Coronary cross-sectional area stenosis severity determined by coronary CT highly correlated with coronary functional flow reserve: a pilot study

Coronary cross-sectional area stenosis severity determined by coronary CT highly correlated with coronary functional flow reserve: a pilot study | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Coronary cross-sectional area stenosis severity determined by coronary CT highly correlated with coronary functional flow reserve: a pilot study Takuto Koumoto, Shozo Kusachi, Takumi Tomiya, Takuya Akagi, Hiroshi Kawamura, and 5 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4552080/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 23 Jul, 2025 Read the published version in Scientific Reports → Version 1 posted 10 You are reading this latest preprint version Abstract Fractional flow reserve (FFR) is the gold standard for assessing the physiological significance of coronary stenosis. We examined the potential correlation between digitally measured coronary cross-sectional area stenosis by coronary CT angiography, and the FFR. We analyzed 32 consecutive patients with stenoses who underwent invasive FFR determination. The cross-sectional area was assessed using 128-slice coronary detector-based spectral CT angiography. Power analysis revealed that the sample size enabled the detection of an area under the receiver operating characteristic (ROC) curve (AUC) of 0.90. FFR ≤ 0.8 and > 0.8 were defined as FFR-positive and FFR-negative, respectively. Intra- and inter-observer differences were negligible. AUC indicated that cross-sectional area reduction effectively discriminated between FFR-positive and FFR-negative cases, yielding a sensitivity of 0.882 and specificity of 0.933 at the cutoff of 50% area reduction, with an AUC of 0.976. Lesions with less than 45% cross-sectional area reduction on coronary CT angiography were not FFR-positive. When ROC analysis was conducted for lesion characteristics, AUC did not significantly improve. In conclusion, the coronary cross-sectional area stenosis severity from coronary CT angiography distinguished between FFR-positive and FFR-negative lesions with high accuracy. Area reduction on CT angiography is indicated to be clinically useful for predicting the FFR. Health sciences/Cardiology Health sciences/Medical research ischemic heart disease reversible ischemia coronary pressure multi-slice CT coronary hemodynamics Figures Figure 1 Introduction Percutaneous coronary intervention (PCI) is now widely used for coronary artery disease, particularly ischemic heart disease. 1, 2 Decisions relating to PCI require demonstration of reversible ischemia and examination of the extent of area perfused by the coronary artery distal to the stenotic culprit lesion. The relationship between coronary stenosis severity and ischemia has been extensively examined. A decrease in hyperemic flow after coronary occlusion has been demonstrated to reduce coronary flow reserve. This diminution in flow is most evident at hyperemic states and begins as early as 40% narrowing of vessel diameter, with more predictable reductions in hyperemic flow for stenoses ≥ 70%. 3 Another study reported that in patients with 70% stenosis, only 32% exhibited severe ischemia and 40% manifested no or mild ischemia according to myocardial perfusion scintigraphy. 4 Coronary diameter reduction is usually measured visually or using the caliper method; however, these methods are not accurate. Furthermore, luminal reduction does not accurately reflect the severity of coronary stenosis. Coronary stenosis is complicated as it is not concentric and is usually eccentric to some degree. The relationship between the grade of coronary diameter stenosis and myocardial ischemia is more complex, with ensuing studies demonstrating an unreliable relationship between stenosis and ischemia. 5 Previous studies did not demonstrate that diameter reduction is a reliable marker for reversible ischemia. On the other hand, fractional flow reserve (FFR) is used for determining reversible ischemia caused by the responsible stenotic lesion. FFR is an index of the physiological significance of coronary stenosis and is defined as the ratio of maximal blood flow in a stenotic artery to normal maximal flow. 6 FFR is the ratio of distal coronary pressure measured with a coronary pressure guidewire to aortic pressure measured simultaneously with the guiding catheter. The process of FFR of the FFR is easy. The FFR of the normal coronary artery was 1.0, and an FFR value of 0.80 or less identifies ischemia-causing coronary stenoses with an accuracy of more than 90%. 6–8 Thus, FFR is the gold standard for determining physiologically significant coronary stenosis. However, the method used to measure FFR is invasive and requires intracoronary pressure measurement. To estimate the FFR non-invasively, a fluid dynamics model applied to coronary CT angiography has been attempted. 9 The model requires many hypotheses and employs complex equations. 10 The fluid dynamic model has its own limitations. Based on these considerations, we refocused on the morphological analysis of coronary stenosis. We hypothesized that the severity of coronary cross-sectional stenosis may correlate with FFR. Although only one study has examined the relationship between cross-sectional area stenosis and FFR, it found a theoretically untenable poor relationship. The study focused on plaque volume, and different CT systems were used. No study has used detector-based spectral CT for cross-sectional area stenosis, which can provide high-quality images with sufficient resolution power. Accordingly, our study focused on analyzing the association of cross-sectional area stenosis severity and stenosis characteristics with FFR using 128-slice detector-based spectral CT. Methods Patients This study was conducted at Okayama Heart Clinic. We analyzed 32 consecutive patients with stable coronary heart disease (CHD) who underwent coronary CT and FFR measurements using coronary angiography. Informed consent was obtained from each participant. An informed consent form outlined the objectives, advantages, disadvantages, and safety concerns of the study. The required minimal sample size was > 8 FFR-positive lesions and > 8 FFR-negative lesions to detect an area under the receiver operating characteristic (ROC) curve (AUC) of 0.90 with a power of 0.90 and a significance level of α = 0.05 in ROC analysis. All examinations and analytical procedures adhered to the principles of the Declaration of Helsinki 2000 and the study was approved by the Institutional Ethics Committee for Human Research of the Okayama Heart Clinic (approval number TK1). Written informed consent for the use of data without personally identifiable information was obtained from all patients. Fractional flow reserve measurements Coronary angiography was performed using a coronary angiography catheter (Good Tec HT™, Goodman, Nagoya, Japan) and a vascular introducer (Radifocus IIH, Terumo, Tokyo, Japan). FFR was defined as the ratio between the distal coronary pressure and aortic pressure, both measured simultaneously during maximal coronary hyperemia and obtained in accordance with established methods. 8 Coronary pressure was measured using a coronary pressure guidewire (OmniWire; Philips Japan, Tokyo, Japan). Maximal hyperemia was induced by a bolus administration of nicorandil (4 mg) into the intracoronary artery. Pullback coronary pressure recordings were performed to discriminate between focal and diffuse disease. The FFR was calculated by dividing the mean distal coronary pressure by the mean aortic pressure during hyperemia. The FFR was considered diagnostic of ischemia at a threshold of 0.80 or less. 10 Coronary computed tomography scan protocol and cross-sectional area measurement Coronary CT angiography was performed using a 128-slice detector-based spectral CT system (Brilliance iCT SP; Philips Healthcare, Cleveland, OH, USA) and an automatic dual-head injector (Stellant DualFlow; Nihon MEDRAD K.K., Osaka, Japan). All patients received 0.6 mg of nitroglycerin spray (Myocor™, Astellas Pharma, Tokyo, Japan) and 2–8 mg of propranolol (Inderal; AstraZeneca, London, UK) intravenously five minutes before the examination to reduce the heart rate when the heart rate was > 70 beats per minute, in the absence of contraindications. Contrast medium (Iopamidol™ 370 mg iodine/ml; Bayer Yakuhin, Osaka, Japan) was intravenously administered at 4.5 ml/s depending on body weight (0.7 ml/kg), followed by 20% diluted contrast medium (30 ml). Imaging was initiated using a bolus-tracking method. The position of the reconstruction window within the cardiac cycle was individually optimized to minimize motion artifacts. Axial images of 0.8-mm slice thickness were reconstructed at 0.4-mm intervals using a multi-cycle reconstruction algorithm with a medium-smooth cardiac kernel (XCB). Coronary CT angiography was used to evaluate the alignment of the coronary arteries between slabs of data acquired during consecutive heart cycles. Images with coronary vessel discontinuity due to motion or arrhythmia were excluded from the study. Coronary CT was performed using a CT workstation (Extended Brilliance Workspace; Philips Healthcare, Cleveland, OH, USA). The cross-sectional area of the coronary artery was measured by tracing it on a high-resolution display with a pen. Inter- and intra-observer differences in coronary cross-area measurements were checked in 10 randomly selected areas from stenotic and non-stenotic lesions. Percents cross-sectional area stenosis severity was calculated as follows: 100×(A-B)/A, where A is the cross-sectional area at non-stenotic pre-stenosis and B is the cross-sectional area of the most severe stenotic lesion. The cross-sectional area stenosis was graded as follows: score 0, ≤ 40% stenosis; score 1, > 40% and ≤ 60% stenosis; score 2, > 40% and ≤ 60% stenosis; and score 3, ≥ 60% stenosis. Both the actual and scored values of the percentage cross-sectional stenosis severity were used for statistical analysis. Examination of other lesion characteristics In addition to cross-sectional area stenosis, the correlation of length and irregularity of stenotic lesions, irregularity of pre-stenotic lesions, and calcification of the lesion with FFR was also examined. Irregularities were graded from 0 to 2. Calcification was graded from 0 to 4. Grading was conducted by referring to sample images of each grade, and when two observers did not agree on the grade, an additional observer checked, and grading was finalized. The actual length of the stenotic lesion was graded as follows: score 0, ≤ 10 mm; score 1, > 10 and ≤ 20 mm; score 3, > 20 and ≤ 40 mm; and score 5, > 40 mm. Statistical analysis Statistical analyses were performed using R version 3.2.2, provided by the R Foundation for Statistics Computing (Vienna, Austria). 11 The power analysis for paired comparison and correlation analysis was conducted using G*Power 3.1.9.7. 