Characterizing the hypertensive cardiovascular phenotype in the UK Biobank.

AIMS: To describe hypertension-related cardiovascular magnetic resonance (CMR) phenotypes in the UK Biobank considering variations across patient populations. METHODS AND RESULTS: We studied 39 095 (51.5% women, mean age: 63.9 ± 7.7 years, 38.6% hypertensive) participants with CMR data available. Hypertension status was ascertained through health record linkage. Associations between hypertension and CMR metrics were estimated using multivariable linear regression adjusting for major vascular risk factors. Stratified analyses were performed by sex, ethnicity, time since hypertension diagnosis, and blood pressure (BP) control. Results are standardized beta coefficients, 95% confidence intervals, and P-values corrected for multiple testing. Hypertension was associated with concentric left ventricular (LV) hypertrophy (increased LV mass, wall thickness, concentricity index), poorer LV function (lower global function index, worse global longitudinal strain), larger left atrial (LA) volumes, lower LA ejection fraction, and lower aortic distensibility. Hypertension was linked to significantly lower myocardial native T1 and increased LV ejection fraction. Women had greater hypertension-related reduction in aortic compliance than men. The degree of hypertension-related LV hypertrophy was greatest in Black ethnicities. Increasing time since diagnosis of hypertension was linked to adverse remodelling. Hypertension-related remodelling was substantially attenuated in hypertensives with good BP control. CONCLUSION: Hypertension was associated with concentric LV hypertrophy, reduced LV function, dilated poorer functioning LA, and reduced aortic compliance. Whilst the overall pattern of remodelling was consistent across populations, women had greater hypertension-related reduction in aortic compliance and Black ethnicities showed the greatest LV mass increase. Importantly, adverse cardiovascular remodelling was markedly attenuated in hypertensives with good BP control.

Burden and prognostic impact of cardiovascular disease in patients with cancer.

The number of patients at the intersection of cancer and cardiovascular disease (CVD) is increasing, reflecting ageing global populations, rising burden of shared cardiometabolic risk factors, and improved cancer survival. Many cancer treatments carry a risk of cardiotoxicity. Baseline cardiovascular risk assessment is recommended in all patients with cancer and requires consideration of individual patient risk and the cardiotoxicity profile of proposed anticancer therapies. Patients with pre-existing CVD are potentially at high or very high risk of cancer-therapy related cardiovascular toxicity. The detection of pre-existing CVD should prompt cardiac optimisation and planning of surveillance during cancer treatment. In patients with severe CVD, the risk of certain cancer therapies may be prohibitively high. Such decisions require multidisciplinary discussion with consideration of alternative anti-cancer therapies, risk-benefit assessment, and patient preference. Current practice is primarily guided by expert opinion and data from select clinical cohorts. There is need for development of a stronger evidence base to guide clinical practice in cardio-oncology. The establishment of multicentre international registries and national-level healthcare data linkage projects are important steps towards facilitating enrichment of cardio-oncology research programmes. In this narrative review, we consider epidemiological trends of cancer and CVD comorbidities and the impact of their co-occurrence on clinical outcomes, current approach to supporting cancer patients with pre-existing CVD and gaps in existing knowledge.

Incident cardiovascular events and imaging phenotypes in UK Biobank participants with past cancer.

OBJECTIVES: To evaluate incident cardiovascular outcomes and imaging phenotypes in UK Biobank participants with previous cancer. METHODS: Cancer and cardiovascular disease (CVD) diagnoses were ascertained using health record linkage. Participants with cancer history (breast, lung, prostate, colorectal, uterus, haematological) were propensity matched on vascular risk factors to non-cancer controls. Competing risk regression was used to calculate subdistribution HRs (SHRs) for associations of cancer history with incident CVD (ischaemic heart disease (IHD), non-ischaemic cardiomyopathy (NICM), heart failure (HF), atrial fibrillation/flutter, stroke, pericarditis, venous thromboembolism (VTE)) and mortality outcomes (any CVD, IHD, HF/NICM, stroke, hypertensive disease) over 11.8±1.7 years of prospective follow-up. Linear regression was used to assess associations of cancer history with left ventricular (LV) and left atrial metrics. RESULTS: We studied 18 714 participants (67% women, age: 62 (IQR: 57-66) years, 97% white ethnicities) with cancer history, including 1354 individuals with cardiovascular magnetic resonance. Participants with cancer had high burden of vascular risk factors and prevalent CVDs. Haematological cancer was associated with increased risk of all incident CVDs considered (SHRs: 1.92-3.56), larger chamber volumes, lower ejection fractions, and poorer LV strain. Breast cancer was associated with increased risk of selected CVDs (NICM, HF, pericarditis and VTE; SHRs: 1.34-2.03), HF/NICM death, hypertensive disease death, lower LV ejection fraction, and lower LV global function index. Lung cancer was associated with increased risk of pericarditis, HF, and CVD death. Prostate cancer was linked to increased VTE risk. CONCLUSIONS: Cancer history is linked to increased risk of incident CVDs and adverse cardiac remodelling independent of shared vascular risk factors.

