Qi Wang1, Gaofeng Shi2, Xiaohui Qi3, Xueli Fan4, Lijia Wang5. 1. Department of Radiology, The Fourth Clinical Hospital of Hebei Medical University, Shijiazhuang, Hebei 050011, China. Electronic address: wq20@hotmail.com. 2. Department of Radiology, The Fourth Clinical Hospital of Hebei Medical University, Shijiazhuang, Hebei 050011, China. Electronic address: gaofengs62@sina.com. 3. Department of Radiology, The Fourth Clinical Hospital of Hebei Medical University, Shijiazhuang, Hebei 050011, China. Electronic address: qixiaohui1984@163.com. 4. Department of Radiology, The Fourth Clinical Hospital of Hebei Medical University, Shijiazhuang, Hebei 050011, China. Electronic address: 407849960@qq.com. 5. Department of Radiology, The Fourth Clinical Hospital of Hebei Medical University, Shijiazhuang, Hebei 050011, China. Electronic address: 893197597@qq.com.
Abstract
OBJECTIVE: To assess the usefulness of the spectral curve slope of dual-energy CT (DECT) for differentiating between hepatocellular carcinoma (HCC), hepatic metastasis, hemangioma (HH) and cysts. METHODS: In total, 121 patients were imaged in the portal venous phase using dual-energy mode. Of these patients, 23 patients had HH, 28 patients had HCC, 40 patients had metastases and 30 patients had simple cysts. The spectral curves of the hepatic lesions were derived from the 40-190 keV levels of virtual monochromatic spectral imaging. The spectral curve slopes were calculated from 40 to 110 keV. The slopes were compared using the Kruskal-Wallis test. Receiver operating characteristic curves (ROC) were used to determine the optimal cut-off value of the slope of the spectral curve to differentiate between the lesions. RESULTS: The spectral curves of the four lesion types had different baseline levels. The HH baseline level was the highest followed by HCC, metastases and cysts. The slopes of the spectral curves of HH, HCC, metastases and cysts were 3.81 ± 1.19, 1.49 ± 0.57, 1.06 ± 0.76 and 0.13 ± 0.17, respectively. These values were significantly different (P<0.008). Based on ROC analysis, the respective diagnostic sensitivity and specificity were 87% and 100% for hemangioma (cut-off value ≥ 2.988), 82.1% and 65.9% for HCC (cut-off value 1.167-2.998), 65.9% and 59% for metastasis (cut-off value 0.133-1.167) and 44.4% and 100% for cysts (cut-off value ≤ 0.133). CONCLUSION: Quantitative analysis of the DECT spectral curve in the portal venous phase can be used to determine whether tumors are benign or malignant.
OBJECTIVE: To assess the usefulness of the spectral curve slope of dual-energy CT (DECT) for differentiating between hepatocellular carcinoma (HCC), hepatic metastasis, hemangioma (HH) and cysts. METHODS: In total, 121 patients were imaged in the portal venous phase using dual-energy mode. Of these patients, 23 patients had HH, 28 patients had HCC, 40 patients had metastases and 30 patients had simple cysts. The spectral curves of the hepatic lesions were derived from the 40-190 keV levels of virtual monochromatic spectral imaging. The spectral curve slopes were calculated from 40 to 110 keV. The slopes were compared using the Kruskal-Wallis test. Receiver operating characteristic curves (ROC) were used to determine the optimal cut-off value of the slope of the spectral curve to differentiate between the lesions. RESULTS: The spectral curves of the four lesion types had different baseline levels. The HH baseline level was the highest followed by HCC, metastases and cysts. The slopes of the spectral curves of HH, HCC, metastases and cysts were 3.81 ± 1.19, 1.49 ± 0.57, 1.06 ± 0.76 and 0.13 ± 0.17, respectively. These values were significantly different (P<0.008). Based on ROC analysis, the respective diagnostic sensitivity and specificity were 87% and 100% for hemangioma (cut-off value ≥ 2.988), 82.1% and 65.9% for HCC (cut-off value 1.167-2.998), 65.9% and 59% for metastasis (cut-off value 0.133-1.167) and 44.4% and 100% for cysts (cut-off value ≤ 0.133). CONCLUSION: Quantitative analysis of the DECT spectral curve in the portal venous phase can be used to determine whether tumors are benign or malignant.
Authors: Rivka Kessner; Nils Große Hokamp; Les Ciancibello; Nikhil Ramaiya; Karin A Herrmann Journal: Br J Radiol Date: 2019-05-24 Impact factor: 3.039