Diagnostic Performance of Fractional Flow Reserve From CT Coronary Angiography With Analytical Method

Diagnostic performance of angiography-derived fractional flow reserve and CT-derived fractional flow reserve: A systematic review and Bayesian network meta-analysis

OBJECTIVE

Accumulating evidence has demonstrated that fractional flow reserves (FFRs) derived from invasive coronary angiograms (CA-FFRs) and coronary computed tomography angiography-derived FFRs (CT-FFRs) are promising alternatives to wire-based FFRs. However, it remains unclear which method has better diagnostic performance. This systematic review and meta-analysis aimed to compare the diagnostic performances of the two approaches.

METHODS

The Cochrane Library, PubMed, Embase, Medline (Ovid), the Chinese China National Knowledge Infrastructure Database (CNKI), VIP, and WanFang Data databases were searched for relevant studies that included comparisons between CA-FFR and CT-FFR, from their respective database inceptions until January 1, 2023. Studies where both noninvasive FFR (including CA-FFR and CT-FFR) and invasive FFR (as a reference standard) were performed for the diagnosis of ischemic coronary artery disease and were designed as prospective, paired diagnostic studies, were pulled. The diagnostic test accuracy method and Bayesian hierarchical summary receiver operating characteristic (ROC) model for network meta-analysis (NMA) of diagnostic tests (HSROC-NMADT) were both used to perform a meta-analysis on the data.

RESULTS

Twenty-six studies were included in this NMA. The results from both the diagnostic test accuracy and HSROC-NMADT methods revealed that the diagnostic accuracy of CA-FFR was higher than that of CT-FFR, in terms of sensitivity (Se; 0.86 vs. 0.84), specificity (Sp; 0.90 vs. 0.78), positive predictive value (PPV; 0.83 vs. 0.70), and negative predictive value (NPV; 0.91 vs. 0.89) for the detection of myocardial ischemia. A cumulative ranking curve analysis indicated that CA-FFR had a higher diagnostic accuracy than CT-FFR in the context of this study, with a higher area under the ROC curve (AUC; 0.94 vs. 0.87).

CONCLUSIONS

Although both of these two commonly used virtual FFR methods showed high levels of diagnostic accuracy, we demonstrated that CA-FFR had a better Se, Sp, PPV, NPV, and AUC than CT-FFR. However, this study provided only indirect comparisions; therefore, larger studies are warranted to directly compare the diagnostic performances of these two approaches.

Coronary CT Angiography-based Morphologic Index for Predicting Hemodynamically Significant Coronary Stenosis

Purpose To develop a new coronary CT angiography (CCTA)-based index, α×LL/MLD4, that considers lesion entrance angle (α) in addition to lesion length (LL) and minimal lumen diameter (MLD) and to evaluate its efficacy in predicting hemodynamically significant coronary stenosis compared with invasive coronary angiography (ICA)-derived fractional flow reserve (FFR). Materials and Methods This prospective study enrolled participants (September 2016-March 2020) from two centers who underwent CCTA followed by ICA (ClinicalTrials.gov identifier: NCT03054324). CCTA images were processed semiautomatically to measure LL, MLD, and α for calculating α×LL/MLD4. Diagnostic performance and accuracy of α×LL/MLD4 and LL/MLD4 in detecting hemodynamically significant coronary stenosis were compared against the reference standard (invasive FFR ≤ 0.80). Results In total, 133 participants (mean age, 63 years ± 9 [SD]; 99 [74%] men) with 210 stenosed coronary arteries were analyzed. Median α×LL/MLD4 was 54.0 degree/mm3 (IQR, 25.3-128.7) in participants with invasive FFR of 0.80 or less and 6.7 degree/mm3 (IQR, 3.3-12.8) in participants with invasive FFR of more than 0.80 (P < .001). The per-vessel accuracy, sensitivity, specificity, positive predictive value, and negative predictive value for discriminating ischemic lesions were 86.2%, 83.1%, 88.4%, 84.1%, and 87.7% for α×LL/MLD4 and 80.5%, 66.3%, 90.9%, 84.3%, and 78.6% for LL/MLD4, respectively. Area under the receiver operating characteristic curve for discriminating hemodynamically significant stenosis was 0.93 for α×LL/MLD4, which was significantly greater than the values of 0.84 for LL/MLD4 and 0.63 for diameter stenosis (both P < .001). Conclusion The new morphologic index, α×LL/MLD4, incorporating lesion entrance angle achieved higher diagnostic performance in detecting hemodynamically significant lesions compared with diameter stenosis and LL/MLD4. Keywords: CT Angiography, Cardiac, Coronary Arteries, Ischemia, Infarction, Technology Assessment Clinical trial registration no. NCT03054324 Supplemental material is available for this article. © RSNA, 2023 See also the commentary by Fairbairn and Nørgaard in this issue.

Diagnosis of coronary artery disease in patients with type 2 diabetes mellitus based on computed tomography and pericoronary adipose tissue radiomics: a retrospective cross-sectional study

BACKGROUND

Patients with type 2 diabetes mellitus (T2DM) are highly susceptible to cardiovascular disease, and coronary artery disease (CAD) is their leading cause of death. We aimed to assess whether computed tomography (CT) based imaging parameters and radiomic features of pericoronary adipose tissue (PCAT) can improve the diagnostic efficacy of whether patients with T2DM have developed CAD.

