Kyungsun Nam1, Young Joo Suh1, Kyunghwa Han1, Sang Joon Park2, Young Jin Kim1, Byoung Wook Choi1. 1. Department of Radiology, Research Institute of Radiological Science, Severance Hospital, Yonsei University College of Medicine, Seoul, Korea (K.N., Y.J.S., K.H., Y.J.K., B.W.C.). 2. Department of Radiology, Seoul National University College of Medicine, Seoul National University, Korea (S.J.P.).
Abstract
BACKGROUND: We aimed to determine whether quantitative computed tomography radiomic features can aid in differentiating between the causes of prosthetic valve obstruction (PVO) in patients who had undergone prosthetic valve replacement. METHODS: This retrospective study included 39 periprosthetic masses in 34 patients who underwent cardiac computed tomography scan from January 2014 to August 2017 and were clinically suspected as PVO. The cause of PVO was assessed by redo-surgery and follow-up imaging as standard reference, and classified as pannus, thrombus, or vegetation. Visual analysis was performed to assess the possible cause of PVO on axial and valve-dedicated views. Computed tomography radiomic analysis of periprosthetic masses was performed and radiomic features were extracted. The advantage of radiomic score compared with visual analysis for differentiation of pannus from other abnormalities was assessed. RESULTS: Of 39 masses, there were 20 cases of pannus, 11 of thrombus, and 8 of vegetation on final diagnosis. The radiomic score was significantly higher in the pannus group compared with nonpannus group (mean, -0.156±0.422 versus -0.883±0.474; P<0.001). The area under the curve of radiomic score for diagnosis of pannus was 0.876 (95% CI, 0.731-0.960). Combination of radiomic score and visual analysis showed a better performance for the differentiation of pannus than visual analysis alone. CONCLUSIONS: Compared with visual analysis, computed tomography radiomic features may have added value for differentiating pannus from thrombus or vegetation in patients with suspected PVO.
BACKGROUND: We aimed to determine whether quantitative computed tomography radiomic features can aid in differentiating between the causes of prosthetic valve obstruction (PVO) in patients who had undergone prosthetic valve replacement. METHODS: This retrospective study included 39 periprosthetic masses in 34 patients who underwent cardiac computed tomography scan from January 2014 to August 2017 and were clinically suspected as PVO. The cause of PVO was assessed by redo-surgery and follow-up imaging as standard reference, and classified as pannus, thrombus, or vegetation. Visual analysis was performed to assess the possible cause of PVO on axial and valve-dedicated views. Computed tomography radiomic analysis of periprosthetic masses was performed and radiomic features were extracted. The advantage of radiomic score compared with visual analysis for differentiation of pannus from other abnormalities was assessed. RESULTS: Of 39 masses, there were 20 cases of pannus, 11 of thrombus, and 8 of vegetation on final diagnosis. The radiomic score was significantly higher in the pannus group compared with nonpannus group (mean, -0.156±0.422 versus -0.883±0.474; P<0.001). The area under the curve of radiomic score for diagnosis of pannus was 0.876 (95% CI, 0.731-0.960). Combination of radiomic score and visual analysis showed a better performance for the differentiation of pannus than visual analysis alone. CONCLUSIONS: Compared with visual analysis, computed tomography radiomic features may have added value for differentiating pannus from thrombus or vegetation in patients with suspected PVO.
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Authors: Riemer H J A Slart; Michelle C Williams; Luis Eduardo Juarez-Orozco; Christoph Rischpler; Marc R Dweck; Andor W J M Glaudemans; Alessia Gimelli; Panagiotis Georgoulias; Olivier Gheysens; Oliver Gaemperli; Gilbert Habib; Roland Hustinx; Bernard Cosyns; Hein J Verberne; Fabien Hyafil; Paola A Erba; Mark Lubberink; Piotr Slomka; Ivana Išgum; Dimitris Visvikis; Márton Kolossváry; Antti Saraste Journal: Eur J Nucl Med Mol Imaging Date: 2021-04-17 Impact factor: 9.236