Multimodality Imaging for Cardiotoxicity: State of the Art and Future Perspectives.

ABSTRACT: Modern cancer therapies have significantly improved survival leading to a growing population of cancer survivors. Similarly, both conventional and newer treatments are associated with a spectrum of cardiovascular disorders with potential long-term sequelae. Prompt detection and treatment of these complications is, therefore, pivotal to enable healthy survivorship and reduce cardiovascular morbidity. Advanced multimodality imaging is a valuable tool for stratifying patient risk, identifying cardiovascular toxicity during and after therapy, and predicting recovery. This review summarizes the potential cardiotoxic complications of anticancer therapies and the multimodality approaches available in each case with special focus on newer techniques and the added value of biomarkers ultimately leading to earlier diagnosis and better prognostication.

Evidence to support magnetic resonance conditional labelling of all pacemaker and defibrillator leads in patients with cardiac implantable electronic devices.

AIMS: Many cardiac pacemakers and defibrillators are not approved by regulators for magnetic resonance imaging (MRI). Even following generator exchange to an approved magnetic resonance (MR)-conditional model, many systems remain classified 'non-MR conditional' due to the leads. This classification makes patient access to MRI challenging, but there is no evidence of increased clinical risk. We compared the effect of MRI on non-MR conditional and MR-conditional pacemaker and defibrillator leads. METHODS AND RESULTS: Patients undergoing clinical 1.5T MRI with pacemakers and defibrillators in three centres over 5 years were included. Magnetic resonance imaging protocols were similar for MR-conditional and non-MR conditional systems. Devices were interrogated pre- and immediately post-scan, and at follow-up, and adverse clinical events recorded. Lead parameter changes peri-scan were stratified by MR-conditional labelling. A total of 1148 MRI examinations were performed in 970 patients (54% non-MR conditional systems, 39% defibrillators, 15% pacing-dependent) with 2268 leads. There were no lead-related adverse clinical events, and no clinically significant immediate or late lead parameter changes following MRI in either MR-conditional or non-MR conditional leads. Small reductions in atrial and right ventricular sensed amplitudes and impedances were similar between groups, with no difference in the proportion of leads with parameter changes greater than pre-defined thresholds (7.1%, 95% confidence interval: 6.1-8.3). CONCLUSIONS: There was no increased risk of MRI in patients with non-MR conditional pacemaker or defibrillator leads when following recommended protocols. Standardizing MR conditions for all leads would significantly improve access to MRI by enabling patients to be scanned in non-specialist centres, with no discernible incremental risk.

Age matters: differences in exercise-induced cardiovascular remodelling in young and middle aged healthy sedentary individuals.

