AIMS:To determine the prevalence of asymmetric septal hypertrophy(ASH) across health and in diseases associated with left ventricular hypertrophy(LVH), including hypertrophic cardiomyopathy(HCM). METHODS AND RESULTS:We analysed two complementary datasets. First, a large UK Biobank healthy reference cohort(n = 4,020) was used to model demographic determinants of septal-to-lateral wall thickness ratio(SLR) and to provide the reference group for age-, sex-, and body-surface area-adjusted comparisons. Second, a multi-cohort clinical CMR dataset included 1,655 subjects comprising local healthy volunteers, athletes, patients with hypertension, aortic stenosis, Fabry disease, AL amyloidosis, ATTR amyloidosis, and HCM. LVH was defined by maximum wall thickness(MWT) ≥ 15 mm and asymmetry defined as SLR≥1.3. Left ventricular morphology was classified as normal, asymmetric remodelling(SLR≥1.3;MWT<15 mm), symmetric hypertrophy(SLR<1.3;MWT≥15 mm) or ASH(SLR≥1.3;MWT≥15 mm). ASH was highly prevalent in HCM(61%) but was also observed in ATTR amyloidosis(37%), AS(26%), and AL amyloidosis(23%). In the healthy reference cohort, a higher septal-to-lateral ratio was independently associated with older age, female sex, and larger BSA(p < 0.001). After adjustment for these demographic factors, only HCM retained a clinically meaningful excess in septal asymmetry(ΔSLR=+0.27;p < 0.001). In contrast, the apparent asymmetry in non-HCM cohorts was partly explained by demographic variation. After adjustment, only HCM showed a clinically meaningful excess in SLR, whereas other disease cohorts showed either no material difference or small negative differences relative to healthy controls. CONCLUSION:ASH is a common but non-specific finding in diseases associated with LVH. Septal asymmetry increases with age and body-size and is more pronounced in women. After adjusting for age, sex, and body-size, disproportionate septal asymmetry was most characteristic of HCM.

Aims:Serial imaging demands precision-particularly for cardiotoxicity screening where small changes gatekeep major decisions. Automated measurement using artificial intelligence (AI)-based techniques should reduce variability and increase confidence for detection of true change. We directly compared the precision of fully automated AI vs. expert manual analysis of left ventricular function by echocardiography. Methods and results:Consecutive cancer patients referred for cardiotoxicity monitoring underwent same-day repeat 2D echocardiography [n = 60, 83% female, mean left ventricular ejection fraction (LVEF) 57 ± 7%], with 3D acquisition where feasible (n = 45). All 2D images underwent blinded analysis by a fully automated analysis software and four experts. Quantitative 2D LVEF measurement was feasible in 96% scans by both methods. Mean absolute difference (MAD) between repeat scans was significantly lower for AI than experts for both 2D LVEF {3.6% [confidence interval (CI) 2.8-4.4] vs. 6.6% [CI 5.3-7.9], P = 0.011} and global longitudinal strain [1.5% (CI 1.1-1.9) vs. 2.5% (CI 2.0-3.0), P = 0.006]. In participants with 3DE datasets, 3D LVEF MAD was lower than manual 2D LVEF [3.6% (CI 2.8-4.6) vs. 6.4% (CI 5.0-8.0), P = 0.006] but comparable to AI-derived 2D LVEF [3.5% (CI 2.9-4.2), P = 0.4]. In a subset (n = 48) also with same-day cardiovascular magnetic resonance (CMR) studies, AI 2DE analysis demonstrated stronger agreement with CMR than expert 2DE analysis [LVEF MAD 5.0% (CI 4.1-5.9) vs. 7.8% (CI 6.6-9.0) P = 0.006]. Conclusion:In cancer patients at risk of cardiotoxicity, the precision of 2D echocardiographic AI analysis exceeds that of experts, matching that of 3D LVEF assessment. Trial Registration:NCT06817044. Lay summary:Some cancer treatments may weaken the heart. As such, at-risk patients have repeat heart scans (echocardiograms) over the course of their cancer treatment. Doctors monitor these scans over time and watch closely for any change; even a small decline in heart function can trigger a major decision, such as pausing life-saving cancer therapy. It is therefore vital that these measurements are as consistent or 'precise' as possible.The problem is that measurements taken by hand can vary widely, and 'precision' may be low, even when performed by skilled experts. This makes it hard to know whether a change in heart function across follow-up scans is real or not and whether any action is therefore needed. We tested whether artificial intelligence (AI) software could measure heart function more precisely than experts.Sixty cancer patients each had two echocardiographic heart scans in close succession on the same day. This approach purposefully reduces the impact of other factors (such as differences in the person or equipment performing the heart scan) that might otherwise mean results differ. We then compared how closely the repeat measurements of heart function matched when performed by AI vs. four echocardiography experts. The AI was more precise, giving closer results between the two scans, whilst the experts' results varied more.In short, AI can measure heart function more precisely than experts in patients with cancer. This could give doctors greater confidence that any change seen on a scan is genuine, helping them make safer, better-informed decisions.

