Simplification of continuous intracoronary thermodilution.

BACKGROUND: Continuous intracoronary thermodilution with saline allows for the accurate measurement of volumetric blood flow (Q) and absolute microvascular resistance (Rµ). However, this requires repositioning of the temperature sensor by the operator to measure the entry temperature of the saline infusate, denoted as Ti. AIMS: We evaluated whether Ti could be predicted based on known parameters without compromising the accuracy of calculated Q. This would significantly simplify the technique and render it completely operator independent. METHODS: In a derivation cohort of 371 patients with Q measured both at rest and during hyperaemia, multivariate linear regression was used to derive an equation for the prediction of Ti. Agreement between standard Q (calculated with measured Ti) and simplified Q (calculated with predicted Ti) was assessed in a validation cohort of 120 patients that underwent repeat Q measurements. The accuracy of simplified Q was assessed in a second validation cohort of 23 patients with [15O]H2O positron emission tomography (PET)-derived Q measurements. RESULTS: Simplified Q exhibited strong agreement with standard Q (r=0.94, confidence interval [CI]: 0.93-0.95; intraclass correlation coefficient [ICC] 0.94, CI: 0.92-0.95; both p<0.001). Simplified Q exhibited excellent agreement with PET-derived Q (r=0.86, CI: 0.75-0.92; ICC=0.84, CI: 0.72-0.91; both p<0.001). Compared with standard Q, there were no statistically significant differences between correlation coefficients (p=0.29) or standard deviations of absolute differences with PET-derived Q (p=0.85). CONCLUSIONS: Predicting Ti resulted in an excellent agreement with measured Ti for the assessment of coronary blood flow. It significantly simplifies continuous intracoronary thermodilution and renders absolute coronary flow measurements completely operator independent.

Absolute coronary flow and microvascular resistance before and after transcatheter aortic valve implantation.

BACKGROUND: Severe aortic stenosis (AS) is associated with left ventricular (LV) remodelling, likely causing alterations in coronary blood flow and microvascular resistance. AIMS: We aimed to evaluate changes in absolute coronary flow and microvascular resistance in patients with AS undergoing transcatheter aortic valve implantation (TAVI). METHODS: Consecutive patients with AS undergoing TAVI with non-obstructive coronary artery disease in the left anterior descending artery (LAD) were included. Absolute coronary flow (Q) and microvascular resistance (Rµ) were measured in the LAD using continuous intracoronary thermodilution at rest and during hyperaemia before and after TAVI, and at 6-month follow-up. Total myocardial mass and LAD-specific mass were quantified by echocardiography and cardiac computed tomography. Regional myocardial perfusion (QN) was calculated by dividing absolute flow by the subtended myocardial mass. RESULTS: In 51 patients, Q and R were measured at rest and during hyperaemia before and after TAVI; in 20 (39%) patients, measurements were also obtained 6 months after TAVI. No changes occurred in resting and hyperaemic flow and resistance before and after TAVI nor after 6 months. However, at 6-month follow-up, a notable reverse LV remodelling resulted in a significant increase in hyperaemic perfusion (QN,hyper: 0.86 [interquartile range {IQR} 0.691.06] vs 1.20 [IQR 0.99-1.32] mL/min/g; p=0.008; pre-TAVI and follow-up, respectively) but not in resting perfusion (QN,rest: 0.34 [IQR 0.30-0.48] vs 0.47 [IQR 0.36-0.67] mL/min/g; p=0.06). CONCLUSIONS: Immediately after TAVI, no changes occurred in absolute coronary flow or coronary flow reserve. Over time, the remodelling of the left ventricle is associated with increased hyperaemic perfusion.

Vascular Remodeling in Coronary Microvascular Dysfunction.