AIMS: Remodelling of the cardiovascular system (including heart and vasculature) is a dynamic process influenced by multiple physiological and pathological factors. We sought to understand whether remodelling in response to a stimulus, exercise training, altered with healthy ageing. METHODS: A total of 237 untrained healthy male and female subjects volunteering for their first time marathon were recruited. At baseline and after 6 months of unsupervised training, race completers underwent tests including 1.5T cardiac magnetic resonance, brachial and non-invasive central blood pressure assessment. For analysis, runners were divided by age into under or over 35 years (U35, O35). RESULTS: Injury and completion rates were similar among the groups; 138 runners (U35: n = 71, women 49%; O35: n = 67, women 51%) completed the race. On average, U35 were faster by 37 minutes (12%). Training induced a small increase in left ventricular mass in both groups (3 g/m2, P < 0.001), but U35 also increased ventricular cavity sizes (left ventricular end-diastolic volume (EDV)i +3%; left ventricular end-systolic volume (ESV)i +8%; right ventricular end-diastolic volume (EDV)i +4%; right ventricular end-systolic volume (ESV)i +5%; P < 0.01 for all). Systemic aortic compliance fell in the whole sample by 7% (P = 0.020) and, especially in O35, also systemic vascular resistance (-4% in the whole sample, P = 0.04) and blood pressure (systolic/diastolic, whole sample: brachial -4/-3 mmHg, central -4/-2 mmHg, all P < 0.001; O35: brachial -6/-3 mmHg, central -6/-4 mmHg, all P < 0.001). CONCLUSION: Medium-term, unsupervised physical training in healthy sedentary individuals induces measurable remodelling of both heart and vasculature. This amount is age dependent, with predominant cardiac remodelling when younger and predominantly vascular remodelling when older.

Maximal Wall Thickness Measurement in Hypertrophic Cardiomyopathy: Biomarker Variability and its Impact on Clinical Care.

OBJECTIVES: The aim of this study was to define the variability of maximal wall thickness (MWT) measurements across modalities and predict its impact on care in patients with hypertrophic cardiomyopathy (HCM). BACKGROUND: Left ventricular MWT measured by echocardiography or cardiovascular magnetic resonance (CMR) contributes to the diagnosis of HCM, stratifies risk, and guides key decisions, including whether to place an implantable cardioverter-defibrillator (ICD). METHODS: A 20-center global network provided paired echocardiographic and CMR data sets from patients with HCM, from which 17 paired data sets of the highest quality were selected. These were presented as 7 randomly ordered pairs (at 6 cardiac conferences) to experienced readers who report HCM imaging in their daily practice, and their MWT caliper measurements were captured. The impact of measurement variability on ICD insertion decisions was estimated in 769 separately recruited multicenter patients with HCM using the European Society of Cardiology algorithm for 5-year risk for sudden cardiac death. RESULTS: MWT analysis was completed by 70 readers (from 6 continents; 91% with >5 years' experience). Seventy-nine percent and 68% scored echocardiographic and CMR image quality as excellent. For both modalities (echocardiographic and then CMR results), intramodality inter-reader MWT percentage variability was large (range -59% to 117% [SD ±20%] and -61% to 52% [SD ±11%], respectively). Agreement between modalities was low (SE of measurement 4.8 mm; 95% CI 4.3 mm-5.2 mm; r = 0.56 [modest correlation]). In the multicenter HCM cohort, this estimated echocardiographic MWT percentage variability (±20%) applied to the European Society of Cardiology algorithm reclassified risk in 19.5% of patients, which would have led to inappropriate ICD decision making in 1 in 7 patients with HCM (8.7% would have had ICD placement recommended despite potential low risk, and 6.8% would not have had ICD placement recommended despite intermediate or high risk). CONCLUSIONS: Using the best available images and experienced readers, MWT as a biomarker in HCM has a high degree of inter-reader variability and should be applied with caution as part of decision making for ICD insertion. Better standardization efforts in HCM recommendations by current governing societies are needed to improve clinical decision making in patients with HCM.

Measurement of T1 Mapping in Patients With Cardiac Devices: Off-Resonance Error Extends Beyond Visual Artifact but Can Be Quantified and Corrected.