METHODS

We retrospectively recruited 229 patients with T2DM but no CAD history (146 were diagnosed with CAD at this visit and 83 were not). We collected clinical information and extracted imaging manifestations from CT images and 93 radiomic features of PCAT from all patients. All patients were randomly divided into training and test groups at a ratio of 7:3. Four models were constructed, encapsulating clinical factors (Model 1), clinical factors and imaging indices (Model 2), clinical factors and Radscore (Model 3), and all together (Model 4), to identify patients with CAD. Receiver operating characteristic curves and decision curve analysis were plotted to evaluate the model performance and pairwise model comparisons were performed via the DeLong test to demonstrate the additive value of different factors.

RESULTS

In the test set, the areas under the curve (AUCs) of Model 2 and Model 4 were 0.930 and 0.929, respectively, with higher recognition effectiveness compared to the other two models (each p < 0.001). Of these models, Model 2 had higher diagnostic efficacy for CAD than Model 1 (p < 0.001, 95% CI [0.129-0.350]). However, Model 4 did not improve the effectiveness of the identification of CAD compared to Model 2 (p = 0.776); similarly, the AUC did not significantly differ between Model 3 (AUC = 0.693) and Model 1 (AUC = 0.691, p = 0.382). Overall, Model 2 was rated better for the diagnosis of CAD in patients with T2DM.

CONCLUSIONS

A comprehensive diagnostic model combining patient clinical risk factors with CT-based imaging parameters has superior efficacy in diagnosing the occurrence of CAD in patients with T2DM.

Diagnostic Performance of On-Site Computed Tomography Derived Fractional Flow Reserve on Non-Culprit Coronary Lesions in Patients with Acute Coronary Syndrome

The role of coronary computed tomography angiography (CCTA) derived fractional flow reserve (CT-FFR) in the assessment of non-culprit lesions (NCL) in patients with acute coronary syndrome (ACS) is debated. In this prospective clinical study, a total of 68 ACS patients with 89 moderate (30−70% diameter stenosis) NCLs were enrolled to evaluate the diagnostic accuracy of on-site CT-FFR compared to invasive fractional flow reserve (FFRi) and dobutamine stress echocardiography (DSE) as reference standards. CT-FFR and FFRi values ≤0.80, as well as new or worsening wall motion abnormality in ≥2 contiguous segments on the supplying area of an NCL on DSE, were considered positive for ischemia. Sensitivity, specificity, positive, and negative predictive value of CT-FFR relative to FFRi and DSE were 51%, 89%, 75%, and 74% and 37%, 77%, 42%, and 74%, respectively. CT-FFR value (β = 0.334, p < 0.001) and CT-FFR drop from proximal to distal measuring point [(CT-FFR drop), β = −0.289, p = 0.002)] were independent predictors of FFRi value in multivariate linear regression analysis. Based on comparing their receiver operating characteristics area under the curve (AUC) values, CT-FFR value and CT-FFR drop provided better discriminatory power than CCTA-based minimal lumen diameter stenosis to distinguish between an NCL with positive and negative FFRi [0.77 (95% Confidence Intervals, CI: 0.67−0.86) and 0.77 (CI: 0.67−0.86) vs. 0.63 (CI: 0.52−0.73), p = 0.029 and p = 0.043, respectively]. Neither CT-FFR value nor CT-FFR drop was predictive of regional wall motion score index at peak stress (β = −0.440, p = 0.441 and β = 0.403, p = 0.494) or was able to confirm ischemia on the territory of an NCL revealed by DSE (AUC = 0.54, CI: 0.43−0.64 and AUC = 0.55, CI: 0.44−0.65, respectively). In conclusion, on-site CT-FFR is superior to conventional CCTA-based anatomical analysis in the assessment of moderate NCLs; however, its diagnostic capacity is not sufficient to make it a gatekeeper to invasive functional evaluation. Moreover, based on its comparison with DSE, CT-FFR might not yield any information on the microvascular dysfunction in the territory of an NCL.

Effect of 320-row CT reconstruction technology on fractional flow reserve derived from coronary CT angiography based on machine learning: single- versus multiple-cardiac periodic images

BACKGROUND

Fractional flow reserve derived from computed tomography (CT-FFR) can be used to noninvasively evaluate the functions of coronary arteries and has been widely welcomed in the field of cardiovascular research. However, whether different image reconstruction schemes have an effect on CT-FFR analysis through single- and multiple-cardiac periodic images in the same patient has not been investigated.

METHODS

This study retrospectively enrolled 122 patients who underwent 320-row computed tomography (CT) examination with both single- and multiple-cardiac periodic reconstruction schemes; a total of 366 coronary arteries were analyzed. The lowest CT-FFR values of each vessel and the poststenosis CT-FFR values of the lesion-specific coronary artery were measured using the two reconstruction techniques. The Wilcoxon signed-rank test was used to compare differences in CT-FFR values between the two reconstruction techniques. Spearman correlation analysis was performed to determine the relationship between CT-FFR values derived using the two methods. Bland-Altman and intraclass correlation coefficient (ICC) analyses were performed to evaluate the consistency of CT-FFR values.

RESULTS

In all blood vessels, the lowest CT-FFR values showed no significant differences between the two reconstruction techniques in the left anterior descending artery (LAD; P=0.65), left circumflex artery (LCx; P=0.46), or right coronary artery (RCA; P=0.22). In blood vessels with atherosclerotic plaques, the poststenosis CT-FFR values (2 cm distal to the maximum stenosis) exhibited no significant differences between the two reconstruction techniques in the LAD (P=0.78), LCx (P=1.00), or RCA (P=1.00). The mean CT-FFR values of single- and multiple-cardiac periodic images showed excellent correlation and minimal bias in all groups.

CONCLUSIONS

CT-FFR analysis based on an artificial intelligence deep learning neural network is stable and not affected by the type of 320-row CT reconstruction technology.