OBJECTIVE: To assess diagnostic performance of dual-input CT perfusion for distinguishing malignant from benign solitary pulmonary nodules (SPNs). METHODS: Fifty-six consecutive subjects with SPNs underwent contrast-enhanced 320-row multidetector dynamic volume CT. The dual-input maximum slope CT perfusion analysis was employed to calculate the pulmonary flow (PF), bronchial flow (BF), and perfusion index [Formula: see text]. Differences in perfusion parameters between malignant and benign tumours were assessed with histopathological diagnosis as the gold standard. Diagnostic value of the perfusion parameters was calculated using the receiver-operating characteristic (ROC) curve analysis. RESULTS: Amongst 56 SPNs, statistically significant differences in all three perfusion parameters were revealed between malignant and benign tumours. The PI demonstrated the biggest difference between malignancy and benignancy: 0.30 ± 0.07 vs. 0.51 ± 0.13 , P < 0.001. The area under the PI ROC curve was 0.92, the largest of the three perfusion parameters, producing a sensitivity of 0.95, specificity of 0.83, positive likelihood ratio (+LR) of 5.59, and negative likelihood ratio (-LR) of 0.06 in identifying malignancy. CONCLUSIONS: The PI derived from the dual-input maximum slope CT perfusion analysis is a valuable biomarker for identifying malignancy in SPNs. PI may be potentially useful for lung cancer treatment planning and forecasting the therapeutic effect of radiotherapy treatment. KEY POINTS: • Modern CT equipment offers assessment of vascular parameters of solitary pulmonary nodules (SPNs) • Dual vascular supply was investigated to differentiate malignant from benign SPNs. • Different dual vascular supply patterns were found in malignant and benign SPNs. • The perfusion index is a useful biomarker for differentiate malignancy from benignancy.
OBJECTIVE: To assess diagnostic performance of dual-input CT perfusion for distinguishing malignant from benign solitary pulmonary nodules (SPNs). METHODS: Fifty-six consecutive subjects with SPNs underwent contrast-enhanced 320-row multidetector dynamic volume CT. The dual-input maximum slope CT perfusion analysis was employed to calculate the pulmonary flow (PF), bronchial flow (BF), and perfusion index [Formula: see text]. Differences in perfusion parameters between malignant and benign tumours were assessed with histopathological diagnosis as the gold standard. Diagnostic value of the perfusion parameters was calculated using the receiver-operating characteristic (ROC) curve analysis. RESULTS: Amongst 56 SPNs, statistically significant differences in all three perfusion parameters were revealed between malignant and benign tumours. The PI demonstrated the biggest difference between malignancy and benignancy: 0.30 ± 0.07 vs. 0.51 ± 0.13 , P < 0.001. The area under the PI ROC curve was 0.92, the largest of the three perfusion parameters, producing a sensitivity of 0.95, specificity of 0.83, positive likelihood ratio (+LR) of 5.59, and negative likelihood ratio (-LR) of 0.06 in identifying malignancy. CONCLUSIONS: The PI derived from the dual-input maximum slope CT perfusion analysis is a valuable biomarker for identifying malignancy in SPNs. PI may be potentially useful for lung cancer treatment planning and forecasting the therapeutic effect of radiotherapy treatment. KEY POINTS: • Modern CT equipment offers assessment of vascular parameters of solitary pulmonary nodules (SPNs) • Dual vascular supply was investigated to differentiate malignant from benign SPNs. • Different dual vascular supply patterns were found in malignant and benign SPNs. • The perfusion index is a useful biomarker for differentiate malignancy from benignancy.
Authors: Bruno Hochhegger; Matheus Zanon; Stephan Altmayer; Gabriel S Pacini; Fernanda Balbinot; Martina Z Francisco; Ruhana Dalla Costa; Guilherme Watte; Marcel Koenigkam Santos; Marcelo C Barros; Diana Penha; Klaus Irion; Edson Marchiori Journal: Lung Date: 2018-10-09 Impact factor: 2.584
Authors: J de Castro; M Cobo; D Isla; J Puente; N Reguart; B Cabeza; A Gayete; M Sánchez; M I Torres; J Ferreirós Journal: Clin Transl Oncol Date: 2014-11-06 Impact factor: 3.405
Authors: Florent L Besson; Brice Fernandez; Sylvain Faure; Olaf Mercier; Andrei Seferian; Xavier Mignard; Sacha Mussot; Cecile le Pechoux; Caroline Caramella; Angela Botticella; Antonin Levy; Florence Parent; Sophie Bulifon; David Montani; Delphine Mitilian; Elie Fadel; David Planchard; Benjamin Besse; Maria-Rosa Ghigna-Bellinzoni; Claude Comtat; Vincent Lebon; Emmanuel Durand Journal: EJNMMI Res Date: 2020-07-30 Impact factor: 3.138