ABSTRACT
Background
Optimal stent expansion is a key determinant of long‐term outcomes after PCI. Intravascular imaging provides the most accurate assessment of stent deployment but remains underused, especially in older patients with MI and multivessel disease. ESV is an angiographic enhancement technology that may help detect gross stent underexpansion when advanced imaging is not feasible.
Aims
To evaluate the procedural and clinical impact of enhanced stent visualization (ESV)‐guided percutaneous coronary intervention (PCI) in older patients with myocardial infarction (MI) and multivessel disease.
Methods
In this prespecified sub‐study of the FIRE trial, we evaluated the impact of ESV use during PCI in older MI patients. Among 1445 enrolled patients, 331 underwent ESV‐guided PCI and 1114 standard angiography‐guided PCI. Procedural optimization triggered by ESV was defined as additional postdilation, extra stent implantation, or use of intravascular imaging. Minimal lumen diameter (MLD) was assessed before and after ESV‐guided optimization. Clinical outcomes were compared using multivariable and competing‐risk adjusted Cox models.
Results
Operator‐driven optimization occurred in 85% of ESV cases, primarily through postdilation (96%). ESV guidance resulted in a significant MLD increase from 2.51 [2.22–2.87] to 2.93 [2.41–3.32] mm (p < 0.001), yielding an acute luminal gain of 0.42 mm (95% CI 0.37–0.47). At 3 years, the composite primary endpoint (death, MI, stroke, or ischemia‐driven revascularization) was lower in the ESV group (adjusted HR 0.70, 95% CI 0.54–0.91; p = 0.008).
Conclusions
In older MI patients with complex multivessel disease, ESV‐guided PCI was associated with greater procedural optimization, improved acute stent expansion, and lower long‐term adverse events. While not a substitute for intracoronary imaging, ESV represents a pragmatic and valuable adjunct to enhance PCI quality in settings where intravascular imaging is seldom performed.
Trial Registration
ClinicalTrials.gov identifier NCT03772743.
Keywords: enhanced stent visualization, multivessel disease, myocardial infarction, older adults, percutaneous coronary intervention, stent optimization
Abbreviations
- AF
atrial fibrillation
- ARC
Academic Research Consortium
- BARC
Bleeding Academic Research Consortium
- CA‐AKI
contrast‐associated acute kidney injury
- CVA
cerebrovascular accident
- ESV
enhanced stent visualization
- IVUS
intravascular ultrasound
- LVEF
left ventricular ejection fraction
- MI
myocardial infarction
- MLD
minimal lumen diameter
- NSTEMI
non‐ST‐segment elevation myocardial infarction
- OCT
optical coherence tomography
- PAD
peripheral artery disease
- PCI
percutaneous coronary intervention
- PSM
propensity score matching
- STEMI
ST‐segment elevation myocardial infarction
1. Introduction
Enhanced stent visualization (ESV) is a simplified imaging technology designed to improve the accuracy of stent implantation during percutaneous coronary intervention (PCI) [1, 2, 3, 4]. By refining standard coronary angiography, ESV provides clearer delineation of coronary lesions, particularly in the presence of heavy calcification, and supports more precise stent positioning [1, 2, 3, 4]. Although its resolution cannot match that of optical coherence tomography (OCT) or intravascular ultrasound (IVUS), ESV reliably identifies major stent‐related issues such as gross underexpansion or suboptimal alignment, offering practical support in real‐world PCI [1, 2, 3, 4]. Older patients with myocardial infarction (MI) and multivessel coronary disease frequently exhibit complex anatomy, including diffuse disease and severe calcifications, which substantially increase the risk of stent underexpansion and malapposition [5, 6]. These procedural limitations are known contributors to adverse outcomes such as restenosis and stent thrombosis [7, 8, 9]. Despite this, the use of high‐resolution intravascular imaging remains remarkably limited in older MI patients, largely due to concerns related to procedural complexity, additional contrast load, cost, and perceived risk in an already fragile population. As a result, operators often rely on angiography alone, even though advanced imaging would represent the ideal approach for optimizing PCI quality in this setting. In contrast, ESV is widely available and frequently employed, yet its clinical value in older MI patients has never been clearly demonstrated. In particular, while ESV is routinely used to support decision‐making around stent expansion, no study to date has established its prognostic relevance in this population. The FIRE (Functional Assessment in Older MI Patients With Multivessel Disease) trial, which enrolled older patients undergoing PCI for MI, offers a unique opportunity to assess the potential role of ESV in this high‐risk group [10, 11, 12, 13, 14]. The CLASSY‐FIRE sub‐study, a prespecified analysis within the trial, specifically evaluates whether ESV can improve procedural assessment and outcomes in patients with complex coronary lesions. This investigation aims to clarify the real‐world utility of ESV and determine whether this commonly used, but insufficiently studied, tool can meaningfully enhance PCI quality and clinical results in older MI patients.
