Article(id=1209139834527027573, tenantId=1146029695717560320, journalId=1189873630562394117, issueId=1209139833285505965, articleNumber=null, orderNo=null, doi=10.11855/j.issn.0577-7402.2021.07.05, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=research-article, receivedDate=1616342400000, receivedDateStr=2021-03-22, revisedDate=1624032000000, revisedDateStr=2021-06-19, acceptedDate=null, acceptedDateStr=null, onlineDate=1766211001283, onlineDateStr=2025-12-20, pubDate=1627401600000, pubDateStr=2021-07-28, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1766211001283, onlineIssueDateStr=2025-12-20, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1766211001283, creator=13701087609, updateTime=1766211001283, updator=13701087609, issue=Issue{id=1209139833285505965, tenantId=1146029695717560320, journalId=1189873630562394117, year='2021', volume='46', issue='7', pageStart='637', pageEnd='742', issueExtLink='null', onlineDate='null', pubDate='null', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=0, createTime=1766211000986, creator=13701087609, updateTime=1766212174313, updator=13701087609, preIssue=null, nextIssue=null, ext={EN=IssueExt(id=1209144754630168707, tenantId=1146029695717560320, journalId=1189873630562394117, issueId=1209139833285505965, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1209144754630168708, tenantId=1146029695717560320, journalId=1189873630562394117, issueId=1209139833285505965, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null}, startPage=666, endPage=672, ext={EN=ArticleExt(id=1209139834841600377, articleId=1209139834527027573, tenantId=1146029695717560320, journalId=1189873630562394117, language=EN, title=Incremental diagnostic value of pericoronary FAI over CT-FFR for diagnosis of abnormal coronary hemodynamics in patients with severe calcification, columnId=1190310109000602400, journalTitle=Medical Journal of Chinese People’s Liberation Army, columnName=Clinical Research, runingTitle=null, highlight=null, articleAbstract=

Objective To explore the impact of severe calcification on the abnormal hemodynamics based on CT-fractional flow reserve (CT-FFR) diagnosis, and evaluate the diagnostic significance of pericoronary fat attenuation index (FAI) on the abnormal hemodynamics of severely calcified coronary artery. Methods The clinical data of patients were retrospectively analyzed who underwent a coronary computed tomography angiography (CCTA) examination within one month before an invasive FFR examination from January 2017 to December 2019 in the First Medical Center of Chinese PLA General Hospital. Regarding invasive FFR≤0.8 as the gold standard of hemodynamically abnormal coronary artery disease (CAD), patients were assigned to FFR≤0.8 group and FFR>0.8 group. The coronary artery calcium score (CACS), degree of major coronary branch stenosis, pericoronary FAI and CT-FFR were measured and compared. Invasive FFR≤0.8 represents the presence of lesion-specific hemodynamic significant CAD. According to the quartiles of CACS, patients were further divided into mildly-moderately calcified (1st-3rd quartiles) and severely calcified (4th quartile) stratification. The diagnostic efficacy for abnormal coronary hemodynamics was analyzed only with CT-FFR and combined with pericoronary FAI detection between the two groups. Results A total of 99 patients with 124 main coronary arteries were included (37 in FFR≤0.8 group, and 87 in FFR>0.8 group). In terms of vascular characteristics, statistically significant differences existed between FFR≤0.8 group and FFR>0.8 group in CACS (85.80, 95%CI 6.750~0.977 vs. 42.50, 95%CI 0.600~110.200, P<0.05), degree of major coronary branch stenosis (63.8%±9.9% vs. 57.6%±9.5%, P<0.01), pericoronary FAI(–73.3±9.5 vs. –80.6±7.5, P<0.01) and CT-FFR (0.77±0.04 vs. 0.86±0.04, P<0.01). The diagnostic efficacy of CT-FFR was lower for severe calcified vessels than for the vessels with mild to moderate calcification (AUC=0.767, 95%CI 0.581~0.899 vs.AUC=0.936, 95%CI 0.865~0.976, P<0.05), while the pericoronary FAI showed good diagnostic efficacy for the severe calcified vessels (AUC=0.850, 95%CI 0.676~0.952). CT-FFR combined with pericoronary FAI improved the diagnostic efficacy than using CT-FFR alone (AUC=0.917, 95%CI 0.760~0.985 vs. AUC=0.767, 95%CI 0.581~0.899, P=0.046). Conclusion For severe calcified vessels, the effectiveness declined of CT-FFR in the diagnosis of significant coronary ischemia, while combined implementation of FAI may improve the diagnosis of CAD with abnormal hemodynamics.

