Wearable technology and the cardiovascular system: the future of patient assessment

The past decade has seen a dramatic rise in consumer technologies able to monitor a variety of cardiovascular parameters. Such devices initially recorded markers of exercise, but now include physiological and health-care focused measurements. The public are keen to adopt these devices in the belief that they are useful to identify and monitor cardiovascular disease. Clinicians are therefore often presented with health app data accompanied by a diverse range of concerns and queries. Herein, we assess whether these devices are accurate, their outputs validated, and whether they are suitable for professionals to make management decisions. We review underpinning methods and technologies and explore the evidence supporting the use of these devices as diagnostic and monitoring tools in hypertension, arrhythmia, heart failure, coronary artery disease, pulmonary hypertension, and valvular heart disease. Used correctly, they might improve health care and support research

Quantifying myocardial blood flow and resistance using 4D-flow cardiac magnetic resonance imaging

Background. Ischaemia with nonobstructive coronary arteries is most commonly caused by coronary microvascular dysfunction but remains difcult to diagnose without invasive testing. Myocardial blood fow (MBF) can be quantifed noninvasively on stress perfusion cardiac magnetic resonance (CMR) or positron emission tomography but neither is routinely used in clinical practice due to practical and technical constraints. Quantifcation of coronary sinus (CS) fow may represent a simpler method for CMR MBF quantifcation. 4D fow CMR ofers comprehensive intracardiac and transvalvular fow quantifcation. However, it is feasibility to quantify MBF remains unknown. Methods. Patients with acute myocardial infarction (MI) and healthy volunteers underwent CMR. Te CS contours were traced from the 2-chamber view. A reformatted phase contrast plane was generated through the CS, and fow was quantifed using 4D fow CMR over the cardiac cycle and normalised for myocardial mass. MBF and resistance (MyoR) was determined in ten healthy volunteers, ten patients with myocardial infarction (MI) without microvascular obstruction (MVO), and ten with known MVO. Results. MBF was quantifed in all 30 subjects. MBF was highest in healthy controls (123.8 ± 48.4 mL/min), signifcantly lower in those with MI (85.7 ± 30.5 mL/min), and even lower in those with MI and MVO (67.9 ± 29.2 mL/min/) (P < 0.01 for both diferences). Compared with healthy controls, MyoR was higher in those with MI and even higher in those with MI and MVO (0.79 (±0.35) versus 1.10 (±0.50) versus 1.50 (±0.69), P = 0.02). Conclusions. MBF and MyoR can be quantifed from 4D fow CMR. Resting MBF was reduced in patients with MI and MVO

Wearable technology and the cardiovascular system: the future of patient assessment

The past decade has seen a dramatic rise in consumer technologies able to monitor a variety of cardiovascular parameters. Such devices initially recorded markers of exercise, but now include physiological and health-care focused measurements. The public are keen to adopt these devices in the belief that they are useful to identify and monitor cardiovascular disease. Clinicians are therefore often presented with health app data accompanied by a diverse range of concerns and queries. Herein, we assess whether these devices are accurate, their outputs validated, and whether they are suitable for professionals to make management decisions. We review underpinning methods and technologies and explore the evidence supporting the use of these devices as diagnostic and monitoring tools in hypertension, arrhythmia, heart failure, coronary artery disease, pulmonary hypertension, and valvular heart disease. Used correctly, they might improve health care and support research