
doi: 10.1007/bf02820867
pmid: 9403308
In order to explore a new approach to the analysis of diastolic dysfunction, we adapted wave-intensity analysis (WIA), a time-domain analysis that provides information regarding both upstream and downstream events, to left ventricular (LV) filling. WIA considers the pressure and flow waves as summations of successive wavelets, characterised by the direction they travel and by the sign of the pressure gradient associated with them. Wave intensity is the product, dPdU, calculated from the incremental differences in LV pressure (dP) and mitral velocity (dU) and, during the diastolic filling interval, yields up to five dPdU peaks. Peak 1 is caused by backward-travelling expansion waves that accelerate the blood while LV pressure falls, and may be related to "diastolic suction". Peak 2 is caused by forward-travelling compression waves which occur if acceleration continues after LV pressure begins to increase. Peak 3 is caused by backward compression waves and is associated with rising LV pressure and deceleration. Peak 4 is caused by forward compression waves and is associated with the increasing LV pressure and acceleration caused by atrial contraction. Peak 5 is caused by backward compression waves and is associated with increasing pressure and deceleration. These preliminary observations suggest that WIA can be useful in describing the mechanics of LV filling and, after much further work has been accomplished, it might prove useful in the detection and characterization of diastolic dysfunction.
Diastole, Coronary Circulation, Hemorheology, Models, Cardiovascular, Pressure, Ventricular Pressure, Humans, Aorta, Ventricular Function, Left
Diastole, Coronary Circulation, Hemorheology, Models, Cardiovascular, Pressure, Ventricular Pressure, Humans, Aorta, Ventricular Function, Left
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 42 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Top 10% | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Top 10% |
