Background In patients with suspected coronary artery disease (CAD), myocardial perfusion is assessed under rest and pharmacological stress to identify ischemia. Splenic switch-off, defined as the stress to rest splenic perfusion attenuation in response to adenosine, has been proposed as an indicator of stress adequacy. Its occurrence has been previously assessed in first-pass perfusion images, but the use of noncontrast techniques would be highly beneficial. Purpose To explore the ability of pseudo-continuous arterial spin labeling (PCASL) to identify splenic switch-off in patients with suspected CAD. Study Type Prospective. Population Five healthy volunteers (age 24.8 +/- 3.8 years) and 32 patients (age 66.4 +/- 8.2 years) with suspected CAD. Field strength/Sequence A 1.5-T/PCASL (spin-echo) and first-pass imaging (gradient-echo). Assessment In healthy subjects, multi-delay PCASL data (500-2000 msec) were acquired to quantify splenic blood flow (SBF) and determine the adequate postlabeling delay (PLD) for single-delay acquisitions (PLD > arterial transit time). In patients, single-delay PCASL (1200 msec) and first-pass perfusion images were acquired under rest and adenosine conditions. PCASL data were used to compute SBF maps and SBF stress-to-rest ratios. Three observers classified patients into "switch-off" and "failed switch-off" groups by visually comparing rest-stress perfusion data acquired with PCASL and first-pass, independently. First-pass categories were used as reference to evaluate the accuracy of quantitative classification. Statistical Tests Wilcoxon signed-rank, Pearson correlation, kappa, percentage agreement, Generalized Linear Mixed Model, Mann-Whitney, Pearson Chi-squared, receiver operating characteristic, area-under-the-curve (AUC) and confusion matrix. Significance: P value < 0.05. Results A total of 27 patients (84.4%) experienced splenic switch-off according to first-pass categories. Comparison of PCASL-derived SBF maps during stress and rest allowed assessment of splenic switch-off, reflected in a reduction of SBF values during stress. SBF stress-to-rest ratios showed a 97% accuracy (sensitivity = 80%, specificity = 100%, AUC = 85.2%). Data Conclusion This study could demonstrate the feasibility of PCASL to identify splenic switch-off during adenosine perfusion MRI, both by qualitative and quantitative assessments. Evidence Level 2 Technical Efficacy 2

BACKGROUNDSmartwatches have become a widely used tool for health self-care. Its role in ischemic heart disease (IHD) has not been assessed. OBJETCIVESTo evaluate the usefulness of smartwatch ECG registry in IHD.METHODSWe present an observational study of 25 consecutive patients with acute IHD. Conventional ECG and smartwatch tracing were obtained simultaneously at admission. Waves of conventional and smartwatch ECGs were objectively compared. A survey on medical attitude was conducted among 12 physicians (3 cardiologists, 3 intensivists, 3 emergency physicians, and 3 general practitioners) and a score (1 to 5) of concordance between the records was requested.RESULTSThere were no differences in Q wave, R wave, ST segment, or T wave. There was a very strong correlation between ST segments, a strong correlation in Q waves and R waves, and a moderate correlation in T wave measurements.All specialists obtained a high level of agreement (4.45 +/- 0.45). Smartwatch tracings would lead to similar management compared to conventional ECG. There were only 6 (2%) discrepant cases due to differences in inferior repolarization, showing an almost perfect agreement (kappa=0.96).CONCLUSIONSIn most patients with acute IHD, smartwatch ECG tracing is a reliable tool to make the diagnosis and guide appropriate medical care. However, due to their intrinsic limitations, inferior myocardial infarctions may be missed and require a conventional 12-lead ECG to rule them out.

Background: The clinical utility of the Apple Inc.& REG; smartwatch in scenarios beyond detecting atrial fibrillation has been debated. Although the device has the capability to record electrocardiograms (ECG) and detect arrhythmias, voltage limitations hinder its accuracy in measuring real voltage when recording precordial leads. This limitation poses challenges for its clinical use in diagnosing ischemia and screening cardiomyopathies. This review aims to analyze the ECG recording capacity of the Apple Watch, investigate the reasons for voltage limitations, and explore alternative approaches for its use in these clinical scenarios. Methods: A comprehensive literature review was conducted to examine the ECG recording capacity of the Apple Watch and the limitations encountered when recording precordial leads. Data in CSV format files were analyzed to gain insights into the underlying causes of voltage limitations. Results: The Apple Watch demonstrates effectiveness in detecting cardiac arrhythmias such as atrial fibrillation using photoplethysmography and ECG recording. However, voltage limitations during precordial lead recordings impede accurate voltage measurement, thereby limiting its clinical utility. Analysis of the data stored in the CSV files revealed that these voltage limitations are primarily attributed to the presentation format. Exploring alternative approaches for data processing could potentially overcome this challenge. Conclusions: This review highlights the potential for addressing voltage limitations through alternative data processing approaches. Further research is necessary to identify suitable alternatives that enable the Apple Watch to be effectively utilized in these clinical scenarios.