Quantitative relationship between coronary artery calcium and myocardial blood flow by hybrid rubidium-82 PET/CT imaging in patients with suspected coronary artery disease

BACKGROUND: We assessed the relationship between coronary artery calcium (CAC) score, myocardial blood flow (MBF) and coronary flow reserve (CFR) in patients undergoing hybrid 82Rb positron emission tomography (PET)/computed tomography (CT) imaging for suspected CAD. We also evaluated if CAC score is able to predict a reduced CFR independently from conventional coronary risk factors. METHODS: A total of 637 (mean age 58 ± 13 years) consecutive patients were studied. CAC score was measured according to the Agatston method and patients were categorized into 4 groups (0, 0.01-99.9, 100-399.9, and ≥400). Baseline and hyperemic MBF were automatically quantified. CFR was calculated as the ratio of hyperemic to baseline MBF and it was considered reduced when <2. RESULTS: Global CAC score showed a significant inverse correlation with hyperemic MBF and CFR (both P < .001), while no correlation between CAC score and baseline MBF was found. At multivariable logistic regression analysis age, diabetes and CAC score were independently associated with reduced CFR (all P < .001). The addition of CAC score to clinical data increased the global chi-square value for predicting reduced CFR from 81.01 to 91.13 (P < .01). Continuous net reclassification improvement, obtained by adding CAC score to clinical data, was 0.36. CONCLUSIONS: CAC score provides incremental information about coronary vascular function over established CAD risk factors in patients with suspected CAD and it might be helpful for identifying those with a reduced CFR

Relation between myocardial blood flow and cardiac events in diabetic patients with suspected coronary artery disease and normal myocardial perfusion imaging

Background: We assessed the prognostic value of structural abnormalities and coronary vasodilator function in diabetic patients referred to a PET/CT for suspected coronary artery disease (CAD). Methods: We studied 451 diabetics and 451 nondiabetics without overt CAD and normal myocardial perfusion. Myocardial blood flow (MBF) was computed from the dynamic rest and stress imaging. Myocardial flow reserve (MFR) was defined as ratio of hyperemic to baseline MBF and was considered reduced when < 2. Results: During a mean follow-up of 44 months 33 events occurred. Annualized event rate (AER) was higher in diabetic than nondiabetic patients (1.4% vs 0.3%, P < .001). Diabetic patients with reduced MFR had higher AER compared to those with preserved MFR (3.3% vs 0.4%, P < .001). At Cox analysis, age, BMI and reduced MFR were independent predictors of events in diabetic patients. Patients with diabetes and reduced MFR had lower event-free survival compared to nondiabetic patients and MFR < 2 (P < .001). Event-free survival was similar in patients with diabetes and normal MFR and those without diabetes and reduced MFR. Conclusions: Diabetic patients with reduced MFR had higher AER and lower event-free survival compared to those with preserved MFR and to nondiabetic patients

Prognostic value of coronary vascular dysfunction assessed by rubidium-82 PET/CT imaging in patients with resistant hypertension without overt coronary artery disease

Purpose: The identification of coronary vascular dysfunction may enhance risk stratification in patients with resistant hypertension (RH). We evaluated if impaired coronary vascular function, assessed by rubidium-82 (82Rb) positron emission tomography/computed tomography (PET/CT) imaging, is associated with increased cardiovascular risk in patients with hypertension without overt coronary artery disease (CAD). Methods: We studied 517 hypertensive subjects, 26% with RH, without overt CAD, and with normal stress-rest myocardial perfusion imaging at 82Rb PET/CT. The outcome end points were cardiac death, nonfatal myocardial infarction, coronary revascularization, and admission for heart failure. Results: Over a median of 38 months (interquartile range 26 to 50), 21 cardiac events (4.1% cumulative event rate) occurred. Patients with RH were older (p < 0.05) and had a higher prevalence of left ventricular hypertrophy (p < 0.001), a lower hyperemic myocardial blood flow (MBF), and myocardial perfusion reserve (MPR) (both p < 0.001) compared to those without. Conversely, coronary artery calcium content and baseline MBF were not different between patients with and without RH. At univariable Cox regression analysis, age, RH, left ventricular ejection fraction, coronary artery calcium score, and reduced MPR were significant predictors of events. At multivariable analysis, age, RH, and reduced MPR (all p < 0.05) were independent predictors of events. Patients with RH and reduced MPR had the highest risk of events and the major risk acceleration over time. Conclusion: The findings suggest that the assessment of coronary vascular function may enhance risk stratification in patients with hypertension

