Volume 1 Supplement 1

Proceedings of the 3rd PSMR Conference on PET/MR and SPECT/MR

Open Access

Combining MRI with PET for partial volume correction improves image-derived input functions in mice

  • Eleanor Evans1,
  • Guido Buonincontri1,
  • David Izquierdo2,
  • Carmen Methner3,
  • Rob C Hawkes1,
  • Richard E Ansorge4,
  • Thomas Kreig3,
  • T Adrian Carpenter1 and
  • Stephen J Sawiak1, 5
EJNMMI Physics20141(Suppl 1):A84

https://doi.org/10.1186/2197-7364-1-S1-A84

Published: 29 July 2014

Kinetic modelling in PET requires the arterial input function (AIF), defined as the time-activity curve (TAC) in plasma. This measure is challenging to obtain in mice due to low blood volumes, resulting in a reliance on image-based methods for AIF derivation. We present a comparison of PET- and MR-based region-of-interest (ROI) analysis to obtain image-derived AIFs from the left ventricle (LV) of a mouse model. ROI-based partial volume correction (PVC) was performed to improve quantification.

MRI and dynamic PET images were obtained from a recent study investigating treatment effects in 12 mice following myocardial infarction [1], where half the mice received a new treatment and half did not. Prospectively gated MRI (4.7T Bruker BioSpec, FLASH TR/TE 400/3ms, spatial resolution 140μm in 1mm slices) were acquired prior to PET acquisition (approx. 25MBq 18F-FDG bolus, 45 minute emission listmode acquisition reconstructed with 3DRP in four cardiac frames) on a split-magnet PET camera [2]. Images were co-registered using SPMMouse [3] (see Figure 1).
Figure 1

Mouse heart MR (left) and fused with 18F-FDG static PET (right). Arrow indicates infarcted region.

AIF extraction AIFs were obtained by taking mean time courses from LV Lumen ROIs, shown in Figure 2. The regional geometric transfer matrix (GTM) method was applied for PVC [4], using ROIs drawn on either the co-registered MR images or directly onto the last dynamic frame PET images. ROIs covered LV lumen, myocardium, lungs/body and background. Patlak [5] analysis was performed to evaluate glucose metabolism.
Figure 2

AIFs and TACs derived for single subject using (A) MR ROIs, (B) PET ROIs with PVC and (C) MR ROIs with PVC. Insets detail first 500s

Uncorrected AIFs and myocardial TACs produced by manual ROI delineation displayed contamination with myocardial signal. AIFs and myocardial curves became distinguishable if GTM PVC was applied. Only MR-based PVC produced significant differences (p<0.05) in Ki values between the treated and untreated groups (see Table 1).

Table 1

 

Glucose metabolism K i (ml/min/cm3), Mean ± SD

 

Without PVC

With PVC

Group

PET ROIs

MR ROIs

PET ROIs

MR ROIs

Untreated

0.03 ± 0.01

0.03 ± 0.01

0.4 ± 0.3

0.6 ± 0.2*

Treated

0.03 ± 0.01

0.03 ± 0.02

0.2 ± 0.3

0.2 ± 0.2*

GTM-based PVC gives best results in mice when ROIs are based on MRI data, due to its high-resolution and excellent soft-tissue contrast.

Authors’ Affiliations

(1)
Wolfson Brain Imaging Centre, University of Cambridge
(2)
Athinoula A Martinos Centre, Harvard University
(3)
Department of Medicine, University of Cambridge
(4)
Department of Physics, University of Cambridge
(5)
Behavioural and Clinical Neurosciences Institute, University of Cambridge

References

  1. Methner C, et al.: Riociguat Reduces Infarct Size and Post-Infarct Heart Failure in Mouse Hearts: Insights from MRI/PET Imaging. PloS One 2013,8(12):e83910. DOI: 10.1371/journal.pone.0083910 10.1371/journal.pone.0083910PubMed CentralPubMedView ArticleGoogle Scholar
  2. Lucas AJ, et al.: Development of a combined microPET®-MR system. IEEE Nucl Sci Symp Record 2006, 4: 2345–8. 10.1109/NSSMIC.2006.354384Google Scholar
  3. Sawiak SJ, et al.: MRI reveals brain asymmetry following 6-OHDA lesions in the mouse brain. Proc. ISMRM 2009, 17: 1077. [http://cds.ismrm.org/protected/09MProceedings/files/01077.pdf]Google Scholar
  4. Rousset OG, et al.: Correction for partial volume effects in PET: principle and validation. J Nucl Med 1998,39(5):904–911.PubMedGoogle Scholar
  5. Patlak CS, et al.: Graphical evaluation of blood-to-brain transfer constants from multiple-time uptake data. J Cereb Blood Flow Metab 1983,3(1):1–7. 10.1038/jcbfm.1983.1PubMedView ArticleGoogle Scholar

Copyright

© Evans et al; licensee Springer 2014

This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.