US 12,285,266 B2
Method and system for determining myocardial ischemia severity based on hemodynamic parameters estimation
Oishee Mazumder, Kolkata (IN); Dibyendu Roy, Kolkata (IN); and Aniruddha Sinha, Kolkata (IN)
Assigned to TATA CONSULTANCY SERVICES LIMITED, Mumbai (IN)
Filed by Tata Consultancy Services Limited, Mumbai (IN)
Filed on Aug. 17, 2021, as Appl. No. 17/445,292.
Claims priority of application No. 202021036165 (IN), filed on Aug. 21, 2020.
Prior Publication US 2022/0104763 A1, Apr. 7, 2022
Int. Cl. A61B 5/00 (2006.01); A61B 5/02 (2006.01); A61B 5/021 (2006.01); A61B 5/36 (2021.01); A61B 5/366 (2021.01); A61B 5/367 (2021.01)
CPC A61B 5/4842 (2013.01) [A61B 5/02007 (2013.01); A61B 5/021 (2013.01); A61B 5/36 (2021.01); A61B 5/366 (2021.01); A61B 5/367 (2021.01)] 7 Claims
OG exemplary drawing
 
1. A processor implemented method for determining myocardial ischemia severity based on hemodynamic parameters estimation, the method comprising:
receiving, via one or more hardware processors, a plurality of Electrophysiology (EP) signals from a heart surface model as an input, wherein each Electrophysiology (EP) signal from the plurality of Electrophysiology (EP) signals corresponds to cardiac transmembrane potential (TMP) giving rise to cardiac contraction, wherein the cardiac transmembrane potential (TMP) of the heart surface model is determined through a contractility function and wherein the contractility function determines a compliance function of auricles and ventricles;
generating, via the one or more hardware processors, by a cardiac source module, a Forward Electrophysiology signal from the plurality of Electrophysiology (EP) signals;
processing, via the one or more hardware processors, the Forward Electrophysiology signal, to generate a single lead ECG template, wherein the single lead ECG template comprises at least one of a characteristic constituent comprising: (i) a auricular depolarization (PQ) segment, (ii) a ventricular depolarization (QRS) segment, (iii) a ventricular repolarization (ST) segment and combination thereof, wherein to generate the single lead ECG template, the cardiac source module is expressed as equivalent double layer of sources on closed surface of atrium and ventricles, wherein the single lead ECG template is generated based on a biophysical model that connects the cardiac transmembrane potential (TMP) of representative myocytes on the heart surface model to an electrocardiogram (ECG) signal on surface of a body, and wherein the generated single lead ECG template serves as a driving signal to a hemodynamic module;
estimating, via the one or more hardware processors, by the hemodynamic module, a plurality of hemodynamic parameters based on the single lead ECG template, wherein the plurality of hemodynamic parameters comprises a left heart atrium compliance function Cla(t) and a left heart ventricle compliance function Clv(t), wherein the left heart atrium compliance function Cla(t) is computed based on at least one of (i) a minimum value of the left heart atrium, (ii) a maximum value of the left heart atrium, (iii) a left heart atrium activation function (Ala), and (iv) a time delay in firing between the left heart atrium and the left heart ventricle, wherein the left heart ventricle activation function (Alv(t)) is computed based on systolic and diastolic time duration of the cardiac cycle analogous to (i) the ventricular depolarization (QRS) segment, and (ii) the ventricular repolarization (ST) segment and wherein the left heart ventricle compliance function Clv(t) is computed based on an end systolic compliance and the left heart ventricle activation function (Alv(t));
estimating, via the one or more hardware processors, a plurality of cardiac pressure-volume loop variables based on at least one of (i) the plurality of hemodynamic parameters, and (ii) pressure variation associated with cardiac excitation, and wherein the plurality of cardiac pressure-volume loop variables includes at least one of (i) a dynamic change observed in a systemic artery pressure is estimated based on at least one of (i) a systemic artery compliance, (ii) the left heart ventricle pressure, (iii) a systemic ventricle pressure, (iv) a systemic artery pressure, (v) a resistance value observed in systemic vessels, and (vi) a resistance value observed in aortic vessel, (ii) a dynamic change observed in a left heart ventricle pressure is estimated based on at least one of (i) the left heart ventricle compliance function, (ii) the left heart ventricle pressure, (iii) a pulmonary vein pressure, (iv) the systemic artery pressure, (v) a resistance value observed in mitral vessel, and (vi) a resistance value observed in aortic vessel and (iii) a dynamic change observed in a right ventricle pressure is estimated based on at least one of (i) the right heart ventricle compliance function, (ii) a systemic vein pressure, (iii) the right heart ventricle pressure, (iv) a resistance value observed in tricuspid vessel, (v) a pulmonary artery pressure, and (vi) a resistance value observed in pulmonary valve; and
determining, via the one or more hardware processors, myocardial ischemia severity of the heart surface model based on (i) a scar tissue size, (ii) a velocity reduction value of the cardiac affected region, (iii) a transmembrane potential (TMP) amplitude and repolarization time, (iv) the single lead ECG template and (v) the plurality of cardiac pressure-volume loop variables, wherein the myocardial ischemia severity includes one of moderate ischemia, severe ischemia and silent ischemia, thereby facilitating in generation of synthetic data for disease classification pertaining to a coronary artery.