Quantitative cardiac dual source CT; from morphology to function
Assen, van, Marly
DOI:
10.33612/diss.93012859
IMPORTANT NOTE: You are advised to consult the publisher's version (publisher's PDF) if you wish to cite from it. Please check the document version below.
Document Version
Publisher's PDF, also known as Version of record
Publication date: 2019
Link to publication in University of Groningen/UMCG research database
Citation for published version (APA):
Assen, van, M. (2019). Quantitative cardiac dual source CT; from morphology to function. Rijksuniversiteit Groningen. https://doi.org/10.33612/diss.93012859
Copyright
Other than for strictly personal use, it is not permitted to download or to forward/distribute the text or part of it without the consent of the author(s) and/or copyright holder(s), unless the work is under an open content license (like Creative Commons).
Take-down policy
If you believe that this document breaches copyright please contact us providing details, and we will remove access to the work immediately and investigate your claim.
Downloaded from the University of Groningen/UMCG research database (Pure): http://www.rug.nl/research/portal. For technical reasons the number of authors shown on this cover page is limited to 10 maximum.
artery disease; the effect of location and
luminal area
Marly van Assen, Carlo N. De Cecco, Simon Martin, Andreas M. Fischer, Richard R. Bayer, Pooyan Shabaee, Chris Schwemmer, H. Todd Hudson, R. Savage, Akos
Varga-Szemes, Matthijs Oudkerk, Rozemarijn Vliegenthart, U.Joseph Schoepf
ABSTRACT
Purpose: To evaluate the effect of measurement location and lumen area changes on CT-FFR values in patients without coronary artery disease.
Methods: Patients that underwent calcium scoring and CCTA with CT-FFR were retrospectively included. Patients were excluded if their CACS was not zero, there were elevated troponin levels, or any cardiac abnormality on the images. On-site CT-FFR was computed for each coronary artery at proximal, mid, and distal segments. At each measurement location, the lumen area and HU value was measured. CT-FFR was considered positive if <0.75. The relationship between lumen areas, HU values, and CT-FFR was evaluated for each coronary artery and each location. Ratios between mid and distal values compared to proximal values for lumen and HU parameters were calculated.
Results: A total of 106 patients were included. In 39 (37%) patients, the LAD had CT-FFR values <0.75, with a decrease in CT-FFR from 0.97 (SD 0.04) proximally to 0.62 (SD 0.10) distally in the abnormal patients. The Cx showed a limited number of patients with CT-FFR values <0.75 (n=16, 15%), with a decrease in CT-FFR values from 0.96 (SD 0.04) proximally to 0.65 (SD 0.09) distally in those patients. The RCA had 36 (34%) patients with CT-FFR <0.75, with distal CT-FFR values of 0.61 (SD 0.12) and proximal CT-FFR values of 0.98 (SD 0.02). 12 abnormal CT-FFR values were measured at mid segment, while all others were measured at distal segments. Lumen area was not significantly different between the abnormal and normal CT-FFR groups, while both HU and HU ratios were significantly lower in the abnormal CT-FFR group for all three major coronary arteries.
Conclusion: CT-FFR values in patients without coronary artery disease can become abnormal at a distal location without indicating flow-limiting stenosis, which depends strongly on HU values. CT-FFR values measured distally should always be interpreted in combination with the CCTA images.
INTRODUCTION
Coronary computed tomography angiography (CCTA) has become an accepted imaging technique for the evaluation of coronary artery disease (CAD), showing high sensitivity and negative predictive value. However, the specificity is low and the functional significance of a stenosis is often overestimated(1–5). Therefore, additional non-invasive functional assessment of coronary artery stenosis has been increasingly used for the evaluation of CAD(6–8).
