Supporting data for ＂Development of a novel bone void detection algorithm based on phantom-less quantitative computed tomography technique and its application in osteoporosis and osteoporotic fracture screening＂

Background: Early screening and intervention for osteoporosis is the key to prevent osteoporotic vertebral compression fracture (VCF). Phantom-less quantitative computed tomography (PL-QCT) technique provides opportunistic screening of osteoporosis but its accuracy is influenced by ROI (region of interest) selection of reference soft tissues. An automatic ROI selection might improve the performance of PL-QCT. Moreover, novel algorithms based on routine computed tomography (CT) images could provide alternative tools for bone quality assessment.Objectives: This thesis aimed to (1) validate the accuracy of an automatic PL-QCT system and extend its application to endplates and subchondral bones; (2) develop a novel bone void detection algorithm and validate its accuracy; (3) explore the bone void distribution in thoracic and lumbar vertebrae; (4) assess the reliability and feasibility of bone void in screening osteoporotic VCF.Methods and results: (1) The automatic PL-QCT system was compared with a phantom-based QCT (PB-QCT) system via a retrospective cohort and a prospective multi-center cohort. Bone mineral density (BMD) measured by two systems highly correlated, and the bias was nearly negligible (-0.9984±16.52mg/cm3). QCT identified higher osteoporosis proportion than dual energy X-ray absorptiometry (DEXA) and screened osteoporosis with good sensitivity and specificity. Furthermore, PL-QCT was used to detect the BMD distribution of endplates and subchodral bones. The lower endplate and subchondral bone demonstrated higher BMD than the upper ones, respectively. The outer edge exhibited higher BMD than central area in the endplates. The posterior regions presented higher BMD than anterior regions in the subchondral bones. (2)Based on PL-QCT technique, a novel bone void detection algorithm was developed. A bone void was defined as area with a BMD 16.5mm3. Artificial bone voids were made in the vertebral body of pig lumbar specimen and detected by our algorithm and third-party software, respectively. The results showed a high consistency and an acceptable bias in void volume between two groups. (3)The multi-center QCT data was used to explore the bone void distribution in thoracolumbar spine. The lumbar vertebrae displayed a higher bone void detection rate and a larger normalized void volume than the thoracic vertebrae. Additionally, void volume correlated positively with age and increased rapidly after age 55. Bone void could distinguish normal, osteopenia, and osteoporosis with high sensitivity and specificity. (4) Retrospective age and gender-matched case and control cohorts were used to investigate the discriminatory ability of bone void for VCF. Results showed that VCF group exhibited lower BMD and T-score, but larger bone void indicators relative to control group. The fracture severity positively correlated with estimated bone void indicator. Moreover, bone void showed superior discriminatory ability compared to BMD and T-score, offering higher sensitivity and specificity.Conclusions: The automatic PL-QCT system was a reliable technique and could be applied on vertebral endplates and subchonral bones. This study further developed a novel bone void detection algorithm and validated its reliability for bone quality assessment. The bone void could be a novel intuitive indicator to screening osteoporosis and discriminate osteoporotic fracture, outperforming DEXA-derived BMD.

背景：骨质疏松症的早期筛查和干预是预防骨质疏松性椎体压缩性骨折（VCF）的关键。无模型量化计算机断层扫描（PL-QCT）技术为骨质疏松症提供了有利的筛查手段，但其准确性受参照软组织感兴趣区域（ROI）选择的影响。自动ROI选择可能提高PL-QCT的性能。此外，基于常规计算机断层扫描（CT）图像的新算法可为骨质量评估提供替代工具。研究目标：本论文旨在（1）验证自动PL-QCT系统的准确性，并扩展其应用至椎体终板和软骨下骨；（2）开发一种新的骨空洞检测算法并验证其准确性；（3）探讨胸腰椎骨空洞的分布；（4）评估骨空洞在筛查骨质疏松性VCF中的可靠性和可行性。方法与结果：（1）通过回顾性队列和前瞻性多中心队列，将自动PL-QCT系统与基于模型量化计算机断层扫描（PB-QCT）系统进行了比较。两种系统测量的骨矿物质密度（BMD）高度相关，偏差几乎可以忽略不计（-0.9984±16.52mg/cm3）。QCT识别出的骨质疏松比例高于双能X射线吸收测定法（DEXA），且对骨质疏松的筛查具有良好灵敏度和特异性。此外，PL-QCT用于检测椎体终板和软骨下骨的BMD分布。较低的终板和软骨下骨的BMD分别高于较高的部位。终板的外边缘BMD高于中心区域。在软骨下骨中，后部区域的BMD高于前部区域。（2）基于PL-QCT技术，开发了一种新的骨空洞检测算法。骨空洞被定义为BMD为16.5mm3的区域。在猪腰椎标本的椎体中人工制造骨空洞，并分别由我们的算法和第三方软件检测。结果显示，两组在空洞体积上具有高度一致性，偏差可接受。（3）使用多中心QCT数据探讨了胸腰椎骨空洞的分布。腰椎的骨空洞检测率和标准化空洞体积均高于胸椎。此外，空洞体积与年龄呈正相关，并在55岁后迅速增加。骨空洞能够以高灵敏度和特异性区分正常、骨量减少和骨质疏松。（4）通过回顾性年龄和性别匹配的病例组和对照组队列，研究了骨空洞对VCF的鉴别能力。结果显示，与对照组相比，VCF组的BMD和T-score较低，但骨空洞指标较大。骨折严重程度与估计的骨空洞指标呈正相关。此外，骨空洞的鉴别能力优于BMD和T-score，具有更高的灵敏度和特异性。结论：自动PL-QCT系统是一种可靠的检测技术，可用于椎体终板和软骨下骨。本研究进一步开发了一种新的骨空洞检测算法，并验证了其在骨质量评估中的可靠性。骨空洞可能成为筛查骨质疏松和鉴别骨质疏松性骨折的新型直观指标，其性能优于DEXA获得的BMD。