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PurposeAttempts by magnetic resonance (MR) manufacturers to help imaging centres improve patient throughput has led to the development of more automated acquisition. This software is capable of customizing individual scan alignment; potentially improving imaging efficiency and standardizing protocols. However, substantial investments are required to introduce such systems, potentially deterring their widespread application. This study assessed the implementation costs and reduction in examination durations for automated knee MR imaging (MRI) software.Materials and MethodsResearch activities were performed at a community-based academic centre on a 3-Tesla (3-T) system using Siemens' Day Optimizing Throughput (Dot) knee software. Examination acquisition times were extracted from the system before and after software implementation. Fiscal year 2012/13 finances were used to determine the average hourly cost of MRI utilization. Costs associated with automated software implementation were also calculated. Finally, the number of knee scans required to achieve a positive return on investment using the software was established.Results and DiscussionThe mean (standard deviation, sample size) pre- and post-Dot software scan times were 23.20 (4.18, n = 266) and 21.94 (4.51, n = 59) minutes, respectively, for a routine knee scan and 11.88 (1.60, n = 74) and 11.24 (1.51, n = 27) minutes, respectively, for a fast knee scan. The overall weighted average resulted in a 64-second time savings per automated knee examination. This negligible time savings would be extremely difficult to make use of clinically. Dot simplified 29 unique knee protocols to two, improving the consistency of knee examinations. Current Dot software is not compatible with all patients and therefore has limitations that are a concern among MR technologists.ConclusionAdoption of automated knee systems could assist in standardizing protocols; however, the cost of implementation and difficulty in modifying patient scheduling to reflect the minimal time savings would make a financial return unlikely to occur at small- and medium-sized institutions.  相似文献   
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IntroductionThis study aims to construct learning curves related to the realization of standardized postprocessing by radiographer students and to discuss their exploitation and interest.Materials and MethodsThis study was carried out in 21 French students in their 3rd year of training. Two postprocessing protocols in CT (#1 traumatic shoulder; #2 petrous bone) were repeated 15 times by each student. Each achievement was timed to obtain overall learning curves. The realization accuracy was also assessed for each student at each repetition.ResultsThe learning rates for the two protocols are 63% and 56%, respectively. The number of repetitions to reach the reference time for each protocol is 11 and 12, respectively. In both protocols, the standard deviations are significantly reduced and stabilized during repetitions. The mean accuracy progresses more quickly in protocol #1.DiscussionThe measured learning rates reflect a rapid learning process for each protocol. The analysis of the standard deviations shows that students have reached a homogeneous level. The average times and accuracies measured during the last repetitions show that the group has reached a high level of performance. Building learning curves helps students measure their progress and motivates them.ConclusionObtaining learning curves allows trainers/supervisors to qualify the learning difficulty of a task while motivating students/radiographers. The use of learning curves is inline with the competency-based training paradigm.  相似文献   
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目的 分析H型高血压患者的舌面诊图像颜色参数特征,探讨H型高血压患者的舌诊、面诊变化规律。方法 运用上海中医药大学自行研制的Smart TCM-1型中医舌面一体仪,采集高血压患者舌面诊图像,提取特征参数,分析健康对照组、H型高血压组与非H型高血压组患者舌面颜色参数特征。结果 ①在舌色各项参数中,H型高血压组舌尖部R值、B值、V值均显著小于健康对照组(P < 0.01);非H型高血压组舌尖部B值显著小于健康对照组(P < 0.01),S值较健康对照组显著增大(P < 0.05);H型高血压组舌尖部R、V值均明显小于非H型高血压组(P < 0.05)。在舌苔各项参数中,H型高血压组舌中H值、V值均明显小于健康对照组(P < 0.05);非H型高血压组舌中V值、舌右V值均显著小于健康对照组(P < 0.01);H型高血压组舌中H值明显小于非H型高血压组(P < 0.05),右侧舌苔S值明显大于非H型高血压组(P < 0.05)。②H型高血压组面色参数鼻G值、下颌G值、口唇R值、口唇V值均明显小于健康对照组(P < 0.05);非H型高血压组前额H值、目眶H值、脸颊H值、鼻H值、下颌H值、整体H值均明显大于健康对照组(P < 0.05);H型高血压组前额H值、目眶G值、目眶H值、脸颊H值、鼻G值、鼻H值、下颌R值、下颌G值、下颌H值、下颌V值、口唇R值、口唇G值、口唇V值、整体R值、整体G值、整体H值、整体V值均明显小于非H型高血压组(P < 0.05)。结论 H型高血压患者苔色偏黄,以舌中部为主,且舌右侧黄苔积聚较明显;H型高血压患者面色为黄中带红,口唇、下颌部更为晦暗。H型高血压患者的舌、面诊特征参数的变化,与高血压病阳亢湿盛病机相符。  相似文献   
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Background and aims

Since accelerated atherosclerosis has been reported in systemic lupus erythematosus (SLE), predictive biomarkers of cardiovascular disease (CVD) are needed. Among non-traditional risk factors, bone mineral density (BMD) has been related to CVD. However, its role in SLE remains controversial. This study aims to analyze the associations of subclinical atherosclerosis with traditional and non-traditional CV risk factors.

Methods and results

In a cross-sectional study, atherosclerosis burden was compared between 112 female SLE patients and 31 controls. Plaque number and carotid intima-media wall thickness (cIMT) were assessed by ultrasonography. In a retrospective study, BMD determinations obtained 5-years before the ultrasonography assessment were analyzed in a subgroup of 62 patients. Plaque frequency was increased in SLE, even in patients without CV events or carotid wall thickening. cIMT was increased in patients with CVD, positively correlated with body mass index (BMI). Interestingly, a paradoxical effect of BMI on carotid parameters was observed. Whereas underweight patients (BMI < 20) showed increased prevalence of carotid plaques with low cIMT, those with BMI > 30 showed higher cIMT and plaque burden. Overweight patients (25 < BMI<30) exhibited both elevated cIMT and plaque number. BMI was an independent predictor of BMD. In our retrospective study, patients with either clinical or subclinical CVD exhibited lower BMD levels than their CV-free counterparts. A low lumbar spine BMD independently predicted CVD development after adjusting for confounders.

Conclusion

SLE was associated with a higher subclinical atherosclerosis burden, a bimodal effect being observed for BMI. Decreased BMD can be a CV risk biomarker in SLE.  相似文献   
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