Early silent coronary bypass graft occlusion following coronary bypass surgery, implication of routine coronary computed tomography angiography.

Objective: To evaluate incidence and predictors of early silent bypass occlusion following coronary bypass surgery using cardiac computed tomography angiography. Methods: A total of 439 consecutive patients with mean age of 66 ± 10 years comprising 17% (n = 75) females underwent isolated coronary bypass surgery followed by CT scan before discharge. Graft patency was evaluated in 1,319 anastomoses where 44% (n = 580) arterial and 56% (n = 739) vein graft anastomosis were performed. Cardiovascular risk factors, demographics, and intraoperative variables were analyzed. We conducted univariable and multivariable logistic regression analyses to analyze variables potentially associated with graft occlusion following CABG. Variables included gender, surgery duration, graft flow, pulsatility index, vein vs. artery graft, and recent MI. Results: Overall incidence of graft occlusion was 2.4% (31/1,319), and it was diagnosed in 6.6% (29/439) of patients. The difference in occlusion between arterial (2.1%) and vein (2.6%) grafts was not significant, p = 0.68. The duration of intervention p = 0.034, cross clamp time p = 0.024 as well the number of distal anastomosis p = 0.034 were significantly higher in occlusion group. The univariate and multivariate logistic regression indicated duration of surgery being predictive for bypass graft occlusion with OR = 1.18; 95% CI: 1.01-1.38; p = 0.035. Conclusions: Early graft occlusion was associated with surgical factors. The number of distant anastamoses, along duration of surgical intervention were, significantly influenced the risk of EGO. Prolonged procedural time reflecting complex coronary pathology and time-consuming revascularization procedure was as well associated to the elevated risk of occlusion.

Diagnostic and prognostic value of mannan-binding lectin associated protein (MAp19) for functionally relevant coronary artery disease.

BACKGROUND: This study aimed to evaluate the diagnostic and prognostic potential of MAp19, a regulating component of the lectin pathway of the complement system, in patients with suspected functionally relevant coronary artery disease (fCAD) as well as the determinants of MAp19 levels. METHODS: The presence of fCAD was adjudicated using myocardial perfusion imaging with single-photon emission tomography and, where available, coronary angiography. MAp19 levels were measured in participants at rest, at peak stress tests, and two hours after the stress. The study also tracked major cardiovascular events, including non-fatal myocardial infarction and cardiovascular death, over a five-year follow-up period. RESULTS: Among the 1,571 patients analyzed (32.3 % women), fCAD was identified in 462 individuals (29.4 %). MAp19 demonstrated no diagnostic significance, yielding an area under the curve (AUC) of 0.51 (0.47-0.55). Throughout the five-year follow-up, 107 patients (6.8 %) experienced non-fatal myocardial infarctions, 99 (6.3 %) had cardiovascular death, 194 (12.3 %) experienced all cause death and 50 (3.1 %) suffered a stroke. Cox and Kaplan-Meier analysis confirmed prognostic value of MAp19 for myocardial infarction, but not for cardiovascular death. Significant increases in the concentration of MAp19 were observed during bicycle (p = 0.001) and combined stress tests (p = 0.001). CONCLUSION: MAp19 demonstrated an association with the risk of myocardial infarction. Increases in MAp19 concentration were observed during bicycle and combined stress-tests.

Combining anatomical and biochemical markers in the detection and risk stratification of coronary artery disease.

