Reporting nuclear cardiology: a joint position paper by the European Association of Nuclear Medicine (EANM) and the European Association of Cardiovascular Imaging (EACVI)

A systematic review for the evidence of recommendations and guidelines in hybrid nuclear cardiovascular imaging

OBJECTIVES

This study aimed to evaluate the level of evidence of expert recommendations and guidelines for clinical indications and procedurals in hybrid nuclear cardiovascular imaging.

METHODS

From inception to August 2023, a PubMed literature analysis of the latest version of guidelines for clinical hybrid cardiovascular imaging techniques including SPECT(/CT), PET(/CT), and PET(/MRI) was performed in two categories: (1) for clinical indications for all-in primary diagnosis; subgroup in prognosis and therapy evaluation; and for (2) imaging procedurals. We surveyed to what degree these followed a standard methodology to collect the data and provide levels of evidence, and for which topic systematic review evidence was executed.

RESULTS

A total of 76 guidelines, published between 2013 and 2023, were included. The evidence of guidelines was based on systematic reviews in 7.9% of cases, non-systematic reviews in 47.4% of cases, a mix of systematic and non-systematic reviews in 19.7%, and 25% of guidelines did not report any evidence. Search strategy was reported in 36.8% of cases. Strengths of recommendation were clearly reported in 25% of guidelines. The notion of external review was explicitly reported in 23.7% of cases. Finally, the support of a methodologist was reported in 11.8% of the included guidelines.

CONCLUSION

The use of evidence procedures for developing for evidence-based cardiovascular hybrid imaging recommendations and guidelines is currently suboptimal, highlighting the need for more standardized methodological procedures.

Patient-level explainable machine learning to predict major adverse cardiovascular events from SPECT MPI and CCTA imaging

BACKGROUND

Machine learning (ML) has shown promise in improving the risk prediction in non-invasive cardiovascular imaging, including SPECT MPI and coronary CT angiography. However, most algorithms used remain black boxes to clinicians in how they compute their predictions. Furthermore, objective consideration of the multitude of available clinical data, along with the visual and quantitative assessments from CCTA and SPECT, are critical for optimal patient risk stratification. We aim to provide an explainable ML approach to predict MACE using clinical, CCTA, and SPECT data.

METHODS

Consecutive patients who underwent clinically indicated CCTA and SPECT myocardial imaging for suspected CAD were included and followed up for MACEs. A MACE was defined as a composite outcome that included all-cause mortality, myocardial infarction, or late revascularization. We employed an Automated Machine Learning (AutoML) approach to predict MACE using clinical, CCTA, and SPECT data. Various mainstream models with different sets of hyperparameters have been explored, and critical predictors of risk are obtained using explainable techniques on the global and patient levels. Ten-fold cross-validation was used in training and evaluating the AutoML model.

RESULTS

A total of 956 patients were included (mean age 61.1 ±14.2 years, 54% men, 89% hypertension, 81% diabetes, 84% dyslipidemia). Obstructive CAD on CCTA and ischemia on SPECT were observed in 14% of patients, and 11% experienced MACE. ML prediction's sensitivity, specificity, and accuracy in predicting a MACE were 69.61%, 99.77%, and 96.54%, respectively. The top 10 global predictive features included 8 CCTA attributes (segment involvement score, number of vessels with severe plaque ≥70, ≥50% stenosis in the left marginal coronary artery, calcified plaque, ≥50% stenosis in the left circumflex coronary artery, plaque type in the left marginal coronary artery, stenosis degree in the second obtuse marginal of the left circumflex artery, and stenosis category in the marginals of the left circumflex artery) and 2 clinical features (past medical history of MI or left bundle branch block, being an ever smoker).

CONCLUSION

ML can accurately predict risk of developing a MACE in patients suspected of CAD undergoing SPECT MPI and CCTA. ML feature-ranking can also show, at a sample- as well as at a patient-level, which features are key in making such a prediction.

