Kinetic analysis of dynamic positron emission tomography data using open-source image processing and statistical inference tools

Wiley Interdisciplinary Reviews: Computational Statistics

Volumn 4, Issue 3, 2012, Pages 316-322

  Hawe, David ^a   Fernández, Francisco R Hernández ^a   O'Suilleabháin, Liam ^a   Huang, Jian ^a   Wolsztynski, Eric ^a   O'Sullivan, Finbarr ^a  

^a UNIVERSITY COLLEGE CORK   (Ireland)

Author keywords

Compartment modeling; Image analysis; Medical imaging; Nonlinear regression; Nonparametric methods; Positron emission tomography

Indexed keywords

BLOOD PERFUSION; COMPARTMENTAL MODEL; COMPUTATIONAL STATISTICS; DIAGNOSTIC IMAGING; DYNAMIC MODES; F-FLUORODEOXYGLUCOSE; FUNCTIONALS; GLUCOSE METABOLISM; KINETIC ANALYSIS; LIFE-TIMES; LINEAR CONVOLUTION; LIVING TISSUES; MEASURED SIGNALS; MODEL INFERENCE; NON-LINEAR REGRESSION; NONPARAMETRIC APPROACHES; NONPARAMETRIC METHODS; OPEN SOURCE TOOLS; OPEN-SOURCE; PATHOLOGICAL TISSUE; PET DATA; PET SCAN; PIECEWISE LINEAR; RESIDUE FUNCTIONS; SPATIAL ASPECT; STATISTICAL ASSESSMENT; STATISTICAL INFERENCE TOOLS; TEMPORAL ASPECTS; TISSUE RESIDUE; TRANSIT TIME;

AMIDES; GLUCOSE; IMAGE ANALYSIS; IMAGE PROCESSING; MEDICAL IMAGING; PIECEWISE LINEAR TECHNIQUES; POSITRON EMISSION TOMOGRAPHY; TISSUE;

DATA FLOW ANALYSIS;

EID: 84867141432     PISSN: 19395108     EISSN: 19390068     Source Type: Journal    
DOI: 10.1002/wics.1196     Document Type: Article

References (21)

1. Natterer F, Wubbeling F. Mathematical methods in image reconstruction. SIAM Monographs on Mathematical Modeling and Computation, 2001.
2. Vardi Y, Shepp LA, Kaufman L. A statistical model for positron emission tomography. J Am Stat Assoc 1985, 80:8-20.
3. O'Sullivan F, Muzi M, Spence AM, Mankoff DM, O'Sullivan JN, Fitzgerald N, Newman GC, Krohn KA. Nonparametric residue analysis of dynamic PET data with application to cerebral FDG studies in normals. J Am Stat Assoc 2009, 104:556-571.
4. Bassingthwaighte JB, Raymond GM, Butterworth E, Alessio A, Caldwell JH. Multiscale modeling ofmetabolism, flows, and exchanges in heterogeneous organs. Ann N Y Acad Sci 2010, 188:111-120.
5. Zaidi H. Quantitative Analysis in Nuclear Medicine Imaging. New York: Springer; 2006. ISBN 0 387238549.
6. Kety SS, Schmidt CF. The nitrous oxide method for the quantitative determination of cerebral blood flow in man; theory, procedure and normal values. J Clin Invest 1948, 27:476-483.
7. Sokoloff L, Reivich M, Kennedy C, Des Rosiers MH, Patlak CS, Pettigrew KD, Sakurada O, Shinohara M. The [14C] deoxyglucose method for the measurement of local cerebral glucose utilization: theory, procedure, and normal values in the conscious and anesthetized albino rat. J Neurochem 1977, 28:897-916.
8. Phelps ME, Huang SC, Hoffman EJ, Selin C, Sokoloff L, Kuhl DE. Tomographic measurement of local cerebral glucose metabolic rate in humans with (F-18)2-fluoro-2-deoxy-d-glucose: validation of method. Ann Neurol 1979, 6:371-388.
9. Carson RE, Yan Y, Daube-Witherspoon ME, Freedman N, Bacharach SL, Herscovitch P. An approximation formula for the variance of PET region of-interest values. IEEE Trans Med Imaging 1993, 12:240-250.
10. Maitra R, O'Sullivan F. Variability assessment in PET and related generalized deconvolution models. J Am Stat Assoc 1998, 93:1340-1355.
11. O'Sullivan F. Locally constrained mixture representation of dynamic imaging data from PET andMRstudies. Biostatistics 2006, 7:318-338.
12. R Development Core Team. R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria, 2010. Available at: http://www.R-project.org. (Accessed October 1, 2010).
13. Gromping U. Inferencewith linear equality and inequality constraints using R: The package ic.infer. J Stat Soft 2010, 33:1-31.
14. Efron B, Tibshirani RJ. Introduction to the bootstrap. Chapman and Hall CRC Monographs on Statistics and Applied Probability, Vol 57, 1994.
15. Cox D, Koh E, Wahba G, Yandell BS. Testing the (parametric) null model hypothesis in (semiparametric) partial and generalized spline models. Ann Stat 1988, 16:113-119.
16. Wahba G. Spline models for observational data. CBMSNSF Regional Conference Series in Applied Mathematics, SIAM 59, Philadelphia, PA; 1990.
17. Muzi M, Mankoff DA, Link JM, Shoner S, Collier AC, Sasongko L, Unadkat JD. Imaging of cyclosporine inhibition of p-glycoprotein activity using 11C-Verapamil in the brain: studies of healthy humans. J Nucl Med 2009, 50:1267-1275.
18. Spence AM, Muzi M, Graham MM, O'Sullivan F, Krohn KA, Link JM, Lewellen TK, Lewellen B, Freeman SD, Berger MS, et al. Glucose metabolism in human malignant gliomas measured quantitatively with PET, 1[C-11]glucose and FDG: analysis of the FDG lumped constant. J Nucl Med 1998, 39:440-448.
19. Loening AM, Gambhir SS. AMIDE: a free software tool for multimodality medical image analysis. Mol Imaging 2003, 2:131-137.
20. Meier P, Zierler KL. On the theory of the indicatordilution method for measurement of blood flow and volume. J Appl Physiol 1954, 6:731-744.
21. Gunn RN, Gunn SR, Turkheimer FE, Aston JA, Cunningham VJ. Positron emission tomography compartmental models: a basis pursuit strategy for kinetic modeling. J Cereb Blood Flow Metab 2002, 22:1425-1439.