AIM: We aimed to test the hypothesis if combining coronary artery calcium score (Ca-score) as a quantitative anatomical marker of coronary atherosclerosis with high-sensitive cardiac troponin as a quantitative biochemical marker of myocardial injury provided incremental value in the detection of functional relevant CAD (fCAD) and risk stratification. METHODS AND RESULTS: Consecutive patients undergoing myocardial perfusion SPECT (MPS) without prior CAD were enrolled. The diagnosis of fCAD was based on the presence of ischemia on MPS and coronary angiography- fCAD was centrally adjudicated in the diagnostic and prognostic domain. Diagnostic accuracy was evaluated using the area under receiver-operating characteristic curve. The composite of cardiovascular death and non-fatal acute myocardial infarction (AMI) within 730 days were the primary prognostic endpoints.Among 1715 patients eligible for the diagnostic analysis, 399 patients had fCAD. The combination of Ca-Score and hs-cTnT had good diagnostic accuracy for the diagnosis of fCAD, AUC 0.79 (95 % CI 0.77-0.81), but no incremental value compared to the Ca-score alone (AUC 0.79 (95%CI 0.77-0.81, p=0.965). Similar results were observed using hs-cTnI (AUC 0.80, 95%CI 0.77-0.82) instead of hs-cTnT.Among 1709 patients (99.7%) with available follow-up, 59 patients (3.5%) suffered the composite primary prognostic endpoint (nonfatal AMI n=34, CV death n=28).Both, Ca-score and hs-cTnT had independent prognostic value. Increased risk was restricted to patients with elevation in both markers. CONCLUSION: The combination of the Ca-score with hs-cTnT increases the prognostic accuracy for future events defining fCAD, but does not provide incremental value versus the Ca-Score alone for the diagnosis of fCAD.

Artificial intelligence to improve ischemia prediction in Rubidium Positron Emission Tomography-a validation study.

Background: Patients are referred to functional coronary artery disease (CAD) testing based on their pre-test probability (PTP) to search for myocardial ischemia. The recommended prediction tools incorporate three variables (symptoms, age, sex) and are easy to use, but have a limited diagnostic accuracy. Hence, a substantial proportion of non-invasive functional tests reveal no myocardial ischemia, leading to unnecessary radiation exposure and costs. Therefore, preselection of patients before ischemia testing needs to be improved using a more predictive and personalised approach. Aims: Using multiple variables (symptoms, vitals, ECG, biomarkers), artificial intelligence-based tools can provide a detailed and individualised profile of each patient. This could improve PTP assessment and provide a more personalised diagnostic approach in the framework of predictive, preventive and personalised medicine (PPPM). Methods: Consecutive patients (n = 2417) referred for Rubidium-82 positron emission tomography were evaluated. PTP was calculated using the ESC 2013/2019 and ACC 2012/2021 guidelines, and a memetic pattern-based algorithm (MPA) was applied incorporating symptoms, vitals, ECG and biomarkers. Five PTP categories from very low to very high PTP were defined (i.e., < 5%, 5-15%, 15-50%, 50-85%, > 85%). Ischemia was defined as summed difference score (SDS) ≥ 2. Results: Ischemia was present in 37.1%. The MPA model was most accurate to predict ischemia (AUC: 0.758, p < 0.001 compared to ESC 2013, 0.661; ESC 2019, 0.673; ACC 2012, 0.585; ACC 2021, 0.667). Using the < 5% threshold, the MPA's sensitivity and negative predictive value to rule out ischemia were 99.1% and 96.4%, respectively. The model allocated patients more evenly across PTP categories, reduced the proportion of patients in the intermediate (15-85%) range by 29% (ACC 2012)-51% (ESC 2019), and was the only tool to correctly predict ischemia prevalence in the very low PTP category. Conclusion: The MPA model enhanced ischemia testing according to the PPPM framework:The MPA model improved individual prediction of ischemia significantly and could safely exclude ischemia based on readily available variables without advanced testing ("predictive").It reduced the proportion of patients in the intermediate PTP range. Therefore, it could be used as a gatekeeper to prevent patients from further unnecessary downstream testing, radiation exposure and costs ("preventive").Consequently, the MPA model could transform ischemia testing towards a more personalised diagnostic algorithm ("personalised"). Supplementary Information: The online version contains supplementary material available at 10.1007/s13167-023-00341-5.

Diagnostic and prognostic value of H-ficolin for functionally relevant coronary artery disease.

