Cardiac computed tomography-derived myocardial mass at risk using the Voronoi-based segmentation algorithm: A histological validation study

Measuring Absolute Coronary Flow and Microvascular Resistance by Thermodilution: JACC Review Topic of the Week

Diagnosing coronary microvascular dysfunction remains challenging, primarily due to the lack of direct measurements of absolute coronary blood flow (Q) and microvascular resistance (Rμ). However, there has been recent progress with the development and validation of continuous intracoronary thermodilution, which offers a simplified and validated approach for clinical use. This technique enables direct quantification of Q and Rμ, leading to precise and accurate evaluation of the coronary microcirculation. To ensure consistent and reliable results, it is crucial to follow a standardized protocol when performing continuous intracoronary thermodilution measurements. This document aims to summarize the principles of thermodilution-derived absolute coronary flow measurements and propose a standardized method for conducting these assessments. The proposed standardization serves as a guide to ensure the best practice of the method, enhancing the clinical assessment of the coronary microcirculation.

Changes in post-PCI physiology based on anatomical vessel location: a DEFINE PCI substudy

BACKGROUND

Anatomical vessel location affects post-percutaneous coronary intervention (PCI) physiology.

AIMS

We aimed to compare the post-PCI instantaneous wave-free ratio (iFR) in left anterior descending (LAD) versus non-LAD vessels and to identify the factors associated with a suboptimal post-PCI iFR.

METHODS

DEFINE PCI was a multicentre, prospective, observational study in which a blinded post-PCI iFR pullback was used to assess residual ischaemia following angiographically successful PCI.

RESULTS

Pre- and post-PCI iFR recordings of 311 LAD and 195 non-LAD vessels were compared. Though pre-PCI iFR in the LAD vessels (median 0.82 [0.63, 0.86]) were higher compared with those in non-LAD vessels (median 0.72 [0.49, 0.84]; p<0.0001), post-PCI iFR were lower in the LAD vessels (median 0.92 [0.88, 0.94] vs 0.98 [0.95, 1.00]; p<0.0001). The prevalence of a suboptimal post-PCI iFR of <0.95 was higher in the LAD vessels (77.8% vs 22.6%; p<0.0001). While the overall frequency of residual physiological diffuse disease (31.4% vs 38.6%; p=0.26) and residual focal disease in the non-stented segment (49.6% vs 50.0%; p=0.99) were similar in both groups, residual focal disease within the stented segment was more common in LAD versus non-LAD vessels (53.7% vs 27.3%; p=0.0009). Improvement in iFR from pre- to post-PCI was associated with angina relief regardless of vessel location.

CONCLUSIONS

After angiographically successful PCI, post-PCI iFR is lower in the LAD compared with non-LAD vessels, resulting in a higher prevalence of suboptimal post-PCI iFR in LAD vessels. This difference is, in part, due to a greater frequency of a residual focal pressure gradient within the stented segment which may be amenable to more aggressive PCI.

Coronary CT Angiography in the Cath Lab: Leveraging Artificial Intelligence to Plan and Guide Percutaneous Coronary Intervention

The role of coronary CT angiography for the diagnosis and risk stratification of coronary artery disease is well established. However, its potential beyond the diagnostic phase remains to be determined. The current review focuses on the insights that coronary CT angiography can provide when planning and performing percutaneous coronary interventions. We describe a novel approach incorporating anatomical and functional pre-procedural planning enhanced by artificial intelligence, computational physiology and online 3D CT guidance for percutaneous coronary interventions. This strategy allows the individualisation of patient selection, optimisation of the revascularisation strategy and effective use of resources.

Non-Contrast and Contrast-Enhanced Cardiac Computed Tomography Imaging in the Diagnostic and Prognostic Evaluation of Coronary Artery Disease

In recent decades, cardiac computed tomography (CT) has emerged as a powerful non-invasive tool for risk stratification, as well as the detection and characterization of coronary artery disease (CAD), which remains the main cause of morbidity and mortality in the world. Advances in technology have favored the increasing use of cardiac CT by allowing better performance with lower radiation doses. Coronary artery calcium, as assessed by non-contrast CT, is considered to be the best marker of subclinical atherosclerosis, and its use is recommended for the refinement of risk assessment in low-to-intermediate risk individuals. In addition, coronary CT angiography (CCTA) has become a gate-keeper to invasive coronary angiography (ICA) and revascularization in patients with acute chest pain by allowing the assessment not only of the extent of lumen stenosis, but also of its hemodynamic significance if combined with the measurement of fractional flow reserve or perfusion imaging. Moreover, CCTA provides a unique incremental value over functional testing and ICA by imaging the vessel wall, thus allowing the assessment of plaque burden, composition, and instability features, in addition to perivascular adipose tissue attenuation, which is a marker of vascular inflammation. There exists the potential to identify the non-obstructive lesions at high risk of progression to plaque rupture by combining all of these measures.