2. Methods
The FIRE trial was a multicenter, investigator‐initiated, randomized superiority study designed to compare physiology‐guided complete revascularization with a culprit‐only strategy in older patients presenting with MI and multivessel coronary artery disease [10, 11, 12, 13, 14]. The full trial design, baseline characteristics, and primary results have been reported previously [10, 11, 12, 13, 14]. Eligible participants were adults aged ≥ 75 years admitted with either ST‐segment elevation MI (STEMI) or non‐ST‐segment elevation MI (NSTEMI) who underwent successful PCI of the culprit lesion and exhibited at least one non‐culprit coronary stenosis measuring 50%–99% in a vessel with a reference diameter of ≥ 2.5 mm [10, 11, 12, 13, 14]. Key exclusion criteria included uncertainty regarding culprit‐lesion identification, the presence of non‐culprit disease in the left main coronary artery, planned or prior surgical revascularization, and an estimated life expectancy of less than 1 year [10, 11, 12, 13, 14]. All patients provided written informed consent. The study protocol was approved by the institutional review board at each participating center. The trial was registered at ClinicalTrials.gov (identifier NCT03772743). The corresponding author had full access to the complete data set and is responsible for the accuracy and integrity of the analyses. Data supporting this manuscript are available from the FIRE Study Executive Committee upon reasonable request.
2.1. Study Procedures
Patients were randomized between July 18, 2019, and October 25, 2021. In the physiology‐guided complete revascularization arm, all non‐culprit lesions underwent functional evaluation using wire‐based indices—either hyperemic or non‐hyperemic—or angiography‐derived quantitative flow ratio (Medis Medical Imaging Systems, Leiden, The Netherlands) [10, 11, 12, 13, 14]. Lesions identified as functionally significant were subsequently treated with PCI and stent implantation. Conversely, patients allocated to the culprit‐only strategy did not receive any revascularization of non‐culprit lesions, regardless of angiographic severity [10, 11, 12, 13, 14]. In both treatment groups, the use of sirolimus‐eluting, biodegradable‐polymer, ultrathin stents (Supraflex Cruz, Sahajanand Medical Technologies Ltd.) was strongly encouraged. All patients were treated with guideline‐recommended optimal medical therapy throughout the study period.
2.2. ESV and Angiographic Core‐Lab
For this analysis, ESV technology (ClearStent, Siemens Healthineers AG, Erlangen, Germany) was available across participating centers, but its use was not prespecified by the study protocol [10, 11, 12, 13, 14]. Deployment of ESV during PCI, on either culprit or non‐culprit lesions, was left entirely to operator discretion and performed according to local practice. All angiographic datasets were analyzed offline by an independent, blinded core laboratory (University of Ferrara, Italy). The core lab adjudicated whether ESV had been used for any treated lesion and classified patients accordingly into an ESV‐guided or non‐ESV‐guided group. Quantitative coronary analyses were performed using QAngio XA software (Medis Medical Imaging Systems, Leiden, the Netherlands). In patients undergoing ESV, the blinded angiographic core laboratory measured quantitative coronary angiography (QCA)‐derived minimal lumen diameter (MLD) on conventional angiographic frames obtained immediately before and after the corrective maneuvers prompted by the qualitative ESV assessment.
2.3. Study Endpoints
The first objective of this analysis was to quantify the proportion of patients in whom ESV use prompted further procedural optimization. Such optimization was defined as any operator‐initiated maneuver following ESV assessment, including postdilation (initial or repeated, with a larger balloon or higher inflation pressure), implantation of additional stent(s), or the use of advanced intracoronary imaging (IVUS or OCT) to guide or refine the final result. The second objective was to evaluate changes in MLD measured by means of QCA, before and after ESV‐guided optimization, in order to determine the acute luminal gain attributable to ESV‐driven procedural adjustments. Finally, clinical outcomes were compared between patients undergoing ESV‐guided PCI and those treated with angiography‐guided PCI alone. This comparison was based on the primary composite endpoint of the FIRE trial, consisting of death, MI, stroke, or ischemia‐driven revascularization within 3 years of randomization [10, 11, 12, 13, 14]. Secondary endpoints included the composite of cardiovascular death or MI, the individual components of the primary endpoint, and stent thrombosis. All outcome events were reported by site investigators and adjudicated by an independent clinical events committee blinded to treatment allocation, using Academic Research Consortium (ARC) and Bleeding Academic Research Consortium (BARC) definitions [15, 16].
