Stress Cardiovascular Magnetic Resonance Research Articles

Kiosk 5R-FC-05 - Automated In-line Quantitative Perfusion Mapping for Exercise Stress CMR: An EMPIRE Substudy

Kiosk 5R-FC-05 - Automated In-line Quantitative Perfusion Mapping for Exercise Stress CMR: An EMPIRE Substudy

Kiosk 9R-FB-07 - Safety and Feasibility of Adenosine Stress CMR in Heart Transplant Recipients with Suspected Cardiac Allograft Vasculopathy

Kiosk 9R-FB-07 - Safety and Feasibility of Adenosine Stress CMR in Heart Transplant Recipients with Suspected Cardiac Allograft Vasculopathy

Kiosk 2R-TB-12 - Novel Endotypes in Hfpef Identified Using Exercise Stress CMR and Machine Learning

Kiosk 2R-TB-12 - Novel Endotypes in Hfpef Identified Using Exercise Stress CMR and Machine Learning

CMR 3-86 - Stress CMR Perfusion Imaging in the Medicare Eligible Population: Insights from the Stress CMR Perfusion Imaging in the United States (SPINS) Study

CMR 3-86 - Stress CMR Perfusion Imaging in the Medicare Eligible Population: Insights from the Stress CMR Perfusion Imaging in the United States (SPINS) Study

Kiosk 9R-FB-06 - Real-world Application of Quantitative Perfusion Analysis in High-risk Appalachian Population Undergoing Regadenoson Stress CMR

Kiosk 9R-FB-06 - Real-world Application of Quantitative Perfusion Analysis in High-risk Appalachian Population Undergoing Regadenoson Stress CMR

Kiosk 10R-TB-01 - Fully Automated Assessment of Global Longitudinal Strain by Machine Learning Predicts Death in Patients with a Normal Stress CMR

Kiosk 10R-TB-01 - Fully Automated Assessment of Global Longitudinal Strain by Machine Learning Predicts Death in Patients with a Normal Stress CMR

Artificial intelligence fully automated assessment of global longitudinal strain predicts death in patients undergoing stress CMR

Artificial intelligence fully automated assessment of global longitudinal strain predicts death in patients undergoing stress CMR

Reduced stress perfusion in myocardial infarction with nonobstructive coronary arteries

Myocardial infarction with nonobstructive coronary arteries (MINOCA) has several possible underlying causes, including coronary microvascular dysfunction (CMD). Early cardiovascular magnetic resonance imaging (CMR) is recommended, however cannot provide a diagnosis in 25% of cases. Quantitative stress CMR perfusion mapping can identify CMD, however it is unknown if CMD is present during long-term follow-up of MINOCA patients. Therefore, this study aimed to evaluate presence of CMD during long-term follow-up in MINOCA patients with an initial normal CMR scan. MINOCA patients from the second Stockholm myocardial infarction with normal coronaries study (SMINC-2), with a normal CMR scan at median 3 days after hospitalization were investigated with comprehensive CMR including stress perfusion mapping a median of 5 years after the index event, together with age- and sex-matched volunteers without symptomatic ischemic heart disease. Cardiovascular risk factors, medication and symptoms of myocardial ischemia measured by the Seattle Angina Questionnaire 7 (SAQ-7), were registered. In total, 15 patients with MINOCA and an initial normal CMR scan (59 ± 7 years old, 60% female), and 15 age- and sex-matched volunteers, underwent CMR. Patients with MINOCA and an initial normal CMR scan had lower global stress perfusion compared to volunteers (2.83 ± 1.8 vs 3.53 ± 0.7 ml/min/g, p = 0.02). There were no differences in other CMR parameters, hemodynamic parameters, or cardiovascular risk factors, except for more frequent use of statins in the MINOCA patient group compared to volunteers. In conclusion, global stress perfusion is lower in MINOCA patients during follow-up, compared to age- and sex-matched volunteers, suggesting that CMD may be a possible pathophysiological mechanism in MINOCA.Clinical Trial Registration: Clinicaltrials.gov identifier NCT02318498. Registered 2014-12-17.

