Optimization of Supervised Cluster Analysis for Extracting Reference Tissue Input Curves in (R)-[(11)C]PK11195 Brain PET Studies

Overview

Journal J Cereb Blood Flow Metab

Publisher Sage Publications

Specialties Cardiology & Vascular Diseases
Endocrinology
Neurology

Date 2012 May 17

PMID 22588187

Citations 82

Authors

Maqsood Yaqub

Bart N M van Berckel

Alie Schuitemaker

Rainer Hinz

Federico E Turkheimer

Giampaolo Tomasi

Adriaan A Lammertsma

Ronald Boellaard

Affiliations

Soon will be listed here.

Abstract

Performance of two supervised cluster analysis (SVCA) algorithms for extracting reference tissue curves was evaluated to improve quantification of dynamic (R)-[(11)C]PK11195 brain positron emission tomography (PET) studies. Reference tissues were extracted from images using both a manually defined cerebellum and SVCA algorithms based on either four (SVCA4) or six (SVCA6) kinetic classes. Data from controls, mild cognitive impairment patients, and patients with Alzheimer's disease were analyzed using various kinetic models including plasma input, the simplified reference tissue model (RPM) and RPM with vascular correction (RPMV(b)). In all subject groups, SVCA-based reference tissue curves showed lower blood volume fractions (V(b)) and volume of distributions than those based on cerebellum time-activity curve. Probably resulting from the presence of specific signal from the vessel walls that contains in normal condition a significant concentration of the 18 kDa translocation protein. Best contrast between subject groups was seen using SVCA4-based reference tissues as the result of a lower number of kinetic classes and the prior removal of extracerebral tissues. In addition, incorporation of V(b) in RPM improved both parametric images and binding potential contrast between groups. Incorporation of V(b) within RPM, together with SVCA4, appears to be the method of choice for analyzing cerebral (R)-[(11)C]PK11195 neurodegeneration studies.

Citing Articles

Cerebral Microbleeds and Their Association With Inflammation and Blood-Brain Barrier Leakage in Small Vessel Disease.

Cai L, Tozer D, Markus H Stroke. 2025; 56(2):427-436.

PMID: 39744850 PMC: 11771357. DOI: 10.1161/STROKEAHA.124.048974.

TSPO Radioligands for Neuroinflammation: An Overview.

Salerno S, Viviano M, Baglini E, Poggetti V, Giorgini D, Castagnoli J Molecules. 2024; 29(17).

PMID: 39275061 PMC: 11397380. DOI: 10.3390/molecules29174212.

Blood inflammation relates to neuroinflammation and survival in frontotemporal lobar degeneration.

Malpetti M, Swann P, Tsvetanov K, Chouliaras L, Strauss A, Chikaura T Brain. 2024; 148(2):493-505.

PMID: 39155063 PMC: 7617268. DOI: 10.1093/brain/awae269.

MINocyclinE to Reduce inflammation and blood-brain barrier leakage in small Vessel diseAse (MINERVA): A phase II, randomized, double-blind, placebo-controlled experimental medicine trial.

Brown R, Tozer D, Loubiere L, Harshfield E, Hong Y, Fryer T Alzheimers Dement. 2024; 20(6):3852-3863.

PMID: 38629936 PMC: 11180856. DOI: 10.1002/alz.13830.

Evaluation of Non-Invasive Methods for (R)-[C]PK11195 PET Image Quantification in Multiple Sclerosis.

Mantovani D, Pitombeira M, Schuck P, de Araujo A, Buchpiguel C, Faria D J Imaging. 2024; 10(2).

PMID: 38392087 PMC: 10889702. DOI: 10.3390/jimaging10020039.

References

Maes F, Collignon A, Vandermeulen D, Marchal G, Suetens P . Multimodality image registration by maximization of mutual information. IEEE Trans Med Imaging. 1997; 16(2):187-98. DOI: 10.1109/42.563664. View

Banati R, Newcombe J, Gunn R, Cagnin A, Turkheimer F, Heppner F . The peripheral benzodiazepine binding site in the brain in multiple sclerosis: quantitative in vivo imaging of microglia as a measure of disease activity. Brain. 2000; 123 ( Pt 11):2321-37. DOI: 10.1093/brain/123.11.2321. View

Boellaard R, van Lingen A, van Balen S, Hoving B, Lammertsma A . Characteristics of a new fully programmable blood sampling device for monitoring blood radioactivity during PET. Eur J Nucl Med. 2001; 28(1):81-9. DOI: 10.1007/s002590000405. View

van Berckel B, Bossong M, Boellaard R, Kloet R, Schuitemaker A, Caspers E . Microglia activation in recent-onset schizophrenia: a quantitative (R)-[11C]PK11195 positron emission tomography study. Biol Psychiatry. 2008; 64(9):820-2. DOI: 10.1016/j.biopsych.2008.04.025. View

