{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,30]],"date-time":"2026-09-30T06:47:49Z","timestamp":1790750869970,"version":"4.1.0"},"reference-count":26,"publisher":"Springer Science and Business Media LLC","issue":"9","license":[{"start":{"date-parts":[[2023,4,28]],"date-time":"2023-04-28T00:00:00Z","timestamp":1682640000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"},{"start":{"date-parts":[[2023,4,28]],"date-time":"2023-04-28T00:00:00Z","timestamp":1682640000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"}],"funder":[{"DOI":"10.13039\/501100022115","name":"Dutch Arthritis Association","doi-asserted-by":"publisher","award":["13-1-101"],"award-info":[{"award-number":["13-1-101"]}],"id":[{"id":"10.13039\/501100022115","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Eur J Nucl Med Mol Imaging"],"published-print":{"date-parts":[[2023,7]]},"abstract":"<jats:title>Abstract<\/jats:title><jats:sec>\n                <jats:title>Purpose<\/jats:title>\n                <jats:p>This study is to develop a structured approach to distinguishing large-artery vasculitis from atherosclerosis using 18-fluorodeoxyglucose positron emission tomography combined with low-dose computed tomography (FDG PET\/CT).<\/jats:p>\n              <\/jats:sec><jats:sec>\n                <jats:title>Methods<\/jats:title>\n                <jats:p>FDG PET\/CT images of 60 patients were evaluated, 30 having biopsy-proven giant cell arteritis (GCA; the most common form of large-artery vasculitis), and 30 with severe atherosclerosis. Images were evaluated by 12 nuclear medicine physicians using 5 criteria: FDG uptake pattern (intensity, distribution, circularity), the degree of calcification, and co-localization of calcifications with FDG-uptake. Criteria that passed agreement, and reliability tests were subsequently analysed for accuracy using receiver operator curve (ROC) analyses. Criteria that showed discriminative ability were then combined in a multi-component scoring system. Both initial and final \u2018gestalt\u2019 conclusion were also reported by observers before and after detailed examination of the images.<\/jats:p>\n              <\/jats:sec><jats:sec>\n                <jats:title>Results<\/jats:title>\n                <jats:p>Agreement and reliability analyses disqualified 3 of the 5 criteria, leaving only FDG uptake intensity compared to liver uptake and arterial wall calcification for potential use in a scoring system. ROC analysis showed an area under the curve (AUC) of 0.90 (95%CI 0.87\u20130.92) for FDG uptake intensity. Degree of calcification showed poor discriminative ability on its own (AUC of 0.62; 95%CI 0.58\u20130.66). When combining presence of calcification with FDG uptake intensity into a 6-tiered scoring system, the AUC remained similar at 0.91 (95%CI 0.88\u20130.93). After exclusion of cases with arterial prostheses, the AUC increased to 0.93 (95%CI 0.91\u20130.95). The accuracy of the \u2018gestalt\u2019 conclusion was initially 89% (95%CI 86\u201391%) and increased to 93% (95%CI 91\u201395%) after detailed image examination.<\/jats:p>\n              <\/jats:sec><jats:sec>\n                <jats:title>Conclusion<\/jats:title>\n                <jats:p>Standardised assessment of arterial wall FDG uptake intensity, preferably combined with assessment of arterial calcifications into a scoring method, enables accurate, but not perfect, distinction between large artery vasculitis and atherosclerosis.<\/jats:p>\n              <\/jats:sec>","DOI":"10.1007\/s00259-023-06220-5","type":"journal-article","created":{"date-parts":[[2023,4,28]],"date-time":"2023-04-28T07:02:33Z","timestamp":1682665353000},"page":"2647-2655","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":11,"title":["Development of a simple standardized scoring system for assessing large vessel vasculitis by 18F-FDG PET-CT and differentiation from atherosclerosis"],"prefix":"10.1007","volume":"50","author":[{"given":"Y. A. A.","family":"Bacour","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"M. P.","family":"van