CCTA derived fractional flow reserve (CT-FFR) is a new method that provides non-invasive information on the functional significance of coronary artery stenosis. It has been clinically validated by matching the point of CT-FFR measurement to that of the respective invasive FFR value acquired during invasive coronary angiography (ICA). Several studies show the higher discriminatory accuracy of CT-FFR compared to invasive FFR in detecting hemodynamically significant stenosis (9–13). However, one major aspect of CT-FFR that has not been taken into account is that CT-FFR calculates FFR values throughout the coronary tree for arteries down to 1.5 mm in diameter. Strikingly, the transition from the validation of the measurements to its clinical implementation lacks a fundamental piece of data. The use of coronary CT-FFR as a standalone diagnostic modality requires establishing the optimal location of the CT-FFR measurement and the profile of CT-FFR values in normal coronary arteries. Several publications discuss the optimal location of CT-FFR (14–17), however, none have yet described the course of CT-FFR values in normal coronary arteries and the effect location and lumen area can have on CT-FFR values independent of the presence of disease.
Therefore, the purpose of this study was to evaluate CT-FFR values in normal coronary arteries and to investigate the effect of measurement location and lumen area changes on CT-FFR values.
METHODS
Patients
We retrospectively selected patients who underwent coronary calcium imaging and CCTA for the suspicion of coronary artery disease or as part of a triple rule out examination between January 2016 and June 2018. Only patients with a coronary calcium score (CACS) of zero and a negative CCTA, meaning no atherosclerotic plaque, were included. Patients with other cardiac issues, such as coronary anomalies, atrial or ventricular enlargement, cardiomyopathies, and valve replacements were excluded.
Patients in which one of the three coronaries was not analyzable for various reasons were also excluded.
Demographic parameters and clinical risk factors were recorded for all patients including: age, gender, race, history of diabetes, hypertension, dyslipidemia, and smoking history.
Imaging Protocol
All patients underwent CT imaging with a third-generation dual-source CT system (SOMATOM Force, Siemens Healthcare) with the following parameters: 70-130kV tube potential automatically selected using an automated tube-voltage selection algorithm (CARE kV, Siemens), 200-650mAs tube current-time product, 0.25s gantry rotation time, 2x192x0.6mm detector collimation with a z-flying focal spot. The CCTA acquisition was performed with a prospectively ECG-triggered sequential acquisition in the case of hearts rates above 60 beats/min, or with a high-pitch spiral acquisition in the case of heart rates under 60 beats/min. A retrospective ECG gated acquisition was used in the case of arrhythmias.
CCTA was performed after administering 50–80 mL of iodinated contrast material with a concentration of 300–370 mg I/mL at a flow rate of 4-5 mL/s.
Image analysis
All CCTA images were assessed for image quality on a 4-point Likert scale, with 1 representing poor image quality and 4 representing excellent image quality. Patients with good and excellent image quality were included.
CCTA datasets were reconstructed with a section thickness of 0.75 mm and 0.5 mm increments and a vascular reconstruction kernel (Bv40) at the optimal phase.
CT-FFR was computed using an on-site prototype application (cFFR version 3.0, Siemens Healthineers, not currently commercially available). With this software, a three-dimensional coronary model was semi-automatically segmented, allowing for manual adjustments if necessary. CT-FFR profiles were generated for the left anterior descending (LAD), left circumflex (Cx), and right coronary artery (RCA). The left main coronary artery was excluded. CT-FFR values were recorded for each vessel at three different locations: proximal, mid, and distal, according to the AHA-segmentation. A threshold of <0.75, for hemodynamically significant CT-FFR values, was used based on previous literature. At each CT-FFR measurement location, the lumen area and HU value of the lumen were measured. A lumen area ratio and HU ratio were calculated using the ratio between the proximal and mid segment measurements and between the
proximal and distal segment measurements. Readings of contrast attenuation, lumen area, and CT-FFR were all done in the same session to ensure similar measurement locations.
