Principal component analysis with pre-normalization improves the signal-to-noise ratio and image quality in positron emission tomography studies of amyloid deposits in Alzheimer's disease

Physics in Medicine and Biology

Volumn 54, Issue 11, 2009, Pages 3595-3612

  Razifar, Pasha ^a,b   Engler, Henry ^c,d   Blomquist, Gunnar ^c   Ringheim, Anna ^b   Estrada, Sergio ^b   Lngström, Bengt ^c   Bergström, Mats ^c  

^a GE HEALTHCARE   (United States)

^b BIACORE AB   (Sweden)

^c UPPSALA UNIVERSITY   (Sweden)

^d University Hospital   (Uruguay)

Author keywords

[No Author keywords available]

Indexed keywords

ALZHEIMER'S DISEASE; AMYLOID DEPOSITS; BENZOTHIAZOLES; BRAIN REGIONS; CLINICAL TOOLS; CORTICAL STRUCTURES; DATA SETS; DIFFERENTIAL DIAGNOSIS; DYNAMIC PET; ENHANCED CONTRAST; IMAGING AGENT; KINETIC BEHAVIOR; KINETIC MODELING; KINETIC MODELS; NEGATIVE VALUES; NEW APPROACHES; NOISE LEVELS; ON DYNAMICS; PARAMETRIC IMAGE; SIGNAL TO NOISE; WHITE MATTER;

ACOUSTIC INTENSITY; DIAGNOSIS; GLYCOPROTEINS; IMAGE QUALITY; POSITRONS; PRINCIPAL COMPONENT ANALYSIS; SIGNAL TO NOISE RATIO;

POSITRON EMISSION TOMOGRAPHY;

2 (4' METHYLAMINOPHENYL) 6 HYDROXY BENZOTHIAZOLE; AMYLOID BETA PROTEIN; CARBON 11; TRACER; UNCLASSIFIED DRUG; BENZOTHIAZOLE DERIVATIVE; N METHYL 2 (4' METHYLAMINOPHENYL) 6 HYDROXYBENZOTHIAZOLE; N-METHYL-2-(4'-METHYLAMINOPHENYL)-6-HYDROXYBENZOTHIAZOLE;

ALZHEIMER DISEASE; ARTICLE; BRAIN REGION; CEREBELLUM CORTEX; CLINICAL ARTICLE; CONTROLLED STUDY; HUMAN; IMAGE QUALITY; POSITRON EMISSION TOMOGRAPHY; PRINCIPAL COMPONENT ANALYSIS; PRIORITY JOURNAL; SIGNAL NOISE RATIO; WHITE MATTER; ALGORITHM; BRAIN; IMAGE ENHANCEMENT; IMAGE PROCESSING; KINETICS; METABOLISM; METHODOLOGY; SCINTISCANNING;

ALGORITHMS; ALZHEIMER DISEASE; AMYLOID BETA-PROTEIN; BENZOTHIAZOLES; BRAIN; HUMANS; IMAGE ENHANCEMENT; IMAGE PROCESSING, COMPUTER-ASSISTED; KINETICS; POSITRON-EMISSION TOMOGRAPHY; PRINCIPAL COMPONENT ANALYSIS;

EID: 69249215513     PISSN: 00319155     EISSN: 13616560     Source Type: Journal    
DOI: 10.1088/0031-9155/54/11/021     Document Type: Article

References (38)