Background: Measurement of myocardial T1 is increasingly incorporated into standard cardiovascular magnetic resonance (CMR) protocols, however accuracy may be reduced in patients with metallic cardiovascular implants. Measurement is feasible in segments free from visual artifact, but there may still be off-resonance induced error. Aim: To quantify off-resonance induced T1 error in patients with metallic cardiovascular implants, and validate a method for error correction for a conventional MOLLI pulse sequence. Methods: Twenty-four patients with cardiac implantable electronic devices (CIEDs: 46% permanent pacemakers, PPMs; 33% implantable loop recorders, ILRs; and 21% implantable cardioverter-defibrillators, ICDs); and 31 patients with aortic valve replacement (AVR) (45% metallic) were studied. Paired mid-myocardial short-axis MOLLI and single breath-hold off-resonance field maps were acquired at 1.5 T. T1 values were measured by AHA segment, and segments with visual artifact were excluded. T1 correction was applied using a published relationship between off-resonance and T1. The accuracy of the correction was assessed in 10 healthy volunteers by measuring T1 before and after external placement of an ICD generator next to the chest to generate off-resonance. Results: T1 values in healthy volunteers with an ICD were underestimated compared to without (967 ± 52 vs. 997 ± 26 ms respectively, p = 0.0001), but were similar after correction (p = 0.57, residual difference 2 ± 27 ms). Artifact was visible in 4 ± 12, 42 ± 31, and 53 ± 27% of AHA segments in patients with ILRs, PPMs, and ICDs, respectively. In segments without artifact, T1 was underestimated by 63 ms (interquartile range: 7-143) per patient. The greatest error for patients with ILRs, PPMs and ICDs were 79, 146, and 191 ms, respectively. The presence of an AVR did not generate T1 error. Conclusion: Even when there is no visual artifact, there is error in T1 in patients with CIEDs, but not AVRs. Off-resonance field map acquisition can detect error in measured T1, and a correction can be applied to quantify T1 MOLLI accurately.

Patterns of myocardial injury in recovered troponin-positive COVID-19 patients assessed by cardiovascular magnetic resonance.

BACKGROUND: Troponin elevation is common in hospitalized COVID-19 patients, but underlying aetiologies are ill-defined. We used multi-parametric cardiovascular magnetic resonance (CMR) to assess myocardial injury in recovered COVID-19 patients. METHODS AND RESULTS: One hundred and forty-eight patients (64 ± 12 years, 70% male) with severe COVID-19 infection [all requiring hospital admission, 48 (32%) requiring ventilatory support] and troponin elevation discharged from six hospitals underwent convalescent CMR (including adenosine stress perfusion if indicated) at median 68 days. Left ventricular (LV) function was normal in 89% (ejection fraction 67% ± 11%). Late gadolinium enhancement and/or ischaemia was found in 54% (80/148). This comprised myocarditis-like scar in 26% (39/148), infarction and/or ischaemia in 22% (32/148) and dual pathology in 6% (9/148). Myocarditis-like injury was limited to three or less myocardial segments in 88% (35/40) of cases with no associated LV dysfunction; of these, 30% had active myocarditis. Myocardial infarction was found in 19% (28/148) and inducible ischaemia in 26% (20/76) of those undergoing stress perfusion (including 7 with both infarction and ischaemia). Of patients with ischaemic injury pattern, 66% (27/41) had no past history of coronary disease. There was no evidence of diffuse fibrosis or oedema in the remote myocardium (T1: COVID-19 patients 1033 ± 41 ms vs. matched controls 1028 ± 35 ms; T2: COVID-19 46 ± 3 ms vs. matched controls 47 ± 3 ms). CONCLUSIONS: During convalescence after severe COVID-19 infection with troponin elevation, myocarditis-like injury can be encountered, with limited extent and minimal functional consequence. In a proportion of patients, there is evidence of possible ongoing localized inflammation. A quarter of patients had ischaemic heart disease, of which two-thirds had no previous history. Whether these observed findings represent pre-existing clinically silent disease or de novo COVID-19-related changes remain undetermined. Diffuse oedema or fibrosis was not detected.

Role of cardiovascular magnetic resonance imaging in cardio-oncology.

Advances in cancer therapy have led to significantly longer cancer-free survival times over the last 40 years. Improved survivorship coupled with increasing recognition of an expanding range of adverse cardiovascular effects of many established and novel cancer therapies has highlighted the impact of cardiovascular disease in this population. This has led to the emergence of dedicated cardio-oncology services that can provide pre-treatment risk stratification, surveillance, diagnosis, and monitoring of cardiotoxicity during cancer therapies, and late effects screening following completion of treatment. Cardiovascular imaging and the development of imaging biomarkers that can accurately and reliably detect pre-clinical disease and enhance our understanding of the underlying pathophysiology of cancer treatment-related cardiotoxicity are becoming increasingly important. Multi-parametric cardiovascular magnetic resonance (CMR) is able to assess cardiac structure, function, and provide myocardial tissue characterization, and hence can be used to address a variety of important clinical questions in the emerging field of cardio-oncology. In this review, we discuss the current and potential future applications of CMR in the investigation and management of cancer patients.