BACKGROUND: We aimed to test the diagnostic and prognostic ability of H-ficolin, an initiator of the lectin pathway of the complement system, for functionally relevant coronary artery disease (fCAD), and explore its determinants. METHODS: The presence of fCAD was adjudicated using myocardial perfusion imaging single-photon emission tomography and coronary angiography. H-ficolin levels were measured by a sandwich-type immunoassay at rest, peak stress-test, and 2 h after stress-test. Cardiovascular death and non-fatal myocardial infarction were assessed during 5-year follow-up. RESULTS: Among 1,571 patients (32.3 % women), fCAD was detected in 462 patients (29.4 %). H-ficolin concentration at rest was 18.6 (15.3-21.8) µg/ml in patients with fCAD versus 17.8 (15.4-21.5) µg/ml, p = 0.33, in patients without fCAD, resulting in an AUC of 0.53 (95 %CI 0.48-0.56). During follow-up, 107 patients (6.8 %) had non-fatal myocardial infarction and 99 patients (6.3 %) experienced cardiovascular death. In Cox regression analysis, H-ficolin was not a predictor of events in the overall cohort. Subgroup analysis suggested a potential link between H-ficolin and non-fatal myocardial infarction in patients without fCAD (adjusted HR 1.03, 95 % CI 1.02-1.15, p = 0.005). H-ficolin concentration showed a weak positive correlation with systolic (r = 0.069, p < 0.001) and diastolic blood pressure (r = 0.111, p < 0.001). CONCLUSION: H-ficolin concentration did not have diagnostic and/or prognostic value in patients referred for fCAD work-up.

Coronary artery calcium score and pre-test probabilities as gatekeepers to predict and rule out perfusion defects in positron emission tomography.

BACKGROUND: Little is known about the gatekeeper performance of coronary artery calcium score (CACS) before myocardial perfusion positron emission tomography (PET), compared with updated pre-test probabilities from American and European guidelines (pre-test-AHA/ACC, pre-test-ESC). METHODS: We enrolled participants without known coronary artery disease undergoing CACS and Rubidium-82 PET. Abnormal perfusion was defined as summed stress score ≥ 4. Using Bayes' formula, pre-test probabilities and CACS were combined into post-test probabilities. RESULTS: We included 2050 participants (54% male, mean age 64.6 years) with median CACS 62 (IQR 0-380), pre-test-ESC 17% (11-26), pre-test-AHA/ACC 27% (16-44), and abnormal perfusion in 437 participants (21%). To predict abnormal perfusion, area under the curve of CACS was 0.81, pre-test-AHA/ACC 0.68, pre-test-ESC 0.69, post-test-AHA/ACC 0.80, and post-test-ESC 0.81 (P < 0.001 for CACS vs. each pre-test, and each post-test vs. pre-test). CACS = 0 had 97% negative predictive value (NPV), pre-test-AHA/ACC ≤ 5% 100%, pre-test-ESC ≤ 5% 98%, post-test-AHA/ACC ≤ 5% 98%, and post-test-ESC ≤ 5% 96%. Among participants, 26% had CACS = 0, 2% pre-test-AHA/ACC ≤ 5%, 7% pre-test-ESC ≤ 5%, 23% post-test-AHA/ACC ≤ 5%, and 33% post-test-ESC ≤ 5% (all P < 0.001). CONCLUSIONS: CACS and post-test probabilities are excellent predictors of abnormal perfusion and can rule it out with very high NPV in a substantial proportion of participants. CACS and post-test probabilities may be used as gatekeepers before advanced imaging. Coronary artery calcium score (CACS) predicted abnormal perfusion (SSS ≥ 4) in myocardial positron emission tomography (PET) better than pre-test probabilities of coronary artery disease (CAD), while pre-test-AHA/ACC and pre-test-ESC performed similarly (left). Using Bayes' formula, pre-test-AHA/ACC or pre-test-ESC were combined with CACS into post-test probabilities (middle). This calculation reclassified a substantial proportion of participants to low probability of CAD (0-5%), not needing further imaging, as shown for AHA/ACC probabilities (2% with pre-test-AHA/ACC to 23% with post-test-AHA/ACC, P < 0.001, right). Very few participants with abnormal perfusion were classified under pre-test or post-test probabilities 0-5%, or under CACS 0. AUC: area under the curve. Pre-test-AHA/ACC: Pre-test probability of the American Heart Association/American College of Cardiology. Post-test-AHA/ACC: Post-test probability combining pre-test-AHA/ACC and CACS. Pre-test-ESC: Pre-test probability of the European Society of Cardiology. SSS: Summed stress score.

Hypertensive Heart Disease-The Imaging Perspective.

