Molecular Imaging and Biology

, Volume 15, Issue 5, pp 569–575 | Cite as

Impact of a Multiple Mice Holder on Quantitation of High-Throughput MicroPET Imaging With and Without Ct Attenuation Correction

  • Frezghi HabteEmail author
  • Gang Ren
  • Timothy C. Doyle
  • Hongguang Liu
  • Zhen Cheng
  • David S. Paik
Research Article



The aim of this study is to evaluate the impact of scanning multiple mice simultaneously on image quantitation, relative to single mouse scans on both a micro-positron emission tomography/computed tomography (microPET/CT) scanner (which utilizes CT-based attenuation correction to the PET reconstruction) and a dedicated microPET scanner using an inexpensive mouse holder “hotel.”


We developed a simple mouse holder made from common laboratory items that allows scanning multiple mice simultaneously. It is also compatible with different imaging modalities to allow multiple mice and multi-modality imaging. For this study, we used a radiotracer (64Cu-GB170) with a relatively long half-life (12.7 h), selected to allow scanning at times after tracer uptake reaches steady state. This also reduces the effect of decay between sequential imaging studies, although the standard decay corrections were performed. The imaging was also performed using a common tracer, 2-deoxy-2-[18 F]fluoro-d-glucose (FDG), although the faster decay and faster pharmacokinetics of FDG may introduce greater biological variations due to differences in injection-to-scan timing. We first scanned cylindrical mouse phantoms (50 ml tubes) both in a groups of four at a time (multiple mice mode) and then individually (single mouse mode), using microPET/CT and microPET scanners to validate the process. Then, we imaged a first set of four mice with subcutaneous tumors (C2C12Ras) in both single- and multiple-mice imaging modes. Later, a second set of four normal mice were injected with FDG and scanned 1 h post-injection. Immediately after completion of the scans, ex vivo biodistribution studies were performed on all animals to provide a “gold-standard” to compare quantitative values obtained from PET. A semi-automatic threshold-based region of interest tool was used to minimize operator variability during image analysis.


Phantom studies showed less than 4.5 % relative error difference between the single- and multiple-mice imaging modes of PET imaging with CT-based attenuation correction and 18.4 % without CT-based attenuation correction. In vivo animal studies (n = 4) showed <5 % (for 64Cu, p > 0.686) and <15 % (for FDG, p > 0.4 except for brain image data p = 0.029) relative mean difference with respect to percent injected dose per gram (%ID/gram) between the single- and multiple-mice microPET imaging mode when CT-based attenuation correction is performed. Without CT-based attenuation correction, we observed relative mean differences of about 11 % for 64Cu and 15 % for FDG.


Our results confirmed the potential use of a microPET/CT scanner for multiple mice simultaneous imaging without significant sacrifice in quantitative accuracy as well as in image quality. Thus, the use of the mouse “hotel” is an aid to increasing instrument throughput on small animal scanners with minimal loss of quantitative accuracy.

Key words

Image quantitation MicroPET Attenuation correction High throughput Imaging Biodistribution 



The authors acknowledge the use of imaging instruments and image analysis support in the Stanford Imaging Facility. This work was supported by grants NCI P50 CA114747 and NIH U54 CA119367 and by the Stanford Cancer Center.

Conflict of Interest

No other potential conflict of interest relevant to this article exists.


