Microvascular dysfunction following primary percutaneous coronary intervention (pPCI) is a well-established determinant of adverse outcomes in ST-segment elevation myocardial infarction (STEMI) patients. Although the invasive Index of Microcirculatory Resistance (IMR) has demonstrated prognostic value, its reliance on thermodilution limits its routine applicability. Angiography-derived functional indices, already validated in the epicardial domain, may offer a simplified, non-invasive alternative for microvascular assessment. To evaluate the prognostic performance of the angiography-derived Index of Microcirculatory Resistance (AngioIMR), we retrospectively analyzed 180 consecutive patients undergoing percutaneous coronary intervention (pPCI) for anterior STEMI at Fondazione Poliambulanza, Brescia, between January 1, 2016, and February 1, 2024. AngioIMR was computed using the formula: AngioIMR = MAP × QFR × TFC. The primary endpoint was a composite of all-cause death, target vessel myocardial infarction, or hospitalization for heart failure. The secondary endpoint additionally included hospitalization for angina. Over a 5-years follow-up, primary and secondary endpoints occurred in 16 (8.9%) and 23 (13%) patients, respectively. The optimal AngioIMR cut-off was 43 (AUC 0.800; 95% CI: 0.714–0.887; p <0.001), with sensitivity 87.5%, specificity 63.4%, PPV 18.9%, and NPV 98.1%. The incidence of both the primary and secondary endpoints were significantly higher in patients with AngioIMR ≥ 43: 18.9% versus 1.9% (p <0.001) and 28.4% versus 1.9% (p <0.001), respectively. AngioIMR ≥ 43 was associated with increased risk of adverse outcomes (HR: 9.5; 95% CI: 2.2–42.0; p <0.001), and remained an independent predictor at multivariable analysis. In conclusion, AngioIMR may be a promising tool to stratify prognosis in patients with STEMI.
Graphical abstract
1 Patients undergoing successful primary PCI for anterior STEMI were enrolled. 2 Angiography-derived Index of Microvascular Resistance was measured, and patients divided in 2 groups according to the derived cut-off. 3. The primary composite endpoint differed significantly between the 2 groups.
The advent of PCI led to a considerable prognostic improvement in patients suffering from ST-segment elevation myocardial infarction (STEMI). However, despite the marked improvements in acute-phase treatment, along with shorter to door-to-balloon time, a considerable proportion of patients with STEMI develop mid and long-term complications.
In recent years, microvascular injury has been increasingly recognized as a key contributor to this process. Traditionally, microvascular damage has been visually assessed via final angiograms and classified using the TIMI Flow Grade, a widely accepted and validated scale. While reliable in detecting overt flow impairment, this method lacks sensitivity in less evident cases.
To address this limitation, novel methods have been proposed for improved risk stratification. Fearon et al. demonstrated that an Index of Microvascular Resistance (IMR) > 40 units is predictive of poor outcomes. However, IMR requires the use of thermistor-equipped pressure wire and the administration of adenosine, so that the high costs and procedural risks associated with this technique limit its use in the clinical practice.
To overcome these limitations, angiography-derived alternatives have been developed using computational fluid dynamics. , The present study was designed to assess the potential utility of the angiography-derived Index of Microcirculatory Resistance (AngioIMR) as a feasible tool for risk stratification in STEMI patients following primary PCI (Central Illustration).
Methods
The study was conducted in accordance with the Declaration of Helsinki, and it was approved by our Institutional Ethic Committee. All patients provided written informed consent.
Study design and population
This is a single-center, retrospective, observational study conducted at Fondazione Poliambulanza, Brescia, Italy. All consecutive patients were considered eligible for inclusion if they were older than 18 years and had been admitted to the hospital between January 1, 2016, and February 1, 2024, with a diagnosis of STEMI and the culprit lesion located in the LAD. Patients were excluded if they met any of the following criteria:
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Complex (or unsuitable for QFR analysis) coronary anatomy, namely concomitant chronic total occlusions or surgical grafts, residual ostial disease or side branch involvement in bifurcation lesions, extreme vascular tortuosity and/or intramyocardial bridges.
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Post-pPCI QFR value < 0.80.
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TIMI Flow Grade < 3 at the end of the procedure.
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Out-of-hospital cardiac arrest, cardiogenic shock, or the need for mechanical circulatory support (MCS).
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Prior STEMI involving the LAD.
