Validation of an on-screen application-based measurement of shoulder range of motion over telehealth medium

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不同年龄阿尔茨海默病患者脑核团ADC值与年龄的相关性

目的 探讨不同年龄阿尔茨海默病（AD）患者ADC值与年龄的相关性。方法 选取30例AD患者（AD组）和年龄与之相匹配的30名志愿者（对照组），按年龄段各分为6个亚组[55~59岁（n=3）、60~64岁（n=4）、65~70岁（n=9）、71~74岁（n=5）、75~80岁（n=6）、>80岁（n=3）]，测量双侧海马、红核、尾状核、杏仁体、壳核ADC值，并进行配对t检验、独立样本t检验、单因素方差分析及Pearson相关分析。结果 AD组红核左、右侧ADC值有统计学差异（P=0.022）。AD组不同年龄亚组右侧海马、双侧尾状核、右侧壳核ADC值差异有统计学意义（P均<0.05）；2组不同年龄亚组双侧海马、壳核、尾状核ADC值差异有统计学意义（P均<0.05）。AD组右侧海马（r=0.615，P<0.001）、右侧壳核（r=0.653，P=0.001）及双侧尾状核（左侧：r=0.397，P=0.030；右侧：r=0.429，P=0.020）ADC值与年龄呈正相关。结论 AD患者右侧海马和壳核、双侧尾状核ADC值随年龄增加而增大。ADC值可为临床预测和早期诊断AD脑内右侧海马和壳核、双侧尾状核神经退行性病变提供参考。     

Polymerase Chain Reaction and Goldmann-Witmer Coefficient Testing in the Diagnosis of Infectious Uveitis in HIV-Positive and HIV-Negative Patients in South Africa

Purpose: To use polymerase chain reaction (PCR) and Goldmann-Witmer coefficient (GWC) calculation to diagnose infectious uveitis.

Methods: Prospective cross-sectional study.

Results: Twenty-seven of 106 patients had positive PCR and/or GWC results on aqueous humor (AH) sampling and 15 of 27 (55.6%) were HIV-positive. Patients with non-anterior uveitis (NAU) were more likely to be HIV+ (p = 0.005). More than 1 possible pathogen was identified in 9 of 27 patients of whom 7 were HIV+. The final clinical diagnosis was discordant with AH findings in 9 of 27 cases. A positive EBV PCR result was associated with a discordant diagnosis (p = 0.001). All cases of herpetic anterior uveitis (42.9% HIV+) tested PCR-/GWC+ while all cases of herpetic NAU tested PCR+/GWC- (83.3% HIV+). All rubella virus cases were PCR+/GWC+.

Conclusion: PCR is useful to diagnose herpetic NAU in HIV+ patients while GWC is useful to diagnose herpetic anterior uveitis.     

调整Kappa角及光学切削直径对准分子激光原位角膜磨镶术后的影响

目的　评价调整光学切削直径及Kappa角后对准分子激光原位角膜磨镶术（laser in situ keratomileusis，LASIK）后效果的影响。方法　选取2017年1月至12月在我院行LASIK手术的高度近视患者313例（626眼），根据切削直径分成两组，试验组157例314眼，切削直径设定为6.0 mm，对照组156例312眼，切削直径设定为6.5 mm。试验组患者激光切削前修正Kappa角，对照组不做修正。患者术前进行裸眼视力、主视眼确定、验光、眼压、暗室下瞳孔直径、泪液分泌试验、裂隙灯、散瞳验光、眼底检查、pentacam测量角膜厚度、角膜地形图测量角膜前后表面及Kappa角等检查。术后1 d、1周、1个月随访，并检查裸眼视力、角膜厚度、波前像差及夜间视力、光晕、眩光等情况。比较两组患者角膜厚度变化、手术所用时间以及两组患者术后的高阶像差的差异。结果　试验组与对照组患者年龄分别为18～44（24.19±5.33）岁、18～42（25.08±4.91）岁，屈光度分别为（-7.47±1.04）D、（-7.61±1.12）D。两组年龄、屈光度比较差异均无统计学意义（均为P>0.05）。试验组与对照组患者术前Kappa角分别为，X轴:（210±40）μm、（200±30）μm，Y轴:（190±30）μm、（220±40）μm，差异无统计学意义（P=0.210）。两组手术前后的角膜厚度及术后角膜基质床的厚度差异均无统计学意义（均为P>0.05）。试验组与对照组的手术时间分别为（15.56±1.89）s和（20.83±3.03）s，差异有统计学意义（P=0.000）。试验组的总高阶像差和垂直慧差的变化均明显低于对照组（均为 P<0.01），但两组间的水平慧差差异无统计学意义（P>0.05），对照组的球差低于试验组（P<0.01）。结论　LASIK手术中科学合理地调整Kappa角可有助于提高患者术后的视觉质量。     

