Radius fractures are among the most common fracture types; however, there is limited consensus on the standard of care. A better understanding of the fracture healing process could help to shape future treatment protocols and thus improve functional outcomes of patients. High-resolution peripheral quantitative computed tomography (HR-pQCT) allows monitoring and evaluation of the radius on the micro-structural level, which is crucial to our understanding of fracture healing. However, current radius fracture studies using HR-pQCT are limited by the lack of automated contouring routines, hence only including small number of patients due to the prohibitively time-consuming task of manually contouring HR-pQCT images. In the present study, a new method to automatically contour images of distal radius fractures based on 3D morphological geodesic active contours (3D-GAC) is presented. Contours of 60 HR-pQCT images of fractured and conservatively treated radii spanning the healing process up to one year post-fracture are compared to the current gold standard, hand-drawn 2D contours, to assess the accuracy of the algorithm. Furthermore, robustness was established by applying the algorithm to HR-pQCT images of intact radii of 73 patients and comparing the resulting morphometric indices to the gold standard patient evaluation including a threshold- and dilation-based contouring approach. Reproducibility was evaluated using repeat scans of intact radii of 19 patients. The new 3D-GAC approach offers contours within inter-operator variability for images of fractured distal radii (mean Dice score of 0.992 ± 0.004 versus median operator Dice score of 0.993 ± 0.006). The generated contours for images of intact radii yielded morphometric indices within the in vivo reproducibility limits compared to the current gold standard. Additionally, the 3D-GAC approach shows an improved robustness against failure (n = 4) when dealing with cortical interruptions, fracture fragments, etc. compared with the automatic, default manufacturer pipeline (n = 40). Using the 3D-GAC approach assures consistent results, while reducing the need for time-consuming hand-contouring.

中文翻译：

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通过体内HR-pQCT图像的3D测地线主动轮廓自动对骨折远端半径进行自动分割

半径裂缝是最常见的裂缝类型之一。但是，关于护理标准的共识有限。对骨折愈合过程的更好理解可能有助于制定未来的治疗方案，从而改善患者的功能结局。高分辨率外围定量计算机断层扫描（HR-pQCT）可在微观结构水平上监测和评估半径，这对于我们了解骨折愈合至关重要。然而，由于缺乏自动轮廓绘制程序，目前使用HR-pQCT进行的radius骨骨折研究受到局限，由于手动绘制HR-pQCT图像的轮廓绘制过程非常耗时，因此仅包括少量患者。在目前的研究中，提出了一种基于3D形态测地线活动轮廓线（3D-GAC）的radius骨远端骨折图像自动轮廓化的新方法。将跨越骨折后长达一年的愈合过程的60张HR-pQCT图像的等高线轮廓与当前的金标准手绘2D等高线进行比较，以评估算法的准确性。此外，通过将算法应用于73例患者完整半径的HR-pQCT图像，并将所得形态指标与金标准患者评估（包括基于阈值和扩张的轮廓法）进行比较，从而建立了鲁棒性。通过重复扫描19例患者的完整半径来评估其可重复性。新的3D-GAC方法可为骨折远端半径的图像在操作者间差异内提供轮廓（平均Dice得分为0.992±0.004，而中位操作者Dice得分为0.993±0.006）。为完整半径的图像生成的轮廓在与目前的金标准相比，体内重现性限制。此外，与自动的默认制造商流水线（n = 40）相比，在处理皮质中断，骨折碎片等时，3D-GAC方法显示出更高的抗故障鲁棒性（n = 4）。使用3D-GAC方法可确保获得一致的结果，同时减少了费时的手动轮廓绘制的需求。