Iranian Heart Journal

Iranian Heart Journal

Impact of Diabetes Mellitus on Left Ventricular Synchrony by Gated Single-Photon Emission Computed Tomography Myocardial Perfusion Imaging Phase Analysis

Document Type : Original Article

Authors
Hadi Malek 1
Rezvaneh Saken Noveiry 1
Nahid Yaghoobi 1
Hooman Bakhshandeh 1
Ahmad Bitarafan-Rajabi 1
Leila Hassanzadeh 1
Raheleh Hedayati 2
1 Rajaie Cardiovascular Medical and Research Center, Iran University of Medical Sciences, Tehran, IR Iran.
2 Rassol-e-akram Hospital, Iran University of Medical Sciences, Tehran, IR Iran.
Abstract
Background: Phase analysis assesses left ventricular (LV) dyssynchrony from gated single-photon emission computed tomography myocardial perfusion imaging (GSPECT-MPI). This study aimed to determine the impact of diabetes mellitus (DM) on phase parameters.
 
Methods: The study population consisted of 121 diabetic patients with no history of coronary artery disease, hypertension, or dyslipidemia and no evidence of perfusion abnormalities or systolic dysfunction in GSPECT-MPI. The resting-state images of MPI were further analyzed using the Cedar–Sinai quantitative GSPECT, and LV phase parameters, including phase histogram bandwidth (PHB), phase standard deviation (PSD), and entropy, were derived. The results were compared with the corresponding figures previously defined in a control group, consisting of 100 subjects with low likelihoods of coronary artery disease, in our center.
 
Results: Significant differences existed in the derived values for PHB, PSD, and entropy between the DM and control groups concerning global whole LV synchrony (P>.05). Likewise, PHB and PSD demonstrated no significant differences between the 2 groups regarding the regional wall-based analysis (P>.05). In contrast, the entropy indices of the LV septum (P= .019) and anterior wall (P= .022) were significantly higher in the DM group.
 
