Novel motion correction algorithm improves diagnostic performance of CT fractional flow reserve.

OBJECTIVES: This study aimed to investigate the diagnostic performance of computed tomography (CT) fractional flow reserve (CT-FFR) derived from standard images (STD) and images processed via first-generation (SnapShot Freeze, SSF1) and second-generation (SnapShot Freeze 2, SSF2) motion correction algorithms. METHODS: 151 patients who underwent coronary CT angiography (CCTA) and invasive coronary angiography (ICA)/FFR within 3 months were retrospectively included. CCTA images were reconstructed using an iterative reconstruction technique and then further processed through SSF1 and SSF2 algorithms. All images were divided into three groups: STD, SSF1, and SSF2. Obstructive stenosis was defined as a diameter stenosis of ≥ 50 % in the left main artery or ≥ 70 % in other epicardial vessels. Stenosis with an FFR of ≤ 0.8 or a diameter stenosis of ≥ 90 % (as revealed via ICA) was considered ischemic. In patients with multiple lesions, the lesion with lowest CT-FFR was used for patient-level analysis. RESULTS: The overall quality score in SSF2 group (median = 3.67) was markedly higher than that in STD (median = 3) and SSF1 (median = 3) groups (P < 0.001). The best correlation (r = 0.652, P < 0.001) and consistency (mean difference = 0.04) between the CT-FFR and FFR values were observed in the SSF2 group. At the per-lesion level, CT-FFRSSF2 outperformed CT-FFRSSF1 in diagnosing ischemic lesions (area under the curve = 0.887 vs. 0.795, P < 0.001). At the per-patient level, the SSF2 group also demonstrated the highest diagnostic performance. CONCLUSION: The SSF2 algorithm significantly improved CCTA image quality and enhanced its diagnostic performance for evaluating stenosis severity and CT-FFR calculations.

Feasibility and Diagnostic Performance of Functional SYNTAX Score Derived From Dynamic CT Myocardial Perfusion Imaging.

BACKGROUND: Computed tomography (CT) fractional flow reserve (FFR)-derived functional SYNTAX score (FSSCT-FFR) is a valuable method for guiding treatment strategy in patients with multivessel coronary artery disease. Dynamic CT myocardial perfusion imaging (CT-MPI) demonstrates higher diagnostic accuracy than CT-FFR in identifying hemodynamically significant coronary artery disease. We aimed to evaluate the feasibility of CT-MPI-derived FSS (FSSCT-MPI) with reference to invasive FSS. METHODS: In this retrospective study, patients with multivessel coronary artery disease who underwent dynamic CT-MPI+ coronary CT angiography and invasive coronary angiography or FFR within 4 weeks were consecutively included. Invasive (FSSinvasive) and noninvasive FSS (FSSCT-MPI and FSSCT-FFR) were calculated by an online calculator, which assigned points to lesions with hemodynamic significance (defined as FFRinvasive ≤0.80, invasive coronary angiography diameter stenosis ≥90%, CT-FFR ≤0.80, and myocardial ischemia on CT-MPI). Weighted κ value and net reclassification index were calculated to determine the consistency and incremental discriminatory power of FSSCT-MPI. Receiver operating characteristic curve analysis was used for the comparison of FSSCT-MPI and FSSCT-FFR in detecting intermediate- to high-risk patients. RESULTS: A total of 119 patients (96 men; 64.6±10.6 years) with 305 obstructive lesions were included. The average FSSCT-MPI, FSSCT-FFR, and FSSinvasive were 15.58±13.03, 16.18±13.30, and 13.11±12.22, respectively. The agreement on risk classification based on the FSSCT-MPI tertiles was good (weighted κ, 0.808). With reference to FSSinvasive, FSSCT-MPI correctly reclassified 27 (22.7%) patients from the intermediate- to high SYNTAX score group to the low-score group (net reclassification index, 0.30; P<0.001). In patients with severe calcification, FSSCT-MPI had better diagnostic value than FSSCT-FFR in detecting intermediate- to high-risk patients when compared with FSSinvasive (area under the curve, 0.976 versus 0.884; P<0.001). CONCLUSIONS: Noninvasive FSS derived from CT-MPI is feasible and has strong concordance with FSSinvasive. It allows accurate categorization of FSS in patients with multivessel coronary artery disease, in particular with severe calcification.