, correspAuthors=Xia Yang, authorNote=null, correspAuthorsNote=
*E-mail:
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目的 探讨重度钙化对基于CT的血流储备分数(CT-FFR)诊断血流动力学异常的影响,并研究冠脉周围脂肪衰减指数(FAI)对重度钙化冠脉血管血流动力学异常的诊断价值。方法 回顾性分析2017年1月—2019年12月于解放军总医院第一医学中心行有创FFR检查前1个月内进行冠状动脉CT血管造影(CCTA)检查的患者的临床资料。以有创FFR≤0.8作为诊断血流动力学异常性冠心病的金标准,将人群分为FFR≤0.8与FFR>0.8两组,从血管水平测量并比较钙化积分、冠脉狭窄程度、冠脉周围FAI及CT-FFR。根据钙化严重程度的四分位数将人群分组,其中冠状动脉钙化积分(CACS) Q1~Q3人群为轻中度钙化组,Q4人群为重度钙化组,分析两组间及组内单独使用CT-FFR与联合冠脉周围FAI对冠脉血流动力学异常的诊断效能。结果 共纳入99例患者总计124支冠脉主支血管,FFR≤0.8组(37支)与FFR>0.8组(87支)在血管水平上的CACS(85.80,95%CI 6.750~0.977 vs. 42.50,95%CI 0.600~110.200,P<0.05)、冠脉狭窄程度(63.8%±9.9% vs. 57.6%±9.5%,P<0.01)、冠脉周围FAI(–73.3±9.5 vs. –80.6±7.5,P<0.01)及CT-FFR值(0.77±0.04 vs. 0.86±0.04,P<0.01)差异均有统计学意义。CT-FFR对重度钙化的诊断效能低于轻中度钙化(AUC=0.767,95%CI 0.581~0.899 vs. AUC=0.936,95%CI 0.865~0.976,P<0.05),而冠脉周围FAI对重度钙化具有良好的诊断效能(AUC=0.850,95%CI 0.676~0.952)。在重度钙化血管中,联合冠脉周围FAI较单独应用CT-FFR的诊断效能提高(AUC=0.917,95%CI 0.760~0.985 vs. AUC=0.767,95%CI 0.581~0.899,P=0.046)。结论 对于重度钙化的血管,CT-FFR诊断冠脉显著缺血的效能降低,联合冠脉周围FAI可为血流动力学异常的冠心病的诊断提供增量价值。

, correspAuthors=杨霞, authorNote=null, correspAuthorsNote=
杨霞,E-mail:
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丁熠璞,硕士研究生,主要从事冠心病诊疗和冠脉影像学方面的临床研究

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丁熠璞,硕士研究生,主要从事冠心病诊疗和冠脉影像学方面的临床研究

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丁熠璞,硕士研究生,主要从事冠心病诊疗和冠脉影像学方面的临床研究

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A. CCTA显示前降支近端存在混合斑块,狭窄程度约50%;B. 在CCTA图像基础上进行FAI测量;C. FAI图像的拉直图;D. 血管横断面。图B中深蓝色曲线表示血管中心线;图B、C中深蓝色直线表示测量血管两端的范围;图B、C中内侧的浅蓝色曲线与图D中红色近圆曲线分别表示MPR图像、拉直MPR图像及血管横截面上的血管边界,其中图D红色曲线上的绿点为对血管边界进行手动调整的位置点;图B、C、D的外侧浅蓝色曲线为测量血管节段距离血管壁外周等于血管直径处的线,即FAI测量区域的外围;血管壁以外至外侧浅蓝色曲线内的彩色图像表示FAI的大小,冠脉周围炎症程度越高,FAI值越大,则颜色越接近红色;反之则越接近黄色。以上曲线及彩色图像均为软件自动计算生成,仅图D中的绿点为可手动调节点。

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Q1-Q4分别代表根据CACS得到的四分位分层,Q4分层中FFR≤0.8的阳性血管中,有5支血管根据CT-FFR诊断为阴性,在各分层中漏诊数量最多。

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FFR. 血流储备分数;FAI. 脂肪衰减指数;AUC. 曲线下面积;A. 轻中度钙化组;B. 重度钙化组

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Imaging features of coronary artery in different FFR groups

, figureFileSmall=null, figureFileBig=null, tableContent=
血管特征总体(n=124)FFR≤0.8(n=37)FFR>0.8(n=87)P
单支血管CACS [M(Q1, Q3)]43.25(2.42, 168.18)85.80(6.75, 234.10)42.50(0.60, 110.20)0.024
病变长度(mm, $\bar{x}±s$)24.8±11.527.8±12.823.5±9.50.075
冠脉狭窄率(%, $\bar{x}±s$)59.6±10.063.8±9.957.6±9.50.003
冠脉周围FAI(HU, $\bar{x}±s$)–78.4±9.2–73.3±9.5–80.6±7.50.000
CT-FFR ($\bar{x}±s$)0.83±0.060.77±0.040.86±0.040.000
有创FFR ($\bar{x}±s$)0.82±0.100.71±0.090.88±0.040.000
), ArticleFig(id=1209197927084454452, tenantId=1146029695717560320, journalId=1189873630562394117, articleId=1209139834527027573, language=CN, label=表1, caption=