Characteristics and 1 year outcome of stress cardiovascular magnetic resonance imaging: Insight from the Multicentre Malaysian CMR Registry

Characteristics and 1 year outcome of stress cardiovascular magnetic resonance imaging: Insight from the Multicentre Malaysian CMR Registry

Thrombotic Thrombocytopenic Purpura (TTP) Survivors Exhibit Impaired Stress Perfusion on Cardiac MRI

Introduction: Thrombotic thrombocytopenic purpura (TTP) survivors have increased rates of cardiovascular morbidity and mortality when compared with the general population. In this prospective pilot study, we sought to further characterize the long-term cardiovascular sequelae of TTP survivors through pharmacologic stress cardiac magnetic resonance imaging (CMR). Stress CMR has been increasingly utilized to detect clinical and subclinical structural and functional changes. A CMR biomarker of myocardial remodeling is extracellular volume (ECV); an increase in ECV may indicate the development of interstitial myocardial fibrosis. ECV was chosen for structural assessment as it has been implicated with diastolic dysfunction and other cardiac issues in other hematologic diseases, like sickle cell anemia. Methods: Adult patients (age ≥18 years of age) with TTP (immune-mediated or congenital) in the Ohio State University (OSU) TTP registry were prospectively consented and enrolled from March 2023 through July 2023 to undergo adenosine stress CMR at standard clinical dosing. All patients in the TTP cohort had confirmed diagnosis based on ADAMTS13 activity <15% during an acute episode and were in clinical remission at the time of CMR testing. Standard baseline and stress CMR parameters were obtained and compared with an age and sex matched control population, selected from patients without TTP who underwent identical stress CMR protocol for other indications and demonstrated normal stress perfusion. Patients in the control cohort predominantly had diagnoses of arrhythmia, stable angina, or heart failure. We collected data on patient demographics, details of TTP history, and underlying comorbidities. On CMR standard structural measurements were evaluated, and ECV was calculated (normal range 25.3 ± 3.5%). Perfusion was measured per standard protocols via global myocardial blood flow (MBF) as ml/min/g. Differences between the TTP and control populations were tested using the Fischer's exact test for categorical variables and Mann-Whitney U test for continuous variables. Results: A total of 10 TTP patients (9 immune-mediated, 1 congenital) were enrolled between March and July 2023. Median age at enrollment was 44.5 years (IQR 40.8-49.5) and 80% (8/10) were female. Patients were in documented clinical and ADAMTS13 activity remission with median ADAMTS13 activity of 68% (64.0-84.5), excluding the activity level of the congenital patient. Median time from initial diagnosis was 15 years (range 0.5 - 41 years) and median number of acute TTP episodes was 2 (IQR 1.0-4.5). Characteristics of the study (n= 10) and control cohort (n = 13) are summarized in Table 1. There were no significant differences in the TTP and control cohorts with respect to age, sex, race, and presence of hypertension or diabetes. Patients in the TTP cohort had significantly higher BMI (median 34.5 mg/m 2 vs 26.5 mg/m 2, p = .012), diastolic blood pressure (94 mmHg vs 82 mmHg, p = .003), and a lower rate of known cardiac disease (10% vs 85%, p<.001). Stress CMR showed reduced myocardial perfusion in TTP survivors: Nine out of 10 (90%) TTP survivors had evidence of structural or perfusion deficits on CMR. The median ECV in the TTP cohort (28.5%, 24.8 - 31.5) was increased compared with controls (26%, 23.5 - 27.5) though it did not reach significance (p = .08). There were no significant differences in median global MBF at rest in the TTP group (1.30, 1.16 - 1.37) compared with controls (1.18, 1.07 - 1.31, p = .210). However, TTP survivors had significantly reduced stress MBF (3.28, 2.21 - 3.53) vs controls (4.1, 3.88 - 4.22, p <.001) with adenosine. Reductions in quantitative stress perfusion in the TTP cohort was primarily noted in the subendocardium as shown in Figure 2. Conclusion: Asymptomatic structural changes and reduction in quantitative perfusion are common in TTP survivors. The study is ongoing to recruit more patients to ensure clinical significance and generalizability of these preliminary findings. Stress CMR may detect subclinical myocardial damage in TTP survivors who otherwise do not exhibit overt cardiovascular symptoms until a later time and may provide the basis to understand increased cardiovascular morbidity and mortality in this population.