  1. 1.
    Henkelman M (2010) Systems biology through mouse imaging centers: experience and new directions. Ann Rev Biomed Eng 12:143–166CrossRefGoogle Scholar
  2. 2.
    Agdeppa ED, Spilker ME (2009) A review of imaging agent development. The AAPS Journal 11:286–299PubMedCrossRefGoogle Scholar
  3. 3.
    Hargreaves RJ (2008) The role of molecular imaging in drug discovery and development. Clin Pharmacol Ther 83:349–353PubMedCrossRefGoogle Scholar
  4. 4.
    Ahn BC (2011) Applications of molecular imaging in drug discovery and development process. Curr Pharm Biotechnol 12:459–468PubMedCrossRefGoogle Scholar
  5. 5.
    Medarova Z, Pham W, Kim Y, Dai G, Moore A (2006) In vivo imaging of tumor response to therapy using a dual-modality imaging strategy. Int J Cancer 118:2796–2802PubMedCrossRefGoogle Scholar
  6. 6.
    Michalski MH, Chen X (2011) Molecular imaging in cancer treatment. Eur J Nucl Med Mol Imaging 38:358–377PubMedCrossRefGoogle Scholar
  7. 7.
    Pike LS, Tannous BA, Deliolanis NC et al (2011) Imaging gene delivery in a mouse model of congenital neuronal ceroid lipofuscinosis. Gene Ther 18:1173–1178PubMedCrossRefGoogle Scholar
  8. 8.
    Yong J, Rasooly J, Dang H et al (2011) Multimodality imaging of B-cells in mouse models of type I and II diabetes. Diabetes 60:1383–1392PubMedCrossRefGoogle Scholar
  9. 9.
    Lyons S (2005) Advances in imaging mouse tumour models in vivo. Journal of Pathology 205:194–205PubMedCrossRefGoogle Scholar
  10. 10.
    Golestani R, Wu C, Tio RA et al (2010) Small-animal SPECT and SPECT/CT: application in cardiovascular research. Eur J Nucl Med Mol Imaging 37:1766–1777PubMedCrossRefGoogle Scholar
  11. 11.
    Roncali E, Cherry SR (2011) Application of silicon photomultipliers to positron emission tomography. Annals of Biomedical Engineering 39:1358–1377PubMedCrossRefGoogle Scholar
  12. 12.
    Hamilton CS, Ma Y, Smith SD, Benveniste H (2007) High resolution 3D in vivo mouse brain imaging at 9.4 T bruker MRI systemBioengineering Conference, 2007 NEBC '07 IEEE 33rd Annual Northeast, pp. 45-46.Google Scholar
  13. 13.
    Hong H, Yang Y, Cai W (2011) Imaging gene expression in live cells and tissues. Cold Spring Harbor Protoc: 354-365.Google Scholar
  14. 14.
    Kluanberg BA, Davis JA (2008) Considerations for laboratory animal imaging center design and setup. ILAR J 49:4–16CrossRefGoogle Scholar
  15. 15.
    Pauux AL, Ong LC, Teh I, et. al. (2011) Comparison of imaging techniques to monitor tumor growth and cancer progression in living animals. Int J Mol Imaging doi: 10.1155/2011/321538 .
  16. 16.
    Chen TE, Yoder KK, Normandin MD et al (2009) A rat head holder for simultaneous scanning of two rats in small animal PET scanners: design, construction, feasibility testing and kinetic validation. J Neurosci Methods 176:24–33CrossRefGoogle Scholar
  17. 17.
    Bock NA, Konyer NB, Henkelman RM (2003) Multiple-mouse MRI. Magnetic Resonance Med 49:158–167CrossRefGoogle Scholar
  18. 18.
    Dazai J, Spring S, Cahill LS, Henkelman RM (2011) Multiple-mouse neuroanatomical magnetic resonance imaging. J Vis Exp: e2497.Google Scholar
  19. 19.
    Siepel FJ, Van Lier MGJTB, Chen M et al (2010) Scanning multiple mice in a small-animal PET scanner: influence on image quality. Nuclear Instruments and Methods in Physics Research A 621:605–610CrossRefGoogle Scholar
  20. 20.
    Disselhorst JA, Boerman OC, Oyen WJG, Slump CH, Visser EP (2010) Spatial resolution of the Inveon small-animal PET scanner for the entire field of view. Nuclear Instruments and Methods in Physics Research A 615:245–248CrossRefGoogle Scholar
  21. 21.
    Aide N, Cd D, Ml B, Meryet-Figuiere M, Poulain L (2010) High-throughput small animal PET imaging in cancer research: evaluation of the capability of the Inveon scanner to image four mice simultaneously. Nuclear Medicine Communications 31:851–858PubMedGoogle Scholar
  22. 22.
    Sheruma N, Peter LK, Wencke L, Steven R M (2006) Maximizing the useful field of view of the microPET: feasibility of imaging large animals, IEEE Nuclear Science Symposium Conference Record 1853-1856Google Scholar
  23. 23.
    Aide N, Visser P, Lheureux S, Heutte N, Szanda I, Hicks R (2012) The motivations and methodology for high-throughput PET imaging of small animals in cancer research. Eur J Nucl Med Imaging 30:1497–1509CrossRefGoogle Scholar
  24. 24.
    Ren G, Blum G, Verdoes M et al (2011) Non-invasive imaging of cysteine cathepsin activity in solid tumors using a 64Cu-labeled activity-based probe. PLoS ONE 6:e28029PubMedCrossRefGoogle Scholar
  25. 25.
    Srinivas M, Dhurairaj T, Basu S, Bural G, Surti S, Alavi A (2009) A recovery coefficient method for partial volume correction of PET images. Ann Nucl Med 23:341–348PubMedCrossRefGoogle Scholar

Copyright information

© World Molecular Imaging Society 2013

Authors and Affiliations

  • Frezghi Habte
    • 1
    • 2
    Email author
  • Gang Ren
    • 1
    • 2
    • 4
  • Timothy C. Doyle
    • 1
    • 3
  • Hongguang Liu
    • 1
    • 2
  • Zhen Cheng
    • 1
    • 2
  • David S. Paik
    • 1
    • 2
  1. 1.Molecular Imaging Program at Stanford (MIPS)StanfordUSA
  2. 2.Department of RadiologyStanfordUSA
  3. 3.Department of PediatricsStanford UniversityStanfordUSA
  4. 4.CellSight TechnologiesSan FranciscoUSA

Personalised recommendations