兔死后肺CT影像随时间变化的规律性研究

Regular Changes of Postmortem Rabbit's Lungs Observed by Computed Tomographic Images with Time

目的研究兔不同原因死后129 h内肺CT影像随时间变化的规律。方法建立失血性休克、空气栓塞和缢死3种死亡模型;在不同死后间隔时间进行肺薄层螺旋CT扫描,结合专业的CT图像分析软件,观察肺平均CT值、肺面积/胸椎面积变化,并用SPSS19.0作统计学分析。结果不同死亡模型中,肺平均CT值均随死亡时间的延长呈先升高后降低趋势。肺面积/胸椎面积总体呈下降趋势,早期变化缓慢,随之下降迅速,后期下降相对缓慢。分别建立失血性休克、空气栓塞和缢死模型肺平均CT值和肺面积/胸椎面积与死后间隔时间的二项式回归方程,具有显著统计学意义(P<0.05)。结论基于CT影像技术建立兔死后肺面积/胸椎面积与死后间隔时间的非线性回归方程,可用于推断晚期死亡时间,可成为一种新的法医学推断死亡时间的方法。

ObjectiveTo investigate the time regularity by the computed tomographic images from lungs of the rabbit died from different causes.MethodsThree death models of hemorrhagic shock, air embolism and strangulation were respectively established for rabbit. The rabbit’s lungs were observed with thin spiral CT scanning at different postmortem intervals （PMI） and analyzed by professional CT image analysis software so that the ratio of lung area / thoracic area and the average lung CT values were determined.ResultsFor the three death models, the average lung CT values were all at the beginning increased then decreased with the PMI ascending. The ratio of lung area / thoracic area showed a similar trend within 129 h of PMI： its declining rate was low at the early stage, followed to a rapid change, and finally appeared slow again. For each of the three death models, multiple regression analysis was individually set up with PMI as the dependent variable and either the ratio of lung area / thoracic area or the average lung CT value as predictor, yielding several formulae of statistical signiifcance （P〈0.05）.R^2 was ranging from 0.437 to 0.551 for the average lung CT value and from 0.881 to 0.927 for the lung area / thoracic area.ConclusionsThe nonlinear regression equation of the lung tissue area / thoracic area can be applied to delimitate the PMI, especially the late PMI, making it a new potential tool for estimation of PMI in forensic medicine.