IMAGE-HF Project I-A: Cardiac Imaging in Ischemic Heart Failure (AIMI-HF) (AIMI-HF)

Alternative Imaging Modalities in Ischemic Heart Failure (AIMI-HF) Project I-A of Imaging Modalities to Assist With Guiding Therapy and the Evaluation of Patients With Heart Failure (IMAGE-HF)

Canadian Institutes of Health Research (CIHR), The Finnish Funding Agency for Technology and Innovation (TEKES)

Medical imaging is one of the fastest growing sectors in health care and increases in utilization underscore the need to ensure imaging technology is developed and used effectively. Evaluation of the clinical and economic impact of such imaging lags behind the technology development. Heart failure (HF) represents the final common pathway for most forms of heart disease and morbidity and mortality remain high. There is a need to identify imaging approaches that have a positive impact on therapy decisions, patient outcomes and costs. As well as standard methods to evaluate new and emerging techniques to better test their potential in a clinical management setting. PRIMARY OBJECTIVES: to compare the effect of HF imaging strategies on the composite clinical endpoint of cardiac death, MI, resuscitated cardiac arrest and cardiac re-hospitalization (WHF, ACS, arrhythmia). Patients with an ischemic heart disease (IHD) etiology will follow HF imaging strategy algorithms according to the question(s) asked by the physicians (is there ischemia and/or viability), in agreement with their local practices for standard and alternative imaging. SECONDARY OBJECTIVES: To evaluate the effect of imaging modalities within and between the imaging subgroups (advanced (CMR and PET), PET, MRI and standard (SPECT)) on the primary and secondary outcomes in patients being evaluated either for viability and/or ischemia. To evaluate the impact of adherence to recommendations between modalities on outcomes in patients being evaluated for either viability or ischemia. To compare the effect of HF imaging strategies on: The incidence of revascularization procedures (PCI, CABG, none) and the interaction of the imaging strategy and types of revascularization on outcomes LV remodeling: LV volumes, LVEF, HF symptoms, NYHA class QOL (MLHFQ, the EQ5D) The evolution of serum prognostic markers in HF (e.g. BNP, RDW, hs-cTnT, hs-CRP, ST2) Health economics: Costs estimated through regression analysis and cost effectiveness assessed through decision modeling. The safety of imaging tests measured by cumulative radiation, adverse reactions to imaging contrast agents and stress testing agents will also be determined. The evolution of renal function (eGFR) and LV remodeling-associated biomarkers (e.g. PIIINP, OPN). Event rates of each component of the composite endpoint as well as the combined endpoint of CV death and HF hospitalization All-cause mortality

Among patients with coronary artery disease and HF, mortality rates range from 10-60% at 1 year. Many trials have demonstrated benefit of revascularization in patients with ischemic heart disease (IHD) and LV dysfunction. Some criteria, such as severe angina or left main coronary artery stenosis may indicate the need for surgical therapy for HF patients; however, a large number of patients fall into a gray zone without clear evidence for benefit from surgical intervention. The need remains for approaches that can help better define and select the HF patients most likely to benefit from revascularization; which could be either surgical or percutaneous intervention. Increasingly over the past three decades, information describing cardiac structure, perfusion, hemodynamics, and metabolism obtained from noninvasive cardiac imaging studies has been used to guide management decisions for patients with HF. AIMI-HF is part of a large international team grant IMAGE-HF (Imaging Modalities to Assist with Guiding therapy and the Evaluation of patients with Heart Failure) involving 3 parallel trials addressing the role of imaging in HF patients according to HF etiology. Primary Hypothesis of AIMI-HF: In patients with HF due to IHD with LVEF less than or equal to 45%, a management algorithm that applies alternative advanced imaging strategies (PET or CMR) achieves a better clinical outcome measured as the composite clinical endpoint (CCE) of cardiac death, MI, resuscitated cardiac arrest and cardiac re-hospitalization (WHF, ACS, arrhythmia) than an approach with "standard care". Secondary Hypotheses of AIMI-HF: i) Compared to standard care, in patients with HF due to IHD with LVEF ≤ 45%, a management algorithm that applies alternative advanced imaging modalities (PET or CMR) achieves: a) more efficient use of revascularization procedures with similar complication rates than standard care imaging strategies b) better LV remodeling (including favorable evolution of serum markers associated with LV remodeling e.g. PIIINP, OPN) c) better HF and angina symptom reduction, d) better QoL, measured using MLHFQ and EQ5D, e) more favorable evolution of selected serum markers of prognosis in HF (e.g. BNP, RDW, hs-cTnT, hs-CRP), f) is economically attractive in patients with HF due to IHD with LVEF<45%, g) reduced event rates of each components of composite endpoint; h) all-cause mortality. ii) In patients with HF due to IHD with LVEF ≤ 45%, a HF management algorithm that applies PET or one that applies MRI, achieves a better primary composite clinical endpoint (CCE) and secondary outcomes compared to one that applies standard of care in patients assessed for ischemia and/or in patients assessed for viability. iii) In patients with HF due to IHD with LVEF ≤ 45%, a HF management algorithm that applies PET achieves a better primary composite clinical endpoint (CCE) and secondary outcomes compared to one that applies CMR in patients assessed for ischemia and/or in patients assessed for viability. iii) Renal function impairment is a known independent predictor of cardiovascular events in HF. Renal function may influence revascularization decisions and its evolution could be modified by revascularization procedures. Study design AIMI-HF is the IMAGE-HF Project 1-A trial; it is a prospective comparative effectiveness study to compare the effect of HF imaging strategies in patients with HF due to IHD. Eligible patients will have LV systolic dysfunction due to IHD where evaluation of ischemia or viability is relevant. Patients will be prospectively randomized to standard (SPECT) versus advanced (PET or CMR) imaging. Patients who meet inclusion criteria but cannot be randomized due to clinical management decisions, yet undergo standard or advanced imaging (SPECT, PET/CT or CMR), will be entered into a registry. Based on site screening logs, patients who could not be randomized, who met all other inclusion criteria and underwent standard or advanced imaging, will be retrospectively enrolled, from the date of original HREB approval, into the study as registry participants. Registry recruitment will be monitored to ensure as best as possible a balanced recruitment for each modality registry.

