Assessment of diastolic function parameters with ECG gated myocardial perfusion spect: comparison of Two algorithms
Esculapio. 2010; 6 (2): 52-57
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| IMEMR
| ID: emr-197172
Biblioteca responsable:
EMRO
Background: To compare Cedars-Sinai QGS and Michigan University Corridor4DM algorithms for determination peak filling rate [PFR], time to peak filling rate [TPFR] and mean filling rate in first third of diastole [MFR3] using 16 frames gated myocardial perfusion single photon emission computed tomography [SPECT]. To determine inter-observer reproducibility of Cedars QGS and Michigan University Corridor4DM for determination PFR, TPFR and MFR3 using 16 frames gated myocardial perfusion SPECT
Methods: Forty patients [28 males and 12 females] with age range 35-70 years [mean 58.85+/-8.82] referred for assessment of left ventricular perfusion and function were included in the study. All patients were injected 1100 Mega Becquerel [MBq] of freshly prepared [99m]Tc Sestamibi. One hour later, patients underwent gated myocardial perfusion SPECT on Siemens ecam dual head variable angle gamma camera using 16 frames per cardiac cycle. Data were reconstructed using filter back projection and re-orientated to generate short axis slices. Short axis slices were processed with QGS and Corridor 4DM for assessment of PFR, TPFR and MFR3 by two observers. Data from both observers were compared to determine inter-observer reproducibility of both methods. Observeri PFR, TPFR and MFR3 values derived from QGS and Corridor4DM were compared and correlated
Results: Peak filling rate values determined with Cedars QGS program were not significantly different from those determined with Corridor4DM [p= 0.564]. Good correlation was found between QGS and 4DM measured PFR values [R[2]=0.6698]. TPFR values determined with QGS program were not significantly different from those determined with Corridor 4DM program [p= 0.615]. However, there was poor correlation between these two methods with R[2] value =0.0382. MFR3 values determined with QGS were not statistically different from those derived from 4DM [p=0.587]. However, there was poor correlation between these values R[2]= 0.0174. Cedars QGS algorithm was highly reproducible for determination of PFR, TPFR and MFR/3 with R2 values of 0.9922, 0.9874 and 0.9932 respectively. PFR, TPFR and MFR3 derived from Corridor4DM were also highly reproducible with R[2] values of 0.7775,0.8381 and 0.456 respectively
Conclusions: Both Cedars QGS and Michigan University Corridor 4DM programs are robust for determination of PFR, TPFR and MFR3 diastolic function parameters. There is good correlation between QGS and 4DM derived PFR measurements. However, there is poor correlation between QGS and 4DM derived TPFR and MFR3 values
Methods: Forty patients [28 males and 12 females] with age range 35-70 years [mean 58.85+/-8.82] referred for assessment of left ventricular perfusion and function were included in the study. All patients were injected 1100 Mega Becquerel [MBq] of freshly prepared [99m]Tc Sestamibi. One hour later, patients underwent gated myocardial perfusion SPECT on Siemens ecam dual head variable angle gamma camera using 16 frames per cardiac cycle. Data were reconstructed using filter back projection and re-orientated to generate short axis slices. Short axis slices were processed with QGS and Corridor 4DM for assessment of PFR, TPFR and MFR3 by two observers. Data from both observers were compared to determine inter-observer reproducibility of both methods. Observeri PFR, TPFR and MFR3 values derived from QGS and Corridor4DM were compared and correlated
Results: Peak filling rate values determined with Cedars QGS program were not significantly different from those determined with Corridor4DM [p= 0.564]. Good correlation was found between QGS and 4DM measured PFR values [R[2]=0.6698]. TPFR values determined with QGS program were not significantly different from those determined with Corridor 4DM program [p= 0.615]. However, there was poor correlation between these two methods with R[2] value =0.0382. MFR3 values determined with QGS were not statistically different from those derived from 4DM [p=0.587]. However, there was poor correlation between these values R[2]= 0.0174. Cedars QGS algorithm was highly reproducible for determination of PFR, TPFR and MFR/3 with R2 values of 0.9922, 0.9874 and 0.9932 respectively. PFR, TPFR and MFR3 derived from Corridor4DM were also highly reproducible with R[2] values of 0.7775,0.8381 and 0.456 respectively
Conclusions: Both Cedars QGS and Michigan University Corridor 4DM programs are robust for determination of PFR, TPFR and MFR3 diastolic function parameters. There is good correlation between QGS and 4DM derived PFR measurements. However, there is poor correlation between QGS and 4DM derived TPFR and MFR3 values