Author + information
- Received January 16, 2018
- Revision received June 27, 2018
- Accepted June 28, 2018
- Published online August 6, 2018.
- Daisuke Nakamura, MDa,
- William Wijns, MD, PhDb,c,
- Matthew J. Price, MDd,
- Michael R. Jones, MDe,
- Emanuele Barbato, MD, PhDb,
- Takashi Akasaka, MD, PhDf,
- Stephen W.-L. Lee, MD, PhDg,
- Sandeep M. Patel, MDa,
- Setsu Nishino, MD, PhDa,
- Wei Wang, PhDa,
- Ajay Gopinath, PhDa,
- Guilherme F. Attizzani, MDa,
- David Holmes, MDh and
- Hiram G. Bezerra, MD, PhDa,∗ ()
- aHarrington Heart and Vascular Institute, University Hospitals Cleveland Medical Center, Case Western Reserve University, Cleveland, Ohio
- bCardiovascular Research Center, OLV Hospital, Aalst, Belgium
- cThe Lambe Institute for Translational Medicine and CURAM, National University of Ireland, Galway, Ireland
- dScripps Clinic, La Jolla, California
- eBaptist Health Lexington, Lexington, Kentucky
- fWakayama Medical University, Wakayama, Japan
- gUniversity of Hong Kong, Queen Mary Hospital, Hospital Authority, Pok Fu Lam, Hong Kong
- hMayo Clinic, Rochester, Minnesota
- ↵∗Address for correspondence:
Dr. Hiram G. Bezerra, Harrington Heart & Vascular Institute, University Hospitals Cleveland Medical Center, 11100 Euclid Avenue, Cleveland, Ohio 44106.
Objectives This study sought to compare conventional methodology (CM) with a newly described optical coherence tomography (OCT)-derived volumetric stent expansion analysis in terms of fractional flow reserve (FFR)-derived physiology and device-oriented composite endpoints (DoCE).
Background The analysis of coronary stent expansion with intracoronary imaging has used CM that relies on the analysis of selected single cross-sections for several decades. The introduction of OCT with its ability to perform semiautomated volumetric analysis opens opportunities to redefine optimal stent expansion.
Methods A total of 291 lesions treated with post-stent OCT and FFR were enrolled. The expansion index was calculated by using a novel volumetric algorithm and was defined as: ([actual lumen area / ideal lumen area] × 100) for each frame of the stented segment. The minimum expansion index (MEI) was defined as the minimum value of expansion index along the entire stented segment. MEI and conventional lumen expansion metrics were compared for the ability to predict post-stent low FFR (<0.90) and DoCE at 1 year.
Results There was a stronger correlation between MEI and final FFR, compared with CM and final FFR (r = 0.690; p < 0.001) versus (r = 0.165; p = 0.044). MEI was significantly lower in patients with DoCE than those without DoCE (72.18 ± 8.23% vs. 81.48 ± 11.03%; p < 0.001), although stent expansion by CM was similar between patients with and without DoCE (85.05 ± 22.19% and 83.73 ± 17.52%; p = 0.858), respectively.
Conclusions OCT analysis of stent expansion with a newly described volumetric method, but not with CM, yielded data that were predictive of both an acute improvement in FFR-derived physiology and DoCE.
Several randomized clinical trials have demonstrated that drug-eluting stents (DES) dramatically reduce the risk of angiographic restenosis and the incidence of repeat revascularization (1,2). Complications resulting from stent underexpansion after DES implantation including persistent angina, restenosis, and stent thrombosis do, however, persist. Studies reporting the use of intravascular ultrasound (IVUS) to optimize stent expansion with conventional methodology (CM) to improve clinical outcomes have reported low success rates in achieving predefined expansion criteria and somewhat discordant results in regards to clinical outcomes. Newer tools that include fractional flow reserve (FFR) and optical coherence tomography (OCT) are now being studied. The use of FFR, an established technique to assess the physiologic significance of coronary stenosis (3), has as well been shown to improve clinical outcomes (4,5) and to predict adverse events following percutaneous coronary intervention (PCI) (6–9). OCT, currently the highest resolution imaging modality available, was shown to have a profound effect on physician decision-making during PCI in the ILUMIEN I study. Its influence on clinical outcomes (when used to assess stent expansion with CM) awaits longer term follow-up.
