Optimal Measurement Sites of Coronary-Computed Tomography Angiography-derived Fractional Flow Reserve

Chen, Yan Chun; Zhou, Fan; Wang, Yi Ning; Zhang, Jia Yin; Yu, Mengchao; Hou, Yang; Xu, Peng; Zhang, Xiao Lei; Xue, Yi; Zheng, Minjuan; Zhang, Bo; Zhang, Dai‐Min; Hu, Xinghao; Xu, Lei; Liu, Hui; Lu, Guang Ming; Tang, Chunbo; Zhang, Long Jiang

doi:10.1097/rti.0000000000000687

Cited by 5 publications

(11 citation statements)

References 44 publications

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“…These findings suggest that FFR CT measured at 2 cm distal to the target lesion had the highest performance in identifying lesion-specific ischemia. Overall, our results are consistent with the findings of previous study [ 15 , 16 , 18 , 24 ]. In our study, FFR CT was measured at four different sites along the same artery and our results showed that FFR CT measured at 2 cm distal to the target lesion are the optimal site for FFR CT measurement, which is in line with previous studies [ 15 , 16 , 18 , 24 ].…”

Section: Discussionsupporting

confidence: 94%

“…Overall, our results are consistent with the findings of previous study [ 15 , 16 , 18 , 24 ]. In our study, FFR CT was measured at four different sites along the same artery and our results showed that FFR CT measured at 2 cm distal to the target lesion are the optimal site for FFR CT measurement, which is in line with previous studies [ 15 , 16 , 18 , 24 ]. It should be noted that the measurement site of the invasive FFR and the definition of the target lesion were not totally consistent between our study and previous studies [ 15 , 16 , 18 , 24 ].…”

Section: Discussionsupporting

confidence: 94%

“…In our study, FFR CT was measured at four different sites along the same artery and our results showed that FFR CT measured at 2 cm distal to the target lesion are the optimal site for FFR CT measurement, which is in line with previous studies [ 15 , 16 , 18 , 24 ]. It should be noted that the measurement site of the invasive FFR and the definition of the target lesion were not totally consistent between our study and previous studies [ 15 , 16 , 18 , 24 ]. Indeed, the invasive FFR was measured 2 to 3 cm distal to the target lesion in our study which was based on the recommendation as previously described [ 19 ],which is as same as the study by Cami et al [ 16 ].…”

Section: Discussionsupporting

confidence: 89%

“…In addition, Nozaki et al [ 18 ] used a CFD-based algorithm and found that the AUC of FFR CT -2 cm was higher than that of FFR CT -lowest (0.80 vs. 0.68, p = 0.002) in identifying lesion-specific ischemia and was comparable with that of FFR CT -1 cm (0.80 vs. 0.79, p = 0.73). In a recent study by Chen et al [ 24 ] where a machine learning-based algorithm was applied, the AUC of FFR CT -2 cm was found to be comparable with that of FFR CT -1 cm (0.91 vs. 0.91, p = 0.663) and was higher than that of FFR CT -3 cm (0.91 vs. 0.88, p = 0.002) and FFR CT -4 cm (0.91 vs. 0.88, p = 0.008) in identifying lesion-specific ischemia using invasive FFR as reference standard. Based on these results, FFR CT measured at 1-to-2 cm distal to the stenosis is better than FFR CT -lowest in identifying lesion-specific ischemia in patients with CAD.…”

Section: Discussionmentioning

confidence: 99%

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Detecting lesion-specific ischemia in patients with coronary artery disease with computed tomography fractional flow reserve measured at different sites