Machine-learning score using CCTA and stress CMR for prediction of cardiovascular events in patients with obstructive CAD

Abstract Background In patients with suspected or known coronary artery disease, traditional prognostic risk assessment is based on a limited selection of clinical and imaging findings as coronary computed tomography angiography (CCTA) and stress cardiovascular magnetic resonance (CMR). Machine learning (ML) methods can take into account a greater number and complexity of variables. Purpose To investigate the feasibility and accuracy of ML using stress CMR and CCTA data to predict major adverse cardiovascular events (MACE) in patients with suspected or known coronary artery disease, and compared its performance with existing clinical, CMR or CCTA scores. Methods Between 2008-2020, consecutive symptomatic patients without known CAD referred for CCTA were screened. Patients with obstructive CAD (at least 1 ≥50% stenosis on CCTA) were further referred for stress CMR. Twenty-three clinical, 7 CCTA, and 11 stress CMR parameters were evaluated. ML involved automated feature selection by LASSO, model building with a XGBoost algorithm. The primary composite outcome was MACE defined by cardiovascular death or nonfatal myocardial infarction. The external validation cohort of the ML score was performed in another center (n=274). Results Of 2,210 patients who completed CMR, 2,038 (47% male, mean age 69±12 years) completed follow-up (median 6.8 [IQR 5.9-9.2] years); 281 experienced a MACE (13.8%). The ML score exhibited a higher area under the curve (AUC) compared with ESC risk score, QRISK3 score, Framingham risk score, and CCTA or stress CMR data alone for prediction of MACE (ML score: 0.85 vs ESC score: 0.66, QRISK3 score: 0.64, Framingham score: 0.63, only CCTA score: 0.76, only CMR: 0.82; all p<0.001). Similar results were obtained with AUC of the Precision-Recall (PR) curves (ML score: 0.59 vs. only CCTA score: 0.39, only CMR: 0.45; all p<0.001). The ML score also exhibited a good area under the curve in the external cohort (AUC ROC: 0.85 and AUC PR curve: 0.57). Conclusions The ML score including CCTA and stress CMR data exhibited a higher prognostic value to predict MACE compared with traditional method or traditional scores. In addition, our ML score including CCTA and stress CMR data showed the best performance compared with scores using only CCTA or CMR parameters.ROC et PR curves: ML scorePR curves: ML score

Safety and incremental prognostic value of stress CMR in patients with known chronic kidney disease

Abstract Background Cardiovascular disease (CVD) is the main cause of mortality in patients with chronic kidney disease (CKD). Although several studies have demonstrated the consistently high prognostic value of stress cardiovascular magnetic resonance (CMR), its prognostic value in patients with CKD is not well established. We aimed to assess the safety and the incremental prognostic value of vasodilator stress perfusion CMR in consecutive symptomatic patients with known CKD. Methods Between 2008 and 2021, we conducted a bi-center longitudinal study with all consecutive symptomatic patients with known CKD, defined by estimated glomerular filtration rate (eGFR) between 30 and 60 ml/min/1.73 m2, referred for vasodilator stress CMR. All patients with eGFR <30 ml/min/1.73 m² (n=62) were excluded due the risk of nephrogenic systemic fibrosis. All patients were followed for the occurrence of major adverse cardiovascular events (MACE) defined as cardiac death or recurrent nonfatal myocardial infarction (MI). Cox regressions were used to determine the prognostic value of stress CMR parameters. Results Of 825 patients with known CKD (71.4±8.8 years, 70% men), 769 (93%) completed the CMR protocol, and among those 702 (91%) completed the follow-up (median follow-up 6.4 (4.0–8.2) years). Stress CMR was well tolerated without occurrence of death or severe adverse event related to the injection of gadolinium or nephrogenic systemic fibrosis case. The presence of inducible ischemia was associated with the occurrence of MACE (hazard ratio [HR] 12.50; 95% confidence interval [CI]: 7.50–20.8; p<0.001). In multivariable analysis, ischemia and late gadolinium enhancement were independent predictors of MACE (HR 15.5; 95% CI: 7.72 to 30.9; and HR:4.67 [95%CI: 2.83-7.68]; respectively, both p<0.001). After adjustment, stress CMR findings showed the best improvement in model discrimination and reclassification above traditional risk factors (C-statistic improvement: 0.13; NRI=0.477; IDI=0.049). Conclusions In patients with known CKD, stress CMR is safe and its findings have an incremental prognostic value to predict MACE over traditional risk factors.Cumulative rates of MACECompeting risk analysis

