Differentiating autoimmune pancreatitis from pancreatic ductal adenocarcinoma with CT radiomics features

PurposeThe purpose of this study was to determine whether computed tomography (CT)-based machine learning of radiomics features could help distinguish autoimmune pancreatitis (AIP) from pancreatic ductal adenocarcinoma (PDAC).Materials and MethodsEighty-nine patients with AIP (65 men, 24 women; mean age, 59.7 ± 13.9 [SD] years; range: 21–83 years) and 93 patients with PDAC (68 men, 25 women; mean age, 60.1 ± 12.3 [SD] years; range: 36–86 years) were retrospectively included. All patients had dedicated dual-phase pancreatic protocol CT between 2004 and 2018. Thin-slice images (0.75/0.5 mm thickness/increment) were compared with thick-slices images (3 or 5 mm thickness/increment). Pancreatic regions involved by PDAC or AIP (areas of enlargement, altered enhancement, effacement of pancreatic duct) as well as uninvolved parenchyma were segmented as three-dimensional volumes. Four hundred and thirty-one radiomics features were extracted and a random forest was used to distinguish AIP from PDAC. CT data of 60 AIP and 60 PDAC patients were used for training and those of 29 AIP and 33 PDAC independent patients were used for testing.ResultsThe pancreas was diffusely involved in 37 (37/89; 41.6%) patients with AIP and not diffusely in 52 (52/89; 58.4%) patients. Using machine learning, 95.2% (59/62; 95% confidence interval [CI]: 89.8–100%), 83.9% (52:67; 95% CI: 74.7–93.0%) and 77.4% (48/62; 95% CI: 67.0–87.8%) of the 62 test patients were correctly classified as either having PDAC or AIP with thin-slice venous phase, thin-slice arterial phase, and thick-slice venous phase CT, respectively. Three of the 29 patients with AIP (3/29; 10.3%) were incorrectly classified as having PDAC but all 33 patients with PDAC (33/33; 100%) were correctly classified with thin-slice venous phase with 89.7% sensitivity (26/29; 95% CI: 78.6–100%) and 100% specificity (33/33; 95% CI: 93–100%) for the diagnosis of AIP, 95.2% accuracy (59/62; 95% CI: 89.8–100%) and area under the curve of 0.975 (95% CI: 0.936–1.0).ConclusionsRadiomic features help differentiate AIP from PDAC with an overall accuracy of 95.2%.     

小学生个性影响因素研究

【目的】分析影响儿童个性的有关因素，为培养儿童的健全人格提供依据。【方法】对西安市所属的七个区各随机抽取一所学校，每所学校抽取四、五、六年级各两个班．采用龚耀先修订的艾森克个性问卷（Eysenck Personality Questionnaire，EPQ）（儿童用）和自编的个人一般情况调查表，对2000名儿童进行调查。将调查所得数椐进行多元逐步回归分析。【结果】影响小学生个性精神性（Psy choticism，P）的因素有性别、是否班干部、父母关系；影响内外向（extrovision and intrnision，E）的因素有性别、父母关系、是否班干部、住所、母亲文化程度、所在学校；影响情绪稳定性（nearoticism，N）、掩饰性（lie,L）的均为性别、父母关系2个因素。【结论】儿童个性受家庭、学校环境等的多重影响。家长、教师应创造良好的家庭、社会环境，保持情绪乐观、稳定，避免对子女儿童的负面影响，以利于其个性向积极方向发展。     

Reassessment of the accuracy of traditional sperm characteristics and adenosine triphosphate (ATP) in estimating the fertilizing potential of human semen in vivo

Receiver operating characteristic curves and accuracy parameters were computed for traditional sperm characteristics (concentration, motility, morphology) and the number of peroxidase negative cells, and the concentration of adenosine triphosphate (ATP) in semen from populations of fertile and infertile men, and men who achieved a pregnancy after varicocele treatment. The percentage and concentration per millilitre of spermatozoa with rapid linear progressive motility, and the ATP concentration, provided the best discrimination between fertile and treated fertile from infertile men. The misclassification rate was higher for sperm morphology, total progressive motility and viability, whereas sperm concentration and the total sperm count per ejaculate had the worst discriminating power. The number of peroxidase negative cells per 100 spermatozoa was highly specific in identifying men who achieved pregnancy after varicocele treatment. The lower limit of normality of sperm characteristics was remarkably different between fertile men and men achieving pregnancy after treatment or during infertility work-up.     