Repeatability of Cardiac Magnetic Resonance Radiomics: A Multi-Centre Multi-Vendor Test-Retest Study.

Aims: To evaluate the repeatability of cardiac magnetic resonance (CMR) radiomics features on test-retest scanning using a multi-centre multi-vendor dataset with a varied case-mix. Methods and Results: The sample included 54 test-retest studies from the VOLUMES resource (thevolumesresource.com). Images were segmented according to a pre-defined protocol to select three regions of interest (ROI) in end-diastole and end-systole: right ventricle, left ventricle (LV), and LV myocardium. We extracted radiomics shape features from all three ROIs and, additionally, first-order and texture features from the LV myocardium. Overall, 280 features were derived per study. For each feature, we calculated intra-class correlation coefficient (ICC), within-subject coefficient of variation, and mean relative difference. We ranked robustness of features according to mean ICC stratified by feature category, ROI, and cardiac phase, demonstrating a wide range of repeatability. There were features with good and excellent repeatability (ICC ≥ 0.75) within all feature categories and ROIs. A high proportion of first-order and texture features had excellent repeatability (ICC ≥ 0.90), however, these categories also contained features with the poorest repeatability (ICC < 0.50). Conclusion: CMR radiomic features have a wide range of repeatability. This paper is intended as a reference for future researchers to guide selection of the most robust features for clinical CMR radiomics models. Further work in larger and richer datasets is needed to further define the technical performance and clinical utility of CMR radiomics.

Improving the Generalizability of Convolutional Neural Network-Based Segmentation on CMR Images.

Background: Convolutional neural network (CNN) based segmentation methods provide an efficient and automated way for clinicians to assess the structure and function of the heart in cardiac MR images. While CNNs can generally perform the segmentation tasks with high accuracy when training and test images come from the same domain (e.g., same scanner or site), their performance often degrades dramatically on images from different scanners or clinical sites. Methods: We propose a simple yet effective way for improving the network generalization ability by carefully designing data normalization and augmentation strategies to accommodate common scenarios in multi-site, multi-scanner clinical imaging data sets. We demonstrate that a neural network trained on a single-site single-scanner dataset from the UK Biobank can be successfully applied to segmenting cardiac MR images across different sites and different scanners without substantial loss of accuracy. Specifically, the method was trained on a large set of 3,975 subjects from the UK Biobank. It was then directly tested on 600 different subjects from the UK Biobank for intra-domain testing and two other sets for cross-domain testing: the ACDC dataset (100 subjects, 1 site, 2 scanners) and the BSCMR-AS dataset (599 subjects, 6 sites, 9 scanners). Results: The proposed method produces promising segmentation results on the UK Biobank test set which are comparable to previously reported values in the literature, while also performing well on cross-domain test sets, achieving a mean Dice metric of 0.90 for the left ventricle, 0.81 for the myocardium, and 0.82 for the right ventricle on the ACDC dataset; and 0.89 for the left ventricle, 0.83 for the myocardium on the BSCMR-AS dataset. Conclusions: The proposed method offers a potential solution to improve CNN-based model generalizability for the cross-scanner and cross-site cardiac MR image segmentation task.

Training for a First-Time Marathon Reverses Age-Related Aortic Stiffening.