不同FFR组的冠脉血管影像特征

, figureFileSmall=null, figureFileBig=null, tableContent=
血管特征总体(n=124)FFR≤0.8(n=37)FFR>0.8(n=87)P
单支血管CACS [M(Q1, Q3)]43.25(2.42, 168.18)85.80(6.75, 234.10)42.50(0.60, 110.20)0.024
病变长度(mm, $\bar{x}±s$)24.8±11.527.8±12.823.5±9.50.075
冠脉狭窄率(%, $\bar{x}±s$)59.6±10.063.8±9.957.6±9.50.003
冠脉周围FAI(HU, $\bar{x}±s$)–78.4±9.2–73.3±9.5–80.6±7.50.000
CT-FFR ($\bar{x}±s$)0.83±0.060.77±0.040.86±0.040.000
有创FFR ($\bar{x}±s$)0.82±0.100.71±0.090.88±0.040.000
), ArticleFig(id=1209197927172534838, tenantId=1146029695717560320, journalId=1189873630562394117, articleId=1209139834527027573, language=EN, label=Tab.2, caption=

Imaging features of coronary artery with different severity of calcification

, figureFileSmall=null, figureFileBig=null, tableContent=
血管特征轻中度钙化组(n=93)重度钙化组(n=31)
FFR≤0.8(n=22)FFR>0.8(n=71)PFFR≤0.8(n=15)FFR>0.8(n=16)P
单支血管CACS[M(Q1, Q3)]7.9(1.7, 78.1)13.7(0.0, 65.3)0.688290.0(213.3, 492.4)255.5(209.6, 338.1)0.635
病变长度(mm, $\bar{x}±s$)24.8±10.821.9±8.80.20232.1±14.730.7±9.40.744
冠脉狭窄率(%, $\bar{x}±s$)64.9±10.657.2±9.60.00362.0±8.859.7±9.00.512
冠脉周围FAI(HU, $\bar{x}±s$)–75.69±9.79–80.08±7.060.061–69.75±8.19–82.77±9.300.000
CT-FFR($\bar{x}±s$)0.77±0.050.86±0.040.0000.78±0.040.83±0.050.003
有创FFR($\bar{x}±s$)0.70±0.110.88±0.040.0000.73±0.060.86±0.030.000
), ArticleFig(id=1209197927256420920, tenantId=1146029695717560320, journalId=1189873630562394117, articleId=1209139834527027573, language=CN, label=表2, caption=

不同钙化严重程度组的冠脉血管影像学特征

, figureFileSmall=null, figureFileBig=null, tableContent=
血管特征轻中度钙化组(n=93)重度钙化组(n=31)
FFR≤0.8(n=22)FFR>0.8(n=71)PFFR≤0.8(n=15)FFR>0.8(n=16)P
单支血管CACS[M(Q1, Q3)]7.9(1.7, 78.1)13.7(0.0, 65.3)0.688290.0(213.3, 492.4)255.5(209.6, 338.1)0.635
病变长度(mm, $\bar{x}±s$)24.8±10.821.9±8.80.20232.1±14.730.7±9.40.744
冠脉狭窄率(%, $\bar{x}±s$)64.9±10.657.2±9.60.00362.0±8.859.7±9.00.512
冠脉周围FAI(HU, $\bar{x}±s$)–75.69±9.79–80.08±7.060.061–69.75±8.19–82.77±9.300.000
CT-FFR($\bar{x}±s$)0.77±0.050.86±0.040.0000.78±0.040.83±0.050.003
有创FFR($\bar{x}±s$)0.70±0.110.88±0.040.0000.73±0.060.86±0.030.000
), ArticleFig(id=1209197927331918394, tenantId=1146029695717560320, journalId=1189873630562394117, articleId=1209139834527027573, language=EN, label=Tab.3, caption=

Diagnostic performance of CT-FFR and CT-FFR+ pericoronary FAI for different severity of calcification

, figureFileSmall=null, figureFileBig=null, tableContent=
组别AUC临界值敏感度(%)特异度(%)PPV(%)NPV(%)
轻中度钙化组
 CT-FFR0.9360.8395.580.360.098.3
 冠脉周围FAI0.642–75.5454.676.141.484.4
 CT-FFR+冠脉周围FAI0.9380.2895.590.175.098.5
重度钙化组
 CT-FFR0.7670.83100.050.065.2100.0
 冠脉周围FAI0.850–80.3986.775.076.585.7
 CT-FFR+冠脉周围FAI0.9170.4180.087.585.782.4
), ArticleFig(id=1209197927407415868, tenantId=1146029695717560320, journalId=1189873630562394117, articleId=1209139834527027573, language=CN, label=表3, caption=

