Noninvasive Stress Testing for Coronary Artery Disease

Multimodality Imaging in Advanced Heart Failure for Diagnosis, Management and Follow-Up: A Comprehensive Review

Advanced heart failure (AHF) presents a complex landscape with challenges spanning diagnosis, management, and patient outcomes. In response, the integration of multimodality imaging techniques has emerged as a pivotal approach. This comprehensive review delves into the profound significance of these imaging strategies within AHF scenarios. Multimodality imaging, encompassing echocardiography, cardiac magnetic resonance imaging (CMR), nuclear imaging and cardiac computed tomography (CCT), stands as a cornerstone in the care of patients with both short- and long-term mechanical support devices. These techniques facilitate precise device selection, placement, and vigilant monitoring, ensuring patient safety and optimal device functionality. In the context of orthotopic cardiac transplant (OTC), the role of multimodality imaging remains indispensable. Echocardiography offers invaluable insights into allograft function and potential complications. Advanced methods, like speckle tracking echocardiography (STE), empower the detection of acute cell rejection. Nuclear imaging, CMR and CCT further enhance diagnostic precision, especially concerning allograft rejection and cardiac allograft vasculopathy. This comprehensive imaging approach goes beyond diagnosis, shaping treatment strategies and risk assessment. By harmonizing diverse imaging modalities, clinicians gain a panoramic understanding of each patient's unique condition, facilitating well-informed decisions. The aim is to highlight the novelty and unique aspects of recently published papers in the field. Thus, this review underscores the irreplaceable role of multimodality imaging in elevating patient outcomes, refining treatment precision, and propelling advancements in the evolving landscape of advanced heart failure management.

Fusion Modeling: Combining Clinical and Imaging Data to Advance Cardiac Care

In addition to the traditional clinical risk factors, an increasing amount of imaging biomarkers have shown value for cardiovascular risk prediction. Clinical and imaging data are captured from a variety of data sources during multiple patient encounters and are often analyzed independently. Initial studies showed that fusion of both clinical and imaging features results in superior prognostic performance compared with traditional scores. There are different approaches to fusion modeling, combining multiple data resources to optimize predictions, each with its own advantages and disadvantages. However, manual extraction of clinical and imaging data is time and labor intensive and often not feasible in clinical practice. An automated approach for clinical and imaging data extraction is highly desirable. Convolutional neural networks and natural language processing can be utilized for the extraction of electronic medical record data, imaging studies, and free-text data. This review outlines the current status of cardiovascular risk prediction and fusion modeling; and in addition gives an overview of different artificial intelligence approaches to automatically extract data from images and electronic medical records for this purpose.

High-Resolution Tactile-Sensation Diagnostic Imaging System for Thyroid Cancer

In this study, we propose the direct diagnosis of thyroid cancer using a small probe. The probe can easily check the abnormalities of existing thyroid tissue without relying on experts, which reduces the cost of examining thyroid tissue and enables the initial self-examination of thyroid cancer with high accuracy. A multi-layer silicon-structured probe module is used to photograph light scattered by elastic changes in thyroid tissue under pressure to obtain a tactile image of the thyroid gland. In the thyroid tissue under pressure, light scatters to the outside depending on the presence of malignant and positive properties. A simple and easy-to-use tactile-sensation imaging system is developed by documenting the characteristics of the organization of tissues by using non-invasive technology for analyzing tactile images and judging the properties of abnormal tissues.

Segmental Tissue Speckle Tracking Predicts the Stenosis Severity in Patients With Coronary Artery Disease

Objective

Two-dimensional speckle tracking echocardiography (2D-STE) has been used as a diagnostic tool for coronary artery disease (CAD). However, whether vessel supplied myocardial strain and strain rate (SR) predict the severity of coronary artery stenosis in patients with CAD is unknown. This study aimed to investigate correlation of cardiac mechanical parameters in tissue speckle tracking measurements with coronary artery stenosis diagnosed by cardiac catheterization in patients with clinically diagnosed CAD.

Methods and Results

Among 59 patients analyzed, 170 vessels were evaluated by coronary angiography and the corresponding echocardiography to quantify left ventricular myocardial strain and SR. The average longitudinal strain and SR of the segmental myocardium supplied by each coronary artery were calculated to achieve vessel myocardium strain (VMS) and strain rate (VMSR). The VMS and VMSR at each of four severity levels of stenosis showed significant differences among groups (p = 0.016, and p < 0.001, respectively). The strain and SR in vessels with very severe stenosis (≥75%, group IV; n = 29), 13.9 ± 4.3, and 0.9 ± 0.3, respectively, were significantly smaller than those of vessels with mild stenosis ≤ 25%, group I; n = 88, 16.9 ± 4.9, p = 0.023, and 1.2 ± 0.3, p = 0.001, respectively. The SR in vessels with moderate stenosis (26–49%, group II; n = 37), 1.0 ± 0.2, was significantly smaller than that in vessels with mild stenosis vessels (p = 0.021). The lower VMS and VMSR, the higher possibility of severe coronary stenosis is. The VMS and VMSR lower than 13.9 ± 4.3 and 0.9 ± 0.3, respectively predicted the severe coronary stenosis. The VMS and VMSR higher than 16.9 ± 4.9 and 1.2 ± 0.3, respectively predicted mild or no coronary artery stenosis.