2.4. Statistical Analysis
Normality of continuous variables was assessed using the Shapiro–Wilk test. Continuous variables were reported as mean (SD) or median [IQR], and comparisons were performed using the Student t‐test or Wilcoxon rank‐sum test, as appropriate. Categorical variables were summarized as counts and percentages and compared using Pearson's χ 2 test or Fisher's exact test when required. Time‐to‐event outcomes were analyzed using Kaplan–Meier estimates and Cox proportional‐hazards models, stratifying patients according to whether they underwent ESV‐guided or non‐ESV‐guided PCI. Multivariable models were adjusted for prespecified confounders with established prognostic relevance, including age, sex, diabetes mellitus, prior MI, estimated glomerular filtration rate < 60 mL/min/1.73 m2, peripheral artery disease, clinical presentation, Killip class, and culprit vessel (Table 1). The proportional hazards assumption was verified using Schoenfeld residuals and was satisfied for all outcomes (p > 0.05). To account for competing risks, Fine–Gray subdistribution hazard models were used. For outcomes including cardiovascular death, non‐cardiovascular death was treated as a competing event. For all other secondary and safety endpoints, overall mortality served as the competing risk. Given baseline imbalances between the ESV‐guided and non‐ESV‐guided groups, a propensity score matching (PSM) analysis was performed as a sensitivity approach. The propensity score was estimated using a logistic regression model incorporating the same covariates used for multivariable adjustment. One‐to‐one nearest‐neighbor matching without replacement was applied, using a caliper of 0.2 SD of the logit of the propensity score. This procedure yielded two smaller but closely comparable cohorts with adequate covariate balance across all matched variables. All patients in the ESV‐guided group were successfully matched to a corresponding patient in the non‐ESV‐guided group. Treatment effects on clinical endpoints were then reassessed within the matched population and reported accordingly. All analyses were conducted using R software (R Foundation for Statistical Computing, Vienna, Austria).
Table 1.
Baseline characteristics.
| Characteristic | No ESV (n = 1114) | ESV (n = 331) | p |
|---|---|---|---|
| Age, years | 81 ± 4 | 80 ± 4 | 0.019 |
| Female sex, n (%) | 405 (36.4) | 123 (37.2) | 0.790 |
| Medical history, n (%) | |||
| Hypertension | 903 (81.1) | 282 (85.2) | 0.085 |
| Dyslipidemia | 590 (53.0) | 169 (51.1) | 0.542 |
| Diabetes | 361 (32.4) | 102 (30.8) | 0.591 |
| Current smoker | 92 (8.3) | 31 (9.4) | 0.533 |
| Prior MI | 159 (14.3) | 61 (18.4) | 0.065 |
| Prior PCI | 198 (17.8) | 59 (17.8) | 0.986 |
| History of AF | 154 (13.8) | 46 (13.9) | 0.977 |
| eGFR < 60 mL/min | 56.70 (20.5) | 57.14 (21.6) | 0.748 |
| PAD | 176 (15.8) | 73 (22.1) | 0.008 |
| CVA | 93 (8.3) | 26 (7.9) | 0.771 |
| Clinical presentation | |||
| NSTEMI | 698 (62.7) | 238 (71.9) | 0.002 |
| STEMI | 416 (37.3) | 93 (28.1) | |
| Killip ≥ 2, n (%) | 302 (27.1) | 110 (33.2) | 0.033 |
| LVEF, % | 49.5 (10.6) | 48.2 (11.0) | 0.057 |
| Radial access, n (%) | 1.042 (93.6) | 314 (94.8) | 0.201 |
| Randomization, n (%) | |||
| Culprit‐only | 560 (50.3) | 165 (49.8) | 0.896 |
| Physiology‐guided complete | 554 (49.7) | 166 (50.2) | |
| Culprit vessel, n (%) | n = 1114 | n = 331 | |
| Left main coronary artery | 34 (3.1) | 42 (12.7) | < 0.001 |
| Left anterior descending artery | 496 (44.5) | 163 (49.2) | |
| Circumflex artery | 218 (19.6) | 51 (15.4) | |
| Right coronary artery | 346 (31.1) | 67 (20.2) | |
| Ramus intermedius artery | 20 (1.8) | 8 (2.4) | |
| Non‐culprit vessel, n (%) | n = 1443 | n = 462 | |
| Left anterior descending artery | 468 (32.4) | 119 (25.8) | 0.037 |
| Circumflex artery | 463 (32.1) | 167 (36.1) | |
| Right coronary artery | 468 (32.4) | 165 (35.7) | |
| Ramus intermedius artery | 44 (3.0) | 11 (2.4) |
Abbreviations: AF, atrial fibrillation; CVA, cerebrovascular accident; eGFR, glomerular filtration rate, calculated by CKD‐EPI formula; LVEF, left ventricular ejection fraction; MI, myocardial infarction; NSTEMI, non‐ST‐segment elevation myocardial infarction; PAD, peripheral artery disease; PCI, percutaneous coronary intervention; STEMI, ST‐segment elevation myocardial infarction.
