On-Site Computed Tomography-Derived Fractional Flow Reserve to Guide Management of Patients With Stable Coronary Artery Disease: The TARGET Randomized Trial.

BACKGROUND: Computed tomography-derived fractional flow reserve (CT-FFR) using on-site machine learning enables identification of both the presence of coronary artery disease and vessel-specific ischemia. However, it is unclear whether on-site CT-FFR improves clinical or economic outcomes when compared with the standard of care in patients with stable coronary artery disease. METHODS: In total, 1216 patients with stable coronary artery disease and an intermediate stenosis of 30% to 90% on coronary computed tomographic angiography were randomized to an on-site CT-FFR care pathway using machine learning or to standard care in 6 Chinese medical centers. The primary end point was the proportion of patients undergoing invasive coronary angiography without obstructive coronary artery disease or with obstructive disease who did not undergo intervention within 90 days. Secondary end points included major adverse cardiovascular events, quality of life, symptoms of angina, and medical expenditure at 1 year. RESULTS: Baseline characteristics were similar in both groups, with 72.4% (881/1216) having either typical or atypical anginal symptoms. A total of 421 of 608 patients (69.2%) in the CT-FFR care group and 483 of 608 patients (79.4%) in the standard care group underwent invasive coronary angiography. Compared with standard care, the proportion of patients undergoing invasive coronary angiography without obstructive coronary artery disease or with obstructive disease not undergoing intervention was significantly reduced in the CT-FFR care group (28.3% [119/421] versus 46.2% [223/483]; P<0.001). Overall, more patients underwent revascularization in the CT-FFR care group than in the standard care group (49.7% [302/608] versus 42.8% [260/608]; P=0.02), but major adverse cardiovascular events at 1 year did not differ (hazard ratio, 0.88 [95% CI, 0.59-1.30]). Quality of life and symptoms improved similarly during follow-up in both groups, and there was a trend towards lower costs in the CT-FFR care group (difference, -¥4233 [95% CI, -¥8165 to ¥973]; P=0.07). CONCLUSIONS: On-site CT-FFR using machine learning reduced the proportion of patients with stable coronary artery disease undergoing invasive coronary angiography without obstructive disease or requiring intervention within 90 days, but increased revascularization overall without improving symptoms or quality of life, or reducing major adverse cardiovascular events. REGISTRATION: URL: https://www. CLINICALTRIALS: gov; Unique identifier: NCT03901326.

Global trans-lesional computed tomography-derived fractional flow reserve gradient is associated with clinical outcomes in diabetic patients with non-obstructive coronary artery disease.

BACKGROUND: Coronary computed tomography angiography (CCTA)-derived fractional flow reserve (CT-FFR) enables physiological assessment and risk stratification, which is of significance in diabetic patients with nonobstructive coronary artery disease (CAD). We aim to evaluate prognostic value of the global trans-lesional CT-FFR gradient (GΔCT-FFR), a novel metric, in patients with diabetes without flow-limiting stenosis. METHODS: Patients with diabetes suspected of having CAD were prospectively enrolled. GΔCT-FFR was calculated as the sum of trans-lesional CT-FFR gradient in all epicardial vessels greater than 2 mm. Patients were stratified into low-gradient without flow-limiting group (CT-FFR > 0.75 and GΔCT-FFR < 0.20), high-gradient without flow-limiting group (CT-FFR > 0.75 and GΔCT-FFR ≥ 0.20), and flow-limiting group (CT-FFR ≤ 0.75). Discriminant ability for major adverse cardiovascular events (MACE) prediction was compared among 4 models [model 1: Framingham risk score; model 2: model 1 + Leiden score; model 3: model 2 + high-risk plaques (HRP); model 4: model 3 + GΔCT-FFR] to determine incremental prognostic value of GΔCT-FFR. RESULTS: Of 1215 patients (60.1 ± 10.3 years, 53.7% male), 11.3% suffered from MACE after a median follow-up of 57.3 months. GΔCT-FFR (HR: 2.88, 95% CI 1.76-4.70, P < 0.001) remained independent risk factors of MACE in multivariable analysis. Compared with the low-gradient without flow-limiting group, the high-gradient without flow-limiting group (HR: 2.86, 95% CI 1.75-4.68, P < 0.001) was associated with higher risk of MACE. Among the 4 risk models, model 4, which included GΔCT-FFR, showed the highest C-statistics (C-statistics: 0.75, P = 0.002) as well as a significant net reclassification improvement (NRI) beyond model 3 (NRI: 0.605, P < 0.001). CONCLUSIONS: In diabetic patients with non-obstructive CAD, GΔCT-FFR was associated with clinical outcomes at 5 year follow-up, which illuminates a novel and feasible approach to improved risk stratification for a global hemodynamic assessment of coronary artery in diabetic patients.