Incremental prognostic value of fully-automatic machine-learning based global circumferential strain during a stress CMR exam

Abstract Background Left ventricular global circumferential strain using cardiovascular magnetic resonance (CMR) is an accurate indicator to predict cardiovascular events. Although several studies have shown the excellent prognostic value of stress CMR, the prognostic value of stress global circumferential strain (sGCS) remains unknown. Purpose To investigate the prognostic value of sGCS for predicting cardiovascular events using a fully automatic machine learning algorithm without human correction in consecutive patients referred for stress CMR. Methods Between 2016 and 2018, all consecutive patients referred for stress CMR were included and followed for the occurrence of major adverse cardiovascular events (MACE), defined by cardiovascular death or nonfatal myocardial infarction (MI). A fully automatic machine learning algorithm was trained and validated on unseen CMR studies (MAGNETOM Aera and Skyra, Siemens Healthcare, Erlangen, Germany) to assess the sGCS from short-axis cine images at stress. The algorithm combines multiple deep learning networks for detection and segmentation with an active contours approach. Cox regressions were performed to determine the prognostic value of sGCS. Results Among 2,906 consecutive patients who underwent stress CMR, the automatic sGCS was successfully computed in 2,859 (98.4%) patients (68% male, mean age 64±12 years). A total of 256 (8.8%) MACEs were observed during a median (IQR) follow-up period of 4.5 (3.7-5.3) years. Using Kaplan-Meier analysis, sGCS and the presence of inducible ischemia were significantly associated with the occurrence of MACE (hazard ratio, HR: 1.12 [95% CI, 1.08-1.17]; and HR: 8.48 [95% CI, 6.05-11.91], both p<0.001; respectively). After adjustment for traditional risk factors, inducible ischemia and late gadolinium enhancement (LGE), sGCS was an independent predictor of a higher incidence of MACE (adjusted HR: 1.12 [95% CI, 1.05-1.20]). Finally, sGCS showed an incremental prognostic value to predict MACE compared to a multivariable model including traditional risk factors, the presence of inducible ischemia and LGE (C-statistic improvement: 0.05, p=0.007; NRI= 0.169; IDI= 0.097; both p<0.001). Conclusions Automatic sGCS has an incremental prognostic value to predict MACE above traditional risk factors, and other stress CMR parameters.Survival curvesIncremental prognostic value

Fully automated assessment of global longitudinal strain by machine learning predicts death in patients undergoing stress CMR

