{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,1,18]],"date-time":"2025-01-18T06:40:18Z","timestamp":1737182418273,"version":"3.33.0"},"reference-count":36,"publisher":"MDPI AG","issue":"2","license":[{"start":{"date-parts":[[2024,1,31]],"date-time":"2024-01-31T00:00:00Z","timestamp":1706659200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/100006775","name":"GE Healthcare","doi-asserted-by":"crossref","award":["12496139131"],"id":[{"id":"10.13039\/100006775","id-type":"DOI","asserted-by":"crossref"}]},{"name":"Coordena\u00e7\u00e3o de Aperfei\u00e7oamento de Pessoal de N\u00edvel Superior\u2014Brasil (CAPES)","award":["001"]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["J. Imaging"],"abstract":"This study aims to evaluate non-invasive PET quantification methods for (R)-[11C]PK11195 uptake measurement in multiple sclerosis (MS) patients and healthy controls (HC) in comparison with arterial input function (AIF) using dynamic (R)-[11C]PK11195 PET and magnetic resonance images. The total volume of distribution (VT) and distribution volume ratio (DVR) were measured in the gray matter, white matter, caudate nucleus, putamen, pallidum, thalamus, cerebellum, and brainstem using AIF, the image-derived input function (IDIF) from the carotid arteries, and pseudo-reference regions from supervised clustering analysis (SVCA). Uptake differences between MS and HC groups were tested using statistical tests adjusted for age and sex, and correlations between the results from the different quantification methods were also analyzed. Significant DVR differences were observed in the gray matter, white matter, putamen, pallidum, thalamus, and brainstem of MS patients when compared to the HC group. Also, strong correlations were found in DVR values between non-invasive methods and AIF (0.928 for IDIF and 0.975 for SVCA, p < 0.0001). On the other hand, (R)-[11C]PK11195 uptake could not be differentiated between MS patients and HC using VT values, and a weak correlation (0.356, p < 0.0001) was found between VTAIF and VTIDIF. Our study shows that the best alternative for AIF is using SVCA for reference region modeling, in addition to a cautious and appropriate methodology.<\/jats:p>","DOI":"10.3390\/jimaging10020039","type":"journal-article","created":{"date-parts":[[2024,1,31]],"date-time":"2024-01-31T14:41:59Z","timestamp":1706712119000},"page":"39","source":"Crossref","is-referenced-by-count":0,"title":["Evaluation of Non-Invasive Methods for (R)-[11C]PK11195 PET Image Quantification in Multiple Sclerosis"],"prefix":"10.3390","volume":"10","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-4883-4680","authenticated-orcid":false,"given":"Dimitri B. A.","family":"Mantovani","sequence":"first","affiliation":[{"name":"Faculdade de Medicina FMUSP, Universidade de Sao Paulo, Sao Paulo 05403-911, Brazil"}]},{"given":"Milena S.","family":"Pitombeira","sequence":"additional","affiliation":[{"name":"Laboratory of Nuclear Medicine (LIM 43), Department of Radiology and Oncology, Faculdade de Medicina FMUSP, Universidade de Sao Paulo, Sao Paulo 05403-911, Brazil"}]},{"given":"Phelipi N.","family":"Schuck","sequence":"additional","affiliation":[{"name":"Weill Cornell Medical College, New York, NY 10065, USA"}]},{"given":"Adriel S.","family":"de Ara\u00fajo","sequence":"additional","affiliation":[{"name":"Graduate Program in Computer Science, Pontificia Universidade Catolica do Rio Grande do Sul PUCRS, Porto Alegre 90619-900, Brazil"}]},{"given":"Carlos Alberto","family":"Buchpiguel","sequence":"additional","affiliation":[{"name":"Faculdade de Medicina FMUSP, Universidade de Sao Paulo, Sao Paulo 05403-911, Brazil"},{"name":"Laboratory of Nuclear Medicine (LIM 43), Department of Radiology and Oncology, Faculdade de Medicina FMUSP, Universidade de Sao Paulo, Sao Paulo 05403-911, Brazil"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1766-2786","authenticated-orcid":false,"given":"Daniele","family":"de Paula