Kanten","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"F.","family":"Smit","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"E. F. I.","family":"Comans","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"M.","family":"Akarriou","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"H. C. W.","family":"de Vet","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"A. E.","family":"Voskuyl","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"C. J.","family":"van der Laken","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Y. M.","family":"Smulders","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2023,4,28]]},"reference":[{"key":"6220_CR1","doi-asserted-by":"publisher","DOI":"10.1136\/bmj.l1964","volume":"365","author":"K Lazarewicz","year":"2019","unstructured":"Lazarewicz K, Watson P. Giant cell arteritis. BMJ. 2019;365: l1964.","journal-title":"BMJ"},{"key":"6220_CR2","doi-asserted-by":"publisher","first-page":"4","DOI":"10.1308\/003588411X12851639107476","volume":"93","author":"CG Davies","year":"2011","unstructured":"Davies CG, May DJ. The role of temporal artery biopsies in giant cell arteritis. Ann R Coll Surg Engl. 2011;93:4\u20135.","journal-title":"Ann R Coll Surg Engl"},{"key":"6220_CR3","doi-asserted-by":"publisher","first-page":"18","DOI":"10.1080\/01658107.2018.1474372","volume":"43","author":"EB Ing","year":"2018","unstructured":"Ing EB, Wang DN, Kirubarajan A, Benard-Seguin E, Ma J, Farmer JP, Belliveau MJ, Sholohov G, Torun N. Systematic review of the yield of temporal artery biopsy for suspected giant cell arteritis. Neuroophthalmology. 2018;43:18\u201325.","journal-title":"Neuroophthalmology"},{"key":"6220_CR4","doi-asserted-by":"publisher","first-page":"19","DOI":"10.1136\/annrheumdis-2019-215672","volume":"79","author":"B Hellmich","year":"2020","unstructured":"Hellmich B, Agueda A, Monti S, Buttgereit F, de Boysson H, Brouwer E, Cassie R, Cid MC, Dasgupta B, Dejaco C, Hatemi G, Hollinger N, Mahr A, Mollan SP, Salvarani C, Sivakumar R, Tian X, Tomasson G, Turesson C, Schmidt W, Viliger PM, Watts R, Toung C, Luqmani RA. 2018 update of the EULAR recommendations for the management of large-vessel vasculitis. Ann Rheum Dis. 2020;79:19\u201330.","journal-title":"Ann Rheum Dis"},{"key":"6220_CR5","doi-asserted-by":"crossref","unstructured":"K. Johnsrud, K. Skagen, T. Seierstad, M. Skjelland, D. Russell, M.E. Revheim(18)F-FDG PET\/CT for the quantification of inflammation in large carotid artery plaques. J Nucl Cardiol 2019;26:883\u2013893","DOI":"10.1007\/s12350-017-1121-7"},{"key":"6220_CR6","doi-asserted-by":"publisher","first-page":"871","DOI":"10.2967\/jnumed.107.050294","volume":"49","author":"JHF Rudd","year":"2008","unstructured":"Rudd JHF, Myers KS, Bansilal S, Machac J, Pinto CA, Rafique A, Hargeaves R, Farkouh M, Fuser V, Fayad ZA. Atherosclerosis inflammation imaging with 18F-FDG PET: carotid, iliac, and femoral uptake reproducibility, quantification methods, and recommendations. J Nucl Med. 2008;49:871\u20138.","journal-title":"J Nucl Med"},{"key":"6220_CR7","doi-asserted-by":"crossref","unstructured":"Lensen KDF, Comans EF, Voskuyl AE, van der Laken CJ, Brouwer E, Zwijnenburg AT, Pereira Arias Bouda LM, Glaudemans AW, Slart RH, Smulders YM. Large-vessel vasculitis: interobserver agreement and diagnostic accuracy of\u00a018F-FDG-PET\/CT.\u00a0BioMed Research Int. 2015:904692","DOI":"10.1155\/2015\/914692"},{"key":"6220_CR8","doi-asserted-by":"crossref","unstructured":"Stellingwerff MD, Bouwer E, Lensen KDF, Rutgers A, Arends S, van der Geest KSM, Glaudemans AW, Slart RHl. Different scoring methods of FDG PET\/CT in giant cell arteritis: need for standardization. Med. 2015;94:e1542","DOI":"10.1097\/MD.0000000000001542"},{"key":"6220_CR9","doi-asserted-by":"publisher","first-page":"2320","DOI":"10.1007\/s00259-008-0874-2","volume":"35","author":"R Boellaard","year":"2008","unstructured":"Boellaard R, Oyen WJ, Hoekstra CJ, Hoekstra OS, Visser EP, Willemsen AT, Arends B, Verzijlbergen FJ, Zijlstra J, Paans AM, Comans EJ, Pruim J. The Netherlands protocol for standardisation and quantification of FDG whole body PET studies in multi-centre trials. Eur J Nucl Med Mol Imaging. 