BACKGROUND: Approximately half of the patients with angina and nonobstructive coronary artery disease (ANOCA) have evidence of coronary microvascular dysfunction (CMD). OBJECTIVES: This study aims to characterize patients with ANOCA by measuring their minimal microvascular resistance and to examine the pattern of vascular remodeling associated with these measurements. METHODS: The authors prospectively included patients with ANOCA undergoing continuous thermodilution assessment. Lumen volume and vessel-specific myocardial mass were quantified using coronary computed tomography angiography (CTA). CMD was defined as coronary flow reserve <2.5 and high minimal microvascular resistance as >470 WU. RESULTS: A total of 153 patients were evaluated; 68 had CMD, and 22 of them showed high microvascular resistance. In patients with CMD, coronary flow reserve was 1.9 ± 0.38 vs 3.2 ± 0.81 in controls (P < 0.001). Lumen volume was significantly correlated with minimal microvascular resistance (r = -0.59 [95% CI: -0.45 to -0.71]; P < 0.001). In patients with CMD and high microvascular resistance, lumen volume was 40% smaller than in controls (512.8 ± 130.3 mm3 vs 853.2 ± 341.2 mm3; P < 0.001). Epicardial lumen volume assessed by coronary CTA was independently associated with minimal microvascular resistance (P < 0.001). The predictive capacity of lumen volume from coronary CTA for detecting high microvascular resistance showed an area under the curve of 0.79 (95% CI: 0.69-0.88). CONCLUSIONS: Patients with CMD and high minimal microvascular resistance have smaller epicardial vessels than those without CMD. Coronary CTA detected high minimal microvascular resistance with very good diagnostic capacity. Coronary CTA could potentially aid in the diagnostic pathway for patients with ANOCA.

Predictors for Vulnerable Plaque in Functionally Significant Lesions.

BACKGROUND: Vulnerable plaque presents prognostic implications in addition to functional significance. OBJECTIVES: The aim of this study was to identify relevant features of vulnerable plaque in functionally significant lesions. METHODS: In this multicenter, prospective study conducted across 5 countries, including patients who had invasive fractional flow reserve (FFR) ≤0.80, a total of 95 patients with available pullback pressure gradient (PPG) and plaque analysis on coronary computed tomographic angiography and optical coherence tomography were analyzed. Vulnerable plaque was defined as the presence of plaque rupture or thin-cap fibroatheroma on optical coherence tomography. Among the 25 clinical characteristics, invasive angiographic findings, physiological indexes, and coronary computed tomographic angiographic findings, significant predictors of vulnerable plaque were identified. RESULTS: Mean percentage diameter stenosis, FFR, and PPG were 77.8% ± 14.6%, 0.66 ± 0.13, and 0.65 ± 0.13, respectively. Vulnerable plaque was present in 53 lesions (55.8%). PPG and FFR were identified as significant predictors of vulnerable plaque (P < 0.05 for all). PPG >0.65 and FFR ≤0.70 were significantly related to a higher probability of vulnerable plaque after adjustment for each other (OR: 6.75 [95% CI: 2.39-19.1]; P < 0.001] for PPG >0.65; OR: 4.61 [95% CI: 1.66-12.8]; P = 0.003 for FFR ≤0.70). When categorizing lesions according to combined PPG >0.65 and FFR ≤0.70, the prevalence of vulnerable plaque was 20.0%, 57.1%, 66.7%, and 88.2% in the order of PPG ≤0.65 and FFR >0.70, PPG ≤0.65 and FFR ≤0.70, PPG >0.65 and FFR >0.70, and PPG >0.65 and FFR ≤0.70 (P for trend < 0.001), respectively. CONCLUSIONS: Among low-FFR lesions, the presence of vulnerable plaque can be predicted by PPG combined with FFR without additional anatomical or plaque characteristics. (Precise Percutaneous Coronary Intervention Plan [P3] Study; NCT03782688).

AngioPy segmentation: An open-source, user-guided deep learning tool for coronary artery segmentation.

BACKGROUND: Quantitative coronary angiography (QCA) typically employs traditional edge detection algorithms that often require manual correction. This has important implications for the accuracy of downstream 3D coronary reconstructions and computed haemodynamic indices (e.g. angiography-derived fractional flow reserve). We developed AngioPy, a deep-learning model for coronary segmentation that employs user-defined ground-truth points to boost performance and minimise manual correction. We compared its performance without correction with an established QCA system. METHODS: Deep learning models integrating user-defined ground-truth points were developed using 2455 images from the Fractional Flow Reserve versus Angiography for Multivessel Evaluation 2 (FAME 2) study. External validation was performed on a dataset of 580 images. Vessel dimensions from 203 images with mild/moderate stenoses segmented by AngioPy (without correction) and an established QCA system (Medis QFR®) were compared (609 diameters). RESULTS: The top-performing model had an average F1 score of 0.927 (pixel accuracy 0.998, precision 0.925, sensitivity 0.930, specificity 0.999) with 99.2 % of masks exhibiting an F1 score > 0.8. Similar results were seen with external validation (F1 score 0.924, pixel accuracy 0.997, precision 0.921, sensitivity 0.929, specificity 0.999). Vessel dimensions from AngioPy exhibited excellent agreement with QCA (r = 0.96 [95 % CI 0.95-0.96], p < 0.001; mean difference - 0.18 mm [limits of agreement (LOA): -0.84 to 0.49]), including the minimal luminal diameter (r = 0.93 [95 % CI 0.91-0.95], p < 0.001; mean difference - 0.06 mm [LOA: -0.70 to 0.59]). CONCLUSION: AngioPy, an open-source tool, performs rapid and accurate coronary segmentation without the need for manual correction. It has the potential to increase the accuracy and efficiency of QCA.