Faria","sequence":"additional","affiliation":[{"name":"Faculdade de Medicina FMUSP, Universidade de Sao Paulo, Sao Paulo 05403-911, Brazil"},{"name":"Laboratory of Nuclear Medicine (LIM 43), Department of Radiology and Oncology, Faculdade de Medicina FMUSP, Universidade de Sao Paulo, Sao Paulo 05403-911, Brazil"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5924-6852","authenticated-orcid":false,"given":"Ana Maria","family":"M. da Silva","sequence":"additional","affiliation":[{"name":"Faculdade de Medicina FMUSP, Universidade de Sao Paulo, Sao Paulo 05403-911, Brazil"}]}],"member":"1968","published-online":{"date-parts":[[2024,1,31]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"1071","DOI":"10.1590\/S0004-282X2009000600021","article-title":"Clinical features of multiple sclerosis in the south of Brazil: A partial analysis","volume":"67","author":"Finkelsztejn","year":"2009","journal-title":"Arq. Neuropsiquiatr."},{"key":"ref_2","doi-asserted-by":"crossref","unstructured":"Samkoff, L.M., and Goodman, A.D. (2014). Multiple Sclerosis and CNS Inflammatory Disorders, John Wiley & Sons Inc.","DOI":"10.1002\/9781118298633"},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"2321","DOI":"10.1093\/brain\/123.11.2321","article-title":"The peripheral benzodiazepine binding site in the brain in multiple sclerosis","volume":"123","author":"Banati","year":"2000","journal-title":"Brain"},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"15","DOI":"10.1186\/2191-219X-2-15","article-title":"Kinetic analysis and test-retest variability of the radioligand [11C](R)-PK11195 binding to TSPO in the human brain\u2014A PET study in control subjects","volume":"2","author":"Arvidsson","year":"2012","journal-title":"EJNMMI Res."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"1019","DOI":"10.2967\/jnumed.116.188029","article-title":"Forward to the Past: The Case for Quantitative PET Imaging","volume":"58","author":"Lammertsma","year":"2017","journal-title":"J. Nucl. Med."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"663","DOI":"10.1109\/TRPMS.2020.3025086","article-title":"PET Parametric Imaging: Past, Present, and Future","volume":"4","author":"Wang","year":"2020","journal-title":"IEEE Trans. Radiat. Plasma Med. Sci."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"1636","DOI":"10.1007\/s00259-022-06057-4","article-title":"Non-invasive kinetic modelling approaches for quantitative analysis of brain PET studies","volume":"50","author":"Mossel","year":"2023","journal-title":"Eur. J. Nucl. Med. Mol. Imaging"},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"1825","DOI":"10.1038\/jcbfm.2009.93","article-title":"Comparison of Eight Methods for the Estimation of the Image-Derived Input Function in Dynamic [18F]-FDG PET Human Brain Studies","volume":"29","author":"Fadaili","year":"2009","journal-title":"J. Cereb. Blood Flow. Metab."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"982","DOI":"10.1097\/MNM.0b013e328356185c","article-title":"Image-derived input function in PET brain studies: Blood-based methods are resistant to motion artifacts","volume":"33","author":"Liow","year":"2012","journal-title":"Nucl. Med. Commun."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"1539","DOI":"10.1007\/s00259-010-1443-z","article-title":"Image-derived input function in dynamic human PET\/CT: Methodology and validation with 11C-acetate and 18F-fluorothioheptadecanoic acid in muscle and 18F-fluorodeoxyglucose in brain","volume":"37","author":"Croteau","year":"2010","journal-title":"Eur. J. Nucl. Med. Mol. Imaging."