Variability of [18F]FDG-PET/LDCT reporting in vascular graft and endograft infection

PURPOSE

18F-fluoro-D-deoxyglucose positron emission tomography with low dose and/or contrast enhanced computed tomography ([18F]FDG-PET/CT) scan reveals high sensitivity for the diagnosis of vascular graft and endograft infection (VGEI), but lower specificity. Reporting [18F]FDG-PET/CT scans of suspected VGEI is challenging, reader dependent, and reporting standards are lacking. The aim of this study was to evaluate variability of [18F]FDG-PET/low dose CT (LDCT) reporting of suspected VGEI using a proposed standard reporting format.

METHODS

A retrospective cohort study was conducted including all patients with a suspected VGEI (according to the MAGIC criteria) without need for urgent surgical treatment who underwent an additional [18F]FDG-PET/LDCT scan between 2006 and 2022 at a tertiary referral centre. All [18F]FDG-PET/LDCT reports were scored following pre-selected criteria that were formulated based on literature and experts in the field. The aim was to investigate the completeness of [18F]FDG-PET/LDCT reports for diagnosing VGEI (proven according to the MAGIC criteria) and to evaluate if incompleteness of reports influenced the diagnostic accuracy.

RESULTS

Hundred-fifty-two patients were included. Median diagnostic interval from the index vascular surgical procedure until [18F]FDG-PET/LDCT scan was 35.5 (7.3-73.3) months. Grafts were in 65.1% located centrally and 34.9% peripherally. Based on the pre-selected reporting criteria, 45.7% of the reports included all items. The least frequently assessed criterion was FDG-uptake pattern (40.6%). Overall, [18F]FDG-PET/LDCT showed a sensitivity of 91%, a specificity of 72%, and an accuracy of 88% when compared to the gold standard (diagnosed VGEI). Lower sensitivity and specificity in reports including ≤ 8 criteria compared to completely evaluated reports were found (83% and 50% vs. 92% and 77%, respectively).

CONCLUSION

Less than half of the [18F]FDG-PET/LDCT reports of suspected VGEI met all pre-selected criteria. Incompleteness of reports led to lower sensitivity and specificity. Implementing a recommendation with specific criteria for VGEI reporting is needed in the VGEI-guideline update. This study provides a first recommendation for a concise and complete [18F]FDG-PET/LDCT report in patients with suspected VGEI.

Prevalence and clinical significance of incidental findings on CT attenuation correction for myocardial perfusion imaging

BACKGROUND

The appropriate clinical approach to incidentally detected lesions (IDLs) on CT attenuation correction (CTAC) images in myocardial perfusion imaging (MPI) remains uncertain. We sought to establish their prevalence and clinical significance in a large cohort and compared to previous studies to help provide further clarity and guide future clinical practice.

METHODS AND RESULTS

A total of 3758 MPI studies were reviewed retrospectively. IDLs of potential clinical significance-not known before MPI - were reported in 245 (6.5%) of these cases. Following appropriate further investigation/follow-up, these were of proven clinical significance in 30 (12.2%) cases with 14 patients (5.7%) harboring previously undiagnosed or progressive malignancies. The positive predictive value (PPV) for clinically significant incidental findings on CTAC images was 17.2% and the PPV value for incidental malignant findings was 8.0%.

CONCLUSION

Although incidental findings on CTAC images in MPI are common and often clearly insignificant at time of MPI reporting, many are clinically significant with a relatively high positive predictive value. This is especially so for malignancies. Our findings, therefore, in combination with previous studies as described here support routine reporting and appropriate further investigation of incidental CTAC findings in MPI.

Common physiologic and proteomic biomarkers in pulmonary and coronary artery disease

Objective

Chronic obstructive pulmonary disease (COPD) and coronary artery disease (CAD) are leading causes of global morbidity and mortality. There is a well-known comorbidity between COPD and CAD, which is only partly explained by smoking and other known common risk factors. In order to better understand the relationship between COPD and CAD, we analyzed myocardial perfusion, pulmonary function and novel cardiovascular biomarkers in patients with symptoms suggesting myocardial ischemia.