3. Results
A total of 1445 MI patients were included, with 331 patients (793 vessels) categorized as ESV‐guided and 1114 patients (2557 vessels) as non‐ESV‐guided (Table 1). Patients in the ESV‐guided group more frequently presented with NSTEMI, higher Killip class, and a greater prevalence of left main culprit lesions. Other baseline clinical characteristics and cardiovascular risk factors were generally comparable between groups.
3.1. Additional Procedural Interventions Triggered by ESV Use
In the ESV‐guided group (n = 331), ESV prompted further optimization in 85% of procedures. Post‐dilatation with a noncompliant balloon constituted the principal maneuver (96%), predominantly via higher‐pressure inflation (67%). Balloon upsizing was less frequent, while IVUS/OCT use and additional stent implantation occurred in 3% and 1% of cases, respectively.
3.2. Quantitative Impact of ESV‐Guided Optimization on MLD
Across the ESV group, MLD improved from 2.51 [2.22−2.87] to 2.93 [2.41−3.32] mm after ESV‐guided adjustments and optimization (p < 0.001). This acute luminal gain (0.42 mm, 95% CI 0.37–0.47) reflects the mechanical effect of targeted postdilation and other corrective maneuvers performed following ESV assessment.
3.3. ESV and Adverse Events
Over 3 years, 381 primary endpoint events (26.4%) were recorded, including 258 deaths (17.8%), 32 strokes (2.2%), 112 MIs (7.7%), and 112 ischemia‐driven target vessel revascularizations (7.7%). The incidence of the primary endpoint was lower in the ESV‐guided group (unadjusted HR 0.75, 95% CI 0.58–0.97; p = 0.028) (Table 2, Figure 1). After adjustment for baseline confounders, this difference remained significant (adjusted HR 0.70, 95% CI 0.54–0.91; p = 0.008) (Table 2). As shown in Table 2, none of the individual components of the primary endpoint differed significantly between groups, and no differences were observed in safety outcomes.
Table 2.
Clinical outcomes.
| Outcome | No ESV (n = 1114) | ESV (n = 331) | p | Adjusted HR (95% CI)a | p | |
|---|---|---|---|---|---|---|
| Primary outcome | ||||||
| Composite of death, myocardial infarction, stroke, or ischemia‐driven revascularization | n (%) | 310 (27.8) | 71 (21.5) | 0.028 | 0.70 (0.54−0.91) | 0.008 |
| HR (95% CI) | 0.75 (0.58−0.97) | |||||
| Secondary outcomes | ||||||
| Cardiovascular death or myocardial infarction | n (%) | 177 (15.9) | 47 (14.2) | 0.346 | 0.79 (0.56−1.11) | 0.177 |
| HR (95% CI) | 0.85 (0.60−1.19) | |||||
| Death | n (%) | 206 (18.5) | 52 (15.7) | 0.256 | 0.78 (0.57−1.06) | 0.115 |
| HR (95% CI) | 0.84 (0.62−1.14) | |||||
| Cardiovascular death | n (%) | 105 (9.4) | 28 (8.5) | 0.615 | 0.83 (0.54−1.27) | 0.391 |
| HR (95% CI) | 0.90 (0.59−1.36) | |||||
| Myocardial infarction | n (%) | 90 (8.1) | 22(6.6) | 0.407 | 0.72 (0.40−1.29) | 0.267 |
| HR (95% CI) | 0.78 (0.44−1.40) | |||||
| Stroke | n (%) | 30 (2.7) | 2(0.6) | NA | NA | NA |
| HR (95% CI) | NA | |||||
| Ischemia‐driven coronary revascularization | n (%) | 93 (8.3) | 19 (5.7) | 0.153 | 0.59 (0.33−1.06) | 0.076 |
| HR (95% CI) | 0.66 (0.37−1.17) | |||||
| Stent thrombosis | n (%) | 16 (1.4) | 1 (0.3) | NA | NA | NA |
| HR (95% CI) | NA | |||||
| Safety outcomes | ||||||
| Composite of CA‐AKI, stroke, or BARC type 3−5 bleeding | n (%) | 269 (24.1) | 87 (26.3) | 0.141 | 1.13 (0.84−1.51) | 0.414 |
| HR (95% CI) | 1.23 (0.93−1.63) | |||||
| CA‐AKI | n (%) | 186 (16.7) | 59 (17.8) | 0.224 | 1.10 (0.77−1.57) | 0.558 |
| HR (95% CI) | 1.23 (0.88−1.73) | |||||
| BARC type 3−5 bleeding | n (%) | 86 (7.7) | 37 (11.2) | 0.07 | 1.49 (0.93−2.39) | 0.101 |
| HR (95% CI) | 1.53 (0.97−2.43) | |||||
Abbreviations: BARC, Bleeding Academic Research Consortium; CA‐AKI, contrast‐associated acute kidney injury.