Baseline clinical, laboratory, echocardiographic and angiographic characteristics of all included patients were collected.
Pharmacologic management
All patients were treated according to local practice and the best available evidence. Unfractionated heparin was administered for procedural anticoagulation as per standard protocol, while intracoronary nitrates were given at the end of the procedure when feasible. All patients received long-term acetylsalicylic acid (100 mg/day) and a P2Y12 inhibitor for 12 months. Guideline-directed optimal medical therapy was prescribed in accordance with current European Society of Cardiology recommendations.
Computational analysis
AngioIMR calculation was performed using the QAngio XA 3D software [Quantitative Flow Ratio (QFR), version 2.2, Medis Medical Imaging, Leiden, Netherlands]. Only the final angiograms- done at the end of the procedure to check the result- were selected if they met technical standards. For each case, QFR was computed from the 3-dimensional vessel’s reconstruction derived from 2 angiographic projections at least 25° apart, while the microvascular assessment was done with the following formula, as previously described:
MAP is the mean arterial pressure; QFR is the pressure ratio virtually estimated with Quantitative Flow Ratio; TFC is the ratio between the number of frames ( N°Frames ) necessary for contrast dye to travel from the coronary ostium to the distal reference and the acquisition rate [ Frames Per Second (FPS) = 15 frames per second], and it was automatically computed by the QFR software. The MAP value was the invasive one recorded by nurses at the end of the procedure, when available. All the analyses were performed by a dedicated physician (C.P.B.), who was unaware of patients’ medical history and in possession of the certification for proper QFR use.
Follow-up and outcome
After the index procedure, in-hospital outcomes were collected. Patients were subsequently followed at the hospital’s outpatient clinic, and follow-up data were recorded in the electronic medical record system, from which they were extracted for analysis. When information was unavailable in the system, follow-up was completed via telephone interviews. Follow-up duration was calculated from the index procedure to the last medical contact, and censored at 5 years if longer. The primary endpoint was a composite of all-cause death, target vessel myocardial infarction, or hospitalization for heart failure. The secondary endpoint additionally included hospitalization for angina with no evidence of obstructive epicardial disease at the subsequent angiography. All clinical events were adjudicated by 3 independent reviewers blinded to AngioIMR values. Adjudication was based on review of electronic health records, hospital discharge summaries, and outpatient documentation. Discrepancies were resolved by consensus, and patients were excluded from the analysis in case of missing information.
Statistical analysis
The distribution of continuous variables was assessed using the Shapiro–Wilk test and visual inspection of histograms. Continuous variables are reported as mean ± standard deviation (SD) for normally distributed data and as median with interquartile range (IQR) for non-normally distributed data. Categorical variables are expressed as absolute numbers and percentages.
Comparisons between groups were performed using the unpaired Student’s t-test for normally distributed continuous variables and the Mann–Whitney U test for non-normally distributed variables. Categorical variables were compared using the χ² test or Fisher’s exact test, as appropriate. A 2-sided p value <0.05 was considered statistically significant.
Receiver operating characteristic (ROC) curve analysis was conducted to evaluate the discriminative performance of AngioIMR, and the optimal cut-off value of AngioIMR was identified using the Youden Index to maximize sensitivity and specificity.
Event-free survival was analyzed using the Kaplan-Meier method and compared between groups using the log-rank test. Cox proportional hazards regression was used to evaluate the association between the optimal binary cut-off value of AngioIMR and the primary endpoint. Variables with p <0.05 in univariate analysis were considered for inclusion in the multivariate model. No imputation for missing data was undertaken, as the variables required for endpoint adjudication and statistical modelling were fully available for all included patients.
All statistical analyses were performed using SPSS software, version 29.0 (IBM Corp., Armonk, NY).
Results
Study population
Of the 440 patients who underwent pPCI in the LAD and were initially screened, 180 were ultimately included in the final analysis ( Figure 1 ). A total of 138 patients were excluded due to technical (112 cases) or anatomical (26 cases) constraints limiting QFR computation. In 29 cases, medical records were either incomplete or no longer available within the computer system. Furthermore, at the end of the procedure, 49 patients exhibited less than TIMI 3 flow and 8 patients had a final QFR value below 0.80. Finally, 36 patients presented with out-of-hospital cardiac arrest, cardiogenic shock and/or the need for MCS.
Flowchart illustrating the final cohort of enrolled patients after screening 440 potentially eligible individuals.