Methods

A total of 396 subjects from the Swedish Biomarkers and Genetics CardioPulmonary Physiology Study (BiG CaPPS) were included, all of whom had been referred to myocardial perfusion imaging due to suspected myocardial ischemia. Subjects performed myocardial perfusion imaging (MPI), pulmonary function tests (PFT) and analysis of 92 proteomic biomarkers, previously associated with cardiovascular disease. Linear regression was used to study the relationship between MPI and PFT results and proteomic biomarkers.

Results

Subjects with CAD (n = 159) had lower diffusing capacity (D_LCO) than patients without CAD (6.64 versus 7.17 mmol/(min*kPa*l); p = 0.004) in models adjusted for common covariates such as smoking, but also diabetes and brain natriuretic peptide (BNP). The association remained significant after additional adjustment for forced expiratory volume in one second (FEV₁) (p = 0.009). Subjects with CAD, compared with subjects without CAD, had higher total airway resistance (0.37 vs 0.36 kPa/(l/s); p = 0.036). Among 92 protein biomarkers, nine were associated with a combined diagnosis of CAD and airflow obstruction: VSIG2, KIM1, FGF-23, REN, XCL1, GIF, ADM, TRAIL-R2 and PRSS8.

Significance

Diffusing capacity for carbon monoxide is decreased in patients with CAD, independently of decreased FEV₁, diabetes, and elevated BNP. Several cardiovascular biomarkers are associated with co-existent CAD and airflow obstruction, but none with airflow obstruction only. The current findings indicate that the interaction between CAD and lung function is complex, including mechanisms beyond the known association between CAD and reduced ventilation.

Machine Learning Algorithms to Distinguish Myocardial Perfusion SPECT Polar Maps

Myocardial perfusion imaging (MPI) plays an important role in patients with suspected and documented coronary artery disease (CAD). Machine Learning (ML) algorithms have been developed for many medical applications with excellent performance. This study used ML algorithms to discern normal and abnormal gated Single Photon Emission Computed Tomography (SPECT) images. We analyzed one thousand and seven polar maps from a database of patients referred to a university hospital for clinically indicated MPI between January 2016 and December 2018. These studies were reported and evaluated by two different expert readers. The image features were extracted from a specific type of polar map segmentation based on horizontal and vertical slices. A senior expert reading was the comparator (gold standard). We used cross-validation to divide the dataset into training and testing subsets, using data augmentation in the training set, and evaluated 04 ML models. All models had accuracy >90% and area under the receiver operating characteristics curve (AUC) >0.80 except for Adaptive Boosting (AUC = 0.77), while all precision and sensitivity obtained were >96 and 92%, respectively. Random Forest had the best performance (AUC: 0.853; accuracy: 0,938; precision: 0.968; sensitivity: 0.963). ML algorithms performed very well in image classification. These models were capable of distinguishing polar maps remarkably into normal and abnormal.

Cost-effectiveness analysis of stand-alone or combined non-invasive imaging tests for the diagnosis of stable coronary artery disease: results from the EVINCI study

AIM

This study aimed at evaluating the cost-effectiveness of different non-invasive imaging-guided strategies for the diagnosis of obstructive coronary artery disease (CAD) in a European population of patients from the Evaluation of Integrated Cardiac Imaging in Ischemic Heart Disease (EVINCI) study.

