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Quantification of Positron Emission Tomography Data Using Simultaneous Estimation of the Input Function: Validation with Venous Blood and Replication of Clinical Studies

  • Elizabeth A. Bartlett
  • Mala Ananth
  • Samantha Rossano
  • Mengru Zhang
  • Jie Yang
  • Shu-fei Lin
  • Nabeel Nabulsi
  • Yiyun Huang
  • Francesca Zanderigo
  • Ramin V. Parsey
  • Christine DeLorenzo
Research Article
  • 17 Downloads

Abstract

Purpose

To determine if one venous blood sample can substitute full arterial sampling in quantitative modeling for multiple positron emission tomography (PET) radiotracers using simultaneous estimation of the input function (SIME).

Procedures

Participants underwent PET imaging with [11C]ABP688, [11C]CUMI-101, and [11C]DASB. Full arterial sampling and additional venous blood draws were performed for quantification with the arterial input function (AIF) and SIME using one arterial or venous (vSIME) sample.

Results

Venous and arterial metabolite-corrected plasma activities were within 6 % of each other at varying time points. vSIME- and AIF-derived outcome measures were in good agreement, with optimal sampling times of 12 min ([11C]ABP688), 90 min ([11C]CUMI-101), and 100 min ([11C]DASB). Simulation-based power analyses revealed that SIME required fewer subjects than the AIF method to achieve statistical power, with significant reductions for [11C]CUMI-101 and [11C]DASB with vSIME. Replication of previous findings and test-retest analyses bolstered the simulation analyses.

Conclusions

We demonstrate the feasibility of AIF recovery using SIME with one venous sample for [11C]ABP688, [11C]CUMI-101, and [11C]DASB. This method simplifies PET acquisition while allowing for fully quantitative modeling, although some variability and bias are present with respect to AIF-based quantification, which may depend on the accuracy of the single venous blood measurement.

Key words

Venous blood Less invasive PET Simultaneous estimation Sample size considerations 

Notes

Acknowledgments

We thank the Center for Understanding Biology using Imaging Technology image analysts at Stony Brook University for their work in image importing, processing, and quality control. We also thank Rajapillai Pillai, PhD, for his contributions to early versions of the paper. We acknowledge the consultation and support provided by the Biostatistical Consulting Core at the Stony Brook University School of Medicine.

Funding.

This study was funded by the National Institute of Mental Health awards: K01MH091354 (PI: Christine DeLorenzo, PhD), R01MH104512 (PI: Christine DeLorenzo, PhD), and R01MH090276 (PI: Ramin V Parsey, MD, PhD).

Compliance with Ethical Standards

Conflict of Interest

The authors declare that they have no conflict of interest.

Ethical Approval

All procedures performed were in accordance with the ethical standards of the institutional committee and with the 1964 Helsinki Declaration and its later amendments.

Informed Consent

Informed consent was obtained from all individual participants included in the study.

Supplementary material

11307_2018_1300_MOESM1_ESM.pdf (338 kb)
ESM 1 (PDF 338 kb)

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Copyright information

© World Molecular Imaging Society 2018

Authors and Affiliations

  • Elizabeth A. Bartlett
    • 1
  • Mala Ananth
    • 2
  • Samantha Rossano
    • 3
  • Mengru Zhang
    • 4
  • Jie Yang
    • 5
  • Shu-fei Lin
    • 6
  • Nabeel Nabulsi
    • 6
  • Yiyun Huang
    • 6
  • Francesca Zanderigo
    • 7
    • 8
  • Ramin V. Parsey
    • 1
    • 9
  • Christine DeLorenzo
    • 1
    • 9
  1. 1.Department of Biomedical EngineeringStony Brook UniversityStony BrookUSA
  2. 2.Department of NeuroscienceStony Brook UniversityStony BrookUSA
  3. 3.Department of Biomedical EngineeringYale UniversityNew HavenUSA
  4. 4.Department of Applied Mathematics and StatisticsStony Brook UniversityStony BrookUSA
  5. 5.Department of Family, Population, and Preventive MedicineStony Brook UniversityStony BrookUSA
  6. 6.Department of Radiology & Biomedical ImagingYale UniversityNew HavenUSA
  7. 7.Department of PsychiatryColumbia UniversityNew YorkUSA
  8. 8.Molecular Imaging and Neuropathology DivisionNew York State Psychiatric InstituteNew YorkUSA
  9. 9.Department of PsychiatryStony Brook UniversityStony BrookUSA

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