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"523","DOI":"10.1212\/WNL.0b013e3182635645","article-title":"Increased PK11195 PET binding in the cortex of patients with MS correlates with disability","volume":"79","author":"Politis","year":"2012","journal-title":"Neurology"},{"key":"ref_12","doi-asserted-by":"crossref","unstructured":"Kang, Y., Schlyer, D., Kaunzner, U.W., Kuceyeski, A., Kothari, P.J., and Gauthier, S.A. (2018). Comparison of two different methods of image analysis for the assessment of microglial activation in patients with multiple sclerosis using (R)-[N-methyl-carbon-11]PK11195. PLoS ONE, 13.","DOI":"10.1371\/journal.pone.0201289"},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"133","DOI":"10.1093\/brain\/awy296","article-title":"Quantitative susceptibility mapping identifies inflammation in a subset of chronic multiple sclerosis lesions","volume":"142","author":"Kaunzner","year":"2019","journal-title":"Brain"},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"1431","DOI":"10.1038\/sj.jcbfm.9600289","article-title":"Evaluation of Reference Tissue Models for the Analysis of [11C](R)-PK11195 Studies","volume":"26","author":"Kropholler","year":"2006","journal-title":"J. Cereb. Blood Flow. Metab."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"874","DOI":"10.1177\/0271678X17742004","article-title":"Generalization of endothelial modelling of TSPO PET imaging: Considerations on tracer affinities","volume":"39","author":"Rizzo","year":"2019","journal-title":"J. Cereb. Blood Flow. Metab."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"789","DOI":"10.1016\/S1474-4422(17)30173-4","article-title":"Assessment of neuroinflammation in patients with idiopathic rapid-eye-movement sleep behaviour disorder: A case-control study","volume":"16","author":"Stokholm","year":"2017","journal-title":"Lancet Neurol."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"340","DOI":"10.1093\/brain\/aww340","article-title":"18 F-AV-1451 positron emission tomography in Alzheimer\u2019s disease and progressive supranuclear palsy","volume":"24","author":"Passamonti","year":"2017","journal-title":"Brain"},{"key":"ref_18","first-page":"158","article-title":"Reference and target region modeling of [11C]-(R)-PK11195 brain studies","volume":"48","author":"Turkheimer","year":"2007","journal-title":"J. Nucl. Med. Off. Publ. Soc. Nucl. Med."},{"key":"ref_19","unstructured":"Boellaard, R., Turkheimer, F.E., Hinz, R., Schuitemaker, A., Scheltens, P., van Berckel, B.N.M., and Lammertsma, A.A. (2008). 2008 IEEE Nuclear Science Symposium Conference Record, IEEE. Available online: http:\/\/ieeexplore.ieee.org\/document\/4774453."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"1600","DOI":"10.1038\/jcbfm.2012.59","article-title":"Optimization of Supervised Cluster Analysis for Extracting Reference Tissue Input Curves in (R)-[11C]PK11195 Brain PET Studies","volume":"32","author":"Yaqub","year":"2012","journal-title":"J. Cereb. Blood Flow. Metab."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"203","DOI":"10.1016\/j.nbd.2014.01.018","article-title":"Microglia activation in multiple sclerosis black holes predicts outcome in progressive patients: An in vivo [(11)C](R)-PK11195-PET pilot study","volume":"65","author":"Giannetti","year":"2014","journal-title":"Neurobiol. Dis."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"939","DOI":"10.2967\/jnumed.113.131698","article-title":"In Vivo Detection of Diffuse Inflammation in Secondary Progressive Multiple Sclerosis Using PET Imaging and the Radioligand 11C-PK11195","volume":"55","author":"Rissanen","year":"2014","journal-title":"J. Nucl. Med."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"e443","DOI":"10.1212\/NXI.0000000000000443","article-title":"Microglial activation, white matter tract damage, and disability in MS","volume":"5","author":"Rissanen","year":"2018","journal-title":"Neurol. Neuroimmunol. Neuroinflamm."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"1646","DOI":"10.2967\/jnumed.116.183020","article-title":"Evaluation of the Effect of Fingolimod Treatment on Microglial Activation Using Serial PET Imaging in Multiple Sclerosis","volume":"58","author":"Sucksdorff","year":"2017","journal-title":"J. Nucl. Med."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"27","DOI":"10.1016\/j.msard.2017.04.008","article-title":"Reduction of PK11195 uptake observed in multiple sclerosis lesions after natalizumab initiation","volume":"15","author":"Kaunzner","year":"2017","journal-title":"Mult. Scler. Relat. Disord."