2008;35:2320\u201333.","journal-title":"Eur J Nucl Med Mol Imaging"},{"key":"6220_CR10","doi-asserted-by":"crossref","unstructured":"Belhocine, Blockmans D, Hustinx R, Vandevivere J, Mortelmans L. Imaging of large vessel vasculitis with (18)FDG PET: illusion or reality? A critical review of the literature data. Eur J Nucl Med Mol Imag. 2003;30:1305\u20131313.","DOI":"10.1007\/s00259-003-1209-y"},{"key":"6220_CR11","doi-asserted-by":"crossref","unstructured":"Puppo, Massollo M, Paparo F, Camellino D, Piccardo A, Shoushtari Zadeh Naseri M, Villavecchia G, Rollandi GA, Cimmino MA. Giant cell arteritis: a systematic review of the qualitative and semiquantitative methods to assess vasculitis with 18F-fluorodeoxyglucose positron emission tomography.\u00a0BioMed Res Int. 2014;2014:574248","DOI":"10.1155\/2014\/574248"},{"key":"6220_CR12","doi-asserted-by":"publisher","DOI":"10.1155\/2014\/687608","volume":"2014","author":"H Balink","year":"2014","unstructured":"Balink H, Bennink RJ, van Eck-Smit BL, Verberne HJ. The role of 18F-FDG PET\/CT in large-vessel vasculitis: appropriateness of current classification criteria? Biomed Res Int. 2014;2014: 687608.","journal-title":"Biomed Res Int"},{"key":"6220_CR13","doi-asserted-by":"crossref","unstructured":"Slart RHJA, Writing group; Reviewer group; Members of EANM Cardiovascular; Members of EANM Infection & Inflammation; Members of Committees, SNMMI Cardiovascular; Members of Council, PET Interest Group; Members of ASNC; EANM Committee Coordinator. FDG-PET\/CT(A) imaging in large vessel vasculitis and polymyalgia rheumatica: joint procedural recommendation of the EANM, SNMMI, and the PET Interest Group (PIG), and endorsed by the ASNC. Eur J Nucl Med Mol Imaging 2018;45:1250\u20131269","DOI":"10.1007\/s00259-018-3973-8"},{"key":"6220_CR14","doi-asserted-by":"publisher","first-page":"875","DOI":"10.3174\/ajnr.A0950","volume":"29","author":"M Wintermark","year":"2008","unstructured":"Wintermark M, Jawadi SS, Rapp JH, Tihan T, Tong E, Glidden DV, Abedin S, Schaeffer S, Acevedo-Bolton G, Boudignon B, Orwoll B, Pan X, Saloner D. High-resolution CT imaging of carotid artery atherosclerotic plaques. Am J Neuroradiol. 2008;29:875\u201382.","journal-title":"Am J Neuroradiol"},{"key":"6220_CR15","doi-asserted-by":"publisher","first-page":"85","DOI":"10.1016\/j.jclinepi.2016.12.007","volume":"83","author":"HCW de Vet","year":"2017","unstructured":"de Vet HCW, Dikmans RE, Eekhout I. Specific agreement on dichotomous outcomes can be calculated for more than two raters. J Clin Epidemiol. 2017;83:85\u20139.","journal-title":"J Clin Epidemiol"},{"key":"6220_CR16","doi-asserted-by":"publisher","first-page":"47","DOI":"10.1016\/j.jclinepi.2017.11.024","volume":"96","author":"HCW de Vet","year":"2018","unstructured":"de Vet HCW, Mullender MG, Eekhout I. Specific agreement on ordinal and multiple nominal outcomes can be calculated for more than two raters. J Clin Epidemiol. 2018;96:47\u201353.","journal-title":"J Clin Epidemiol"},{"key":"6220_CR17","doi-asserted-by":"publisher","first-page":"613","DOI":"10.1177\/001316447303300309","volume":"33","author":"JL Fleiss","year":"1973","unstructured":"Fleiss JL, Cohen J. The equivalence of weighted kappa and the intraclass correlation coefficient as measures of reliability. Educat Psychol Meas. 1973;33:613\u20139.","journal-title":"Educat Psychol Meas"},{"key":"6220_CR18","doi-asserted-by":"publisher","first-page":"159","DOI":"10.2307\/2529310","volume":"33","author":"JR Landis","year":"1977","unstructured":"Landis JR, Koch GG. The measurement of observer agreement for categorical data. Biometrics. 1977;33:159\u201371.","journal-title":"Biometrics"},{"key":"6220_CR19","doi-asserted-by":"publisher","first-page":"769","DOI":"10.3389\/fpsyg.2016.00769","volume":"7","author":"I Trizano-Hermosilla","year":"2016","unstructured":"Trizano-Hermosilla I, Alvarado JM. Best alternatives to Cronbach\u2019s alpha reliability in realistic conditions: congeneric and asymmetrical measurements. Front Psychol. 2016;7:769.","journal-title":"Front Psychol"},{"key":"6220_CR20","doi-asserted-by":"publisher","first-page":"132","DOI":"10.1111\/j.1365-2753.2005.00598.x","volume":"12","author":"A Linden","year":"2006","unstructured":"Linden A. Measuring diagnostic and predictive accuracy in disease management: an introduction to receiver operating characteristic (ROC) analysis. J Eval Clin Prac. 2006;12:132\u20139.","journal-title":"J Eval Clin Prac"},{"key":"6220_CR21","doi-asserted-by":"publisher","first-page":"833","DOI":"10.1097\/MNM.0000000000000515","volume":"37","author":"GG Bural","year":"2016","unstructured":"Bural GG, Torigian D, Rubello D, Alavi A. Atherosclerotic 18F-FDG and MDP uptake in femoral arteries, changes with age. Nucl Med Commun. 