Department of Medical Physics in Radiation Oncology, German Cancer Research Center (DKFZ), Im Neuenheimer Feld 280, 69120 Heidelberg, Germany.
Med Phys. 2013 Dec;40(12):123501. doi: 10.1118/1.4828843.
Most of the patients who died of breast cancer have developed bone metastases. To understand the pathogenesis of bone metastases and to analyze treatment response of different bone remodeling therapies, preclinical animal models are examined. In breast cancer, bone metastases are often bone destructive. To assess treatment response of bone remodeling therapies, the volumes of these lesions have to be determined during the therapy process. The manual delineation of missing structures, especially if large parts are missing, is very time-consuming and not reproducible. Reproducibility is highly important to have comparable results during the therapy process. Therefore, a computerized approach is needed. Also for the preclinical research, a reproducible measurement of the lesions is essential. Here, the authors present an automated segmentation method for the measurement of missing bone mass in a preclinical rat model with bone metastases in the hind leg bones based on 3D CT scans.
The affected bone structure is compared to a healthy model. Since in this preclinical rat trial the metastasis only occurs on the right hind legs, which is assured by using vessel clips, the authors use the left body side as a healthy model. The left femur is segmented with a statistical shape model which is initialised using the automatically segmented medullary cavity. The left tibia and fibula are segmented using volume growing starting at the tibia medullary cavity and stopping at the femur boundary. Masked images of both segmentations are mirrored along the median plane and transferred manually to the position of the affected bone by rigid registration. Affected bone and healthy model are compared based on their gray values. If the gray value of a voxel indicates bone mass in the healthy model and no bone in the affected bone, this voxel is considered to be osteolytic.
The lesion segmentations complete the missing bone structures in a reasonable way. The mean ratio vr∕vm of the reconstructed bone volume vr and the healthy model bone volume vm is 1.07, which indicates a good reconstruction of the modified bone.
The qualitative and quantitative comparison of manual and semi-automated segmentation results have shown that comparing a modified bone structure with a healthy model can be used to identify and measure missing bone mass in a reproducible way.
大多数死于乳腺癌的患者都发生了骨转移。为了了解骨转移的发病机制并分析不同骨重塑疗法的治疗反应，研究人员检查了临床前动物模型。在乳腺癌中，骨转移通常是骨破坏性的。为了评估骨重塑疗法的治疗反应，必须在治疗过程中确定这些病变的体积。对于缺失结构的手动描绘，特别是如果大部分缺失，是非常耗时且不可重复的。可重复性对于治疗过程中获得可比的结果非常重要。因此，需要一种计算机方法。对于临床前研究，病变的可重复测量也是必不可少的。在这里，作者提出了一种基于 3D CT 扫描的自动分割方法，用于测量后腿骨中有骨转移的临床前大鼠模型中缺失的骨量。
将受影响的骨结构与健康模型进行比较。由于在这项临床前大鼠试验中，转移仅发生在右侧后腿，这是通过使用血管夹来保证的，因此作者将左侧身体作为健康模型。使用统计形状模型对左侧股骨进行分割，该模型使用自动分割的骨髓腔进行初始化。使用体积生长从胫骨骨髓腔开始，在股骨边界处停止，对左侧胫骨和腓骨进行分割。将这两个分割的掩模图像沿中平面镜像，并通过刚性配准手动转移到受影响骨骼的位置。基于其灰度值比较受影响的骨骼和健康模型。如果一个体素的灰度值表示健康模型中的骨量且在受影响的骨骼中没有骨，则认为该体素为溶骨性。
病变分割以合理的方式完成了缺失的骨骼结构。重建骨体积 vr 和健康模型骨体积 vm 的比值 vr∕vm 的平均值为 1.07，这表明对修改后的骨骼进行了良好的重建。
手动和半自动分割结果的定性和定量比较表明，将修改后的骨骼结构与健康模型进行比较，可以用于以可重复的方式识别和测量缺失的骨量。