Adjusted hazard ratio (HR) for age, sex, diabetes mellitus, prior MI, eGFR< 60 mL/min, PAD, clinical presentation, Killip Class, and culprit vessel.
Figure 1.
Cumulative occurrence of primary endpoint in the study groups. ESV, enhanced stent visualization. [Color figure can be viewed at wileyonlinelibrary.com]
3.4. Propensity‐Score Matched Analysis
In the sensitivity analysis, we used a propensity score model to perform a matched comparison. We matched the 331 ESV‐guided patients with an equal number of non‐ESV‐guided patients (Table 3). This analysis confirmed the lower incidence of the primary endpoint in the ESV‐guided group (HR 0.67; 95% CI 0.49–0.91) (Table 4, Figure 2). This difference was mainly driven by a significant reduction in ischemia‐driven coronary revascularization (HR 0.51; 95% CI 0.27–0.97) (Table 4). As expected, no differences were observed in the safety endpoints.
Table 3.
Baseline characteristics of propensity‐score matched cohorts.
| Characteristic | No ESV (n = 331) | ESV (n = 331) | p |
|---|---|---|---|
| Age, years | 80.3 ± 3 | 80.6 ± 4.5 | 0.634 |
| Female sex, n (%) | 126 (38.1) | 123 (37.2) | 0.816 |
| Medical history, n (%) | |||
| Hypertension | 267 (80.7) | 282 (85.2) | 0.123 |
| Dyslipidemia | 177 (53.5) | 169 (51.1) | 0.538 |
| Diabetes | 114 (34.4) | 102 (30.8) | 0.327 |
| Current smoker | 21 (6.3) | 31 (9.4) | 0.155 |
| Prior MI | 58 (17.5) | 61 (18.4) | 0.761 |
| Prior PCI | 74 (22.4) | 59 (17.8) | 0.155 |
| History of AF | 43 (13.0) | 46 (13.9) | 0.738 |
| eGFR < 60 mL/min | 57.07 (20.99) | 57.14 (21.6) | 0.960 |
| PAD | 79 (23.9) | 73 (22.1) | 0.587 |
| CVA | 26 (7.9) | 26 (7.9) | 0.999 |
| Clinical presentation | |||
| NSTEMI | 236 (71.3) | 238 (71.9) | 0.862 |
| STEMI | 95 (28.7) | 93 (28.1) | |
| Killip ≥ 2, n (%) | 100 (30.2) | 110 (33.2) | 0.403 |
| LVEF, % | 47.93 (11.23) | 48.2 (11.0) | 0.744 |
| Radial access, n (%) | 312 (94.2) | 314 (94.6) | 0.813 |
| Randomization, n (%) | |||
| Culprit‐only | 175 (52.9) | 165 (49.8) | 0.445 |
| Physiology‐guided complete | 156 (47.1) | 166 (50.2) | |
| Culprit vessel, n (%) | n = 331 | n = 331 | |
| Left main coronary artery | 24 (7.2) | 32 (9.7) | 0.169 |
| Left anterior descending artery | 177 (53.4) | 163 (49.2) | |
| Circumflex artery | 57 (17.2) | 51 (15.4) | |
| Right coronary artery | 68 (21.8) | 77 (23.2) | |
| Ramus intermedius artery | 5 (1.5) | 8 (2.4) | |
| Non‐culprit vessel, n (%) | n = 442 | n = 462 | |
| Left anterior descending artery | 104 (24.4) | 119 (26.0) | 0.393 |
| Circumflex artery | 140 (33.2) | 165 (36.0) | |
| Right coronary artery | 162 (38.4) | 163 (35.6) | |
| Ramus intermedius artery | 17 (4.0) | 11 (2.4) |
Abbreviations: AF, atrial fibrillation; CVA, cerebrovascular accident; eGFR, glomerular filtration rate, calculated by CKD‐EPI formula; LVEF, left ventricular ejection fraction; MI, myocardial infarction; NSTEMI, non‐ST‐segment elevation myocardial infarction; PAD, peripheral artery disease; PCI, percutaneous coronary intervention; STEMI, ST‐segment elevation myocardial infarction.
Table 4.
Clinical outcomes of the propensity‐score matched cohorts.