METHODS AND RESULTS

Cost-effectiveness analysis was performed in 350 patients (209 males, mean age 59 ± 9 years) with symptoms of suspected stable CAD undergoing computed tomography coronary angiography (CTCA) and at least one cardiac imaging stress-test prior to invasive coronary angiography (ICA) and in whom imaging exams were analysed at dedicated core laboratories. Stand-alone stress-tests or combined non-invasive strategies, when the first exam was uncertain, were compared. The diagnostic end-point was obstructive CAD defined as > 50% stenosis at quantitative ICA in the left main or at least one major coronary vessel. Effectiveness was defined as the percentage of correct diagnosis (cd) and costs were calculated using country-specific reimbursements. Incremental cost-effectiveness ratios (ICERs) were obtained using per-patient data and considering "no-imaging" as reference. The overall prevalence of obstructive CAD was 28%. Strategies combining CTCA followed by stress ECHO, SPECT, PET, or stress CMR followed by CTCA, were all cost-effective. ICERs values indicated cost saving from - 969€/cd for CMR-CTCA to - 1490€/cd for CTCA-PET, - 3092€/cd for CTCA-SPECT and - 3776€/cd for CTCA-ECHO. Similarly when considering early revascularization as effectiveness measure.

CONCLUSION

In patients with suspected stable CAD and low prevalence of disease, combined non-invasive strategies with CTCA and stress-imaging are cost-effective as gatekeepers to ICA and to select candidates for early revascularization.

Prevalence and variability in reporting of clinically actionable incidental findings on attenuation-correction CT scans in a veteran population

BACKGROUND

Myocardial perfusion imaging (MPI) often employs attenuation-correction computed tomography (CTAC) to reduce attenuation artifacts and improve specificity. While there is no specific guideline on how they should be reported, incidental noncardiac findings identified on these scans may be clinically significant. The prevalence of these findings in veterans is not currently known. In addition, variability in reporting these findings may depend on the interpreting physician's specialty.

METHODS

To guide future decision-making, CTACs in veterans referred for MPI were prospectively evaluated in a quality-control project for a set of prespecified actionable incidental findings by cardiologists and a radiologist.

RESULTS

On the 771 scans performed over eight months, 285 incidental noncardiac findings were identified by the interpreting cardiologists and 378 were identified by the interpreting radiologist. Pulmonary nodules were the most common occurring in 20% of studies read by the radiologist. Interreader agreements between cardiologists and the radiologist were poor for pulmonary nodules ≥ 10 mm and hiatal hernias; fair for pulmonary nodules < 10 mm, extracardiac masses, and aortic aneurysms; and moderate for pleural plaques.

CONCLUSION

Incidental noncardiac findings on CTACs are common in our veteran population. Overall interobserver agreement in identifying these findings between cardiologists and radiologists is fair. Specific guidelines are needed on how CTACs should be read and reported.

The need for standardization of nuclear cardiology reporting and data system (NCAD-RADS): Learning from coronary artery disease (CAD), breast imaging (BI), liver imaging (LI), and prostate imaging (PI) RADS

Newer structured reporting manners, the reporting and data system (RADS), have made vast steps in improving standardized and structured reporting, allowing better communication between radiologists and referring providers. This has been implemented in several fields: breast (BI-RADS), lung (Lung-RADS), liver (LI-RADS), thyroid (TI-RADS), prostate (PI-RADS), and in cardiovascular radiology (CAD-RADS). The field of nuclear cardiology began its efforts of standardization years ago; however, a widespread standardized reporting structure has not yet been adopted. Such an approach in nuclear cardiology, the nuclear cardiology reporting and data system (NCAD-RADS), will assist radiologists and treating clinicians in conveying and understanding reports and determining the appropriate next steps in management. By linking explicit findings to defined recommendations, patients will receive more consistent and appropriate care.

High prevalence of undiagnosed COPD among patients evaluated for suspected myocardial ischaemia

Objective

Chronic obstructive pulmonary disease (COPD) and coronary artery disease (CAD) are leading causes of global morbidity and mortality. Despite the well-known comorbidity between COPD and CAD, the presence of COPD may be overlooked in patients undergoing coronary evaluation. We aimed to assess the prevalence of undiagnosed COPD among outpatients evaluated due to suspected myocardial ischemia.