Full lumen expansion has been found to be an important aspect of optimizing PCI to reduce the occurrence of post-stent complications. OCT, with its higher resolution imaging capability and semiautomated image analysis, has been applied, like IVUS, to expansion analysis using conventional geometric methods that compare the minimal cross-sectional area of a single frame within the stent compared with the reference vessel (10–12). This CM, whether using IVUS or OCT, may have important limitations because it does not take into account vessel tapering, thus not accurately reflecting areas of underexpansion. Volumetric analysis to assess lumen expansion that takes into account vessel tapering may be more functionally accurate and therefore more predictive of outcomes. The aims of the present study were to derive a mathematical model for use in OCT-derived volumetric analysis of stent expansion following stent placement in the ILUMIEN I cohort, and to evaluate the impact of volumetric analysis versus CM on post-PCI physiology (FFR) and clinical outcomes (device-oriented composite endpoints [DoCE]) to 1 year.
This paper reports an ad hoc subanalysis of ILUMIEN I, a prospective, multicenter study enrolling 418 patients at 36 centers in the United States, Canada, European Union, Australia, and Asia designed to identify the impact of OCT on physician decision-making (13). A detailed study protocol has been published elsewhere (13). The trial was approved by the institutional ethics committee of each participating institution and by the appropriate national ethics committees. In brief, patients with stable angina, unstable angina, or non–ST-segment elevation myocardial infarction having at least 1 de novo lesion with an angiographic diameter stenosis >50% by visual estimation and planned DES placement were enrolled. Up to 2 major vessels and 3 lesions could be treated. Subjects with acute ST-segment elevation myocardial infarction, emergent PCI, cardiogenic shock, target lesions involving the left main coronary artery, restenosis or stent thrombosis, aorto-ostial or diffuse disease, and extreme angulation or calcification and those with the planned use of a bare-metal stent were excluded. FFR and OCT were performed pre-PCI and post-PCI. If OCT assessment post-PCI was deemed unsatisfactory because of flow-limiting edge dissection, significant malapposition, thrombus/tissue protrusion with flow reduction, or stent underexpansion (≥30% compared with the reference distal lumen area), further optimization was recommended before repeat OCT imaging and FFR were performed. The present study assessed pre-PCI and final OCT images, and final post-stent FFR. Only patients who had both final OCT imaging and FFR available were included. Furthermore, to determine the role of stent expansion on final FFR, only cases without significant angiographic stenosis in the treated artery outside the stented area (<30% by quantitative coronary angiography) were included in this analysis. All patients were included in the clinical event analysis.
FFR acquisition and analysis
FFR measurements were performed using a 0.014-inch pressure guidewire (St. Jude Medical, Minneapolis, Minnesota) (14,15). Maximal myocardial hyperemia was induced before each FFR measurement per standard institutional practice. The pressure wire was initially positioned distal to the most peripheral lesion and at the same position between pre- and post-PCI FFR determinations. FFR was calculated as the mean distal coronary pressure divided by the mean aortic pressure during maximal hyperemia (3). All recorded FFR tracings were analyzed by the angiographic/FFR core laboratory (Cardiovascular Imaging Core Laboratory, Harrington Heart & Vascular Institute, University Hospitals Cleveland Medical Center, Cleveland, Ohio). Two independent readers blinded to patient information performed the FFR analysis and selected the lowest FFR value. Quantitative coronary angiography was also done by 2 independent readers.
OCT image acquisition and analysis
OCT images were acquired with a frequency domain OCT system (St. Jude Medical) after administration of intracoronary nitroglycerin. Two independent readers from the Cardiovascular Imaging Core Laboratory (Harrington Heart & Vascular Institute, University Hospitals Cleveland Medical Center), who were blinded to patient information, performed quantitative and qualitative OCT analyses using dedicated software (Off-line Review Software, version E.0.2, St. Jude Medical). All cross-sectional images were initially screened for quality assessment and excluded from analysis if any portion of the stent was out of the screen or if image quality was considered poor because of residual blood, artifact, or reverberation (16). Quantitative (i.e., luminal areas and diameters) and qualitative measurements were performed for every frame along the entire target segment. For the morphometric analysis, standard definitions of cross-sectional area and volume measurements were applied as previously reported (16). Respective volumes were calculated according to the Simpson rule. Proximal and distal references were measured at the site with the largest lumen within 5 mm proximal and distal to the stented segment. Percent area stenosis was calculated as: ([reference lumen area − minimum lumen area]/reference lumen area) × 100 pre-PCI.