Baseline clinical, laboratory, echocardiographic and angiographic findings are summarized in Table 1 , while post-PCI characteristics are shown in Table 2 . The mean age was 64 years, and 83% of the patients were male. The most prevalent cardiovascular risk factors were hypertension (54%) and current or former smoking habit (47%). A small proportion of patients had a history of prior myocardial infarction (8%) or previous PCI (7%). The average left ventricular ejection fraction (LVEF) at presentation- either in the emergency department or upon admission to the coronary care unit- was 40%, improving to a mean of 51% at discharge. Only 12% of patients exhibited severely reduced LVEF (<40%) at discharge. More than half of the cohort had single-vessel disease and presented with complete occlusion (TIMI 0 flow). Total ischemic time was less than 2 hours in approximately 68% of cases, and the mean door-to-balloon time was 53 minutes; only 5 patients (3.2%) received a P2Y12 inhibitor loading dose before angiography. Manual thrombus aspiration was performed in 21% of patients, while a drug-eluting stent was implanted in 177 cases (98%). Plain old balloon angioplasty (POBA) was performed in 2 cases and a drug-coated balloon (DCB) was used in only 1 patient. Glycoprotein IIb/IIIa inhibitors and Cangrelor were administered in 8% and 7% of cases, respectively. The mean postprocedural QFR and AngioIMR values were 0.94 (interquartile range: 0.90–0.98) and 40 (interquartile range: 31–47), respectively. Procedural data are shown in Table 2 . All patients were prescribed acetylsalicylic acid (100 mg/day) indefinitely and a P2Y12 inhibitor for 12 months after the index procedure, while optimal medical therapy was administered according to current guidelines from the European Society of Cardiology.
Table 1
Baseline clinical, laboratory and angiographic findings
| AngioIMR <43 ( n = 106) | AngioIMR ≥43 ( n = 74) | p-value | |
|---|---|---|---|
| Age, years | 63 ± 14 | 66 ± 15 | 0.10 |
| BMI | 26.5 ± 4.9 | 26 ± 3.4 | 0.39 |
| Male, n (%) | 85 (80.2%) | 64 (86.5%) | 0.27 |
| Hypertension, n (%) | 57 (53.8%) | 40 (54.1%) | 0.97 |
| Diabetes mellitus, n (%) | 18 (17.0%) | 10 (13.5%) | 0.57 |
| Smoking habit, n (%) | 52 (49.1%) | 32 (43.2%) | 0.41 |
| Dyslipidaemia, n (%) | 44 (41.5%) | 20 (27.0%) | 0.057 |
| CKD, n (%) | 16 (15.1%) | 14 (18.9%) | 0.52 |
| Cerebrovascular events, n (%) | 2 (1.9%) | 2 (2.7%) | 0.72 |
| Carotid plaque (>50%), n (%) | 12 (11.3%) | 7 (9.5%) | 0.69 |
| Atrial Fibrillation, n (%) | 3 (2.8%) | 4 (5.4%) | 0.38 |
| Previous MI, n (%) | 8 (7.5%) | 7 (9.5%) | 0.66 |
| Previous PCI, n (%) | 6 (5.7%) | 6 (8.1%) | 0.52 |
| LVEF at admission, % | 41.5 [38–46] | 40.0 [35–45] | 0.089 |
| hsTnI at admission (ng/L) | 65 [21–341] | 162 [34–1,026] | 0.039 |
| TIMI flow 0 at admission, n (%) | 63 (59.4%) | 43 (58.1%) | 0.86 |
| TIMI flow 1 at admission, n (%) | 6 (5.7%) | 3 (4.1%) | 0.63 |
| TIMI flow 2 at admission, n (%) | 12 (11.3%) | 11 (14.9%) | 0.48 |
| TIMI flow 3 at admission, n (%) | 20 (18.9%) | 16 (21.6%) | 0.65 |
| Ischemic time <2 hours, n (%) | 78 (73.6%) | 44 (59.5%) | 0.13 |
| Door-to-balloon time (minutes) | 55 (38–66) | 49 (34–63) | 0.39 |
| Single-vessel disease, n (%) | 61 (57.5%) | 37 (50.0%) | 0.39 |
| Two-vessel disease, n (%) | 23 (21.7%) | 24 (32.4%) | 0.087 |
| Three-vessel disease, n (%) | 20 (18.9%) | 10 (13.5%) | 0.38 |
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