Quantitative Clinical Nuclear Cardiology, Part 1: Established Applications

Caffeine consumed prior to cardiac stress testing may affect diagnostic accuracy of nuclear medicine myocardial imaging of myocardial ischemia: A systematic review and meta-analysis

BACKGROUND

Myocardial perfusion imaging (MPI) is a well-established, non-invasive imaging procedure for the diagnosis and evaluation of patients with known or suspected coronary artery disease. With the increasing use of pharmacologic stress agents in myocardial perfusion imaging, strict preparation, including caffeine abstinence, is required. The aim of this review was to determine the effect of caffeine consumed prior to nuclear cardiac stress testing on the diagnostic accuracy.

METHODS

Medline, Embase and CINAHL were searched from the earliest available time until August 2022. Methodological quality was assessed using the Quality Assessment of Diagnostic Accuracy Studies version 2. Data pertaining to diagnostic accuracy were analysed using meta-analysis where appropriate and overall certainty of evidence evaluated using the Grades of Research, Assessment, Development and Evaluation approach.

RESULTS

Six studies (307 participants) from a yield of 735 articles were identified. Meta-analysis of two studies found no difference in the left ventricular ejection fraction of patients pre and post caffeine consumption (MD -0.31 %, 95% CI -4.32% to 3.7%). Meta-analysis of three studies found there was uncertainty as to whether caffeine consumption affected reversibility (MD -2.16 segments 95% CI -4.61 to 0.28) and descriptive summary of three studies found mixed results for size of stress defects.

CONCLUSION

The low quality evidence synthesized in this systematic review suggests caffeine may affect the diagnostic accuracy in myocardial perfusion imaging for ischemia detection in patients with chest pain and intermediate-to-high risk of coronary artery disease.

Multimodality cardiovascular imaging in hypertension

PURPOSE OF THE REVIEW

Hypertension accounts for the largest proportion of cardiovascular (CV) mortality worldwide and its prevalence continues to rise. While prominent CV societies have offered strong recommendations on the management of hypertension in adults, the role of noninvasive CV imaging in the evaluation of hypertensive patients remains incompletely defined.

RECENT FINDINGS

Noninvasive imaging is a rapidly expanding field with a growing number of sophisticated and readily applicable modalities to assess how cardiac structure and function changes after periods of sustained, elevated blood pressure. Echocardiography remains the initial modality to screen these patients while developments in nuclear, computed tomography and cardiac magnetic resonance complement and expand investigations for alternative diagnoses that may complement or conflict with the diagnosis of left ventricular hypertrophy.

SUMMARY

In this review article, we summarize the application of echocardiography, nuclear imaging, cardiac computed tomography, and cardiac magnetic resonance imaging in the evaluation and management of hypertensive heart disease.

Preparing for the Artificial Intelligence Revolution in Nuclear Cardiology

A major opportunity in nuclear cardiology is the many significant artificial intelligence (AI) applications that have recently been reported. These developments include using deep learning (DL) for reducing the needed injected dose and acquisition time in perfusion acquisitions also due to DL improvements in image reconstruction and filtering, SPECT attenuation correction using DL without need for transmission images, DL and machine learning (ML) use for feature extraction to define myocardial left ventricular (LV) borders for functional measurements and improved detection of the LV valve plane and AI, ML, and DL implementations for MPI diagnosis, prognosis, and structured reporting. Although some have, most of these applications have yet to make it to widespread commercial distribution due to the recency of their developments, most reported in 2020. We must be prepared both technically and socio-economically to fully benefit from these and a tsunami of other AI applications that are coming.

A highly predictive cardiac positron emission tomography (PET) risk score for 90-day and one-year major adverse cardiac events and revascularization

BACKGROUND

With the increase in cardiac PET/CT availability and utilization, the development of a PET/CT-based major adverse cardiovascular events, including death, myocardial infarction (MI), and revascularization (MACE-Revasc) risk assessment score is needed. Here we develop a highly predictive PET/CT-based risk score for 90-day and one-year MACE-Revasc.

METHODS AND RESULTS

11,552 patients had a PET/CT from 2015 to 2017 and were studied for the training and development set. PET/CT from 2018 was used to validate the derived scores (n = 5049). Patients were on average 65 years old, half were male, and a quarter had a prior MI or revascularization. Baseline characteristics and PET/CT results were used to derive the MACE-Revasc risk models, resulting in models with 5 and 8 weighted factors. The PET/CT 90-day MACE-Revasc risk score trended toward outperforming ischemic burden alone [P = .07 with an area under the curve (AUC) 0.85 vs 0.83]. The PET/CT one-year MACE-Revasc score was better than the use of ischemic burden alone (P < .0001, AUC 0.80 vs 0.76). Both PET/CT MACE-Revasc risk scores outperformed risk prediction by cardiologists.

CONCLUSION

The derived PET/CT 90-day and one-year MACE-Revasc risk scores were highly predictive and outperformed ischemic burden and cardiologist assessment. These scores are easy to calculate, lending to straightforward clinical implementation and should be further tested for clinical usefulness.

