Abstract
Kinetic analysis is an essential tool of Positron Emission Tomography image analysis. However it requires a pure tissue time activity curve (TAC) in order to calculate the system parameters. Pure tissue TACs are particularly difficult to obtain in the brain as the low resolution of PET means almost all voxels are a mixture of tissues. Factor analysis explicitly accounts for mixing but is an underdetermined problem that can give arbitrary results. A joint factor and kinetic analysis is proposed whereby factor analysis explicitly accounts for mixing of tissues. Hence, more meaningful parameters are obtained by the kinetic models, which also ensure a less ambiguous solution to the factor analysis. The method was tested using a cylindrical phantom and the 18F-DOPA data of a brain cancer patient.
Chapter PDF
Similar content being viewed by others
Keywords
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
References
Barber, D.C.: The use of principal components in the quantiative analysis of gamma camera dynamic studies. Phys. Med. Biol. 25(2), 283–292 (1980)
di Paola, R., Bazin, J.P., Aubry, F., Aurengo, A., Cavailloles, F., Herry, J.Y., Kahn, E.: Handling of dynamic sequences in nuclear medcine. IEEE. T. Nuclear Science NS-29(4), 1310–1321 (1982)
El Fakhri, G., Sitek, A., Guerin, B., Foley Kijewski, M., Di Carli, M.F., Moore, S.C.: Quantitative dynamic cardiac 82rb pet using generalised factor and compartment analyses. J. Nucelar Medicine 46(8), 1264–1271 (2005)
Greene, F.L. (ed.): AJCC Cancer Staging Manual, 6th edn., ch. 47, pp. 387–390. Springer, Heidelberg (2002)
Gunn, R.N., Gunn, S.R., Turkheimer, F.E., Aston, J.A.D., Cunningham, V.J.: Positron emission tomography compartmental models: A basis pursuit strategy for kinetic modeling. J. Cerebral Blood Flow & Metabolism 22, 1425–1439 (2002)
Knight, P.A.: Fast rectangular matrix multiplication and qr decomposition. Linear Algebra and its Applications 221, 69–81 (1995)
Newton, H.B., Jolesz, F.A. (eds.): Handbook of Neuro-Oncology Neuroimaging. Academic Press, London (2007)
Reilhac, A., Batan, G., Michel, C., Grova, C., Tohka, J., Collins, D.L., Costes, N., Evans, A.C.: PET-SORTEO: Validation and development of database of simulated PET volumes. IEEE T. Nuclear Science 52(5), 1321–1328 (2005)
Saad, A., Hamarneh, G., Moller, T., Smith, B.: Kinetic modeling based probabilistic segmentation for molecular images. In: Metaxas, D., Axel, L., Fichtinger, G., Székely, G. (eds.) MICCAI 2008, Part I. LNCS, vol. 5241, pp. 244–252. Springer, Heidelberg (2008)
Schiepers, C., Chen, W., Cloughesy, T., Dahlbom, M., Huang, S.-C.: 18fdopa kinetics and brain tumours. J. Nuclear Medicine 48(10), 1651–1661 (2007)
Schiepers, C., Hoh, C.K., Nuyts, J., Wu, H.M., Phelps, M.E., Dahlbom, M.: Factor analysis in prostate cancer: Delineation of organ structures and automatic generation of in- and output functions. IEEE T. Nuclear Science 49(5), 2338–2343 (2002)
Sitek, A., Di Bella, E.V.R., Gullberg, G.T., Huesman, R.H.: Correction of ambiguous solutions in factor analysis using a penalized least squares objective. IEEE T. Medical Imaging 21(3), 216–225 (2002)
Szczesny, M.: Complexity of initial-value problems for ordinary differential equations of order k. Journal of Complexity 22(4), 514–532 (2006)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2010 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Dowson, N. et al. (2010). Joint Factor and Kinetic Analysis of Dynamic FDOPA PET Scans of Brain Cancer Patients. In: Jiang, T., Navab, N., Pluim, J.P.W., Viergever, M.A. (eds) Medical Image Computing and Computer-Assisted Intervention – MICCAI 2010. MICCAI 2010. Lecture Notes in Computer Science, vol 6362. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-15745-5_23
Download citation
DOI: https://doi.org/10.1007/978-3-642-15745-5_23
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-15744-8
Online ISBN: 978-3-642-15745-5
eBook Packages: Computer ScienceComputer Science (R0)