不同钙化严重程度组中CT-FFR单独应用及联合冠脉周围FAI的诊断效能

, figureFileSmall=null, figureFileBig=null, tableContent=
组别AUC临界值敏感度(%)特异度(%)PPV(%)NPV(%)
轻中度钙化组
 CT-FFR0.9360.8395.580.360.098.3
 冠脉周围FAI0.642–75.5454.676.141.484.4
 CT-FFR+冠脉周围FAI0.9380.2895.590.175.098.5
重度钙化组
 CT-FFR0.7670.83100.050.065.2100.0
 冠脉周围FAI0.850–80.3986.775.076.585.7
 CT-FFR+冠脉周围FAI0.9170.4180.087.585.782.4
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冠状动脉周围FAI对CT-FFR诊断重度钙化患者冠脉血流动力学异常的增量价值
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丁熠璞 1, 2 , 单冬凯 1 , 王玺 1 , 杨俊杰 1 , 陈韵岱 1 , 杨霞 1, *
解放军医学杂志 | 临床研究 2021,46(7): 666-672
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解放军医学杂志 | 临床研究 2021, 46(7): 666-672
冠状动脉周围FAI对CT-FFR诊断重度钙化患者冠脉血流动力学异常的增量价值
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丁熠璞1, 2, 单冬凯1, 王玺1, 杨俊杰1, 陈韵岱1, 杨霞1, *
作者信息
  • 1解放军总医院第一医学中心心血管内科,北京 100853
  • 2南开大学医学院,天津 300071
  • 丁熠璞,硕士研究生,主要从事冠心病诊疗和冠脉影像学方面的临床研究

通讯作者:

杨霞,E-mail:
Incremental diagnostic value of pericoronary FAI over CT-FFR for diagnosis of abnormal coronary hemodynamics in patients with severe calcification
Yi-Pu Ding1, 2, Dong-Kai Shan1, Xi Wang1, Jun-Jie Yang1, Yun-Dai Chen1, Xia Yang1, *
Affiliations
  • 1Department of Cardiology, the First Medical Center of Chinese PLA General Hospital, Beijing 100853, China
  • 2School of Medicine, Nankai University, Tianjin 300071, China
出版时间: 2021-07-28 doi: 10.11855/j.issn.0577-7402.2021.07.05
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目的 探讨重度钙化对基于CT的血流储备分数(CT-FFR)诊断血流动力学异常的影响,并研究冠脉周围脂肪衰减指数(FAI)对重度钙化冠脉血管血流动力学异常的诊断价值。方法 回顾性分析2017年1月—2019年12月于解放军总医院第一医学中心行有创FFR检查前1个月内进行冠状动脉CT血管造影(CCTA)检查的患者的临床资料。以有创FFR≤0.8作为诊断血流动力学异常性冠心病的金标准,将人群分为FFR≤0.8与FFR>0.8两组,从血管水平测量并比较钙化积分、冠脉狭窄程度、冠脉周围FAI及CT-FFR。根据钙化严重程度的四分位数将人群分组,其中冠状动脉钙化积分(CACS) Q1~Q3人群为轻中度钙化组,Q4人群为重度钙化组,分析两组间及组内单独使用CT-FFR与联合冠脉周围FAI对冠脉血流动力学异常的诊断效能。结果 共纳入99例患者总计124支冠脉主支血管,FFR≤0.8组(37支)与FFR>0.8组(87支)在血管水平上的CACS(85.80,95%CI 6.750~0.977 vs. 42.50,95%CI 0.600~110.200,P<0.05)、冠脉狭窄程度(63.8%±9.9% vs. 57.6%±9.5%,P<0.01)、冠脉周围FAI(–73.3±9.5 vs. –80.6±7.5,P<0.01)及CT-FFR值(0.77±0.04 vs. 0.86±0.04,P<0.01)差异均有统计学意义。CT-FFR对重度钙化的诊断效能低于轻中度钙化(AUC=0.767,95%CI 0.581~0.899 vs. AUC=0.936,95%CI 0.865~0.976,P<0.05),而冠脉周围FAI对重度钙化具有良好的诊断效能(AUC=0.850,95%CI 0.676~0.952)。在重度钙化血管中,联合冠脉周围FAI较单独应用CT-FFR的诊断效能提高(AUC=0.917,95%CI 0.760~0.985 vs. AUC=0.767,95%CI 0.581~0.899,P=0.046)。结论 对于重度钙化的血管,CT-FFR诊断冠脉显著缺血的效能降低,联合冠脉周围FAI可为血流动力学异常的冠心病的诊断提供增量价值。