Hypertensive heart disease (HHD) develops in response to the chronic exposure of the left ventricle and left atrium to elevated systemic blood pressure. Left ventricular structural changes include hypertrophy and interstitial fibrosis that in turn lead to functional changes including diastolic dysfunction and impaired left atrial and LV mechanical function. Ultimately, these changes can lead to heart failure with a preserved (HFpEF) or reduced (HFrEF) ejection fraction. This review will outline the clinical evaluation of a patient with hypertension and/or suspected HHD, with a particular emphasis on the role and recent advances of multimodality imaging in both diagnosis and differential diagnosis.

Serum neurofilament light chain in functionally relevant coronary artery disease and adverse cardiovascular outcomes.

Background: Functionally relevant coronary artery disease (fCAD), causing symptoms of myocardial ischemia, can currently only be reliably detected with advanced cardiac imaging. Serum neurofilament light chain (sNfL) is a biomarker for neuro-axonal injury known to be elevated by cardiovascular (CV) risk factors and cerebrovascular small-vessel diseases. Due to their pathophysiological similarities with fCAD and the link to CV risk factors, we hypothesised that sNfL may have diagnostic and prognostic value for fCAD and adverse cardiovascular outcomes.Methods: Of the large prospective Basel VIII study (NCT01838148), 4'016 consecutive patients undergoing cardiac work-up for suspected fCAD were included (median age 68 years, 32.5% women, 46.9% with history of CAD). The presence of fCAD was adjudicated using myocardial perfusion imaging single-photon emission tomography (MPI-SPECT) and coronary angiography. sNfL was measured using a high-sensitive single-molecule array assay. All-cause and cardiovascular death, myocardial infarction (MI), and stroke/transient ischaemic attack (TIA) during 5-year follow-up were the prognostic endpoints.Results: The diagnostic accuracy of sNfL for fCAD as quantified by the area under the curve (AUC) was low (0.58, 95%CI 0.56-0.60). sNfL was strongly associated with age, renal dysfunction, and body mass index and was a strong and independent predictor of all-cause death, cardiovascular death, and stroke/TIA but not MI. Time-dependent AUC for cardiovascular-death at 1-year was 0.85, 95%CI 0.80-0.89, and 0.81, 95%CI 0.77-0.86 at 2-years.Conclusion: While sNfL concentrations did not show a diagnostic role for fCAD, in contrast, sNfL was a strong and independent predictor of cardiovascular outcomes, including all-cause death, cardiovascular death and stroke/TIA.

The power of zero calcium in 82-Rubidium PET irrespective of sex and age.

BACKGROUND: Despite clinical suspicion, many non-invasive tests for coronary artery disease (CAD) are normal. Coronary artery calcification score (CACS) is a well-validated method to detect and risk stratify CAD. Patients with zero calcium score (ZCS) rarely have abnormal tests. Therefore, aims were to evaluate CACS as a gatekeeper to further functional downstream testing for CAD and estimate potential radiation and cost savings. METHODS: Consecutive patients with suspected CAD referred for PET were included (n = 2640). Prevalence and test characteristics of ZCS were calculated in different groups. Summed stress score ≥ 4 was considered abnormal and summed difference score ≥ 7 equivalent to ≥ 10% ischemia. To estimate potential radiation/cost reduction, PET scans were hypothetically omitted in ZCS patients. RESULTS: Mean age was 65 ± 11 years, 46% were female. 21% scans were abnormal and 26% of patients had ZCS. CACS was higher in abnormal PET (median 561 vs 27, P < 0.001). Abnormal PET was significantly less frequent in ZCS patients (2.6% vs 27.6%, P < 0.001). Sensitivity/negative predictive value (NPV) of ZCS to detect/exclude abnormal PET and ≥ 10% ischemia were 96.8% (95%-CI 95.0%-97.9%)/97.4% (95.9%-98.3%) and 98.9% (96.7%-99.6%)/99.6% (98.7%-99.9%), respectively. Radiation and cost reduction were estimated to be 23% and 22%, respectively. CONCLUSIONS: ZCS is frequent, and most often consistent with normal PET scans. ZCS offers an excellent NPV to exclude an abnormal PET and ≥ 10% ischemia across different gender and age groups. CACS is a suitable gatekeeper before advanced cardiac imaging, and potential radiation/cost savings are substantial. However, further studies including safety endpoints are needed.

Pulmonary transit time of cardiovascular magnetic resonance perfusion scans for quantification of cardiopulmonary haemodynamics.

