Effect of permanent right internal mammary artery occlusion on right coronary artery supply: A randomized placebo-controlled clinical trial

Clinical Efficacy of Permanent Internal Mammary Artery Occlusion in Chronic Coronary Syndrome: A Double-Blind, Randomized, Sham-Controlled Trial

The Clinical Efficacy of Permanent Internal Mammary Artery Occlusion in Chronic Coronary Syndrome (CLIMACCS) trial, a randomized, sham-controlled trial, tested the clinical efficacy of permanent internal mammary artery (IMA) device occlusion on symptoms in patients with chronic coronary syndrome (CCS), coronary artery occlusive blood supply, and myocardial ischemia. This was a prospective trial in 101 patients with CCS randomly allocated (1:1) to IMA device occlusion (verum group) or to IMA sham intervention (placebo group). The primary study end point was the change in treadmill exercise time (ET) (ΔET in seconds) at 6 weeks after trial intervention. Secondary study end points were the changes in collateral flow index (CFI) and angina pectoris during a simultaneous 1-minute proximal balloon occlusion of a coronary artery. CFI is the ratio between simultaneous mean coronary occlusive, divided by mean aortic pressure, both subtracted by central venous pressure. In the verum and placebo groups, the ET changed from 398 ± 176 seconds to 421 ± 198s in the verum group (p = 0.1745) and from 426 ± 162 seconds to 430 ± 166 seconds in the placebo group (p = 0.55); ΔET amounted to +23 ± 116s and +4 ± 120 seconds, respectively (p = 0.44). CFI change during follow-up equaled +0.022 ± 0.061 in the verum and -0.039 ± 0.072 in the placebo group (p <0.0001). Angina pectoris at follow-up during the coronary balloon occlusion for CFI measurement had decreased or disappeared in 20 of 48 patients in the verum group and in 9 of 47 patients in the placebo group (p = 0.0242). In conclusion, permanent IMA device occlusion tends to augment treadmill ET in response to increased coronary artery occlusive blood supply, which is reflected by mitigated symptoms and signs of myocardial ischemia.

Algorithm for real-time analysis of intracoronary electrocardiogram

Introduction

Since its first implementation in 1985, intracoronary (ic) electrocardiogram (ECG) has shown ample evidence for its diagnostic value given the higher sensitivity for myocardial ischemia detection in comparison to surface ECG. However, a lack of online systems to quantitatively analyze icECG in real-time prevents its routine use. The present study aimed to develop and validate an autonomous icECG analyzing algorithm.

Materials and methods

This is a retrospective observational study in 100 patients with chronic coronary syndrome. From each patient, a non-ischemic as well as ischemic icECG at the end of a 1-min proximal coronary balloon occlusion was available. An ECG expert as well as the newly developed algorithm for autonomous icECG analysis measured the icECG ST-segment shift in mV for each icECG tracing.

Results

Intraclass correlation coefficient (ICC) demonstrated low variability between the two methods (ICC = 0.968). Using the time point of icECG recording as allocation reference for absent or present myocardial ischemia, ROC-analysis for ischemia detection by the manually determined icECG ST-segment shift showed an area under the curve (AUC) of 0.968 ± 0.021 (p &lt; 0.0001). AUC for the algorithm analysis was 0.967 ± 0.023 (p &lt; 0.0001; p = 0.925 for the difference between the ROC curve AUCs). Time to complete analysis was below 1,000 ms for the autonomous icECG analysis and above 5 min for manual analysis.

Conclusion

A newly developed autonomous icECG analysing algorithm detects myocardial ischemia with equal accuracy as manual ST-segment shift assessment. The algorithm provides the technical fundament for an analysing system to quantitatively obtain icECG in real-time.

Extracardiac coronary steal induced by upper limb hyperemia: a feature of internal mammary artery arteriogenesis

Function of naturally existing internal mammary artery (IMA)-to-coronary artery anastomoses has been shown by augmented blood supply to the coronary collateral circulation in response to IMA occlusion. Theoretically, this beneficial functional connection is invertible and can be linked to coronary steal, the verification of whose hypothesis would provide alternate proof to the mentioned functional evidence. This was an observational study including 40 patients with chronic coronary syndrome, distal IMA occlusion, and upper limb hyperemia (verum group), and 40 propensity score matched controls (placebo group) without IMA occlusion or hyperemia. Primary study end point was the intergroup difference and temporal development in coronary collateral function (i.e., collateral flow index; CFI) as obtained at 30, 45, and 60 s following a proximal coronary artery balloon occlusion. CFI is the ratio between simultaneous mean coronary occlusive pressure divided by mean aortic pressure both subtracted by central venous pressure. To provoke a steal phenomenon, upper limb hyperemia was induced by upper arm blood pressure cuff deflation following a 5-min suprasystolic inflation ipsilateral to the sensor-wired coronary artery with release immediately after the first CFI measurement. Between the first and the second CFI measurement, CFI change (i.e., CFI@45s - CFI@30s) was absent in the verum group whereas there was CFI recruitment in the placebo group: 0.000 ± 0.023 and +0.009 ± 0.013, respectively; P = 0.032. Among patients with artificial distal IMA occlusion, induction of ipsilateral upper limb hyperemia provokes extracardiac coronary steal as expressed by temporarily absent collateral recruitment as it normally takes place without upper limb hyperemia.NEW & NOTEWORTHY Induction of ipsilateral upper limb hyperemia provokes extracardiac coronary steal among patients with artificial distal internal mammary artery occlusion. Coronary steal via the occluded internal mammary arteries serves as alternate proof of concept of the already existing evidence of their functional extracoronary collateral supply.