Benjamin Dowsing describes the Whitehall studies, which established the inverse relationship between socioeconomic status and the risk of death from coronary heart disease, leading to the concept of social determinants of health.

International guidelines recommend cardiac resynchronization therapy (CRT) in heart failure (HF) patients with left ventricular ejection fraction (LVEF) <35% and prolonged QRS duration, despite optimal medical therapy (1); where CRT significantly improves symptoms and reduces morbidity and mortality (2-4). Heart failure is common in cancer patients due to shared oncological and cardiovascular risk factors and cardiotoxic cancer therapies. The safety and efficacy of CRT in this growing cohort of potentially eligible cancer patients with heart failure remains uncertain. To investigate the outcomes of cancer patients who underwent CRT at our local institution. Multicentre retrospective cohort study of cancer patients referred for CRT following CO-MDT review. Patient characteristics, including cancer and cardiac status, as well as procedural complications and longer-term outcomes (from CO-MDT referral to latest follow up) were extracted from electronic health records. Between January 2022 and December 2024, 11 patients were referred for CRT following CO-MDT review (total 417 individual cases reviewed). The patients were predominately older men, undergoing active cancer therapy (median age 76, 65% male, 73% current systemic cancer therapy, 82% solid tumours, 67% metastatic disease) (table 1). Mean QRS duration was 156ms (+/-30), and mean LVEF 29% (+/-11) prior to CRT. Indication for CRT was symptomatic severe HF in 91% (n=10) of patients. One referred patient had CRT despite moderate LV dysfunction, given concerns for decline in LVEF with reintroduction of breast cancer therapy. CRT implantation occurred in 55% (n=6) without complication, remainder were awaiting implantation (n=2) or no longer eligible due to later improvements in LVEF/HF symptoms (n=3). One patient underwent CRT with defibrillator, she was the youngest patient at age 55 and had LVEF of 18%. Following CRT implantation, t-mean biventricular pacing percentage was 94% (+/-6); there was a meaningful reduction in QRS duration (mean 38ms +/- 25, p=0.008) and increase in LVEF (mean LVEF pre-CRT 29%, mean LVEF post-CRT 42%, p=0.09) at a follow up of 12 months. One patient was hospitalised with heart failure (unrelated to CRT implantation) and all patients remained alive at 12 months follow up. Cancer patients underwent successful CRT following CO-MDT review, without procedural or long-term complications. CRT resulted in satisfactory biventricular pacing percentage, plus meaningful improvements in QRS duration and left ventricular function, and can help facilitate ongoing cancer therapies. Cancer patients should not be excluded from the potential benefits of CRT and CO-MDTs can aid in ensuring cancer patients with heart failure receive equitable, guideline directed care.