12 Inter- and intra-observer differences in measurements of coronary cross-area were tested by linear regression analysis and Bland-Altman plots. A Student’s t-test or Mann-Whitney U-test was used to compare the data between the patients with FFR ≤ 0.80 (FFR-positive group) and those with FFR > 0.80 groups (FFR-negative group) in accordance with the data distribution pattern. The Kolmogorov-Smirnov test and histograms were used to determine whether the data were normally distributed. The homogeneity of variance was checked using the F-test. Chi-square tests with 2×2 or m × n tables and two-tailed tests for categorical variables were used to compare the two groups or ≥ three groups when appropriate. Correlation analysis was used to analyze the relationships between the actual FFR values and continuous variables, including percent-cross area severity. Simple and multivariate regression analyses were employed to evaluate the relationship between these factors and FFR. ROC curve analysis was used to distinguish between FFR-positive and FFR-negative groups. The AUC and optimum cutoff level were determined using ROC curve analysis to evaluate the discriminant power ability. Although the number of patients was small and multivariate analysis may have had low accuracy, an ROC curve using propensity scores derived from multiple logistic regression analysis was used as a reference. Before ROC analysis, multiple linear regression analysis was performed with actual FFR values as independent variables to evaluate the correlation of the factors with FFR values. Based on the results, the scores were selected for use in the ROC analysis. Data are presented as mean ± one standard deviation (SD) or as median with 25th and 75th percentiles. Statistical significance was set at p < 0.05. Results Inter- and intra-observer differences Correlation analysis showed a correlation coefficient of 0.99 for both intra- and inter-observer differences. Linear regression analysis demonstrated that the regression coefficient and intercept were 0.98 and 0.42, respectively, in intra-observer differences. Similarly, a regression coefficient and intercept of 0.96 and 0.08, respectively, were obtained for inter-observer differences. Bland-Altman plots showed good agreement between the first and second observations and between one examiner’s measurement and another examiner’s measurement. In both intra- and inter-observer differences, all differences between the two measurements were located within 1.96 SD of differences in Bland-Altman plots. Patients’ clinical characteristics Table 1 summarizes the results of the comparison of patient clinical characteristics between the FFR-positive and FFR-negative groups. There were no significant differences in the clinical characteristics between the two groups. Univariate analysis for angiographic measurements Table 2 summarizes the results of angiographic measurements. The FFR was higher in the FFR-positive patients than in the FFR-negative patients. FFR-positive patients showed a significantly lower percentage of cross-sectional area stenosis, indicating higher stenosis, than that in FFR-negative patients. The actual stenosis length tended to be longer in FFR-positive patients than in FFR-negative patients. Simple correlation analysis revealed that the percent of cross-sectional area stenosis and grades of irregularity of stenosis were significantly correlated with the FFR. Other angiographic factors did not correlate with the actual FFR values. Multivariate analysis for angiographic measurements The results of multiple regression analysis with the actual FFR value as the independent variable and angiographic factors as the dependent variables to assess the univariate analysis are presented in Table 3. Among the factors examined, only cross-sectional area stenosis severity significantly correlated with the FFR. Receiver operating characteristic curve analysis Fig. 1 shows the ROC curve analysis used to distinguish between the FFR-positive and FFR-negative groups. Power analysis showed that detecting an AUC of 0.95 in ROC analysis required a sample size of n >10 in the FFR-positive and FFR-negative groups to obtain a statistical power of 0.95 with α=0.01. Therefore, the number of FFR-positive and FFP-negative patients was sufficient to detect an AUC of 0.95. The AUC results are presented in Fig. 1 and summarized in Table 4. AUC demonstrated that the percent cross-sectional area stenosis showed high accuracy for distinguishing FFR-positive patients from FFR-negative patients with a sensitivity of 88% and specificity of 93% at a cutoff value of 50%. When the analysis was performed only for left anterior descending artery lesions, an identical or slightly superior AUC was obtained. Additionally, ROC analysis of stenosis length and irregularity, in addition to percent cross-area stenosis, was performed using propensity scores derived from multiple logistic regression analysis. The results did not show a significant increase in AUC compared with that obtained by percent cross-sectional area stenosis. Discussion The major findings of the present study were as follows: 1) cross-sectional area stenosis severity, as measured by coronary CT, was significantly correlated with FFR, and 2) cross-sectional area reduction demonstrated a high AUC that distinguished FFR-positive patients from FFR-negative patients. Significant relationships between morphological coronary stenosis grades and coronary flow reserves have been well demonstrated experimentally in dogs. 13, 14 Clinically, there have been many clinical studies that evaluated the effect of the severity of coronary stenosis on the coronary flow reserve. One study examined coronary flow reserve using digital subtraction angiography, where the area of the coronary cross-section was determined by the square of the coronary diameter, instead of the planimetry tracing method. The study found significant relationships between coronary stenosis grade and impairment of flow reserve, which indicated the reversibility of ischemia. 15 A coronary stenosis of 50-70% was associated with a decrease in flow reserve, while stenosis greater than 70% severely decreased flow reserve. Another study examined coronary dimensional stenosis and exercise testing for the detection of reversible myocardial ischemia in 276 patients. Coronary stenosis was evaluated by a combination of simple visual assessment, caliper measurements, and digital measurements. This study found that 75% luminal diameter reduction is the best cutoff point for significant coronary stenosis. 16 A coronary diameter stenosis of 70-80%, associated with AUC 0.7-0.8, has been reported to distinguish a positive exercise test from a negative one. These results are in good agreement with the present results, although the target index was a positive exercise test, while ours was FFR-positive. These results support that the coronary stenosis grade plays an essential role in the impairment of the coronary flow reserve, which causes reversible myocardial ischemia. Among several methods available for detecting significant coronary stenosis, including exercise testing, digital subtraction angiography, positron emission tomography, and FFR, FFR has been demonstrated to be a reliable method for detecting significant pathophysiological coronary stenosis. 6, 8, 17 FFR is now widely used as the gold standard for significant lesion-specific coronary stenosis. FFR-guided PCI exhibited better clinical outcomes, including a reduction in death, nonfatal myocardial infarction, and repeat revascularization. 18 The use of FFR as a reliable index of significant coronary stenosis is thus appropriate for this study. Our study found that coronary cross-sectional area stenosis severity was highly correlated with FFR. In contrast, coronary artery luminal diameter stenosis was insufficiently correlated with the FFR. A previous study measuring the FFR using invasive coronary angiography and the coronary diameter luminal stenosis using coronary CT angiography (54-slice or dual-source) found that luminal diameter stenosis did not correlate well with the FFR. 19 Similarly, another study visually determined coronary luminal diameter stenosis in 1414 lesions and reported that coronary diameter correlated, albeit not accurately, with FFR. 5 Their study revealed that coronary luminal diameter stenosis was inaccurate in predicting FFR. To the best of our knowledge, there has only been one report that examined coronary area stenosis by coronary CT angiography and lesion ischemia by FFR. 20 The study reported a poor AUC of 0.66 for distinguishing lesions associated with ischemia from those without. The reasons for the difference in the AUC results were entirely obscured. The study was performed in two centers and used dual-source CT (Somatom Definition, Siemens, Forchheim, Germany) or 320-detector row CT (Aquilion One, Toshiba, Otawara, Japan). In contrast, the present study was performed in a single center and used a 128-slice detector-based spectral CT. These differences might account for the different results regarding AUC. Despite this, many studies have reported significant relationships between luminal diameter stenosis and reversible ischemia. Although luminal diameter stenosis was not sufficiently correlated with reversible coronary ischemia, a study found that an AUC of 0.7-0.8 and a cutoff point of 75% luminal diameter reduction may detect reversible ischemia, as supported by a stress test. Thus, the previously reported AUC of 0.66 from coronary area stenosis was considerably lower than established AUCs for diameter reduction. In contrast, our AUC findings were consistent with those of previous studies. 15, 16 Regarding the estimation of flow reserve at the site of the coronary stenotic lesion by coronary CT angiography, a computational flow kinetics model has been devised to predict FFR. 9, 10 A study analyzed 159 vessels using computational flow dynamics and reported an AUC of 0.90 for distinguishing FFR-positive from FFR-negative lesions. 21 Another study found a slightly lower AUC of 0.81 for the determination of FFR-positive lesions. 22 Accuracy, sensitivity, and specificity for discrimination of FFR ≤0.80 from FFR >0.80 were reported to be 73%, 90%, and 54% respectively. 22 The model requires many hypotheses and complicated equations, limiting its applications for estimating FFR. The results of multiple linear regression analysis in our study revealed that other factors, such as lesion irregularity and calcification, did not correlate with the FFR and did not improve the AUC. These results indicate that the severity of coronary cross-sectional stenosis is a major factor related to FFR. The present study had several limitations. First, although the power analysis showed sufficient numbers of FFR-positive and FFR-negative patients to detect an AUC of 0.95, further studies with an increased number of lesions are warranted to confirm the present results. In addition, the numbers of right coronary artery (RCA) and left circumflex artery (LCx) lesions were small. Statistically, the findings for RCA and LCx were not outliers, but an increase in the number of RCA and LCx lesions would further confirm our results. Third, the present study did not analyze complex bifurcation lesions. Studies on these lesions will be the next step in the present study. In conclusion, coronary cross-sectional stenosis severity determined digitally from coronary CT angiography can distinguish FFR-positive from FFR-negative lesions at a cutoff value of 50% with high sensitivity (0.882) and specificity (0.933) in non-complex stenosis. Declarations Acknowledgments: None. Disclosure: There are no conflicts of interest in connection with the present study. Funding source: This research did not receive any specific grants from funding agencies in the public, commercial, or not-for-profit sectors. Author contributions All authors meet the criteria for authorship. Contribution of each author to the four criteria of contribution noted below was as follows: T.K. contributed to 1), 2), 3), and 4). S.Ku. contributed to 1), 2), 3), and 4). T.T. contributed to 1), 3), and 4). T.A. contributed to 1), 3), and 4). H.K. contributed to 2) and 3). S.H. contributed to 3) and 4). H.Y. contributed to 3) and 4). T.M. contributed to 3) and 4). S.Ka. contributed to 2), 3), and 4). M.M. contributed to 1), 2), 3), and 4). Criteria of author contribution: 1. Made substantial contributions to the conception and design, acquisition of data, or analysis and interpretation of data. 2. Participated in drafting the article or revising it critically for important intellectual content. 3. Gave final approval of the version to be published. 4. Agreed to be accountable for all aspects of the work to ensure that questions related to the accuracy or integrity of any part of the work were appropriately investigated and resolved. Data availability statement Data supporting the findings of this study are available from the corresponding author, S. K., upon reasonable request. Ethics approval The examination and analytical procedures adhered to the principles of the Declaration of Helsinki and were approved by the Institutional Ethics Committee for Human Research of the Okayama Heart Clinic (ID, TK1). Written informed consent for the use of data without personally identifiable information was obtained from all patients. References Hoole, S.P., Bambrough, P. Recent advances in percutaneous coronary intervention. Heart. 2020;106:1380–6. Al-Lamee, R.K., Nowbar, A.N., Francis, D.P. Percutaneous coronary intervention for stable coronary artery disease. Heart. 2019;105:11–9. Uren, N.G., Melin, J.A., De Bruyne, B., Wijns, W., Baudhuin, T., Camici, P.G. Relation between myocardial blood flow and the severity of coronary-artery stenosis. N Engl J Med. 1994;330:1782–8. Shaw, L.J., et al. Optimal medical therapy with or without percutaneous coronary intervention to reduce ischemic burden: results from the Clinical Outcomes Utilizing Revascularization and Aggressive Drug Evaluation (COURAGE) trial nuclear substudy. Circulation. 2008;117:1283–91. Tonino, P.A., et al. Angiographic versus functional severity of coronary artery stenoses in the FAME study fractional flow reserve versus angiography in multivessel evaluation. J Am Coll Cardiol. 2010;55:2816–21. Pijls, N.H., et al. Measurement of fractional flow reserve to assess the functional severity of coronary-artery stenoses. N Engl J Med. 1996;334:1703–8. De Bruyne, B., et al. Fractional flow reserve in patients with prior myocardial infarction. Circulation. 2001;104:157–62. Pijls, N.H., et al. Fractional flow reserve. A useful index to evaluate the influence of an epicardial coronary stenosis on myocardial blood flow. Circulation. 