Tissue-growth-based synthetic tree generation and perfusion simulation

Biological tissues receive oxygen and nutrients from blood vessels by developing an indispensable supply and demand relationship with the blood vessels. We implemented a synthetic tree generation algorithm by considering the interactions between the tissues and blood vessels. We first segment major arteries using medical image data and synthetic trees are generated originating from these segmented arteries. They grow into extensive networks of small vessels to fill the supplied tissues and satisfy the metabolic demand of them. Further, the algorithm is optimized to be executed in parallel without affecting the generated tree volumes. The generated vascular trees are used to simulate blood perfusion in the tissues by performing multiscale blood flow simulations. One-dimensional blood flow equations were used to solve for blood flow and pressure in the generated vascular trees and Darcy flow equations were solved for blood perfusion in the tissues using a porous model assumption. Both equations are coupled at terminal segments explicitly. The proposed methods were applied to idealized models with different tree resolutions and metabolic demands for validation. The methods demonstrated that realistic synthetic trees were generated with significantly less computational expense compared to that of a constrained constructive optimization method. The methods were then applied to cerebrovascular arteries supplying a human brain and coronary arteries supplying the left and right ventricles to demonstrate the capabilities of the proposed methods. The proposed methods can be utilized to quantify tissue perfusion and predict areas prone to ischemia in patient-specific geometries.

Relationship between coronary volume, myocardial mass, and post-PCI fractional flow reserve

BACKGROUND

Fractional flow reserve (FFR) measured after percutaneous coronary intervention (PCI) carries prognostic information. Yet, myocardial mass subtended by a stenosis influences FFR. We hypothesized that a smaller coronary lumen volume and a large myocardial mass might be associated with lower post-PCI FFR.

AIM

We sought to assess the relationship between vessel volume, myocardial mass, and post-PCI FFR.

METHODS

This was a subanalysis with an international prospective study of patients with significant lesions (FFR ≤ 0.80) undergoing PCI. Territory-specific myocardial mass was calculated from coronary computed tomography angiography (CCTA) using the Voronoi's algorithm. Vessel volume was extracted from quantitative CCTA analysis. Resting full-cycle ratio (RFR) and FFR were measured before and after PCI. We assessed the association between coronary lumen volume (V) and its related myocardial mass (M), and the percent of total myocardial mass (%M) with post-PCI FFR.

RESULTS

We studied 120 patients (123 vessels: 94 left anterior descending arteries, 13 left Circumflex arteries, 16 right coronary arteries). Mean vessel-specific mass was 61 ± 23.1 g (%M 39.6 ± 11.7%). The mean post-PCI FFR was 0.88 ± 0.06 FFR units. Post-PCI FFR values were lower in vessels subtending higher mass (0.87 ± 0.05 vs. 0.89 ± 0.07, p = 0.047), and with lower V/M ratio (0.87 ± 0.06 vs. 0.89 ± 0.07, p = 0.02). V/M ratio correlated significantly with post-PCI RFR and FFR (RFR r = 0.37, 95% CI: 0.21-0.52, p < 0.001 and FFR r = 0.41, 95% CI: 0.26-0.55, p < 0.001).

CONCLUSION

Post-PCI RFR and FFR are associated with the subtended myocardial mass and the coronary volume to mass ratio. Vessels with higher mass and lower V/M ratio have lower post-PCI RFR and FFR.

A Novel CT Perfusion-Based Fractional Flow Reserve Algorithm for Detecting Coronary Artery Disease

