| ORIGINAL ARTICLE |
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| Year : 2018 | Volume
: 33
| Issue : 1 | Page : 32-38 |
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Role of myocardial perfusion study in differentiating ischemic versus nonischemic cardiomyopathy using quantitative parameters
Preeti Singh1, Bhairavi Bhatt2, Shwetal U Pawar1, Ashish Kamra1, Suruchi Shetye1, Mangala Ghorpade1
1 Department of Nuclear Medicine and PET-CT, Seth GS Medical College and KEM Hospital, Mumbai, Maharashtra, India
2 Department of Nuclear Medicine, BYL Nair Hospital, Mumbai, Maharashtra, India
Correspondence Address:
Dr. Bhairavi Bhatt
Department of Nuclear Medicine, 218, OPD Building, BYL Nair Hospital, Mumbai Central, Mumbai, Maharashtra
India
 Source of Support: None, Conflict of Interest: None  | Check |
DOI: 10.4103/ijnm.IJNM_118_17
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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.
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