1. Andersen A H, Gash D M and Avison M J 1999 Principal component analysis of the dynamic response measured by fMRI: a generalized linear systems framework Magn. Reson. Imaging 17 795-815
2. Andersson J L and Thurfjell L 1997 Implementation and validation of a fully automatic system for intra- and inter individual registration of PET brain scans J. Comput. Assist. Tomogr. 21 136-44
3. Bergström M, Kumlien E, Lilja A, Trefors N, Westerberg G and Lngström B 1998 Temporal lobe epilepsy visualized with PET with 11 C-L-deuterium-deprenyl-analysis of kinetic data Acta. Neurol. Scand. 98 224-31
4. Bertoldo A, Sparacino Gand and Cobelli C 2004 Population, approach improves parameter estimation of kinetic models from dynamic PET data IEEE Trans. Med. Imaging 23 297-306
5. Blomquist G, Hinz R, Engler H, Ringheim A and Lngström B 2005 Analysis of PIB uptake in AD patients and controls using reference tissue methods Eur. J. Nucl. Med. Mol. Imaging 32 (Sup 1) 262
6. Blomqvist G 1984 On the construction of functional maps in positron emission tomography J. Cereb. Blood. Flow. Metab. 4 629-32
7. Cohen J 1998 Statistical Power Analysis for the Behavioral Sciences 2nd ed (Hillsdale, NJ: Lawrence Earlbaum Associates)
8. Cunningham V J and Jones T 1993 Spectral analysis of dynamic PET studies J. Cereb. Blood. Flow. Metab. 13 15-23
9. Engler H 2003 Multitracer study with positron emission tomography in Creutzfeldt-Jakob disease Eur. J. Nucl. Med. 30 85-95 (Pubitemid 36692897)
10. Esbensen K and Geladi P 1989 Strategy of multivariate image analysis (MIA) Chemometr. Intell. Lab. Syst. 7 67-86
11. Famili A, Shen W M, Weber R and Simoudis E 1997 Data preprocessing and intelligent data analysis Intell. Data. Anal. 1 1-19
12. Friston K J, Frith C D, Liddle P F and Frackowiak R S J 1993 Functional connectivity: the principal-component analysis of large (PET) data sets J. Cereb. Blood. Flow. Metabol. 13 5-14
13. Friston K, Phillips J, Chawla D and Buchel C 1999 Revealing interactions among brain systems with nonlinear PCA Hum. Brain. Mapp. 8 92-7
14. Friston K J, Poline J B, Holmes A P, Frith C D and Frackowiak R S J 1996 A multivariate analysis of PET activation studies Hum. Brain. Mapp. 4 140-51
15. Gefvert O, Lindstrom L H, Waters N, Waters S, Carlsson A and Tedroff J 2003 Different corticostriatal patterns of L-DOPA utilization in patients with untreated schizophrenia and patients treated with classical antipsychotics or clozapine Scand. J. Psychol. 44 289-92
16. Hansen L K et al 1999 Generalizable patterns in neuroimaging: how many principal components? NeuroImage 9 534-44
17. Johnson R A D and Wichern W 1988 Applied Multivariate Statistical Analysis 2nd ed (Englewoods Cliff, NJ: Prentice-Hall)
18. Joliffe I T 2002 Principal Component Analysis 2nd ed (New York: Springer)
19. Kalukin A R, Van Geet M and Swennen R 2000 Principal components analysis of multienergy x-ray computed tomography of mineral samples IEEE Trans. Nucl. Sci. 47 1729-36
20. Klunk W E et al 2004 Imaging brain amyloid in Alzheimer's disease with Pittsburgh compound-B Ann. Neurol. 55 306-19
21. Logan J 2000 Graphical analysis of PET data applied to reversible and irreversible tracers Nucl. Med. Biol. 7 661-70
22. Mathis C A, Wang Y, Holt D P, Huang G F, Debnath M L and Klunk W E 2003 Synthesis and evaluation of 11 C-labeled 6-substituted 2-aryl benzothiazoles as amyloid imaging agents J. Med. Chem. 46 2740-54
23. Nichols N F, Cimini M G, Haas J V, Staton B A, Tedroff J and Svensson K A 2002 PNU-96391 A (OSU6162) antagonizes the development of behavioral sensitization induced by dopamine agonists in a rat model for Parkinson's disease Neuropharmacology 43 817-24
24. Pakrasi S and O'Brien J T 2005 Emission tomography in dementia Nucl. Med. Commun. 26 189-96
25. Patlak C S and Blasberg R G 1985 Graphical evaluation of blood-to-brain transfer constants from multiple-time uptake data Generalizations J. Cereb. Blood. Flow. Metab. 5 584-90
26. Pearson K 1901 On lines and planes of closest fit to systems of points in space Phil. Mag. 6 559-72
27. Pedersen F, Bergström M, Bengtsson E and Maripuu E 1993a Principal component analysis of dynamic PET and gamma camera images: a methodology to visualize the signals in the presence of large noise Nucl. Sci. Symp. and Med. Imag. Conf., IEEE Conf. Record vol 3 pp 1734-8
28. Pedersen F, Bengtsson E and Jonsson D 1993b A numerically derived method for preprocessing of noisy data before applying principal component analysis Proc. 8th Scandinavian Conf. Image Analysis (Tromsø, Norway) pp 981-8
29. Pedersen F, Bergström M, Bengtsson E and Lngström B 1994 Principal component analysis of dynamic positron emission tomography images Eur. J. Nucl. Med. 21 1285-92
30. Pedersen F, Bengtsson E and Nordin B 1995 An extended strategy for exploratory multivariate image analysis including noise considerations J. Chemometr. 9 389-409
31. Razifar P, Axelsson J, Schneider H, Lngström B, Bengtsson E and Bergström M 2006 A new application of pre-normalized principal component analysis for improvement of image quality and clinical diagnosis in human brain PET studies-clinical brain studies using [11 C]-GR205171, [11 C]-L-deuterium-deprenyl, [11 C]-5-Hydroxy-L-Tryptophan, [11 C]-L-DOPA and Pittsburgh Compound-B Neuroimage 33 588-98
32. Razifar P, Lubberink M, Schneider H, Lngström B, Bengtsson E and Bergström M 2005a Non-isotropic noise correlation in PET data reconstructed by FBP but not by OSEM demonstrated using auto-correlation function BMC Med. Imaging 5 3
33. Razifar P, Sandström M, Schneider H, Lngström B, Maripuu E, Bengtsson E and Bergström M 2005b Noise correlation in PET, CT, SPECT and PET/CT data evaluated using autocorrelation function: a phantom study on data, reconstructed using FBP and OSEM BMC Med. Imaging 5 5
34. Rosnow R L and Rosenthal R 1996 Computing contrasts, effect sizes, and counter nulls on other people's published data: general procedures for research consumers Pyschol. Methods 1 331-40
35. Samal M, Karny M, Benali H, Backfrieder W, Todd-Pokropek A and Bergmann H 1999 Experimental comparison of data transformation procedures for analysis of principal components Phys. Med. Biol. 44 2821-34
36. Thireou T, Strauss L G, Dimitrakopoulou-Strauss A, Kontaxakis G, Pavlopoulos S and Santos A 2003 Performance evaluation of principal component analysis in dynamic FDG-PET studies of recurrent colorectal cancer Comp. Med. Imaging Graph. 27 43-51
37. Thireou T, Strauss L, Kontaxakis G, Pavlopoulos S and Santos A 2001 Principal component analysis in dynamic PET Conf. Rec CASEIB pp 241-3
38. Thomas C G, Harshman R A and Menon R S 2002 Noise reduction in BOLD-based fMRI using component analysis Neuroimage 17 1521-37