Automatic epicardial adipose tissue segmentation in pulmonary computed tomography venography using nnU-Net.

Background: Epicardial adipose tissue (EAT) is a key aspect in the investigation of cardiac pathophysiology. We sought to develop a deep learning (DL) model for fully automatic extraction and quantification of EAT through pulmonary computed tomography venography (PCTV) images. Methods: In this retrospective study, we included 128 patients with atrial fibrillation and PCTV from 2 hospitals. A DL model for automated EAT segmentation was developed from a training set of 51 patients and a validation set of 13 patients from hospital A. The algorithm was further validated using an internal test set of 16 patients from hospital A and an external test set of 48 patients from hospital B. The consistency and measurement agreement of EAT quantification were compared between the DL model and the conventional manual protocol using the Dice score coefficient (DSC), Hausdorff distance (HD95), Pearson correlation coefficient, and Bland-Altman plot. Results: In the internal and external test set, automated segmentation with DL was successful in all cases. The total analysis time was shorter for DL than for manual reconstruction (5.43±2.52 vs. 106.20±15.90 min; P<0.001). The EAT segmented with the DL model had good consistency with manual segmentation (the DSC of the internal and external test sets were 0.92±0.02 and 0.88±0.03, respectively). The quantification of EAT evaluated with the 2 methods showed excellent correlation (all correlation coefficients >0.9; all P values <0.001) and minimal measurement difference. Conclusions: The proposed DL model achieved fully automatic quantification of EAT from PCTV images. The yielded results were highly consistent with those of manual quantification.

Microvascular Myocardial Ischemia in Patients With Diabetes Without Obstructive Coronary Stenosis and Its Association With Angina.

OBJECTIVE: To investigate the incidence of microvascular myocardial ischemia in diabetic patients without obstructive coronary artery disease (CAD) and its relationship with angina. MATERIALS AND METHODS: Diabetic patients and an intermediate-to-high pretest probability of CAD were prospectively enrolled. Non-diabetic patients but with an intermediate-to-high pretest probability of CAD were retrospectively included as controls. The patients underwent dynamic computed tomography-myocardial perfusion imaging (CT-MPI) and coronary computed tomography angiography (CCTA) to quantify coronary stenosis, myocardial blood flow (MBF), and extracellular volume (ECV). The proportion of patients with microvascular myocardial ischemia, defined as any myocardial segment with a mean MBF ≤ of 100 mL/min/100 mL, in patients without obstructive CAD (Coronary Artery Disease-Reporting and Data System [CAD-RADS] grade 0-2 on CCTA) was determined. Various quantitative parameters of the patients with and without diabetes without obstructive CAD were compared. Multivariable analysis was used to determine the association between microvascular myocardial ischemia and angina symptoms in diabetic patients without obstructive CAD. RESULTS: One hundred and fifty-two diabetic patients (mean age: 59.7 ± 10.7; 77 males) and 266 non-diabetic patients (62.0 ± 12.3; 167 males) were enrolled; CCTA revealed 113 and 155 patients without obstructive CAD, respectively. For patients without obstructive CAD, the mean global MBF was significantly lower for those with diabetes than for those without (152.8 mL/min/100 mL vs. 170.4 mL/min/100 mL, P < 0.001). The mean ECV was significantly higher for diabetic patients (27.2% vs. 25.8%, P = 0.009). Among the patients without obstructive CAD, the incidence of microvascular myocardial ischemia (36.3% [41/113] vs. 10.3% [16/155], P < 0.001) and interstitial fibrosis (69.9% [79/113] vs. 33.3% [8/24], P = 0.001) were significantly higher in diabetic patients than in the controls. The presence of microvascular myocardial ischemia was independently associated with angina symptoms (adjusted odds ratio = 3.439, P = 0.037) in diabetic patients but without obstructive CAD. CONCLUSION: Dynamic CT-MPI + CCTA revealed a high incidence of microvascular myocardial ischemia in diabetic patients without obstructive CAD. Microvascular myocardial ischemia is strongly associated with angina.