Validation of virtual fractional flow reserve pullback curves.

BACKGROUND: Angiography-derived fractional flow reserve (virtual FFR) has shown excellent diagnostic performance compared with wire-based FFR. However, virtual FFR pullback curves have not been validated yet. OBJECTIVES: To validate the accuracy of virtual FFR pullback curves compared to wire-based FFR pullbacks and to assess their clinical utility using patient-reported outcomes. METHODS: Pooled analysis of two prospective studies, including patients with hemodynamically significant (FFR ≤ 0.80) coronary artery disease (CAD). Virtual and wire-based FFR pullbacks were compared to assess the accuracy of virtual pullbacks to characterize CAD as focal or diffuse. Pullbacks were analyzed visually and quantitatively using the pullback pressure gradient (PPG). Patients underwent PCI, and the Seattle Angina Questionnaire (SAQ) was administered at 3-month follow-up. RESULTS: A total of 298 patients (300 vessels) with both virtual and wire-based pullbacks who underwent PCI were included in the analysis. The mean age was 61.8 ± 8.8, and 15% were female. The agreement on the visual adjudication of the CAD pattern was fair (Cohen's Kappa: 0.31, 95% confidence interval: 0.18-0.45). The mean PPG were 0.65 ± 0.18 from virtual pullbacks and 0.65 ± 0.13 from wire-based pullbacks (r = 0.68, mean difference 0, limits of agreement -0.27 to 0.28). At follow-up, patients with high virtual PPG (>0.67) had higher SAQ angina frequency scores (i.e., less angina) than those with low virtual PPG (SAQ scores 92.0 ± 14.3 vs. 85.5 ± 23.1, p = 0.022). CONCLUSION: Virtual FFR pullback curves showed moderate agreement with wire-based FFR pullbacks. Nonetheless, patients with focal disease based on virtual PPG reported greater improvement in angina after PCI.

Outcomes According to Coronary Disease Complexity and Optimal Thresholds to Guide Revascularization Approach: FAME 3 Trial.

BACKGROUND: Coronary disease complexity is commonly used to guide revascularization strategy in patients with multivessel disease (MVD). OBJECTIVES: The aim of this study was to assess the interactive effects of coronary complexity on percutaneous coronary intervention (PCI) and coronary artery bypass grafting (CABG) outcomes and identify the optimal threshold at which PCI can be considered a reasonable option. METHODS: A total of 1,444 of 1,500 patients with MVD from the FAME (Fractional Flow Reserve versus Angiography for Multi-vessel Evaluation) 3 randomized trial were included in the analysis (710 CABG vs 734 PCI). SYNTAX (Synergy Between PCI With Taxus and Cardiac Surgery) scores were transformed into restricted cubic splines, and logistic regression models were fitted, with multiplicative interaction terms for revascularization strategy. Optimal thresholds at which PCI is a reasonable alternative to CABG were determined on the basis of Cox regression model performance. RESULTS: The mean SYNTAX score (SS) was 25.9 ± 7.1. SS was associated with 1-year major adverse cardiac and cerebrovascular events among PCI patients and 3-year death, myocardial infarction, and stroke among CABG patients. Significant interactions were present between revascularization strategy and SS for 1- and 3-year composite endpoints (P for interaction <0.05 for all). In Cox regression models, outcomes were comparable between CABG and PCI for the 3-year primary endpoint for SS ≤24 (P = 0.332), with 44% of patients below this threshold and 32% below the conventional SS threshold of ≤22. CONCLUSIONS: In patients with MVD without left main disease, PCI and CABG outcomes remain comparable up to SS values in the mid- rather than low 20s, which allows the identification of a greater proportion of patients in whom PCI may be a reasonable alternative to CABG.