1995;92:3183–93. Taylor, C.A., Fonte, T.A., Min, J.K. Computational fluid dynamics applied to cardiac computed tomography for noninvasive quantification of fractional flow reserve: scientific basis. J Am Coll Cardiol. 2013;61:2233–41. Min, J.K., et al. Diagnostic accuracy of fractional flow reserve from anatomic CT angiography. JAMA. 2012;308:1237–45. Kanda, Y. Investigation of the freely available easy-to-use software 'EZR' for medical statistics. Bone Marrow Transplant. 2013;48:452–8. Faul, F., Erdfelder, E., Buchner, A., Lang, A.G. Statistical power analyses using G*Power 3.1: tests for correlation and regression analyses. Behav Res Methods. 2009;41:1149–60. Gould, K.L., Lipscomb, K., Hamilton, G.W. Physiologic basis for assessing critical coronary stenosis. Instantaneous flow response and regional distribution during coronary hyperemia as measures of coronary flow reserve. Am J Cardiol. 1974;33:87–94. Gould, K.L., Lipscomb, K. Effects of coronary stenoses on coronary flow reserve and resistance. Am J Cardiol. 1974;34:48–55. Zijlstra, F., van Ommeren, J., Reiber, J.H., Serruys, P.W. Does the quantitative assessment of coronary artery dimensions predict the physiologic significance of a coronary stenosis? Circulation. 1987;75:1154–61. Lipinski, M., Do, D., Morise, A., Froelicher, V. What percent luminal stenosis should be used to define angiographic coronary artery disease for noninvasive test evaluation? Ann Noninvasive Electrocardiol. 2002;7:98–105. Bartunek, J., Sys, S.U., Heyndrickx, G.R., Pijls, N.H., De Bruyne, B. Quantitative coronary angiography in predicting functional significance of stenoses in an unselected patient cohort. J Am Coll Cardiol. 1995;26:328–34. Tonino, P.A., et al. Fractional flow reserve versus angiography for guiding percutaneous coronary intervention. N Engl J Med. 2009;360:213–24. Meijboom, W.B., et al. Comprehensive assessment of coronary artery stenoses: computed tomography coronary angiography versus conventional coronary angiography and correlation with fractional flow reserve in patients with stable angina. J Am Coll Cardiol. 2008;52:636–43. Nakazato, R., et al. Aggregate plaque volume by coronary computed tomography angiography is superior and incremental to luminal narrowing for diagnosis of ischemic lesions of intermediate stenosis severity. J Am Coll Cardiol. 2013;62:460–7. Koo, B.K., et al. Diagnosis of ischemia-causing coronary stenoses by noninvasive fractional flow reserve computed from coronary computed tomographic angiograms. Results from the prospective multicenter DISCOVER-FLOW (Diagnosis of Ischemia-Causing Stenoses Obtained Via Noninvasive Fractional Flow Reserve) study. J Am Coll Cardiol. 2011;58:1989–97. Min, J.K., Kochar, M. Diagnostic accuracy of coronary computed tomography angiography in patients post-coronary artery bypass grafting. Indian Heart J. 2012;64:261–2. Tables Table 1. Patients' clinical characteristics Total FFR-positive FFR-negative p-value Number of patients 32 17 15 Age years 72±9 69±9 75±8 0.100 Female n (%) 7 : 22 6 : 11 1 : 11 0.187 Body mass index 24.1±3.6 24.5±3.5 23.8±3.7 0.585 Hypertension n (%) 21 (66) 9 (52) 10 (65) 0.362 Diabetes mellitus n (%) 9 (28) 6 (35) 3 (20) 0.197 Hyperlipidemia n (%) 19 (59) 10 (59) 9 (60) 0.535 Creatinine clearance ml/min 89±28 91 ± 28 80±21 0.455 FFR, functional flow reserve Table 2. Comparison between FFR-positive and FFR-negative groups Total FFR-negative FFR-positive p-value Number of patients 32 15 17 FFR 0.830±0.090 0.901±0.044 0.749±0.048 <0.0001 cross-area stenosis seerity 0.44±0.19 0.30±0.13 0.60 ±0.11 <0.0001 Stenosis lesion length (mm) 17.1±11.1 14.0±89 20.7±12.4 0.088 Irregularity of stenotic lesion; grades 0 : 1 : 2 7 : 19 : 6 1 : 10 : 4 6 : 9 : 2 0.142 Irregularity of pre-stenotic lesion; grades 0 : 1 : 2 16 : 15 : 1 7 : 7 : 1 9 : 8 : 0 0.854 Calcification of stenotic lesion; grades 0 : 1 : 2 : 3 : 4 11 : 10 : 6 : 4 : 1 7 : 3 : 3 : 2 :0 4 : 7 : 3 : 2 : 1 0.502 Correlation analysis Correlation coefficient p-value FFR vs. cross-sectional area stenosis -0.811 <0.00001 FFR vs. stenosis lesion lenghth -0.340 0.0569 FFR vs. irregularity of stenotic lesion -0.385 0.029 FFR vs. irregularity of pre-stenotic lesion -0.244 0.178 FFR vs. calcification of the lesion -0.085 0.643 FFR, functional flow reserve; Table 3. Results of mutiple linear regression analysis Independent variable Actual FFR value Partial regression coefficient SE of partial regression coefficient Standardized regression coefficient Partial correlation coefficient F value p-value Dependent variables % cross-sectional area stenosis -0.0036 0.0005 -0.7635 -0.8025 47.0300 <0.000001 Length of stenotic lesion -0.0001 0.0010 -0.0166 -0.0272 0.0190 0.8907 Irregularity of stenotic lesion -0.0219 0.0233 -0.1582 -0.1816 0.8870 0.3558 Irregularity of stenosis origin -0.0331 0.1911 -0.2095 -0.3215 2.9970 0.0953 Calcification of the lesion 0.0096 0.0110 0.1235 0.1694 0.7680 0.3887 Constant 1.0220 Multiple correlation coefficient: 0.7928, p<0.001 Table 4. Results of receiver operating characteristic curve analysis for distinguishing between FFR-positive and FFP-negative groups Patients Applied factor Scores or actual value AUC 95% confidence interval Cut-off value Sensitivity Specificity Number of patients All patients n=32 cross-sectional area stenosis actual value 0.976 0.938 - 1.000 0.500 0.882 0.933 Patients with LAD lesions n=26 cross-sectional area stenosis actual value 0.982 0.947 - 1.000 0.500 0.909 0.933 All patients n=32 cross-sectional area stenosis scored value 0.927 0.837- 1.000 2.000 0.882 0.933 Patients with LAD lesions n=26 cross-sectional area stenosis scored value 0.936 0.845 - 1.000 2.000 0.909 0.933 All patients n=32 cross-sectional area stenosis and stenosis length and irregularity actual value +scored value (irregularity) 0.980 0.939 - 1.000 0.713 1.000 0.933 Patients with LAD lesions n=26 cross-sectional area stenosis and stenosis length and irregularity actual value +scored value (irregularity) 0.982 0.941 - 1.000 0.478 0.909 1.000 FFR, functional flow reserve; LAD, left anterior descending cut-off value, 0.500 indicated 50% coronary cross-area reduction Additional Declarations No competing interests reported. Cite Share Download PDF Status: Published Journal Publication published 23 Jul, 2025 Read the published version in Scientific Reports → Version 1 posted Editorial decision: Revision requested 10 Dec, 2024 Reviews received at journal 17 Nov, 2024 Reviewers agreed at journal 31 Oct, 2024 Reviews received at journal 30 Aug, 2024 Reviewers agreed at journal 30 Aug, 2024 Reviewers invited by journal 25 Aug, 2024 Editor assigned by journal 23 Aug, 2024 Editor invited by journal 19 Jul, 2024 Submission checks completed at journal 11 Jun, 2024 First submitted to journal 08 Jun, 2024 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-4552080","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":313718217,"identity":"2885c26d-3bcf-4d7a-a82a-1cdb090e97cf","order_by":0,"name":"Takuto Koumoto","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAzklEQVRIiWNgGAWjYPACCTk2ZuYDIIYMsVpsjPnY2RJAWniI1ZKWOI+fxwDEIqyFv7078cPHnMOJbcw8n1/dqLHgYWA/fHQDPi0SZ85ulpy57bBxGzPvNuucY0CH8aSl3cCnxUAidxtQ8WFZkBbjHDagFgkeM6K0MAId9sw45x/xWtIUgVqYH+e2EaEF6hcbYzZmNjPm3D4JHjZCfuFv79344eM2CTn5/sOPP+d8q5PjZz98DK8WZMAmASaJVQ4CzB9IUT0KRsEoGAUjBwAAqt1BjzB1FnQAAAAASUVORK5CYII=","orcid":"","institution":"Okayama Heart Clinic","correspondingAuthor":true,"prefix":"","firstName":"Takuto","middleName":"","lastName":"Koumoto","suffix":""},{"id":313718218,"identity":"d1e606f3-48dc-440b-b6d3-b72f11faf6ae","order_by":1,"name":"Shozo Kusachi","email":"","orcid":"","institution":"Okayama Heart Clinic","correspondingAuthor":false,"prefix":"","firstName":"Shozo","middleName":"","lastName":"Kusachi","suffix":""},{"id":313718219,"identity":"305bde72-e1d1-4246-92fc-ad4cabda44a0","order_by":2,"name":"Takumi Tomiya","email":"","orcid":"","institution":"Okayama Heart Clinic","correspondingAuthor":false,"prefix":"","firstName":"Takumi","middleName":"","lastName":"Tomiya","suffix":""},{"id":313718220,"identity":"e616c01d-cad4-4fc0-acf8-ad762e9f5df8","order_by":3,"name":"Takuya Akagi","email":"","orcid":"","institution":"Okayama Heart Clinic","correspondingAuthor":false,"prefix":"","firstName":"Takuya","middleName":"","lastName":"Akagi","suffix":""},{"id":313718221,"identity":"222d072e-8274-4910-bdca-5ba515c4ab05","order_by":4,"name":"Hiroshi Kawamura","email":"","orcid":"","institution":"Okayama Heart Clinic","correspondingAuthor":false,"prefix":"","firstName":"Hiroshi","middleName":"","lastName":"Kawamura","suffix":""},{"id":313718222,"identity":"abbdd676-4ba8-44bb-b776-a03c6501f616","order_by":5,"name":"Satoshi Hirohata","email":"","orcid":"","institution":"Okayama University Graduate School of Health Sciences","correspondingAuthor":false,"prefix":"","firstName":"Satoshi","middleName":"","lastName":"Hirohata","suffix":""},{"id":313718223,"identity":"c995c3bb-c1ec-4044-ba82-028a82e20b48","order_by":6,"name":"Hirosuke Yamaji","email":"","orcid":"","institution":"Okayama Heart Clinic","correspondingAuthor":false,"prefix":"","firstName":"Hirosuke","middleName":"","lastName":"Yamaji","suffix":""},{"id":313718224,"identity":"6960b2d6-89ea-4cfd-bc46-8fe0f11d59dd","order_by":7,"name":"Takashi Murakami","email":"","orcid":"","institution":"Okayama Heart Clinic","correspondingAuthor":false,"prefix":"","firstName":"Takashi","middleName":"","lastName":"Murakami","suffix":""},{"id":313718225,"identity":"37bbc180-3163-41bf-9fe8-f549ce66cda9","order_by":8,"name":"Shigeshi Kamikawa","email":"","orcid":"","institution":"Okayama Heart Clinic","correspondingAuthor":false,"prefix":"","firstName":"Shigeshi","middleName":"","lastName":"Kamikawa","suffix":""},{"id":313718226,"identity":"5c39bdc3-2a2d-4efa-89cc-b643392c712e","order_by":9,"name":"Masaaki Murakami","email":"","orcid":"","institution":"Okayama Heart Clinic","correspondingAuthor":false,"prefix":"","firstName":"Masaaki","middleName":"","lastName":"Murakami","suffix":""}],"badges":[],"createdAt":"2024-06-09 00:53:16","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4552080/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4552080/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1038/s41598-025-11920-z","type":"published","date":"2025-07-23T15:57:44+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":59870288,"identity":"71810499-9f5e-4e3b-9e39-c5df52bb6926","added_by":"auto","created_at":"2024-07-08 16:58:17","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":51486,"visible":true,"origin":"","legend":"\u003cp\u003eReceiver operating characteristic (ROC) curve analysis for coronary cross-sectional area stenosis severity to distinguish FFR-positive from FFR-negative stenosis. The upper panel was obtained from all stenoses, and the lower panel was obtained from stenoses located in the left anterior descending coronary artery (LAD). Cutoff values for cross-sectional area reduction obtained by the ratio of the stenotic lesion to the non-stenotic lesion are presented in the corner of the curve. Thus, 0.500 indicated 50% stenosis. Numbers in parentheses indicate specificity and sensitivity. AUC, area under the curve.\u003c/p\u003e","description":"","filename":"KoumotoFFRCTFig1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4552080/v1/0148f675fed3b200021c3291.jpg"},{"id":87756713,"identity":"01ed045f-1c4e-44d5-9fa8-39ec149bed1b","added_by":"auto","created_at":"2025-07-28 16:08:03","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":851154,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4552080/v1/4470d7b3-18b4-45f2-b0b3-974998b296e5.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Coronary cross-sectional area stenosis severity determined by coronary CT highly correlated with coronary functional flow reserve: a pilot study","fulltext":[{"header":"Introduction","content":"\u003cp\u003ePercutaneous coronary intervention (PCI) is now widely used for coronary artery disease, particularly ischemic heart disease.\u003csup\u003e1, 2\u003c/sup\u003e Decisions relating to PCI require demonstration of reversible ischemia and examination of the extent of area perfused by the coronary artery distal to the stenotic culprit lesion. The relationship between coronary stenosis severity and ischemia has been extensively examined. A decrease in hyperemic flow after coronary occlusion has been demonstrated to reduce coronary flow reserve. This diminution in flow is most evident at hyperemic states and begins as early as 40% narrowing of vessel diameter, with more predictable reductions in hyperemic flow for stenoses\u0026thinsp;\u0026ge;\u0026thinsp;70%.\u003csup\u003e3\u003c/sup\u003e Another study reported that in patients with 70% stenosis, only 32% exhibited severe ischemia and 40% manifested no or mild ischemia according to myocardial perfusion scintigraphy.