medical imaging, heart failure, morbidity and mortality, PET/CT,CMR,SPECT, echo, coronary angiography, knowledge translation, cost effectiveness, quality of life, prospective comparative effectiveness clinical trial

Patients will undergo cardiac imaging as evaluation of heart failure using 1 of the following alternate/advanced imaging modalities: Positron Emission Tomography (PET/CT), Cardiac Magnetic Resonance (CMR)

Patients will undergo standard cardiac imaging procedures for evaluation of heart failure such as single photon emission computed tomography (SPECT).

Primary analysis, the time-to-event of the composite clinical endpoint of cardiac death, MI, arrest and cardiac re-hospitalization (WHF, ACS, arrhythmia) will be compared between advanced (PET or CMR) vs standard care (SPECT). A competing risk analysis will be performed using non-cardiac death. Cumulative incidence function will be used in estimating the probability of the composite endpoints in each of advanced and standard groups. The sub-distribution hazard model (Fine and Gray) will be used to compare the cumulative incidence curves. The hazard ratio and associated 95 percent confidence interval will be calculated. To adjust for possible effects of confounding variables on survival between advanced and standard, the propensity scores generated on baseline patient factors (e.g. in/outpatient, NYHA class, HF, diabetes, atrial fibrillation, renal function, obesity), site factor and status of randomized versus registry will be also included in the competing risk multivariable model.

The time-to-event of the composite clinical endpoint of cardiac death, MI, arrest and cardiac re-hospitalization (WHF, ACS, arrhythmia) will be compared between advanced (PET or CMR) vs standard care (SPECT). A competing risk analysis will be performed using non-cardiac death. Cumulative incidence function will be used in estimating the probability of the composite endpoints in each of advanced and standard groups. The sub-distribution hazard model (Fine and Gray) will be used to compare the cumulative incidence curves. The hazard ratio and associated 95 percent confidence interval will be calculated. To adjust for possible effects of confounding variables on survival between advanced and standard, the propensity scores generated on baseline patient factors (e.g. in/outpatient, NYHA class, HF, diabetes, atrial fibrillation, renal function, obesity), site factor and status of randomized versus registry will be also included in the competing risk multivariable model.

The time-to-event of the composite clinical endpoint of cardiac death, MI, arrest and cardiac re-hospitalization (WHF, ACS, arrhythmia) will be compared between advanced (PET or CMR) vs standard care (SPECT). A competing risk analysis will be performed using non-cardiac death. Cumulative incidence function will be used in estimating the probability of the composite endpoints in each of advanced and standard groups. The sub-distribution hazard model (Fine and Gray) will be used to compare the cumulative incidence curves. The hazard ratio and associated 95 percent confidence interval will be calculated. To adjust for possible effects of confounding variables on survival between advanced and standard, the propensity scores generated on baseline patient factors (e.g. in/outpatient, NYHA class, HF, diabetes, atrial fibrillation, renal function, obesity), site factor and status of randomized versus registry will be also included in the competing risk multivariable model.