AIMS: Pulmonary transit time (PTT) is the time blood takes to pass from the right ventricle to the left ventricle via pulmonary circulation. We aimed to quantify PTT in routine cardiovascular magnetic resonance imaging perfusion sequences. PTT may help in the diagnostic assessment and characterization of patients with unclear dyspnoea or heart failure (HF). METHODS AND RESULTS: We evaluated routine stress perfusion cardiovascular magnetic resonance scans in 352 patients, including an assessment of PTT. Eighty-six of these patients also had simultaneous quantification of N-terminal pro-brain natriuretic peptide (NTproBNP). NT-proBNP is an established blood biomarker for quantifying ventricular filling pressure in patients with presumed HF. Manually assessed PTT demonstrated low inter-rater variability with a correlation between raters >0.98. PTT was obtained automatically and correctly in 266 patients using artificial intelligence. The median PTT of 182 patients with both left and right ventricular ejection fraction >50% amounted to 6.8 s (Pulmonary transit time: 5.9-7.9 s). PTT was significantly higher in patients with reduced left ventricular ejection fraction (<40%; P < 0.001) and right ventricular ejection fraction (<40%; P < 0.0001). The area under the receiver operating characteristics curve (AUC) of PTT for exclusion of HF (NT-proBNP <125 ng/L) was 0.73 (P < 0.001) with a specificity of 77% and sensitivity of 70%. The AUC of PTT for the inclusion of HF (NT-proBNP >600 ng/L) was 0.70 (P < 0.001) with a specificity of 78% and sensitivity of 61%. CONCLUSION: PTT as an easily, even automatically obtainable and robust non-invasive biomarker of haemodynamics might help in the evaluation of patients with dyspnoea and HF.

Low-dose coronary artery calcium scoring compared to the standard protocol.

BACKGROUND: We aimed to compare coronary artery calcium scoring (CACS) with computed tomography (CT) with 80 and 120 kVp in a large patient population and to establish whether there is a difference in risk classification between the two scores. METHODS: Patients with suspected CAD undergoing MPS were included. All underwent standard CACS assessment with 120-kVp tube voltage and with 80 kVp. Two datasets (low-dose and standard) were generated and compared. Risk classes (0 to 25, 25 to 50, 50 to 75, 75 to 90, and > 90%) were recorded. RESULTS: 1511 patients were included (793 males, age 69 ± 9.1 years). There was a very good correlation between scores calculated with 120 and 80 kVp (R = 0.94, R2 = 0.88, P < .001), with Bland-Altman limits of agreement of - 563.5 to 871.9 and a bias of - 154.2. The proportion of patients assigned to the < 25% percentile class (P = .03) and with CACS = 0 differed between the two protocols (n = 264 vs 437, P < .001). CONCLUSION: In a large patient population, despite a good correlation between CACS calculated with standard and low-dose CT, there is a systematic underestimation of CACS with the low-dose protocol. This may have an impact especially on the prognostic value of the calcium score, and the established "power of zero" may no longer be warranted if CACS is assessed with low-dose CT.

Use of artificial intelligence to assess the risk of coronary artery disease without additional (non-invasive) testing: validation in a low-risk to intermediate-risk outpatient clinic cohort.

OBJECTIVES: Predicting the presence or absence of coronary artery disease (CAD) is clinically important. Pretest probability (PTP) and CAD consortium clinical (CAD2) model and risk scores used in the guidelines are not sufficiently accurate as the only guidance for applying invasive testing or discharging a patient. Artificial intelligence without the need of additional non-invasive testing is not yet used in this context, as previous results of the model are promising, but available in high-risk population only. Still, validation in low-risk patients, which is clinically most relevant, is lacking. DESIGN: Retrospective cohort study. SETTING: Secondary outpatient clinic care in one Dutch academic hospital. PARTICIPANTS: We included 696 patients referred from primary care for further testing regarding the presence or absence of CAD. The results were compared with PTP and CAD2 using receiver operating characteristic (ROC) curves (area under the curve (AUC)). CAD was defined by a coronary stenosis >50% in at least one coronary vessel in invasive coronary or CT angiography, or having a coronary event within 6 months. OUTCOME MEASURES: The first cohort validating the memetic pattern-based algorithm (MPA) model developed in two high-risk populations in a low-risk to intermediate-risk cohort to improve risk stratification for non-invasive diagnosis of the presence or absence of CAD. RESULTS: The population contained 49% male, average age was 65.6±12.6 years. 16.2% had CAD. The AUCs of the MPA model, the PTP and the CAD2 were 0.87, 0.80, and 0.82, respectively. Applying the MPA model resulted in possible discharge of 67.7% of the patients with an acceptable CAD rate of 4.2%. CONCLUSIONS: In this low-risk to intermediate-risk population, the MPA model provides a good risk stratification of presence or absence of CAD with a better ROC compared with traditional risk scores. The results are promising but need prospective confirmation.