Statistical analysis
Continuous variables are represented as a mean (SD) or median (interquartile range [IQR]), depending on their distribution (tested with Shapiro Wilks test). Categorical data are displayed as absolute frequencies (n) and proportions (%). Comparisons were made between patients and coronary arteries with and without abnormal CT-FFR values using an independent student t-test. All coronary arteries and measurement locations (proximal, mid, and distal) were compared separately. A multivariate regression analysis was run to test which variables contributed to the prediction of CT-FFR corrected for measurement location .A p-value <0.05 was considered statistically significant. Statistical analyses were conducted using SPSS version 23 (IBM, Armonk, New York).
RESULTS
A total of 106 patients with a mean age of 54 (SD 11) were included. Of these 106 patients, 73 (60%) were female. Table 1 shows an overview of demographic data. Analysis resulted in 318 coronary arteries with corresponding CT-FFR, as well as lumen area and HU measurements in the proximal, mid, and distal segments. An overview of CT-FFR and lumen areas of all three coronaries at the different locations are found in Table 2. An overall 90 (28%) coronary arteries in 63 (60%) patients had CT-FFR values <0.75. In 43 (40%) patients, no abnormal CT-FFR value was measured in any of the coronary arteries. 40 (38%) patients had an abnormal CT-FFR value in one of the coronary arteries, 19 (18%) had abnormal CT-FFR values in two coronary arteries, and 4 (4%) had abnormal CT-FFR values in all three coronary arteries. The patients with an abnormal CT-FFR value in any of the coronary arteries had a significantly higher BMI (31.8, SD 5.9) compared to patients with no abnormal CT-FFR values (27.4, SD 4.7, p-value <0.001).
Figur e 1: The first r ow sho w s the decr ease in HU v alues , with a mor e pr onounc ed decr ease in pa tien ts with a abnor mal C T-FFR v alue (r ed) c ompar ed t o pa tien ts with no abnor mal C T-FFR v alues (blue). The sec ond r ow sho w s the tr end of lumen ar ea decr ease , wher e although ther e is a diff er enc e pr esenc e bet w een the t w o g roups
, this is not sig
nifican
t
Figure 1, shows the trends of HU measurements and lumen area measurements from proximal to distal locations for the patients with and without abnormal CT-FFR values. In 67 (63%) patients, the LAD had CT-FFR values >0.75 at every measurement point, with a proximal mean CT-FFR value of 0.97 (SD 0.03) that declined to 0.81 (SD 0.11) at the distal LAD. In 39 (37%) patients, the LAD had CT-FFR values <0.75, with a decrease in CT-FFR from 0.97 (SD 0.04) proximally to 0.62 (SD 0.10) distally. Of those 39 patients, 7 had an abnormal CT-FFR value in the mid LAD segment and all other abnormal values were measured in the distal segment. The Cx shows only a limited number of patients with CT-FFR values <0.75 (n=16, 15%), all measured at the distal segment, with a decrease in CT-FFR values from 0.96 (SD 0.04) proximally to 0.65 ( SD 0.09) distally. The RCA shows results similar to the LAD, with 70 (66%) patients with all CT-FFR values >0.75 and 36 (34%) patients with CT-FFR <0.75, with distal mean CT-FFR values of 0.61 (SD 0.12) compared to proximal mean CT-FFR values of 0.98 (SD 0.02). Of the 36 patients with abnormal CT-FFR values in the RCA, 5 had an abnormal value measured in the mid segment, whereas all other abnormal values were measured in the distal segment of the RCA.
Table 1: Patient characteristics All patients (n=106) Normal CT-FFR(n=43) Abnormal CT-FFR(n=63) Age, years 53.5±10.9 54.8±58 52.8±10.6 Male 33 (27) 12 (28) 21 (33.3) BMI, kg/m2 29.9 (5.8) 27.4 (4.7) 31.8 (5.9)* Race Caucasian Afro-American Other 69 (57) 29 (24) 6 (5) 29 (67) 11 (25) 2 (5) 40 (64) 18 (29) 4 (6) Hypertension 33 (27) 12 (28) 21 (33) Hyperlipidemia 36 (30) 15 (35) 21 (33) Diabetes 23 (19) 8 (22) 15 (24) Smoking 20 (16) 7 (16) 13 (21)
Data is presented as mean (SD) or n (%). * indicates significant difference between the normal and abnormal CT-FFR group (p-value <0.05)
Independent of measurement location, the LAD lumen area does not show any significant difference between patients with or without an abnormal CT-FFR measurement. For all patients with an abnormal CT-FFR value in the LAD, the HU values at the distal segment (169, SD 71) were significantly lower than vessels without an abnormal CT-FFR value (267, SD 87) with a p-value <0.001. For the distal measurement location, both the lumen area ratio and the HU ratio were significantly different between patients with and without an abnormal CT-FFR value (p-values 0.021 and <0.001, respectively).
