MSCT像素指数在慢性阻塞性肺疾病诊断中的应用价值初探

Preliminary Clinical Study of Pixel Index(PI) in Diagnosing COPD

目的结合临床肺功能检查,评价MSCT的像素指数(PI)指标在诊断慢性阻塞性肺疾病(COPD)方面的应用价值。资料与方法对40例临床确诊为COPD的患者及对照组26名健康志愿者,使用MSCT进行胸部扫描,测量和计算各PI的相关指标,并与临床肺功能指标进行相关性分析。用受试者工作特征曲线(ROC)法评价PI各项指标在预测诊断和筛检COPD患者的准确性和敏感性。结果正常组与COPD组在最大吸气末、呼气末时的PI值及PI变化比率存在明显差异(P<0.01)。最大呼气末像素指数(PIex)与FEV1和FEV1/FVC相关性最好,相关系数分别为-0.819,-0.841。PIin、PIex和PI变化比率最恰当预测COPD的临界点分别为33.9、5.1、7.0,其约登指数分别为0.73、0.966、0.937。其中以PIex的临界值预测诊断准确性最高,诊断COPD敏感性为96.6%、特异性为100%。结论MSCT能便捷、准确地获得评价肺功能的指标,与临床肺功能检查指标有很好的相关性。PI指标的临界值可用于预测诊断和筛检COPD患者,有较高的临床应用价值。

Objective To evaluate the clinical value of the MSCT pixel index in the diagnosis of chronic obstructive pulmonary disease （COPD）. Materials and Methods The MSCT chest CT scanning was used between the group of 40 patients clinically diagnosed COPD and 26 healthy volunteers as comparison group, the pixel index （PI） of the relevant indicators was measured and calculated, the pertinence between pixel index （PI） and indicators of clinical lung function was also analyzed. And then, by using ROC curve method, an evaluation of the accuracy and sensitivity of every indicator in pixel index （PI） on forecasting diagnosis and screening COPD patients will be made. Results There were significant differences between the healthy group and the COPD group in PI and the ratio of the change of P1 （ P 〈 0.01 ） when inspiratory and expiratory were maximal. The PIex showed best correlation with FEVI% and FEVI/FVC （r = -0. 819, -0. 841, P 〈 0.001 ）. The most appropriate critical point of PI in maximum inspiratory, PI in maximum expiratory and the ratio of change of PI for forecasting COPD were 33.9,5.1,7.0 respectively. The Youdeng indexes were 0.73,0. 966,0. 937 respectively. Among the three indexes, the critical point of PI in maximum expiratory ranked the most accurate in forecasting diagnosis. which diagnosis sensitivity was 96.6%, the diagnosis specificity was 100% and the Youden＇s index was 0. 966. Conclusion MSCT pixel index has very close relativity with the indicator of clinical lung functional tests, which can be used to evaluate the lung function indicator conveniently and accurately. The critical point of pixel index （PI） can be used in forecasting diagnosis and screening COPD patients and has very high clinical application value.