Alessandra Soriano1, Giulia Pazzola2, Luigi Boiardi1, Massimiliano Casali3, Francesco Muratore2, Nicolò Pipitone1, Mariagrazia Catanoso1, Raffaella Aldigeri4, Luca Cimino5, Annibale Versari3, Carlo Salvarani6. 1. Rheumatology Unit, Azienda Ospedaliera ASMN, Istituto di Ricovero e Cura a Carattere Scientifico, Reggio Emilia, Italy. 2. Rheumatology Unit, Azienda Ospedaliera ASMN, Istituto di Ricovero e Cura a Carattere Scientifico, Reggio Emilia, and Università di Modena e Reggio Emilia, Italy. 3. Nuclear Medicine Unit, Azienda Ospedaliera ASMN, Istituto di Ricovero e Cura a Carattere Scientifico, Reggio Emilia, Italy. 4. Department of Medicine and Surgery, University of Parma, Italy. 5. Università di Modena e Reggio Emilia, Italy. 6. Rheumatology Unit, Azienda Ospedaliera ASMN, Istituto di Ricovero e Cura a Carattere Scientifico, Reggio Emilia, and Università di Modena e Reggio Emilia, Italy. carlo.salvarani@ausl.re.it.
Abstract
OBJECTIVES: To compare patterns of vascular involvement using 18F-fluorodeoxyglucose-positron emission tomography computed tomography (FDG PET/CT) in patients with giant cell arteritis (GCA) and Takayasu's arteritis (TAK). METHODS: A total of 130 consecutive 18F-FDG PET/CT scans performed during the disease course for evaluating disease activity in 15 GCA and 13 TAK patients were retrospectively examined by two nuclear physicians blinded to clinical data. Standardised uptake values (SUVmax) in 14 vascular districts including all the aortic segments and the main tributaries were measured. The average SUVmax value for each vascular district was also calculated. Principal component analysis (PCA) and agglomerative hierarchical cluster analysis (CA) were used to explore distribution patterns of vascular FDG uptake. RESULTS: The aortic segments showed the highest SUV max values among the different districts in both GCA and TAK. SUV max values measured in the different districts were significantly higher in GCA compared to TAK, except for the axillary arteries. Regarding thoracic and abdominal aorta, ascending aorta and aortic arch had the highest correlation in both vasculitis (p<0.0001). CA confirmed that carotid, axillary, subclavian, iliac and femoral arteries clustered with their contralateral counterpart in both vasculitis. The 3 components of thoracic aorta clustered with abdominal aorta in TAK, while aortic arch clustered only with ascending aorta, and descending and abdominal aorta grouped together with iliac and femoral arteries in GCA. PCA analysis identified 3 different components for TAK and GCA explaining 72% and 71% of the total variance respectively in these two vasculitis. Confirming CA, a component including the entire aortic district was identified in TAK, but not in GCA. Similar results in PCA using averaged data were observed. CONCLUSIONS: Strong similarities, but also a subtle skewing in terms of distribution patterns of arterial involvement assessed by SUVmax values were observed between GCA and TAK.
OBJECTIVES: To compare patterns of vascular involvement using 18F-fluorodeoxyglucose-positron emission tomography computed tomography (FDG PET/CT) in patients with giant cell arteritis (GCA) and Takayasu's arteritis (TAK). METHODS: A total of 130 consecutive 18F-FDG PET/CT scans performed during the disease course for evaluating disease activity in 15 GCA and 13 TAK patients were retrospectively examined by two nuclear physicians blinded to clinical data. Standardised uptake values (SUVmax) in 14 vascular districts including all the aortic segments and the main tributaries were measured. The average SUVmax value for each vascular district was also calculated. Principal component analysis (PCA) and agglomerative hierarchical cluster analysis (CA) were used to explore distribution patterns of vascular FDG uptake. RESULTS: The aortic segments showed the highest SUV max values among the different districts in both GCA and TAK. SUV max values measured in the different districts were significantly higher in GCA compared to TAK, except for the axillary arteries. Regarding thoracic and abdominal aorta, ascending aorta and aortic arch had the highest correlation in both vasculitis (p<0.0001). CA confirmed that carotid, axillary, subclavian, iliac and femoral arteries clustered with their contralateral counterpart in both vasculitis. The 3 components of thoracic aorta clustered with abdominal aorta in TAK, while aortic arch clustered only with ascending aorta, and descending and abdominal aorta grouped together with iliac and femoral arteries in GCA. PCA analysis identified 3 different components for TAK and GCA explaining 72% and 71% of the total variance respectively in these two vasculitis. Confirming CA, a component including the entire aortic district was identified in TAK, but not in GCA. Similar results in PCA using averaged data were observed. CONCLUSIONS: Strong similarities, but also a subtle skewing in terms of distribution patterns of arterial involvement assessed by SUVmax values were observed between GCA and TAK.
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Authors: Riemer H J A Slart; Andor W J M Glaudemans; Olivier Gheysens; Mark Lubberink; Tanja Kero; Marc R Dweck; Gilbert Habib; Oliver Gaemperli; Antti Saraste; Alessia Gimelli; Panagiotis Georgoulias; Hein J Verberne; Jan Bucerius; Christoph Rischpler; Fabien Hyafil; Paola A Erba Journal: Eur Heart J Cardiovasc Imaging Date: 2020-12-01 Impact factor: 6.875
Authors: Riemer H J A Slart; Andor W J M Glaudemans; Olivier Gheysens; Mark Lubberink; Tanja Kero; Marc R Dweck; Gilbert Habib; Oliver Gaemperli; Antti Saraste; Alessia Gimelli; Panagiotis Georgoulias; Hein J Verberne; Jan Bucerius; Christoph Rischpler; Fabien Hyafil; Paola A Erba Journal: Eur J Nucl Med Mol Imaging Date: 2020-10-27 Impact factor: 9.236