Long-term HER2-targeted therapies improve survival in metastatic HER2-positive breast cancer (BC) (1) but are associated with cancer therapy related cardiac dysfunction (CTRCD) (2); indefinite cardiac surveillance is therefore mandated (3). EMA guidance recommends 3 monthly imaging, although recent guidelines suggest clinicians consider increased surveillance intervals (3). Rationalising cardiac surveillance could improve patients’ quality of life and reduce costs, but doing so requires better understanding of CTRCD in this population. To investigate the incidence, severity and timing of CTRCD in metastatic HER2-positive BC patients receiving long-term HER2 targeted therapy. A retrospective multicentre cohort study of metastatic HER2-positive BC patients receiving HER2 targeted therapy between 2012-2024. Patients were identified from cancer therapy prescriptions at two large oncology centres. CTRCD was defined as per the European Society of Cardiology (ESC) Cardio-Oncology guidelines (3). Patients were stratified by Heart Failure Association and International Cardio-Oncology Society (HFA-ICOS) cardiotoxicity risk (4). 191 patients (median age 53 [interquartile range [IQR] 45-62], 99% female, 45% non-Caucasian) were identified. Median HER2 treatment duration was 38 months [IQR 19-57]), each with a median of 12 [IQR 8-18] echocardiograms (total n=2091) for CTRCD surveillance (Table 1). CTRCD occurred in 43% (n=82) at a median of 62 weeks (IQR 25 - 122) from treatment initiation; most commonly mild asymptomatic (50%, n=41) followed by moderate asymptomatic (41%, n=34), symptomatic (5%, n=4) and severe asymptomatic (4%, n=3). Symptomatic and moderate or severe asymptomatic CTRCD occurred significantly earlier than mild asymptomatic (median 41, 18 and 6 vs 87 weeks respectively, p<0.05). HER2 targeted therapy was interrupted in 33% of patients with CTRCD (n=27) for a median of 12 [4-16] weeks; 96% were re-challenged successfully with cardio-protective therapies. Moderate, high or very high-risk patients, by baseline HFA-ICOS risk, were significantly more likely to develop CTRCD than low risk (hazard ratio 3.1, 95% confidence interval 1.7-5.9; p = 0.028). In the largest-to-date multicentre analysis of cardiotoxicity surveillance in metastatic HER2-positive BC patients receiving long-term HER2-targeted therapies, CTRCD was common but generally mild, asymptomatic. With cardio-oncology support, most patients were able to continue HER2 targeted therapies. The HFA-ICOS cardiotoxicity risk score can identify those most at risk of CTRCD. Only half of all cases of CTRCD were symptomatic or moderate or greater asymptomatic, and 63% presented within 12 months. For patients receiving long-term HER2 targeted therapies in the metastatic setting, reducing the frequency of cardiac surveillance after the first 12 months is unlikely to significantly impact the sensitivity of detection of clinically significant CTRCD.Table 1.Patient demographics (n=191). Figure 1.A) Incidence B) HFA-ICOS Risk

Abstract Background Serial surveillance screening for cardiotoxicity demands measurement precision to detect dysfunction early and avoid inappropriate treatment interruptions. 3D LVEF and GLS imaging are therefore recommended, or CMR where image quality is suboptimal [1]. Automated (AI) analysis of CMR has demonstrated ‘superhuman’ precision [2], however the impact of AI on echocardiographic precision is unknown. Purpose To compare human versus AI analysis for LVEF and GLS using echocardiography in oncology patients at risk of cardiotoxicity. Methods Adult oncology patients underwent same day repeat echocardiography (GE Vivid9 machine) using recommended protocols (ethics 16/LO/1815). Manual analysis by a single blinded expert observer was compared to AI analysis (of 2D images) using two commercial AI packages (AI1, AI2) and a third AI package currently undergoing regulatory approval (AI3). A subset of patients also underwent paired same day CMR, analysed using commercial software (Circle CVI). Primary outcome measure was mean absolute difference (MAD) between repeat scans, and within subject co-efficient of variation (WSCoV), minimal detectable difference (MDD) and Bland-Altman limits of agreement were also analysed. Statistical analysis was performed in R, with n=10,000 bootstrap to estimate confidence intervals. MAD was compared with a Mann-Whitney U test. Results 61 cancer patients (median age 51, 84% female) underwent same day repeat echocardiography. Image quality was graded acceptable for LVEF analysis by humans in 92% cases for 2D and 74% of 3D images. AI analysis was feasible in 96% (AI1), 93% (AI2) and 100% (AI3) of adequate 2D studies. Median LVEF across the group was 58% (IQR 50 – 66%). MAD for 2D LVEF (n=56) was similar between humans and AI software packages AI1, AI2 and AI3 respectively (4.2% [3.5-49] vs 4.8% [3.7–5.9], 5.2% [4.2-6.4], 3.5% [2.7-4.2]), Figure 1 and Table 1. However for LVEDV and LVESV, AI3 had significantly lower MAD (6.8ml [5.5-8.1] vs 11.8ml [9.5-14.2] and 3.4ml [2.7-4.1] vs 6.5ml [5.3-7.7], p<0.001) compared with humans. MDD for EDV was 10.5ml [8.2-12.3] for AI3 vs 20ml [16.1-23.4] for human 2D LVEF (p<0.05). For GLS, MAD was similar between humans, AI2 and AI3 though significantly higher for AI1 (2.6% [2.2-3.0] vs 1.4% [1.1-1.7], p<0.001). For participants (48) with matched CMR paired data, MAD for CMR LVEF was significantly lower than human, AI1 and AI2 for LVEF, LVEDV and LVESV respectively [p<0.05], but not significantly different to AI3 for LVEF (3.9% [3.2-4.7] vs CMR 2.9% [2.3-3.4] or 3D 3.3% [2.7-3.9] p>0.05). Conclusion In oncology patients at risk of cardiotoxicity, newer fully-automated AI based echocardiography analysis improves measurement precision, with similar performance to 3D echocardiography and approaching CMR. Feasible even with challenging images, this should improve both confidence and efficiency for cardiotoxicity surveillance in cancer patients.