Stent underexpansion was assessed with OCT using both CM and OCT-derived volumetric data. MSA was derived from automatic lumen segmentation within the stented lesion. CM underexpansion was defined as a minimal stent area (MSA) <80% of the average of proximal and distal reference lumen areas if both references were available (Figure 1A), ≤90% if only the distal reference was available, or ≤70% if only the proximal reference was available.
The newly proposed volumetric analysis definition of underexpansion, based on a minimum expansion index (MEI), was obtained by creating an ideal lumen profile along the stented region, considering vessel tapering (Figure 1B). The method proposed in this manuscript calculates an adaptive reference frame, depending on the specific frame location and major side-branches. A major side-branch is defined as a branch having a radius >0.50 mm.
The adaptive ideal reference profile is computed using the natural taper of the vessel due to side-branches. There is a mathematical relationship between the distal and proximal reference and the intermediate side-branch that was described by Huo et al. (17) and known as the H-K model.(Equation 1)Where Dprox is the diameter of the proximal vessel, Ddist is the diameter of the distal reference, and B is the diameter of the intermediate side-branch.
In case no major side-branch is detected between the distal and the proximal reference, the ideal lumen diameter at each location is calculated by using linear interpolation between the distal and the proximal references (Figure 1B). In cases of multiple side-branches, the ideal reference profile between the distal and proximal reference frames is tapered with a step at each side-branch, the larger side-branch contributes proportionally to a larger step (Figures 1C and 1D). This is formalized in a mathematical relationship described in Online Appendix I.
Each frame was assigned a normalized expansion index value, calculated as: ([actual lumen area / ideal lumen area] × 100). MEI was defined as the cross-section with lowest expansion index along the entire stented segment (Figure 2). Cases with low expansion index were defined as cases with at least 1 cross-section with an MEI <80%. Percentage of frames with low MEI was calculated as: ([number of the frames with low MEI / number of all frames in the stent] × 100).
Strut-lumen distance was determined based on automated measurements performed from the center of the strut blooming to the luminal contour of the artery wall. Major malapposition was defined when strut-lumen distance was higher than 200 μm (13). Edge dissection was defined as the disruption of the vessel luminal surface with a visible flap at the stent edge or within 5 mm of the proximal and distal reference segments. Intrastent tissue protrusion/thrombus was defined when intimal irregular protruding was observed and the distance from the arc connecting adjacent stent struts to the greatest extent of protrusion was >200 μm (13). Plaque assessment was performed for the target lesion and the lesion was categorized according to its most prevalent component as follows: 1) normal (3-layered architecture, comprising intima, media, and adventitia); 2) fibrous plaque (homogeneous, highly backscattering regions with intimal thickness ≥300 μm); 3) calcified plaque (low scattering regions with sharply delineated borders); and 4) lipid plaque (signal-poor regions with diffuse borders and high attenuation) (18). The reproducibility of this method for qualitative assessment of plaque characteristics has been previously demonstrated (18).
Clinical follow-up and the definition of major adverse cardiac events
DoCE included cardiac death, target vessel–related myocardial infarction, target lesion revascularization (TLR), and stent thrombosis (19,20). Stent thrombosis was classified as definite, probable, or possible (19). Cardiac death was defined as death related to immediate cardiac causes, procedure-related complications, or any death in which a cardiac cause could not be excluded. Myocardial infarction was reported according to Academic Research Consortium definition (21). TLR was defined as any revascularization procedure (either percutaneous or coronary artery bypass grafting) of the target lesion in the presence of angiographic restenosis and signs or symptoms of ischemia.
All statistical analyses were performed using SAS version 9.4 (SAS Institute, Cary, North Carolina) and statistical significance was assessed at the 0.05 level. Continuous variables are presented as median (interquartile range) or mean ± SD as appropriate and categorical variables are presented as number (%). For continuous variables, comparisons between 2 groups were made with use of the nonparametric Mann-Whitney U test and categorical variables were compared using Fisher exact test at the patient level. At the lesion level, continuous and binary variables between 2 groups with different FFR values were compared using generalized estimating equations modeled with exchangeable correlation structure to account for the clustering of multiple lesions within the same subject. Univariate logistic regression models were developed, and odds ratios were used to evaluate different OCT measurements associated with DoCE. The multivariate analysis was performed with a stepwise selection procedure (entry criteria of 0.30 and stay criteria of 0.05) to identify independent factors associated with outcome. Receiver operating characteristic analyses were performed to determine the predictability of the DoCE using the minimum underexpansion. Pearson correlation coefficients were used to measure the strength between continuous variables and the Hotelling-Williams test was used to determine the statistical significance of any differences observed in the correlation coefficients between final FFR value versus CM and final FFR values versus MEI.
