Preoperative Evaluation of Hepatocellular Carcinoma Differentiation Using Contrast-Enhanced Ultrasound-Based Deep-Learning Radiomics Model

References

• Forner A, Reig M, Bruix J. Hepatocellular carcinoma. Lancet. 2018;391:1301–1314. doi:10.1016/S0140-6736(18)30010-2
   PubMed Web of Science ®Google Scholar
• Yang JD, Hainaut P, Gores GJ, Amadou A, Plymoth A, Roberts LR. A global view of hepatocellular carcinoma: trends, risk, prevention and management. Nat Rev Gastroenterol Hepatol. 2019;16:589–604. doi:10.1038/s41575-019-0186-y
   PubMed Web of Science ®Google Scholar
• Tabrizian P, Jibara G, Shrager B, Schwartz M, Roayaie S. Recurrence of hepatocellular cancer after resection: patterns, treatments, and prognosis. Ann Surg. 2015;261:947–955. doi:10.1097/SLA.0000000000000710
   PubMed Web of Science ®Google Scholar
• Chen W, Zheng R, Baade PD, et al. Cancer statistics in China, 2015. CA Cancer J Clin. 2016;66:115–132. doi:10.3322/caac.21338
   PubMed Web of Science ®Google Scholar
• Zhou J, Sun HC, Wang Z, et al. 原发性肝癌诊疗规范(2019年版)[Guidelines for diagnosis and treatment of primary liver cancer in China (2019 edition)]. Zhonghua Gan Zang Bing Za Zhi. 2020;28:112–128. Chinese. doi:10.3760/cma.j.issn.1007-3418.2020.02.004
   PubMedGoogle Scholar
• Jonas S, Bechstein WO, Steinmüller T, et al. Vascular invasion and histopathologic grading determine outcome after liver transplantation for hepatocellular carcinoma in cirrhosis. Hepatology. 2001;33:1080–1086. doi:10.1053/jhep.2001.23561
   PubMed Web of Science ®Google Scholar
• Zhou L, Rui JA, Zhou WX, Wang SB, Chen SG, Qu Q. Edmondson-Steiner grade: a crucial predictor of recurrence and survival in hepatocellular carcinoma without microvascular invasion. Pathol Res Pract. 2017;213:824–830. doi:10.1016/j.prp.2017.03.002
   PubMed Web of Science ®Google Scholar
• Sasaki K, Matsuda M, Ohkura Y, et al. In hepatocellular carcinomas, any proportion of poorly differentiated components is associated with poor prognosis after hepatectomy. World J Surg. 2014;38:1147–1153. doi:10.1007/s00268-013-2374-1
   PubMed Web of Science ®Google Scholar
• Vernuccio F, Rosenberg MD, Meyer M, Choudhury KR, Nelson RC, Marin D. Negative biopsy of focal hepatic lesions: decision tree model for patient management. AJR Am J Roentgenol. 2019;212:677–685. doi:10.2214/AJR.18.20268
   PubMed Web of Science ®Google Scholar
• Sato K, Tanaka S, Mitsunori Y, et al. Contrast-enhanced intraoperative ultrasonography for vascular imaging of hepatocellular carcinoma: clinical and biological significance. Hepatology. 2013;57:1436–1447. doi:10.1002/hep.26122
   PubMed Web of Science ®Google Scholar
• Nicolau C, Catalá V, Vilana R, et al. Evaluation of hepatocellular carcinoma using SonoVue, a second generation ultrasound contrast agent: correlation with cellular differentiation. Eur Radiol. 2004;14:1092–1099. doi:10.1007/s00330-004-2298-0
   PubMed Web of Science ®Google Scholar
• Kondo T, Maruyama H, Kiyono S, et al. Intensity-based assessment of microbubble-enhanced ultrasonography: phase-related diagnostic ability for cellular differentiation of hepatocellular carcinoma. Ultrasound Med Biol. 2015;41:3079–3087. doi:10.1016/j.ultrasmedbio.2015.07.033
   PubMed Web of Science ®Google Scholar
• Fan PL, Ding H, Mao F, Chen LL, Dong Y, Wang WP. Enhancement patterns of small hepatocellular carcinoma (≤ 30 mm) on contrast-enhanced ultrasound: correlation with clinicopathologic characteristics. Eur J Radiol. 2020;132:109341. doi:10.1016/j.ejrad.2020.109341
   PubMed Web of Science ®Google Scholar
• von Herbay A, Vogt C, Westendorff J, Häussinger D, Gregor M. Correlation between SonoVue enhancement in CEUS, HCC differentiation and HCC diameter: analysis of 130 patients with hepatocellular carcinoma (HCC). Ultraschall Med. 2009;30:544–550. doi:10.1055/s-0028-1109745
   PubMed Web of Science ®Google Scholar
• Ding Y, Ruan S, Wang Y, et al. Novel deep learning radiomics model for preoperative evaluation of hepatocellular carcinoma differentiation based on computed tomography data. Clin Transl Med. 2021;11:e570. doi:10.1002/ctm2.570
   PubMed Web of Science ®Google Scholar
• Sun K, Zhang J, Liu Z, et al. A deep learning radiomics analysis for identifying sinus invasion in patients with meningioma before operation using tumor and peritumoral regions. Eur J Radiol. 2022;149:110187. doi:10.1016/j.ejrad.2022.110187
   PubMed Web of Science ®Google Scholar
• Bi WL, Hosny A, Schabath MB, et al. Artificial intelligence in cancer imaging: clinical challenges and applications. CA Cancer J Clin. 2019;69:127–157. doi:10.3322/caac.21552
   PubMed Web of Science ®Google Scholar
• Edmondson HA, Steiner PE. Primary carcinoma of the liver: a study of 100 cases among 48,900 necropsies. Cancer. 1954;7:462–503. doi:10.1002/1097-0142(195405)7:3<462::AID-CNCR2820070308>3.0.CO;2-E
   PubMed Web of Science ®Google Scholar
• Radiology ACo. CE US LI-RADS®2017 CORE. Available from: https://www.acr.org/-/media/ACR/Files/RADS/LI-RADS/CEUS-LI-RADS-2017-Core.pdf. Accessed January 31, 2023.