Background: The diagnostic accuracy of fractional flow reserve (FFR) derived from coronary computed tomography angiography (CCTA) (FFR-CT) needs to be further improved despite promising results available in the literature. While an innovative myocardial computed tomographic perfusion (CTP)-derived fractional flow reserve (CTP-FFR) model has been initially established, the feasibility of CTP-FFR to detect coronary artery ischemia in patients with suspected coronary artery disease (CAD) has not been proven. Methods: This retrospective study included 93 patients (a total of 103 vessels) who received CCTA and CTP for suspected CAD. Invasive coronary angiography (ICA) was performed within 2 weeks after CCTA and CTP. CTP-FFR, CCTA (stenosis ≥ 50% and ≥70%), ICA, FFR-CT and CTP were assessed by independent laboratory experts. The diagnostic ability of the CTP-FFR grouped by quantitative coronary angiography (QCA) in mild (30–49%), moderate (50–69%) and severe stenosis (≥70%) was calculated. The effect of calcification of lesions, grouped by FFR on CTP-FFR measurements, was also assessed. Results: On the basis of per-vessel level, the AUCs for CTP-FFR, CTP, FFR-CT and CCTA were 0.953, 0.876, 0.873 and 0.830, respectively (all p < 0.001). The sensitivity, specificity, accuracy, positive predictive value (PPV) and negative predictive value (NPV) of CTP-FFR for per-vessel level were 0.87, 0.88, 0.87, 0.85 and 0.89 respectively, compared with 0.87, 0.54, 0.69, 0.61, 0.83 and 0.75, 0.73, 0.74, 0.70, 0.77 for CCTA ≥ 50% and ≥70% stenosis, respectively. On the basis of per-vessel analysis, CTP-FFR had higher specificity, accuracy and AUC compared with CCTA and also higher AUC compared with FFR-CT or CTP (all p < 0.05). The sensitivity and accuracy of CTP-FFR + CTP + FFR-CT were also improved over FFR-CT alone (both p < 0.05). It also had improved specificity compared with FFR-CT or CTP alone (p < 0.01). A strong correlation between CTP-FFR and invasive FFR values was found on per-vessel analysis (Pearson’s correlation coefficient 0.89). The specificity of CTP-FFR was higher in the severe calcification group than in the low calcification group (p < 0.001). Conclusions: A novel CTP-FFR model has promising value to detect myocardial ischemia in CAD, particularly in mild-to-moderate stenotic lesions.

Cardiac computed tomography-derived coronary artery volume to myocardial mass

In the absence of disease impacting the coronary arteries or myocardium, there exists a linear relationship between vessel volume and myocardial mass to ensure balanced distribution of blood supply. This balance may be disturbed in diseases of either the coronary artery tree, the myocardium, or both. However, in contemporary evaluation the coronary artery anatomy and myocardium are assessed separately. Recently the coronary lumen volume to myocardial mass ratio (V/M), measured noninvasively using coronary computed tomography angiography (CTCA), has emerged as an integrated measure of myocardial blood supply and demand in vivo. This has the potential to yield new insights into diseases where this balance is altered, thus impacting clinical diagnoses and management. In this review, we outline the scientific methodology underpinning CTCA-derived measurement of V/M. We describe recent studies describing alterations in V/M across a range of cardiovascular conditions, including coronary artery disease, cardiomyopathies and coronary microvascular dysfunction. Lastly, we highlight areas of unmet research need and future directions, where V/M may further enhance our understanding of the pathophysiology of cardiovascular disease.

Correlation between quantification of myocardial area at risk and ischemic burden at cardiac computed tomography

Purpose

This study aims to investigate the correlation between myocardial area at risk at coronary computed tomography angiography (CCTA) and the ischemic burden derived from myocardial computed tomography perfusion (CTP) by using the 17-segment model.

Methods

Forty-two patients with chest pain complaints who underwent a combined CCTA and CTP protocol were identified. Patients with reversible ischemia at CTP and at least one stenosis of ≥ 50% at CCTA were selected. Myocardial area at risk was calculated using a Voronoi-based segmentation algorithm at CCTA and was defined as the sum of all territories related to a ≥ 50% stenosis as a percentage of the total left ventricular (LV) mass. The latter was calculated using LV contours which were automatically drawn using a machine learning algorithm. Subsequently, the ischemic burden was defined as the number of segments demonstrating relative hypoperfusion as a percentage of the total amount of segments (=17). Finally, correlations were tested between the myocardial area at risk and the ischemic burden using Pearson’s correlation coefficient.

Results

A total of 77 coronary lesions were assessed. Average myocardial area at risk and ischemic burden for all lesions was 59% and 23%, respectively. Correlations for ≥ 50% and ≥ 70% stenosis based myocardial area at risk compared to ischemic burden were moderate (r = 0.564; p < 0.01) and good (r = 0.708; p < 0.01), respectively.

Conclusion

The relation between myocardial area at risk as calculated by using a Voronoi-based algorithm at CCTA and ischemic burden as assessed by CTP is dependent on stenosis severity.