| Outcome | No ESV (n = 331) | ESV (n = 331) | p | |
|---|---|---|---|---|
| Primary outcome | ||||
| Composite of death, myocardial infarction, stroke, or ischemia‐driven revascularization | n (%) | 101 (30.5) | 71 (21.5) | 0.008 |
| HR (95% CI) | 0.67 (0.49−0.91) | |||
| Secondary outcomes | ||||
| Cardiovascular death or myocardial infarction | n (%) | 64 (19.3) | 47 (14.2) | 0.077 |
| HR (95% CI) | 0.71 (0.48−1.06) | |||
| Death | n (%) | 66 (19.9) | 52 (15.7) | 0.166 |
| HR (95% CI) | 0.77 (0.54−1.11) | |||
| Cardiovascular death | no. (%) | 38 (11.5) | 28 (8.5) | 0.199 |
| HR (95% CI) | 0.73 (0.45−1.18) | |||
| Myocardial infarction | n (%) | 32 (9.7) | 22 (6.6) | 0.168 |
| HR (95% CI) | 0.69 (0.35−1.37) | |||
| Stroke | n (%) | 10 (3) | 2 (0.6) | NA |
| HR (95% CI) | NA | |||
| Ischemia‐driven coronary revascularization | n (%) | 36 (10.9) | 19 (5.7) | 0.041 |
| HR (95% CI) | 0.51 (0.27−0.97) | |||
| Stent thrombosis | n (%) | 7 (2.1) | 1 (0.3) | NA |
| HR (95% CI) | NA | |||
| Safety outcomes | ||||
| Composite of CA‐AKI, stroke, or BARC type 3−5 bleeding | n (%) | 94 (28.4) | 87 (26.3) | 0.543 |
| HR (95% CI) | 1.16 (0.81−1.64) | |||
| CA‐AKI | n (%) | 67 (20.2) | 59 (17.8) | 0.434 |
| HR (95% CI) | 1.13 (0.74−1.73) | |||
| BARC type 3−5 bleeding | n (%) | 28 (8.5) | 37 (11.2) | 0.241 |
| HR (95% CI) | 1.73 (0.91−3.26) |
Abbreviations: BARC, Bleeding Academic Research Consortium; CA‐AKI, contrast‐associated acute kidney injury.
Figure 2.
Cumulative occurrence of primary endpoint in the propensity‐score matched subgroups. ESV, enhanced stent visualization. [Color figure can be viewed at wileyonlinelibrary.com]
4. Discussion
In this prespecified analysis of the FIRE trial, we evaluated the role of ESV during PCI in older patients with MI and multivessel disease. In this high‐risk population, ESV use was associated with a high rate of operator‐driven optimization, a measurable acute luminal gain, and a lower incidence of long‐term adverse events. Although ESV does not provide the detailed anatomical information obtainable with IVUS or OCT, our findings suggest that it may serve as a useful adjunct for improving stent deployment quality in settings where intravascular imaging is seldom used. Optimal stent expansion is a cornerstone of durable PCI success [7, 8, 9]. Underexpansion, malapposition, and geographic miss are well‐established predictors of stent failure, contributing to restenosis, thrombosis, and recurrent ischemia [7, 8, 9]. While IVUS and OCT offer unparalleled resolution for assessing stent architecture and lesion morphology, their adoption in routine clinical practice remains limited, particularly in older patients, due to concerns related to procedural complexity, time requirements, contrast volume, and cost. As a result, most stent optimizations still rely on angiography alone, despite its known inability to detect subtle mechanical issues. ESV technologies, such as ClearStent, were developed to partially bridge this gap by enhancing stent visibility without adding procedural steps [1, 2, 3, 4]. Through motion‐correction algorithms and real‐time image enhancement, ESV improves the delineation of stent contour and allows operators to recognize gross underexpansion or geographic miss that may be missed on standard angiography [1, 2, 3, 4]. Although it cannot quantify minimal stent area or characterize plaque, ESV provides actionable information that can prompt additional optimization or selective use of advanced imaging [1, 2, 3, 4].
In our analysis, ESV triggered further operator‐driven refinement in the majority of cases (85%). Most interventions involved additional postdilation with noncompliant balloons, using either higher inflation pressures or larger diameters, and these maneuvers produced a significant acute luminal gain (median +0.42 mm). The specific morphological reason for each corrective maneuver was not prospectively recorded. While modest in absolute terms, such improvements are consistent with established evidence showing the prognostic benefit of achieving adequate stent expansion. Importantly, these corrective actions were performed without increasing procedural complications. The FIRE population reflects real‐world older patients (≥ 75 years) presenting with MI and multivessel disease, a group characterized by extensive calcification, diffuse atherosclerosis, and challenging anatomy [17]. Ironically, these patients are those who would benefit most from imaging‐guided PCI, yet they are the least likely to receive it. In FIRE, IVUS/OCT use was < 5%, mirroring contemporary registries [18]. Within this context, ESV emerges as a practical and feasible adjunct. By enhancing angiographic interpretation, ESV provides an intermediate step between pure angiography‐guided PCI and full imaging‐guided optimization—an approach that may be particularly valuable in older or frail individuals where procedural simplicity is essential. Clinically, ESV use was associated with a significantly lower incidence of the composite primary endpoint at 3 years, and this benefit persisted after comprehensive adjustment. Although this observational analysis cannot infer causality, the findings are biologically plausible. Better acute stent expansion likely facilitates more favorable vessel healing, reduces neointimal proliferation, and lowers the risk of stent failure. Indeed, even small improvements in lumen dimensions can meaningfully reduce shear stress and thrombogenic potential, supporting the mechanistic link between ESV‐guided optimization and clinical benefit.
