Manual correction of automatically generated contours for high-resolution peripheral quantitative computed tomography can be time consuming and introduces precision error. However, bias related to the automated protocol is unknown. This study provides insight into error bias that is present when using uncorrected contours and inter-operator precision error based on operator training. INTRODUCTION High-resolution peripheral quantitative computed tomography workflow includes manually correcting contours generated by the manufacturer's automated protocol. There is interest in minimizing corrections to save time and reduce precision error; however, bias related to the automated protocol is unknown. This study quantifies error bias when contours are uncorrected and identifies the impact of operator training on bias and precision error. METHODS Forty-five radii and tibiae scans across a representative range of bone density were analyzed using the automated and manually corrected contours of three operators, with training ranging from beginner to expert, and compared with a "ground truth" to estimate bias. Inter-operator precision was measured across operators. RESULTS The tibia had greater error bias than the radius when contours were uncorrected, with compartmental bone mineral densities and cortical microarchitecture having greatest biases, which could have significant implications for interpretation of studies using this skeletal site. Bias and precision error were greatest when contours were corrected by the beginner operator; however, when this operator was removed, bias was no longer present and inter-operator precision was between 0.01 and 3.74% for all parameters except cortical porosity. CONCLUSION These findings establish the need for manual correction and provide guidance on operator training needed to maximize workflow efficiency.

中文翻译：

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优化HR-pQCT工作流程：偏差和精确度误差的比较，用于定量骨分析。

手动校正自动生成的轮廓以进行高分辨率外围定量计算机断层扫描可能很耗时，并且会导致精度误差。但是，与自动化协议有关的偏差是未知的。这项研究提供了对基于操作员培训的未校正轮廓和操作员间精度误差时出现的误差偏差的见解。简介高分辨率外围定量计算机断层扫描工作流程包括手动校正由制造商的自动协议生成的轮廓。有必要使校正最小化以节省时间并减少精度误差。但是，与自动化协议相关的偏见是未知的。本研究量化了轮廓未校正时的误差偏差，并确定了操作员培训对偏差和精度误差的影响。方法使用三个操作员的自动和手动校正轮廓，分析了代表骨密度范围内的四十五个半径和胫骨扫描，训练范围从初学者到专家，并与“地面真相”进行比较以估计偏差。跨操作员之间的操作员之间的精度进行了测量。结果当轮廓未校正时，胫骨的误差偏差比半径大，隔室的骨矿物质密度和皮质微结构的偏差最大，这可能对使用该骨骼部位进行研究的解释具有重要意义。当初学者对轮廓进行校正时，偏差和精度误差最大。但是，删除该操作员后，将不再存在偏差，并且操作员之间的精度在0.01到3之间。除皮质孔隙度外，所有其他参数均为​​74％。结论这些发现确定了手动校正的必要性，并为最大限度地提高工作流程效率所需的操作员培训提供了指导。