BACKGROUND: Aging increases aortic stiffness, contributing to cardiovascular risk even in healthy individuals. Aortic stiffness is reduced through supervised training programs, but these are not easily generalizable. OBJECTIVES: The purpose of this study was to determine whether real-world exercise training for a first-time marathon can reverse age-related aortic stiffening. METHODS: Untrained healthy individuals underwent 6 months of training for the London Marathon. Assessment pre-training and 2 weeks post-marathon included central (aortic) blood pressure and aortic stiffness using cardiovascular magnetic resonance distensibility. Biological "aortic age" was calculated from the baseline chronological age-stiffness relationship. Change in stiffness was assessed at the ascending (Ao-A) and descending aorta at the pulmonary artery bifurcation (Ao-P) and diaphragm (Ao-D). Data are mean changes (95% confidence intervals [CIs]). RESULTS: A total of 138 first-time marathon completers (age 21 to 69 years, 49% male) were assessed, with an estimated training schedule of 6 to 13 miles/week. At baseline, a decade of chronological aging correlated with a decrease in Ao-A, Ao-P, and Ao-D distensibility by 2.3, 1.9, and 3.1 × 10-3 mm Hg-1, respectively (p < 0.05 for all). Training decreased systolic and diastolic central (aortic) blood pressure by 4 mm Hg (95% CI: 2.8 to 5.5 mm Hg) and 3 mm Hg (95% CI: 1.6 to 3.5 mm Hg). Descending aortic distensibility increased (Ao-P: 9%; p = 0.009; Ao-D: 16%; p = 0.002), while remaining unchanged in the Ao-A. These translated to a reduction in "aortic age" by 3.9 years (95% CI: 1.1 to 7.6 years) and 4.0 years (95% CI: 1.7 to 8.0 years) (Ao-P and Ao-D, respectively). Benefit was greater in older, male participants with slower running times (p < 0.05 for all). CONCLUSIONS: Training for and completing a marathon even at relatively low exercise intensity reduces central blood pressure and aortic stiffness-equivalent to a ∼4-year reduction in vascular age. Greater rejuvenation was observed in older, slower individuals.

Sex and regional differences in myocardial plasticity in aortic stenosis are revealed by 3D model machine learning.

AIMS: Left ventricular hypertrophy (LVH) in aortic stenosis (AS) varies widely before and after aortic valve replacement (AVR), and deeper phenotyping beyond traditional global measures may improve risk stratification. We hypothesized that machine learning derived 3D LV models may provide a more sensitive assessment of remodelling and sex-related differences in AS than conventional measurements. METHODS AND RESULTS: One hundred and sixteen patients with severe, symptomatic AS (54% male, 70 ± 10 years) underwent cardiovascular magnetic resonance pre-AVR and 1 year post-AVR. Computational analysis produced co-registered 3D models of wall thickness, which were compared with 40 propensity-matched healthy controls. Preoperative regional wall thickness and post-operative percentage wall thickness regression were analysed, stratified by sex. AS hypertrophy and regression post-AVR was non-uniform-greatest in the septum with more pronounced changes in males than females (wall thickness regression: -13 ± 3.6 vs. -6 ± 1.9%, respectively, P < 0.05). Even patients without LVH (16% with normal indexed LV mass, 79% female) had greater septal and inferior wall thickness compared with controls (8.8 ± 1.6 vs. 6.6 ± 1.2 mm, P < 0.05), which regressed post-AVR. These differences were not detectable by global measures of remodelling. Changes to clinical parameters post-AVR were also greater in males: N-terminal pro-brain natriuretic peptide (NT-proBNP) [-37 (interquartile range -88 to -2) vs. -1 (-24 to 11) ng/L, P = 0.008], and systolic blood pressure (12.9 ± 23 vs. 2.1 ± 17 mmHg, P = 0.009), with changes in NT-proBNP correlating with percentage LV mass regression in males only (ß 0.32, P = 0.02). CONCLUSION: In patients with severe AS, including those without overt LVH, LV remodelling is most plastic in the septum, and greater in males, both pre-AVR and post-AVR. Three-dimensional machine learning is more sensitive than conventional analysis to these changes, potentially enhancing risk stratification. CLINICAL TRIAL REGISTRATION: Regression of myocardial fibrosis after aortic valve replacement (RELIEF-AS); NCT02174471. https://clinicaltrials.gov/ct2/show/NCT02174471.

Advanced Imaging Modalities to Monitor for Cardiotoxicity.