The time-to-event of the composite clinical endpoint of cardiac death, MI, arrest and cardiac re-hospitalization (WHF, ACS, arrhythmia) will be compared between PET and MRI. A competing risk analysis will be performed using non-cardiac death. Cumulative incidence function will be used in estimating the probability of the composite endpoints in each of advanced and standard groups. The sub-distribution hazard model (Fine and Gray) will be used to compare the cumulative incidence curves. The hazard ratio and 95% confidence interval will be calculated. To adjust for possible effects of confounding variables on survival between advanced and standard, the propensity scores generated on baseline patient factors (e.g. in/outpatient, NYHA class, HF, diabetes, atrial fibrillation, renal function, obesity), site factor and status of randomized versus registry will be also included in the competing risk multivariable model. All will be considered separately for viability and ischemia imaging.

Imaging modalities: Comparing PET and MRI vs SPECT modalities and for the components of the composite

For the secondary analysis, comparing the PET and MRI vs SPECT modalities, potential confounding variables of the relationship between the imaging technologies and the primary endpoint will be assessed. In particular, propensity scores based on patient factors (e.g. in/outpatient, NYHA class, HF duration, diabetes, atrial fibrillation, renal function) and site factors (e.g. time-to-imaging, time-to-therapy) will be used in the analysis if necessary to adjust for potential differences between PET and MRI vs SPECT. A Cox proportional hazard models will be used to assess the occurrence of the endpoints between the imaging technologies (model will include a group indicator variable) adjusting for any pertinent baseline differences identified. The proportional hazards assumption underlying the Cox model will be assessed. Analyses will be considered separately for viability and ischemia imaging.

For the secondary analysis, comparing the PET vs SPECT modalities, potential confounding variables of the relationship between the imaging technologies and the primary endpoint will be assessed. In particular, propensity scores based on patient factors (e.g. in/outpatient, NYHA class, HF duration, diabetes, atrial fibrillation, renal function) and site factors (e.g. time-to-imaging, time-to-therapy) will be used in the analysis if necessary to adjust for potential differences between PET vs SPECT. A Cox proportional hazard models will be used to assess the occurrence of the endpoints between the imaging technologies (model will include a group indicator variable) adjusting for any pertinent baseline differences identified. The proportional hazards assumption underlying the Cox model will be assessed. Analyses will be considered separately for viability and ischemia imaging.

For the secondary analysis, comparing the MRI vs SPECT modalities, potential confounding variables of the relationship between the imaging technologies and the primary endpoint will be assessed. In particular, propensity scores based on patient factors (e.g. in/outpatient, NYHA class, HF duration, diabetes, atrial fibrillation, renal function) and site factors (e.g. time-to-imaging, time-to-therapy) will be used in the analysis if necessary to adjust for potential differences between MRI vs SPECT. A Cox proportional hazard models will be used to assess the occurrence of the endpoints between the imaging technologies (model will include a group indicator variable) adjusting for any pertinent baseline differences identified. The proportional hazards assumption underlying the Cox model will be assessed. Analyses will be considered separately for viability and ischemia imaging.

For the secondary analysis, comparing the PET vs CMR modalities, potential confounding variables of the relationship between the imaging technologies and the primary endpoint will be assessed. In particular, propensity scores based on patient factors (e.g. in/outpatient, NYHA class, HF duration, diabetes, atrial fibrillation, renal function) and site factors (e.g. time-to-imaging, time-to-therapy) will be used in the analysis if necessary to adjust for potential differences between PET and CMR. A Cox proportional hazard models will be used to assess the occurrence of the endpoints between the imaging technologies (model will include a group indicator variable) adjusting for any pertinent baseline differences identified. The proportional hazards assumption underlying the Cox model will be assessed. The secondary outcomes will be analyzed in a similar fashion. Analyses will be considered separately for viability and ischemia imaging.

A i) Revascularization rates (PCI &CABG) chi-square tests will be used to compare the advanced and standard imaging technologies; logistic regression analysis will be used for adjusting any pertinent baseline differences identified. Analyses will be considered separately for viability and ischemia imaging.

A ii) HF symptoms (NYHA class) chi-square tests will be used to compare the advanced and standard imaging technologies; logistic regression analysis will be used for adjusting any pertinent baseline differences identified. Analyses will be considered separately for viability and ischemia imaging.