In contrast to the LAD, the proximal lumen area of the Cx was significantly lower in patients with an abnormal Cx CT-FFR value (4.21, SD 1.27) than in patients with normal CT-FFR values (6.23, SD 3.44, p-value 0.017). The difference in lumen area was not present at the mid and distal segment locations. Additionally, the lumen ratio showed no significant difference in any of the locations. Analysis of the HU values in the Cx vessels showed a significant difference in HU values at the distal segment between coronary arteries with (222, SD 58) and without (277 (91)) an abnormal CT-FFR value (p-value 0.025). Besides the difference in absolute HU values, the HU ratio also showed a significant difference of 0.80 (SD 0.16) and 0.68 (SD 0.22) between Cx arteries with normal and abnormal CT-FFR values (p-value 0.009).
For the RCA, independent of the measurement location, the lumen area and the lumen area ratio did not show any significant differences between patients with or without an abnormal CT-FFR measurement. In all locations, the RCA showed significantly lower HU values (p-value <0.001) in the abnormal CT-FFR coronary arteries with HU values of 302 (SD 136), 272 (SD 96), and 196 (SD 61) when compared to the normal CT-FFR coronary arteries with HU values of 402 (SD 133), 374 (SD 128), and 347 (SD 129) for the proximal, mid, and distal segments, respectively. For the distal location, the HU ratio was also significantly different, with a decreased ratio of 0.71 (SD 0.29) in vessels with an abnormal CT-FFR value compared to 0.86 (SD 0.16) in patients with normal CT-FFR values (p-value 0.002). An overview of these results is given in Table 2.
Figure 2 shows two examples of patients with CCTA and CT-FFR images.
A multiple regression was run to predict CT-FFR from HU-values and lumen area, corrected for measurement location. These variables statistically significantly predicted CT-FFR, F(3, 923) = 270.545, p < .001, R2 = .468. The HU variable added statistically significantly to the prediction, p < .05, where lumen area gave borderline significant p-values (0.042).
5
Table 2 LAD Cx RC A O ve ra ll n=1 06 CT -F FR A re a A re a ra ti o HU H U r at io CT -F FR A re a A re a ra ti o HU H U r at io CT -F FR A re a A re a ra ti o HU H U ratio Pr ox im al 0. 97 ( 0. 03 ) 7.6 6 ( 3.1 9) -36 2 ( 12 6) -0. 97 ( 0. 03 ) 5. 97 (3 .2 9) -35 2 ( 12 2) -0. 99 ( 0. 01 ) 6. 82 (2 .76 ) -37 0 ( 14 2) -M id 0. 88 ( 0. 06 ) 3. 05 (1. 54 ) 0. 42 ( 0.1 8) 32 2 ( 11 4) 0. 89 (0 .12 ) 0. 89 ( 0. 06 ) 3. 01 (1. 58 ) 0. 55 ( 0. 