Cai

Yang

et al. 2023

BMC Med Imaging

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Objectives Whether a stenosis can cause hemodynamic lesion-specific ischemia is critical for the treatment decision in patients with coronary artery disease (CAD). Based on coronary computed tomography angiography (CCTA), CT fractional flow reserve (FFRCT) can be used to assess lesion-specific ischemia. The selection of an appropriate site along the coronary artery tree is vital for measuring FFRCT. However the optimal site to measure FFRCT for a target stenosis remains to be adequately determined. The purpose of this study was to determine the optimal site to measure FFRCT for a target lesion in detecting lesion-specific ischemia in CAD patients by evaluating the performance of FFRCT measured at different sites distal to the target lesion in detecting lesion-specific ischemia with FFR measured with invasive coronary angiography (ICA) as reference standard. Methods In this single-center retrospective cohort study, a total of 401 patients suspected of having CAD underwent invasive ICA and FFR between March 2017 and December 2021 were identified. 52 patients having both CCTA and invasive FFR within 90 days were enrolled. Patients with vessels 30%-90% diameter stenosis as determined by ICA were referred to invasive FFR evaluation, which was performed 2–3 cm distal to the stenosis under the condition of hyperemia. For each vessel with 30%–90% diameter stenosis, if only one stenosis was present, this stenosis was selected as the target lesion; if serial stenoses were present, the stenosis most distal to the vessel end was chosen as the target lesion. FFRCT was measured at four sites: 1 cm, 2 cm, and 3 cm distal to the lower border of the target lesion (FFRCT-1 cm, FFRCT-2 cm, FFRCT-3 cm), and the lowest FFRCT at the distal vessel tip (FFRCT-lowest). The normality of quantitative data was assessed using the Shapiro–Wilk test. Pearson's correlation analysis and Bland–Altman plots were used for assessing the correlation and difference between invasive FFR and FFRCT. Correlation coefficients derived from Chi-suqare test were used to assess the correlation between invasive FFR and the cominbaiton of FFRCT measred at four sites. The performances of significant obstruction stenosis (diameter stenosis ≥ 50%) at CCTA and FFRCT measured at the four sites and their combinations in diagnosing lesion-specific ischemia were evaluated by receiver-operating characteristic (ROC) curves using invasive FFR as the reference standard. The areas under ROC curves (AUCs) of CCTA and FFRCT were compared by the DeLong test. Results A total of 72 coronary arteries in 52 patients were included for analysis. Twenty-five vessels (34.7%) had lesion-specific ischemia detected by invasive FFR and 47 vesseles (65.3%) had no lesion-spefifice ischemia. Good correlation was found between invasive FFR and FFRCT-2 cm and FFRCT-3 cm (r = 0.80, 95% CI, 0.70 to 0.87, p < 0.001; r = 0.82, 95% CI, 0.72 to 0.88, p < 0.001). Moderate correlation was found between invasive FFR and FFRCT-1 cm and FFRCT-lowest (r = 0.77, 95% CI, 0.65 to 0.85, p < 0.001; r = 0.78, 95% CI, 0.67 to 0.86, p < 0.001). FFRCT-1 cm + FFRCT-2 cm, FFRCT-2 cm + FFRCT-3 cm, FFRCT-3 cm + FFRCT-lowest, FFRCT-1 cm + FFRCT-2 cm + FFRCT-3 cm, and FFRCT-2 cm + FFRCT-3 cm + FFRCT-lowest were correatled with invasive FFR (r = 0.722; 0.722; 0.701; 0.722; and 0.722, respectively; p < 0.001 for all). Bland–Altman plots revealed a mild difference between invasive FFR and the four FFRCT (invasive FFR vs. FFRCT-1 cm, mean difference -0.0158, 95% limits of agreement: -0.1475 to 0.1159; invasive FFR vs. FFRCT-2 cm, mean difference 0.0001, 95% limits of agreement: -0.1222 to 0.1220; invasive FFR vs. FFRCT-3 cm, mean difference 0.0117, 95% limits of agreement: -0.1085 to 0.1318; and invasive FFR vs. FFRCT-lowest, mean difference 0.0343, 95% limits of agreement: -0.1033 to 0.1720). AUCs of CCTA, FFRCT-1 cm, FFRCT-2 cm, FFRCT-3 cm, and FFRCT-lowest in detecting lesion-specific ischemia were 0.578, 0.768, 0.857, 0.856 and 0.770, respectively. All FFRCT had a higher AUC than CCTA (all p < 0.05), FFRCT-2 cm achieved the highest AUC at 0.857. The AUCs of FFRCT-2 cm and FFRCT-3 cm were comparable (p > 0.05). The AUCs were similar between FFRCT-1 cm + FFRCT-2 cm, FFRCT-3 cm + FFRCT-lowest and FFRCT-2 cm alone (AUC = 0.857, 0.857, 0.857, respectively; p > 0.05 for all). The AUCs of FFRCT-2 cm + FFRCT-3 cm, FFRCT-1 cm + FFRCT-2 cm + FFRCT-3 cm, FFRCT-and 2 cm + FFRCT-3 cm + FFRCT-lowest (0.871, 0.871, 0.872, respectively) were slightly higher than that of FFRCT-2 cm alone (0.857), but without significnacne differences (p > 0.05 for all). Conclusions FFRCT measured at 2 cm distal to the lower border of the target lesion is the optimal measurement site for identifying lesion-specific ischemia in patients with CAD.

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Section: Discussionsupporting

confidence: 94%

Section: Discussionsupporting

confidence: 94%

Section: Discussionsupporting

confidence: 89%

Section: Discussionmentioning

confidence: 99%

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Detecting lesion-specific ischemia in patients with coronary artery disease with computed tomography fractional flow reserve measured at different sites

Cai

Yang

et al. 2023

BMC Med Imaging

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“…FFR CT calculations were blindly and independently conducted on CCTA datasets using a software prototype (cFFR, version 3.0.1; Siemens Healthcare). The software is based on the machine learning platform for the noninvasive computation of FFR values using existing CCTA data, and the detailed algorithm has been reported in previous studies 7,15,16 . An observer (Hong Yan Qiao with 5 y of experience in FFR CT analysis), who was blinded to all participants’ baseline clinical data, measured lesion-specific FFR CT values at 2 to 4 cm distal to coronary stenosis in real time.…”

Section: Methodsmentioning

confidence: 99%

FFRCT and Static Computed Tomography Myocardial Perfusion Imaging for Therapeutic Decision-making and Prognosis in Patients With Coronary Artery Disease