\u003csup\u003e4\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eCoronary diameter reduction is usually measured visually or using the caliper method; however, these methods are not accurate. Furthermore, luminal reduction does not accurately reflect the severity of coronary stenosis. Coronary stenosis is complicated as it is not concentric and is usually eccentric to some degree. The relationship between the grade of coronary diameter stenosis and myocardial ischemia is more complex, with ensuing studies demonstrating an unreliable relationship between stenosis and ischemia.\u003csup\u003e5\u003c/sup\u003e Previous studies did not demonstrate that diameter reduction is a reliable marker for reversible ischemia.\u003c/p\u003e \u003cp\u003eOn the other hand, fractional flow reserve (FFR) is used for determining reversible ischemia caused by the responsible stenotic lesion. FFR is an index of the physiological significance of coronary stenosis and is defined as the ratio of maximal blood flow in a stenotic artery to normal maximal flow.\u003csup\u003e6\u003c/sup\u003e FFR is the ratio of distal coronary pressure measured with a coronary pressure guidewire to aortic pressure measured simultaneously with the guiding catheter. The process of FFR of the FFR is easy. The FFR of the normal coronary artery was 1.0, and an FFR value of 0.80 or less identifies ischemia-causing coronary stenoses with an accuracy of more than 90%.\u003csup\u003e6\u0026ndash;8\u003c/sup\u003e Thus, FFR is the gold standard for determining physiologically significant coronary stenosis. However, the method used to measure FFR is invasive and requires intracoronary pressure measurement. To estimate the FFR non-invasively, a fluid dynamics model applied to coronary CT angiography has been attempted.\u003csup\u003e9\u003c/sup\u003e The model requires many hypotheses and employs complex equations.\u003csup\u003e10\u003c/sup\u003e The fluid dynamic model has its own limitations.\u003c/p\u003e \u003cp\u003eBased on these considerations, we refocused on the morphological analysis of coronary stenosis. We hypothesized that the severity of coronary cross-sectional stenosis may correlate with FFR. Although only one study has examined the relationship between cross-sectional area stenosis and FFR, it found a theoretically untenable poor relationship. The study focused on plaque volume, and different CT systems were used. No study has used detector-based spectral CT for cross-sectional area stenosis, which can provide high-quality images with sufficient resolution power. Accordingly, our study focused on analyzing the association of cross-sectional area stenosis severity and stenosis characteristics with FFR using 128-slice detector-based spectral CT.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003ePatients\u003c/h2\u003e \u003cp\u003eThis study was conducted at Okayama Heart Clinic. We analyzed 32 consecutive patients with stable coronary heart disease (CHD) who underwent coronary CT and FFR measurements using coronary angiography. Informed consent was obtained from each participant. An informed consent form outlined the objectives, advantages, disadvantages, and safety concerns of the study.\u003c/p\u003e \u003cp\u003eThe required minimal sample size was \u0026gt;\u0026thinsp;8 FFR-positive lesions and \u0026gt;\u0026thinsp;8 FFR-negative lesions to detect an area under the receiver operating characteristic (ROC) curve (AUC) of 0.90 with a power of 0.90 and a significance level of α\u0026thinsp;=\u0026thinsp;0.05 in ROC analysis.\u003c/p\u003e \u003cp\u003e All examinations and analytical procedures adhered to the principles of the Declaration of Helsinki 2000 and the study was approved by the Institutional Ethics Committee for Human Research of the Okayama Heart Clinic (approval number TK1). Written informed consent for the use of data without personally identifiable information was obtained from all patients.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003eFractional flow reserve measurements\u003c/h2\u003e \u003cp\u003eCoronary angiography was performed using a coronary angiography catheter (Good Tec HT\u0026trade;, Goodman, Nagoya, Japan) and a vascular introducer (Radifocus IIH, Terumo, Tokyo, Japan). FFR was defined as the ratio between the distal coronary pressure and aortic pressure, both measured simultaneously during maximal coronary hyperemia and obtained in accordance with established methods.\u003csup\u003e8\u003c/sup\u003e Coronary pressure was measured using a coronary pressure guidewire (OmniWire; Philips Japan, Tokyo, Japan). Maximal hyperemia was induced by a bolus administration of nicorandil (4 mg) into the intracoronary artery. Pullback coronary pressure recordings were performed to discriminate between focal and diffuse disease. The FFR was calculated by dividing the mean distal coronary pressure by the mean aortic pressure during hyperemia. The FFR was considered diagnostic of ischemia at a threshold of 0.80 or less.\u003csup\u003e10\u003c/sup\u003e\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eCoronary computed tomography scan protocol and cross-sectional area measurement\u003c/h2\u003e \u003cp\u003eCoronary CT angiography was performed using a 128-slice detector-based spectral CT system (Brilliance iCT SP; Philips Healthcare, Cleveland, OH, USA) and an automatic dual-head injector (Stellant DualFlow; Nihon MEDRAD K.K., Osaka, Japan). All patients received 0.6 mg of nitroglycerin spray (Myocor\u0026trade;, Astellas Pharma, Tokyo, Japan) and 2\u0026ndash;8 mg of propranolol (Inderal; AstraZeneca, London, UK) intravenously five minutes before the examination to reduce the heart rate when the heart rate was \u0026gt;\u0026thinsp;70 beats per minute, in the absence of contraindications. Contrast medium (Iopamidol\u0026trade; 370 mg iodine/ml; Bayer Yakuhin, Osaka, Japan) was intravenously administered at 4.5 ml/s depending on body weight (0.7 ml/kg), followed by 20% diluted contrast medium (30 ml). Imaging was initiated using a bolus-tracking method. The position of the reconstruction window within the cardiac cycle was individually optimized to minimize motion artifacts. Axial images of 0.8-mm slice thickness were reconstructed at 0.4-mm intervals using a multi-cycle reconstruction algorithm with a medium-smooth cardiac kernel (XCB). Coronary CT angiography was used to evaluate the alignment of the coronary arteries between slabs of data acquired during consecutive heart cycles. Images with coronary vessel discontinuity due to motion or arrhythmia were excluded from the study.\u003c/p\u003e \u003cp\u003eCoronary CT was performed using a CT workstation (Extended Brilliance Workspace; Philips Healthcare, Cleveland, OH, USA). The cross-sectional area of the coronary artery was measured by tracing it on a high-resolution display with a pen. Inter- and intra-observer differences in coronary cross-area measurements were checked in 10 randomly selected areas from stenotic and non-stenotic lesions. Percents cross-sectional area stenosis severity was calculated as follows: 100\u0026times;(A-B)/A, where A is the cross-sectional area at non-stenotic pre-stenosis and B is the cross-sectional area of the most severe stenotic lesion. The cross-sectional area stenosis was graded as follows: score 0, \u0026le;\u0026thinsp;40% stenosis; score 1, \u0026gt;\u0026thinsp;40% and \u0026le;\u0026thinsp;60% stenosis; score 2, \u0026gt;\u0026thinsp;40% and \u0026le;\u0026thinsp;60% stenosis; and score 3, \u0026ge;\u0026thinsp;60% stenosis. Both the actual and scored values of the percentage cross-sectional stenosis severity were used for statistical analysis.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003eExamination of other lesion characteristics\u003c/h2\u003e \u003cp\u003eIn addition to cross-sectional area stenosis, the correlation of length and irregularity of stenotic lesions, irregularity of pre-stenotic lesions, and calcification of the lesion with FFR was also examined. Irregularities were graded from 0 to 2. Calcification was graded from 0 to 4. Grading was conducted by referring to sample images of each grade, and when two observers did not agree on the grade, an additional observer checked, and grading was finalized. The actual length of the stenotic lesion was graded as follows: score 0, \u0026le;\u0026thinsp;10 mm; score 1, \u0026gt;\u0026thinsp;10 and \u0026le;\u0026thinsp;20 mm; score 3, \u0026gt;\u0026thinsp;20 and \u0026le;\u0026thinsp;40 mm; and score 5, \u0026gt;\u0026thinsp;40 mm.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003eStatistical analysis\u003c/h2\u003e \u003cp\u003eStatistical analyses were performed using R version 3.2.2, provided by the R Foundation for Statistics Computing (Vienna, Austria).\u003csup\u003e11\u003c/sup\u003e The power analysis for paired comparison and correlation analysis was conducted using G*Power 3.1.9.7.\u003csup\u003e12\u003c/sup\u003e Inter- and intra-observer differences in measurements of coronary cross-area were tested by linear regression analysis and Bland-Altman plots. A Student\u0026rsquo;s t-test or Mann-Whitney U-test was used to compare the data between the patients with FFR\u0026thinsp;\u0026le;\u0026thinsp;0.80 (FFR-positive group) and those with FFR\u0026thinsp;\u0026gt;\u0026thinsp;0.80 groups (FFR-negative group) in accordance with the data distribution pattern. The Kolmogorov-Smirnov test and histograms were used to determine whether the data were normally distributed. The homogeneity of variance was checked using the F-test. Chi-square tests with 2\u0026times;2 or m \u0026times; n tables and two-tailed tests for categorical variables were used to compare the two groups or \u0026ge;\u0026thinsp;three groups when appropriate. Correlation analysis was used to analyze the relationships between the actual FFR values and continuous variables, including percent-cross area severity. Simple and multivariate regression analyses were employed to evaluate the relationship between these factors and FFR. ROC curve analysis was used to distinguish between FFR-positive and FFR-negative groups. The AUC and optimum cutoff level were determined using ROC curve analysis to evaluate the discriminant power ability. Although the number of patients was small and multivariate analysis may have had low accuracy, an ROC curve using propensity scores derived from multiple logistic regression analysis was used as a reference. Before ROC analysis, multiple linear regression analysis was performed with actual FFR values as independent variables to evaluate the correlation of the factors with FFR values. Based on the results, the scores were selected for use in the ROC analysis. Data are presented as mean\u0026thinsp;\u0026plusmn;\u0026thinsp;one standard deviation (SD) or as median with 25th and 75th percentiles. Statistical significance was set at p\u0026thinsp;\u0026lt;\u0026thinsp;0.05.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003e\u003cstrong\u003eInter- and intra-observer differences\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eCorrelation analysis showed a correlation coefficient of 0.99 for both intra- and inter-observer differences. Linear regression analysis demonstrated that the regression coefficient and intercept were 0.98 and 0.42, respectively, in intra-observer differences. Similarly, a regression coefficient and intercept of 0.96 and 0.08, respectively, were obtained for inter-observer differences. Bland-Altman plots showed good agreement between the first and second observations and between one examiner\u0026rsquo;s measurement and another examiner\u0026rsquo;s measurement. In both intra- and inter-observer differences, all differences between the two measurements were located within 1.96 SD of differences in Bland-Altman plots. \u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ePatients\u0026rsquo; clinical characteristics\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTable 1 summarizes the results of the comparison of patient clinical characteristics between the FFR-positive and FFR-negative groups. There were no significant differences in the clinical characteristics between the two groups.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eUnivariate analysis for angiographic measurements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTable 2 summarizes the results of angiographic measurements. The FFR was higher in the FFR-positive patients than in the FFR-negative patients. FFR-positive patients showed a significantly lower percentage of cross-sectional area stenosis, indicating higher stenosis, than that in FFR-negative patients. The actual stenosis length tended to be longer in FFR-positive patients than in FFR-negative patients.