20 ) 32 5 ( 10 9) 0. 94 ( 0.1 7) 0. 88 ( 0. 09 ) 3. 79 (2 .01) 0. 57 ( 0. 20 ) 34 0 ( 12 8) 0. 94 (0.18) D ist al 0. 77 ( 0. 4) 1.0 9 (0 .4 6) 0.1 7 ( 0. 09 ) 231 (9 4) 0. 64 (0 .16) 0. 84 ( 0.1 0) 1.0 8 (0 .5 8) 0. 21 ( 0.1 2) 26 8 ( 89) 0. 79 ( 0.1 7) 0. 76 ( 0.1 5) 1. 31 ( 0. 83 ) 0. 21 ( 0.1 2) 29 7 ( 13 2) 0. 82 (0 .2 2) LA D Cx RC A A ll > 0.7 5 CT -FFR (n =67 ) A re a A re a ra ti o HU H U ra ti o CT -FFR (n =9 1) A re a A re a ra ti o HU H U r at io CT- FFR (n=7 0) A re a A re a ra ti o HU H U ra ti o Pr ox im al 0. 97 ( 0. 03 ) 8. 40 (3 .18) -387 (1 27 ) -0. 97 ( 0. 03 ) 6. 23 (3.44) -35 2 (12 2) -0. 99 (0.01) 7.2 7 (3 .01) -40 2 ( 13 3) -M id 0. 89 ( 0. 06 ) 3. 33 (1 .71) 0. 40 ( 0.1 7) 33 8 ( 111 ) 0. 88 (0.12) 0. 90 ( 0. 05 ) 3. 09 (1. 63 ) 0. 54 (0 .2 0) 32 9 (111 ) 0. 95 ( 0.1 6) 0. 92 (0.05) 4.1 4 (2 .18 ) 0. 57 ( 0. 20 ) 37 4 ( 12 8) 0. 93 (0.15) D ist al 0. 81 ( 0.1 1) 1.1 1 (0 .4 8) 0.1 5 ( 0. 08 ) 267 (8 7) 0. 70 (0 .13 ) 0. 87 ( 0. 06 ) 1.1 0 (0 .5 8) 0. 21 (0 .11 ) 277 (91) 0. 80 ( 0.1 6) 0. 86 (0.06) 1.4 4 (0 .9 4) 0. 21 ( 0.1 2) 34 7 ( 12 9) 0. 86 (0.16) LA D Cx RC A A ny < 0.7 5 CT -FFR (n =3 9) A re a A re a ra ti o HU H U ra ti o CT -FFR (n =15 ) A re a A re a ra ti o HU H U r at io CT- FFR (n=3 6) A re a A re a ra ti o HU H U ra ti o Pr ox im al 0. 97 ( 0. 04 ) 7.3 0 ( 3. 22 ) -32 0 ( 11 3) -0. 96 ( 0. 04 ) 4. 21 (1.27)* -35 0 (12 5) -0. 98 (0.02) 6.1 8 (2 .11 ) -30 2 ( 136 )* -M id 0. 84 ( 0. 06 ) 3. 00 (1.00) 0. 47 ( 0. 20 ) 295 (1 17 ) 0. 92 (0.13) 0. 81 ( 0. 06 ) 2. 43 (0 .9 6) 0. 58 (0 .19 ) 307 (95) 0. 91 ( 0. 21 ) 0. 81 (0.10) 3. 28 (1. 52 ) 0. 55 ( 0.1 9) 27 2 (9 6) * 0. 95 (0.22) D ist al 0. 62 ( 0.1 0) 1.1 9 (0 .4 6) 0.19 (0.10 )* 169 (7 1)* 0. 54 (0 .16) * 0. 65 ( 0. 09 ) 0. 96 (0.56) 0. 26 (0 .17 ) 222 (58) * 0. 68 ( 0. 22 )* 0. 61 (0.12) 1.13 (0.55 ) 0. 20 ( 0.1 2) 19 6 ( 61) * 0. 71 (0.29) * D at a i s p re se nt ed a s m ea n ( SD ).* i nd ic at es s ig ni fic an t d iffe re nc e b et w ee n t he n or m al a nd a bn or m al C T-FF R. L AD : L ef t a nt er io r d es ce nd in g a rt er y, C x: C irc um fle x c or on ar y a rt er y, R CA : R ig ht co ro na ry a rt er y g ro up ( p-va lu e < 0. 05 )Figure 2: The first row shows a patient with normal CT-FFR values throughout the coronary tree and no decrease in contrast attenuation. The second row shows a patient with an abnormal CT-FFR value in the LAD, corresponding to a decrease in attenuation with a ratio of 0.44 on the CCTA images from proximal to distal. The LAD from both patients show a similar decrease in lumen area.