Baseline patient characteristics and procedural data
A total of 291 lesions in 289 patients were evaluated in this substudy. A total of 11 lesions (3.8% of treated lesions) in 11 patients experienced DoCE during 1-year follow-up. There were no significant differences in patient baseline characteristics or lesion location between patients with and without DoCE (Table 1). Stent diameter was significantly lower in DoCE group (Table 2).
Correlation of OCT findings with final FFR
Enrolled lesions were divided into 2 groups according to the median FFR value after optimal stent treatment: the low-FFR (≤0.90) group and the normal-FFR (>0.90) group. There were 159 lesions with a post-treatment FFR ≤0.90 and 132 lesions with an FFR >0.90 (Figure 3). Seventy-four patients had angiographic mild/moderate stenosis (defined as diameter stenosis >30% by quantitative coronary angiography) of a nonculprit lesion in the same treated vessel. Among the 159 cases with low FFR, 67 (42.1%) had angiographic moderate stenosis outside of the stented segment, whereas among the 132 cases with normal FFR, 7 cases (5.3%) had moderate stenosis outside the stent segment (p < 0.001).
We compared the OCT findings between 92 cases with FFR ≤0.90 and 125 cases with FFR >0.90 without mild-moderate stenosis involving a nonculprit lesion because coronary stenosis outside of the stented segment could impact the FFR value in the study vessel. There were no significant differences between the low and normal post-stent FFR groups in terms of the presence of underexpansion as defined by the CM (78.14 ± 14.66% vs. 82.46 ± 16.99%; p = 0.087), respectively. However, MEI was significantly lower (72.68 ± 9.21% and 84.10 ± 8.44%; p < 0.001) and the frequency of cases with low MEI (72.2% and 30.9%; p < 0.001) and the percentage of frames with low MEI (17.07 ± 18.66% and 3.71 ± 9.08%; p < 0.001) were significantly higher in the FFR ≤0.90 group compared with the FFR >0.90 group (Table 3).
There was a weak positive correlation coefficient between MSA and final FFR (r = 0.321; p < 0.001) and moderate negative correlation between percentage of frames with low MEI and final FFR (r = −0.501; p < 0.001). MEI also demonstrated moderate correlation with FFR values (r = 0.690; p < 0.001), whereas the CM had only weak correlation (r = 0.165; p = 0.044) with post-stent FFR. This resulted in a statistically higher correlation between MEI and final FFR compared with the CM (Hotelling-Williams test for correlation coefficient comparison, p < 0.001) (Figure 4).
MSA was significantly lower in lesions with FFR ≤0.90 (4.77 ± 1.47 mm2 and 5.99 ± 2.78 mm2; p < 0.001) (Table 3). Cases with low MEI were more prevalent in the group with FFR ≤0.90 (72.2% vs. 30.9%; p < 0.001). In 48.5% of cases, MEI was present in a different location compared with MSA. Prevalence of underexpanded stent as defined by CM was not different on FFR ≤0.90 (50.7% vs. 41.5%; p = 0.263). The incidence of major stent malapposition, edge dissection, and intrastent protrusion/thrombus at final OCT were similar between groups (Table 3).
Correlation of OCT findings with clinical outcome at 1-year follow-up
There were no significant differences in pre-OCT images between the groups with or without DoCE, with the exception of a smaller reference vessels in the DoCE group (Table 4). Stent expansion as assessed by CM was similar between the DoCE+ and DoCE- groups (45.5% and 36.7%; p = 0.557). However, cases with any frame with low MEI were more prevalent in the DoCE group (80.0% and 40.5%; p = 0.019) and MEI was significantly lower in patients with DoCE than those without DoCE (72.18 ± 8.23% vs. 81.48 ± 11.03%; p < 0.001), although the CM to assess stent expansion did not show significant differences (85.05 ± 22.19% and 83.73 ± 17.52%; p = 0.858). The percentage of frames with low MEI was also significantly higher on the DoCE group (19.39 ± 15.54% and 7.76 ± 14.26%; p = 0.015). Receiver operating characteristic curve analyses identified the best cutoff value for MEI in predicting DoCE as 73.3% (Figure 5, Table 5).
There were no significant differences for all other post-stent findings between the DoCE+ and DoCE- groups with the exception of MSA. MSA was significantly lower (4.33 ± 1.66 mm2 vs. 5.47 ± 2.37 mm2; p = 0.022) in DoCE+ group. The frequency of lesions with MSA <4.0 mm2 (54.5% and 27.9%; p = 0.069) and <5.0 mm2 (72.7% and 50.7%; p = 0.166) were not statistically different in DoCE+ group (Table 5).