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eSimple correlation analysis revealed that the percent of cross-sectional area stenosis and grades of irregularity of stenosis were significantly correlated with the FFR. Other angiographic factors did not correlate with the actual FFR values. \u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMultivariate analysis for angiographic measurements \u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe results of multiple regression analysis with the actual FFR value as the independent variable and angiographic factors as the dependent variables to assess the univariate analysis are presented in Table 3. Among the factors examined, only cross-sectional area stenosis severity significantly correlated with the FFR. \u0026nbsp; \u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eReceiver operating characteristic curve analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eFig. 1 shows the ROC curve analysis used to distinguish between the FFR-positive and FFR-negative groups. Power analysis showed that detecting an AUC of 0.95 in ROC analysis required a sample size of n \u0026gt;10 in the FFR-positive and FFR-negative groups to obtain a statistical power of 0.95 with \u0026alpha;=0.01. Therefore, the number of FFR-positive and FFP-negative patients was sufficient to detect an AUC of 0.95. The AUC results are presented in Fig. 1 and summarized in Table 4. AUC demonstrated that the percent cross-sectional area stenosis showed high accuracy for distinguishing FFR-positive patients from FFR-negative patients with a sensitivity of 88% and specificity of 93% at a cutoff value of 50%. When the analysis was performed only for left anterior descending artery lesions, an identical or slightly superior AUC was obtained. Additionally, ROC analysis of stenosis length and irregularity, in addition to percent cross-area stenosis, was performed using propensity scores derived from multiple logistic regression analysis. The results did not show a significant increase in AUC compared with that obtained by percent cross-sectional area stenosis.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThe major findings of the present study were as follows: 1) cross-sectional area stenosis severity, as measured by coronary CT, was significantly correlated with FFR, and 2) cross-sectional area reduction demonstrated a high AUC that distinguished FFR-positive patients from FFR-negative patients.\u003c/p\u003e\n\u003cp\u003eSignificant relationships between morphological coronary stenosis grades and coronary flow reserves have been well demonstrated experimentally in dogs.\u003csup\u003e13, 14\u003c/sup\u003e Clinically, there have been many clinical studies that evaluated the effect of the severity of coronary stenosis on the coronary flow reserve. One study examined coronary flow reserve using digital subtraction angiography, where the area of the coronary cross-section was determined by the square of the coronary diameter, instead of the planimetry tracing method. The study found significant relationships between coronary stenosis grade and impairment of flow reserve, which indicated the reversibility of ischemia.\u003csup\u003e15\u003c/sup\u003e A coronary stenosis of 50-70% was associated with a decrease in flow reserve, while stenosis greater than 70% severely decreased flow reserve. Another study examined coronary dimensional stenosis and exercise testing for the detection of reversible myocardial ischemia in 276 patients. Coronary stenosis was evaluated by a combination of simple visual assessment, caliper measurements, and digital measurements. This study found that 75% luminal diameter reduction is the best cutoff point for significant coronary stenosis.\u003csup\u003e16\u003c/sup\u003e A coronary diameter stenosis of 70-80%, associated with AUC 0.7-0.8, has been reported to distinguish a positive exercise test from a negative one. These results are in good agreement with the present results, although the target index was a positive exercise test, while ours was FFR-positive. These results support that the coronary stenosis grade plays an essential role in the impairment of the coronary flow reserve, which causes reversible myocardial ischemia.\u003c/p\u003e\n\u003cp\u003eAmong several methods available for detecting significant coronary stenosis, including exercise testing, digital subtraction angiography, positron emission tomography, and FFR, FFR has been demonstrated to be a reliable method for detecting significant pathophysiological coronary stenosis.\u003csup\u003e6, 8, 17\u003c/sup\u003e FFR is now widely used as the gold standard for significant lesion-specific coronary stenosis. FFR-guided PCI exhibited better clinical outcomes, including a reduction in death, nonfatal myocardial infarction, and repeat revascularization.\u003csup\u003e18\u003c/sup\u003e The use of FFR as a reliable index of significant coronary stenosis is thus appropriate for this study. \u003c/p\u003e\n\u003cp\u003eOur study found that coronary cross-sectional area stenosis severity was highly correlated with FFR. In contrast, coronary artery luminal diameter stenosis was insufficiently correlated with the FFR. A previous study measuring the FFR using invasive coronary angiography and the coronary diameter luminal stenosis using coronary CT angiography (54-slice or dual-source) found that luminal diameter stenosis did not correlate well with the FFR.\u003csup\u003e19\u003c/sup\u003e Similarly, another study visually determined coronary luminal diameter stenosis in 1414 lesions and reported that coronary diameter correlated, albeit not accurately, with FFR.\u003csup\u003e5\u003c/sup\u003e Their study revealed that coronary luminal diameter stenosis was inaccurate in predicting FFR.\u003c/p\u003e\n\u003cp\u003eTo the best of our knowledge, there has only been one report that examined coronary area stenosis by coronary CT angiography and lesion ischemia by FFR.\u003csup\u003e20\u003c/sup\u003e The study reported a poor AUC of 0.66 for distinguishing lesions associated with ischemia from those without. The reasons for the difference in the AUC results were entirely obscured. The study was performed in two centers and used dual-source CT (Somatom Definition, Siemens, Forchheim, Germany) or 320-detector row CT (Aquilion One, Toshiba, Otawara, Japan). In contrast, the present study was performed in a single center and used a 128-slice detector-based spectral CT. These differences might account for the different results regarding AUC. Despite this, many studies have reported significant relationships between luminal diameter stenosis and reversible ischemia. Although luminal diameter stenosis was not sufficiently correlated with reversible coronary ischemia, a study found that an AUC of 0.7-0.8 and a cutoff point of 75% luminal diameter reduction may detect reversible ischemia, as supported by a stress test. Thus, the previously reported AUC of 0.66 from coronary area stenosis was considerably lower than established AUCs for diameter reduction. In contrast, our AUC findings were consistent with those of previous studies.\u003csup\u003e15, 16\u003c/sup\u003e\u003c/p\u003e\n\u003cp\u003eRegarding the estimation of flow reserve at the site of the coronary stenotic lesion by coronary CT angiography, a computational flow kinetics model has been devised to predict FFR.\u003csup\u003e9, 10\u003c/sup\u003e A study analyzed 159 vessels using computational flow dynamics and reported an AUC of 0.90 for distinguishing FFR-positive from FFR-negative lesions.\u003csup\u003e21\u003c/sup\u003e Another study found a slightly lower AUC of 0.81 for the determination of FFR-positive lesions.\u003csup\u003e22\u003c/sup\u003e Accuracy, sensitivity, and specificity for discrimination of FFR \u0026le;0.80 from FFR \u0026gt;0.80 were reported to be 73%, 90%, and 54% respectively.\u003csup\u003e22\u003c/sup\u003e The model requires many hypotheses and complicated equations, limiting its applications for estimating FFR. The results of multiple linear regression analysis in our study revealed that other factors, such as lesion irregularity and calcification, did not correlate with the FFR and did not improve the AUC. These results indicate that the severity of coronary cross-sectional stenosis is a major factor related to FFR. \u003c/p\u003e\n\u003cp\u003eThe present study had several limitations. First, although the power analysis showed sufficient numbers of FFR-positive and FFR-negative patients to detect an AUC of 0.95, further studies with an increased number of lesions are warranted to confirm the present results. In addition, the numbers of right coronary artery (RCA) and left circumflex artery (LCx) lesions were small. Statistically, the findings for RCA and LCx were not outliers, but an increase in the number of RCA and LCx lesions would further confirm our results. Third, the present study did not analyze complex bifurcation lesions. Studies on these lesions will be the next step in the present study.\u003c/p\u003e\n\u003cp\u003eIn conclusion, coronary cross-sectional stenosis severity determined digitally from coronary CT angiography can distinguish FFR-positive from FFR-negative lesions at a cutoff value of 50% with high sensitivity (0.882) and specificity (0.933) in non-complex stenosis.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgments: \u003c/strong\u003eNone.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDisclosure: \u003c/strong\u003eThere are no conflicts of interest in connection with the present study. \u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding source: \u003c/strong\u003eThis research did not receive any specific grants from funding agencies in the public, commercial, or not-for-profit sectors.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll authors meet the criteria for authorship.\u003c/p\u003e\n\u003cp\u003eContribution of each author to the four criteria of contribution noted below was as follows:\u003c/p\u003e\n\u003cp\u003eT.K. contributed to 1), 2), 3), and 4).\u003c/p\u003e\n\u003cp\u003eS.Ku. contributed to 1), 2), 3), and 4).\u003c/p\u003e\n\u003cp\u003eT.T. contributed to 1), 3), and 4).\u003c/p\u003e\n\u003cp\u003eT.A. contributed to 1), 3), and 4).\u003c/p\u003e\n\u003cp\u003eH.K. contributed to 2) and 3).\u003c/p\u003e\n\u003cp\u003eS.H. contributed to 3) and 4).\u003c/p\u003e\n\u003cp\u003eH.Y. contributed to 3) and 4).\u003c/p\u003e\n\u003cp\u003eT.M. contributed to 3) and 4).\u003c/p\u003e\n\u003cp\u003eS.Ka. contributed to 2), 3), and 4).\u003c/p\u003e\n\u003cp\u003eM.M. contributed to 1), 2), 3), and 4).\u003c/p\u003e\n\n\u003cp\u003eCriteria of author contribution:\u003c/p\u003e\n\u003cp\u003e1. Made substantial contributions to the conception and design, acquisition of data, or analysis and interpretation of data.\u003c/p\u003e\n\u003cp\u003e2. Participated in drafting the article or revising it critically for important intellectual content.\u003c/p\u003e\n\u003cp\u003e3. Gave final approval of the version to be published.\u003c/p\u003e\n\u003cp\u003e4. Agreed to be accountable for all aspects of the work to ensure that questions related to the accuracy or integrity of any part of the work were appropriately investigated and resolved.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData availability statement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eData supporting the findings of this study are available from the corresponding author, S. K., upon reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics approval \u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe examination and analytical procedures adhered to the principles of the Declaration of Helsinki and were approved by the Institutional Ethics Committee for Human Research of the Okayama Heart Clinic (ID, TK1). Written informed consent for the use of data without personally identifiable information was obtained from all patients. \u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eHoole, S.P., Bambrough, P. Recent advances in percutaneous coronary intervention. Heart. 2020;106:1380\u0026ndash;6.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAl-Lamee, R.K., Nowbar, A.N., Francis, D.P. Percutaneous coronary intervention for stable coronary artery disease. Heart. 2019;105:11\u0026ndash;9.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eUren, N.G., Melin, J.A., De Bruyne, B., Wijns, W., Baudhuin, T., Camici, P.G. Relation between myocardial blood flow and the severity of coronary-artery stenosis. N Engl J Med. 1994;330:1782\u0026ndash;8.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eShaw, L.J., et al. Optimal medical therapy with or without percutaneous coronary intervention to reduce ischemic burden: results from the Clinical Outcomes Utilizing Revascularization and Aggressive Drug Evaluation (COURAGE) trial nuclear substudy. Circulation. 2008;117:1283\u0026ndash;91.