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Wang K, Zhang S, Zhou W, Wen L, Zhang S, Yu D. Clinical Application of Shear Wave Elastography With Shear Wave Dispersion Imaging in the Preoperative Evaluation of Hepatic Parenchyma in Patients With Liver Tumors. JOURNAL OF ULTRASOUND IN MEDICINE : OFFICIAL JOURNAL OF THE AMERICAN INSTITUTE OF ULTRASOUND IN MEDICINE 2023; 42:797-807. [PMID: 35730210 DOI: 10.1002/jum.16029] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/27/2022] [Revised: 05/10/2022] [Accepted: 05/13/2022] [Indexed: 06/15/2023]
Abstract
OBJECTIVES This study aimed to compare the diagnostic accuracy of shear wave elastography (SWE) with that of shear wave dispersion (SWD) in evaluation of hepatic parenchyma in patients with liver tumors before resection. METHODS A total of 174 patients with liver tumors were prospectively enrolled. SWE and SWD examinations were performed. Fibrosis stage and necroinflammatory activity were determined histopathologically according to the Scheuer standard. We compared the diagnostic accuracy of SWE and SWD. RESULTS Both SWE and SWD values of the liver were highly correlated with liver fibrosis stage (P < .05, respectively). Both SWE and SWD values of the liver were moderately correlated with necroinflammatory activity (P < .05, respectively). Both SWE and SWD values of the liver were not correlated with steatosis (P > .05, respectively). Both SWE and SWD values were significantly different among the patients with different stages of liver fibrosis (P < .001, respectively). The area under the receiver operating characteristic (ROC) curve of SWE value was 0.982, 0.977, 0.969, and 0.984 for predicting S ≥ 1, S ≥ 2, S ≥ 3, and S = 4, respectively. The optimal cutoff SWE values were 6.9, 7.9, 8.7, and 10.6 kPa for S ≥ 1, S ≥ 2, S ≥ 3, and S = 4, respectively. The area under the ROC curve of SWD value was 0.967, 0.960, 0.925, and 0.954 for predicting S ≥ 1, S ≥ 2, S ≥ 3, and S = 4, respectively. The optimal cutoff SWD values were 11.2, 12.0, 13.2, and 16.0 m/s/kHz for S ≥ 1, S ≥ 2, S ≥ 3, and S = 4, respectively. CONCLUSIONS SWE and SWD could be noninvasive and accurate for predicting the stage of liver fibrosis in patients with liver tumors before surgery. SWE was more accurate than SWD in predicting severe fibrosis (S ≥ 3) and cirrhosis (S = 4).
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Affiliation(s)
- Kun Wang
- Department of Ultrasound, The Affiliated Hospital of Binzhou Medical University, Binzhou, China
| | - Shuchen Zhang
- Department of Ultrasound, Yancheng City, No. 1 People' s Hospital, Yancheng, China
| | - Wenyan Zhou
- Department of Ultrasound, Yancheng City, No. 1 People' s Hospital, Yancheng, China
| | - Li Wen
- Function, The Special Care Hospital of Hebei Province, Shijiazhuang, China
| | - Shanshan Zhang
- Department of Ultrasound, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Dong Yu
- Department of Ultrasound, North China Medical Treatment Health Group, Fengfeng General Hospital, Handan, China
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Sugimoto K, Moriyasu F, Oshiro H, Takeuchi H, Abe M, Yoshimasu Y, Kasai Y, Sakamaki K, Hara T, Itoi T. The Role of Multiparametric US of the Liver for the Evaluation of Nonalcoholic Steatohepatitis. Radiology 2020; 296:532-540. [PMID: 32573385 DOI: 10.1148/radiol.2020192665] [Citation(s) in RCA: 141] [Impact Index Per Article: 28.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
Abstract
Background Nonalcoholic steatohepatitis (NASH) is diagnosed with histopathologic testing, but noninvasive surrogate markers are desirable for screening patients who are at high risk of NASH. Purpose To investigate the diagnostic performance of dispersion slope, attenuation coefficient, and shear-wave speed measurements obtained using two-dimensional (2D) shear-wave elastography (SWE) in assessing inflammation, steatosis, and fibrosis and in the noninvasive diagnosis of NASH in patients suspected of having nonalcoholic fatty liver disease (NAFLD). Materials and Methods This prospective study collected data from 120 consecutive adults who underwent liver biopsy for suspected NAFLD and were enrolled between April 2017 and March 2019. Three US parameters (dispersion slope [(m/sec)/kHz], attenuation coefficient [dB/cm/MHz], and shear-wave speed [in meters per second]) were measured using a 2D SWE system immediately before biopsy. The biopsy specimens were scored by one expert pathologist according to the Nonalcoholic Steatohepatitis