Hybrid Imaging to Assess the Impact of Vulnerable Plaque on Post Myocardial Infarction Myocardial Scar

Background: Multimodality imaging improves the accuracy of cardiac assessment in patients with prior myocardial infarction. The aim of this study was to investigate the association between coronary plaque vulnerability (PV) and myocardial viability in the territory irrigated by the infarct-related artery (IRA). Secondary objectives include evaluation of the systemic inflammation but also different cardiac risk scores (SYNTAX score, Duke jeopardy score, or calcium score) using hybrid imaging models of coronary computed tomography angiography (CCTA) and cardiac magnetic resonance (CMR) in patients who have suffered a previous myocardial infarction (MI). Material and methods: The study included 45 subjects with documented MI in the 30 days prior to study enrolment, who underwent CCTA and CMR examinations. Computational postprocessing of CCTA and CMR images was used to generate fused imaging models. Based on the vulnerability degree of the associated non-culprit lesion located proximally in the IRA, the study population was divided into 3 groups: Group 1 – subjects with no sign of vulnerability (n = 7); Group 2 – subjects with 1 or 2 CT vulnerability features (n = 28); and Group 3 – subjects with >2 features of vulnerability (n = 12). Results: CCTA features indicative for the severity of coronary artery disease were not different between groups in terms of calcium scoring (460 ± 501 vs. 579 ± 430 vs. 432 ± 494, p = 0.7) or SYNTAX score (25 ± 9.2 vs. 24.9 ± 8.3 vs. 20.2 ± 11.9, p = 0.4). However, after 1 month, infarct size and the Duke jeopardy score were associated with increased PV (infarct size 8.77 ± 3.4 g in Group 1, compared to 20.87 ± 8.3 g in Group 2 and 27.99 ± 11.8 g in Group 3 (p = 0.007), while the Duke jeopardy score was 4.4 ± 1.6 in Group 1, vs. 7.07 ± 2.1 in Group 2 vs. 7.5 ± 1.73 in Group 3 (p = 0.01). Inflammatory biomarkers were directly associated with coronary plaque vulnerability (p = 0.007 for hs-CRP and p = 0.038 for MMP-9). Conclusion: In patients with prior myocardial infarction, the size of myocardial scar was directly correlated with the vulnerability degree of coronary plaques and with systemic inflammation quantified during the acute phase of the coronary event. Hybrid imaging may help to identify the hemodynamically significant plaques with superior accuracy.

Quantification of myocardial ischemia and subtended myocardial mass at adenosine stress cardiac computed tomography: a feasibility study

Combination of coronary computed tomography angiography (CCTA) and adenosine stress CT myocardial perfusion (CTP) allows for coronary artery lesion assessment as well as myocardial ischemia. However, myocardial ischemia on CTP is nowadays assessed semi-quantitatively by visual analysis. The aim of this study was to fully quantify myocardial ischemia and the subtended myocardial mass on CTP. We included 33 patients referred for a combined CCTA and adenosine stress CTP protocol, with good or excellent imaging quality on CTP. The coronary artery tree was automatically extracted from the CCTA and the relevant coronary artery lesions with a significant stenosis (≥ 50%) were manually defined using dedicated software. Secondly, epicardial and endocardial contours along with CT perfusion deficits were semi-automatically defined in short-axis reformatted images using MASS software. A Voronoi-based segmentation algorithm was used to quantify the subtended myocardial mass, distal from each relevant coronary artery lesion. Perfusion defect and subtended myocardial mass were spatially registered to the CTA. Finally, the subtended myocardial mass per lesion, total subtended myocardial mass and perfusion defect mass (per lesion) were measured. Voronoi-based segmentation was successful in all cases. We assessed a total of 64 relevant coronary artery lesions. Average values for left ventricular mass, total subtended mass and perfusion defect mass were 118, 69 and 7 g respectively. In 19/33 patients (58%) the total perfusion defect mass could be distributed over the relevant coronary artery lesion(s). Quantification of myocardial ischemia and subtended myocardial mass seem feasible at adenosine stress CTP and allows to quantitatively correlate coronary artery lesions to corresponding areas of myocardial hypoperfusion at CCTA and adenosine stress CTP.

Assessment of lesion-associated myocardial ischemia based on fusion coronary CT imaging - the FUSE-HEART study: A protocol for non-randomized clinical trial

INTRODUCTION

Multimodality assessment of coronary artery lesions has demonstrated superior effectiveness compared to the conventional approach, for assessing both anatomical and functional significance of a coronary stenosis. Multiple imaging modalities can be integrated into a fusion imaging tool to better assess myocardial ischemia.