Introduction A quarter of breast cancers show human epidermal growth factor-2 (HER2) overexpression, where targeted therapy dramatically improves survival. However, cancer therapy-related cardiac dysfunction (CTRCD) occurs in up to 15% of patients. With the interruption of HER2 therapy, if necessary, and the initiation of heart failure therapy (HFT), HER2 CTRCD recovers in over 80% of cases. The need to continue HFT in ‘recovered’ HER2 CTRCD following completion of HER2 therapy is unclear and there are potential significant impacts on patient’s quality of life (QoL). The Randomised Controlled Trial for the Safety of Withdrawal of Pharmacological Treatment for Recovered HER2 Targeted Therapy Related Cardiac Dysfunction (HER-SAFE) aims to evaluate whether HFT can be safely withdrawn in non-high cardiovascular (CV) risk patients with ‘recovered’ HER2 CTRCD.Methods and analysis This is a multicentre, open-label randomised controlled trial investigating whether withdrawal of HFT is non-inferior to continuation in non-high CV risk, breast cancer survivors with recovered HER2 CTRCD after cancer treatment completion. The primary endpoint is the incidence of guideline-defined cardiac dysfunction or clinical heart failure. Secondary endpoints include changes in cardiac blood biomarkers, cardiovascular magnetic resonance (CMR)-derived strain and tissue mapping and heart failure symptom questionnaires. The study will recruit 90 participants who will undergo serial clinical assessment over 12 months with advanced cardiovascular imaging (CMR scans with automated analysis at baseline, 6 and 12 months), cardiac biomarker measurement (six time points over 12 months), plus complete heart failure QoL and medication disutility questionnaires. This is the first multicentre study to address this significant clinical issue.Ethics and dissemination This study was approved by the research ethics committee (London—London Bridge, 23/LO/0152). The results will be disseminated in peer-reviewed scientific journals.Trial registration number NCT05880160.

Introduction: The definition of hypertrophic cardiomyopathy (HCM), unaltered for 50 years, requires unexplained left ventricular hypertrophy with a maximum wall thickness (MWT) ≥15mm in probands. However, this doesn’t consider age, sex and body-size which is inadequate for a precision therapy era. Aim: To develop a personalised definition of inappropriate hypertrophy using cardiac MRI and evaluate potential care implications. Methods: Healthy reference cardiac MRIs from the Framingham Heart Study, UK Biobank, and multiple healthy volunteer studies were analysed by a validated AI algorithm. Generalized additive mixed models accounting for age, sex, and body surface area (BSA) established a personalized hypertrophy threshold for MWT (>95% prediction interval) and conditional Z-scores. We assessed the discordance in HCM diagnosis between a “≥15mm” and “personalized hypertrophy” threshold applied to the UK Biobank and clinical HCM cohorts. Results: In healthy subjects (n=5,255), 36% of MWT variation was explained by age, sex and BSA. In the UK Biobank (n=44,690), using ≥15mm, there is a substantial sex skew; 8% of males and 1% of females are classified as hypertrophic. With a personalized threshold, this reduces to 3% of males and 2% of females classified as hypertrophic. 17% of subjects have a predicted hypertrophy threshold of 15mm (with 46% predicted ≤ 14mm, 37% predicted ≥16mm). In clinical HCM cohorts (n=1,854) across 5 centres in 4 countries (UK, USA, Italy, Portugal), females had thinner hearts (17.7 vs 19.1mm; p<0.001) but more relative hypertrophy evidenced by greater deviation (Z-scores) from their predicted MWT (5.4 vs 5.1; p=0.05). Conclusion: We propose a new, personalised definition for hypertrophy that mitigates for significant age, sex and BSA confounding inherent in a 15mm cut point. We have identified potential for under/over diagnosis in a population cohort and suboptimal risk stratification in smaller, younger and/or female HCM patients.

