Paukovitsch Michael, Fechner Tom, Felbel Dominik, Moerike Johannes, Rottbauer Wolfgang, Klömpken Steffen, Brunner Horst, Kloth Christopher, Beer Meinrad, Sekuboyina Anjany, Buckert Dominik, Kirschke Jan S, Sollmann Nico
Department of Cardiology, Ulm University Heart Center, Albert-Einstein-Allee 23, 89081, Ulm, Germany.
Department of Diagnostic and Interventional Radiology, University Hospital Ulm, Albert-Einstein-Allee 23, 89081, Ulm, Germany.
Arch Osteoporos. 2025 Jul 17;20(1):100. doi: 10.1007/s11657-025-01579-4.
CT-based opportunistic screening using artificial intelligence finds a high prevalence (43%) of osteoporosis in CT scans obtained for planning of transcatheter aortic valve replacement. Thus, opportunistic screening may be a cost-effective way to assess osteoporosis in high-risk populations.
Osteoporosis is an underdiagnosed condition associated with fractures and frailty, but may be detected in routine computed tomography (CT) scans.
Volumetric bone mineral density (vBMD) was measured in clinical routine thoraco-abdominal CT scans of 207 patients for planning of transcatheter aortic valve replacement (TAVR) using an artificial intelligence (AI)-based algorithm.
43% of patients had osteoporosis (vBMD < 80 mg/cm L1-L3) and were elderly (83.0 {interquartile range [IQR]: 78.0-85.5} vs. 79.0 {IQR: 71.8-84.0} years, p < 0.001), more often female (55.1 vs. 28.8%, p < 0.001), and had a higher Society of Thoracic Surgeon's score for mortality (3.0 {IQR:1.8-4.6} vs. 2.1 {IQR: 1.4-3.2}%, p < 0.001). In addition to lumbar vBMD (58.2 ± 14.7 vs. 106 ± 21.4 mg/cm, p < 0.001), thoracic vBMD (79.5 ± 17.9 vs. 127.4 ± 26.0 mg/cm, p < 0.001) was also significantly reduced in these patients and showed high diagnostic accuracy for osteoporosis assessment (area under curve: 0.96, p < 0.001). Osteoporotic patients were significantly more often at risk for falls (40.4 vs. 22.9%, p = 0.007) and required help in activities of daily life (ADL) more frequently (48.3 vs. 33.1%, p = 0.026), while direct-to-home discharges were fewer (88.8 vs. 96.6%, p = 0.026). In-hospital bleeding complications (3.4 vs. 5.1%), stroke (1.1 vs. 2.5%), and death (1.1 vs. 0.8%) were equally low, while in-hospital device success was equally high (94.4 vs. 94.9%, p > 0.05 for all comparisons). However, one-year probability of survival was significantly lower (84.0 vs. 98.2%, log-rank p < 0.01).
Applying an AI-based algorithm to TAVR planning CT scans can reveal a high rate of 43% patients having osteoporosis. Osteoporosis may represent a marker related to frailty and worsened outcome in TAVR patients.
使用人工智能进行基于CT的机会性筛查发现，在为经导管主动脉瓣置换术规划而进行的CT扫描中，骨质疏松症的患病率很高（43%）。因此，机会性筛查可能是评估高危人群骨质疏松症的一种具有成本效益的方法。
骨质疏松症是一种诊断不足的疾病，与骨折和虚弱有关，但可能在常规计算机断层扫描（CT）中被检测到。
使用基于人工智能（AI）的算法，在207例为经导管主动脉瓣置换术（TAVR）规划而进行的临床常规胸腹CT扫描中测量骨体积密度（vBMD）。
43%的患者患有骨质疏松症（vBMD < 80 mg/cm L1-L3），且年龄较大（83.0 {四分位间距[IQR]：78.0-85.5}岁对79.0 {IQR：71.8-84.0}岁，p < 0.001），女性比例更高（55.1%对28.8%，p < 0.001），胸外科医师协会死亡率评分更高（3.0 {IQR：1.8-4.6}%对2.1 {IQR：1.4-3.2}%，p < 0.001）。除腰椎vBMD（58.2 ± 14.7对106 ± 21.4 mg/cm，p < 0.001）外，这些患者的胸椎vBMD（79.5 ± 17.9对127.4 ± 26.0 mg/cm，p < 0.001）也显著降低，并且在骨质疏松症评估中显示出高诊断准确性（曲线下面积：0.96，p < 0.001）。骨质疏松症患者跌倒风险显著更高（40.4%对22.9%，p = 0.007），日常生活活动（ADL）中更频繁需要帮助（48.3%对33.1%，p = 0.026），而直接回家出院的患者较少（88.8%对96.6%，p = 0.026）。院内出血并发症（3.4%对5.1%）、中风（1.1%对2.5%）和死亡（1.1%对0.8%）同样较低，而院内器械成功率同样较高（94.4%对94.9%，所有比较p > 0.05）。然而，一年生存率显著更低（84.0%对98.2%，对数秩检验p < 0.01）。
将基于AI的算法应用于TAVR规划CT扫描可发现43%的患者患有骨质疏松症。骨质疏松症可能是TAVR患者虚弱和预后恶化的一个相关标志物。