DISCUSSION
This study reports on CT-FFR profiles in the coronary arteries of patients without coronary artery disease, where CT-FFR is measured throughout the coronary arteries, and evaluates the relationship between decreasing CT-FFR values, lumen area, and HU values. The results show that 90 (28%) coronary arteries in 63 (60%) patients had CT-FFR values <0.75 in a population without any stenosis. This decrease in CT-FFR was independent of lumen area but has shown to be highly related to overall low HU values and a steep decrease in HU values from proximal to distal, compared to patients without abnormal CT-FFR values.
Other studies on location in diagnostic studies focused mainly on the optimal location to measure CT-FFR compared to either invasive FFR or perfusion studies. A study by Solecki et al. evaluated 73 patients by measuring CT-FFR at multiple locations, determined as either the distance from the lesion of interest or as a multiple of the reference vessel diameter distal to the minimum lumen area, with stress MRI perfusion as the reference standard (15). One of the measurement locations was the most distal end of the coronary artery, resulting in the lowest absolute CT-FFR values compared to the other locations as well as the lowest diagnostic accuracy. The distal measurement point showed a lower specificity and positive predictive value compared to more proximal measurement locations, indicating that the distal measurements led to an increased number of false positives. This is confirmed by our study results and described in a short review paper by Rabbat et al. about CT-FFR calculated using computational fluid dynamics. Another study done by Cami et al., published as an abstract only, evaluated 729 patients with varying stenosis severity grades(16). They also concluded that CT-FFR declines from proximal to distal, and has two different components, one stenosis specific and one unrelated to the stenosis, that are present in patients without any stenosis. Kueh et al. compared the stenotic specific CT-FFR and lowest CT-FFR values in 192 patients, with results showing that 44% of patients with the lowest abnormal CT-FFR value were reclassified as normal when stenotic specific CT-FFR values were used (17).
The added value of doing the evaluation of CT-FFR measurements at various locations along the vessel is that it enables us to separate the effect of stenosis related decreases in CT-FFR values and investigate the causes of non-stenosis related decreases in CT-FFR. It is important to determine whether CT-FFR value drops indicate necessary stenosis treatment or are the result of other causes, such as a decrease in HU values proximal to distal, as demonstrated in the current study. We have to emphasize that distal stenoses are not likely to be treated by stenting due to the vessel diameter and limited effect on myocardial blood flow. However, it is important to distinguish whether the decrease is a delayed effect of a more proximal stenosis or whether it is caused by a decrease in HU values. The effect of measurement location could have an influence on the accuracy of CT-FFR measurement, taking into account the proximal to distal changes could provide additional information and increase accuracy especially in this so called grey zone, CT-FFR values around 0.70-0.80.
The axial decrease in HU values, also known as the transluminal attenuation gradient (TAG), has been investigated in multiple studies as a parameter to add flow information to CCTA analysis. Research on TAG as a parameter to predict myocardial ischemia has shown varying results(18–21). A study by Bom et al. on 557 patients with PET perfusion as a reference showed that TAG has no added value when compared to CCTA alone (21).
Whereas, Wong et al. showed that TAG has a sensitivity of 77% and a specificity of 74% compared to invasive FFR and adds incremental value to CCTA analysis alone (20). Bom et al. also shows that a decreasing diameter gradient does not predict ischemia. Although the TAG may have a limited function as an independent parameter, this study shows that TAG, even it not caused by a stenosis, can have an effect on the functional analysis. A reason for the decrease in HU values could be the short time of acquisition in the recently developed scan modes. Shorter acquisition times as well as capturing the proximal and distal parts of the coronaries at the same time does not allow for the dispersion of contrast to the distal parts. Further research should investigate the impact of these fast acquisition times.
