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Multimodality CT Imaging Contributes to Improving the Diagnostic Accuracy of Solitary Pulmonary Nodules: A Multi-institutional and Prospective Study

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Abstract Background Solitary pulmonary nodules (SPNs) are one of the most common chest computed tomography (CT) abnormalities clinically. We aimed to investigate the value of non-contrast enhanced CT (NECT), contrast… Click to show full abstract

Abstract Background Solitary pulmonary nodules (SPNs) are one of the most common chest computed tomography (CT) abnormalities clinically. We aimed to investigate the value of non-contrast enhanced CT (NECT), contrast enhanced CT (CECT), CT perfusion imaging (CTPI), and dual- energy CT (DECT) used for differentiating benign and malignant SPNs with a multi-institutional and prospective study. Patients and methods Patients with 285 SPNs were scanned with NECT, CECT, CTPI and DECT. Differences between the benign and malignant SPNs on NECT, CECT, CTPI, and DECT used separately (NECT combined with CECT, DECT, and CTPI were methods of A, B, and C) or in combination (Method A + B, A + C, B + C, and A + B + C) were compared by receiver operating characteristic curve analysis. Results Multimodality CT imaging showed higher performances (sensitivities of 92.81% to 97.60%, specificities of 74.58% to 88.14%, and accuracies of 86.32% to 93.68%) than those of single modality CT imaging (sensitivities of 83.23% to 85.63%, specificities of 63.56% to 67.80%, and accuracies of 75.09% to 78.25%, all p < 0.05). Conclusions SPNs evaluated with multimodality CT imaging contributes to improving the diagnostic accuracy of benign and malignant SPNs. NECT helps to locate and evaluate the morphological characteristics of SPNs. CECT helps to evaluate the vascularity of SPNs. CTPI using parameter of permeability surface and DECT using parameter of normalized iodine concentration at the venous phase both are helpful for improving the diagnostic performance.

Keywords: multimodality imaging; solitary pulmonary; dect; improving diagnostic; pulmonary nodules

Journal Title: Radiology and Oncology
Year Published: 2023

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