Abstract Background Several studies described the independent prognostic value of left ventricular global longitudinal strain (GLS) using cardiovascular magnetic resonance (CMR) to predict death and cardiovascular events. While routine GLS evaluation is a time consuming and partially operator-dependent process, the potential interest of GLS using a fully automated method has not yet been established. Purpose To assess the feasibility and prognostic value of GLS to predict all-cause death using a fully automated machine-learning algorithm without human correction in consecutive patients referred for stress CMR. Methods Between 2016 and 2018, all consecutive patients referred for stress CMR were included and followed for the occurrence of all-cause death. A fully automated machine learning algorithm was trained and validated on unseen CMR studies (MAGNETOM Aera and Skyra) to assess the GLS from long-axis cine images acquired at rest. The algorithm combines multiple deep learning networks for detection and segmentation with an active contours approach. Cox regressions were performed to determine the prognostic value of GLS. Results In a retrospective study of 9,883 consecutive patients who underwent stress CMR between 2016 and 2018, automated GLS was successfully computed in 9,638 (97.5%) patients (67% male, mean age 66±12 years). A total of 510 (5.3%) deaths were observed during a median follow-up period of 4.5 years (interquartile range: 3.7-5.2). GLS, the presence of inducible ischemia and late gadolinium enhancement (LGE) were significantly associated with the occurrence of death (hazard ratio, HR: 1.22 [95% CI, 1.17-1.26]; HR: 2.23 [95% CI, 1.61-3.10]; and HR: 2.04 [95% CI, 1.41-2.95], respectively, all p<0.001). After adjustment for traditional risk factors, inducible ischemia and LGE, GLS was an independent predictor of a higher incidence of death (adjusted HR: 1.14 [95% CI, 1.08-1.20]). Automated GLS showed an incremental prognostic value to predict death compared to traditional risk factors, inducible ischemia and LGE (C-statistic improvement: 0.05; NRI=0.146; IDI=0.244; all p<0.001). Conclusions Fully automated GLS measured at rest has an incremental prognostic value to predict all-cause death above traditional risk factors, and other stress CMR parameters. This finding suggests that unsupervised GLS measurements are accurate and allow improved risk stratification.

Ai-based fully automated left atrioventricular coupling index as a prognostic marker in patients undergoing stress-CMR

Abstract Background The left atrioventricular coupling index (LACI) is a strong and independent predictor of heart failure (HF) in individuals without clinical cardiovascular disease. Its prognostic value is not established in patients with cardiovascular disease. Purpose To determine in patients undergoing stress CMR whether fully automated artificial intelligence-based LACI can provide incremental prognostic value to predict HF. Methods Between 2016 and 2018, we conducted a longitudinal study including all consecutive patients with abnormal (inducible ischemia or late gadolinium enhancement (LGE)) vasodilator stress CMR. Control subjects with normal stress CMR were selected using propensity score-matching. LACI was defined as the ratio of LA to LV end-diastolic volumes. The primary outcome included hospitalization for acute HF or cardiovascular death. Cox regression was used to evaluate the association of LACI with the primary outcome after adjustment for traditional risk factors. Results In 2,134 patients [65±12 years, 77% men, 1:1 matched patients (1,067 with normal and 1,067 with abnormal CMR)], LACI was positively associated with the primary outcome (median follow-up 5.2 (4.8-5.5) years) before and after adjustment for risk factors in the overall propensity-matched population (adjusted hazard ratio [HR], 1.18 [95%CI, 1.13-1.24] per 0.1% increment), patients with abnormal (adjusted HR, 1.22 [95%CI, 1.14-1.30] per 0.1% increment), and normal CMR (adjusted HR, 1.12 [95%CI, 1.05-1.20] per 0.1% increment; all p<0.001). After adjustment, a higher LACI of ≥25% showed the greatest improvement in model discrimination and reclassification over and above traditional risk factors and stress CMR findings (C-statistic improvement: 0.16; NRI=0.388; IDI=0.153, all p<0.001; LR-test p<0.001). Conclusion LACI is independently associated with hospitalization for HF and cardiovascular death in patients undergoing stress CMR, with an incremental prognostic value over traditional risk factors including inducible ischemia and LGE.LACI measurement method using CMRKaplan-Meier curves by LACI value

Incremental prognostic value of fully automatic LVEF measured at stress using machine learning