A iii) Event rates of each component of the composite endpoint, combination of CV death and HF hospitalization and all cause mortality chi-square tests will be used to compare the advanced and standard imaging technologies; logistic regression analysis will be used for adjusting any pertinent baseline differences identified. Analyses will be considered separately for viability and ischemia imaging.

B i) Left ventricular ejection fraction change over time; an analysis of variance will be used to compare trends over time between the advanced and standard technologies. Analysis of covariance will be used for adjusting any pertinent baseline differences identified. Analyses will be considered separately for viability and ischemia imaging.

B ii)Left ventricular volumes change over time: analysis of variance will be used to compare trends over time between the advanced and standard technologies. Analysis of covariance will be used for adjusting any pertinent baseline differences identified. Analyses will be considered separately for viability and ischemia imaging.

B iii) Cardiac biomarkers change over time analysis of variance will be used to compare trends over time between the advanced and standard technologies. Analysis of covariance will be used for adjusting any pertinent baseline differences identified. Analyses will be considered separately for viability and ischemia imaging.

B iv) Quality of life measures (MLHFQ and EQ5D) change over time analysis of variance will be used to compare trends over time between the advanced and standard technologies. Analysis of covariance will be used for adjusting any pertinent baseline differences identified. Analyses will be considered separately for viability and ischemia imaging.

A cost-effectiveness analysis of advanced versus standard modality groups will be conducted. Analysis will take the form of a cost utility analysis with cost effectiveness assessed in terms of the incremental cost per quality life year. Analysis will incorporate data on resource use and patients utility values for the period from initiation of treatment to study termination. Resource use will be assessed through review of patient charts and patient utility values will be derived using the EQ5D and MLHF. A decision model will be created to estimate long term costs and quality adjusted life years (QALYs) for all comparators. Uncertainty within the analysis will be assessed through Monte Carlo and other simulation techniques.

Safety will be evaluated by documenting all adverse events. Adverse event listings, event classification (seriousness, modality relationship, resolution etc.), descriptive statistics (frequency distributions, numerical descriptors) and possibly 95%CIs and basic tests will be calculated. The as-treated population will be the main analysis population for this safety evaluation.

Inclusion criteria: Age >18 years Known or highly suspected coronary artery disease (CAD) documented by coronary angiography or by history of previous MI or evidence of moderate ischemia or scar based on prior imaging LV dysfunction most likely attributable to ischemic heart disease with EF <45% measured by any acceptable means (echo, nuclear RNA, PET or SPECT perfusion, Angiography, Cardiac MR) within the previous 6 months AND NYHA class II-IV symptoms within the past 12 months. OR LV dysfunction most likely attributable to ischemic heart disease with EF ≤30% measured by any acceptable means (echo, nuclear RNA, PET or SPECT perfusion, Angiography, Cardiac MR) within the previous 6 months AND NYHA class I within the past 12 months Exclusion criteria: Severe medical conditions that significantly affect the patient's outcome (eg. severe COPD, active metastatic malignancy) and would preclude revascularization. < 4 weeks post ST segment elevation myocardial infarction (STEMI) Already identified as not suitable for revascularization; Emergency revascularization indicated Severe valvular heart disease requiring surgery Contraindications to CMR (eg metallic implant, claustrophobia, renal failure (GFR <30 ml/min/1.73m2),). However patients with permanent pacemakers or implanted defibrillators or GFR <30 ml/min/1.7m2, will be randomized only to standard imaging (SPECT) versus PET or entered into the registry if only 1 modality is available Pregnancy Potential for non compliance to tests involved in this protocol Incapacity to provide informed consent

Paterson DI, OMeara E, Chow BJ, Ukkonen H, Beanlands RS. Recent advances in cardiac imaging for patients with heart failure. Curr Opin Cardiol. 2011 Mar;26(2):132-43. doi: 10.1097/HCO.0b013e32834380e7.

O'Meara E, Mielniczuk LM, Wells GA, deKemp RA, Klein R, Coyle D, Mc Ardle B, Paterson I, White JA, Arnold M, Friedrich MG, Larose E, Dick A, Chow B, Dennie C, Haddad H, Ruddy T, Ukkonen H, Wisenberg G, Cantin B, Pibarot P, Freeman M, Turcotte E, Connelly K, Clarke J, Williams K, Racine N, Garrard L, Tardif JC, DaSilva J, Knuuti J, Beanlands R; IMAGE HF investigators. Alternative Imaging Modalities in Ischemic Heart Failure (AIMI-HF) IMAGE HF Project I-A: study protocol for a randomized controlled trial. Trials. 2013 Jul 16;14:218. doi: 10.1186/1745-6215-14-218.