MATERIAL AND METHODS

The FUSE-HEART trial is a single center, prospective, cohort study that will assess the impact of a coronary artery stenosis on myocardial function and viability, based on advanced fusion imaging technics derived from Cardiac Computed Tomography Angiography (CCTA). Moreover, the study will investigate the correlation between morphology and composition of the coronary plaques and myocardial ischemia in the territory irrigated by the same coronary artery. At the same time, imaging parameters will be correlated with inflammatory status of the subjects. The trial will include 100 subjects with coronary lesions found on CCTA examination. The study population will be divided into 2 groups: first group will consist of subjects with anatomically significant coronary lesions on native coronary arteries and the second one will include subjects surviving an acute myocardial infarction. The vulnerability score of the subjects will be calculated based on presence of CCTA vulnerability markers of the coronary plaques: napkin ring sign, positive remodeling, spotty calcifications, necrotic core, and low-density plaques. 3D fusion images of the coronary tree will be generated, integrating the images reflecting wall motion with the ones of coronary circulation. The fusion models will establish the correspondence between plaque composition and wall motion in the subtended myocardium of the coronary artery. The study primary outcome will be represented by the rate of major adverse cardiac events related to myocardial ischemia at 1-year post assessment, in correlation with the degree of coronary artery stenosis and myocardial ischemia or viability.The secondary outcomes are represented by the rate of re-hospitalization, rate of survival and rate of major adverse cardiovascular events (including cardiovascular death or stroke), in correlation with the morphology and composition of atheromatous plaques located in a coronary artery, and myocardial ischemia in the territory irrigated by the same coronary artery.

CONCLUSION

In conclusion, FUSE-HEART will be a study based on modern imaging tools that will investigate the impact of a coronary artery stenosis on myocardial function and viability, using advanced fusion imaging technics derived from CCTA, sighting to validate plaque composition and morphology, together with inflammatory biomarkers, as predictors to myocardial viability.

Anatomical attributes of clinically relevant diagonal branches in patients with left anterior descending coronary artery bifurcation lesions

AIMS

This study aimed to investigate the anatomical attributes determining myocardial territory of diagonal branches and to develop prediction models for clinically relevant branches using myocardial perfusion imaging (MPI) and coronary CT angiography (CCTA).

METHODS AND RESULTS

The amount of ischaemia and subtended myocardial mass of diagonal branches was quantified using MPI by percent ischaemic myocardium (%ischaemia) and CCTA by percent fractional myocardial mass (%FMM), respectively. In 49 patients with isolated diagonal branch disease, the mean %ischaemia by MPI was 6.8±4.0%, whereas in patients with total occlusion or severe disease of all diagonal branches it was 8.4±3.3%. %ischaemia was different according to the presence of non-diseased diagonal branches and dominant left circumflex artery (LCx). In the CCTA cohort (306 patients, 564 diagonal branches), mean %FMM was 5.9±4.4% and 86 branches (15.2%) had %FMM ≥10%. %FMM was different according to LCx dominance, number of branches, vessel size, and relative dominance between two diagonal branches. The diagnostic accuracy of prediction models for %FMM ≥10% based on logistic regression and decision tree was 0.92 (95% CI: 0.85-0.96) and 0.91 (95% CI: 0.84-0.96), respectively. There was no difference in the diagnostic performance of models with and without size criterion.

CONCLUSIONS

LCx dominance, number of branches, vessel size, and dominance among diagonal branches determined the myocardial territory of diagonal branches. Clinical application of prediction models based on these anatomical attributes can help to determine the clinically relevant diagonal branches in the cardiac catheterisation laboratory.

CLINICAL TRIAL REGISTRATION

NCT03935542

Diagnostic value of comprehensive on-site and off-site coronary CT angiography for identifying hemodynamically obstructive coronary artery disease

BACKGROUND

This study aimed to investigate the diagnostic value of comprehensive on-site coronary computed tomography angiography (CCTA) using stenosis and plaque measures and subtended myocardial mass (V_sub) for fractional flow reserve (FFR) defined hemodynamically obstructive coronary artery disease (CAD). Additionally, the incremental diagnostic value of off-site CT-derived FFR (FFR_CT) was assessed.

METHODS

Prospectively enrolled patients underwent CCTA followed by invasive FFR interrogation of all major coronary arteries. Vessels with ≥30% stenosis were included for analysis. On-site CCTA assessment included qualitative and quantitative stenosis (visual grading and minimal lumen area, MLA) and plaque measures (characteristics and volumes), and V_sub. Diagnostic value of comprehensive on-site CCTA assessment was tested by comparing area under the curves (AUC). In vessels with available FFR_CT, the incremental value of off-site FFR_CT was tested.

RESULTS

In 236 vessels (132 patients), MLA, positive remodeling, non-calcified plaque volume, and V_sub were independent on-site CCTA predictors for hemodynamically obstructive CAD (p < 0.05 for all). V_sub/MLA² outperformed all these on-site CCTA parameters (AUC = 0.85) and V_sub was incremental to all other CCTA predictors (p = 0.02). In subgroup analysis (n = 194 vessels), diagnostic performance of FFR_CT and V_sub/MLA² was similar (AUC 0.89 and 0.85 respectively, p = 0.25). Furthermore, diagnostic performance significantly albeit minimally increased when FFR_CT was added to on-site CCTA assessment (ΔAUC = 0.03, p = 0.02).