Abstract Background Cardiovascular magnetic resonance (CMR) is the gold standard to measure left ventricular ejection fraction (LVEF), and novel artificial intelligence-based automatic analyses have been proposed for less user interaction and time saving. However, whether automatic LVEF delivers similar information for risk stratification remains unknown. Purpose To assess the prognostic value for all-cause mortality of LVEF measured by stress CMR using a fully automatic machine learning algorithm without human correction. Methods Between 2016 and 2018, all consecutive patients referred for vasodilator stress CMR were included and followed for the occurrence of all-cause death. A fully automatic machine learning algorithm was trained on 3,700 scans and validated on 1,719 unseen CMR studies (MAGNETOM Aera and Skyra, Siemens Healthcare, Erlangen, Germany) to identify end-diastolic and end-systolic phases and segment LV volumes from short-axis cine images at stress. The algorithm combines multiple deep learning networks for detection and segmentation with an active contours approach. Manual and automatic LVEF measured at stress were compared with the paired Wilcoxon test, Pearson correlation and Bland-Altman analysis. Cox regressions were performed to determine the prognostic value of automatic LVEF measured at stress. Results Among 9,883 included patients included to this study, the automatic LVEF was successfully computed in 9,712 (98.3%) patients (66.6% male, mean age 66±12 years). The agreement between manual and automatic LVEF was good (bias = -0.01%, 95% limits of agreement, -6.7% to 6.7%; Pearson’s correlation coefficient r=0.94). A total of 504 (5.2%) deaths were observed during a median (IQR) follow-up period of 4.5 (3.7-5.2) years. Both manual and automatic volumetric assessments showed similar impact on outcome in univariate analyses (manual LVEF per 5%: hazard ratio [HR], 0.80 [95% CI 0.77–0.83]; p<0.001; automatic LVEF per 5%: HR, 0.84 [95% CI, 0.81–0.86]; p<0.001) and multivariable analyses (manual LVEF per 5%: HR, 0.81 [95% CI, 0.78–0.84]; p<0.001; automatic LVEF per 5%: HR, 0.84 [95% CI, 0.82–0.87]; p<0.001). Fully automatic stress LVEF showed an incremental prognostic value to predict all-cause mortality above all traditional risk factors, LVEF measured at rest, the presence of inducible ischemia and LGE (C-statistic improvement: 0.04; NRI=0.221; IDI=0.049; all p<0.001). Conclusions Automatic LVEF is equally predictive of all-cause mortality compared to manual LVEF, and has an incremental prognostic value compared to traditional risk factors, and other stress CMR parameters. Figures: Figure 1: Linear regression plots (A) and Bland-Altman plots (B) comparing stress LVEF measured by experts (LVEFexpert) and computed by fully-automated artificial-intelligence algorithms (LVEFAI). Figure 2: Kaplan-Meier curves for MACE stratified by fully-automated LVEF value. Test comparing the three groups is based on the log-rank test.

Residual ischemia by stress CMR in stable post-STEMI patients. Association with clinical events and implications of guided revascularization

Abstract Introduction Stress cardiac magnetic resonance (sCMR) represents a gold standard approach to identify and localize myocardial ischemia. However, in the setting of stable STEMI patients, data on the prognostic implications of residual ischemia as derived from sCMR are scarce. Moreover, the association of sCMR-guided revascularization with angina class improvement and patients’ outcomes is unknown. Objectives To evaluate the implications of residual ischemia and sCMR related revascularization with prognosis and anginal symptoms of STEMI patients after the index event. Material and methods Reperfused, stable STEMI patients submitted to undergo sCMR within the first year after STEMI were included in the registry. We analyzed the association of residual ischemia and sCMR related revascularization with the occurrence of major adverse cardiac events (MACE), comprised of all-cause death, non-fatal myocardial infarction, re-admission for heart failure, or unplanned revascularization. Additionally, we explored the effect of sCMR related revascularization on angina class as derived from the Canadian Cardiovascular Society (CCS) Angina Score. A p-value <0.05 was considered statistically significant. Results The study group was made up of 234 patients who underwent sCMR for evaluation of non-revascularized lesions in the non-culprit arteries (n=139, 59.4%) or assessment of new onset chest pain (n=95, 40.6%). Residual ischemia was noted in a minority of patients (n=63, 26.9%), and most of them presented with mild or moderate ischemic burden (n=56, 88.9% with residual ischemia in ≤5 myocardial segments). During a median follow up of 7.49 [3.03-10.02] years, 78 (33.3%) patients presented MACE. In multivariate analysis, the extent (number of segments) of residual ischemia did not associate with MACE (HR 0.97 [0.83-1.12] per segment, p=0.65). Patients were categorized in 3 groups: Group 1 (G1, no ischemia-no revascularization, n=166), Group 2 (G2, ischemia-no revascularization, n=29), and Group 3 (G3, ischemia-revascularization, n=34). No differences in survival free from MACE were noted between these groups. Most patients (n=192, 84.6%) were in CCS Angina Score Class I before sCMR. Patients in G1 remained asymptomatic or paucisymptomatic during follow-up (CCS II-IV between 4.8 and 9%, p>0.05). In G3, patients were predominantly in CCS II-IV (52.9%) before sCMR, and a significant reduction in anginal symptoms was noted after revascularization (CCS II-IV between 6.5 and 12.1%, p≤0.001). Patients with ischemia on sCMR but no revascularization (G2) depicted higher proportion of patients with CCS II-IV before (24.1%) and after sCMR (13 to 19.2%, p>0.05). Conclusions In STEMI patients evaluated post-discharge in stable phase, residual ischemia as derived from sCMR is usually mild and does not associate with the occurrence of MACE. sCMR-guided revascularization relates to a significant and sustained improvement of anginal symptoms but not to the event rate.Survival free from MACE.Changes in CCS Angina Score.