Conclusions

The actual stenosis rate in catheterization demonstrates that this technique was able to assess coronary artery condition. Thus, the application of a non-invasive method of 2D-STE to evaluate and simplify diagnosis of CAD is feasible.

Performance and Interpretation of Office Exercise Stress Testing

In an era where cardiovascular disease continues to increase in prevalence, chest pain is a commonly encountered complaint in the outpatient setting. Clinicians are often tasked with the challenge of selecting the most appropriate screening tool in the evaluation of a patient with suspected coronary artery disease. With proper consideration of indications and contraindications, exercise electrocardiogram (ECG) stress testing is an accessible, cost-conscious, and validated outpatient diagnostic modality for predicting coronary artery disease.

Clinical Utility of Stress Echocardiography in Remote Indigenous and Non-Indigenous Populations: A 10-Year Study in Central Australia

BACKGROUND

Remote Central Australia has a large Indigenous population and a significant burden of cardiovascular disease. Stress echocardiography has been previously validated as a useful investigation for long-term prognostication. However, there are no prior studies assessing its utility in remote or Indigenous populations.

METHOD

Consecutive individuals undergoing stress echocardiography in Central Australia between 2007 and 2017 were included. Stress echocardiography was performed and reported via standard protocols. Individuals were followed up for all-cause mortality.

RESULTS

One-thousand and eight patients (1,008) (54% Indigenous Australian) were included. After a mean follow-up of 3.5±2.4 years, 54 (5%) patients were deceased. Overall, 797 (79%) patients had no abnormalities during rest or stress echocardiography, with no difference according to ethnicity (p>0.05). In patients with a normal test, annual mortality averaged 1.3% over 5 years of follow-up, with annual mortality significantly higher in Indigenous compared to non-Indigenous individuals (1.8% vs 0.6% respectively). In those with an abnormal test, annual mortality was 4.4% vs 1.3% in Indigenous and non-Indigenous individuals respectively. Increasing age, Indigenous ethnicity and cardiometabolic comorbidities were associated with mortality in univariate analyses (p<0.05 for all). In multivariate models, only chronic kidney disease remained predictive of mortality, with other associations (including Indigenous ethnicity) becoming attenuated.

CONCLUSION

This is the first study to report on the use of stress echocardiography in a remote or Indigenous population. A normal stress echocardiogram in remote Indigenous individuals was able to identify a lower risk group of patients in this setting. Although Indigenous individuals with a normal test still had a higher annual rate of mortality compared to non-Indigenous individuals, this association appeared to be mediated by cardiometabolic comorbidities.

Preoperative nuclear stress testing in the very old patient population

BACKGROUND

Elderly patients awaiting moderate to high-risk surgery may undergo nuclear stress testing (NST) in order to evaluate their cardiovascular risk. The prognostic utility of such testing in the very elderly (≥ 85 years) has yet to be fully evaluated. Octogenarians and nonogenarians frequently have a number of concurrent conditions including a high rate of coronary disease, and therefore the prognostic value of NST for their preoperative risk assessment has been questioned. Our evaluation assesses the ability of nuclear stress testing to predict peri-operative cardiac outcomes in this patient population.

AIM

To investigate the ability of NST to predict peri-operative cardiac outcomes in elderly patients awaiting moderate to high-risk surgery.

METHODS

Patients ≥ 85 years undergoing pre-operative NST were retrospectively evaluated. Patients undergoing low-risk surgery were excluded. Major adverse cardiac events (MACE) were considered any adverse event that occurred prior to discharge and included acute heart failure, arrhythmia, acute myocardial infarction, unstable angina, or death. Associations between patient risk factors, MACE, and the obtained results of the pre-operative stress testing, ejection fraction (< 40% or ≥ 40%), summed stress score (≤ 8, ≥ 9), and the summed difference score (≤ 0, > 0) were analyzed.