CT血管造影术  /  血流储备分数  /  钙化  /  冠脉周围脂肪衰减指数

Objective To explore the impact of severe calcification on the abnormal hemodynamics based on CT-fractional flow reserve (CT-FFR) diagnosis, and evaluate the diagnostic significance of pericoronary fat attenuation index (FAI) on the abnormal hemodynamics of severely calcified coronary artery. Methods The clinical data of patients were retrospectively analyzed who underwent a coronary computed tomography angiography (CCTA) examination within one month before an invasive FFR examination from January 2017 to December 2019 in the First Medical Center of Chinese PLA General Hospital. Regarding invasive FFR≤0.8 as the gold standard of hemodynamically abnormal coronary artery disease (CAD), patients were assigned to FFR≤0.8 group and FFR>0.8 group. The coronary artery calcium score (CACS), degree of major coronary branch stenosis, pericoronary FAI and CT-FFR were measured and compared. Invasive FFR≤0.8 represents the presence of lesion-specific hemodynamic significant CAD. According to the quartiles of CACS, patients were further divided into mildly-moderately calcified (1st-3rd quartiles) and severely calcified (4th quartile) stratification. The diagnostic efficacy for abnormal coronary hemodynamics was analyzed only with CT-FFR and combined with pericoronary FAI detection between the two groups. Results A total of 99 patients with 124 main coronary arteries were included (37 in FFR≤0.8 group, and 87 in FFR>0.8 group). In terms of vascular characteristics, statistically significant differences existed between FFR≤0.8 group and FFR>0.8 group in CACS (85.80, 95%CI 6.750~0.977 vs. 42.50, 95%CI 0.600~110.200, P<0.05), degree of major coronary branch stenosis (63.8%±9.9% vs. 57.6%±9.5%, P<0.01), pericoronary FAI(–73.3±9.5 vs. –80.6±7.5, P<0.01) and CT-FFR (0.77±0.04 vs. 0.86±0.04, P<0.01). The diagnostic efficacy of CT-FFR was lower for severe calcified vessels than for the vessels with mild to moderate calcification (AUC=0.767, 95%CI 0.581~0.899 vs.AUC=0.936, 95%CI 0.865~0.976, P<0.05), while the pericoronary FAI showed good diagnostic efficacy for the severe calcified vessels (AUC=0.850, 95%CI 0.676~0.952). CT-FFR combined with pericoronary FAI improved the diagnostic efficacy than using CT-FFR alone (AUC=0.917, 95%CI 0.760~0.985 vs. AUC=0.767, 95%CI 0.581~0.899, P=0.046). Conclusion For severe calcified vessels, the effectiveness declined of CT-FFR in the diagnosis of significant coronary ischemia, while combined implementation of FAI may improve the diagnosis of CAD with abnormal hemodynamics.