Estimation of stress-strength reliability from unit-Burr â ¢ distribution under records data.

This paper explores estimation of stress-strength reliability based on upper record values. When the strength and stress variables follow unit-Burr Ⅲ distributions, a generalized inferential approach is proposed for estimating stress-strength reliability (SSR). Under the common strength and stress parameter case, two types of pivotal quantities are constructed respectively, and then the generalized point and interval estimates for SSR are proposed in consequence, where the associated Monte-Carlo sampling approach is provided for computation. In addition, when strength and stress variables feature unequal model parameters, different generalized point and confidence interval estimates are also established in this regard. Extensive simulation studies are conducted to examine the behavior of proposed methods. Finally, a real-life data example is presented for illustration.

Financial and clinical outcomes of CT myocardial perfusion imaging and coronary CT angiography-guided versus coronary CT angiography-guided strategy.

OBJECTIVES: To compare the financial and clinical outcomes of CT myocardial perfusion imaging (CT-MPI) + coronary CT angiography (CCTA)-guided versus CCTA-guided strategy in patients suspected of chronic coronary syndrome (CCS). MATERIALS AND METHODS: This study retrospectively included consecutive patients suspected of CCS and referred for CT-MPI+CCTA-guided and CCTA-guided treatment. The details of medical costs within 3 months after index imaging, including downstream invasive procedures, hospitalization, and medications, were recorded. All patients were followed up for major adverse cardiac events (MACE) at a median time of 22 months. RESULTS: A total of 1335 patients (559 in the CT-MPI+CCTA group and 776 in the CCTA group) were finally included. In the CT-MPI+CCTA group, 129 patients (23.1%) underwent ICA and 95 patients (17.0%) received revascularization. In the CCTA group, 325 patients (41.9%) underwent ICA whereas 194 patients (25.0%) received revascularization. An addition of CT-MPI in the evaluation strategy remarkably reduced the healthcare expenditure, compared with CCTA-guided strategy (USD 1441.36 vs. USD 232.91, p < 0.001). After adjustment for potential cofounders after inverse probability weighting, the CT-MPI+CCTA strategy was significantly associated with lower medical expenditure [adjusted cost ratio (95% CI) for total costs: 0.77 (0.65-0.91), p < 0.001]. In addition, there was no significant difference regarding the clinical outcome between the two groups (adjusted HR= 0.97; p = 0.878). CONCLUSIONS: CT-MPI+CCTA considerably reduced medical expenditures in patients suspected of CCS, compared to the CCTA strategy alone. Moreover, CT-MPI+CCTA led to a lower rate of invasive procedures with a similar long-term prognosis. CLINICAL RELEVANCE STATEMENT: CT myocardial perfusion imaging + coronary CT angiography-guided strategy reduced medical expenditure and invasive procedure rate. KEY POINTS: • CT-MPI+CCTA strategy yielded significantly lower medical expenditure than did the CCTA strategy alone in patients with suspected CCS. • After adjustment for potential confounders, the CT-MPI+CCTA strategy was significantly associated with lower medical expenditure. • No significant difference was observed regarding the long-term clinical outcome between the two groups.

CT-derived fractional flow reserve for prediction of major adverse cardiovascular events in diabetic patients.

OBJECTIVES: To investigate the prognostic value of computed tomography fractional flow reserve (CT-FFR) in patients with diabetes and to establish a risk stratification model for major adverse cardiac event (MACE). METHODS: Diabetic patients with intermediate pre-test probability of coronary artery disease were prospectively enrolled. All patients were referred for coronary computed tomography angiography and followed up for at least 2 years. In the training cohort comprising of 957 patients, two models were developed: model1 with the inclusion of clinical and conventional imaging parameters, model2 incorporating the above parameters + CT-FFR. An internal validation cohort comprising 411 patients and an independent external test cohort of 429 patients were used to validate the proposed models. RESULTS: 1797 patients (mean age: 61.0 ± 7.0 years, 1031 males) were finally included in the present study. MACE occurred in 7.18% (129/1797) of the current cohort during follow- up. Multivariate Cox regression analysis revealed that CT-FFR ≤ 0.80 (hazard ratio [HR] = 4.534, p < 0.001), HbA1c (HR = 1.142, p = 0.015) and low attenuation plaque (LAP) (HR = 3.973, p = 0.041) were the independent predictors for MACE. In the training cohort, the Log-likelihood test showed statistical significance between model1 and model2 (p < 0.001). The C-index of model2 was significantly larger than that of model1 (C-index = 0.82 [0.77-0.87] vs. 0.80 [0.75-0.85], p = 0.021). Similar findings were found in internal validation and external test cohorts. CONCLUSION: CT-FFR was a strong independent predictor for MACE in diabetic cohort. The model incorporating CT-FFR, LAP and HbA1c yielded excellent performance in predicting MACE.

