Mehmet ERDOĞAN, Bayram Ali UYSAL, Mustafa KARABACAK, Mevlüt Serdar KUYUMCU, Mustafa AVCI, Samet YAĞCI, Adnan KARAIBRAHIMOGLU, Sevim Süreyya ŞENGÜL

99mTc-MIBI Miyokard Perfüzyon Sintigrafisi ile Değerlendirilen Kantitatif Verilerin, Koroner Arter Hastalığını Öngörme Kabiliyeti

Amaç: 99mTc-MIBI miyokardiyal perfüzyon görüntülemenin, visual yorumunun etkinliği, koroner arter hastalığının (KAH) tanısal ve prognostik değerlendirmesinde defalarca doğrulanmasına rağmen, bilgisayar programlarına bağımlı otomatik kantitatif değerlendirmenin etkinliği tartışma konusudur. Biz çalışmamızda, sum stress score (SSS) ve sum difference score (SDS) gibi otomatik kantitatif verileri, koroner anjiyografi sonuçları ile karşılaştırdık. SSS ve SDS değerlerinin, koroner arter hastalığını öngörme kabiliyetini araştırdık. Yöntem: SSS ve SDS, myocardial perfüzyonun global skorlamasında kullanılan ölçümlerdir. SSS’u iskeminin derecesini gösterirken, SDS iskeminin geri döndürülebilir olma derecesini tanımlar. Myokardiyal perfüzyonun global skorlamasında, SSS’u 4 ve üzerinde ise MPS pozitif olarak değerlendirildi. Koroner anjiografide ise >%50 üzerinde darlık pozitif olarak değerlendirildi. SSS’nu hafif (4-8), orta (9-12) ve ileri (>13) düzeyde hipoperfüzyon olmak üzere 3 gruba ayırdık. SDS’nu %10 un altı ve üstü olmak üzere 2 gruba ayırdık. Bu kantitatif verileri, 3 grup koroner anjiyografi sonuçlarıyla karşılaştırdık (%70 darlık). Bulgular: Çalışmaya toplam 104 anjiyo uygulaması yapılan hasta dahil edildi. Hastaların genel kantitatif MPS ve anjiyografi yöntemleri arasındaki pozitiflik tespitindeki doğruluk %80,8 olarak hesaplandı. Uyuşum değeri anlamlı bulundu (Kappa=0,602; p

Anahtar Kelimeler:

Miyokard Perfüzyon Sintigrafisi, SSS, SRS, SDS

The Ability of Quantitative Data Evaluated by 99m Tc-MIBI Myocardial Perfusion Scintigraphy to Predict Coronary Artery Disease

Objective: Although the efficacy of the visual interpretation of 99mTc-MIBI myocardial perfusion imaging has been repeatedly confirmed in the diagnostic and prognostic evaluation of coronary artery disease (CAD), the efficacy of the automated quantitative evaluation dependent on computer programs is controversial. In our study, we compared automated quantitative data, such as the sum stress score (SSS) and the sum difference score (SDS), with coronary angiography results. We investigated the ability of SSS and SDS values to predict coronary artery disease. Method: SSS and SDS are measurements used in the global scoring of myocardial perfusion. While SSS indicates the degree of ischemia, SDS defines the reversibility degree of ischemia. In the global scoring of myocardial perfusion, when the SSS was 4 and above, MPI was evaluated as positive. In the coronary angiography, a stenosis value of >50% was evaluated as positive. We divided the SSS into three groups; mild (4-8), moderate (9-12), and advanced (>13) hypoperfusion. We divided the SDS into two groups as below and above 10%. We compared the subsequent quantitative data with the results of the three groups of coronary angiographies (70% stenosis). Results: A total of 104 patients who underwent angiography were included in the study. The accuracy in detecting positivity between the general quantitative MPI and angiography methods of the patients was calculated as 80.8%. The agreement value was found to be significant (Kappa=0.602; p

Keywords:

