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1.
《Diagnostic and interventional imaging》2020,101(9):555-564
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%. 相似文献
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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. 相似文献
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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. 相似文献
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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. 相似文献
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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. 相似文献
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提出了文题所述的控制策略,依据输出分布曲线的特征变量选取方法和依据该项信息的规则控制系统。仿真研究得到了满意的结果。在一个实验性二元精馏塔上用IBM-PC进行试验亦获成功。本法对具有非线性特性的分布参数对象,较常规控制策略有明显的优越性。 相似文献
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研究了LDPE/CPE/炭黑三相复合导电体系的导性能和电流-电压特性。实验结果表明复合体系具有明显的导电渗滤效应,在共混比LDPE/CPE>50/50时,导电性能随CPE含量增加而显著提高,这主要是由于炭黑粒子在LDPE和CPE两组分分中的分布不均匀性所致。 相似文献