Morphological imaging and CT histogram analysis to differentiate pancreatic neuroendocrine tumor grade 3 from neuroendocrine carcinoma

PurposeTo compare morphological imaging features and CT texture histogram parameters between grade 3 pancreatic neuroendocrine tumors (G3-NET) and neuroendocrine carcinomas (NEC).Materials and methodsPatients with pathologically proven G3-NET and NEC, according to the 2017 World Health Organization classification who had CT and MRI examinations between 2006-2017 were retrospectively included. CT and MRI examinations were reviewed by two radiologists in consensus and analyzed with respect to tumor size, enhancement patterns, hemorrhagic content, liver metastases and lymphadenopathies. Texture histogram analysis of tumors was performed on arterial and portal phase CT images. images. Morphological imaging features and CT texture histogram parameters of G3-NETs and NECs were compared.ResultsThirty-seven patients (21 men, 16 women; mean age, 56 ± 13 [SD] years [range: 28-82 years]) with 37 tumors (mean diameter, 60 ± 46 [SD] mm) were included (CT available for all, MRI for 16/37, 43%). Twenty-three patients (23/37; 62%) had NEC and 14 patients (14/37; 38%) had G3-NET. NECs were larger than G3-NETs (mean, 70 ± 51 [SD] mm [range: 18 - 196 mm] vs. 42 ± 24 [SD] mm [range: 8 - 94 mm], respectively; P = 0.039), with more tumor necrosis (75% vs. 33%, respectively; P = 0.030) and lower attenuation on precontrast (30 ± 4 [SD] HU [range: 25-39 HU] vs. 37 ± 6 [SD] [range: 25-45 HU], respectively; P = 0.002) and on portal venous phase CT images (75 ± 18 [SD] HU [range: 43 - 108 HU] vs. 92 ± 19 [SD] HU [range: 46 - 117 HU], respectively; P = 0.014). Hemorrhagic content on MRI was only observed in NEC (P = 0.007). The mean ADC value was lower in NEC ([1.1 ± 0.1 (SD)] × 10⁻³ mm²/s [range: (0.91 - 1.3) × 10⁻³ mm²/s] vs. [1.4 ± 0.2 (SD)] × 10⁻³ mm²/s [range: (1.1 - 1.6) × 10⁻³ mm²/s]; P = 0.005). CT histogram analysis showed that NEC were more heterogeneous on portal venous phase images (Entropy-0: 4.7 ± 0.2 [SD] [range: 4.2-5.1] vs. 4.5 ± 0.4 [SD] [range: 3.7-4.9]; P = 0.023).ConclusionPancreatic NECs are larger, more frequently hypoattenuating and more heterogeneous with hemorrhagic content than G3-NET on CT and MRI.     

Impact of sampling rate on statistical significance for single subject fMRI connectivity analysis

A typical time series in functional magnetic resonance imaging (fMRI) exhibits autocorrelation, that is, the samples of the time series are dependent. In addition, temporal filtering, one of the crucial steps in preprocessing of functional magnetic resonance images, induces its own autocorrelation. While performing connectivity analysis in fMRI, the impact of the autocorrelation is largely ignored. Recently, autocorrelation has been addressed by variance correction approaches, which are sensitive to the sampling rate. In this article, we aim to investigate the impact of the sampling rate on the variance correction approaches. Toward this end, we first derived a generalized expression for the variance of the sample Pearson correlation coefficient (SPCC) in terms of the sampling rate and the filter cutoff frequency, in addition to the autocorrelation and cross‐covariance functions of the time series. Through simulations, we illustrated the importance of the variance correction for a fixed sampling rate. Using the real resting state fMRI data sets, we demonstrated that the data sets with higher sampling rates were more prone to false positives, in agreement with the existing empirical reports. We further demonstrated with single subject results that for the data sets with higher sampling rates, the variance correction strategy restored the integrity of true connectivity.     

扩散加权成像在鉴别颅内环形强化病灶的价值

目的讨论扩散加权成像(DWI)和表观扩散系数(ADC)在鉴别颅内环形强化病灶性质的价值。资料与方法应用1.5TMR对16例胶质瘤、6例转移瘤、4例脑脓肿进行常规MR及DWI成像和ADC测量,分析其影像学表现。结果4例脑脓肿在DWI上呈高信号,16例胶质瘤和6例转移瘤呈低信号,脓肿腔平均ADC值为0.44×10-3cm2/s,脑肿瘤坏死囊变区平均ADC值为1.82×10-3cm2/s(P<0.01)。结论DWI和ADC值可以用来鉴别脑脓肿及坏死囊变的肿瘤病灶。     

灰关联分析应用于因素分析时关联度指标的改进

本文指出在应用灰关联分析进行因素分析时传统的关联度计算方法的不足，并提出采用新的关联度指标来表示因素之间的关联关系，同时给出了实例介绍计算方法。