Clinical Research Network criteria (119 participants underwent a histologic examination). Diagnostic performance was assessed using the area under the receiver operating characteristic curve (AUC) for the categories of inflammation, steatosis, and fibrosis. Results One hundred eleven adults (mean age, 53 years ± 18 [standard deviation]; 57 men) underwent a US examination. Dispersion slope enabled the identification of lobular inflammation, with an AUC of 0.95 (95% confidence interval [CI]: 0.91, 0.10) for an inflammation grade greater than or equal to A1 (mild), 0.81 (95% CI: 0.72, 0.89) for an inflammation grade greater than or equal to A2 (moderate), and 0.85 (95% CI: 0.74, 0.97) for an inflammation grade equal to A3 (marked). Attenuation coefficient enabled the identification of steatosis, with an AUC of 0.88 (95% CI: 0.80, 0.97) for steatosis grade greater than or equal to S1 (mild), 0.86 (95% CI: 0.79, 0.93) for steatosis grade greater than or equal to S2 (moderate), and 0.79 (95% CI: 0.68, 0.89) for steatosis grade equal to S3 (severe). Shear-wave speed enabled the identification of fibrosis, with an AUC of 0.79 (95% CI: 0.69, 0.88) for fibrosis stage greater than or equal to F1 (portal fibrosis), 0.88 (95% CI: 0.82, 0.94) for fibrosis stage greater than or equal to F2 (periportal fibrosis), 0.90 (95% CI: 0.84, 0.96) for fibrosis stage greater than or equal to F3 (septal fibrosis), and 0.95 (95% CI: 0.91, 0.99) for fibrosis stage equal to F4 (cirrhosis). The combination of dispersion slope, attenuation coefficient, and shear-wave speed showed an AUC of 0.81 (95% CI: 0.71, 0.91) for the diagnosis of NASH. Conclusion Dispersion slope, attenuation coefficient, and shear-wave speed were found to be useful for assessing lobular inflammation, steatosis, and fibrosis, respectively, in participants with biopsy-proven nonalcoholic fatty liver disease. © RSNA, 2020 Online supplemental material is available for this article.
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Affiliation(s)
- Katsutoshi Sugimoto
- From the Department of Gastroenterology and Hepatology, Tokyo Medical University, 6-7-1 Nishishinjuku, Shinjuku-ku, Tokyo 160-0023, Japan (K. Sugimoto, H.T., M.A., Y.Y., Y.K., T.I.); Department of Pathology, Jichi Medical University, Tochigi, Japan (H.O.); Center for Data Science, Yokohama City University, Kanagawa, Japan (K. Sakamaki); Department of Gastroenterology and Hepatology, International University of Health and Welfare, Sanno Hospital, Tokyo, Japan (F.M.); and Department of Electrical, Electronic and Computer Engineering, Faculty of Engineering, Gifu University, Gifu, Japan (T.H.)
| | - Fuminori Moriyasu
- From the Department of Gastroenterology and Hepatology, Tokyo Medical University, 6-7-1 Nishishinjuku, Shinjuku-ku, Tokyo 160-0023, Japan (K. Sugimoto, H.T., M.A., Y.Y., Y.K., T.I.); Department of Pathology, Jichi Medical University, Tochigi, Japan (H.O.); Center for Data Science, Yokohama City University, Kanagawa, Japan (K. Sakamaki); Department of Gastroenterology and Hepatology, International University of Health and Welfare, Sanno Hospital, Tokyo, Japan (F.M.); and Department of Electrical, Electronic and Computer Engineering, Faculty of Engineering, Gifu University, Gifu, Japan (T.H.)
| | - Hisashi Oshiro
- From the Department of Gastroenterology and Hepatology, Tokyo Medical University, 6-7-1 Nishishinjuku, Shinjuku-ku, Tokyo 160-0023, Japan (K. Sugimoto, H.T., M.A., Y.Y., Y.K., T.I.); Department of Pathology, Jichi Medical University, Tochigi, Japan (H.O.); Center for Data Science, Yokohama City University, Kanagawa, Japan (K. Sakamaki); Department of Gastroenterology and Hepatology, International University of Health and Welfare, Sanno Hospital, Tokyo, Japan (F.M.); and Department of Electrical, Electronic and Computer Engineering, Faculty of Engineering, Gifu University, Gifu, Japan (T.H.)
| | - Hirohito Takeuchi
- From the Department of Gastroenterology and Hepatology, Tokyo Medical University, 6-7-1 Nishishinjuku, Shinjuku-ku, Tokyo 160-0023, Japan (K. Sugimoto, H.T., M.A., Y.Y., Y.K., T.I.); Department of Pathology, Jichi Medical University, Tochigi, Japan (H.O.); Center for Data Science, Yokohama City University, Kanagawa, Japan (K. Sakamaki); Department of Gastroenterology and Hepatology, International University of Health and Welfare, Sanno Hospital, Tokyo, Japan (F.M.); and Department of Electrical, Electronic and Computer Engineering, Faculty of Engineering, Gifu University, Gifu, Japan (T.H.)