Detection of myocardial ischemia by intracoronary ECG using convolutional neural networks

INTRODUCTION

The electrocardiogram (ECG) is a valuable tool for the diagnosis of myocardial ischemia as it presents distinctive ischemic patterns. Deep learning methods such as convolutional neural networks (CNN) are employed to extract data-derived features and to recognize natural patterns. Hence, CNN enable an unbiased view on well-known clinical phenomenon, e.g., myocardial ischemia. This study tested a novel, hypothesis-generating approach using pre-trained CNN to determine the optimal ischemic parameter as obtained from the highly susceptible intracoronary ECG (icECG).

METHOD

This was a retrospective observational study in 228 patients with chronic coronary syndrome. Each patient had participated in clinical trials with icECG recording and ST-segment shift measurement at the beginning (i.e., non-ischemic) and the end (i.e., ischemic) of a one-minute proximal coronary artery balloon occlusion establishing the reference. Using these data (893 icECGs in total), two pre-trained, open-access CNN (GoogLeNet/ResNet101) were trained to recognize ischemia. The best performing CNN during training were compared with the icECG ST-segment shift for diagnostic accuracy in the detection of artificially induced myocardial ischemia.

RESULTS

Using coronary patency or occlusion as reference for absent or present myocardial ischemia, receiver-operating-characteristics (ROC)-analysis of manually obtained icECG ST-segment shift (mV) showed an area under the ROC-curve (AUC) of 0.903±0.043 (p<0.0001, sensitivity 80%, specificity 92% at a cut-off of 0.279mV). The best performing CNN showed an AUC of 0.924 (sensitivity 93%, specificity 92%). DeLong-Test of the ROC-curves showed no significant difference between the AUCs. The underlying morphology responsible for the network prediction differed between the trained networks but was focused on the ST-segment and the T-wave for myocardial ischemia detection.

CONCLUSIONS

When tested in an experimental setting with artificially induced coronary artery occlusion, quantitative icECG ST-segment shift and CNN using pathophysiologic prediction criteria detect myocardial ischemia with similarly high accuracy.

Accuracy of intracoronary ECG parameters for myocardial ischemia detection

INTRODUCTION

The electrocardiogram (ECG) is a valuable diagnostic tool for the diagnosis of myocardial ischemia during acute coronary syndrome. Aside from the commonly used ST-segment shift indicative of ischemia, several other ECG parameters are pathophysiologically reasonable. Thus, the goal of this study was to assess the accuracy of different ischemia parameters as obtained by the highly susceptible intracoronary ECG (icECG).

METHOD

This was a retrospective observational study in 100 patients with chronic coronary syndrome. From each patient, a non-ischemic as well as ischemic icECG at the end of a one-minute proximal coronary balloon occlusion was available, and analysed twice by three different physicians, as well as once together for consensual results. The evaluated parameters were icECG ST-segment shift (mV), ST-integral (mV*sec), T-wave-integral (mV*sec), T-peak (mV), T-peak-to-end time (TPE; msec) and QTc-time (msec).

RESULTS

All six icECG parameters showed significant differences between the non-ischemic and the ischemic recording. Using the icECG recording during coronary patency or occlusion as criterion for absent or present myocardial ischemia, ROC-analysis of icECG ST-segment shift showed an area under the curve (AUC) of 0.963 ± 0.029 (p < 0.0001). AUC for ST-integral was 0.899 ± 0.044 (p < 0.0001), for T-wave integral 0.791 ± 0.059 (p < 0.0001), for T-peak 0.811 ± 0.057 (p < 0.0001), for TPE 0.667 ± 0.068 (p < 0.0001), and for QTc-time 0.770 ± 0.061 (p < 0.0001). The best cut-off point for the detection of ischemia by icECG ST-segment shift was 0.365 mV (sensitivity 90%, specificity 95%).

CONCLUSION

When tested in a setting with artificially induced absolute myocardial ischemia, icECG ST-segment shift at a threshold of 0.365 mV most accurately distinguishes between absent and present ischemia.