4.1. Limitations
Several limitations merit consideration. First, ESV use was not randomized and was left to operator discretion, introducing the possibility of selection bias. Because ESV use was not mandated by the trial protocol, acquisition in two orthogonal projections was not systematically required or prospectively recorded. In addition, ESV provides a projection‐dependent two‐dimensional representation of a three‐dimensional stent; orthogonal acquisitions were not standardized, and underexpansion outside the selected projection may therefore have remained undetected. Although multivariable and propensity‐score adjustments were applied, residual confounding cannot be excluded. Second, ESV offers only a qualitative assessment of stent expansion and lacks the quantitative data provided by IVUS or OCT. The observed increase represents an angiographic QCA estimate and should not be interpreted as a direct measurement of minimal stent area or three‐dimensional stent expansion, which requires IVUS or OCT. Third, the observed acute luminal gain, while statistically significant, is modest, and its direct relationship with long‐term healing remains to be fully determined. Because the operator‐reported morphological cause prompting post‐dilatation was not prospectively collected, the relative contributions of focal or diffuse underexpansion, edge abnormalities, and geographic miss could not be separately quantified. Finally, the study was not powered to detect differences in individual clinical endpoints, which should be interpreted with caution.
5. Conclusions
In older MI patients with multivessel disease, ESV use was associated with more frequent procedural optimization, improved acute stent expansion, and lower long‐term adverse events. Although ESV cannot replace intravascular imaging, it represents a practical and effective adjunct for enhancing stent deployment in real‐world settings where imaging remains underused. Wider adoption of ESV may help reduce the gap between angiography‐guided and imaging‐guided PCI, ultimately contributing to safer and more effective revascularization in this vulnerable population.
Ethics Statement
All patients provided written informed consent, and the protocol was approved by the institutional review board at each participating center.
Conflicts of Interest
S.B. received a speaker's fee, a research grant, and performed advisory board activity for Siemens Healthineers. The other authors declare no conflicts of interest.
Acknowledgments
Sahajanand Medical Technologies Ltd. (SMT), Medis Medical Imaging Systems, Eukon S.r.l., Siemens Healthineers, General Electric (GE) Healthcare, and Insight Lifetech provided unrestricted funding to the study sponsor for the conduction of the FIRE trial. These companies had no involvement in the trial design, data collection, analysis, interpretation, or writing of the manuscript. Open access publishing facilitated by Universita degli Studi di Ferrara, as part of the Wiley ‐ CRUI‐CARE agreement.
Data Availability Statement
Data supporting this manuscript are available from the FIRE Study Executive Committee upon reasonable request.
References
- 1. Biscaglia S., Tebaldi M., Tumscitz C., et al., “Prospective Identification of Stent Fracture by Enhanced Stent Visualization System During Percutaneous Coronary Intervention,” Circulation Journal 81, no. 1 (December 2017): 82–89, 10.1253/circj.CJ-16-0785. [DOI] [PubMed] [Google Scholar]
- 2. Sant Bakshsingh V., Bundhoo S. S., and Protty M. B., “The Role of Enhanced Stent Visualization Imaging in Percutaneous Coronary Intervention: A Systematic Review of Efficacy and Clinical Outcomes,” Expert Review of Cardiovascular Therapy 23, no. 12 (October 2025): 915–921, 10.1080/14779072.2025.2574262. [DOI] [PubMed] [Google Scholar]
- 3. Biscaglia S., Campo G., Tebaldi M., et al., “Bioresorbable Vascular Scaffold Overlap Evaluation With Optical Coherence Tomography After Implantation With or Without Enhanced Stent Visualization System (WOLFIE Study): A Two‐Centre Prospective Comparison,” International Journal of Cardiovascular Imaging 32, no. 2 (February 2016): 211–223, 10.1007/s10554-015-0756-1. [DOI] [PubMed] [Google Scholar]
- 4. Biscaglia S., Tumscitz C., Tebaldi M., et al., “Enhanced Stent Visualization Systems During PCI: A Case Series and Review of Literature,” Journal of Cardiology Cases 12, no. 1 (March 2015): 1–5, 10.1016/j.jccase.2015.02.008. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 5. Kovach C. P., Lipinski J., Mesenbring E. C., et al., “Characteristics and Outcomes of PCI Among Patients Ineligible for Surgical Revascularization in the Veterans Affairs Healthcare System,” Circulation: Cardiovascular Interventions 18 (2025): e014899, 10.1161/CIRCINTERVENTIONS.124.014899. [DOI] [PubMed] [Google Scholar]