Validation of hemodynamic stress calculation in coronary computed tomography angiography versus intravascular ultrasound.

Background: Development in computational fluid dynamics and 3D construction could facilitate the calculation of hemodynamic stresses in coronary computed tomography angiography (CCTA). However, the agreement between CCTA derived stresses and intravascular ultrasound/intravascular coronary angiography (IVUS/ICA)-derived stresses remains undetermined. Thus, the purpose of this study is to investigate if CCTA can serve as alternative to IVUS/ICA for hemodynamic evaluation. Methods: In this retrospective study, 13 patients (14 arteries) with unstable angina who underwent both CCTA and IVUS/ICA at an interval of less than 7 days were consecutively included at the Chinese PLA General Hospital within the year of 2021. Slice-level minimal lumen area (MLA), percent area stenosis, velocity, pressure, Reynolds number, wall shear stress (WSS) and axial plaque stress (APS) were determined by both modalities. The agreement between CCTA and IVUS/ICA was assessed using the intraclass correlation coefficient (ICC), Pearson's correlation coefficient and Bland-Altman analysis. Results: CCTA overestimated the degree of area stenosis (50.22%±16.15% vs. 36.41%±19.37%, P=0.004) with the MLA showing no significant difference (5.81±2.24 vs. 6.72±2.04 mm2, P=0.126). No statistical difference was observed in WSS (6.57±6.26 vs. 5.98±5.55 Pa, P=0.420) and APS (16.03±1,159.45 vs. -1.27±890.39 Pa, P=0.691) between CCTA and IVUS. Good correlation was found in velocity (ICC: 0.796, 95% CI: 0.752-0.833), Reynolds number (ICC: 0.810, 95% CI: 0.768-0.844) and WSS (ICC: 0.769, 95% CI: 0.718-0.810), while the ICC of APS was (ICC: 0.341, 95% CI: 0.197-0.458), indicating a relatively poor correlation. Conclusions: CCTA can serve as a satisfactory alternative to the reference standard, IVUS/ICA in morphology simulation and hemodynamic stress calculation, especially in the calculation of WSS.

Incremental diagnostic value of perivascular fat attenuation index for identifying hemodynamically significant ischemia with severe calcification.

PURPOSE: To explore the incremental value of perivascular fat attenuation index (FAI) to identify hemodynamically significant ischemia in severe calcified vessels. METHODS: Patients who underwent coronary computed tomographic angiography (CCTA) examination at Chinese PLA General Hospital from 2017 to 2020 and subsequently underwent fractional flow reserve (FFR) examination within 1 month were consecutively included. Several CCTA-derived indices were measured, including the coronary artery calcification score (CACS), lesion length, ≥CAD-RADS 4 proportion, perivascular FAI and CT-FFR. The included vessels were divided into a nonsevere calcification group and a severe calcification group according to the quartile of CACS. FFR ≤ 0.80 represents the presence of hemodynamically significant ischemia. RESULTS: A total of 124 patients with 152 vessels were included (age: 61.1 ± 9.2 years; male 64.5%). Significant differences in lesion length (28.4 ± 14.2 vs. 23.1 ± 12.3 mm, P = 0.021), perivascular FAI (-73.0 ± 7.5 vs. -79.0 ± 7.4 HU, P < 0.001) and CT-FFR (0.78 ± 0.06 vs. 0.86 ± 0.04, P < 0.001) were noted between the FFR ≤ 0.80 group (47 vessels) and the FFR > 0.80 group (105 vessels). Furthermore, the perivascular FAI in the FFR ≤ 0.80 group was significantly greater than that in the FFR > 0.80 group (nonsevere calcification: -73.2 ± 7.5 vs. -78.2 ± 7.4 HU, P = 0.002; severe calcification: -72.8 ± 7.7 vs. -82.7 ± 6.3 HU, P < 0.001). In discriminating hemodynamically significant ischemia, the specificity and accuracy of CT-FFR were significantly affected by severe calcification, which demonstrated a significantly declining trend (P = 0.033 and P = 0.010, respectively). The diagnostic performance of CT-FFR in the severe calcification group was lower than that in the nonsevere calcified group. However, perivascular FAI showed good discriminative performance in the severe calcification group. In combination with perivascular FAI, the predictive value of CT-FFR in identifying hemodynamically significant ischemia with severe calcification increased from an AUC of 0.740 to 0.919. CONCLUSION: For coronary artery with severe calcification, the diagnostic performance of CT-FFR in discriminating flow-limiting lesions could be greatly impaired. Perivascular FAI represents a potential reliable imaging marker to provide incremental diagnostic value over CT-FFR for identifying hemodynamically significant ischemia with severe calcification.

