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Optimization of reconstruction and quantification of motion-corrected coronary PET-CT

  • Mhairi K. Doris
  • Yuka Otaki
  • Sandeep K. Krishnan
  • Jacek Kwiecinski
  • Mathieu Rubeaux
  • Adam Alessio
  • Tinsu Pan
  • Sebastien Cadet
  • Damini Dey
  • Marc R. Dweck
  • David E. Newby
  • Daniel S. Berman
  • Piotr J. Slomka
Original Article
  • 144 Downloads

Abstract

Background

Coronary PET shows promise in the detection of high-risk atherosclerosis, but there remains a need to optimize imaging and reconstruction techniques. We investigated the impact of reconstruction parameters and cardiac motion-correction in 18F Sodium Fluoride (18F-NaF) PET.

Methods

Twenty-two patients underwent 18F-NaF PET within 22 days of an acute coronary syndrome. Optimal reconstruction parameters were determined in a subgroup of six patients. Motion-correction was performed on ECG-gated data of all patients with optimal reconstruction. Tracer uptake was quantified in culprit and reference lesions by computing signal-to-noise ratio (SNR) in diastolic, summed, and motion-corrected images.

Results

Reconstruction using 24 subsets, 4 iterations, point-spread-function modelling, time of flight, and 5-mm post-filtering provided the highest median SNR (31.5) compared to 4 iterations 0-mm (22.5), 8 iterations 0-mm (21.1), and 8 iterations 5-mm (25.6; all P < .05). Motion-correction improved SNR of culprit lesions (n = 33) (24.5[19.9-31.5]) compared to diastolic (15.7[12.4-18.1]; P < .001) and summed data (22.1[18.9-29.2]; P < .001). Motion-correction increased the SNR difference between culprit and reference lesions (10.9[6.3-12.6]) compared to diastolic (6.2[3.6-10.3]; P = .001) and summed data (7.1 [4.8-11.6]; P = .001).

Conclusions

The number of iterations and extent of post-filtering has marked effects on coronary 18F-NaF PET quantification. Cardiac motion-correction improves discrimination between culprit and reference lesions.

Keywords

Atherosclerosis Positron emission tomography Cardiac motion Computed tomography 

Abbreviations

PET

Positron emission tomography

CT

Computed tomography

ACS

Acute coronary syndrome

CTA

Computed tomography angiography

ECG

Electrocardiograph

SNR

Signal-to-noise ratio

TBR

Tissue-to-background ratio

SUV

Standardized uptake value

Notes

Disclosure

No other potential conflict of interest relevant to this article was reported.

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Copyright information

© American Society of Nuclear Cardiology 2018

Authors and Affiliations

  • Mhairi K. Doris
    • 1
    • 2
  • Yuka Otaki
    • 2
  • Sandeep K. Krishnan
    • 2
  • Jacek Kwiecinski
    • 1
    • 2
  • Mathieu Rubeaux
    • 2
  • Adam Alessio
    • 3
  • Tinsu Pan
    • 4
  • Sebastien Cadet
    • 2
  • Damini Dey
    • 2
  • Marc R. Dweck
    • 1
  • David E. Newby
    • 1
  • Daniel S. Berman
    • 2
  • Piotr J. Slomka
    • 2
    • 5
  1. 1.BHF Centre for Cardiovascular Science, Clinical Research Imaging Centre, Edinburgh Heart CentreUniversity of EdinburghEdinburghUK
  2. 2.Department of Imaging and Medicine and Biomedical SciencesCedars-Sinai Medical CenterLos AngelesUSA
  3. 3.Department of RadiologyUniversity of WashingtonSeattleUSA
  4. 4.Department of Imaging Physics, MD Anderson Cancer CenterThe University of TexasHoustonUSA
  5. 5.Artificial Intelligence in Medicine ProgramLos AngelesUSA

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