- 6. Berry N. C., Mauri L., Steg P. G., et al., “Effect of Lesion Complexity and Clinical Risk Factors on the Efficacy and Safety of Dabigatran Dual Therapy Versus Warfarin Triple Therapy in Atrial Fibrillation After Percutaneous Coronary Intervention: A Subgroup Analysis From the REDUAL PCI Trial,” Circulation: Cardiovascular Interventions 13 (2020): e008349, 10.1161/CIRCINTERVENTIONS.119.008349. [DOI] [PubMed] [Google Scholar]
- 7. Yamaji K., Ueki Y., Souteyrand G., et al., “Mechanisms of Very Late Bioresorbable Scaffold Thrombosis,” Journal of the American College of Cardiology 70, no. 19 (November 2017): 2330–2344, 10.1016/j.jacc.2017.09.014. [DOI] [PubMed] [Google Scholar]
- 8. Lee C. W., Kang S. J., Park D. W., et al., “Intravascular Ultrasound Findings in Patients With Very Late Stent Thrombosis After Either Drug‐Eluting or Bare‐Metal Stent Implantation,” Journal of the American College of Cardiology 55, no. 18 (May 2010): 1936–1942, 10.1016/j.jacc.2009.10.077. [DOI] [PubMed] [Google Scholar]
- 9. Fujii K., Carlier S. G., Mintz G. S., et al., “Stent Underexpansion and Residual Reference Segment Stenosis Are Related to Stent Thrombosis After Sirolimus‐Eluting Stent Implantation,” Journal of the American College of Cardiology 45, no. 7 (April 2005): 995–998, 10.1016/j.jacc.2004.12.066. [DOI] [PubMed] [Google Scholar]
- 10. Biscaglia S., Guiducci V., Escaned J., et al., “Complete or Culprit‐Only PCI in Older Patients With Myocardial Infarction,” New England Journal of Medicine 389 (2023): 889–898, 10.1056/NEJMoa2300468. [DOI] [PubMed] [Google Scholar]
- 11. Biscaglia S., Guiducci V., Santarelli A., et al., “Physiology‐Guided Revascularization Versus Optimal Medical Therapy of Nonculprit Lesions in Elderly Patients With Myocardial Infarction: Rationale and Design of the FIRE Trial,” American Heart Journal 229 (2020): 100–109, 10.1016/j.ahj.2020.08.007. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 12. Erriquez A., Campo G., Guiducci V., et al., “Complete vs Culprit‐Only Revascularization in Older Patients With Myocardial Infarction and High Bleeding Risk: A Randomized Clinical Trial,” JAMA Cardiology 9 (2024): 565–573, 10.1001/jamacardio.2024.0804. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 13. Biscaglia S., Erriquez A., Guiducci V., et al., “Physiology‐Guided Complete Revascularization in Older Patients With Myocardial Infarction: Three‐Year Outcomes of a Randomized Clinical Trial,” JAMA Cardiology 10, no. 11 (November 2025): 1130–1137, 10.1001/jamacardio.2025.3099. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 14. Cocco M., Campo G., Guiducci V., et al., “Complete vs Culprit‐Only Revascularization in Older Patients With Myocardial Infarction With or Without ST‐Segment Elevation,” Journal of the American College of Cardiology 84 (2024): 2014–2022. [DOI] [PubMed] [Google Scholar]
- 15. Garcia‐Garcia H. M., McFadden E. P., Farb A., et al., “Standardized End Point Definitions for Coronary Intervention Trials: The Academic Research Consortium‐2 Consensus Document,” Circulation 137 (2018): 2635–2650, 10.1161/CIRCULATIONAHA.117.029289. [DOI] [PubMed] [Google Scholar]
- 16. Mehran R., Rao S. V., Bhatt D. L., et al., “Standardized Bleeding Definitions for Cardiovascular Clinical Trials: A Consensus Report From the Bleeding Academic Research Consortium,” Circulation 123 (2011): 2736–2747, 10.1161/CIRCULATIONAHA.110.009449. [DOI] [PubMed] [Google Scholar]
- 17. Sarti A., Erriquez A., Dal Passo B., et al., “Complete Revascularization in Older Patients With Myocardial Infarction With or Without Complex Nonculprit Lesions,” Circulation: Cardiovascular Interventions 18, no. 11 (October 2025): e015902, 10.1161/CIRCINTERVENTIONS.125.015902. [DOI] [PubMed] [Google Scholar]
- 18. Chaturvedi A., Cellamare M., Verma B. R., et al., “Regional Disparities and Predictors of Intracoronary Imaging Use During Percutaneous Coronary Intervention in the United States,” American Journal of Cardiology 255 (July 2025): 1–9, 10.1016/j.amjcard.2025.06.017. [DOI] [PubMed] [Google Scholar]
Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Data Availability Statement
Data supporting this manuscript are available from the FIRE Study Executive Committee upon reasonable request.