Advanced CT Imaging for the Assessment of Calcific Coronary Artery Disease and PCI Planning.

Vascular calcification is a hallmark of atherosclerosis and adds considerable challenges for percutaneous coronary intervention (PCI). This review underscores the critical role of coronary computed tomography (CT) angiography in assessing and quantifying vascular calcification for optimal PCI planning. Severe calcification significantly impacts procedural outcomes, necessitating accurate preprocedural evaluation. We describe the potential of coronary CT for calcium assessment and how CT may enhance precision in device selection and procedural strategy. These advancements, along with the ongoing Precise Procedural and PCI Plan study, represent a transformative shift toward personalized PCI interventions, ultimately improving patient outcomes in the challenging landscape of calcified coronary lesions.

A randomised trial of selective intracoronary hypothermia during primary PCI.

BACKGROUND: While experimental data suggest that selective intracoronary hypothermia decreases infarct size, studies in patients with ST-elevation myocardial infarction (STEMI) are lacking. AIMS: We investigated the efficacy of selective intracoronary hypothermia during primary percutaneous coronary intervention (PCI) to decrease infarct size in patients with STEMI. METHODS: In this multicentre randomised controlled trial, 200 patients with large anterior wall STEMI were randomised 1:1 to selective intracoronary hypothermia during primary PCI or primary PCI alone. Using an over-the-wire balloon catheter for infusion of cold saline and a pressure-temperature wire to monitor the intracoronary temperature, the anterior myocardium distal to the occlusion was selectively cooled to 30-33°C for 7-10 minutes before reperfusion (occlusion phase), immediately followed by 10 minutes of cooling after reperfusion (reperfusion phase). The primary endpoint was infarct size as a percentage of left ventricular mass on cardiovascular magnetic resonance imaging after 3 months. RESULTS: Selective intracoronary hypothermia was performed in 94/100 patients randomised to cooling. Distal coronary temperature decreased by 6°C within 43 seconds (interquartile range [IQR] 18-113). The median duration of the occlusion phase and reperfusion phase were 8.2 minutes (IQR 7.2-9.0) and 9.1 minutes (IQR 8.2-10.0), respectively. The infarct size at 3 months was 23.1±12.5% in the selective intracoronary hypothermia group and 21.6±12.2% in the primary PCI alone group (p=0.43). The left ventricular ejection fraction at 3 months in each group were 49.1±10.2% and 50.1±10.4%, respectively (p=0.53). CONCLUSIONS: Selective intracoronary hypothermia during primary PCI in patients with anterior wall STEMI was feasible and safe but did not decrease infarct size compared with standard primary PCI. (ClinicalTrials.gov: NCT03447834).

Stent sizing by coronary CT angiography compared with optical coherence tomography.

BACKGROUND: Coronary CT angiography (CCTA) is well-established for diagnosis and stratification of coronary artery disease (CAD). Its usefulness in guiding percutaneous coronary interventions (PCI) and stent sizing is unknown. METHODS: This is a sub-analysis of the Precise Percutaneous Coronary Intervention Plan (P3) study (NCT03782688). We analyzed 65 vessels with matched CCTA and pre-PCI optical coherence tomography (OCT) assessment. The CCTA-guided stent size was defined by the mean distal reference lumen diameter rounded up to the nearest stent diameter. The OCT lumen-guided stent size was the mean distal reference lumen diameter rounded to the closest stent diameter. The agreement on stent diameters was determined with Kappa statistics, Passing-Bablok regression analysis, and the Bland-Altman method. RESULTS: The distal reference lumen diameter by CCTA and OCT were 2.75 â€‹± â€‹0.53 â€‹mm and 2.72 â€‹± â€‹0.55 â€‹mm (mean difference 0.06, limits of agreement -0.7 to 0.82). There were no proportional or systematic differences (coefficient A 1.06, 95% CI 0.84 to 1.3 and coefficient B -0.22, 95% CI -0.83 to 0.36) between methods. The agreement between the CCTA and OCT stent size was substantial (Cohen's weighted Kappa 0.74, 95% CI 0.64 to 0.85). Compared to OCT stent diameter, CCTA stent size was concordant in 52.3% of the cases; CCTA overestimated stent size in 20.0% and underestimated in 27.7%. CONCLUSION: CCTA accurately assessed the reference vessel diameter used for stent sizing. CCTA-based stent sizing showed a substantial agreement with OCT. CCTA allows for PCI planning and may aid in selecting stent diameter.