Computed Tomography Radiomics Model Predicts Procedure Success of Coronary Chronic Total Occlusions.

BACKGROUND: Coronary computed tomography (CT) angiography imaging is useful for the preprocedural evaluation of chronic total occlusion (CTO). However, the predictive value of CT radiomics model for successful percutaneous coronary intervention (PCI) has not been studied. We aimed to develop and validate a CT radiomics model for predicting PCI success of CTOs. METHODS: In this retrospective study, a radiomics-based model for predicting PCI success was developed on the training and internal validation sets of 202 and 98 patients with CTO, collected from 1 tertiary hospital. The proposed model was validated on an external test set of 75 CTO patients enrolled from another tertiary hospital. CT radiomics features of each CTO lesion were manually labeled and extracted. Other anatomical parameters, including occlusion length, entry morphology, tortuosity, and calcification burden, were also measured. Fifteen radiomics features, 2 quantitative plaque features, and CT-derived Multicenter CTO Registry of Japan score were used to train different models. The predictive values of each model were evaluated for predicting revascularization success. RESULTS: In the external test set, 75 patients (60 men; 65 years [58.5, 71.5]) with 83 CTO lesions were assessed. Occlusion length was shorter (13.00 mm versus 29.30 mm, P=0.007) in PCI success group whereas the presence of tortuous course was more commonly presented in PCI failure group (1.49% versus 25.00%, P=0.004). The radiomics score was significantly smaller in PCI success group (0.10 versus 0.55, P<0.001). The area under the curve of CT radiomics-based model was significantly higher than that of CT-derived Multicenter CTO Registry of Japan score for predicting PCI success (area under the curve=0.920 versus 0.752, P=0.008). The proposed radiomics model accurately identified 89.16% (74/83) CTO lesions with procedure success. CONCLUSIONS: CT radiomics-based model outperformed CT-derived Multicenter CTO Registry of Japan score for predicting PCI success. The proposed model is more accurate than the conventional anatomical parameters to identify CTO lesions with PCI success.

Prediction of microvascular complications in diabetic patients without obstructive coronary stenosis based on peri-coronary adipose tissue attenuation model.

OBJECTIVES: To investigate the predictive value of peri-coronary adipose tissue (PCAT) attenuation for microvascular complications in diabetic patients without significant stenosis and to develop a prediction model for early risk stratification. METHODS: This study retrospectively included patients clinically identified for coronary computed tomography angiography (CCTA) and type 2 diabetes between January 2017 and December 2020. All patients were followed up for at least 1 year. The clinical data and CCTA-based imaging characteristics (including PCAT of major epicardial vessels, high-risk plaque features) were recorded. In the training cohort comprising of 579 patients, two models were developed: model 1 with the inclusion of clinical factors and model 2 incorporating clinical factors + RCAPCAT using multivariable logistic regression analysis. An internal validation cohort comprising 249 patients and an independent external validation cohort of 269 patients were used to validate the proposed models. RESULTS: Microvascular complications occurred in 69.1% (758/1097) of the current cohort during follow-up. In the training cohort, model 2 exhibited improved predictive power over model 1 based on clinical factors (AUC = 0.820 versus 0.781, p = 0.003) with lower prediction error (Brier score = 0.146 versus 0.164) compared to model 1. Model 2 accurately categorized 78.58% of patients with diabetic microvascular complications. Similar performance of model 2 in the internal validation cohort and the external validation cohort was further confirmed. CONCLUSIONS: The model incorporating clinical factors and RCAPCAT predicts the development of microvascular complications in diabetic patients without significant coronary stenosis. KEY POINTS: • Hypertension, HbA1c, duration of diabetes, and RCAPCAT were independent risk factors for microvascular complications. • The prediction model integrating RCAPCAT exhibited improved predictive power over the model only based on clinical factors (AUC = 0.820 versus 0.781, p = 0.003) and showed lower prediction error (Brier score=0.146 versus 0.164).