Several limitations of this study need to be discussed. Patients in this study were selected based on negative test results, however, there is still a small chance these patients have some cardiac issues that were not detected on CACS or CCTA images. This study only includes patients from a single center using a high-end scanner with extensive cardiac imaging and CT-FFR expertise, and results may not be generalizable to other institutes. Future studies should be done to investigate the effect of false positive distal CT-FFR values and proximal to distal HU decreases on the clinical implementation of CT-FFR. In conclusion, CT-FFR values can become abnormal at a distal location without indicating flow-limiting stenosis and are strongly influenced by a decrease in HU values. CT-FFR values measured distal should always be interpreted in combination with the CCTA images.
REFERENCES
1. Abbara S. Chapter 9–Cardiac Imaging / 319. 2007;319–20.
2. Mowatt G, Cook JA, Hillis GS, Walker S, Fraser C, Jia X, et al. 64-Slice computed tomography angiography in the diagnosis and assessment of coronary artery disease: Systematic review and meta-analysis. Heart. 2008;94(11):1386–93.
3. Miller JM, Rochitte CE, Dewey M, Arbab-Zadeh A, Niinuma H, Gottlieb I, et al. Diagnostic Performance of Coronary Angiography by 64-Row CT. N Engl J Med [Internet]. 2008;359(22):2324– 36. Available from: http://www.nejm.org/doi/abs/10.1056/NEJMoa0806576
4. Meijboom WB, Meijs MFL, Schuijf JD, Cramer MJ, Mollet NR, van Mieghem CAG, et al. Diagnostic Accuracy of 64-Slice Computed Tomography Coronary Angiography. A Prospective, Multicenter, Multivendor Study. J Am Coll Cardiol [Internet]. 2008;52(25):2135–44. Available from: http://dx.doi.org/10.1016/j.jacc.2008.08.058
5. Meijboom WB, Van Mieghem CAG, van Pelt N, Weustink A, Pugliese F, Mollet NR, 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 [Internet]. 2008;52(8):636–43. Available from: http://dx.doi.org/10.1016/j.jacc.2008.05.024
6. Douglas PS, Hoffmann U, Patel MR, Mark DB, Al-Khalidi HR, Cavanaugh B, et al. Outcomes of Anatomical versus Functional Testing for Coronary Artery Disease. N Engl J Med [Internet]. 2015;372(14):1291–300. Available from: http://www.nejm.org/doi/10.1056/NEJMoa1415516 7. Danad I, Szymonifka J, Twisk JWR, Norgaard BL, Zarins CK, Knaapen P, et al. Diagnostic
performance of cardiac imaging methods to diagnose ischaemia-causing coronary artery disease when directly compared with fractional flow reserve as a reference standard: A meta-analysis. Eur Heart J. 2017;38(13):991–8.
8. Vliegenthart R, Henzler T, Moscariello A, Ruzsics B, Bastarrika G, Oudkerk M, et al. CT of coronary heart disease: Part 1, CT of myocardial infarction, ischemia, and viability. Am J Roentgenol. 2012;198(3):531–47.
9. Baumann S, Wang R, Schoepf UJ, Steinberg DH, Spearman J V., Bayer RR, et al. Coronary CT angiography-derived fractional flow reserve correlated with invasive fractional flow reserve measurements – initial experience with a novel physician-driven algorithm. Eur Radiol. 2015;25(4):1201–7.