OPINION STATEMENT: Early detection and treatment of cardiotoxicity from cancer therapies is key to preventing a rise in adverse cardiovascular outcomes in cancer patients. Over-diagnosis of cardiotoxicity in this context is however equally hazardous, leading to patients receiving suboptimal cancer treatment, thereby impacting cancer outcomes. Accurate screening therefore depends on the widespread availability of sensitive and reproducible biomarkers of cardiotoxicity, which can clearly discriminate early disease. Blood biomarkers are limited in cardiovascular disease and clinicians generally still use generic screening with ejection fraction, based on historical local expertise and resources. Recently, however, there has been growing recognition that simple measurement of left ventricular ejection fraction using 2D echocardiography may not be optimal for screening: diagnostic accuracy, reproducibility and feasibility are limited. Modern cancer therapies affect many myocardial pathways: inflammatory, fibrotic, metabolic, vascular and myocyte function, meaning that multiple biomarkers may be needed to track myocardial cardiotoxicity. Advanced imaging modalities including cardiovascular magnetic resonance (CMR), computed tomography (CT) and positron emission tomography (PET) add improved sensitivity and insights into the underlying pathophysiology, as well as the ability to screen for other cardiotoxicities including coronary artery, valve and pericardial diseases resulting from cancer treatment. Delivering screening for cardiotoxicity using advanced imaging modalities will however require a significant change in current clinical pathways, with incorporation of machine learning algorithms into imaging analysis fundamental to improving efficiency and precision. In the future, we should aspire to personalized rather than generic screening, based on a patient's individual risk factors and the pathophysiological mechanisms of the cancer treatment they are receiving. We should aspire that progress in cardiooncology is able to track progress in oncology, and to ensure that the current 'one size fits all' approach to screening be obsolete in the very near future.

Cardiac Rhythm Device Identification Using Neural Networks.

OBJECTIVES: This paper reports the development, validation, and public availability of a new neural network-based system which attempts to identify the manufacturer and even the model group of a pacemaker or defibrillator from a chest radiograph. BACKGROUND: Medical staff often need to determine the model of a pacemaker or defibrillator (cardiac rhythm device) quickly and accurately. Current approaches involve comparing a device's radiographic appearance with a manual flow chart. METHODS: In this study, radiographic images of 1,676 devices, comprising 45 models from 5 manufacturers were extracted. A convolutional neural network was developed to classify the images, using a training set of 1,451 images. The testing set contained an additional 225 images consisting of 5 examples of each model. The network's ability to identify the manufacturer of a device was compared with that of cardiologists, using a published flowchart. RESULTS: The neural network was 99.6% (95% confidence interval [CI]: 97.5% to 100.0%) accurate in identifying the manufacturer of a device from a radiograph and 96.4% (95% CI: 93.1% to 98.5%) accurate in identifying the model group. Among 5 cardiologists who used the flowchart, median identification of manufacturer accuracy was 72.0% (range 62.2% to 88.9%), and model group identification was not possible. The network's ability to identify the manufacturer of the devices was significantly superior to that of all the cardiologists (p < 0.0001 compared with the median human identification; p < 0.0001 compared with the best human identification). CONCLUSIONS: A neural network can accurately identify the manufacturer and even model group of a cardiac rhythm device from a radiograph and exceeds human performance. This system may speed up the diagnosis and treatment of patients with cardiac rhythm devices, and it is publicly accessible online.

MRI for patients with cardiac implantable electronic devices: simplifying complexity with a 'one-stop' service model.

BACKGROUND: Patients with cardiac pacemakers and defibrillators are disadvantaged because of poor access to MRI scans, leading to late and misdiagnosis particularly for cancer and neurological disease. New technology allied to tested protocols now allows safe MRI scanning of such patients; however, logistical barriers persist. AIM: To deliver a streamlined sustainable service that provides timely MRI scans to patients with cardiac implantable electronic devices (CIEDs). METHODS: Patients requested a 'one-stop' service for MRI, whereby devices could be reprogrammed and scans acquired at a single location and visit. To provide this 'one-stop' service, we trained a team including administrators, physicians, cardiac physiologists and radiographers. A standard protocol was used to prevent unnecessary request refusals and delays to scheduling. Service volume, waiting time and safety were analysed 6 months before and 2 years after service redesign. Waiting times for internal and external inpatient referrals plus time to treatment for patients on a cancer pathway were analysed. RESULTS: 215 MRI scans were performed over 2 years. After service redesign, MRI provision increased six-fold to 20 times the national average with reduced waiting time from 60 to 15 days and no adverse events. Departmental throughput was maintained. 85 (40%) referrals were external. 41 (19%) inpatients were scanned, reducing bed-stay by 3 days for internal referrals. 24 (11%) scans were for suspected cancer, 83% allowed treatment within the national standard of 62 days. There was no preintervention service for either inpatients or suspected cancer investigation. CONCLUSION: Implementation of a 'one-stop' service model to provide MRI for patients with CIEDs is safe, streamlined, scalable and has reduced delays making economic and clinical sense. Protocols and checklists are available at mrimypacemaker.com.