Bone Quality Research Lab, Department of Radiology and Biomedical Imaging, University of California, San Francisco, CA, USA.
J Bone Miner Res. 2023 Jul;38(7):1006-1014. doi: 10.1002/jbmr.4819. Epub 2023 May 13.
Although second-generation high-resolution peripheral quantitative computed tomography (XCTII) provides the highest-resolution in vivo bone microstructure assessment, the manufacturer's standard image processing protocol omits fine features in both trabecular and cortical compartments. To optimize fine structure segmentation, we implemented a binarization approach based on a Laplace-Hamming (LH) segmentation and documented the reproducibility and accuracy of XCTII structure segmentation using both the standard Gaussian-based binarization and the proposed LH segmentation approach. To evaluate reproducibility, 20 volunteers (9 women, 11 men; aged 23-75 years) were recruited, and three repeat scans of the radii and tibias were acquired using the manufacturer's standard in vivo protocol. To evaluate accuracy, cadaveric structure phantoms (14 radii, 6 tibias) were scanned on XCTII using the same standard in vivo protocol and on μCT at 24.5 μm resolution. XCTII images were analyzed twice-first, with the manufacturer's standard patient evaluation protocol and, second, with the proposed LH segmentation approach. The LH approach rescued fine features evident in the grayscale images but omitted or overrepresented (thickened) by the standard approach. The LH approach significantly reduced error in trabecular volume fraction (BV/TV) and thickness (Tb.Th) compared with the standard approach; however, higher error was introduced for trabecular separation (Tb.Sp). The LH approach improved the correlation between XCTII and μCT for cortical porosity (Ct.Po) and significantly reduced error in cortical pore diameter (Ct.Po.Dm) compared with the standard approach. The LH approach resulted in improved precision compared with the standard approach for BV/TV, Tb.Th, Ct.Po, and Ct.Po.Dm at the radius and for Ct.Po at the tibia. Our results suggest that the proposed LH approach produces substantially improved binary masks, reduces proportional bias, and provides greater accuracy and reproducibility in important outcome metrics, all due to more accurate segmentation of the fine features in both trabecular and cortical compartments. © 2023 The Authors. Journal of Bone and Mineral Research published by Wiley Periodicals LLC on behalf of American Society for Bone and Mineral Research (ASBMR).
尽管第二代高分辨率外周定量计算机断层扫描 (XCTII) 提供了最高分辨率的活体骨微观结构评估，但制造商的标准图像处理协议忽略了小梁和皮质腔室中的精细特征。为了优化精细结构分割，我们实现了一种基于拉普拉斯-汉明 (LH) 分割的二值化方法，并记录了使用标准基于高斯的二值化和所提出的 LH 分割方法的 XCTII 结构分割的可重复性和准确性。为了评估可重复性，招募了 20 名志愿者（9 名女性，11 名男性；年龄 23-75 岁），并使用制造商的标准体内协议获得了桡骨和胫骨的三次重复扫描。为了评估准确性，使用相同的标准体内协议在 XCTII 上扫描了 14 个桡骨和 6 个胫骨的尸体结构体模，并在 24.5 μm 分辨率的 μCT 上进行了扫描。XCTII 图像首先使用制造商的标准患者评估协议进行分析，然后使用所提出的 LH 分割方法进行分析。LH 方法挽救了标准方法中明显的灰度图像中的细微特征，但忽略或过度表示（增厚）了标准方法中的特征。与标准方法相比，LH 方法显著降低了小梁体积分数 (BV/TV) 和厚度 (Tb.Th) 的误差；然而，对于小梁分离 (Tb.Sp)，引入了更高的误差。与标准方法相比，LH 方法提高了 XCTII 和 μCT 之间的皮质孔隙率 (Ct.Po) 的相关性，并显著降低了皮质孔径 (Ct.Po.Dm) 的误差。与标准方法相比，LH 方法提高了桡骨处的 BV/TV、Tb.Th、Ct.Po 和 Ct.Po.Dm 以及胫骨处的 Ct.Po 的精度。我们的结果表明，所提出的 LH 方法产生了大大改进的二进制掩模，减少了比例偏差，并提供了更准确和可重复的重要结果指标，这一切都归因于小梁和皮质腔室中的精细特征的更准确分割。2023 年，作者。《骨与矿物研究杂志》由 Wiley 期刊公司代表美国骨与矿物研究协会 (ASBMR) 出版。