CONCLUSIONS

In comprehensive on-site CCTA assessment, V_sub/MLA2 demonstrated greatest diagnostic value for hemodynamically obstructive CAD and V_sub was incremental to all evaluated CCTA indices. Additionally, adding FFR_CT only minimally increased diagnostic performance, demonstrating that on-site CCTA assessment is a reasonable alternative to FFR_CT.

Vessel-specific coronary perfusion territories using a CT angiogram with a minimum cost path technique and its direct comparison to the American Heart Association 17-segment model

OBJECTIVES

This study compared the accuracy of an automated, vessel-specific minimum cost path (MCP) myocardial perfusion territory assignment technique as compared with the standard American Heart Association 17-segment (AHA) model.

METHODS

Six swine (42 ± 9 kg) were used to evaluate the accuracy of the MCP technique and the AHA method. In each swine, a dynamic acquisition, comprised of twenty consecutive whole heart volume scans, was acquired with a computed tomography scanner, following peripheral injection of contrast material. From this acquisition, MCP and AHA perfusion territories were determined, for the left (LCA) and right (RCA) coronary arteries. Each animal underwent additional dynamic acquisitions, consisting of twenty consecutive volume scans, following direct intracoronary contrast injection into the LCA or RCA. These images were used as the reference standard (REF) LCA and RCA perfusion territories. The MCP and AHA techniques' perfusion territories were then quantitatively compared with the REF perfusion territories.

RESULTS

The myocardial mass of MCP perfusion territories (M_MCP) was related to the mass of reference standard perfusion territories (M_REF) by M_MCP = 0.99M_REF + 0.39 g (r = 1.00; R² = 1.00). The mass of AHA perfusion territories (M_AHA) was related to M_REF by M_AHA = 0.81M_REF + 5.03 g (r = 0.99; R² = 0.98).

CONCLUSION

The vessel-specific MCP myocardial perfusion territory assignment technique more accurately quantifies LCA and RCA perfusion territories as compared with the current standard AHA 17-segment model. Therefore, it can potentially provide a more comprehensive and patient-specific evaluation of coronary artery disease.

KEY POINTS

• The minimum cost path (MCP) technique accurately determines left and right coronary artery perfusion territories, as compared with the American Heart Association 17-segment (AHA) model. • The minimum cost path (MCP) technique could be applied to cardiac computed-tomography angiography images to accurately determine patient-specific left and right coronary artery perfusion territories. • The American Heart Association 17-segment (AHA) model often fails to accurately determine left and right coronary artery perfusion territories, especially in the inferior and inferoseptal walls of the left ventricular myocardium.

Computed tomographic myocardial mass compared with invasive myocardial perfusion measurement

Objective

The prognostic importance of a coronary stenosis depends on its functional severity and its depending myocardial mass. Functional severity can be assessed by fractional flow reserve (FFR), estimated non-invasively by a specific validated CT algorithm (FFR_CT). Calculation of myocardial mass at risk by that same set of CT data (CTmass), however, has not been prospectively validated so far. The aim of the present study was to compare relative territorial-based CTmass assessment with relative flow distribution, which is closely linked to true myocardial mass.

Methods

In this exploratory study, 35 patients with (near) normal coronary arteries underwent CT scanning for computed flow-based CTmass assessment and underwent invasive myocardial perfusion measurement in all 3 major coronary arteries by continuous thermodilution. Next, the mass and flows were calculated as relative percentages of total mass and perfusion.

Results

The mean difference between CTmass per territory and invasively measured myocardial perfusion, both expressed as percentage of total mass and perfusion, was 5.3±6.2% for the left anterior descending territory, −2.0±7.4% for the left circumflex territory and −3.2±3.4% for the right coronary artery territory. The intraclass correlation between the two techniques was 0.90.

Conclusions

Our study shows a close relationship between the relative mass of the perfusion territory calculated by the specific CT algorithm and invasively measured myocardial perfusion. As such, these data support the use of CTmass to estimate territorial myocardium-at-risk in proximal coronary arteries.

The Functional Severity Assessment of Coronary Stenosis Using Coronary Computed Tomography Angiography-Based Myocardial Mass at Risk and Minimal Lumen Diameter

Background

We investigated whether or not the addition of myocardial mass at risk (MMAR) to quantitative coronary angiography was useful for diagnosing functionally significant coronary stenosis in the daily practice.

