目的:比较区域Hounsfield单位(aHU)的性能,体积亨氏单位(vHU),通过定量CT(QCT)区分椎骨骨折(VFs)的风险和体积骨矿物质密度(vBMD)。
方法:我们回顾性纳入101例腰椎VFs的CT扫描(60名女性,平均年龄:64±4岁;41名男性,平均年龄:73±10岁),性别和年龄匹配的101名对照受试者(60名女性,平均年龄:64±4岁;41名男性,平均年龄:72±7岁)。为了评估aHU的歧视能力,vHU,以及L1和L2水平的vBMD测量,以识别椎骨骨折,我们对男性和女性进行了二元逻辑回归和受试者工作特征(ROC)曲线分析.灵敏度,特异性,阳性预测值(PPV),并计算阴性预测值(NPV)。
结果:在有和没有VF的男性和女性中,aHU,vHU,和vBMD高度相关(r2从0.832到0.957,所有p<0.001)。aHU有统计学上的显著差异,vHU,有和没有VF的受试者之间的vBMD(p<0.001)。当年龄,性别和BMI作为协方差考虑并同时调整,AHU的赔率比(OR),vHU,和vBMD值,代表VF的风险,显著(p<0.001)。与aHU和vHU相比,vBMD与VF风险更密切相关(vBMD:OR,6.29;95%CI,3.83-10.35vsvHU:或,3.64;95%CI,2.43-5.46vs.HU:OR,2.56;95%CI,1.79-3.67)。在男人和女人中,进一步,vBMD具有更高的AUC值,灵敏度,特异性,PPV,和净现值与vHU相比,vHU反过来超过aHU。使用平均aHU区分VFs的接收器工作特征曲线下面积(AUC),vHU,两个椎骨的vBMD男性为0.72、0.77和0.87,女性为0.76、0.79和0.86。在男人和女人中,当采用三种测量时,AUC存在统计学上的显著差异-即,aHU,vHU,和vBMD-区分骨折(p<0.05)。
结论:QCT测量的骨矿物质密度与急性VFs的相关性高于腰椎的vHU和aHU值。尽管使用vHU和aHU值诊断骨质疏松和区分骨折风险仅限于特定的扫描仪和成像方案,他们在机会性骨质疏松症筛查方面有很大的潜力,尤其是vHU。
OBJECTIVE: To compare the performance of areal Hounsfield units (aHUs), volumetric Hounsfield units (vHUs), and volumetric bone mineral density (vBMD) by quantitative CT (QCT) in discriminating vertebral fractures (VFs) risk.
METHODS: We retrospectively included CT scans of the lumbar spine 101 VFs cases (60 women, mean age: 64 ± 4 years; 41 men, mean age: 73 ± 10 years) and sex- and age-matched 101 control subjects (60 women, mean age: 64 ± 4 years; 41 men, mean age: 72 ± 7 years). In order to assess the discriminatory capability of aHU, vHU, and vBMD measurements at the L1 and L2 levels in identifying VFs, we conducted binary logistic regression and receiver operating characteristic (ROC) curve analyses in men and women. Sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) were calculated.
RESULTS: In both men and women with and without VFs, aHU, vHU, and vBMD were highly correlated with each other (r2 from 0.832 to 0.957, all P < .001). There was a statistically significant difference in aHU, vHU, and vBMD between subjects with and without VFs (P < .001). When age, gender, and BMI were taken into account as covariances and adjusted simultaneously, odds ratios (ORs) for aHU, vHU, and vBMD values, which represent the risk of VFs, were significant (P < .001). Compared with aHU and vHU, vBMD was more strongly associated with VF risk (vBMD: OR, 6.29; 95% CI, 3.83-10.35 vs vHU: OR, 3.64; 95% CI, 2.43-5.46 vs aHU: OR, 2.56; 95% CI, 1.79-3.67). In both men and women, further, vBMD had higher values for AUC, sensitivity, specificity, PPV, and NPV compared to vHU, with vHU in turn surpassing aHU. The area under the receiver operating characteristic curve (AUC) for discriminating VFs using the average aHU, vHU, and vBMD of 2 vertebrae was 0.72, 0.77, and 0.87 in men and 0.76, 0.79, and 0.86 in women. In both men and women, there exist statistically significant differences in the AUC when employing the 3 measurements-namely, aHU, vHU, and vBMD-to discriminate fractures (P < .05).
CONCLUSIONS: The QCT-measured vBMD is more associated with acute VFs than vHU and aHU values of the lumbar spine. Although the use of vHU and aHU values for the diagnosis of osteoporosis and discriminating fracture risk is limited to scanner- and imaging protocol-specific, they have great potential for opportunistic osteoporosis screening, particularly vHU.
CONCLUSIONS: The novelty of this study presents a comparison of the VF discriminative capabilities among aHU, vHU, and vBMD. The vHU values introduced in this study demonstrate a greater capacity to discriminate fractures compared to aHU, presenting an improved clinical choice. Although its discriminatory capability is slightly lower than that of vBMD, it is more convenient to measure and does not require specialized software.