Storage phosphor digital mammography

Digital mammography using storage phosphor CR is still in the investigational stage. It is the only digital mammography system that has been tested in preliminary clinical trials with promising early results. Further clinical studies are needed to assess the impact of the limited spatial resolution of storage phosphor technology on its application as a digital screening mammography system. Further studies also are needed to determine the optimum image processing parameters needed in digital mammography.     

抑郁障碍患者人格特征与发病关系的研究

目的探讨抑郁障碍患者的人格特征与其疾病发病间的关系。方法采用自评抑郁量表(SDS)、艾森克人格问卷 (EPQ)、应对方式评定量表 (WCRS)和归因方式问卷 (ASQ)对 76名抑郁障碍患者进行测试 ,同时选取 84名健康被试进行对照研究。结果①抑郁组患者在EPQ中神经质 (N)与精神质 (P)的得分显著高于健康组。②WCRS的结果显示在“宣泄接纳”、“退避调节”两个因子上 ,抑郁组的平均得分低于健康组。③在ASQ的得分中 ,抑郁组在负性事件归因的自身性、持久性和整体性均显著高于健康组。④抑郁障碍患者的“神经质”人格特质与应对方式的“宣泄接纳”和“退避调节”因子呈负相关 (r = 0 .474)。结论抑郁障碍患者的人格特征可表现为较强的神经质及孤僻、交往障碍 ,他们这种人格特征及应对和归因方式在其发病过程中起着重要作用。     

应用力学因素检测膝关节功能的实验研究

目的研究应用力学因素检测膝关节功能方法的有效性.方法利用测力平台测量得到人体下肢在运动过程中的力学曲线,用数学方法确定力学曲线的最大值F和曲线特征值R.结果给出51例骨关节炎患者的分析数据,并给出30例正常人的结果作为对照.结论应用力学因素可以有效地检测膝关节功能状态.     

Applying item response theory to enhance health outcomes assessment

Background Health-related quality of life (HRQL) is an accepted outcome measure in patients with mood and anxiety disorders. Yet, surprisingly little attention has been paid to the determinants. In this paper we test the hypothesis that it is associated with personality traits while controlling for mental disorders. Methods A large sample of outpatients (n=640) with mood and anxiety disorders was studied. The empirically supported five factor model of normal personality traits was assessed using the NEO-FFI and includes: neuroticism, extraversion, openness to experience, agreeableness, and conscientiousness. Mental disorders were assessed with the CIDI, and HRQL with the SF-36. Results Regression analyses revealed that the NEO-FFI scores, with the exception of conscientiousness, were significantly associated with SF-36 subscales and summary scores, independently from the mental disorders. The percentage of explained variance due to the personality traits was highest for the subscales Vitality (10.0%), Mental Health (13.3%) and the Mental Health Summary Score (9.5%). Furthermore, specific personality traits were related to specific SF-36 subscales. Conclusions A low HRQL of patients with mood or anxiety disorders is not only determined by the disease or the current health but is also shaped by personality traits that are relatively stable throughout an individual's life time.     

Novel ROC-type method for testing the efficiency of multivariate statistical methods in fMRI.

The receiver operating characteristic (ROC) method is a useful and popular tool for testing the efficiency of various diagnostic tests applicable to functional MRI (fMRI) data. Typically, the diagnostic tests are applied on simulated and pseudo-human fMRI data, and the area under the ROC curve is used as a measure of the efficiency of the diagnostic test. The effectiveness of such a method depends on how well the simulated data approximate the real data. For multivariate statistical methods, however, this technique is usually inadequate, as the spatial dependence among voxels is ignored for simulated data. In this work a modified ROC method using real fMRI data with a broader scope is proposed. This method can be applied to most fMRI postprocessing techniques, including multivariate analyses such as canonical correlation analysis (CCA). Also, the relationship of the modified ROC method with the conventional ROC method is discussed in detail.