10. Min JK, Leipsic J, Pencina MJ, Berman DS, Koo B-K, van Mieghem C, et al. Diagnostic Accuracy of Fractional Flow Reserve From Anatomic CT Angiography. Jama [Internet]. 2012;308(12):1237. Available from: http://jama.jamanetwork.com/article.aspx?doi=10.1001/2012.jama.11274 11. Coenen A, Lubbers MM, Kurata A, Kono A, Dedic A, Chelu RG, et al. Fractional Flow Reserve
Computed from Noninvasive CT Angiography Data: Diagnostic Performance of an On-Site Clinician-operated Computational Fluid Dynamics Algorithm. Radiology [Internet]. 2015;274(3):674–83. Available from: http://pubs.rsna.org/doi/10.1148/radiol.14140992
12. Kruk M, Wardziak Ł, Demkow M, Pleban W, Pręgowski J, Dzielińska Z, et al. Workstation-Based Calculation of CTA-Workstation-Based FFR for Intermediate Stenosis. JACC Cardiovasc Imaging. 2016;9(6):690–9.
13. Renker M, Schoepf UJ, Wang R, Meinel FG, Rier JD, Bayer RR, et al. Comparison of diagnostic value of a novel noninvasive coronary computed tomography angiography method versus standard coronary angiography for assessing fractional flow reserve. Am J Cardiol [Internet]. 2014;114(9):1303–8. Available from: http://www.ncbi.nlm.nih.gov/pubmed/25205628
14. Rabbat MG, Berman DS, Kern M, Raff G, Chinnaiyan K, Koweek L, et al. Interpreting results of coronary computed tomography angiography-derived fractional flow reserve in clinical practice. J Cardiovasc Comput Tomogr [Internet]. 2017;11(5):383–8. Available from: http://dx.doi. org/10.1016/j.jcct.2017.06.002
15. Solecki M, Kruk M, Demkow M, Schoepf UJ, Reynolds MA, Wardziak Ł, et al. What is the optimal anatomic location for coronary artery pressure measurement at CT-derived FFR? J Cardiovasc Comput Tomogr. 2017;11(5):397–403.
16. Cami E, Tagami T, Raff G, Gallagher M, Chinnaiyan K, Bilolikar AN, et al. Profiles of Fractional Flow Reserve Derived From Computed Tomography Angiography (Ffrct) in Patients With Coronary Artery Disease. J Am Coll Cardiol [Internet]. 2018;71(11):A1574. Available from: http:// linkinghub.elsevier.com/retrieve/pii/S0735109718321156
17. Kueh SH, Mooney J, Ohana M, Kim U, Blanke P, Grover R, et al. Fractional flow reserve derived from coronary computed tomography angiography reclassification rate using value distal to lesion compared to lowest value. J Cardiovasc Comput Tomogr. 2017;11(6):462–7.
18. Ko BS, Wong DTL, Nørgaard BL, Leong DP, Cameron JD, Gaur S, et al. Diagnostic Performance of Transluminal Attenuation Gradient and Noninvasive Fractional Flow Reserve Derived from 320–Detector Row CT Angiography to Diagnose Hemodynamically Significant Coronary Stenosis: An NXT Substudy. Radiology [Internet]. 2016;279(1):75–83. Available from: http:// pubs.rsna.org/doi/10.1148/radiol.2015150383
19. Orzan M, Hodas R, Dobra M, Rat N, Chitu M, Benedek I. Original Research. Transluminal Contrast Attenuation Gradient Is Associated with Coronary Plaque Vulnerability — a Computed Tomography Angiography-based Study. J Cardiovasc Emergencies [Internet]. 2017;3(3):121–7. Available from: http://content.sciendo.com/view/journals/jce/3/3/article-p121.xml
20. Wong DTL, Ko BS, Cameron JD, Nerlekar N, Leung MCH, Malaiapan Y, et al. Transluminal attenuation gradient in coronary computed tomography angiography is a novel noninvasive approach to the identification of functionally significant coronary artery stenosis: A comparison with fractional flow reserve. J Am Coll Cardiol. 2013;61(12):1271–9.
21. Bom MJ, Driessen RS, Stuijfzand WJ, Raijmakers PG, Van Kuijk CC, Lammertsma AA, et al. Diagnostic Value of Transluminal Attenuation Gradient for the Presence of Ischemia as Defined by Fractional Flow Reserve and Quantitative Positron Emission Tomography. JACC Cardiovasc Imaging. 2017;