   Google Scholar
• Ramprasaath R, Selvaraju MC, Abhishek D, et al. Grad-CAM: visual explanations from deep networks via gradient-based localization. Proc IEEE Int Conf Computer Vision. 2017;2017 618–626.
   Google Scholar
• Nishie A, Tajima T, Asayama Y, et al. Diagnostic performance of apparent diffusion coefficient for predicting histological grade of hepatocellular carcinoma. Eur J Radiol. 2011;80:e29–33. doi:10.1016/j.ejrad.2010.06.019
   PubMed Web of Science ®Google Scholar
• Iida H, Aihara T, Ikuta S, Yamanaka N. Comparative study of percutaneous radiofrequency ablation and hepatic resection for small, poorly differentiated hepatocellular carcinomas. Hepatol Res. 2014;44:E156–162. doi:10.1111/hepr.12264
   PubMed Web of Science ®Google Scholar
• Ren S, Qi Q, Liu S, et al. Preoperative prediction of pathological grading of hepatocellular carcinoma using machine learning-based ultrasomics: a multicenter study. Eur J Radiol. 2021;143:109891. doi:10.1016/j.ejrad.2021.109891
   PubMed Web of Science ®Google Scholar
• Mao B, Zhang L, Ning P, et al. Preoperative prediction for pathological grade of hepatocellular carcinoma via machine learning-based radiomics. Eur Radiol. 2020;30:6924–6932. doi:10.1007/s00330-020-07056-5
   PubMed Web of Science ®Google Scholar
• He K, Ren XZ, Sun J. Deep residual learning for image recognition. Proc IEEE Confe Computer Vision Pattern Recog. 2016;2016:770–778.
   Google Scholar
• Gu D, Guo D, Yuan C, et al. Multi-scale patches convolutional neural network predicting the histological grade of hepatocellular carcinoma. Annu Int Conf IEEE Eng Med Biol Soc. 2021;2021:2584–2587. doi:10.1109/EMBC46164.2021.9630413
   PubMedGoogle Scholar
• Zhou Q, Zhou Z, Chen C, et al. Grading of hepatocellular carcinoma using 3D SE-DenseNet in dynamic enhanced MR images. Comput Biol Med. 2019;107:47–57. doi:10.1016/j.compbiomed.2019.01.026
   PubMed Web of Science ®Google Scholar
• Gu J, Tong T, He C, et al. Deep learning radiomics of ultrasonography can predict response to neoadjuvant chemotherapy in breast cancer at an early stage of treatment: a prospective study. Eur Radiol. 2022;32:2099–2109. doi:10.1007/s00330-021-08293-y
   PubMed Web of Science ®Google Scholar
• Jiang M, Li CL, Luo XM, et al. Ultrasound-based deep learning radiomics in the assessment of pathological complete response to neoadjuvant chemotherapy in locally advanced breast cancer. Eur J Cancer. 2021;147:95–105. doi:10.1016/j.ejca.2021.01.028
   PubMed Web of Science ®Google Scholar
• Liu F, Liu D, Wang K, et al. Deep learning radiomics based on contrast-enhanced ultrasound might optimize curative treatments for very-early or early-stage hepatocellular carcinoma patients. Liver Cancer. 2020;9:397–413. doi:10.1159/000505694
   PubMed Web of Science ®Google Scholar
• Schaible J, Stroszczynski C, Beyer LP, Jung EM. Quantitative perfusion analysis of hepatocellular carcinoma using dynamic contrast enhanced ultrasound (CEUS) to determine tumor microvascularization. Clin Hemorheol Microcirc. 2019;73:95–104. doi:10.3233/CH-199221
   PubMed Web of Science ®Google Scholar
• Castelvecchi D. Can we open the black box of AI? Nature. 2016;538:20–23. doi:10.1038/538020a
   PubMed Web of Science ®Google Scholar