The Chinese Experience of Imaging in Cardiac Intervention: A Bird's Eye Review.

Recent scientific and technological advances have greatly contributed to the development of medical imaging that could enable specific functions. It has become the primary focus of cardiac intervention in preoperative assessment, intraoperative guidance, and postoperative follow-up. This review provides a contemporary overview of the Chinese experience of imaging in cardiac intervention in recent years.

CT-Based Leiden Score Outperforms Confirm Score in Predicting Major Adverse Cardiovascular Events for Diabetic Patients with Suspected Coronary Artery Disease.

OBJECTIVE: Evidence supports the efficacy of coronary computed tomography angiography (CCTA)-based risk scores in cardiovascular risk stratification of patients with suspected coronary artery disease (CAD). We aimed to compare two CCTA-based risk score algorithms, Leiden and Confirm scores, in patients with diabetes mellitus (DM) and suspected CAD. MATERIALS AND METHODS: This single-center prospective cohort study consecutively included 1241 DM patients (54.1% male, 60.2 ± 10.4 years) referred for CCTA for suspected CAD in 2015-2017. Leiden and Confirm scores were calculated and stratified as < 5 (reference), 5-20, and > 20 for Leiden and < 14.3 (reference), 14.3-19.5, and > 19.5 for Confirm. Major adverse cardiovascular events (MACE) were defined as the composite outcomes of cardiovascular death, nonfatal myocardial infarction (MI), stroke, and unstable angina requiring hospitalization. The Cox model and Kaplan-Meier method were used to evaluate the effect size of the risk scores on MACE. The area under the curve (AUC) at the median follow-up time was also compared between score algorithms. RESULTS: During a median follow-up of 31 months (interquartile range, 27.6-37.3 months), 131 of MACE were recorded, including 17 cardiovascular deaths, 28 nonfatal MIs, 64 unstable anginas requiring hospitalization, and 22 strokes. An incremental incidence of MACE was observed in both Leiden and Confirm scores, with an increase in the scores (log-rank p < 0.001). In the multivariable analysis, compared with Leiden score < 5, the hazard ratios for Leiden scores of 5-20 and > 20 were 2.37 (95% confidence interval [CI]: 1.53-3.69; p < 0.001) and 4.39 (95% CI: 2.40-8.01; p < 0.001), respectively, while the Confirm score did not demonstrate a statistically significant association with the risk of MACE. The Leiden score showed a greater AUC of 0.840 compared to 0.777 for the Confirm score (p < 0.001). CONCLUSION: CCTA-based risk score algorithms could be used as reliable cardiovascular risk predictors in patients with DM and suspected CAD, among which the Leiden score outperformed the Confirm score in predicting MACE.

Integrating Coronary Plaque Information from CCTA by ML Predicts MACE in Patients with Suspected CAD.