Methods

We retrospectively enrolled 111 consecutive patients with 149 lesions who underwent clinically indicated coronary computed tomography angiography and subsequent elective coronary angiography with fractional flow reserve (FFR) measurement. MMAR was calculated using a workstation-based software program with ordinary thin slice images acquired for the computed tomography, and the minimal lumen diameter (MLD) and the diameter stenosis were measured with quantitative coronary angiography.

Results

The MLD and MMAR were significantly correlated with the FFR, and the MMAR-to-MLD ratio (MMAR/MLD) showed a good correlation. The area under the receiver operating characteristic curve (AUC) of MMAR/MLD for FFR ≤ 0.8 was 0.746, and the sensitivity, specificity, positive predictive value, and negative predictive value were 60%, 83%, 68%, and 77%, respectively, at a cut-off value of 29.5 ml/mm. The addition of MMAR/MLD to diameter stenosis thus made it possible to further discriminate lesions with FFR ≤ 0.8 (AUC = 0.750). For the proximal left coronary artery lesions, in particular, MMAR/MLD showed a better correlation with the FFR, and the AUC of MMAR/MLD for FFR ≤ 0.8 was 0.919 at a cut-off value of 31.7 ml/mm.

Conclusions

The index of MMAR/MLD correlated well with the physiological severity of coronary stenosis and showed good accuracy for detecting functional significance. The MMAR/MLD might be a useful parameter to consider when deciding the indication for revascularization.

Coronary artery stenosis-related perfusion ratio using dynamic computed tomography myocardial perfusion imaging: a pilot for identification of hemodynamically significant coronary artery disease

The purpose of this study was to evaluate the feasibility of the stenosis-related quantitative perfusion ratio (QPR) for detecting hemodynamically significant coronary artery disease (CAD). Twenty-seven patients were retrospectively enrolled. All patients underwent dynamic myocardial computed tomography perfusion (CTP) and coronary computed tomography angiography (CTA) before invasive coronary angiography (ICA) measuring the fractional flow reserve (FFR). Coronary lesions with FFR ≤ 0.8 were defined as hemodynamically significant CAD. The myocardial blood flow (MBF) was calculated using dynamic CTP data, and CT-QPR was calculated as the CT-MBF relative to the reference CT-MBF. The stenosis-related CT-MBF and QPR were calculated using Voronoi diagram-based myocardial segmentation from coronary CTA data. The relationships between FFR and stenosis-related CT-MBF or QPR and the diagnostic performance of the stenosis-related CT-MBF and QPR were evaluated. Of 81 vessels, FFR was measured in 39 vessels, and 20 vessels (51%) in 15 patients were diagnosed as hemodynamically significant CAD. The stenosis-related CT-QPR showed better correlation (r = 0.70, p < 0.05) than CT-MBF (r = 0.56, p < 0.05). Sensitivity and specificity for detecting hemodynamically significant CAD were 95% and 58% for CT-MBF, and 95% and 90% for CT-QPR, respectively. The area under the receiver operating characteristic curve for the CT-QPR was significantly higher than that for the CT-MBF (0.94 vs. 0.79; p < 0.05). The stenosis-related CT-QPR derived from dynamic myocardial CTP and coronary CTA showed a better correlation with FFR and a higher diagnostic performance for detecting hemodynamically significant CAD than the stenosis-related CT-MBF.

Quantification of Myocardial Mass Subtended by a Coronary Stenosis Using Intracoronary Physiology

Background:

In patients with stable coronary artery disease, the amount of myocardium subtended by coronary stenoses constitutes a major determinant of prognosis, as well as of the benefit of coronary revascularization. We devised a novel method to estimate partial myocardial mass (PMM; ie, the amount of myocardium subtended by a stenosis) during physiological stenosis interrogation. Subsequently, we validated the index against equivalent PMM values derived from applying the Voronoi algorithm on coronary computed tomography angiography.

Methods:

Based on the myocardial metabolic demand and blood supply, PMM was calculated as follows: PMM (g)=APV×D 2 ×π/(1.24×10 − 3 ×HR×sBP+1.6), where APV indicates average peak blood flow velocity; D, vessel diameter; HR, heart rate; and sBP, systolic blood pressure. We calculated PMM to 43 coronary vessels (32 patients) interrogated with pressure and Doppler guidewires, and compared it with computed tomography–based PMM.

