AimsLeft ventricular (LV) pressure–strain loop area reflects regional myocardial work and metabolic demand, but the clinical use of this index is limited by the need for invasive pressure. In this study, we introduce a non-invasive method to measure LV pressure–strain loop area.Methods and resultsLeft ventricular pressure was estimated by utilizing the profile of an empiric, normalized reference curve which was adjusted according to the duration of LV isovolumic and ejection phases, as defined by timing of aortic and mitral valve events by echocardiography. Absolute LV systolic pressure was set equal to arterial pressure measured invasively in dogs (n = 12) and non-invasively in patients (n = 18). In six patients, myocardial glucose metabolism was measured by positron emission tomography (PET). First, we studied anaesthetized dogs and observed an excellent correlation (r = 0.96) and a good agreement between estimated LV pressure–strain loop area and loop area by LV micromanometer and sonomicrometry. Secondly, we validated the method in patients with various cardiac disorders, including LV dyssynchrony, and confirmed an excellent correlation (r = 0.99) and a good agreement between pressure–strain loop areas using non-invasive and invasive LV pressure. Non-invasive pressure–strain loop area reflected work when incorporating changes in local LV geometry (r = 0.97) and showed a strong correlation with regional myocardial glucose metabolism by PET (r = 0.81).ConclusionsThe novel non-invasive method for regional LV pressure–strain loop area corresponded well with invasive measurements and with directly measured myocardial work and it reflected myocardial metabolism. This method for assessment of regional work may be of clinical interest for several patients groups, including LV dyssynchrony and ischaemia.

Providing therapies tailored to each patient is the vision of precision medicine, enabled by the increasing ability to capture extensive data about individual patients. In this position paper, we argue that the second enabling pillar towards this vision is the increasing power of computers and algorithms to learn, reason, and build the ‘digital twin’ of a patient. Computational models are boosting the capacity to draw diagnosis and prognosis, and future treatments will be tailored not only to current health status and data, but also to an accurate projection of the pathways to restore health by model predictions. The early steps of the digital twin in the area of cardiovascular medicine are reviewed in this article, together with a discussion of the challenges and opportunities ahead. We emphasize the synergies between mechanistic and statistical models in accelerating cardiovascular research and enabling the vision of precision medicine.

Echocardiographic assessment of LV filling pressure is feasible and accurate. When combined with clinical data, it leads to a more accurate diagnosis, regardless of LVEF.

Reduced deformation despite preserved EF can be explained through geometric factors. Due to geometric confounders, strain better reflects systolic function in patients with preserved EF.

The presence of a region of reduced MWI in patients with NSTE-ACS identified patients with ACO and was superior to all other parameters. The regional MWI was able to account for the influence of systolic blood pressure on regional contraction. We therefore propose that MWI may serve as an important clinical tool for selecting patients in need of prompt invasive treatment.

Aims The aim of this study is to investigate determinants of left atrial (LA) reservoir and pump strain and if these parameters may serve as non-invasive markers of left ventricular (LV) filling pressure. Methods and results In a multicentre study of 322 patients with cardiovascular disease of different aetiologies, LA strain and other echocardiographic parameters were compared with invasively measured LV filling pressure. The strongest determinants of LA reservoir and pump strain were LV global longitudinal strain (GLS) (r-values 0.64 and 0.51, respectively) and LV filling pressure (r-values −0.52 and −0.57, respectively). Left atrial volume was another independent, but weaker determinant of both LA strains. For both LA strains, association with LV filling pressure was strongest in patients with reduced LV ejection fraction. Left atrial reservoir strain <18% and LA pump strain <8% predicted elevated LV filling pressure better (P < 0.05) than LA volume and conventional Doppler parameters. Accuracy to identify elevated LV filling pressure was 75% for LA reservoir strain alone and 72% for pump strain alone. When combined with conventional parameters, accuracy was 82% for both LA strains. In patients with normal LV systolic function by GLS, LA pump strain >14% identified normal LV filling pressure with 92% accuracy. Conclusion Left atrial reservoir and pump strain are determined predominantly by LV GLS and filling pressure. Accuracy of LA strains to identify elevated LV filling pressure was best in patients with reduced LV systolic function. High values of LA pump strain, however, identified normal LV filling pressure with good accuracy in patients with normal systolic function.

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