title: Single-beat estimation of end-diastolic pressure-volume relationship: a novel method with potential for noninvasive application.
abstract: Whereas end-systolic and end-diastolic pressure-volume relations (ESPVR, EDPVR) characterize left ventricular (LV) pump properties, clinical utility of these relations has been hampered by the need for invasive measurements over a range of pressure and volumes. We propose a single-beat approach to estimate the whole EDPVR from one measured volume-pressure (Vm and Pm) point. Ex vivo EDPVRs were measured from 80 human hearts of different etiologies (normal, congestive heart failure, left ventricular assist device support). Independent of etiology, when EDPVRs were normalized (EDPVRn) by appropriate scaling of LV volumes, EDPVRns were nearly identical and were optimally described by the relation EDP = An.EDV (Bn), with An = 28.2 mmHg and Bn = 2.79. V0 (the volume at the pressure of approximately 0 mmHg) was predicted by using the relation V0 = Vm.(0.6 - 0.006.Pm) and V30 by V30 = V0 + (Vm,n - V0)/(Pm/An) (1/Bn). The entire EDPVR of an individual heart was then predicted by forcing the curve through Vm, Pm, and the predicted V0 and V30. This technique was applied prospectively to the ex vivo human EDPVRs not used in determining optimal An and Bn values and to 36 in vivo human, 12 acute and 14 chronic canine, and 80 in vivo and ex vivo rat studies. The root-mean-square error (RMSE) in pressure between measured and predicted EDPVRs over the range of 0-40 mmHg was < 3 mmHg of measured EDPVR in all settings, indicating a good predictive value of this approach. Volume-normalized EDPVRs have a common shape, despite different etiology and species. This allows the entire curve to be predicted by a new method with a potential for noninvasive application. The results are most accurate when applied to groups of hearts rather than to individual hearts.
authors.affiliation: Department of Medicine, College of Physicians and Surgeons, Columbia University, New York City, New York, USA.
authors.forename: Stefan
authors.initials: S
authors.lastname: Klotz
authors.forename: Ilan
authors.initials: I
authors.lastname: Hay
authors.forename: Marc L
authors.initials: ML
authors.lastname: Dickstein
authors.forename: Geng-Hua
authors.initials: GH
authors.lastname: Yi
authors.forename: Jie
authors.initials: J
authors.lastname: Wang
authors.forename: Mathew S
authors.initials: MS
authors.lastname: Maurer
authors.forename: David A
authors.initials: DA
authors.lastname: Kass
authors.forename: Daniel
authors.initials: D
authors.lastname: Burkhoff
mesh_terms: D000465:Algorithms; D000818:Animals; D001794:Blood Pressure; D001795:Blood Pressure Determination / Q000379:methods*; D002102:Cadaver; D003198:Computer Simulation; D003936:Diagnosis, Computer-Assisted / Q000379:methods*; D003971:Diastole; D004285:Dogs; D006331:Heart Diseases / Q000175:diagnosis* / Q000503:physiopathology*; D006339:Heart Rate / Q000502:physiology*; D006801:Humans; D066298:In Vitro Techniques; D008955:Models, Cardiovascular; D011673:Pulsatile Flow / Q000502:physiology; D051381:Rats; D017207:Rats, Sprague-Dawley; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D013318:Stroke Volume