Methods

Among 500 outpatients who were referred to myocardial perfusion imaging due to suspected stable myocardial ischaemia, 433 patients performed spirometry. Of these, a total of 400 subjects (age 66 years; 45% women) had no previous COPD diagnosis and were included in the current study. We compared the prevalence of previously undiagnosed COPD according to spirometry criteria from The Global Initiative for Chronic Obstructive Lung Disease (GOLD) or lower limit of normal (LLN) and reversible myocardial ischaemia according to symptoms and clinical factors.

Results

A total of 134 (GOLD criteria; 33.5 %) or 46 patients (LLN criteria; 11.5%) had previously undiagnosed COPD, whereas 55 patients (13.8 %) had reversible myocardial ischaemia. The presenting symptoms (chest discomfort, dyspnoea) did not differ between COPD, myocardial ischaemia and normal findings. Except for smoking, no clinical factors were consistently associated with previously undiagnosed COPD.

Conclusions

Among middle-aged outpatients evaluated due to suspected myocardial ischaemia, previously undiagnosed COPD is at least as common as reversible myocardial ischaemia and the presenting symptoms do not differentiate between these entities. Patients going through a coronary ischaemia evaluation should be additionally tested for COPD, especially if there is a positive history of smoking.

Hybrid cardiac imaging using PET/MRI: a joint position statement by the European Society of Cardiovascular Radiology (ESCR) and the European Association of Nuclear Medicine (EANM)

Positron emission tomography (PET) and magnetic resonance imaging (MRI) have both been used for decades in cardiovascular imaging. Since 2010, hybrid PET/MRI using sequential and integrated scanner platforms has been available, with hybrid cardiac PET/MR imaging protocols increasingly incorporated into clinical workflows. Given the range of complementary information provided by each method, the use of hybrid PET/MRI may be justified and beneficial in particular clinical settings for the evaluation of different disease entities. In the present joint position statement, we critically review the role and value of integrated PET/MRI in cardiovascular imaging, provide a technical overview of cardiac PET/MRI and practical advice related to the cardiac PET/MRI workflow, identify cardiovascular applications that can potentially benefit from hybrid PET/MRI, and describe the needs for future development and research. In order to encourage its wide dissemination, this article is freely accessible on the European Radiology and European Journal of Hybrid Imaging web sites.

KEY POINTS

• Studies and case-reports indicate that PET/MRI is a feasible and robust technology. • Promising fields of application include a variety of cardiac conditions. • Larger studies are required to demonstrate its incremental and cost-effective value. • The translation of novel radiopharmaceuticals and MR-sequences will provide exciting new opportunities.

Nuclear cardiology practice in Spain

BACKGROUND

In Spain, nuclear cardiology (NC) procedures represent the second most frequently performed studies in nuclear medicine (NM) centers.

METHODS

The NC Working Group of the Spanish Society of Nuclear Medicine and Molecular Imaging invited NM departments across the country to answer an online questionnaire regarding 2014 activity.

RESULTS

Data on 40,161 patients from 42 centers were collected. The responding public centers served 39% of Spain´s population. The estimated NC activity for public hospitals was 2 studies/1,000 population/year. Of all the NC procedures, 69% were SPECT myocardial perfusion imaging (MPI), 17% equilibrium ventriculography, 12% 18F-FDG PET, 1.3% first pass ventriculography, and <1% innervation and amyloidosis imaging, respectively. The most frequent NC study was a 99mTc tracer, exercise, 2-day MPI ECG-gated SPECT ordered by a cardiologist for diagnosis in an outpatient with 21 days of mean waiting time, the stress phase being supervised by both a cardiologist and a NM physician, with a NM physician writing a complete report.

CONCLUSIONS

A major challenge for NC in Spain is the gradual adoption of high-sensitivity, low-dose-dedicated cardiac SPECT cameras and the broadening of cardiac PET utilization with more cameras, and the availability of MPI tracers alongside the viability/inflammation setup.

