Dong Ho Lee1,2, Eun Sun Lee3,4, Jae Seok Bae1, Jae Young Lee5,6,7, Joon Koo Han1,2,8, Nam-Joon Yi9, Kwang-Woong Lee9, Kyung-Suk Suh9, Haeryoung Kim10, Kyung Bun Lee10, Byung Ihn Choi3. 1. Department of Radiology, Seoul National University Hospital, 101 Daehakro, Jongno-gu, Seoul, 03080, South Korea. 2. Institute of Radiation Medicine, Seoul National University Medical Research Center, Seoul, South Korea. 3. Department of Radiology, Chung-Ang University Hospital, Seoul, South Korea. 4. Department of Radiology, Chung-Ang University College of Medicine, Seoul, South Korea. 5. Department of Radiology, Seoul National University Hospital, 101 Daehakro, Jongno-gu, Seoul, 03080, South Korea. leejy4u@gmail.com. 6. Institute of Radiation Medicine, Seoul National University Medical Research Center, Seoul, South Korea. leejy4u@gmail.com. 7. Department of Radiology, Seoul National University College of Medicine, Seoul, South Korea. leejy4u@gmail.com. 8. Department of Radiology, Seoul National University College of Medicine, Seoul, South Korea. 9. Department of Surgery, Seoul National University College of Medicine, Seoul, South Korea. 10. Department of Pathology, Seoul National University College of Medicine, Seoul, South Korea.
Abstract
OBJECTIVES: Both transient elastography (TE) and 2D shear wave elastography (SWE) are accurate methods to evaluate liver fibrosis. We aimed to evaluate the diagnostic performance of 2D-SWE in predicting post-hepatectomy complication and to compare it with TE. METHODS: We prospectively enrolled 125 patients with liver tumors. Liver stiffness (LS) (kilopascal [kPa]) was measured using both TE and 2D-SWE before surgery. All post-operative complication was evaluated using the comprehensive complication index (CCI), and CCI ≥ 26.2 was defined as severe complication. Logistic regression analysis was performed to identify predictive factors for severe complication. Receiver operating characteristic analysis was used to evaluate the diagnostic performance of TE/2D-SWE in detecting liver fibrosis and severe complication. RESULTS: Severe complication developed in 18 patients. The median LS in patients with severe complication was significantly higher for both 2D-SWE (11.4 kPa vs. 7.0 kPa, p < 0.001) and TE (8.9 kPa vs. 6.2 kPa, p = 0.009). LS obtained from 2D-SWE was a significant factor correlated with severe complication (odds ratio: 1.27 per kPa [1.10-1.46], p = 0.001). The diagnostic performance of 2D-SWE was significantly higher than that of TE in detecting both ≥F3 (p = 0.024) and F4 (p = 0.048). The area under the curve of 2D-SWE to predict severe complication was 0.854, significantly higher than 0.692 of TE (p = 0.004). The optimal cut-off LS from 2D-SWE to predict severe complication was 8.6 kPa, with sensitivity of 88.9% (16/18) and specificity of 73.8% (79/107). CONCLUSION: LS obtained from 2D-SWE was a significant predictive factor for severe complication, and 2D-SWE showed significantly a better diagnostic performance than TE in detecting liver fibrosis and severe complication. KEY POINTS: • The diagnostic performance of 2D-SWE was significantly higher than that of TE in detecting both ≥ F3 (AUC: 0.853 vs. 0.779, p = 0.024) and F4 (AUC: 0.929 vs. 0.872, p = 0.048). • Liver stiffness value obtained from 2D-SWE was a significant factor correlated with the development of severe complication defined as CCI ≥ 26.2 after hepatic resection for liver tumors (odds ratio: 1.27 per kPa [1.10-1.46], p = 0.001). • 2D-SWE provided significantly a better diagnostic performance in predicting severe complication after hepatic resection than TE (AUC for 2D-SWE: 0.853 vs. AUC for TE: 0.692, p = 0.004).
OBJECTIVES: Both transient elastography (TE) and 2D shear wave elastography (SWE) are accurate methods to evaluate liver fibrosis. We aimed to evaluate the diagnostic performance of 2D-SWE in predicting post-hepatectomy complication and to compare it with TE. METHODS: We prospectively enrolled 125 patients with liver tumors. Liver stiffness (LS) (kilopascal [kPa]) was measured using both TE and 2D-SWE before surgery. All post-operative complication was evaluated using the comprehensive complication index (CCI), and CCI ≥ 26.2 was defined as severe complication. Logistic regression analysis was performed to identify predictive factors for severe complication. Receiver operating characteristic analysis was used to evaluate the diagnostic performance of TE/2D-SWE in detecting liver fibrosis and severe complication. RESULTS: Severe complication developed in 18 patients. The median LS in patients with severe complication was significantly higher for both 2D-SWE (11.4 kPa vs. 7.0 kPa, p < 0.001) and TE (8.9 kPa vs. 6.2 kPa, p = 0.009). LS obtained from 2D-SWE was a significant factor correlated with severe complication (odds ratio: 1.27 per kPa [1.10-1.46], p = 0.001). The diagnostic performance of 2D-SWE was significantly higher than that of TE in detecting both ≥F3 (p = 0.024) and F4 (p = 0.048). The area under the curve of 2D-SWE to predict severe complication was 0.854, significantly higher than 0.692 of TE (p = 0.004). The optimal cut-off LS from 2D-SWE to predict severe complication was 8.6 kPa, with sensitivity of 88.9% (16/18) and specificity of 73.8% (79/107). CONCLUSION: LS obtained from 2D-SWE was a significant predictive factor for severe complication, and 2D-SWE showed significantly a better diagnostic performance than TE in detecting liver fibrosis and severe complication. KEY POINTS: • The diagnostic performance of 2D-SWE was significantly higher than that of TE in detecting both ≥ F3 (AUC: 0.853 vs. 0.779, p = 0.024) and F4 (AUC: 0.929 vs. 0.872, p = 0.048). • Liver stiffness value obtained from 2D-SWE was a significant factor correlated with the development of severe complication defined as CCI ≥ 26.2 after hepatic resection for liver tumors (odds ratio: 1.27 per kPa [1.10-1.46], p = 0.001). • 2D-SWE provided significantly a better diagnostic performance in predicting severe complication after hepatic resection than TE (AUC for 2D-SWE: 0.853 vs. AUC for TE: 0.692, p = 0.004).
Authors: Christoph F Dietrich; Jeffrey Bamber; Annalisa Berzigotti; Simona Bota; Vito Cantisani; Laurent Castera; David Cosgrove; Giovanna Ferraioli; Mireen Friedrich-Rust; Odd Helge Gilja; Ruediger Stephan Goertz; Thomas Karlas; Robert de Knegt; Victor de Ledinghen; Fabio Piscaglia; Bogdan Procopet; Adrian Saftoiu; Paul S Sidhu; Ioan Sporea; Maja Thiele Journal: Ultraschall Med Date: 2017-04-13 Impact factor: 6.548