Associations between fully-automated, 3D-based functional analysis of the left atrium and classification schemes in atrial fibrillation.

BACKGROUND: Atrial fibrillation (AF) has been linked to left atrial (LA) enlargement. Whereas most studies focused on 2D-based estimation of static LA volume (LAV), we used a fully-automatic convolutional neural network (CNN) for time-resolved (CINE) volumetry of the whole LA on cardiac MRI (cMRI). Aim was to investigate associations between functional parameters from fully-automated, 3D-based analysis of the LA and current classification schemes in AF. METHODS: We retrospectively analyzed consecutive AF patients who underwent cMRI on 1.5T systems including a stack of oblique-axial CINE series covering the whole LA. The LA was automatically segmented by a validated CNN. In the resulting volume-time curves, maximum, minimum and LAV before atrial contraction were automatically identified. Active, passive and total LA emptying fractions (LAEF) were calculated and compared to clinical classifications (AF Burden score (AFBS), increased stroke risk (CHA2DS2VASc≥2), AF type (paroxysmal/persistent), EHRA score, and AF risk factors). Moreover, multivariable linear regression models (mLRM) were used to identify associations with AF risk factors. RESULTS: Overall, 102 patients (age 61±9 years, 17% female) were analyzed. Active LAEF (LAEF_active) decreased significantly with an increase of AFBS (minimal: 44.0%, mild: 36.2%, moderate: 31.7%, severe: 20.8%, p<0.003) which was primarily caused by an increase of minimum LAV. Likewise, LAEF_active was lower in patients with increased stroke risk (30.7% vs. 38.9%, p = 0.002). AF type and EHRA score did not show significant differences between groups. In mLRM, a decrease of LAEF_active was associated with higher age (per year: -0.3%, p = 0.02), higher AFBS (per category: -4.2%, p<0.03) and heart failure (-12.1%, p<0.04). CONCLUSIONS: Fully-automatic morphometry of the whole LA derived from cMRI showed significant relationships between LAEF_active with increased stroke risk and severity of AFBS. Furthermore, higher age, higher AFBS and presence of heart failure were independent predictors of reduced LAEF_active, indicating its potential usefulness as an imaging biomarker.

Cardiovascular imaging following perioperative myocardial infarction/injury.

Patients developing perioperative myocardial infarction/injury (PMI) have a high mortality. PMI work-up and therapy remain poorly defined. This prospective multicenter study included high-risk patients undergoing major non-cardiac surgery within a systematic PMI screening and clinical response program. The frequency of cardiovascular imaging during PMI work-up and its yield for possible type 1 myocardial infarction (T1MI) was assessed. Automated PMI detection triggered evaluation by the treating physician/cardiologist, who determined selection/timing of cardiovascular imaging. T1M1 was considered with the presence of a new wall motion abnormality within 30 days in transthoracic echocardiography (TTE), a new scar or ischemia within 90 days in myocardial perfusion imaging (MPI), and Ambrose-Type II or complex lesions within 7 days of PMI in coronary angiography (CA). In patients with PMI, 21% (268/1269) underwent at least one cardiac imaging modality. TTE was used in 13% (163/1269), MPI in 3% (37/1269), and CA in 5% (68/1269). Cardiology consultation was associated with higher use of cardiovascular imaging (27% versus 13%). Signs indicative of T1MI were found in 8% of TTE, 46% of MPI, and 63% of CA. Most patients with PMI did not undergo any cardiovascular imaging within their PMI work-up. If performed, MPI and CA showed high yield for signs indicative of T1MI.Trial registration: https://clinicaltrials.gov/ct2/show/NCT02573532 .