Prognostic Value of Combined Clinical and Myocardial Perfusion Imaging Data Using Machine Learning

OBJECTIVES

This study evaluated the added predictive value of combining clinical information and myocardial perfusion single-photon emission computed tomography (SPECT) imaging (MPI) data using machine learning (ML) to predict major adverse cardiac events (MACE).

BACKGROUND

Traditionally, prognostication by MPI has relied on visual or quantitative analysis of images without objective consideration of the clinical data. ML permits a large number of variables to be considered in combination and at a level of complexity beyond the human clinical reader.

METHODS

A total of 2,619 consecutive patients (48% men; 62 ± 13 years of age) who underwent exercise (38%) or pharmacological stress (62%) with high-speed SPECT MPI were monitored for MACE. Twenty-eight clinical variables, 17 stress test variables, and 25 imaging variables (including total perfusion deficit [TPD]) were recorded. Areas under the receiver-operating characteristic curve (AUC) for MACE prediction were compared among: 1) ML with all available data (ML-combined); 2) ML with only imaging data (ML-imaging); 3) 5-point scale visual diagnosis (physician [MD] diagnosis); and 4) automated quantitative imaging analysis (stress TPD and ischemic TPD). ML involved automated variable selection by information gain ranking, model building with a boosted ensemble algorithm, and 10-fold stratified cross validation.

RESULTS

During follow-up (3.2 ± 0.6 years), 239 patients (9.1%) had MACE. MACE prediction was significantly higher for ML-combined than ML-imaging (AUC: 0.81 vs. 0.78; p < 0.01). ML-combined also had higher predictive accuracy compared with MD diagnosis, automated stress TPD, and automated ischemic TPD (AUC: 0.81 vs. 0.65 vs. 0.73 vs. 0.71, respectively; p < 0.01 for all). Risk reclassification for ML-combined compared with visual MD diagnosis was 26% (p < 0.001).

CONCLUSIONS

ML combined with both clinical and imaging data variables was found to have high predictive accuracy for 3-year risk of MACE and was superior to existing visual or automated perfusion assessments. ML could allow integration of clinical and imaging data for personalized MACE risk computations in patients undergoing SPECT MPI.

Common genetic polymorphisms of adenosine A2A receptor do not influence response to regadenoson

AIM

Hemodynamic response to regadenoson varies greatly, and underlying mechanisms for variability are poorly understood. We hypothesized that five common variants of adenosine A2A receptor (ADORA2A) are associated with altered response to regadenoson.

METHODS

Consecutive subjects (n = 357) undergoing resting regadenoson nuclear stress imaging were enrolled. Genotyping was performed using Taqman-based assays for rs5751862, rs2298383, rs3761422, rs2267076 and rs5751876.

RESULTS

There was no significant difference in heart rate or blood pressure between different genotypes following regadenoson administration. There was also no significant difference in myocardial ischemia detected by nuclear perfusion imaging as defined by summed difference score, or in self-reported side effects among the genotypes tested.

CONCLUSION

The common A2A variants studied are not associated with variability in hemodynamic response to regadenoson or variability in detection of ischemia with nuclear perfusion stress imaging.

Trials of Quality Improvement in Imaging

Cardiovascular imaging plays a central role in the diagnosis and treatment of cardiovascular disease. Recently, increased emphasis has been placed on quality in cardiovascular imaging, and it is becoming a central priority for various stakeholders, including patients, physicians, and payers. The changing health care landscape and associated challenges imposed on cardiac imagers, including reductions in reimbursement and growing need for pre-authorization, have also helped bring quality metrics to the forefront. Continuous quality improvement initiatives provide the framework for the team of physicians, technical staff members, administrators, and other health care professionals to deliver high-quality care. Efforts to improve quality in cardiac imaging have started to form the foundation for numerous research studies in this arena, and although few in number, randomized control trials have begun to emerge. This review highlights quality improvement studies focusing on appropriate use education, reporting, and radiation dose reduction in cardiovascular imaging.