under the curve: 0.894; 95%CI: 0.823-0.964). The integrated discrimination improvement analysis showed a significant improvement in the accuracy of liver failure prediction when radiomics signature was added to the clinical prediction model(integrated discrimination improvement = 0.117, P =0.002). The calibration curve and an insignificant Hosmer-Lemeshow test statistic(P = 0.841) demonstrated good calibration of the radiomics-based model. The decision curve analysis showed that patients would benefit more from a radiomics-based prediction model than from a clinical prediction model and radiomics signature alone.CONCLUSION A radiomics-based model of preoperative gadoxetic acid–enhanced MRI can be used to predict liver failure in cirrhotic patients with HCC after major hepatectomy.     

HPLC-MS Method for Simultaneous Quantitative Determination of an Innovative Russian Gestagen and its Metabolites in Rat and Rabbit Blood Sera

Pharmaceutical Chemistry Journal - An HPLC-MS method for simultaneous quantitative determination of a novel gestagenic pharmaceutical and two of its metabolites in rat and rabbit blood sera was...     

不伴红细胞增多的慢性阻塞性肺疾病患者并发肺栓塞的影响因素研究

背景　慢性阻塞性肺疾病（COPD）患者肺栓塞（PE）发生率显著高于常人，但目前不伴红细胞增多的COPD患者并发PE的机制尚不明确。目的　探讨不伴红细胞增多的COPD患者并发PE的影响因素。方法　本研究为回顾性病例对照研究。收集2017年1-12月在新疆医科大学第一附属医院呼吸与呼吸危重症中心住院治疗的血红蛋白（Hb）≤140 g/L的COPD患者。依据肺多层螺旋CT肺血管成像（CTPA）检查结果将患者分为并发PE组和单纯COPD组。记录患者的年龄、性别、合并症、服用抗血小板或抗凝药物史。采用倾向性评分匹配（PSM）方法，通过二元Logistic回归分析估计倾向性评分值，采用1∶1最邻近原则匹配，卡钳值为0.05，筛选出基线相同的两组病例。记录患者的D-二聚体、血常规检查结果，比较两组间差异；分析不伴红细胞增多的COPD患者并发PE的影响因素，红细胞分布宽度（RDW）与中性粒细胞/淋巴细胞比值（NLR）的相关性。结果　共纳入病例339例，其中单纯COPD组289例，并发PE组50例。采用PSM方法筛选两组患者，最终得到单纯COPD组、并发PE组各50例进行后续研究。并发PE组患者D-二聚体、中性粒细胞计数（N）、RDW、NLR高于单纯COPD组，淋巴细胞计数（L）低于单纯COPD组（P<0.05）。二元Logistic回归分析结果显示，RDW是不伴红细胞增多的COPD患者并发PE的影响因素〔OR=1.561，95%CI（1.096，2.225），P<0.05〕。Spearman秩相关分析结果显示，不伴红细胞增多的COPD患者RDW与NLR呈正相关（rs=0.225，P<0.05）。结论　RDW升高是Hb≤140 g/L的COPD患者并发PE的危险因素，且RDW与NLR呈正相关。     

Erosive pustular dermatosis of the scalp in an adolescent with near‐total hair regrowth: Case report and review of the literature

Erosive pustular dermatosis of the scalp (EPDS) is an uncommon chronic inflammatory response to scalp trauma that usually resolves with cicatricial alopecia. It most commonly affects elderly patients with a history of actinic damage. Herein, we describe a 16‐year‐old girl with acrofacial dysostosis type 1 presenting after surgery with crusting purulent scalp lesions, whose clinical presentation and histopathologic findings were consistent with EPDS. A review of the literature on EPDS in children is also detailed.     

Utility of Tissue Similarity Maps Based on Relative Cerebral Blood Volume for Grading Gliomas as Validated by Histological Results

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Uncertainty evaluation at three spatial scales for the NDVI-based VWC estimation method used in the SMAP algorithm

Vegetation water content (VWC) is the key input parameter for a soil moisture retrieval algorithm based on microwave remote sensing, and VWC uncertainty can limit the estimated accuracy of soil moisture. There has been little research on VWC algorithm development and validation in China, and the uncertainty of the VWC estimation method has not been well evaluated. Therefore, the aim of this study is to evaluate the uncertainty of the VWC estimation method used in the SMAP (Soil Moisture Active Passive) algorithm on three spatial scales (the point-scale, 30 m scale, and 1 km scale) for maize in northeast China. Results from three ground experimental datasets showed that the SMAP VWC estimation method was strongly biased with an average overestimation of 1.16 kg m^?2,1.04 kg m^?2, and 1.13 kg m^?2 for the point-scale, 30 m scale, and 1 km scale respectively, and maximum bias occurred in the mid-stage of maize. Also, a new power relationship between NDVI (Normalized Difference Vegetation Index) and VWC was proposed for the 30 m scale based on Sentinel 2 NDVI and field VWC values from 2017 experiment, with respective R² (coefficient of determination) and Root Mean Squared Error (RMSE) values of 0.80 and 0.67 kg m^?2. The results confirmed that this power relationship was still suitable for VWC estimation at the 1 km scale, and it has smaller bias than the original SMAP VWC method. Future work will be carried out to evaluate the applicability of this VWC estimation method over a lager region. It is expected that it can improve the accuracy of soil moisture by providing high precision VWC input parameters.