Role of myocardial perfusion study in differentiating ischemic versus nonischemic cardiomyopathy using quantitative parameters

• Published in: Indian journal of nuclear medicine 2018-01, Vol.33 (1), p.32-38
• Main Authors: Singh, Preeti, Bhatt, Bhairavi, Pawar, Shwetal, Kamra, Ashish, Shetye, Suruchi, Ghorpade, Mangala
• Format: Article
• Language: English
• Subjects: Adenosine; Angiography; Cameras; Cardiology; Cardiomyopathy; Cardiovascular disease; Coronary vessels; Diagnostic software; Diagnostic systems; Ejection fraction; Fasting; Glucose; Heart failure; Hospitals; Ischemia; Mathematical analysis; Medical imaging; Medical prognosis; Metabolism; Myocardial diseases; NMR; Nuclear magnetic resonance; Nuclear medicine; Original; Patients; Rest; Sensitivity; Stresses; Studies; Tomography
• ISSN: 0972-3919; 0974-0244
• DOI: 10.4103/ijnm.IJNM_118_17

Purpose: Ischemic cardiomyopathy (ICM) and non-ICM (NICM) causes of dilated cardiomyopathy with similar clinical presentation have different management and prognosis. This study employed myocardial perfusion imaging (MPI) to differentiate between the two using quantitative parameters in Indian population. Methods and Materials: Fifty patients prospectively underwent MPI and 18F-fluorodeoxyglucose metabolism studies. P values (0.05 as significant) were calculated for the left ventricular ejection fraction (EF), end diastolic volume (EDV) at rest and stress, end systolic volume (ESV) at rest and stress, summed rest score (SRS), summed difference score (SDS), and eccentricity. On 6-month follow-up, rate of hospital admission, change in management and death was correlated for ICM and NICM. Coronary angiography (CAG) being gold standard, sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and level of agreement were calculated for MPI. Results: MPI and CAG had a moderate level of agreement (κ = 0.463) for differentiating ICM and NICM. The sensitivity, specificity, PPV, NPV, and diagnostic accuracy were 79.31%, 66.67%, 76.67%, 70.0%, and 74% for ICM and 66.67%, 79.31%, 70%, 76.67%, and 74% for NICM, respectively. Significant differences were seen in EDV stress (P = 0.045), EDV rest (P = 0.031), ESV rest (P = 0.034), SRS (P = 0.004), Left ventricular EF rest (P = 0.049) and SDS in ICM and NICM, respectively. Conclusion: EDV at rest and stress, ESV at rest, SRS, SDS, and EF at rest obtained using MPI provides precise quantitative information to differentiate ICM and NICM. It is wide and easy availability, noninvasiveness, objectivity, and near absence of complications favors it as a preferable diagnostic tool with its given sensitivity, specificity, and accuracy for the purpose.