CT angiography  /  fractional flow reserve  /  calcification  /  pericoronary fat attenuation index
丁熠璞, 单冬凯, 王玺, 杨俊杰, 陈韵岱, 杨霞. 冠状动脉周围FAI对CT-FFR诊断重度钙化患者冠脉血流动力学异常的增量价值. 解放军医学杂志, 2021 , 46 (7) : 666 -672 . DOI: 10.11855/j.issn.0577-7402.2021.07.05
Yi-Pu Ding, Dong-Kai Shan, Xi Wang, Jun-Jie Yang, Yun-Dai Chen, Xia Yang. Incremental diagnostic value of pericoronary FAI over CT-FFR for diagnosis of abnormal coronary hemodynamics in patients with severe calcification[J]. Medical Journal of Chinese People’s Liberation Army, 2021 , 46 (7) : 666 -672 . DOI: 10.11855/j.issn.0577-7402.2021.07.05
冠状动脉功能学评价是冠状动脉粥样硬化性心脏病(atherosclerotic coronary artery disease,CAD,冠心病)诊疗策略的关键手段。传统的冠状动脉CT血管造影(CCTA)检查已作为诊断CAD的一线手段[1],然而CCTA仅是解剖学诊断,对功能学异常的评估尚存不足。同时,冠脉血管的钙化会导致部分容积效应或伪影,造成CCTA对管腔狭窄程度的高估。因此,在重度钙化患者中,CCTA诊断冠脉显著缺血的准确性和特异性均会受到影响。基于CCTA的血流储备分数(CT-derived fractional flow reserve,CT-FFR)是一种新兴的无创检测冠状动脉血流动力学异常的方法,弥补了CCTA特异性较低的不足,可以更好地指导临床决策[2-3],具有广阔的应用前景。多项临床试验证实,CT-FFR在诊断冠脉缺血方面优于CCTA,具备较高的诊断效能[4-7]。然而,CT-FFR的测量仍需基于冠脉CCTA图像进行管腔边界识别,不可避免地会受到钙化的影响,而目前对这种影响的评估仍然存在不足。
近年来的研究发现,在CCTA重建图像上测量获取的冠脉周围脂肪衰减指数(fat attenuation index,FAI)可作为一种新的血管炎症影像学标志物[8]。在急性冠脉综合征中,罪犯病变的冠脉周围FAI高于非罪犯病变[8]。冠脉周围FAI与总斑块体积及直径狭窄率联合预测冠脉缺血具有较高的准确性[9]。此外,冠脉周围FAI升高还与心血管不良预后相关[10]。由于冠脉周围脂肪主要位于冠脉外膜之外,图像受钙化容积效应的影响较小,应用该指标评价病变特点时为冠状动脉重度钙化患者带来了额外的价值。本研究探讨了重度钙化对CT-FFR诊断冠脉显著缺血的影响,并进一步分析了冠脉周围FAI对重度钙化冠脉血管血流动力学异常的增量诊断价值。
纳入2017年1月—2019年12月于解放军总医院第一医学中心因疑似冠心病行CCTA检查的患者共99例(124支冠脉主支血管)进行回顾性分析,所有患者于CCTA检查后1个月内接受有创冠脉造影及FFR检查。排除标准:(1)年龄<30岁;(2)经皮冠状动脉介入或冠状动脉旁路移植手术史;(3)影像质量差、无法分析CT-FFR或冠脉周围FAI。本研究已经通过解放军总医院伦理审查委员会的批准。
系统收集患者的临床基线数据,包括年龄、性别、体重指数(body mass index,BMI)、心血管危险因素(包括高血压、糖尿病、高脂血症及吸烟史)。所有危险因素定义均按指南推荐的定义执行[11-13]
使用第二代双源CT(Somatom Definition Flash,Siemens Medical Solutions,Forchheim,Germany)进行扫描。扫描步骤由CT平扫和增强扫描组成。在整个扫描过程中进行心电持续监测,心率>70次/min时,静脉给予盐酸艾司洛尔50~100 mg。扫描前指导患者屏气以避免呼吸伪影,舌下含服硝酸甘油以确保血管扩张。平扫完成后,测量冠状动脉钙化积分(coronary artery calcium score,CACS),并定位心脏的扫描范围。增强扫描时,在肘前静脉以5 ml/s的速度静脉注射非离子型造影剂(Ultravist®,370 mgI/ml,Schering AG,德国拜耳公司)。扫描参数如下:探测器准直2 mm×128 mm×0.6 mm;管电流290~560 mA/转;管电压80~120 kV(取决于BMI)。
所有扫描图像被传送到专用后处理工作站(synoMultiModality Workplace,syngoMMWP VE40A,Siemens,Germany),由两名经验丰富且对患者的临床情况不知情的心内科医师进行分析。根据美国心脏协会的分类,冠状动脉被划分为17段,所有直径>2 mm的血管节段均纳入分析[14]。钙化定义为3个相邻像素>130 HU。标记每支冠状动脉中的所有钙化病变,并采用Agatston方法[15]计算血管水平CACS。依据CACS的四分位数,将患者分为轻中度钙化(第1~3四分位区间,Q1-Q3)和重度钙化(第4四分位区间,Q4)两组。
在专用工作站(Anythink CT,Coronary Artery Analysis,version 1.01,CREALIFE,China)对行FFR检测的冠脉血管进行冠脉周围FAI测量。冠脉周围脂肪组织测量及FAI测量采用Antonopoulos等[8]描述的方法。冠脉周围脂肪组织定义为距离血管壁外周等于血管直径的径向距离内的脂肪组织(图1)。冠脉周围脂肪组织测量范围为从冠脉开口处10 mm到此后40 mm。脂肪组织的CT值定义为–190到–30 HU。冠脉周围FAI测量值观察者内和观察者间一致性良好(r观察者内=0.96;r观察者间=0.97)。
ICA检查按照标准流程,由股动脉或桡动脉穿刺实施。对所有狭窄程度在30%~90%的主要冠状动脉分支进行FFR检测以评估血管重建的必要性。通过6F或7F导管将压力导丝(PressureWire Certus, St. Jude Medical)送入冠状动脉后进行FFR测量。经肘正中静脉以140~180 μg/(kg·min)的速度注射三磷酸腺苷(ATP)以使冠状动脉达到充血状态。注射ATP后,记录充血稳定状态下最低的稳定FFR值。FFR值为冠状动脉内远端压力与近端压力的比值。单支血管FFR≤0.8诊断为血管水平冠脉显著缺血,即出现血流动力学异常的标志。据此将患者分为FFR≤0.8组与FFR>0.8组。