The Influence of Epicardial Resistance on Microvascular Resistance Reserve.

BACKGROUND: The optimal index of microvascular function should be specific for the microvascular compartment. Yet, coronary flow reserve (CFR), despite being widely used to diagnose coronary microvascular dysfunction (CMD), is influenced by both epicardial and microvascular resistance. Conversely, microvascular resistance reserve (MRR) adjusts for fractional flow reserve (FFR), and thus is theoretically independent of epicardial resistance. OBJECTIVES: The authors tested the hypothesis that MRR, unlike CFR, is not influenced by increasing epicardial resistance, and thus is a more specific index of microvascular function. METHODS: In a cohort of 16 patients who had undergone proximal left anterior descending artery stenting, we created 4 grades of artificial stenosis (no stenosis, mild, moderate, and severe) using a coronary angioplasty balloon inflated to different degrees within the stent. For each stenosis grade, we calculated CFR and MRR using continuous thermodilution (64 measurements of each) to assess their response to changing epicardial resistance. RESULTS: Graded balloon inflation resulted in a significant sequential decrease in mean FFR (no stenosis: 0.82 ± 0.05; mild: 0.72 ± 0.04; moderate: 0.61 ± 0.05; severe: 0.48 ± 0.09; P < 0.001). This translated into a linear decrease in mean hyperemic coronary flow (no stenosis: 170.5 ± 66.8 mL/min; mild: 149.8 ± 58.8 mL/min; moderate: 124.4 ± 53.0 mL/min; severe: 94.0 ± 45.2 mL/min; P < 0.001). CFR exhibited a marked linear decrease with increasing stenosis (no stenosis: 2.5 ± 0.9; mild: 2.2 ± 0.8; moderate: 1.8 ± 0.7; severe: 1.4 ± 0.6), corresponding to a decrease of 0.3 for a decrease in FFR of 0.1 (P < 0.001). In contrast, MRR exhibited a negligible decrease across all stenosis grades (no stenosis: 3.0 ± 1.0; mild: 3.0 ± 1.0; moderate: 2.9 ± 1.0; severe: 2.8 ± 1.0), corresponding to a decrease of just 0.05 for a decrease in FFR of 0.1 (P < 0.001). CONCLUSIONS: MRR, unlike CFR, is minimally influenced by epicardial resistance, and thus should be considered the more specific index of microvascular function. This suggests that MRR can also reliably evaluate microvascular function in patients with significant epicardial disease.

Artificial Intelligence-Enabled Quantitative Coronary Plaque and Hemodynamic Analysis for Predicting Acute Coronary Syndrome.

BACKGROUND: A lesion-level risk prediction for acute coronary syndrome (ACS) needs better characterization. OBJECTIVES: This study sought to investigate the additive value of artificial intelligence-enabled quantitative coronary plaque and hemodynamic analysis (AI-QCPHA). METHODS: Among ACS patients who underwent coronary computed tomography angiography (CTA) from 1 month to 3 years before the ACS event, culprit and nonculprit lesions on coronary CTA were adjudicated based on invasive coronary angiography. The primary endpoint was the predictability of the risk models for ACS culprit lesions. The reference model included the Coronary Artery Disease Reporting and Data System, a standardized classification for stenosis severity, and high-risk plaque, defined as lesions with ≥2 adverse plaque characteristics. The new prediction model was the reference model plus AI-QCPHA features, selected by hierarchical clustering and information gain in the derivation cohort. The model performance was assessed in the validation cohort. RESULTS: Among 351 patients (age: 65.9 ± 11.7 years) with 2,088 nonculprit and 363 culprit lesions, the median interval from coronary CTA to ACS event was 375 days (Q1-Q3: 95-645 days), and 223 patients (63.5%) presented with myocardial infarction. In the derivation cohort (n = 243), the best AI-QCPHA features were fractional flow reserve across the lesion, plaque burden, total plaque volume, low-attenuation plaque volume, and averaged percent total myocardial blood flow. The addition of AI-QCPHA features showed higher predictability than the reference model in the validation cohort (n = 108) (AUC: 0.84 vs 0.78; P < 0.001). The additive value of AI-QCPHA features was consistent across different timepoints from coronary CTA. CONCLUSIONS: AI-enabled plaque and hemodynamic quantification enhanced the predictability for ACS culprit lesions over the conventional coronary CTA analysis. (Exploring the Mechanism of Plaque Rupture in Acute Coronary Syndrome Using Coronary Computed Tomography Angiography and Computational Fluid Dynamics II [EMERALD-II]; NCT03591328).