Conclusions: It appears that except for the regional wall-based entropy of the septum and the anterior wall, DM does not inherently impose any significant alterations on the mechanical synchrony indices of GSPECT-MPI. Consequently, the provided normal databases for GSPECT-MPI-derived synchrony parameters could be utilized in DM patients. (Iranian Heart Journal 2023; 24(1): 54-61)
Keywords
Diabetes mellitus
Single-photon emission computed tomography
Myocardial perfusion imaging
  1. Abraham WT, Chin FMH, Feldman AM, Francis FGS, Ganiats FTG, Mancini DM, et al. 2009 Focused update incorporated into the ACC/AHA 2005 Guidelines for the Diagnosis and Management of Heart Failure in Adults. Journal of the American College of Cardiology. 2009; 53(15):e1-90.
  2. Linde C, Ellenbogen K, McAlister FA. Cardiac resynchronization therapy (CRT): Clinical trials, guidelines, and target populations. Heart Rhythm. 2012; 9(8, Supplement):S3-S13.
  3. Yu C-M, Abraham WT, Bax J, Chung E, Fedewa M, Ghio S, et al. Predictors of response to cardiac resynchronization therapy (PROSPECT)-study design. American heart journal. 2005; 149(4):600-5.
  4. White RD, Patel MR, Abbara S, Bluemke DA, Herfkens RJ, Picard M, et al. 2013 ACCF/ACR/ASE/ASNC/SCCT/SCMR appropriate utilization of cardiovascular imaging in heart failure: an executive summary: a joint report of the ACR Appropriateness Criteria® Committee and the ACCF Appropriate Use Criteria Task Force. Journal of the American College of Radiology. 2013; 10(7):493-500.
  5. Oyenuga OA, Onishi T, Gorcsan J. A practical approach to imaging dyssynchrony for cardiac resynchronization therapy. Heart failure reviews. 2011; 16(4):397-410.
  6. Yu C-M, Fung JW-H, Zhang Q, Chan C-K, Chan Y-S, Lin H, et al. Tissue Doppler imaging is superior to strain rate imaging and postsystolic shortening on the prediction of reverse remodeling in both ischemic and nonischemic heart failure after cardiac resynchronization therapy. Circulation. 2004; 110(1):66-73.
  7. Wilson PW, D'Agostino RB, Levy D, Belanger AM, Silbershatz H, Kannel WB. Prediction of coronary heart disease using risk factor categories. Circulation. 1998; 97(18):1837-47.
  8. Scognamiglio R, Negut C, Ramondo A, Tiengo A, Avogaro A. Detection of coronary artery disease in asymptomatic patients with type 2 diabetes mellitus. Journal of the American College of Cardiology. 2006; 47(1):65.
  9. Malek H. Nuclear Cardiology. In: Maleki M, Alizadehasl A, Haghjoo M, editors. Practical Cardiology: Elsevier Health Sciences.; 2017. p. 167-72.
  10. Chen J, Garcia EV, Folks RD, Cooke CD, Faber TL, Tauxe EL, et al. Onset of left ventricular mechanical contraction as determined by phase analysis of ECG-gated myocardial perfusion SPECT imaging: development of a diagnostic tool for assessment of cardiac mechanical dyssynchrony. Journal of Nuclear Cardiology. 2005; 12(6):687-95.
  11. Rastgou F, Shojaeifard M, Amin A, Ghaedian T, Firoozabadi H, Malek H, et al. Assessment of left ventricular mechanical dyssynchrony by phase analysis of gated-SPECT myocardial perfusion imaging and tissue Doppler imaging: comparison between QGS and ECTb software packages. Journal of Nuclear Cardiology. 2014; 21(6):1062-71.
  12. Al-Jaroudi W, Iqbal F, Heo J, Iskandrian AE. Relation between heart rate and left ventricular mechanical dyssynchrony in patients with end-stage renal disease. The American journal of cardiology. 2011; 107(8):1235-40.
  13. Malek H, Rayegan F, Firoozabadi H, Rastgoo F, Haghjoo M, Bakhshandeh H, et al. Determination of normal ranges of regional and global phase parameters using gated myocardial perfusion imaging with Cedars-Sinai's QGS software. Iranian Journal of Nuclear Medicine. 2018; 26(1):16-21.
  14. AlJaroudi W, Koneru J, Heo J, Iskandrian AE. Impact of ischemia on left ventricular dyssynchrony by phase analysis of gated single photon emission computed tomography myocardial perfusion imaging. Journal of Nuclear Cardiology. 2011; 18(1):36-42.
  15. Yaghoobi N, Jamshidi Araghi Z, Malek H, Firoozabadi H, Rastgou F, Bakhshande H, et al. Impact of Hypertension on the Phase Analysis Parameters of Gated Single-Photon Emission Computed Tomography Myocardial Perfusion Imaging. Iranian Heart Journal. 2019; 20(2):47-55.
  16. AlJaroudi W, Jaber WA, Cerqueira MD. Effect of tracer dose on left ventricular mechanical dyssynchrony indices by phase analysis of gated single photon emission computed tomography myocardial perfusion imaging. Journal of Nuclear Cardiology. 2012; 19(1):63-72.
  17. Li D, Zhou Y, Feng J, Yuan D, Cao K, Garcia EV, et al. Impact of image reconstruction on phase analysis of ECG-gated myocardial perfusion SPECT studies. Nuclear medicine communications. 2009; 30(9):700.
  18. Misaka T, Hosono M, Kudo T, Ito T, Syomura T, Uemura M, et al. Influence of acquisition orbit on phase analysis of gated single photon emission computed tomography myocardial perfusion imaging for assessment of left ventricular mechanical dyssynchrony. Annals of nuclear medicine. 2017; 31(3):235-44.
  19. Malek H, Hedayati R, Yaghoobi N, Bitarafan-Rajabi A, Firoozabadi SH, Rastgou F. The effect of milk, water and lemon juice on various subdiaphragmatic activity-related artifacts in myocardial perfusion imaging. Research in cardiovascular medicine. 2015; 4(4).
  20. Van Kriekinge SD, Nishina H, Ohba M, Berman DS, Germano G. Automatic global and regional phase analysis from gated myocardial perfusion SPECT imaging: application to the characterization of ventricular contraction in patients with left bundle branch block. Journal of Nuclear Medicine. 2008; 49(11):1790-7.
  21. Malek H, Yaghoobi N, Hedayati R. Artifacts in Quantitative analysis of myocardial perfusion SPECT, using Cedars-Sinai QPS Software. Journal of Nuclear Cardiology. 2017; 24(2):534-42.
  22. Nakajima K, Okuda K, Matsuo S, Kiso K, Kinuya S, Garcia EV. Comparison of phase dyssynchrony analysis using gated myocardial perfusion imaging with four software programs: Based on the Japanese Society of Nuclear Medicine working group normal database. Journal of Nuclear Cardiology. 2017; 24(2):611-21.
  23. Pazhenkottil AP, Buechel RR, Herzog BA, Nkoulou RN, Valenta I, Fehlmann U, et al. Ultrafast assessment of left ventricular dyssynchrony from nuclear myocardial perfusion imaging on a new high-speed gamma camera. European journal of nuclear medicine and molecular imaging. 2010; 37(11):2086-92.
  24. Hajar R. Risk factors for coronary artery disease: historical perspectives. Heart views: the official journal of the Gulf Heart Association. 2017; 18(3):109.
  25. Nichols GA, Gullion CM, Koro CE, Ephross SA, Brown JB. The incidence of congestive heart failure in type 2 diabetes: an update. Diabetes care. 2004; 27(8):1879-84.
  26. Nichols GA, Hillier TA, Erbey JR, Brown JB. Congestive heart failure in type 2 diabetes: prevalence, incidence, and risk factors. Diabetes care. 2001; 24(9):1614-9.
  27. Ho JE, Lyass A, Lee DS, Vasan RS, Kannel WB, Larson MG, et al. Predictors of new-onset heart failure: differences in preserved versus reduced ejection fraction. Circulation: heart failure. 2013; 6(2):279-86.
  28. Malik D, Mittal B, Sood A, Parmar M, Kaur G, Bahl A. Left ventricular mechanical dyssynchrony assessment in long-standing type II diabetes mellitus patients with normal gated SPECT-MPI. Journal of Nuclear Cardiology. 2019; 26(5):1650-8.
  29. Hämäläinen H, Hedman M, Laitinen T, Hedman A, Kivelä A, Laitinen T. Reference values for left ventricular systolic synchrony according to phase analysis of ECG-gated myocardial perfusion SPECT. Clinical physiology and functional imaging. 2016; 38(1):38-45.
  30. Singh H, Patel CD, Sharma P, Naik N, Singh S, Narang R. Does perfusion pattern influence stress-induced changes in left ventricular mechanical dyssynchrony on thallium-201-gated SPECT myocardial perfusion imaging? Journal of Nuclear Cardiology. 2015; 22(1):36-43.
Iranian Heart Journal
Volume 24, Issue 1
Winter 2023
Pages 54-61