对实施有创FFR检查的所有对应冠脉进行CT-FFR检测,数据通过人工智能软件(DeepFFR V1.0.0, Beijing CuraCloud Technology Co., Ltd., Beijing, China)计算获得。此软件利用原始CCTA成像来测量人工智能模型中的模拟FFR值[16]。病变特异性CT-FFR定义为距病变远端10~20 mm处的FFR值。
采用MedCalc(version 15.2.2;MedCalc Software,Mariakerke,Belgium)和SPSS(version 22.0;IBM Corporation,Armonk,NY,USA)进行统计分析。分别从患者水平及血管水平对数据进行分析。连续变量以$\bar{x}±s$或M(Q1Q3)表示,组间比较若为正态分布,则采用t检验,若为非正态分布,则采用Mann-Whitney U检验。分类变量以例(%)表示,组间比较采用χ2检验或Fisher精确检验。绘制ROC曲线并进一步计算曲线下面积(AUC)的95%置信区间(95%CI)以评估诊断性能,并计算相应的敏感度、特异度、阳性预测值和阴性预测值,临界值由约登指数的最大值决定。为了确定最优模型,采用逻辑回归分析对单因素模型和多因素模型进行评价;采用DeLong方法比较AUC[17]。所有统计检验均为双侧检验,P<0.05为差异有统计学意义。
本研究纳入99例患者,共计124支冠脉主支血管。患者年龄为(61.6±5.5)岁,其中,男65例(65.7%),女34例(34.3%)。99例患者的心血管疾病危险因素包括高血压63例(63.6%)、糖尿病34例(34.3%)、高脂血症44例(44.4%)、吸烟29例(29.3%)。
血管水平上,FFR≤0.8组的单支血管CACS (85.80,95%CI 6.75~0.977 vs. 42.50,95%CI 0.60~110.20,P<0.05)、冠脉狭窄程度(63.8%±9.9% vs. 57.6%±9.5%,P<0.01)等CT血管特征与FFR>0.8组比较差异有统计学意义。FFR≤0.8组的冠脉周围FAI明显高于FFR>0.8组(–73.3±9.5 vs. –80.6±7.5,P<0.01),而CT-FFR值明显低于FFR>0.8组(0.77±0.04 vs.0.86±0.04,P<0.01)(表1)。此外,图2从血管水平展示了在不同钙化分层中CT-FFR的漏诊情况,在钙化四分位分层的Q1-Q4中,漏诊病例数分别为1、2、1和5例,Q4漏诊数量最多且漏诊率最高。
依据钙化的严重程度,我们比较了不同FFR组的血管特征参数。在轻中度钙化组中,FFR≤0.8组的冠脉狭窄率明显高于FFR>0.8组,而CT-FFR明显低于FFR>0.8组,但两组冠脉周围FAI差异并无统计学意义[(–75.69±9.79) HU vs. (–80.08±7.06) HU,P=0.061]。在重度钙化组中,FFR≤0.8组的冠脉周围FAI明显高于FFR>0.8组[(–69.75±8.19) HU vs.(–82.77±9.30) HU,P=0.000],CT-FFR仍明显低于FFR>0.8组,但两组的冠脉狭窄率差异无统计学意义(表2)。
单因素分析显示,两组间CT-FFR和冠脉周围FAI差异均有统计学意义,因此,采用诊断试验进一步分析此两项指标的诊断效能。结果显示,CT-FFR单独应用在轻中度钙化组和重度钙化组中均体现出了高敏感度及高阴性预测值,而在重度钙化组中特异度明显下降,由80.3%降至50.0%。联合应用冠脉周围FAI时,在两组中的诊断特异度均明显提升(表3)。图3进一步以ROC曲线分析CT-FFR联合FAI对诊断效能的提升作用。在轻中度钙化组中,单独应用CT-FFR即可表现出优异的诊断效能(AUC=0.936),将其与冠脉周围FAI联合时,诊断效能并未出现明显提升(AUC=0.938,95%CI 0.868~0.977 vs.AUC=0.936,95%CI 0.865~0.976,P=0.861);而在重度钙化组中,CT-FFR在确定血流动力学异常方面仅具有中等的诊断效能(AUC=0.767),CT-FFR联合冠脉周围FAI后诊断效能得到了明显提升(AUC=0.917,95%CI 0.760~0.985 vs. AUC=0.767,95%CI 0.581~0.899,P=0.046)。
本研究分析了钙化对CT-FFR技术诊断冠脉血流动力学异常的影响,并探讨了冠脉周围FAI对CT-FFR诊断效能的增量价值,结果发现,与轻中度钙化血管相比,CT-FFR在重度钙化血管中对冠脉血流动力学异常的诊断效能明显降低,而联合应用冠脉周围FAI后,其诊断重度钙化血管血流动力学异常的效能得到明显提升。
CT-FFR在血流动力学异常CAD诊断中的价值已在多项大规模临床研究中得到了验证[5-7]。PLATFORM研究[4]也发现,CT-FFR技术在临床诊疗路径中可有效减少不必要的有创ICA,造影发现的阴性患者比例从常规流程的73.7%降至CT-FFR指导组的12.4%,且1年随访的不良结局无明显增加。但由于CT-FFR技术的测算均基于CCTA后处理图像,因此,严重的钙化很有可能会影响其结果的准确性。在NXT子研究[18]中,CT-FFR对重度与轻度钙化血管的诊断能力差异无统计学意义(AUC:0.91 vs. 0.95,P=0.65),无论在何种钙化程度下,CT-FFR的诊断效能均高于CCTA。同样,在DISCOVERY-FLOW研究[6]中,对于存在钙化相关伪影的血管,CT-FFR在诊断血流动力学异常方面优于CCTA,准确度和特异度均更高。但在本研究中,CT-FFR在重度钙化血管中未能重复此结果,一方面可能基于机器学习的CT-FFR结果与基于流体动力学算法得到的结果不同,另一方面可能是由于本研究钙化严重程度的具体分层不同于其他前期研究。此外,本研究在重建提取3D冠脉树时,研究人员仍需手动描记血管边界,从而不可避免地高估病变,导致CT-FFR诊断特异度降低。
基于机器学习的CT-FFR技术是一种检测冠脉血流动力学异常的新方法,部分研究已经使用此技术评估冠脉功能学异常并指导临床实践[16,19-20]。该技术无需复杂的血流动力学算法,主要关注的是人工智能模型在影像分析中的应用。Tesche等[19]研究了CT-FFR对不同程度钙化的诊断能力,发现其较CCTA具有更好的诊断价值。然而,当CACS>400分时,CT-FFR的诊断效能较CACS<400分时明显下降(AUC:0.71 vs. 0.85,P=0.04),提示CT-FFR的诊断准确性受重度钙化的影响而明显下降。该结果与本研究相似,可能均是由相同的技术手段和无法避免的手动图像处理过程所造成的。因此,CT-FFR也不是一种能够完美应用于各种场景的技术。