Radiomics features of pericoronary adipose tissue improve CT-FFR performance in predicting hemodynamically significant coronary artery stenosis.

OBJECTIVES: To evaluate the value of radiomics-based model of pericoronary adipose tissue (PCAT) combined with CT fractional flow reserve (CT-FFR) in predicting hemodynamically significant coronary stenosis. METHODS: Patients with suspected or known coronary artery disease, who had coronary computed tomography angiography (CCTA), invasive coronary angiography (ICA), and FFR within 1 month, were retrospectively included. Radiomics features of lesion-based PCAT were extracted. The lesion-specific CT-FFR values, CCTA-derived diameter stenosis, lesion length, and PCAT attenuation were also measured. FFR values were used as the reference standard to assess the diagnostic performance of radiomics model, CT-FFR, and combined model for detection of flow-limiting stenosis. RESULTS: A total of 146 patients with 180 lesions were included in the study. All lesions were divided into training and validation cohorts at a ratio of 2:1. CT-FFR model exhibited the highest area under the curve (AUC) (0.803 for training, 0.791 for validation) in predicting hemodynamically significant stenosis, followed by radiomics model (0.776 for training, 0.744 for validation). However, no statistically significant difference was found between the AUCs of the above two models (p > 0.05). When CT-FFR was combined with radiomics model, the AUC reached 0.900 for training cohort and 0.875 for validation cohort, which were significantly higher than that of CT-FFR and radiomics model alone (both p < 0.05). CONCLUSION: The diagnostic performance of PCAT radiomics model was comparable to that of CT-FFR for identification of ischemic coronary stenosis. Adding PCAT radiomics model to CT-FFR showed incremental value in discriminating flow-limiting from non-flow-limiting lesions. KEY POINTS: • Radiomics analysis of lesion-based PCAT is potentially an alternative method to identify hemodynamic significance of coronary artery stenosis. • Adding radiomics model of PCAT to CT-FFR improved diagnostic performance for the detection of flow-limiting coronary stenosis. • Radiomics features + CT-FFR is a promising noninvasive method for comprehensive evaluation of hemodynamic significance of coronary artery stenosis.

Directivity-Enhanced Detection of a Single Nanoparticle Using a Plasmonic Slot Antenna.

In situ refractive index sensors integrated with nanoaperture-based optical tweezers possess stable and sensitive responsivity to single nanoparticles. In most existing works, detection events are only identified using the total light intensity with directivity information ignored, leading to a low signal-to-noise ratio. Here, we propose to detect an optically trapped 20 nm silica particle by monitoring directivity of a plasmonic antenna. The main and secondary radiation lobes of the antenna reverse upon trapping because the particle-induced perturbation negates the relative phase between two antenna elements, leading to a significant change of the antenna front-to-back ratio. As a result, we obtain a signal-to-noise ratio of 20, with an order-of-magnitude improvement as compared to the intensity-only detection scheme.

Increased coronary pericoronary adipose tissue attenuation in diabetic patients compared to non-diabetic controls: A propensity score matching analysis.

