Neng Dai1, Xianlin Zhang2, Yi Zhang2, Lei Hou2, WeiMing Li2, Bing Fan3, TianSong Zhang4, YaWei Xu5. 1. Cardiology Department, Tenth People's Hospital of Tongji University, Shanghai, China; Center for Systems Biology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA. 2. Cardiology Department, Tenth People's Hospital of Tongji University, Shanghai, China. 3. Cardiology Department, ZhongShan Hospital of Fudan University, Shanghai, China. Electronic address: fanbingzs@126.com. 4. Department of TCM, Jing'An District Centre Hospital, Shanghai, China. Electronic address: ztsdoctor@126.com. 5. Cardiology Department, Tenth People's Hospital of Tongji University, Shanghai, China. Electronic address: xuyaweish@aliyun.com.
Abstract
AIM: The aim of this study is to determine the diagnostic utility of 6 cardiac imaging modalities using fractional flow reserve (FFR) as the reference standard. METHODS: Studies reporting diagnostic performance of computed tomographic perfusion imaging (CTP), fractional flow reserve derived from computed tomography (FFRCT), cardiac magnetic resonance (CMR), positron emission tomography (PET), single-photon emission computed tomography (SPECT) and dobutamine stress echocardiography (DSE) for diagnosis of ischemia-causing lesions were included. RESULTS: On vessel-based and patient-based analyses, CMR, PET, CTP and FFRCT exhibited comparable sensitivity (per-vessel: 87% vs. 86% vs. 89% vs. 86%; per-patient: 88% vs. 90% vs. 88% vs. 90%, P>0.05) and specificity (per-vessel: 89% vs. 88% vs. 89% vs. 83%; per-patient: 84% vs. 84% vs. 87% vs. 75%, P>0.05); whereas SPECT yielded significantly lower sensitivity (per-vessel: 72%; per-patient: 78%, P<0.05) and specificity (per-vessel: 79%; per-patient: 79%, P<0.05) and DES yielded significantly lower sensitivity (per-vessel: 62%, per-patient: 69%, P<0.05). On the other hand, within the same imaging modality, myocardial blood flow (MBF) derived by CTP had a higher sensitivity (90% vs. 80%, P=0.048) but lower specificity (77% vs. 93%, P=0.02) than that of perfusion defect (PD). Moreover, MBF derived by CMR had a lower specificity than that of PD (60% vs. 93%, P=0.02), while coronary flow reserve (CRF) derived by PET had a lower specificity than that of MBF (81% vs. 89%, P=0.005). CONCLUSION: CMR, PET, CTP and FFRCT expressed similar and high accuracy in detecting functional CAD, whereas different analysis methods for each imaging modality may vary their diagnostic utility.
AIM: The aim of this study is to determine the diagnostic utility of 6 cardiac imaging modalities using fractional flow reserve (FFR) as the reference standard. METHODS: Studies reporting diagnostic performance of computed tomographic perfusion imaging (CTP), fractional flow reserve derived from computed tomography (FFRCT), cardiac magnetic resonance (CMR), positron emission tomography (PET), single-photon emission computed tomography (SPECT) and dobutamine stress echocardiography (DSE) for diagnosis of ischemia-causing lesions were included. RESULTS: On vessel-based and patient-based analyses, CMR, PET, CTP and FFRCT exhibited comparable sensitivity (per-vessel: 87% vs. 86% vs. 89% vs. 86%; per-patient: 88% vs. 90% vs. 88% vs. 90%, P>0.05) and specificity (per-vessel: 89% vs. 88% vs. 89% vs. 83%; per-patient: 84% vs. 84% vs. 87% vs. 75%, P>0.05); whereas SPECT yielded significantly lower sensitivity (per-vessel: 72%; per-patient: 78%, P<0.05) and specificity (per-vessel: 79%; per-patient: 79%, P<0.05) and DES yielded significantly lower sensitivity (per-vessel: 62%, per-patient: 69%, P<0.05). On the other hand, within the same imaging modality, myocardial blood flow (MBF) derived by CTP had a higher sensitivity (90% vs. 80%, P=0.048) but lower specificity (77% vs. 93%, P=0.02) than that of perfusion defect (PD). Moreover, MBF derived by CMR had a lower specificity than that of PD (60% vs. 93%, P=0.02), while coronary flow reserve (CRF) derived by PET had a lower specificity than that of MBF (81% vs. 89%, P=0.005). CONCLUSION: CMR, PET, CTP and FFRCT expressed similar and high accuracy in detecting functional CAD, whereas different analysis methods for each imaging modality may vary their diagnostic utility.
Authors: Anders Thomassen; Poul-Erik Braad; Kasper T Pedersen; Henrik Petersen; Allan Johansen; Axel C P Diederichsen; Hans Mickley; Lisette O Jensen; Juhani Knuuti; Oke Gerke; Poul F Høilund-Carlsen Journal: Int J Cardiovasc Imaging Date: 2018-07-31 Impact factor: 2.357
Authors: Jagat Narula; Y Chandrashekhar; Amir Ahmadi; Suhny Abbara; Daniel S Berman; Ron Blankstein; Jonathon Leipsic; David Newby; Edward D Nicol; Koen Nieman; Leslee Shaw; Todd C Villines; Michelle Williams; Harvey S Hecht Journal: J Cardiovasc Comput Tomogr Date: 2020-11-20
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