Cagnin A, Brooks D, Kennedy A, Gunn R, Myers R, Turkheimer F . In-vivo measurement of activated microglia in dementia. Lancet. 2001; 358(9280):461-7. DOI: 10.1016/S0140-6736(01)05625-2. View

Tomasi G, Edison P, Bertoldo A, Roncaroli F, Singh P, Gerhard A . Novel reference region model reveals increased microglial and reduced vascular binding of 11C-(R)-PK11195 in patients with Alzheimer's disease. J Nucl Med. 2008; 49(8):1249-56. DOI: 10.2967/jnumed.108.050583. View

Dodel R, Spottke A, Gerhard A, Reuss A, Reinecker S, Schimke N . Minocycline 1-year therapy in multiple-system-atrophy: effect on clinical symptoms and [(11)C] (R)-PK11195 PET (MEMSA-trial). Mov Disord. 2009; 25(1):97-107. DOI: 10.1002/mds.22732. View

Gunn R, Gunn S, Cunningham V . Positron emission tomography compartmental models. J Cereb Blood Flow Metab. 2001; 21(6):635-52. DOI: 10.1097/00004647-200106000-00002. View

Schuitemaker A, van der Doef T, Boellaard R, van der Flier W, Yaqub M, Windhorst A . Microglial activation in healthy aging. Neurobiol Aging. 2010; 33(6):1067-72. DOI: 10.1016/j.neurobiolaging.2010.09.016. View

10.

Lammertsma A, Hume S . Simplified reference tissue model for PET receptor studies. Neuroimage. 1996; 4(3 Pt 1):153-8. DOI: 10.1006/nimg.1996.0066. View

11.

Kropholler M, Boellaard R, Schuitemaker A, van Berckel B, Luurtsema G, Windhorst A . Development of a tracer kinetic plasma input model for (R)-[11C]PK11195 brain studies. J Cereb Blood Flow Metab. 2005; 25(7):842-51. DOI: 10.1038/sj.jcbfm.9600092. View

12.

Defrise M, Kinahan P, Townsend D, Michel C, Sibomana M, Newport D . Exact and approximate rebinning algorithms for 3-D PET data. IEEE Trans Med Imaging. 1997; 16(2):145-58. DOI: 10.1109/42.563660. View

13.

Gray K, Contractor K, Kenny L, Al-Nahhas A, Shousha S, Stebbing J . Kinetic filtering of [(18)F]Fluorothymidine in positron emission tomography studies. Phys Med Biol. 2010; 55(3):695-709. DOI: 10.1088/0031-9155/55/3/010. View

14.

West J, Fitzpatrick J, Wang M, Dawant B, Maurer Jr C, Kessler R . Comparison and evaluation of retrospective intermodality brain image registration techniques. J Comput Assist Tomogr. 1997; 21(4):554-66. DOI: 10.1097/00004728-199707000-00007. View

15.

Turkheimer F, Edison P, Pavese N, Roncaroli F, Anderson A, Hammers A . Reference and target region modeling of [11C]-(R)-PK11195 brain studies. J Nucl Med. 2007; 48(1):158-67. View

16.

Gerhard A, Banati R, Goerres G, Cagnin A, Myers R, Gunn R . [11C](R)-PK11195 PET imaging of microglial activation in multiple system atrophy. Neurology. 2003; 61(5):686-9. DOI: 10.1212/01.wnl.0000078192.95645.e6. View

17.

Zhang Y, Brady M, Smith S . Segmentation of brain MR images through a hidden Markov random field model and the expectation-maximization algorithm. IEEE Trans Med Imaging. 2001; 20(1):45-57. DOI: 10.1109/42.906424. View

18.

Schuitemaker A, van Berckel B, Kropholler M, Veltman D, Scheltens P, Jonker C . SPM analysis of parametric (R)-[11C]PK11195 binding images: plasma input versus reference tissue parametric methods. Neuroimage. 2007; 35(4):1473-9. DOI: 10.1016/j.neuroimage.2007.02.013. View

19.

Gunn R, Lammertsma A, Hume S, Cunningham V . Parametric imaging of ligand-receptor binding in PET using a simplified reference region model. Neuroimage. 1998; 6(4):279-87. DOI: 10.1006/nimg.1997.0303. View