| | - Masakazu Abe
- From the Department of Gastroenterology and Hepatology, Tokyo Medical University, 6-7-1 Nishishinjuku, Shinjuku-ku, Tokyo 160-0023, Japan (K. Sugimoto, H.T., M.A., Y.Y., Y.K., T.I.); Department of Pathology, Jichi Medical University, Tochigi, Japan (H.O.); Center for Data Science, Yokohama City University, Kanagawa, Japan (K. Sakamaki); Department of Gastroenterology and Hepatology, International University of Health and Welfare, Sanno Hospital, Tokyo, Japan (F.M.); and Department of Electrical, Electronic and Computer Engineering, Faculty of Engineering, Gifu University, Gifu, Japan (T.H.)
| | - Yu Yoshimasu
- From the Department of Gastroenterology and Hepatology, Tokyo Medical University, 6-7-1 Nishishinjuku, Shinjuku-ku, Tokyo 160-0023, Japan (K. Sugimoto, H.T., M.A., Y.Y., Y.K., T.I.); Department of Pathology, Jichi Medical University, Tochigi, Japan (H.O.); Center for Data Science, Yokohama City University, Kanagawa, Japan (K. Sakamaki); Department of Gastroenterology and Hepatology, International University of Health and Welfare, Sanno Hospital, Tokyo, Japan (F.M.); and Department of Electrical, Electronic and Computer Engineering, Faculty of Engineering, Gifu University, Gifu, Japan (T.H.)
| | - Yoshitaka Kasai
- From the Department of Gastroenterology and Hepatology, Tokyo Medical University, 6-7-1 Nishishinjuku, Shinjuku-ku, Tokyo 160-0023, Japan (K. Sugimoto, H.T., M.A., Y.Y., Y.K., T.I.); Department of Pathology, Jichi Medical University, Tochigi, Japan (H.O.); Center for Data Science, Yokohama City University, Kanagawa, Japan (K. Sakamaki); Department of Gastroenterology and Hepatology, International University of Health and Welfare, Sanno Hospital, Tokyo, Japan (F.M.); and Department of Electrical, Electronic and Computer Engineering, Faculty of Engineering, Gifu University, Gifu, Japan (T.H.)
| | - Kentaro Sakamaki
- From the Department of Gastroenterology and Hepatology, Tokyo Medical University, 6-7-1 Nishishinjuku, Shinjuku-ku, Tokyo 160-0023, Japan (K. Sugimoto, H.T., M.A., Y.Y., Y.K., T.I.); Department of Pathology, Jichi Medical University, Tochigi, Japan (H.O.); Center for Data Science, Yokohama City University, Kanagawa, Japan (K. Sakamaki); Department of Gastroenterology and Hepatology, International University of Health and Welfare, Sanno Hospital, Tokyo, Japan (F.M.); and Department of Electrical, Electronic and Computer Engineering, Faculty of Engineering, Gifu University, Gifu, Japan (T.H.)
| | - Takeshi Hara
- From the Department of Gastroenterology and Hepatology, Tokyo Medical University, 6-7-1 Nishishinjuku, Shinjuku-ku, Tokyo 160-0023, Japan (K. Sugimoto, H.T., M.A., Y.Y., Y.K., T.I.); Department of Pathology, Jichi Medical University, Tochigi, Japan (H.O.); Center for Data Science, Yokohama City University, Kanagawa, Japan (K. Sakamaki); Department of Gastroenterology and Hepatology, International University of Health and Welfare, Sanno Hospital, Tokyo, Japan (F.M.); and Department of Electrical, Electronic and Computer Engineering, Faculty of Engineering, Gifu University, Gifu, Japan (T.H.)
| | - Takao Itoi
- From the Department of Gastroenterology and Hepatology, Tokyo Medical University, 6-7-1 Nishishinjuku, Shinjuku-ku, Tokyo 160-0023, Japan (K. Sugimoto, H.T., M.A., Y.Y., Y.K., T.I.); Department of Pathology, Jichi Medical University, Tochigi, Japan (H.O.); Center for Data Science, Yokohama City University, Kanagawa, Japan (K. Sakamaki); Department of Gastroenterology and Hepatology, International University of Health and Welfare, Sanno Hospital, Tokyo, Japan (F.M.); and Department of Electrical, Electronic and Computer Engineering, Faculty of Engineering, Gifu University, Gifu, Japan (T.H.)
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