Myocardial Perfusion Scintigraphy, SSS, SRS, SDS,

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1) Goff Jr DC, Lloyd-Jones DM, Bennett G, Coady S, D’Agostino Sr RB, Gibbons R, Greenland P, Lackland DT, Levy D, O’Donnell CJ, Robinson JG, Schwartz JS, Shero ST, Smith Jr SC, Sorlie P, et al. 2013 ACC/AHA guideline on the assessment of cardiovascular risk: a report of the American College of Cardiology/Ameri- can Heart Association Task Force on Practice Guidelines. Circulation 2014; 129(25 Suppl. 2):S49–73.
2) Monika Czaja, Zbigniew Wygoda, Agata Duszańska, Dominik Szczerba, Jan Głowacki, Mariusz Gąsior, Jarosław P. Wasilewski. Interpreting myocardial perfusion scintigraphy using single-photon emission computed tomography. Kardiochriugia i Torakochirurgia Polska 2017; 14 (3): 192-199
3) William D. Leslie, Shawn A. Tully, Marina S. Yogendran, Linda M. Ward, Khaled A. Nour, and Colleen J. Metge. Prognostic Value of Automated Quantification of 99m Tc-Sestamibi Myocardial Perfusion Imaging. J Nucl Med. 2005;46:204-211.
4) Yoda S, Nakanishi K, Tano A, Hori Y, Suzuki Y, Matsumoto N, Hirayama A. Validation of automated quantification of nuclear cardiology in Japanese patients using total perfusion deficits: comparison with visual assessment. J Cardiol 2014; 63: 350-357.
5) Berman DS, Kang X, Gransar H, Gerlach J, Friedman JD, Hayes SW, Thom- son LE, Hachamovitch R, Shaw LJ, Slomka PJ, Yang LD, Germano G. Quantita- tive assessment of myocardial perfusion abnormality on SPECT myocardial perfusion imaging is more reproducible than expert visual analysis. J Nucl Cardiol 2009; 16: 45-53.
6) Hachamovitch R, Rozanski A, Hayes SW, Thomson LE, Germano G, Fried- man JD, Cohen I, Berman DS. Predicting therapeutic benefit from myocardial revascularization procedures: are measurements of both resting left ventricular ejection fraction and stress-induced myocardial ischemia necessary J Nucl Cardiol 2006; 13: 768-778.
7) Weintraub WS, Karlsberg RP, Tcheng JE, Boris JR, Buxton AE, Dove JT, et al. ACCF/AHA 2011 key data elements and definitions of a base cardiovascular vocabulary for electronic health records: a report of the American College of Cardiology Foundation/American Heart Association Task Force on Clinical Data Standards. J Am Coll Cardiol. 2011;58(2):202–222.
8) Patel MR, Bailey SR, Bonow RO, Chambers CE, Chan PS, Dehmer GJ, et al. ACCF/SCAI/AATS/AHA/ASE/ASNC/HFSA/HRS/SCCM/SCCT/SCMR/STS 2012 Appropriate use criteria for diagnostic catheterization: a report of the American College of Cardiology Foundation. Appropriate use criteria Tak Force, Society for Cardiovascular Angiography and Interventions, American Association for Thoracic Surgery. J Am Coll Cardiol. 2012;59(22):1995–2027.
9) Hendel RC, Budoff MJ, Cardella JF, Chambers CE, Dent JM, Fitzgerald DM, et al. ACC/ACR/ASE/ASNC/HRS/NASCI/RSNA/SAIP/SCAI/SCCT/SCMR/SIR 2008 key data elements and definitions for cardiac imaging: a report of the American College of Cardiology/American Heart Association Task Force on Clinical Data Standards (Writing Committee to Develop Clinical Data Standards for Cardiac Imaging) J Am Coll Cardiol. 2009;53(1):91–124.
10) Fatma Aboul-Enein, Majed O. Aljuaid, Hail T. Alharthi, Abdulkarim M. Almudhhi, Mohammad A. Alzahrani. Hindawi Publishing Corporation Cardiology Research and Practice Volume 2016, Article ID 9847575, 6 pages http://dx.doi.org/10.1155/2016/9847575
11) Shelley S, Indirani M, Sathyamurthy I, Subramanian K, Priti N, Harshad K, et al. Correlation of myocardial perfusion SPECT with invasive and computed tomography coronary angiogram. Indian Heart J. 2012;64(1):43–9. doi: 10.1016/S0019-4832(12)60010-8. [PubMed: 22572425].
12) Fard-Esfahani A, Fallahi B, Saghari M, Eftekhari M, Beiki D. Myocar- dial perfusion scan accuracy in detection of coronary artery disease- comparison with exercise stress test [In Persian]. Iran J Nucl Med.  2007;15:16–23.
13) Fiechter M, Ghadri JR, Kuest SM, Pazhenkottil AP, Wolfrum M, Nk- oulou RN, et al. Nuclear myocardial perfusion imaging with a novel cadmium-zinc-telluride detector SPECT/CT device: first vali- dation versus invasive coronary angiography. Eur J Nucl Med Mol Imaging. 2011;38(11):2025–30. doi: 10.1007/s00259-011-1877-y. [PubMed: 21761267].
14) Berman DS, Kang X, Van Train KF, et al. Comparative prognostic value of automatic quantitative analysis versus semiquantitative visual analysis of exercise myocardial perfusion single-photon emission computed tomography. J Am Coll Cardiol. 1998;32:1987–1995.