Stress computed tomography perfusion versus stress cardiac magnetic resonance for the management of suspected or known coronary artery disease: resources and outcomes impact (STRATEGY II Study)

Abstract Background Non-invasive techniques have evolved as "gatekeepers" to invasive coronary angiography (ICA) for symptomatic patients with suspected or known coronary artery disease (CAD). Evaluation of myocardial ischemia with functional tests represents a milestone in CAD detection with proved diagnostic and prognostic power. Coronary computed tomography angiography (CCTA), a non-invasive anatomical assessment, intrinsically lacks physiologic data to categorize the downstream hemodynamic significance of lesions. Stress CT perfusion (stress-CTP) is a recently evolved imaging modality able to assess inducible myocardial perfusion defects. The aim of this study is to compare resources and outcomes Impact of combined CCTA+stress-CTP versus stress cardiovascular magnetic resonance (stress-CMR) in consecutive symptomatic patients with suspected CAD and intermediate to high pre-test likelihood of disease or known CAD or previous history of revascularization. Methods 624 symptomatic patients with intermediate to high risk pre-test likelihood for CAD or previous history of revascularization referred to our hospital for clinically indicated CCTA+stress-CTP or stress-CMR were enrolled. Stress-CTP scans were performed in 223 patients using 256-row whole heart-coverage scanner, static protocol acquisition and vasodilation induced by adenosine. 401 patients with clinically indicated stress-CMR were evaluated in a 1.5-T scanner after vasodilatation induced with dipyridamole. Patient follow-up was performed at 1 year after index test performance. Endpoints were as follow: 1) all cardiac events as a combined endpoint of revascularization, non-fatal MI and death; 2) hard cardiac events as combined endpoint of non-fatal MI and death. Results Stress-CMR group showed lower age, higher prevalence of male gender and higher prevalence of previous revascularization, while CCTA+CTP group showed higher prevalence of family history of CAD and statin use. CCTA was defined positive for obstructive disease in 62% of patients while the addition of CTP on top of CCTA reduced the number of positive patients to 46%. Stress-CMR resulted positive in 23% of subjects. Patients who underwent CCTA+CTP underwent more revascularization (29% versus 7%, p: 0.001) while no differences were found in terms of non-fatal MI and death between the two strategies. According to the predefined endpoints, CCTA+CTP group showed higher rate of all cardiac events (29% vs 8%, p: 0.001) and lower rate of hard cardiac events (0.4% vs 3%, p: 0.033), respectively. Stratifying the baseline characteristics by all cardiac events and hard cardiac events, left ventricle volume and index test strategy predicted all cardiac events while only index test strategy predicted hard cardiac events. Conclusions The use of CCTA+CTP strategy was associated with higher referral to revascularization but with a protective trend in terms of hard cardiac events as compared to the usual strategy with lone functional evaluation.