Results:

Median PMM was 15.8 g (Q1, Q3: 11.7, 28.4 g) for physiology-based PMM, and 17.0 g (Q1, Q3: 12.5, 25.9 g) for computed tomography–based PMM ( P =0.84). Spearman rank correlation coefficient was 0.916 ( P <0.001), and Passing-Bablok analysis revealed absence of both constant and proportional differences (coefficient A: −0.9; 95% CI, −4.5 to 0.9; and coefficient B, 1.00; 95% CI, 0.91 to 1.25]. Bland-Altman analysis documented a mean bias of 0.5 g (limit of agreement: −9.1 to 10.2 g).

Conclusions:

Physiology-based calculation of PMM in the catheterization laboratory is feasible and can be accurately performed as part of functional stenosis assessment.

The best predictor of ischemic coronary stenosis: subtended myocardial volume, machine learning-based FFRCT, or high-risk plaque features?

OBJECTIVES

The present study aimed to compare the diagnostic performance of a machine learning (ML)-based FFR_CT algorithm, quantified subtended myocardial volume, and high-risk plaque features for predicting if a coronary stenosis is hemodynamically significant, with reference to FFR_ICA.

METHODS

Patients who underwent both CCTA and FFR_ICA measurement within 2 weeks were retrospectively included. ML-based FFR_CT, volume of subtended myocardium (V_sub), percentage of subtended myocardium volume versus total myocardium volume (V_ratio), high-risk plaque features, minimal lumen diameter (MLD), and minimal lumen area (MLA) along with other parameters were recorded. Lesions with FFR_ICA ≤ 0.8 were considered to be functionally significant.

RESULTS

One hundred eighty patients with 208 lesions were included. The lesion length (LL), diameter stenosis, area stenosis, plaque burden, V_sub, V_ratio, V_ratio/MLD, V_ratio/MLA, and LL/MLD⁴ were all significantly longer or larger in the group of FFR_ICA ≤ 0.8 while smaller minimal lumen area, MLD, and FFR_CT value were noted. The AUC of FFR_CT + V_ratio/MLD was significantly better than that of FFR_CT alone (0.935 versus 0.873, p < 0.001). High-risk plaque features failed to show difference between functionally significant and insignificant groups. V_ratio/MLD-complemented ML-based FFR_CT for "gray zone" lesions with FFR_CT value ranged from 0.7 to 0.8 and the combined use of these two parameters yielded the best diagnostic performance (86.5%, 180/208).

CONCLUSIONS

ML-based FFR_CT simulation and V_ratio/MLD both provide incremental value over CCTA-derived diameter stenosis and high-risk plaque features for predicting hemodynamically significant lesions. V_ratio/MLD is more accurate than ML-based FFR_CT for lesions with simulated FFR_CT value from 0.7 to 0.8.

KEY POINTS

• Machine learning-based FFR _CT and subtended myocardium volume both performed well for predicting hemodynamically significant coronary stenosis. • Subtended myocardium volume was more accurate than machine learning-based FFR _CT for "gray zone" lesions with simulated FFR value from 0.7 to 0.8. • CT-derived high-risk plaque features failed to correctly identify hemodynamically significant stenosis.

Quantification of vessel-specific coronary perfusion territories using minimum-cost path assignment and computed tomography angiography: Validation in a swine model

BACKGROUND

As combined morphological and physiological assessment of coronary artery disease (CAD) is necessary to reliably resolve CAD severity, the objective of this study was to validate an automated minimum-cost path assignment (MCP) technique which enables accurate, vessel-specific assignment of the left (LCA) and right (RCA) coronary perfusion territories using computed tomography (CT) angiography data for both left and right ventricles.

METHODS

Six swine were used to validate the MCP technique. In each swine, a dynamic acquisition comprised of twenty consecutive volume scans was acquired with a 320-slice CT scanner following peripheral injection of contrast material. From this acquisition the MCP technique was used to automatically assign LCA and RCA perfusion territories for the left and right ventricles, independently. Each animal underwent another dynamic CT acquisition following direct injection of contrast material into the LCA or RCA. Using this acquisition, reference standard LCA and RCA perfusion territories were isolated from the myocardial blush. The accuracy of the MCP technique was evaluated by quantitatively comparing the MCP-derived LCA and RCA perfusion territories to these reference standard territories.

RESULTS

All MCP perfusion territory masses (Mass_MCP) and all reference standard perfusion territory masses (Mass_RS) in the left ventricle were related by Mass_MCP = 0.99Mass_RS+0.35 g (r = 1.00). Mass_MCP and Mass_RS in the right ventricle were related by Mass_MCP = 0.94Mass_RS+0.39 g (r = 0.96).

CONCLUSION

The MCP technique was validated in a swine animal model and has the potential to be used for accurate, vessel-specific assignment of LCA and RCA perfusion territories in both the left and right ventricular myocardium using CT angiography data.