Zhong

Qiao

et al. 2023

Journal of Thoracic Imaging

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Purpose: The purpose of this study was to investigate the effect of integrated evaluation of resting static computed tomography perfusion (CTP) and coronary computed tomography angiography (CCTA)–derived fractional flow reserve (FFRCT) on therapeutic decision-making and predicting major adverse cardiovascular events (MACEs) in patients with suspected coronary artery disease. Materials and Methods: In this post hoc analysis of a prospective trial of CCTA in patients assigned to either CCTA or CCTA plus FFRCT arms, 500 patients in the CCTA plus FFRCT arm were analyzed. Both resting static CTP and FFRCT were evaluated by using the conventional CCTA. Perfusion defects in the myocardial segments with ≥50% degree of stenosis in the supplying vessels were defined as resting static CTP positive, and any vessel with an FFRCT value of ≤0.80 was considered positive. Patients were divided into 3 groups: (1) negative CTP-FFRCT match group (resting static CTP-negative and FFRCT-negative group); (2) mismatch CTP-FFRCT group (resting static CTP-positive and FFRCT-negative or resting static CTP-negative and FFRCT-positive group); and (3) positive CTP-FFRCT match group (resting static CTP-positive and FFRCT-positive group). We compared the revascularization-to-invasive coronary angiography ratio and the MACE rate among 3 subgroups at 1- and 3-year follow-ups. The adjusted Cox hazard proportional model was used to assess the prognostic value of FFRCT and resting static CTP to determine patients at risk of MACE. Results: Patients in the positive CTP-FFRCT match group were more likely to undergo revascularization at the time of invasive coronary angiography compared with those in the mismatch CTP-FFRCT group (81.4% vs 57.7%, P=0.033) and the negative CTP-FFRCT match group (81.4% vs 33.3%, P=0.001). At 1- and 3-year follow-ups, patients in the positive CTP-FFRCT match group were more likely to have MACE than those in the mismatch CTP-FFRCT group (10.5% vs 4.2%, P=0.046; 35.6% vs 9.4%, P<0.001) and the negative CTP-FFRCT match group (10.5% vs 0.9%, P<0.001; 35.6% vs 5.4%, P<0.001). A positive CTP-FFRCT match was strongly related to MACE at 1-year (hazard ratio=8.06, P=0.003) and 3-year (hazard ratio=6.23, P<0.001) follow-ups. Conclusion: In patients with suspected coronary artery disease, the combination of FFRCT with resting static CTP could guide therapeutic decisions and have a better prognosis with fewer MACE in a real-world scenario.

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The Plaque Analysis Classifies the Coronary Artery Disease‐Reporting and Data System (CAD‐RADS) Stenosis and Plaque Burden Categories: Association of the Plaque Features, Fat Attenuation Index, Coronary Computed Tomography Fractional Flow Reserve, and the Combination of Stenosis and Calcification

Chen,

Nie,

Zhang

et al. 2024

Clinical Cardiology

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BackgroundThe coronary artery disease‐reporting and data system (CAD‐RADS) 2.0 is used to standardize the reporting of coronary computed tomography angiography (CCTA) results. Artificial intelligence software can quantify the plaque composition, fat attenuation index, and fractional flow reserve.ObjectiveTo analyze plaque features of varying severity in patients with a combination of CAD‐RADS stenosis and plaque burden categorization and establish a random forest classification model.MethodsThe data of 100 patients treated between April 2021 and February 2022 were retrospectively collected. The most severe plaque observed in each patient was the target lesion. Patients were categorized into three groups according to CAD‐RADS: CAD‐RADS 1−2 + P0−2, CAD‐RADS 3−4B + P0−2, and CAD‐RADS 3−4B + P3−4. Differences and correlations between variables were assessed between groups. AUC, accuracy, precision, recall, and F1 score were used to evaluate the diagnostic performance.ResultsA total of 100 patients and 178 arteries were included. The differences of computed tomography fractional flow reserve (CT‐FFR) (H = 23.921, p < 0.001), the volume of lipid component (H = 12.996, p = 0.002), the volume of fibro‐lipid component (H = 8.692, p = 0.013), the proportion of lipid component volume (H = 22.038, p < 0.001), the proportion of fibro‐lipid component volume (H = 11.731, p = 0.003), the proportion of calcification component volume (H = 11.049, p = 0.004), and plaque type (χ2 = 18.110, p = 0.001) was statistically significant.ConclusionCT‐FFR, volume and proportion of lipid and fibro‐lipid components of plaques, the proportion of calcified components, and plaque type were valuable for CAD‐RADS stenosis + plaque burden classification, especially CT‐FFR, volume, and proportion of lipid and fibro‐lipid components. The model built using the random forest was better than the clinical model (AUC: 0.874 vs. 0.647).

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Optimal Measurement Sites of Coronary-Computed Tomography Angiography-derived Fractional Flow Reserve

Cited by 5 publications

References 44 publications

Detecting lesion-specific ischemia in patients with coronary artery disease with computed tomography fractional flow reserve measured at different sites

Detecting lesion-specific ischemia in patients with coronary artery disease with computed tomography fractional flow reserve measured at different sites

FFRCT and Static Computed Tomography Myocardial Perfusion Imaging for Therapeutic Decision-making and Prognosis in Patients With Coronary Artery Disease

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