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Meeting ReportClinical Science

Myocardial Energy Estimated by PET Strain and Myocardial Flow Reserve: New Strategy for Coronary Artery Disease

Atsushi Yamamoto, Michinobu Nagao, Masateru Kawakubo, Kiyoe Ando, Risako Nakao, Yuka Matsuo, Akiko Sakai, Mitsuru Momose, Koichiro Kaneko, Kenji Fukushima, Nobuhisa Hagiwara and Shuji Sakai
Journal of Nuclear Medicine August 2022, 63 (supplement 2) 3354;
Atsushi Yamamoto
1Department of Diagnostic Imaging & Nuclear Medicine, Tokyo Women’s Medical University
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Michinobu Nagao
1Department of Diagnostic Imaging & Nuclear Medicine, Tokyo Women’s Medical University
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Masateru Kawakubo
2Kyushu University
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Kiyoe Ando
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Risako Nakao
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Yuka Matsuo
1Department of Diagnostic Imaging & Nuclear Medicine, Tokyo Women’s Medical University
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Akiko Sakai
3Department of Cardiology, Tokyo Women’s Medical University
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Mitsuru Momose
4Momose Clinic
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Koichiro Kaneko
5Tokyo Women's Medical University Hospital
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Kenji Fukushima
6Fukushima Medical Univesity
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Nobuhisa Hagiwara
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Shuji Sakai
1Department of Diagnostic Imaging & Nuclear Medicine, Tokyo Women’s Medical University
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Abstract

3354

Introduction: Myocardial flow reserve (MFR), which is quantitatively measured by 13N-ammonia positron emission tomography (NH3-PET), can predict the prognosis of patients with various heart diseases. We have applied feature-tracking technique to NH3-PET and developed the world's first PET-dedicated cardiac function analysis algorithm that can measure regional myocardial strain ratio (MSR) of stress to rest MS. PET-derived MSR and MFR are considered as independent vectors and we propose their sum as myocardial energy (ME). Present study aimed to investigate the potential of ME as prognostic factors in ischemic heart disease (IHD).

Methods: Between January 2017 to January 2019, 263 consecutive patients who underwent resting/ stressed myocardial NH3-PET because of known or suspected coronary artery disease at a single center were enrolled. In this study, we included patients with coronary artery stenosis of more than 50%, diagnosed by coronary computed tomography angiography, from this cohort. Among them, congenital heart disease, a transplanted heart or adenosine ineffectiveness were excluded.

MSR was defined as the ratio of strains at stress and rest, and ME was calculated from the following equation.

The endpoint was major adverse cardiac events (MACEs) comprising all-cause death, acute coronary syndrome, hospitalization due to heart failure, revascularization, and cerebrovascular disease. The ability to predict MACE was assessed using the receiver-operating characteristic (ROC) analysis. The predictability of ME was analyzed using Kaplan–Meier analysis. The Cox proportional hazards regression model was used to calculate hazard ratios (HR) with 95% confidence intervals (CI).

Results: Consecutive 95 patients were prospectively analyzed. The ROC curve analysis demonstrated a cutoff of 2.29 for MACE with ME (sensitivity and specificity of 83% and 60%). Patients with ME <2.29 had a significantly higher MACE rate than those with ME ≥2.29 (p=0.0016). The Cox proportional hazards regression analysis indicated that ME was an independent marker that could predict MACE in imaging parameters (HR: 24.2, 95% CI: 1.66–353, p=0.020).

Conclusions: ME helped identify patients at higher risk of MACE, and it may be a new index for risk stratification in IHD.

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Journal of Nuclear Medicine
Vol. 63, Issue supplement 2
August 1, 2022
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Myocardial Energy Estimated by PET Strain and Myocardial Flow Reserve: New Strategy for Coronary Artery Disease
Atsushi Yamamoto, Michinobu Nagao, Masateru Kawakubo, Kiyoe Ando, Risako Nakao, Yuka Matsuo, Akiko Sakai, Mitsuru Momose, Koichiro Kaneko, Kenji Fukushima, Nobuhisa Hagiwara, Shuji Sakai
Journal of Nuclear Medicine Aug 2022, 63 (supplement 2) 3354;

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Myocardial Energy Estimated by PET Strain and Myocardial Flow Reserve: New Strategy for Coronary Artery Disease
Atsushi Yamamoto, Michinobu Nagao, Masateru Kawakubo, Kiyoe Ando, Risako Nakao, Yuka Matsuo, Akiko Sakai, Mitsuru Momose, Koichiro Kaneko, Kenji Fukushima, Nobuhisa Hagiwara, Shuji Sakai
Journal of Nuclear Medicine Aug 2022, 63 (supplement 2) 3354;
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