BACKGROUND: Pericoronary adipose tissue (PCAT) attenuation is an indicator of active inflammation of perivascular adipose tissue, which is supposed to increase in diabetic patients. We aimed to investigate the PCAT attenuation values and high-risk plaque (HRP) features in diabetic and non-diabetic subjects with different stenotic extents. METHODS: Consecutive type 2 diabetes patients and non-diabetic patients with chest pain and intermediate pre-test probability of coronary artery disease (CAD) were prospectively enrolled and underwent coronary computed tomography angiography (CCTA). At per-patient level, PCAT attenuation values of three major epicardial coronary vessels, as well as HRP features were measured. PCAT attenuation values and HRP features were compared between diabetic and non-diabetic subjects according to the presence or absence of obstructive stenosis. RESULTS: 1700 patients (mean age: 65.5 â€‹± â€‹11.7, 940 males) were divided into two groups according to presence of obstructive stenosis on CCTA. Propensity score matching was performed in further analysis. RCAPCAT was significantly higher in diabetic subjects than that in non-diabetic subjects, regardless of the presence of obstructive stenosis (-83.60 â€‹± â€‹9.51 HU vs. -88.58 â€‹± â€‹9.37 HU, p â€‹< â€‹0.001) or absence of obstructive stenosis (-83.70 â€‹± â€‹10.32 HU vs. -88.76 â€‹± â€‹8.28 HU, p â€‹< â€‹0.001). In contrast, HRP features were more commonly presented in diabetic patients with obstructive stenosis than in those without obstructive stenosis. According to subgroup analysis based on acquisition tube voltage, RCAPCAT was the only parameter showing consistent difference between diabetic and non-diabetic patients. CONCLUSIONS: RCAPCAT was significantly higher in diabetic patients than that in non-diabetic patients regardless of stenotic severity and plaque vulnerability.

The use of lesion-specific calcium morphology to guide the appropriate use of dynamic CT myocardial perfusion imaging and CT fractional flow reserve.

BACKGROUND: We aimed to optimize the diagnostic strategy for dynamic computed tomography myocardial perfusion imaging (CT-MPI) and CT fractional flow reserve (CT-FFR) in the evaluation of coronary artery disease (CAD). METHODS: Patients who had undergone coronary CT angiography (CCTA) + dynamic CT-MPI and invasive coronary angiography (ICA)/FFR within a 4-week period were retrospectively included. Lesion-specific characteristics were recorded, and multivariate logistic regression was performed to determine the predictors of mismatched CT findings with ICA results. An optimized diagnostic strategy was proposed based on the diagnostic performance of dynamic CT-MPI and CT-FFR compared with ICA/FFR. A net reclassification index (NRI) was calculated to determine the incremental discriminatory power of optimized CT-FFR + dynamic CT-MPI strategy compared to CT-FFR alone. RESULTS: The study included 180 patients with 229 diseased vessels. For CT-FFR, a calcified lesion with a calcium arc >180° was the only independent predictor for misdiagnosis of ischemic coronary stenosis (odds ratio =2.367; P=0.002). For noncalcified lesions and calcified lesions with a calcium arc ≤180°, the sensitivity and negative predictive value (NPV) of CT-FFR were similar to those of CT-MPI (all P values >0.05), whereas the specificity and positive predictive value (PPV) of CT-FFR were significantly lower (all P values <0.05). For calcified lesions with a calcium arc >180°, the specificity, NPV, and PPV of CT-FFR were inferior to those of CT-MPI (21.2% vs. 100%, 58.3% vs. 86.8%, and 62.9% vs. 100%, respectively; all P values <0.05). As guided by lesion-specific calcium morphology, an optimized CT-FFR + dynamic CT-MPI strategy (NRI =0.2; P=0.004) would have resulted in a 27.0% and 33.9% reduction of radiation dose and contrast medium consumption, respectively, and 25.3% of patients would have avoided unnecessary invasive tests. CONCLUSIONS: The diagnostic performance of CT-FFR was significantly inferior in lesions with a calcium arc >180°. Lesion-specific calcium morphology is the preferred parameter to guide the appropriate use of CT-based functional assessment.

CT Fractional Flow Reserve for the Diagnosis of Myocardial Bridging-Related Ischemia: A Study Using Dynamic CT Myocardial Perfusion Imaging as a Reference Standard.