冠脉周围FAI作为一种与CAD和心脏风险相关的新型影像学标志物越来越受到关注。冠脉周围脂肪可能会向血管内皮和循环中释放大量炎性因子,导致局部血管炎症。相反,血管炎症也会影响冠脉周围脂肪,导致脂质转化为“水相”,表现为CT值的增加。因此,与血管炎症相关的CT值变化可以作为CAD风险分层的有效影像学指标。Antonopoulos等[8]发现,CAD患者与健康受试者在冠脉周围FAI方面存在差异,急性心肌梗死患者与稳定型心绞痛患者之间也存在明显差异。此外,CRISP CT研究[10]提示,冠脉周围FAI可较好地预测全因死亡和心源性死亡。
前期研究发现,冠脉周围脂肪与CAD的发生发展存在相关性,且可能与较低的有创FFR值相关[21]。可能的原因是,与整体心外膜脂肪相比,冠脉周围脂肪对冠脉病变的作用更强且更为直接。Shan等[22]发现,与整体心外膜脂肪体积相比,前降支血管周围脂肪体积在预测心肌缺血方面具有更好的潜力,主要是由于冠脉周围脂肪接受了炎症血管节段所释放的炎性因子,从而影响了脂肪细胞的正常分化、增殖和脂解。此外,升高的冠脉周围FAI被认为是冠脉周围脂肪水肿的标志[8],而冠脉周围脂肪的变化则受血管炎症的影响。由于血管炎症是内皮功能障碍的重要原因,如果冠脉斑块病变引起狭窄段的舒张功能受损,则有创FFR会呈现阳性结果。因此,冠脉周围FAI与血流动力学紊乱之间存在潜在的临床相关性。当FFR为阳性时,冠脉周围FAI值较高。冠脉周围FAI联合总斑块体积和最大直径狭窄率对血流动力学异常CAD的诊断准确性较高,表明血管外影像学指标冠脉周围FAI可用于CAD的诊断及预后评估[9]。本研究结果显示,联合冠脉周围FAI后,重度钙化组中CT-FFR的诊断效能从0.767提升至0.917,表明此指标可以较好地对冠状动脉病变的整体血流动力学变化提供额外信息,且受管腔内钙化容积效应的影响较小。
但需要注意的是,单独应用冠脉周围FAI诊断血流动力学异常仍存有局限。在轻中度钙化血管中,冠脉周围FAI的敏感度仅为54.6%,AUC为0.642。在重度钙化患者中,冠脉周围FAI的敏感度增加至86.7%,这可能与重度钙化组中FFR阳性样本数量少有关。由于弥漫性钙化与活跃的血管炎症反应有关,因此冠脉周围FAI在此类病变周围可能增高,有助于在重度钙化患者中发现更多的潜在阳性病例。此外,本研究中重度钙化患者较少,且重度钙化患者中FAI值偏低的阴性患者比例较高,因此计算所得FAI特异度较实际增高。与单独应用CT-FFR比较,CT-FFR联合冠脉周围FAI对冠脉血流动力学异常的诊断效能更高,提示重度钙化的血管不仅需要进行CT-FFR检测,还需要评估冠脉周围FAI以进行综合分析。
本研究仍存在一定的局限性。首先,本研究为小样本的回顾性研究,总体FFR阳性样本的数量相对较少。从样本人群来看,由于所有患者均接受ICA和FFR检查,大多数患者处于高危CAD风险分层,与更广泛的中低危人群在危险因素谱的分布上存有差异,冠脉周围FAI的应用场景存在局限性。其次,本研究采用的CT-FFR技术基于机器学习算法,与流体力学算法得到的CT-FFR结果孰优孰劣尚不清楚。最后,在个别极重度钙化的血管中,部分钙化容积效应可能会干扰血管外膜的观察,导致局部冠脉周围FAI增加,虽然研究中进行了图像的精细处理,但这部分钙化对结果的影响还缺少数据支持,在血管水平CACS达到200分的以上的冠脉血管中,应谨慎进行冠脉周围FAI的测量。
综上所述,在重度钙化的冠脉血管中,与单独应用CT-FFR相比,CT-FFR联合冠脉周围FAI对血流动力学异常的CAD的诊断具有增量价值,冠脉周围FAI可为血流动力学异常的评估提供更全面的信息。
  • 国家重点研发计划(2016YFC1300304)
  • 北京市科技新星计划(Z181100006218055)
  • 全军医学科技青年培育计划孵化项目(16QNP137)
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2021年第46卷第7期
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doi: 10.11855/j.issn.0577-7402.2021.07.05
  • 接收时间:2021-03-22
  • 首发时间:2025-12-20
  • 出版时间:2021-07-28
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  • 收稿日期:2021-03-22
  • 修回日期:2021-06-19
基金
National Key Research and Development Program of China(2016YFC1300304)
国家重点研发计划(2016YFC1300304)
Beijing NOVA Program(Z181100006218055)
北京市科技新星计划(Z181100006218055)
Incubation Project of Military Medical Science and Technology Youth Cultivation Program(16QNP137)
全军医学科技青年培育计划孵化项目(16QNP137)
作者信息
    1解放军总医院第一医学中心心血管内科,北京 100853
    2南开大学医学院,天津 300071

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2种不同金属材料的力学参数

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Genus
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Number of
species
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鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
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