Does quantification of [11C]meta-hydroxyephedrine and [13N]ammonia kinetics improve risk stratification in ischemic cardiomyopathy

BACKGROUND

In ischemic cardiomyopathy patients, cardiac sympathetic nervous system dysfunction is a predictor of sudden cardiac arrest (SCA). This study compared abnormal innervation and perfusion measured by [11C]meta-hydroxyephedrine (HED) vs [13N]ammonia (NH3), conventional uptake vs parametric tracer analysis, and their SCA risk discrimination.

METHODS

This is a sub-study analysis of the prospective PAREPET trial, which followed ischemic cardiomyopathy patients with reduced left ventricular ejection fraction (LVEF ≤ 35%) for events of SCA. Using n = 174 paired dynamic HED and NH3 positron emission tomography (PET) scans, regional defect scores (%LV extent × severity) were calculated using HED and NH3 uptake, as well as HED distribution volume and NH3 myocardial blood flow by kinetic modeling.

RESULTS

During 4.1 years follow-up, there were 27 SCA events. HED defects were larger than NH3, especially in the lowest tertile of perfusion abnormality (P < .001). Parametric defects were larger than their respective tracer uptake defects (P < .001). SCA risk discrimination was not significantly improved with parametric or uptake mismatch (AUC = 0.73 or 0.70) compared to HED uptake defect scores (AUC = 0.67).

CONCLUSION

Quantification of HED distribution volume and NH3 myocardial blood flow produced larger defects than their respective measures of tracer uptake, but did not lead to improved SCA risk stratification vs HED uptake alone.

Reproducible Quantification of Regional Sympathetic Denervation with [11C]meta-Hydroxyephedrine PET Imaging

BACKGROUND

Regional cardiac sympathetic denervation is predictive of sudden cardiac arrest in patients with ischemic cardiomyopathy. The reproducibility of denervation scores between automated software programs has not been evaluated. This study seeks to (1) compare the inter-rater reliability of regional denervation measurements using two analysis programs: FlowQuant® and Corridor4DM®; (2) evaluate test-retest repeatability of regional denervation scores.

METHODS

N = 190 dynamic [11C]meta-hydroxyephedrine (HED) PET scans were reviewed from the PAREPET trial in ischemic cardiomyopathy patients with reduced left ventricular ejection fraction(LVEF ≤ 35%). N = 12 scans were excluded due to non-diagnostic quality. N = 178 scans were analyzed using FlowQuant and Corridor4DM software, each by two observers. Test-retest scans from N = 20 patients with stable heart failure were utilized for test-retest analysis. Denervation scores were defined as extent × severity of relative uptake defects in LV regions with < 75% of maximal uptake. Results were evaluated using intraclass correlation coefficient (ICC) and Bland-Altman coefficient of repeatability (RPC).

RESULTS

Inter-observer, inter-software, and test-retest ICC values were excellent (ICC = 94% to 99%) and measurement variability was small (RPC < 11%). Mean differences between observers ranged .2% to 1.1% for Corridor4DM (P = .28), FlowQuant (P < .001), and between software programs (P < .001). Kaplan-Meier analysis demonstrated HED scores from both programs were predictive of SCA.

CONCLUSION

Inter-rater reliability for both analysis programs was excellent and test-retest repeatability was consistent. The minimal difference in scores between FlowQuant and Corridor4DM supports their use in future trials.

Quantitative clinical nuclear cardiology, part 2: Evolving/emerging applications

Quantitative analysis has been applied extensively to image processing and interpretation in nuclear cardiology to improve disease diagnosis and risk stratification. This is Part 2 of a two-part continuing medical education article, which will review the potential clinical role for emerging quantitative analysis tools. The article will describe advanced methods for quantifying dyssynchrony, ventricular function and perfusion, and hybrid imaging analysis. This article discusses evolving methods to measure myocardial blood flow with positron emission tomography and single-photon emission computed tomography. Novel quantitative assessments of myocardial viability, microcalcification and in patients with cardiac sarcoidosis and cardiac amyloidosis will also be described. Lastly, we will review the potential role for artificial intelligence to improve image analysis, disease diagnosis, and risk prediction. The potential clinical role for all these novel techniques will be highlighted as well as methods to optimize their implementation.

Quantitative clinical nuclear cardiology, part 2: Evolving/emerging applications

Quantitative analysis has been applied extensively to image processing and interpretation in nuclear cardiology to improve disease diagnosis and risk stratification. This is Part 2 of a two-part continuing medical education article, which will review the potential clinical role for emerging quantitative analysis tools. The article will describe advanced methods for quantifying dyssynchrony, ventricular function and perfusion, and hybrid imaging analysis. This article discusses evolving methods to measure myocardial blood flow with positron emission tomography and single-photon emission computed tomography. Novel quantitative assessments of myocardial viability, microcalcification and in patients with cardiac sarcoidosis and cardiac amyloidosis will also be described. Lastly, we will review the potential role for artificial intelligence to improve image analysis, disease diagnosis, and risk prediction. The potential clinical role for all these novel techniques will be highlighted as well as methods to optimize their implementation. (J Nucl Cardiol 2020).