摘要
目的 探讨DECT-MPI对冠状动脉微循环障碍(CMD)的应用价值。方法 通过植入单分散聚苯乙烯微球建立山羊CMD模型,完成心脏CT、SPECT、PET及CMR检查。将图像传输至后处理工作站,观察障碍心肌在四种检查方法中的分布区域,以病理学为金标准分析不同检查方法的敏感性、特异性。分别测量主动脉、正常及障碍心肌的碘浓度,计算标准化碘浓度(NID),比较正常与障碍心肌碘浓度及NID的差异。结果 四种方法评估CMD的敏感性分别为56.8%、68.4%、94.4%、50.0%;特异性分别为98.0%、99.0%、98.0%、100%。障碍心肌组碘浓度和NID(-0.200±1.005和-0.027±0.133)均低于正常心肌组(1.578±0.936和0.204±0.128),差异有统计学意义(P<0.05),且碘图、NID及二者联合分析障碍心肌AUC分别为81.7%、90.8%和93.6%。结论 多模态影像学中DECT在CMD的诊断中具有很高的应用价值,碘图、NID联合指标诊断CMD效能较好,为人体临床实验提供研究基础及影像学参数。
Objective To evaluate the diagnostic value of DECT-MPI in goat coronary microcirculation disorder(CMD) using pathology as gold standard. Methods We established the model of coronary microcirculation disorder in goats by intervening monodisperse polystyrene microspheres, and completed cardiac CT, SPECT, PET and CMR examination. The images were transferred to the post-processing workstation to observe the distribution area of impaired myocardium in the four examinationmethods. The sensitivity and specificity of different examination methods were analyzed using pathology as the gold standard to measure the iodine concentration of normaland impaired myocardium, the normalized iodine-density(NID) was calculated, and the difference of iodine concentration and NID between normal and impaired myocardium were compared. Results The sensitivity of CMD was 56.8%, 68.4%, 94.4%, 50.0%. The specificity of CMD was 98.0%, 99.0%, 98.0%, 100%. The iodine concentration and NID(-0.200±1.005 and-0.027±0.133) of the impaired myocardium group were lower than those of the normal myocardium group(1.578±0.936 and 0.204±0.128), and the difference was statistically significant(P<0.5). The AUC of impaired myocardium was 81.7%, 90.8% and 93.6% by iodine-diagram, NID and combined analysis of both, respectively. Conclusion DECT in multimodal imaging has a high application value in the diagnosis of CMD. The combined index of iodine-NID has a good performance in the diagnosis of CMD, providing research basis and imaging parameters for human clinical experiments.
作者
宋佳敏
刘晓林
周茂荣
孙凯
SONG Jiamin;LIU Xiaolin;ZHOU Maorong;SUN Kai(Graduate School of Baotou Medical College,Inner Mongolia University of Science and Technology,Baotou 014060,China;Department of Imaging,Baotou Central Hospital of Inner Mongolia,Baotou 014040,China)
出处
《医学影像学杂志》
2023年第2期318-323,共6页
Journal of Medical Imaging
基金
内蒙古自治区自然科学基金项目(编号:2020MS08066)。