Conventional prognostic risk analysis in patients undergoing noninvasive imaging is based upon a limited selection of clinical and imaging findings, whereas machine learning (ML) algorithms include a greater number and complexity of variables. Therefore, this paper aimed to explore the predictive value of integrating coronary plaque information from coronary computed tomographic angiography (CCTA) with ML to predict major adverse cardiovascular events (MACEs) in patients with suspected coronary artery disease (CAD). Patients who underwent CCTA due to suspected coronary artery disease with a 30-month follow-up for MACEs were included. We collected demographic characteristics, cardiovascular risk factors, and information on coronary plaques by analyzing CCTA information (plaque length, plaque composition and coronary artery stenosis of 18 coronary artery segments, coronary dominance, myocardial bridge (MB), and patients with vulnerable plaque) and follow-up information (cardiac death, nonfatal myocardial infarction and unstable angina requiring hospitalization). An ML algorithm was used for survival analysis (CoxBoost). This analysis showed that chest symptoms, the stenosis severity of the proximal anterior descending branch, and the stenosis severity of the middle right coronary artery were among the top three variables in the ML model. After the 22nd month of follow-up, in the testing dataset, ML showed the largest C-index and AUC compared with Cox regression, SIS, SIS score + clinical factors, and clinical factors. The DCA of all the models showed that the net benefit of the ML model was the highest when the treatment threshold probability was between 1% and 9%. Integrating coronary plaque information from CCTA based on ML technology provides a feasible and superior method to assess prognosis in patients with suspected coronary artery disease over an approximately three-year period.

Prognostic Value of Atherosclerotic Extent in Diabetic Patients with Nonobstructive Coronary Artery Disease.

METHODS AND RESULTS: 813 DM patients (mean age 58.9 ± 9.9 years, 48.1% male) referred for CCTA due to suspected CAD in 2015-2017 were consecutively included. During a median follow-up of 31.77 months, 50 major adverse cardiovascular events (MACEs) (6.15%) were experienced, including 2 cardiovascular deaths, 14 nonfatal myocardial infarctions, 27 unstable anginas requiring hospitalization, and 7 strokes. Three groups were defined based on coronary stenosis combined with Leiden score as normal, nonobstructive Leiden < 5, and nonobstructive Leiden ≥ 5. Cox models were used to assess the prognosis of plaque burden within these groups. An incremental incidence of MACE rates was observed. After adjustment for age, gender, and presence of high-risk plaque, the group of Leiden ≥ 5 showed a higher risk than Leiden < 5 (HR: 1.88, 95% CI: 1.03-3.42, p = 0.039). Similar results were observed when segment involvement score (SIS) was used for sensitivity analysis. CONCLUSION: Atherosclerotic extent was associated with the prognosis of DM patients with nonobstructive coronary artery disease, highlighting the importance of better risk stratification and management.

Impact of atherosclerotic extent on clinical outcome for diabetic patients with non-obstructive coronary artery disease.

Background and aims: The prognostic impact of non-obstructive coronary artery disease (CAD) has long been underestimated due to its mild stenosis (<50% stenosis). We aim to investigate the prognostic value of atherosclerotic extent in DM patients with non-obstructive CAD. Methods: The analysis was based on a single center cohort of DM patients referred for coronary computed tomography angiography (CCTA) due to suspect CAD in 2015-2017. Based on coronary stenosis combined with segment involvement score (SIS), the study population were divided into four groups: normal (0% stenosis), non-obstructive SIS<3, non-obstructive SIS≥3 and obstructive (≥50% stenosis). The intra-class correlation (ICC) was used to test the inter-and intra-reviewer agreement. Multivariate Cox model and Kaplan-Meier method were used to evaluate the effect size of atherosclerotic extent on the prognosis. Results: In total, 1241 patients (age 60.2 ± 10.4 years, 54.1% male) were included, of which 50.2% were non-obstructive. During a median follow-up of 2.6 years, 131 MACEs (10.6%) were adjudicated, including 17 cardiovascular deaths, 28 non-fatal myocardial infarctions, 64 unstable anginas requiring hospitalization and 22 strokes. Incremental event rates could be observed across the four groups. After adjustment for age, gender, hyperlipidemia and presence of high-risk plaque, Hazard Ratio (HR) for non-obstructive SIS<3, non-obstructive SIS≥3 and the obstructive group was 1.84 (95%CI: 0.70-4.79), 3.71 (95%CI: 1.37-10.00) and 5.46 (95%CI: 2.18-13.69), respectively. Compared with non-obstructive SIS<3, non-obstructive SIS≥3 showed a significantly higher risk (HR:2.02 95%CI:1.11-3.68, p = 0.021). Similar results were demonstrated when Leiden risk score was used for sensitivity analysis. Conclusion: In DM patients with non-obstructive CAD, atherosclerotic extent was associated with higher risk of major adverse cardiac events at long-term follow-up. Efforts should be made to determine risk stratification for the management of DM patients with non-obstructive CAD.