A Comparison among different machine learning pretest approaches to predict stress-Induced ischemia at PET/CT myocardial perfusion imaging

Traditional approach for predicting coronary artery disease (CAD) is based on demographic data, symptoms such as chest pain and dyspnea, and comorbidity related to cardiovascular diseases. Usually, these variables are analyzed by logistic regression to quantifying their relationship with the outcome; nevertheless, their predictive value is limited. In the present study, we aimed to investigate the value of different machine learning (ML) techniques for the evaluation of suspected CAD; having as gold standard, the presence of stress-induced ischemia by 82Rb positron emission tomography/computed tomography (PET/CT) myocardial perfusion imaging (MPI) ML was chosen on their clinical use and on the fact that they are representative of different classes of algorithms, such as deterministic (Support vector machine and Naïve Bayes), adaptive (ADA and AdaBoost), and decision tree (Random Forest, rpart, and XGBoost). The study population included 2503 consecutive patients, who underwent MPI for suspected CAD. To testing ML performances, data were split randomly into two parts: training/test (80%) and validation (20%). For training/test, we applied a 5-fold cross-validation, repeated 2 times. With this subset, we performed the tuning of free parameters for each algorithm. For all metrics, the best performance in training/test was observed for AdaBoost. The Naïve Bayes ML resulted to be more efficient in validation approach. The logistic and rpart algorithms showed similar metric values for the training/test and validation approaches. These results are encouraging and indicate that the ML algorithms can improve the evaluation of pretest probability of stress-induced myocardial ischemia

Coronary Atherosclerotic Plaque Activity and Future Coronary Events

This study was funded by a Wellcome Trust Senior Investigator Award (WT103782AIA). Image analysis was supported by National Institutes for Health (R34HL161195 and 1R01HL135557). The content is solely the responsibility of the authors and does not necessarily represent the official views of the Wellcome Trust or the National Institutes of Health. The British Heart Foundation supports DEN (CH/09/002, RG/16/10/32375, RE/18/5/34216), MRD (FS/SCRF/21/32010), NLM (CH/F/21/90010, RG/20/10/34966, RE/18/5/34216) AJM (AA/18/3/34220) and MCW (FS/ICRF/20/26002) and DD (FS/RTF/20/30009, NH/19/1/34595, PG/18/35/33786, PG/15/88/31780, PG/17/64/33205). MRD is the recipient of the Sir Jules Thorn Award for Biomedical Research 2015 (15/JTA). PJS is supported by outstanding investigator award National Institutes for Health (R35HL161195). JK is supported by the National Science Centre 2021/41/B/NZ5/02630. EvB is supported by SINAPSE (www.sinapse.ac.uk). AB is supported by a Clinical Research Training Fellowships (MR/V007254/1). DD is supported by Chest Heart and Stroke Scotland (19/53), Tenovus Scotland (G.18.01), and Friends of Anchor and Grampian NHS-Endowments. The Edinburgh Clinical Research Facilities, Edinburgh Imaging facility and Edinburgh Clinical Trials Unit are supported by the National Health Service Research Scotland through National Health Service Lothian Health Board. The Leeds Clinical Research Facilities are supported by the UK National Institute for Health Research (NIHR) via its Clinical Research Facility programme. The work at Cedars-Sinai Medical Center (the Los Angeles site) was supported in part by the Dr. Miriam and Sheldon G. Adelson Medical Research Foundation. For the purpose of open access, the author has applied a Creative Commons Attribution (CC BY) licence to any Author Accepted Manuscript version arising from this submission. The Chief Investigator and Edinburgh Clinical Trials Unit had full access to all the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis.Peer reviewedPostprin