Abstract Funding Acknowledgements Type of funding sources: None. Background Serial screening for cancer therapy related cardiac dysfunction (CTRCD) demands precise measurement of left ventricular ejection fraction (LVEF) and global longitudinal strain (GLS) to detect cardiotoxicity early and avoid inappropriate treatment breaks. Precision can be maximised by better image quality and more accurate analysis(1). Cardiovascular magnetic resonance (CMR) is gold standard for image acquisition(2,3), but the benefit of fully-automated AI-based analysis is unclear(4). Purpose To compare the precision (test-retest reproducibility) of AI-based analysis with human measurement for quantification of LVEF and GLS using echocardiography (TTE) and CMR. Methods Consented adult oncology patients underwent paired same day repeat scans using TTE and CMR (GE Vivid9 machine and Siemens 1.5T Aera) following EACVI protocols. Manual image analysis was performed by 2 blinded experts (ECHO-PAC and CVI42 software). TTE images were analysed by two FDA-approved fully-automated (unsupervised) AI packages (EchoAI1 and EchoAI2), and CMR images by one FDA-approved AI package (CMRAI1) and one validated fully-automated inline deep-learning algorithm (CMRAI2). Precision was calculated between repeat studies for each modality and analysis technique by the mean absolute difference (MAD), co-efficient of variation (CoV), minimal detectable difference (MDD) and Bland-Altman limits of agreement; compared using Levene’s test. Results 48 patients (median age 52 years, 81% female, 60% breast cancer), underwent same day repeat TTE and CMR (4 scans). Manual median LVEF was lower with TTE than CMR 57% (95%CI 56.2–57.8) vs 61.4% (95%CI 61–67.7), p<0.01. Analysis failed in 8%, 12% and 4% TTE scans using EchoAI1, EchoAI2 and manual techniques. There were no significant differences in the MAD, CoV or MDD in measurements for LVEF (p>0.05) between analysis methods, Table 1. Human analysis was superior to EchoAI1 for measurements of GLS; MAD 1.37 vs 2.71 (p<0.01), MDD 2.5 vs 5.7 (p<0.01) and CoV 6.9% vs 10.6%, (p = 0.03). There were zero analysis failures for analysis of CMR data. The CoV (3.6% vs 4.5%, p = 0.03), MAD (1.8 vs 2.9, p = 0.03) and MDD (4.3 vs 4.8, p>0.5) for LVEF metrics was lower with CMRAI2 compared to human analysis. The CoV (6.2% vs 11.7%, P<0.01), MAD (1.23 vs 1.92, p = 0.03) and MDD (2.4 vs 3.6, p>0.05) for repeat GLS measurements was lower with human analysis compared with CMRAI1. There were no other significant differences, Table 1. Conclusions Measurement precision is higher with CMR than TTE, in keeping with prior studies. Fully automated AI algorithms can provide incremental improvements in LVEF measurement precision for analysing CMR images. AI techniques for analysis of echocardiographic images provide similar precision to expert human readers. With continued development, fully-automated analysis algorithms should improve confidence in CTRCD surveillance imaging for cancer patients, with results generalisable to other clinical indications.

BACKGROUND Patients with previous coronary artery bypass graft (CABG) surgery typically have complex coronary disease and remain at high risk of adverse events. Quantitative myocardial perfusion indices predict outcomes in native vessel disease, but their prognostic performance in patients with prior CABG is unknown. OBJECTIVES In this study, we sought to evaluate whether global stress myocardial blood flow (MBF) and perfusion reserve (MPR) derived from perfusion mapping cardiac magnetic resonance (CMR) independently predict adverse outcomes in patients with prior CABG. METHODS This was a retrospective analysis of consecutive patients with prior CABG referred for adenosine stress perfusion CMR. Perfusion mapping was performed in-line with automated quantification of MBF. The primary outcome was a composite of all-cause mortality and major adverse cardiovascular events defined as nonfatal myocardial infarction and unplanned revascularization. Associations were evaluated with the use of Cox proportional hazards models after adjusting for comorbidities and CMR parameters. RESULTS A total of 341 patients (median age 67 years, 86% male) were included. Over a median follow-up of 638 days (IQR: 367-976 days), 81 patients (24%) reached the primary outcome. Both stress MBF and MPR independently predicted outcomes after adjusting for known prognostic factors (regional ischemia, infarction). The adjusted hazard ratio (HR) for 1 mL/g/min of decrease in stress MBF was 2.56 (95% CI: 1.45-4.35) and for 1 unit of decrease in MPR was 1.61 (95% CI: 1.08-2.38). CONCLUSIONS Global stress MBF and MPR derived from perfusion CMR independently predict adverse outcomes in patients with previous CABG. This effect is independent from the presence of regional ischemia on visual assessment and the extent of previous infarction. (C) 2022 Published by Elsevier on behalf of the American College of Cardiology Foundation.