Abstract 13882: Myocardial Hypoperfusion in Severe Aortic Stenosis is Reversed by Aortic Valve Replacement

Background: Myocardial hypoperfusion in severe aortic stenosis (AS) without obstructive coronary disease may be secondary to hemodynamic influences (and therefore readily reversible by aortic valve replacement[AVR]) or structural alterations in the left ventricle (LV) such as increased mass and reduction in capillary density. Aim: To evaluate the early effect of AVR on myocardial blood flow (MBF) in patients with severe symptomatic AS without flow-limiting coronary artery disease. Methods: Prospective case-control study of severe symptomatic AS without obstructive coronary disease referred for surgical or transcatheter AVR and propensity matched to a control cohort with unobstructed coronary arteries. Patients underwent adenosine stress cardiovascular magnetic resonance at baseline and 8-weeks (median) post-operatively. Histology from 9 myocardial septal biopsies taken at AVR were compared against necropsy controls (n=5). Results: 52 patients were included; 26 with severe AS (median [IQR] age 71[66-75], 73% male) and 26 age, sex and co-morbidity matched controls. In AS, peak velocity(Vmax) was 4.3m/s[4.1-4.5] and AVA 0.8cm 2 [0.6-0.9]. AS patients had greater LV mass and late gadolinium enhancement. AS patients had lower stress MBF than controls (1.63ml/g/min[1.38-2.08] vs 2.13[1.76-2.52], p=0.003) which increased to 1.97ml/g/min after AVR (p=0.7 post-AVR vs. Controls). This was driven by a 40% increase in subendocardial MBF (1.26ml/g/min[1.18-1.78] to 1.77[1.62-2.32]). Capillary density was reduced almost threefold in AS (495/mm 2 [407-686] vs 1376[1208-1579], p<0.001). Conclusions: Severe AS results in subendocardial hypoperfusion which is rapidly improved after AVR. There is a threefold reduction in capillary density, however factors related to elevated afterload (which is reduced by AVR) are the most influential.

Abstract 13074: Incremental Value of Abnormal Quantitative Myocardial Perfusion and Myocardial Infarction Using Cardiovascular Magnetic Resonance as Prognostic Markers in Type 2 Diabetes Mellitus

Introduction: Abnormal myocardial perfusion and MI are each associated with cardiovascular events in individuals with diabetes mellitus (DM). Hypothesis: We hypothesised that, in patients with T2DM, CMR determined quantitative myocardial perfusion and MI are independent predictors of major adverse cardiovascular and cerebrovascular events (MACCE) and that the presence of both offers incremental prognostic value. Methods: A prospective multicentre cohort of individuals with T2DM and healthy controls underwent stress CMR with inline quantitative myocardial perfusion and late gadolinium enhancement (LGE). Adjusted cox proportional hazard models (adjusted for age, sex, LVEF, LV end diastolic volume (LVEDV) and LV mass quantified associations between quantitative myocardial perfusion and MI with MACCE (composite of all-cause death, MI, stroke, heart failure hospitalisation and coronary revascularisation). Results: A total of 572 participants with T2DM from four centres and 52 healthy controls were followed for a median of 851 (IQR 765-935) days, during which 82 (14%) participants accrued at least one MACCE, including 25 (4%) deaths. Presence of either CMR pathology was associated with increased MACCE (normal quantitative myocardial perfusion and no MI: 7% MACCE; abnormal quantitative myocardial perfusion or MI: 13% MACCE (adjusted HR compared with normal 2.06 (95% CI 1.07-3.97, p=0.03)); and both abnormal quantitative myocardial perfusion and MI was associated with the highest event rate: 28% MACCE (adjusted HR compared with normal quantitative myocardial perfusion and no MI 4.55 (95% CI 2.32-8.90, p<0.001)). Conclusion: In individuals with T2DM, the presence of either abnormal quantitative myocardial perfusion or MI is associated with MACCE and the presence of both offers strong incremental prognostic value.