2016;37:833\u20136.","journal-title":"Nucl Med Commun"},{"key":"6220_CR22","doi-asserted-by":"publisher","first-page":"941","DOI":"10.1007\/s00259-017-3914-y","volume":"45","author":"T Salomon","year":"2017","unstructured":"Salomon T, Nganoa C, Gac AC, Fruchart C, Damaj G, Lasnon C. Assessment of alteration in liver 18F\u2013FDG uptake due to steatosis in lymphoma patients and its impact on the Deauville score. Eur J Nucl Med Mol Imaging. 2017;45:941\u201350.","journal-title":"Eur J Nucl Med Mol Imaging"},{"key":"6220_CR23","doi-asserted-by":"publisher","first-page":"677","DOI":"10.2967\/jnumed.112.108530","volume":"54","author":"RR Boktor","year":"2013","unstructured":"Boktor RR, Walker G, Stacey R, Gledhill S, Pitman AG. Reference range for intrapatient variability in blood-pool and liver SUV for 18F-FDG PET. J Nucl Med. 2013;54:677\u201382.","journal-title":"J Nucl Med"},{"key":"6220_CR24","doi-asserted-by":"publisher","first-page":"295","DOI":"10.1016\/j.jacr.2018.06.026","volume":"16","author":"MK Kalra","year":"2019","unstructured":"Kalra MK, Becker HC, Enterline DS, Lowry CR, Molvin LZ, Singh R, Rybicki FJ. Contrast administration in CT: a patient-centric approach. J Am Coll Radiol. 2019;16:295\u2013301.","journal-title":"J Am Coll Radiol"},{"key":"6220_CR25","doi-asserted-by":"crossref","unstructured":"Taimen K, Salomaki SP, Hohenthal U, Kajander MM, Seppanen M, Nuutila P, Palomaki A, Roivanen A, Pirila L, Kemppainen J. The clinical impact of using\u00a018F-FDG-PET\/CT in the diagnosis of suspected vasculitis: the effect of dose and timing of glucocorticoid treatment.\u00a0Contrast Media Mol Imaging 2019:9157637","DOI":"10.1155\/2019\/9157637"},{"key":"6220_CR26","doi-asserted-by":"crossref","unstructured":"Prieto-Pe\u00f1a D,\u00a0Mart\u00ednez-Rodr\u00edguez I,\u00a0Loricera J,\u00a0Banzo I, Calderon-Goerke M, Calo-Rio V, Gonzales-Vela C, Corrales A, Castaneda S, Blanco R, Hernandez JL, Gonzales-Gay MA. Predictors of positive (18)F-FDG PET\/CT-scan for large vessel vasculitis in patients with persistent polymyalgia rheumatic Semin Arthritis Rheum\u00a02019;48:720\u2013727","DOI":"10.1016\/j.semarthrit.2018.05.007"}],"container-title":["European Journal of Nuclear Medicine and Molecular Imaging"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s00259-023-06220-5.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s00259-023-06220-5\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s00259-023-06220-5.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,7,3]],"date-time":"2023-07-03T09:05:59Z","timestamp":1688375159000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s00259-023-06220-5"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,4,28]]},"references-count":26,"journal-issue":{"issue":"9","published-print":{"date-parts":[[2023,7]]}},"alternative-id":["6220"],"URL":"https:\/\/doi.org\/10.1007\/s00259-023-06220-5","relation":{},"ISSN":["1619-7070","1619-7089"],"issn-type":[{"value":"1619-7070","type":"print"},{"value":"1619-7089","type":"electronic"}],"subject":[],"published":{"date-parts":[[2023,4,28]]},"assertion":[{"value":"29 December 2022","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"2 April 2023","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"28 April 2023","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"The protocol was performed in line with the principles of the Declaration of Helsinki and was approved by the institution\u2019s Medical Ethics Committee.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Ethics approval"}},{"value":"Informed consent was obtained from all individual participants included in the study.","order":3,"name":"Ethics","group":{"name":"EthicsHeading","label":"Informed consent"}},{"value":"The authors declare no competing interests.","order":4,"name":"Ethics","group":{"name":"EthicsHeading","label":"Competing interests"}}]}}