Predictors of DoCE and TLR
The univariate model showed MSA <4.0 mm2, final FFR <0.86, MEI, and severe low MEI, defined as MEI ≤73.3%, were predictors of 1-year DoCE. The multivariate model identified severe low MEI as the only independent OCT predictor for DoCE and TLR (p = 0.017 and p = 0.037). Final FFR <0.86 was a predictor for TLR at 1 year (p = 0.04) (Table 6).
The ILUMIEN I study is the largest prospective study to report the influence of pre- and post-procedural FFR and OCT on physician decision-making during DES placement. We now report a post hoc analysis of these data that compares a newly described OCT volumetric analysis algorithm with OCT analysis using conventional metrics to assess stent expansion. Despite advances in coronary stent technology and the evolution of guidelines that define best medical treatment for patients, device-oriented clinical events including cardiac death, target vessel–related myocardial infarction, TLR, and stent thrombosis persist. Over the last several decades, several studies evaluating the optimization of stent implantation using IVUS have been published. The interpretation of these studies has been challenging on several fronts that include differing definitions of optimal stent expansion, discordance of results, and the absence of adjuvant physiologic data (FFR) to complement anatomic data. We thus elected to carry out a post hoc analysis of ILUMIEN I data that takes advantage of the ability of OCT to carry out semiautomated volumetric data quantification and to compare volumetric versus conventional criteria for stent optimization with any immediate improvement in post-stent physiology (as defined by FFR) and 1-year DoCE.
The findings of this study are as follows: 1) in this ad hoc analysis of ILUMIEN I data, the use of semiautomated OCT-guided volumetric analysis of stent expansion proved feasible; 2) volumetric MEI was strongly correlated with post-procedure FFR, whereas CM was not; 3) MEI was significantly lower in patients with DoCE than without DoCE, whereas CM to assess stent underexpansion showed no differences between these groups of patients; and 4) MEI was an independent predictor of 1-year DoCE.
Correlation of abnormal post-stent OCT findings with a persistently abnormal FFR
Some studies have shown that FFR after stent implantation could be a useful predictor of adverse cardiac events at follow-up (6–9,22). There are several potential mechanisms for a persistent low FFR after stent implantation including lumen underexpansion, stent edge dissection, and plaque protrusion. Non-stent-related mechanisms could also include residual moderate stenosis or diffuse plaque outside the stented segment (23). In the present study, we demonstrate that MEI-defined underexpansion (but not CM-defined expansion) is predictive of a low post-procedure FFR. We also demonstrate that non-stent-related stenosis is frequently present in patients with low post-stent FFR. Among lesions with an FFR ≤0.90, a total of 42.5% (67 of 159) had mild-moderate stenosis in the nonstented segment, whereas in those with an FFR >0.90, only 5.3% (7 of 132) had similar stenosis in the nonstented segment. Among lesions without stenosis outside the stented segment, OCT findings of stent edge dissection and malapposition were not correlated with final FFR.
Correlation of MEI with FFR and clinical outcome
Prior IVUS studies have demonstrated that MSA is associated with clinical outcomes (10–12). A single study using OCT reported that a small MSA, defined as a lesion with a MSA <5.0 mm2 in a DES or <5.6 mm2 in a bare-metal stent was an independent OCT predictor of 1-year device-oriented adverse clinical outcomes (24). MSA and minimal lumen area post-stent are, however, dependent on the reference vessel diameter of the target lesion, which varies according to the coronary vessel (i.e., left anterior descending artery, right coronary artery, or left circumflex artery) and lesion location (proximal, mid, or distal). For example, it would be hard to attain an MSA >5.0 mm2 for a stent that is implanted within the small vessel (e.g., 2.25-mm diameter). We thus believe that MSA determination alone has limited use in individual cases. Stent expansion has been evaluated conventionally by comparing the minimal lumen area or diameter within the stent with the reference vessel lumen. This CM to assess underexpansion does not take into account vessel tapering and often has limited impact on decisions for additional post-dilatation. Our proposed metric, the MEI, takes into account vessel tapering and the presence of major side branches, resulting in an ideal lumen profile that tapers from the proximal to the distal part of the vessel. Every cross-section is indexed to an ideal lumen value. Without taking into account vessel tapering there is a bias to find MSA post-stent in the distal segment of the stent, which very often represents a well-expanded segment in the setting of natural vessel tapering, rather than true underexpansion. In fact, our MEI location differed from minimal lumen area post-stent in almost one-half of the cases (Figure 3). OCT is particularly suitable for the task of full volumetric lumen analysis because of its high resolution that allows automatic lumen segmentation. We have been able to demonstrate that MEI is an independent predictor of lower FFR value after stenting. Furthermore, in addition to MEI, the only other independent predictor of low FFR was left anterior descending artery location. It has been shown that left anterior descending artery lesions have consistently lower FFR values than other coronary vessels with similar degrees of stenosis because of the large area of myocardium supplied by this vessel (25,26). In this study, volumetric analysis of stent expansion was a strong independent predictor of not only FFR-defined physiology but of the risk of DoCE at 1 year, whereas CM was not. In a multivariate analysis MEI was the only independent predictor of DoCE (odds ratio: 5.7).