Influence of Pathophysiologic Patterns of Coronary Artery Disease on Immediate Percutaneous Coronary Intervention Outcomes.

BACKGROUND: Diffuse coronary artery disease affects the safety and efficacy of percutaneous coronary intervention (PCI). Pathophysiologic coronary artery disease patterns can be quantified using fractional flow reserve (FFR) pullbacks incorporating the pullback pressure gradient (PPG) calculation. This study aimed to establish the capacity of PPG to predict optimal revascularization and procedural outcomes. METHODS: This prospective, investigator-initiated, single-arm, multicenter study enrolled patients with at least one epicardial lesion with an FFR ≤0.80 scheduled for PCI. Manual FFR pullbacks were used to calculate PPG. The primary outcome of optimal revascularization was defined as an FFR ≥0.88 after PCI. RESULTS: A total of 993 patients with 1044 vessels were included. The mean FFR was 0.68±0.12, PPG 0.62±0.17, and the post-PCI FFR was 0.87±0.07. PPG was significantly correlated with the change in FFR after PCI (r=0.65 [95% CI, 0.61-0.69]; P<0.001) and demonstrated excellent predictive capacity for optimal revascularization (area under the receiver operating characteristic curve, 0.82 [95% CI, 0.79-0.84]; P<0.001). FFR alone did not predict revascularization outcomes (area under the receiver operating characteristic curve, 0.54 [95% CI, 0.50-0.57]). PPG influenced treatment decisions in 14% of patients, redirecting them from PCI to alternative treatment modalities. Periprocedural myocardial infarction occurred more frequently in patients with low PPG (<0.62) compared with those with focal disease (odds ratio, 1.71 [95% CI, 1.00-2.97]). CONCLUSIONS: Pathophysiologic coronary artery disease patterns distinctly affect the safety and effectiveness of PCI. PPG showed an excellent predictive capacity for optimal revascularization and demonstrated added value compared with an FFR measurement. REGISTRATION: URL: https://www.clinicaltrials.gov; Unique identifier: NCT04789317.

Impact of vessel volume on thermodilution measurements in patients with coronary microvascular dysfunction.

BACKGROUND: Two invasive methods are available to estimate microvascular resistance: bolus and continuous thermodilution. Comparative studies have revealed a lack of concordance between measurements of microvascular resistance obtained through these techniques. AIMS: This study aimed to examine the influence of vessel volume on bolus thermodilution measurements. METHODS: We prospectively included patients with angina with non-obstructive coronary arteries (ANOCA) undergoing bolus and continuous thermodilution assessments. All patients underwent coronary CT angiography to extract vessel volume. Coronary microvascular dysfunction was defined as coronary flow reserve (CFR) < 2.0. Measurements of absolute microvascular resistance (in Woods units) and index of microvascular resistance (IMR) were compared before and after volumetric adjustment. RESULTS: Overall, 94 patients with ANOCA were included in this study. The mean age was 64.7 ± 10.8 years, 48% were female, and 19% had diabetes. The prevalence of CMD was 16% based on bolus thermodilution, while continuous thermodilution yielded a prevalence of 27% (Cohen's Kappa 0.44, 95% CI 0.23-0.65). There was no correlation in microvascular resistance between techniques (r = 0.17, 95% CI -0.04 to 0.36, p = 0.104). The adjustment of IMR by vessel volume significantly increased the agreement with absolute microvascular resistance derived from continuous thermodilution (r = 0.48, 95% CI 0.31-0.63, p < 0.001). CONCLUSIONS: In patients with ANOCA, invasive methods based on coronary thermodilution yielded conflicting results for the assessment of CMD. Adjusting IMR with vessel volume improved the agreement with continuous thermodilution for the assessment of microvascular resistance. These findings strongly suggest the importance of considering vessel volume when interpreting bolus thermodilution assessment.