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"4551","DOI":"10.1007\/s00259-022-05899-2","article-title":"Innate immune cells and myelin profile in multiple sclerosis: A multi-tracer PET\/MR study","volume":"49","author":"Pitombeira","year":"2022","journal-title":"Eur. J. Nucl. Med. Mol. Imaging"},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"2494","DOI":"10.4103\/1673-5374.313062","article-title":"11C-PK11195 plasma metabolization has the same rate in multiple sclerosis patients and healthy controls: A cross-sectional study","volume":"16","author":"Pitombeira","year":"2021","journal-title":"Neural Regen. Res."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"224","DOI":"10.1002\/hbm.10123","article-title":"Three-dimensional maximum probability atlas of the human brain, with particular reference to the temporal lobe","volume":"19","author":"Hammers","year":"2003","journal-title":"Hum. Brain Mapp."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"672","DOI":"10.1016\/j.neuroimage.2007.11.034","article-title":"Automatic segmentation of brain MRIs of 2-year-olds into 83 regions of interest","volume":"40","author":"Gousias","year":"2008","journal-title":"NeuroImage"},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"257","DOI":"10.1007\/s00259-021-05309-z","article-title":"Supervised clustering for TSPO PET imaging","volume":"49","author":"Schubert","year":"2021","journal-title":"Eur. J. Nucl. Med. Mol. Imaging"},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"661","DOI":"10.1016\/S0969-8051(00)00137-2","article-title":"Graphical analysis of PET data applied to reversible and irreversible tracers","volume":"27","author":"Logan","year":"2000","journal-title":"Nucl. Med. Biol."},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"834","DOI":"10.1097\/00004647-199609000-00008","article-title":"Distribution Volume Ratios without Blood Sampling from Graphical Analysis of PET Data","volume":"16","author":"Logan","year":"1996","journal-title":"J. Cereb. Blood Flow. Metab."},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"246","DOI":"10.1007\/s00259-021-05248-9","article-title":"Kinetic modeling and parameter estimation of TSPO PET imaging in the human brain","volume":"49","author":"Wimberley","year":"2021","journal-title":"Eur. J. Nucl. Med. Mol. Imaging"},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"1829","DOI":"10.1118\/1.4943565","article-title":"Patient motion effects on the quantification of regional myocardial blood flow with dynamic PET imaging","volume":"43","author":"Hunter","year":"2016","journal-title":"Med. Phys."},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"132","DOI":"10.1109\/42.370409","article-title":"A modified expectation maximization algorithm for penalized likelihood estimation in emission tomography","volume":"14","year":"1995","journal-title":"IEEE Trans. Med. Imaging"},{"key":"ref_36","unstructured":"Qi, J., and Huesman, R.H. (2002, January 7\u201310). List mode reconstruction for PET with motion compensation: A simulation study. Proceedings of the IEEE International Symposium on Biomedical Imaging, Washington, DC, USA."}],"container-title":["Journal of Imaging"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2313-433X\/10\/2\/39\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,1,18]],"date-time":"2025-01-18T06:00:49Z","timestamp":1737180049000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2313-433X\/10\/2\/39"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,1,31]]},"references-count":36,"journal-issue":{"issue":"2","published-online":{"date-parts":[[2024,2]]}},"alternative-id":["jimaging10020039"],"URL":"https:\/\/doi.org\/10.3390\/jimaging10020039","relation":{},"ISSN":["2313-433X"],"issn-type":[{"type":"electronic","value":"2313-433X"}],"subject":[],"published":{"date-parts":[[2024,1,31]]}}}