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTonino, P.A., et al. Angiographic versus functional severity of coronary artery stenoses in the FAME study fractional flow reserve versus angiography in multivessel evaluation. J Am Coll Cardiol. 2010;55:2816\u0026ndash;21.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePijls, N.H., et al. Measurement of fractional flow reserve to assess the functional severity of coronary-artery stenoses. N Engl J Med. 1996;334:1703\u0026ndash;8.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDe Bruyne, B., et al. Fractional flow reserve in patients with prior myocardial infarction. Circulation. 2001;104:157\u0026ndash;62.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePijls, N.H., et al. Fractional flow reserve. A useful index to evaluate the influence of an epicardial coronary stenosis on myocardial blood flow. Circulation. 1995;92:3183\u0026ndash;93.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTaylor, C.A., Fonte, T.A., Min, J.K. Computational fluid dynamics applied to cardiac computed tomography for noninvasive quantification of fractional flow reserve: scientific basis. J Am Coll Cardiol. 2013;61:2233\u0026ndash;41.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMin, J.K., et al. Diagnostic accuracy of fractional flow reserve from anatomic CT angiography. JAMA. 2012;308:1237\u0026ndash;45.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKanda, Y. Investigation of the freely available easy-to-use software 'EZR' for medical statistics. Bone Marrow Transplant. 2013;48:452\u0026ndash;8.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFaul, F., Erdfelder, E., Buchner, A., Lang, A.G. Statistical power analyses using G*Power 3.1: tests for correlation and regression analyses. Behav Res Methods. 2009;41:1149\u0026ndash;60.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGould, K.L., Lipscomb, K., Hamilton, G.W. Physiologic basis for assessing critical coronary stenosis. Instantaneous flow response and regional distribution during coronary hyperemia as measures of coronary flow reserve. Am J Cardiol. 1974;33:87\u0026ndash;94.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGould, K.L., Lipscomb, K. Effects of coronary stenoses on coronary flow reserve and resistance. Am J Cardiol. 1974;34:48\u0026ndash;55.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZijlstra, F., van Ommeren, J., Reiber, J.H., Serruys, P.W. Does the quantitative assessment of coronary artery dimensions predict the physiologic significance of a coronary stenosis? Circulation. 1987;75:1154\u0026ndash;61.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLipinski, M., Do, D., Morise, A., Froelicher, V. What percent luminal stenosis should be used to define angiographic coronary artery disease for noninvasive test evaluation? Ann Noninvasive Electrocardiol. 2002;7:98\u0026ndash;105.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBartunek, J., Sys, S.U., Heyndrickx, G.R., Pijls, N.H., De Bruyne, B. Quantitative coronary angiography in predicting functional significance of stenoses in an unselected patient cohort. J Am Coll Cardiol. 1995;26:328\u0026ndash;34.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTonino, P.A., et al. Fractional flow reserve versus angiography for guiding percutaneous coronary intervention. N Engl J Med. 2009;360:213\u0026ndash;24.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMeijboom, W.B., et al. Comprehensive assessment of coronary artery stenoses: computed tomography coronary angiography versus conventional coronary angiography and correlation with fractional flow reserve in patients with stable angina. J Am Coll Cardiol. 2008;52:636\u0026ndash;43.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eNakazato, R., et al. Aggregate plaque volume by coronary computed tomography angiography is superior and incremental to luminal narrowing for diagnosis of ischemic lesions of intermediate stenosis severity. J Am Coll Cardiol. 2013;62:460\u0026ndash;7.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKoo, B.K., et al. Diagnosis of ischemia-causing coronary stenoses by noninvasive fractional flow reserve computed from coronary computed tomographic angiograms. Results from the prospective multicenter DISCOVER-FLOW (Diagnosis of Ischemia-Causing Stenoses Obtained Via Noninvasive Fractional Flow Reserve) study. J Am Coll Cardiol. 2011;58:1989\u0026ndash;97.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMin, J.K., Kochar, M. Diagnostic accuracy of coronary computed tomography angiography in patients post-coronary artery bypass grafting. Indian Heart J. 2012;64:261\u0026ndash;2.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"},{"header":"Tables","content":"\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"573\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"87.43455497382199%\" colspan=\"6\" style=\"width: 99.8255%;\"\u003e\n \u003cp\u003eTable 1. Patients\u0026apos; clinical characteristics\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"27.399650959860384%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.69284467713787%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.041884816753926%\"\u003e\n \u003cp\u003eTotal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.801047120418847%\"\u003e\n \u003cp\u003eFFR-positive\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.49912739965096%\"\u003e\n \u003cp\u003eFFR-negative\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.565445026178011%\"\u003e\n \u003cp\u003ep-value\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"27.399650959860384%\"\u003e\n \u003cp\u003eNumber of patients\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.69284467713787%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"12.041884816753926%\"\u003e\n \u003cp\u003e32\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.801047120418847%\"\u003e\n \u003cp\u003e17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.49912739965096%\"\u003e\n \u003cp\u003e15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.565445026178011%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"27.399650959860384%\"\u003e\n \u003cp\u003eAge\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.69284467713787%\"\u003e\n \u003cp\u003eyears\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.041884816753926%\"\u003e\n \u003cp\u003e72\u0026plusmn;9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.801047120418847%\"\u003e\n \u003cp\u003e69\u0026plusmn;9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.49912739965096%\"\u003e\n \u003cp\u003e75\u0026plusmn;8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.565445026178011%\"\u003e\n \u003cp\u003e0.100\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"27.399650959860384%\"\u003e\n \u003cp\u003eFemale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.69284467713787%\"\u003e\n \u003cp\u003e \u0026nbsp;n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.041884816753926%\"\u003e\n \u003cp\u003e\u0026nbsp; 7 : 22\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.801047120418847%\"\u003e\n \u003cp\u003e\u0026nbsp; 6 \u0026nbsp;: 11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.49912739965096%\"\u003e\n \u003cp\u003e\u0026nbsp;1 \u0026nbsp;: \u0026nbsp;11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.565445026178011%\"\u003e\n \u003cp\u003e0.187\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"27.399650959860384%\"\u003e\n \u003cp\u003eBody mass index\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.69284467713787%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"12.041884816753926%\"\u003e\n \u003cp\u003e24.1\u0026plusmn;3.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.801047120418847%\"\u003e\n \u003cp\u003e24.5\u0026plusmn;3.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.49912739965096%\"\u003e\n \u003cp\u003e23.8\u0026plusmn;3.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.565445026178011%\"\u003e\n \u003cp\u003e0.585\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"27.399650959860384%\"\u003e\n \u003cp\u003eHypertension\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.69284467713787%\"\u003e\n \u003cp\u003en (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.041884816753926%\"\u003e\n \u003cp\u003e21 (66)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.801047120418847%\"\u003e\n \u003cp\u003e9 (52)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.49912739965096%\"\u003e\n \u003cp\u003e10 (65)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.565445026178011%\"\u003e\n \u003cp\u003e0.362\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"27.399650959860384%\"\u003e\n \u003cp\u003eDiabetes mellitus\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.69284467713787%\"\u003e\n \u003cp\u003en (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.041884816753926%\"\u003e\n \u003cp\u003e9 (28)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.801047120418847%\"\u003e\n \u003cp\u003e6 (35)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.49912739965096%\"\u003e\n \u003cp\u003e3 (20)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.565445026178011%\"\u003e\n \u003cp\u003e0.197\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"27.399650959860384%\"\u003e\n \u003cp\u003eHyperlipidemia\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.69284467713787%\"\u003e\n \u003cp\u003e\u0026nbsp;n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.041884816753926%\"\u003e\n \u003cp\u003e19 (59)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.801047120418847%\"\u003e\n \u003cp\u003e10 (59)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.49912739965096%\"\u003e\n \u003cp\u003e9 (60)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.565445026178011%\"\u003e\n \u003cp\u003e0.535\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"27.399650959860384%\"\u003e\n \u003cp\u003eCreatinine clearance\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.69284467713787%\"\u003e\n \u003cp\u003eml/min\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.041884816753926%\"\u003e\n \u003cp\u003e89\u0026plusmn;28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.801047120418847%\"\u003e\n \u003cp\u003e91 \u0026plusmn; 28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.49912739965096%\"\u003e\n \u003cp\u003e80\u0026plusmn;21\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.565445026178011%\"\u003e\n \u003cp\u003e0.455\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"100%\" colspan=\"6\"\u003e\n \u003cp\u003eFFR, functional flow reserve\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"905\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"52.86975717439294%\" colspan=\"5\" style=\"width: 99.8654%;\"\u003e\n \u003cp\u003eTable 2. Comparison between FFR-positive and FFR-negative groups \u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"52.86975717439294%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.803532008830022%\"\u003e\n \u003cp\u003eTotal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.362030905077262%\"\u003e\n \u003cp\u003eFFR-negative\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.686534216335541%\"\u003e\n \u003cp\u003eFFR-positive\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.278145695364238%\"\u003e\n \u003cp\u003ep-value\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"52.86975717439294%\"\u003e\n \u003cp\u003eNumber of patients\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.803532008830022%\"\u003e\n \u003cp\u003e32\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.362030905077262%\"\u003e\n \u003cp\u003e15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.686534216335541%\"\u003e\n \u003cp\u003e17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.278145695364238%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"52.86975717439294%\"\u003e\n \u003cp\u003eFFR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.803532008830022%\"\u003e\n \u003cp\u003e0.830\u0026plusmn;0.090\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.362030905077262%\"\u003e\n \u003cp\u003e0.901\u0026plusmn;0.044\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.686534216335541%\"\u003e\n \u003cp\u003e0.749\u0026plusmn;0.048\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.278145695364238%\"\u003e\n \u003cp\u003e\u0026lt;0.0001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"52.86975717439294%\"\u003e\n \u003cp\u003ecross-area stenosis seerity\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.803532008830022%\"\u003e\n \u003cp\u003e0.44\u0026plusmn;0.19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.362030905077262%\"\u003e\n \u003cp\u003e\u0026nbsp;0.30\u0026plusmn;0.13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.686534216335541%\"\u003e\n \u003cp\u003e0.60 \u0026plusmn;0.11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.278145695364238%\"\u003e\n \u003cp\u003e\u0026lt;0.0001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"52.86975717439294%\"\u003e\n \u003cp\u003eStenosis lesion length (mm)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.803532008830022%\"\u003e\n \u003cp\u003e17.1\u0026plusmn;11.