Abnormal post-stent FFR poses a risk for poor clinical outcomes (6–8); however, its use as a surrogate to optimize stent expansion is limited, as demonstrated in this report, at least in part because of the effects of diffuse disease that commonly occurs outside of the stented segment. Coronary imaging with IVUS or OCT using CM to optimize stent expansion has shown limitations in optimizing stent expansion that may be in part caused by geometric considerations (e.g., tapering) within the vessel. We show that MEI determination, a new method using OCT-derived volumetric analysis of stent expansion, has a good correlation with both post-stent physiology as determined by FFR and 1-year clinical outcomes, whereas CM does not. Automatic volumetric lumen analysis with the creation of an ideal lumen profile may be the most practical and efficient way to evaluate stent expansion to optimize patient outcomes.
First, patients with ST-segment elevation myocardial infarction and those with left main and other higher risk coronary artery anatomy were not included in this study. Second, by simply measuring the diameter of the side branch ostium without perpendicular adjustment to the side-branch centerline, the newly proposed algorithm may incur errors that cannot be quantified in the current study. Third, side-branch ostium stenosis may impact our assessment of the actual size of the side-branch and consequently the creation of an ideal lumen profile. Fourth, in tortuous vessels, guidewire bias and oblique orientation of the OCT catheter might cause erroneous side-branch lumen measurements. Finally, although there was difference in DoCE between the 2 groups, there were only 11 patients with events and the study was not powered to determine the effect of OCT-derived volumetric stent expansion on clinical outcomes.
Volumetric analysis of stent expansion for the measurement of MEI using OCT is superior to conventional stent expansion methodology for the prediction of post-intervention FFR and 1-year DoCE. MEI should be considered as part of a PCI optimization strategy in a prospective trial.
WHAT IS KNOWN? Conventional ways to quantify stent expansion rely on simple cross-section measurements and do not take into account vessel tapering.
WHAT IS NEW? We propose a new methodology for stent expansion that consists of full volumetric lumen analysis and takes into account lumen tapering. This had a better correlation with clinical outcome and post-FFR values.
WHAT IS NEXT? A prospective trial applying this algorithm.
Authors from participating sites report institutional study support from St. Jude Medical. Dr. Wijns has received research grants from Volcano and Boston Scientific; received speaker fees from Abbott Vascular, Biotronik, and MicroPort; is a cofounder, shareholder, and nonexecutive board member of Argonauts Partners; and a past board member of Cardio3Biosciences, now Celyad. Dr. Price has received fees from St. Jude, Boston Scientific, Medtronic, and Terumo. Dr. Jones serves on the Abbott Vascular Speakers Bureau. Dr. Akasaka has received fees from St. Jude Medical Japan, Abbott Vascular Japan, Terumo, and Goodman. Dr. Attizzani has received consulting fees from St. Jude Medical; is a proctor for Edwards Lifesciences and Medtronic; and serves on the Abbott Vascular Speakers Bureau. Dr. Gopinath is an Abbott employee. Dr. Bezerra has received consulting fees from St. Jude Medical, and Abbott Vascular; and is an employee of Abbott Vascular. All other authors have reported that they have no relationships relevant to the contents of this paper to disclose.
- Abbreviations and Acronyms
- conventional methodology
- drug-eluting stent(s)
- device-oriented composite endpoint
- fractional flow reserve
- minimum expansion index
- minimal stent area
- optical coherence tomography
- percutaneous coronary intervention
- target lesion revascularization
- Received January 16, 2018.
- Revision received June 27, 2018.
- Accepted June 28, 2018.
- 2018 American College of Cardiology Foundation
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