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Quantification of myocardial blood flow (MBF) and reserve (MFR) incorporated with a novel segmentation approach: Assessments of quantitative precision and the lower limit of normal MBF and MFR in patients

  • ORIGINAL ARTICLE
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Journal of Nuclear Cardiology Aims and scope

Abstract

Background

Quantification of myocardial blood flow (MBF) and myocardial flow reserve (MFR) has shown diagnostic and prognostic values for the assessment of coronary artery disease (CAD). This study aimed to evaluate in patients a highly automatic Yale-MQ (myocardial blood flow quantification) software incorporated with a novel image segmentation approach for quantification of global and regional MBF and MFR from dynamic 82Rb cardiac positron emission tomography (PET).

Methods

Global and regional MBFs and MFRs were quantified in 80 patients (18 normal and 62 CAD subjects) by two different observers using the Yale-MQ software. Lower limits of normal (LLN) values and intra- and inter-observer variabilities of MBFs and MFRs were calculated for the assessment of quantitative precision. The Yale-MQ was compared with a commercially available software (Corridor 4DM) being used as a reference.

Results

The Yale-MQ method provided precise assessments of LLNs of MBF and MFR. The global and regional MBFs and MFR quantified via Yale-MQ were correlated strongly with those via Corridor4DM (R ≥ 0.867). The intra- and inter-observer variabilities of MBFs and MFRs quantified via Yale-MQ were small (≤ 7.7% for MBFs and ≤ 10.0% for MFRs) with excellent correlations (R ≥ 0.980 for MBFs and R ≥ 0.976 for MFRs).

Conclusions

The new Yale-MQ software associated with the automatic processing scheme provides a highly reproducible clinical tool for precise quantification of MBF and MFR in patients with reliable LLN values.

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Abbreviations

CI:

Confidence interval

CV:

Coefficient of variation

ICC:

Intraclass correction coefficient

LLN:

Lower limit of normal

MBF:

Myocardial blood flow

MFR:

Myocardial flow reserve

PVE:

Partial volume effect

SD:

Standard deviation

TAC:

Time-activity curve

TNMF:

Triple-factor non-negative matrix factorization

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Acknowledgements

The authors would like to thank Mrs. Vera Tsatkin, Dr. Maria Salas, and Mrs. Donna McMahon for their assistance in coordination of the PET/CT imaging protocols, and Drs. Tung-Hsin Wu and Jing-Yi Sun for their helpful discussions in the LV image segmentation.

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Authors and Affiliations

  1. Department of Internal Medicine, Yale University School of Medicine, New Haven, CT, USA

    Hui Liu PhD, Stephanie Thorn PhD, Edward J. Miller MD, PhD, Albert J. Sinusas MD & Yi-Hwa Liu PhD

  2. Department of Radiology and Biomedical Imaging, Yale University, New Haven, CT, USA

    Hui Liu PhD, Jing Wu PhD, Edward J. Miller MD, PhD & Albert J. Sinusas MD

  3. Department of Nuclear Cardiology, Heart and Vascular Center, Yale New Haven Hospital, New Haven, CT, USA

    Ramesh Fazzone-Chettiar BS, Veronica Sandoval BS, Edward J. Miller MD, PhD, Albert J. Sinusas MD & Yi-Hwa Liu PhD

  4. Department of Biomedical Engineering, Chung Yuan Christian University, Taoyuan, Taiwan

    Yi-Hwa Liu PhD

Authors
  1. Hui Liu PhD
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Contributions

HL: data collection, software development, data analysis, manuscript preparation. JW and YHL: study design, data analysis, manuscript preparation. ST, AJS, and EJM: patient recruitments, data collection. RFC and VS: data analysis, critical contribution to the manuscript. All authors read and approved the final manuscript.

Corresponding authors

Correspondence to Jing Wu PhD or Yi-Hwa Liu PhD.

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Disclosures

This material was supported by the State of Connecticut under the Connecticut Bioscience Innovation Fund (16-00248, LIU). Its contents are solely the responsibility of the authors and do not necessarily represent the official views of the State of Connecticut or Connecticut Innovations, Inc. No potential conflicts of interest relevant to this work. A grant for creation of a normal PET database (Sinusas) was funded by Invia Medical Imaging Solutions (Ann Arbor, MI).

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Liu, H., Thorn, S., Wu, J. et al. Quantification of myocardial blood flow (MBF) and reserve (MFR) incorporated with a novel segmentation approach: Assessments of quantitative precision and the lower limit of normal MBF and MFR in patients. J. Nucl. Cardiol. 28, 1236–1248 (2021). https://doi.org/10.1007/s12350-020-02278-y

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