OBJECTIVE: To investigate the diagnostic performance of CT fractional flow reserve (CT-FFR) for myocardial bridging-related ischemia using dynamic CT myocardial perfusion imaging (CT-MPI) as a reference standard. MATERIALS AND METHODS: Dynamic CT-MPI and coronary CT angiography (CCTA) data obtained from 498 symptomatic patients were retrospectively reviewed. Seventy-five patients (mean age ± standard deviation, 62.7 ± 13.2 years; 48 males) who showed myocardial bridging in the left anterior descending artery without concomitant obstructive stenosis on the imaging were included. The change in CT-FFR across myocardial bridging (ΔCT-FFR, defined as the difference in CT-FFR values between the proximal and distal ends of the myocardial bridging) in different cardiac phases, as well as other anatomical parameters, were measured to evaluate their performance for diagnosing myocardial bridging-related myocardial ischemia using dynamic CT-MPI as the reference standard (myocardial blood flow < 100 mL/100 mL/min or myocardial blood flow ratio ≤ 0.8). RESULTS: ΔCT-FFRsystolic (ΔCT-FFR calculated in the best systolic phase) was higher in patients with vs. without myocardial bridging-related myocardial ischemia (median [interquartile range], 0.12 [0.08-0.17] vs. 0.04 [0.01-0.07], p < 0.001), while CT-FFRsystolic (CT-FFR distal to the myocardial bridging calculated in the best systolic phase) was lower (0.85 [0.81-0.89] vs. 0.91 [0.88-0.96], p = 0.043). In contrast, ΔCT-FFRdiastolic (ΔCT-FFR calculated in the best diastolic phase) and CT-FFRdiastolic (CT-FFR distal to the myocardial bridging calculated in the best diastolic phase) did not differ significantly. Receiver operating characteristic curve analysis showed that ΔCT-FFRsystolic had largest area under the curve (0.822; 95% confidence interval, 0.717-0.901) for identifying myocardial bridging-related ischemia. ΔCT-FFRsystolic had the highest sensitivity (91.7%) and negative predictive value (NPV) (97.8%). ΔCT-FFRdiastolic had the highest specificity (85.7%) for diagnosing myocardial bridging-related ischemia. The positive predictive values of all CT-related parameters were low. CONCLUSION: ΔCT-FFRsystolic reliably excluded myocardial bridging-related ischemia with high sensitivity and NPV. Myocardial bridging showing positive CT-FFR results requires further evaluation.

Design and rationale of randomized CT-PRECISION study.

BACKGROUND: Coronary computed tomography angiography (CCTA) combined with dynamic CT myocardial perfusion imaging (CT-MPI) and CCTA combined with CT fractional flow reserve (CT-FFR) are both expected to be efficient one-stop shop imaging strategies to guide clinical management. The aim of the study is to determine which of these two methods has superiority in terms of guiding treatment in patients with intermediate to high pretest probability of coronary artery disease (CAD). METHODS: CT-PRECISION (Computed Tomography myocardial PeRfusion imaging vErsus Computed tomography derived fractional flow reServe: impact ON guiding treatment and prognosis in patients with intermediate to high pretest probability of CAD) is a multicenter, prospective, open-label, randomized study to directly compare the clinical value of guiding treatment and prognostic discrimination of CCTA + dynamic CT-MPI strategy and CCTA + CT-FFR strategy in patients with intermediate to high pretest probability of CAD. Four hundred and twelve patients will be enrolled in this study and randomized to CCTA + dynamic CT-MPI arm and CCTA + CT-FFR arm. All patients will be followed up for at least 2 years. The primary endpoint is the rate of unnecessary invasive coronary angiography (ICA) within 90 days, which is defined as ICA without revascularization. The secondary endpoints will include: (I) a composite of major adverse cardiac events (MACE, defined as all-cause mortality, non-fatal myocardial infarction, rehospitalization due to aggravated angina symptoms, and late revascularization); (II) symptom change at 1 year; (III) the rate of late revascularization after CT examination; (IV) reclassification rate of CCTA + dynamic CT-MPI and CCTA + CT-FFR guided strategies compared with CCTA alone; (V) overall radiation dose, contrast media usage and medical cost. DISCUSSION: The study will provide valuable information about the optimal CT-based diagnostic strategy with regard to the clinical management of patients with intermediate to high pretest probability of CAD. TRIAL REGISTRATION: The study is registered at Chinese Clinical Trial Registry (ChiCTR) with the identifier number ChiCTR2000041102. The first enrollment is planned for January 2021.