Abstract Introduction Patients with cardiac implantable electronic devices (CIEDs) should have access to Magnetic Resonance Imaging (MRI) but are less likely to be referred and hospitals lack provision. A major barrier to service delivery is the administrative demand required to obtain accurate CIED details prior to scheduling. We aimed to understand the administrative requirements of a high-volume Cardiac Device-MRI service to inform the design of an electronic referrals platform that can facilitate workflow. Methods Single centre retrospective audit of a high-volume Cardiac Device-MRI service in a tertiary unit in the UK. Six months of referrals were reviewed for patient and CIED details and barriers met. Referrals were stratified by source, indication, MR-Conditional labelling and referrer. Results Administrative barriers were reviewed for 116 patients with CIEDs referred for MRI (48% cardiac, 52% non-cardiac) between September 2020 and March 2021 (Table 1). Referrers were 47% cardiologists and 53% other specialties. Referral to scan time was 15 days (interquartile range, 8–32). There were no scan-related complications. 34% of referrals contained complete CIED details and 30% stated the MR labelling of the CIED. None incorrectly labelled a CIED as MR-Conditional, but 8% incorrectly labelled as non-MR Conditional. 7 additional days were required to obtain complete CIED details where not provided (involving information requests from two device clinics in 27%), 10% had delays over 2 weeks (maximum 145 days). 35% required 3 or more repeat discussions with referrers after initial referral. Obtaining CIED information for external referrals required 17 days (11–42), compared to 14 (6–35) days for internal referrals (p=0.25). Patients with non-MR Conditional CIEDs required on average 14 days longer to obtain complete referral details than patients with MR-Conditional CIEDs. Even when referrers were aware of non-MR Conditional labelling and received information on risk, 41% required further discussion between patient and referrer regarding risks and benefits of MRI scanning. For cancer referrals, obtaining correct details took 1 day longer than other referrals (p=0.074) and required 2 extra emails to maintain provision within the national time-to-treatment target of 62 days. Missing data was similarly present in referrals from Cardiologists and non-Cardiologists (59% versus 61% respectively), but non-Cardiologists recorded more incorrect CIED details (8% vs 0%). Conclusions Referral for MRI in patients with CIEDs demands significant administrative input to obtain correct device information, leading to delays. These delays are greater for patients with non-MR conditional CIEDs, and data provided is often incorrect or incomplete. This may explain why some patients are not referred for MRI. An online referrals platform has been developed to streamline this process, initially deployed through a network of 60 centres registered in the UK. Funding Acknowledgement Type of funding sources: Private grant(s) and/or Sponsorship. Main funding source(s): This work is supported by British Heart Foundation Innovations funding (HFHF_016).

Coronary artery bypass graft (CABG) surgery effectively relieves symptoms and improves outcomes. However, patients undergoing CABG surgery typically have advanced coronary atherosclerotic disease and remain at high risk for symptom recurrence and adverse events. Functional non-invasive testing for ischaemia is commonly used as a gatekeeper for invasive coronary and graft angiography, and for guiding subsequent revascularisation decisions. However, performing and interpreting non-invasive ischaemia testing in patients post CABG is challenging, irrespective of the imaging modality used. Multiple factors including advanced multi-vessel native vessel disease, variability in coronary hemodynamics post-surgery, differences in graft lengths and vasomotor properties, and complex myocardial scar morphology are only some of the pathophysiological mechanisms that complicate ischaemia evaluation in this patient population. Systematic assessment of the impact of these challenges in relation to each imaging modality may help optimize diagnostic test selection by incorporating clinical information and individual patient characteristics. At the same time, recent technological advances in cardiac imaging including improvements in image quality, wider availability of quantitative techniques for measuring myocardial blood flow and the introduction of artificial intelligence-based approaches for image analysis offer the opportunity to re-evaluate the value of ischaemia testing, providing new insights into the pathophysiological processes that determine outcomes in this patient population.

