Hesong Shen1, Xiaoqian Yuan1, Daihong Liu1, Yuanying Huang2, Yu Wang1, Shixi Jiang1, Jiuquan Zhang3. 1. Department of Radiology, Chongqing University Cancer Hospital & Chongqing Cancer Institute & Chongqing Cancer Hospital, No. 181 Hanyu Road, Shapingba District, Chongqing, 400030, PR China. 2. Department of Oncology and Hematology, Chongqing General Hospital, No. 104 Pipashan Street, Yuzhong District, Chongqing, 400014, PR China. 3. Department of Radiology, Chongqing University Cancer Hospital & Chongqing Cancer Institute & Chongqing Cancer Hospital, No. 181 Hanyu Road, Shapingba District, Chongqing, 400030, PR China. Electronic address: zhangjq_radiol@foxmail.com.
Abstract
OBJECTIVES: To determine the optimal kiloelectron volt of noise-optimized virtual monoenergetic images [VMI (+)] for visualization of nasopharyngeal carcinoma (NPC) and nasopharyngeal lymphoma (NPL), and to explore the clinical value of quantitative parameters derived from dual-energy computed tomography (DECT) for distinguishing the two entities. MATERIALS AND METHODS: Eighty patients including 51 with NPC and 29 with NPL were enrolled. The VMIs (+) at 40-80 keV with an interval of 10 keV were reconstructed by contrast enhanced images. The overall image quality and demarcation of lesion margins, signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) were assessed in VMIs (+) and polyenergetic images (PEI). Normalized iodine concentration (NIC), slope of the spectral Hounsfield unit curve (λHU) and effective atomic number (Zeff) were calculated. Diagnostic performance was assessed by receiver operating characteristic (ROC) curve. RESULTS: The 40 keV VMI (+) yielded highest overall image quality scores, demarcation of lesion margins scores, SNR and CNR. The values of NIC, λHU and Zeff in NPL were higher than those in NPC (P < 0.001). Multivariate logistic regression model combining NIC, λHU and Zeff showed the best performance for distinguishing NPC from NPL (AUC: 0.947, sensitivity: 93.1 % and specificity: 92.2 %). CONCLUSION: VMI (+) reconstruction at 40 keV was optimal for visualizing NPC and NPL. Quantitative parameters derived from DECT were helpful for differentiating NPC from NPL.
OBJECTIVES: To determine the optimal kiloelectron volt of noise-optimized virtual monoenergetic images [VMI (+)] for visualization of nasopharyngeal carcinoma (NPC) and nasopharyngeal lymphoma (NPL), and to explore the clinical value of quantitative parameters derived from dual-energy computed tomography (DECT) for distinguishing the two entities. MATERIALS AND METHODS: Eighty patients including 51 with NPC and 29 with NPL were enrolled. The VMIs (+) at 40-80 keV with an interval of 10 keV were reconstructed by contrast enhanced images. The overall image quality and demarcation of lesion margins, signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) were assessed in VMIs (+) and polyenergetic images (PEI). Normalized iodine concentration (NIC), slope of the spectral Hounsfield unit curve (λHU) and effective atomic number (Zeff) were calculated. Diagnostic performance was assessed by receiver operating characteristic (ROC) curve. RESULTS: The 40 keV VMI (+) yielded highest overall image quality scores, demarcation of lesion margins scores, SNR and CNR. The values of NIC, λHU and Zeff in NPL were higher than those in NPC (P < 0.001). Multivariate logistic regression model combining NIC, λHU and Zeff showed the best performance for distinguishing NPC from NPL (AUC: 0.947, sensitivity: 93.1 % and specificity: 92.2 %). CONCLUSION: VMI (+) reconstruction at 40 keV was optimal for visualizing NPC and NPL. Quantitative parameters derived from DECT were helpful for differentiating NPC from NPL.