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.362030905077262%\"\u003e\n \u003cp\u003e14.0\u0026plusmn;89\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.686534216335541%\"\u003e\n \u003cp\u003e20.7\u0026plusmn;12.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.278145695364238%\"\u003e\n \u003cp\u003e0.088\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"52.86975717439294%\"\u003e\n \u003cp\u003eIrregularity of stenotic lesion; \u0026nbsp; \u0026nbsp; grades 0 : 1 : 2\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.803532008830022%\"\u003e\n \u003cp\u003e\u0026nbsp;7 : 19 : 6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.362030905077262%\"\u003e\n \u003cp\u003e\u0026nbsp;1 : 10 : 4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.686534216335541%\"\u003e\n \u003cp\u003e\u0026nbsp; 6 : 9 : 2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.278145695364238%\"\u003e\n \u003cp\u003e0.142\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"52.86975717439294%\"\u003e\n \u003cp\u003eIrregularity of pre-stenotic lesion; \u0026nbsp; \u0026nbsp; grades 0 : 1 : 2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.803532008830022%\"\u003e\n \u003cp\u003e\u0026nbsp;16 : 15 : 1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.362030905077262%\"\u003e\n \u003cp\u003e\u0026nbsp;7 : 7 : 1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.686534216335541%\"\u003e\n \u003cp\u003e\u0026nbsp;9 : 8 : 0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.278145695364238%\"\u003e\n \u003cp\u003e0.854\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"52.86975717439294%\"\u003e\n \u003cp\u003eCalcification of stenotic lesion; grades 0 : 1 : 2 : 3 : 4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.803532008830022%\"\u003e\n \u003cp\u003e\u0026nbsp;11 : 10 : 6 : 4 : 1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.362030905077262%\"\u003e\n \u003cp\u003e7 : 3 : 3 : 2 :0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.686534216335541%\"\u003e\n \u003cp\u003e\u0026nbsp;4 : 7 : 3 : 2 : \u0026nbsp;1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.278145695364238%\"\u003e\n \u003cp\u003e0.502\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"52.86975717439294%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"12.803532008830022%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"12.362030905077262%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"13.686534216335541%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"8.278145695364238%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"52.86975717439294%\"\u003e\n \u003cp\u003eCorrelation analysis\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.803532008830022%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"12.362030905077262%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"21.96467991169978%\" colspan=\"2\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"52.86975717439294%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.165562913907284%\" colspan=\"2\"\u003e\n \u003cp\u003eCorrelation coefficient\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.96467991169978%\" colspan=\"2\"\u003e\n \u003cp\u003ep-value\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"52.86975717439294%\"\u003e\n \u003cp\u003eFFR vs. cross-sectional area stenosis\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.165562913907284%\" colspan=\"2\"\u003e\n \u003cp\u003e-0.811\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.96467991169978%\" colspan=\"2\"\u003e\n \u003cp\u003e\u0026lt;0.00001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"52.86975717439294%\"\u003e\n \u003cp\u003eFFR vs. stenosis lesion lenghth \u0026nbsp; \u0026nbsp;\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.165562913907284%\" colspan=\"2\"\u003e\n \u003cp\u003e-0.340\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.96467991169978%\" colspan=\"2\"\u003e\n \u003cp\u003e0.0569\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"52.86975717439294%\"\u003e\n \u003cp\u003eFFR vs. irregularity of stenotic lesion\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.165562913907284%\" colspan=\"2\"\u003e\n \u003cp\u003e-0.385\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.96467991169978%\" colspan=\"2\"\u003e\n \u003cp\u003e0.029\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"52.86975717439294%\"\u003e\n \u003cp\u003eFFR vs. irregularity of pre-stenotic lesion\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.165562913907284%\" colspan=\"2\"\u003e\n \u003cp\u003e-0.244\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.96467991169978%\" colspan=\"2\"\u003e\n \u003cp\u003e0.178\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"52.86975717439294%\"\u003e\n \u003cp\u003eFFR vs. calcification of the lesion\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.165562913907284%\" colspan=\"2\"\u003e\n \u003cp\u003e-0.085\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.96467991169978%\" colspan=\"2\"\u003e\n \u003cp\u003e0.643\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"100%\" colspan=\"5\"\u003e\n \u003cp\u003eFFR, functional flow reserve;\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"908\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"100%\" colspan=\"7\"\u003e\n \u003cp\u003eTable 3. Results of mutiple linear regression analysis\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"24.035281146637267%\"\u003e\n \u003cp\u003eIndependent variable\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.458654906284455%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.648291069459756%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.553472987872105%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.458654906284455%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.474090407938258%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.371554575523705%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"24.035281146637267%\"\u003e\n \u003cp\u003eActual FFR value\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.458654906284455%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"16.648291069459756%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"14.553472987872105%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"12.458654906284455%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"10.474090407938258%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"9.371554575523705%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"24.035281146637267%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"12.458654906284455%\"\u003e\n \u003cp\u003ePartial regression coefficient\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.648291069459756%\"\u003e\n \u003cp\u003eSE of partial regression coefficient\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.553472987872105%\"\u003e\n \u003cp\u003eStandardized regression coefficient\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.458654906284455%\"\u003e\n \u003cp\u003ePartial correlation coefficient\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.474090407938258%\"\u003e\n \u003cp\u003eF value\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.371554575523705%\"\u003e\n \u003cp\u003ep-value\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"24.035281146637267%\"\u003e\n \u003cp\u003eDependent variables\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.458654906284455%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"16.648291069459756%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"14.553472987872105%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"12.458654906284455%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"10.474090407938258%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"9.371554575523705%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"24.035281146637267%\"\u003e\n \u003cp\u003e% cross-sectional area stenosis\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.458654906284455%\"\u003e\n \u003cp\u003e-0.0036\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.648291069459756%\"\u003e\n \u003cp\u003e0.0005\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.553472987872105%\"\u003e\n \u003cp\u003e-0.7635\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.458654906284455%\"\u003e\n \u003cp\u003e-0.8025\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.474090407938258%\"\u003e\n \u003cp\u003e47.0300\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.371554575523705%\"\u003e\n \u003cp\u003e\u0026lt;0.000001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"24.035281146637267%\"\u003e\n \u003cp\u003eLength of stenotic lesion\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.458654906284455%\"\u003e\n \u003cp\u003e-0.0001\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.648291069459756%\"\u003e\n \u003cp\u003e0.0010\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.553472987872105%\"\u003e\n \u003cp\u003e-0.0166\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.458654906284455%\"\u003e\n \u003cp\u003e-0.0272\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.474090407938258%\"\u003e\n \u003cp\u003e0.0190\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.371554575523705%\"\u003e\n \u003cp\u003e0.8907\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"24.035281146637267%\"\u003e\n \u003cp\u003eIrregularity of stenotic lesion\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.458654906284455%\"\u003e\n \u003cp\u003e-0.0219\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.648291069459756%\"\u003e\n \u003cp\u003e0.0233\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.553472987872105%\"\u003e\n \u003cp\u003e-0.1582\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.458654906284455%\"\u003e\n \u003cp\u003e-0.1816\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.474090407938258%\"\u003e\n \u003cp\u003e0.8870\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.371554575523705%\"\u003e\n \u003cp\u003e0.3558\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"24.035281146637267%\"\u003e\n \u003cp\u003eIrregularity of stenosis origin\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.458654906284455%\"\u003e\n \u003cp\u003e-0.0331\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.648291069459756%\"\u003e\n \u003cp\u003e0.1911\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.553472987872105%\"\u003e\n \u003cp\u003e-0.2095\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.458654906284455%\"\u003e\n \u003cp\u003e-0.3215\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.474090407938258%\"\u003e\n \u003cp\u003e2.9970\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.371554575523705%\"\u003e\n \u003cp\u003e0.0953\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"24.035281146637267%\"\u003e\n \u003cp\u003eCalcification of the lesion\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.458654906284455%\"\u003e\n \u003cp\u003e0.0096\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.648291069459756%\"\u003e\n \u003cp\u003e0.0110\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.553472987872105%\"\u003e\n \u003cp\u003e0.1235\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.458654906284455%\"\u003e\n \u003cp\u003e0.1694\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.474090407938258%\"\u003e\n \u003cp\u003e0.7680\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.371554575523705%\"\u003e\n \u003cp\u003e0.3887\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"24.035281146637267%\"\u003e\n \u003cp\u003eConstant\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.458654906284455%\"\u003e\n \u003cp\u003e1.0220\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.648291069459756%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.553472987872105%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.458654906284455%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.474090407938258%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.371554575523705%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"100%\" colspan=\"7\"\u003e\n \u003cp\u003eMultiple correlation coefficient: 0.7928, p\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"993\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"100%\" colspan=\"9\"\u003e\n \u003cp\u003e\u003cstrong\u003eTable 4. Results of receiver operating characteristic curve analysis for distinguishing between FFR-positive and FFP-negative groups\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.303822937625753%\"\u003e\n \u003cp\u003ePatients\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.148893360160965%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.824949698189133%\"\u003e\n \u003cp\u003eApplied factor\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.179074446680081%\"\u003e\n \u003cp\u003eScores or actual value\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.929577464788732%\"\u003e\n \u003cp\u003eAUC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.770623742454728%\"\u003e\n \u003cp\u003e95% confidence interval\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.740442655935614%\"\u003e\n \u003cp\u003eCut-off value\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.551307847082494%\"\u003e\n \u003cp\u003eSensitivity\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.551307847082494%\"\u003e\n \u003cp\u003eSpecificity\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.303822937625753%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.148893360160965%\"\u003e\n \u003cp\u003eNumber of patients\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.824949698189133%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.179074446680081%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.929577464788732%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.770623742454728%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.740442655935614%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.551307847082494%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.551307847082494%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.303822937625753%\"\u003e\n \u003cp\u003eAll patients\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.148893360160965%\"\u003e\n \u003cp\u003en=32\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.824949698189133%\"\u003e\n \u003cp\u003ecross-sectional area stenosis\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.179074446680081%\"\u003e\n \u003cp\u003eactual value\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.929577464788732%\"\u003e\n \u003cp\u003e0.976\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.770623742454728%\"\u003e\n \u003cp\u003e0.938 - 1.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.740442655935614%\"\u003e\n \u003cp\u003e0.500\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.551307847082494%\"\u003e\n \u003cp\u003e0.882\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.551307847082494%\"\u003e\n \u003cp\u003e0.933\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.303822937625753%\"\u003e\n \u003cp\u003ePatients with LAD lesions\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.148893360160965%\"\u003e\n \u003cp\u003en=26\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.824949698189133%\"\u003e\n \u003cp\u003ecross-sectional area stenosis\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.179074446680081%\"\u003e\n \u003cp\u003eactual value\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.929577464788732%\"\u003e\n \u003cp\u003e0.982\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.770623742454728%\"\u003e\n \u003cp\u003e0.947 - 1.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.740442655935614%\"\u003e\n \u003cp\u003e0.500\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.551307847082494%\"\u003e\n \u003cp\u003e0.909\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.551307847082494%\"\u003e\n \u003cp\u003e0.933\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.303822937625753%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"8.148893360160965%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"20.824949698189133%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"13.179074446680081%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"4.929577464788732%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"11.770623742454728%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"6.740442655935614%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"8.551307847082494%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"8.551307847082494%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.303822937625753%\"\u003e\n \u003cp\u003eAll patients\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.148893360160965%\"\u003e\n \u003cp\u003en=32\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.824949698189133%\"\u003e\n \u003cp\u003ecross-sectional area stenosis\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.179074446680081%\"\u003e\n \u003cp\u003escored value\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.929577464788732%\"\u003e\n \u003cp\u003e0.927\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.770623742454728%\"\u003e\n \u003cp\u003e0.837- 1.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.740442655935614%\"\u003e\n \u003cp\u003e2.000\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.551307847082494%\"\u003e\n \u003cp\u003e0.882\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.551307847082494%\"\u003e\n \u003cp\u003e0.933\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.303822937625753%\"\u003e\n \u003cp\u003ePatients with LAD lesions\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.148893360160965%\"\u003e\n \u003cp\u003en=26\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.824949698189133%\"\u003e\n \u003cp\u003ecross-sectional area stenosis\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.179074446680081%\"\u003e\n \u003cp\u003escored value\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.929577464788732%\"\u003e\n \u003cp\u003e0.936\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.770623742454728%\"\u003e\n \u003cp\u003e0.845 - 1.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.740442655935614%\"\u003e\n \u003cp\u003e2.000\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.551307847082494%\"\u003e\n \u003cp\u003e0.909\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.551307847082494%\"\u003e\n \u003cp\u003e0.933\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.303822937625753%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"8.148893360160965%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"20.824949698189133%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"13.179074446680081%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"4.929577464788732%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"11.770623742454728%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"6.740442655935614%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"8.551307847082494%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"8.551307847082494%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.303822937625753%\"\u003e\n \u003cp\u003eAll patients\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.148893360160965%\"\u003e\n \u003cp\u003en=32\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.824949698189133%\"\u003e\n \u003cp\u003ecross-sectional area stenosis and stenosis length and irregularity\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.179074446680081%\"\u003e\n \u003cp\u003eactual value \u003c/p\u003e\n \u003cp\u003e+scored value (irregularity)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.929577464788732%\"\u003e\n \u003cp\u003e0.980\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.770623742454728%\"\u003e\n \u003cp\u003e\u0026nbsp;0.939 - 1.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.740442655935614%\"\u003e\n \u003cp\u003e0.713\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.551307847082494%\"\u003e\n \u003cp\u003e1.000\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.551307847082494%\"\u003e\n \u003cp\u003e0.933\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.303822937625753%\"\u003e\n \u003cp\u003ePatients with LAD lesions\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.148893360160965%\"\u003e\n \u003cp\u003en=26\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.824949698189133%\"\u003e\n \u003cp\u003e\u0026nbsp;cross-sectional area stenosis and stenosis length and irregularity\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.179074446680081%\"\u003e\n \u003cp\u003eactual value +scored value (irregularity)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.929577464788732%\"\u003e\n \u003cp\u003e0.982\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.770623742454728%\"\u003e\n \u003cp\u003e0.941 - 1.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.740442655935614%\"\u003e\n \u003cp\u003e0.478\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.551307847082494%\"\u003e\n \u003cp\u003e0.909\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.551307847082494%\"\u003e\n \u003cp\u003e1.000\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"100%\" colspan=\"9\"\u003e\n \u003cp\u003eFFR, functional flow reserve; LAD, left anterior descending\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"100%\" colspan=\"9\"\u003e\n \u003cp\u003ecut-off value, 0.500 indicated 50% coronary cross-area reduction\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"ischemic heart disease, reversible ischemia, coronary pressure, multi-slice CT, coronary hemodynamics","lastPublishedDoi":"10.21203/rs.3.rs-4552080/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4552080/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eFractional flow reserve (FFR) is the gold standard for assessing the physiological significance of coronary stenosis. We examined the potential correlation between digitally measured coronary cross-sectional area stenosis by coronary CT angiography, and the FFR. We analyzed 32 consecutive patients with stenoses who underwent invasive FFR determination. The cross-sectional area was assessed using 128-slice coronary detector-based spectral CT angiography. Power analysis revealed that the sample size enabled the detection of an area under the receiver operating characteristic (ROC) curve (AUC) of 0.90. FFR\u0026thinsp;\u0026le;\u0026thinsp;0.8 and \u0026gt;\u0026thinsp;0.8 were defined as FFR-positive and FFR-negative, respectively. Intra- and inter-observer differences were negligible. AUC indicated that cross-sectional area reduction effectively discriminated between FFR-positive and FFR-negative cases, yielding a sensitivity of 0.882 and specificity of 0.933 at the cutoff of 50% area reduction, with an AUC of 0.976. Lesions with less than 45% cross-sectional area reduction on coronary CT angiography were not FFR-positive. When ROC analysis was conducted for lesion characteristics, AUC did not significantly improve. In conclusion, the coronary cross-sectional area stenosis severity from coronary CT angiography distinguished between FFR-positive and FFR-negative lesions with high accuracy. Area reduction on CT angiography is indicated to be clinically useful for predicting the FFR.\u003c/p\u003e","manuscriptTitle":"Coronary cross-sectional area stenosis severity determined by coronary CT highly correlated with coronary functional flow reserve: a pilot study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-07-08 16:58:12","doi":"10.21203/rs.3.rs-4552080/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2024-12-10T05:11:16+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-11-18T04:23:09+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"137573343939393885446720892685747210129","date":"2024-10-31T08:43:10+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-08-30T06:00:33+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"46322768764096423105885956011314319209","date":"2024-08-30T05:49:00+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2024-08-25T05:45:35+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2024-08-24T00:38:49+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2024-07-19T11:48:38+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2024-06-11T07:58:10+00:00","index":"","fulltext":""},{"type":"submitted","content":"Scientific Reports","date":"2024-06-09T00:46:46+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"bdc5657a-6db8-4938-812b-24c609cfbd74","owner":[],"postedDate":"July 8th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[{"id":33173732,"name":"Health sciences/Cardiology"},{"id":33173733,"name":"Health sciences/Medical research"}],"tags":[],"updatedAt":"2025-07-28T16:02:00+00:00","versionOfRecord":{"articleIdentity":"rs-4552080","link":"https://doi.org/10.1038/s41598-025-11920-z","journal":{"identity":"scientific-reports","isVorOnly":false,"title":"Scientific Reports"},"publishedOn":"2025-07-23 15:57:44","publishedOnDateReadable":"July 23rd, 2025"},"versionCreatedAt":"2024-07-08 16:58:12","video":"","vorDoi":"10.1038/s41598-025-11920-z","vorDoiUrl":"https://doi.org/10.1038/s41598-025-11920-z","workflowStages":[]},"version":"v1","identity":"rs-4552080","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4552080","identity":"rs-4552080","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}