Introduction Patients with cardiac implantable electronic devices (CIEDs) should have access to Magnetic Resonance Imaging (MRI) when needed. Patients are still less likely to be referred and hospitals may not provide a service. A major barrier is reducing the logistical demand required at scale for a safe service. We aimed to quantify the logistical requirements of a high-volume Cardiac Device-MRI service. Methods A single centre retrospective audit of a high-volume Cardiac Device-MRI service in a tertiary cardiac imaging unit in the UK. Six months of consecutive referrals from September 2020 were reviewed for patient and CIED details and barriers met. Referrals were sorted by source, indication, MR-Conditional labelling and referrer specialty. Results 116 MRIs (48% cardiac, 52% non-cardiac) were performed on CIED patients in six months (table 1). 53% were external referrals, 11% inpatient and 25% were suspected malignancy. Referrers were 47% cardiologists and 53% other specialty. Time from referral to scan was 15 days (interquartile range, IQR: 8 – 32). There were no complications.70% of referrals contained complete CIED details and 34% identified the CIED MR labelling. 17% were referred with incorrect MR-Conditional labelling and 8% with incorrect non-MR Conditional labelling. 7 additional days were required to obtain complete CIED details, 10% had delays over 2 weeks (0-145 days). A cardiac physiology department was contacted for 54%, involving 2 departments in 27%. For cancer referrals, obtaining correct details took 1 day longer compared to other referrals and required 2 extra emails to maintain provision within the national time to treatment targets of 62 days. Missing data was similarly present in referrals from Cardiologists and non-Cardiologists (59% versus 61% respectively). The non-Cardiologists recorded more incorrect CIED details (8% vs 0%) (figure 1). External referrals required 17 days (11 – 42), compared to 14 (6 -35) days for internal referrals to obtain CIED information. Missing data was similarly present in external and internal referrals (67% versus 64%), and 35% required 3 or more repeat discussions with referrers after initial referral. Patients with non-MR Conditional CIED took 14 days longer to obtain complete referral details than MR-Conditional CIEDs. Even when referrers were aware of non-MR Conditional labelling, 41% required further discussion between patient and referrer regarding risks and benefits of MRI scanning. Conclusions Both cardiology and non-cardiology referrers of patients with cardiac implantable electronic devices to MRI incorrectly classify MR-Conditional labelling. There is a large logistical burden to maintaining an MRI service for patients with CIEDs and may explain why some patients are not referred for MRI when required. An online referrals platform is under development to streamline this process, and institutional registration is available at www.mrimypacemaker.com. Conflict of Interest Nil

Coronary artery bypass graft (CABG) surgery effectively relieves symptoms and improves outcomes. However, patients undergoing CABG surgery typically have advanced coronary atherosclerotic disease and remain at high risk for symptom recurrence and adverse events. Functional non-invasive testing for ischaemia is commonly used as a gatekeeper for invasive coronary and graft angiography, and for guiding subsequent revascularisation decisions. However, performing and interpreting non-invasive ischaemia testing in patients post CABG is challenging, irrespective of the imaging modality used. Multiple factors including advanced multi-vessel native vessel disease, variability in coronary hemodynamics post-surgery, differences in graft lengths and vasomotor properties, and complex myocardial scar morphology are only some of the pathophysiological mechanisms that complicate ischaemia evaluation in this patient population. Systematic assessment of the impact of these challenges in relation to each imaging modality may help optimize diagnostic test selection by incorporating clinical information and individual patient characteristics. At the same time, recent technological advances in cardiac imaging including improvements in image quality, wider availability of quantitative techniques for measuring myocardial blood flow and the introduction of artificial intelligence-based approaches for image analysis offer the opportunity to re-evaluate the value of ischaemia testing, providing new insights into the pathophysiological processes that determine outcomes in this patient population.

Methods We conducted a retrospective study of 477 patients referred for CTCA or CT-FFR for investigation of possible coronary ischaemia. Patients were excluded if the image quality was poor or inconclusive. Patient-based PPV was calculated to detect or rule out significant CAD, defined as more than 70% stenosis on ICA. A sub-analysis of PPV by indication for scan was also performed. Patients that underwent invasive non-hyperaemic pressure wire measurements had their iFR or RFR compared with their CT-FFR values. Results