RESULTS

A total of 69 patients (mean age 88 ± 2.6 years, 31 males) underwent nuclear stress testing prior to surgery. There were 41 (60%) patients found to have an abnormal NST. Sixteen (23%) patients were noted to experience post-operative MACE. No significant associations between risk factors and MACE were noted. Patients with an abnormal NST and/or a summed stress score ≥ 9 were significantly (P < 0.01) more likely to develop peri-operative MACE.

CONCLUSION

Indicated preoperative NST is useful to assess pre-operative risk in elderly patients ≥ 85 years undergoing moderate to high-risk surgery.

Artificial neural network-based model enhances risk stratification and reduces non-invasive cardiac stress imaging compared to Diamond-Forrester and Morise risk assessment models: A prospective study

BACKGROUND

Coronary artery disease (CAD) accounts for more than half of all cardiovascular events. Stress testing remains the cornerstone for non-invasive assessment of patients with possible or known CAD. Clinical utilization reviews show that most patients presenting for evaluation of stable CAD by stress testing are categorized as low risk prior to the test. Attempts to enhance risk stratification of individuals who are sent for stress testing seem to be more in need today. The present study compares artificial neural networks (ANN)-based prediction models to the other risk models being used in practice (the Diamond-Forrester and the Morise models).

METHODS

In our study, we prospectively recruited patients who were 19 years of age or older, and were being evaluated for coronary artery disease with imaging-based stress tests. For ANN, the network architecture employed a systematic method, where the number of neurons is changed incrementally, and bootstrapping was performed to evaluate the accuracy of the models.

RESULTS

We prospectively enrolled 486 patients. The mean age of patients undergoing stress test was 55.2 ± 11.2 years, 35% were women, and 12% had a positive stress test for ischemic heart disease. When compared to Diamond-Forrester and Morise risk models, the ANN model for predicting ischemia provided higher discriminatory power (DP)(1.61), had a negative predictive value of 98%, Sensitivity 91% [81%-97%], Specificity 65% [60%-79%], positive predictive value 26%, and a potential 59% reduction of non-invasive imaging.

CONCLUSION

The ANN models improved risk stratification when compared to the other risk scores (Diamond-Forrester and Morise) with a 98% negative predictive value and a significant potential reduction in non-invasive imaging tests.

Adding value to myocardial perfusion SPECT/CT studies that include coronary calcium CT: Detection of incidental pulmonary arterial dilatation

The aim of the present study was to evaluate the incidence of undiagnosed pulmonary arterial dilatation using the gated computed tomography (CT) images acquired in patients with an otherwise normal Tc-sestamibi single-photon-emission CT (SPECT)/CT myocardial perfusion study.This was a retrospective review of 200 consecutive patients (100 men, mean age 58.7 years) who underwent a myocardial perfusion Tc-sestamibi SPECT/CT study with normal perfusion and with gated CT images acquired for coronary calcium scoring. The CT images were reviewed using a previously validated mean main pulmonary artery diameter (mPAD) measurement method which has been correlated with pulmonary arterial hypertension (PAH). Clinical information on multiple comorbidities was also retrieved. Previously reported mPAD cutoffs (>29.5 and >31.5 mm) were used to stratify patients.Indications for the study included dyspnea on exertion (58.9%), preoperative workup (22.3%), and chest pain (13.9%). The mean mPAD measurement was 26.3 mm (±0.5). There was a significant correlation between body mass index and mPAD (correlation coefficient [ρ]: 0.28; P < .001). About 23% (46/200) of patients had mPAD > 29.5 mm and 15.0% (30/200) of patients had mPAD > 31.5 mm. From previous work, these cutoffs have a sensitivity and specificity for PAH of 70.8%, 79.4% and 52.0%, 90.2%, respectively. Among patients undergoing a preoperative myocardial perfusion study, 35.6% (16/45) patients had mPAD > 29.5 mm and 26.7% (12/45) patients had mPAD > 31.5 mm. There was a higher prevalence of congestive heart failure (62.5% vs 19.6%; P < .001) and hypertension (78.3% vs 21.7%; P < .02) in patients with mPAD > 29.5 mm. Similarly, there was a high prevalence of congestive heart failure (P < .001), hyperlipidemia (P < .04), and hypertension (P < .04) in patients with mPAD > 31.5 mm.Incidental pulmonary arterial dilatation (mPAD ≥ 29.5 mm) can be detected in a large number of patients with normal myocardial perfusion scintigraphy and correlates with multiple different comorbidities. The mPAD can be measured in all patients undergoing gated imaging as part of a myocardial perfusion study, and PAH may be considered as an alternative explanation for symptoms in some patients without perfusion deficits. The data to make this potential diagnosis is already being acquired and represents an opportunity to add value to the interpretations of otherwise negative myocardial perfusion studies.