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Research Article

A radiomics nomogram model for predicting prognosis of pancreatic ductal adenocarcinoma after high-intensity focused ultrasound surgery

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Article: 2184397 | Received 24 Nov 2022, Accepted 20 Feb 2023, Published online: 08 Mar 2023

References

  • Mcguigan A, Kelly P, Turkington RC, et al. Pancreatic cancer: a review of clinical diagnosis, epidemiology, treatment and outcomes. World J Gastroenterol. 2018;24(43):4846–4861.
  • Ilic M, Ilic I. Epidemiology of pancreatic cancer. World J Gastroenterol. 2016;22(44):9694–9705.
  • Vincent A, Herman J, Schulick R, et al. Pancreatic cancer. Lancet. 2011;378(9791):607–620.
  • VON Hoff DD, Ervin T, Arena FP, et al. Increased survival in pancreatic cancer with nab-paclitaxel plus gemcitabine. N Engl J Med. 2013;369(18):1691–1703.
  • VAN DEN Bijgaart RJ, Eikelenboom DC, Hoogenboom M, et al. Thermal and mechanical high-intensity focused ultrasound: perspectives on tumor ablation, immune effects and combination strategies. Cancer Immunol Immunother. 2017;66(2):247–258.
  • Mihcin S, Melzer A. Principles of focused ultrasound. Minim Invasive Ther Allied Technol. 2018;27(1):41–50.
  • Tao SF, Gu WH, Gu JC, et al. A retrospective case series of high-intensity focused ultrasound (HIFU) in combination with gemcitabine and oxaliplatin (Gemox) on treating elderly middle and advanced pancreatic cancer. OncoTargets Ther. 2019;12:9735–9745.
  • Li CC, Wang YQ, Li YP, et al. High-intensity focused ultrasound for treatment of pancreatic cancer: a systematic review. J Evid Based Med. 2014;7(4):270–281.
  • Xiaoping L, Leizhen Z. Advances of high intensity focused ultrasound (HIFU) for pancreatic cancer. Int J Hyperthermia. 2013;29(7):678–682.
  • Ren S, Zhao R, Zhang J, et al. Diagnostic accuracy of unenhanced CT texture analysis to differentiate mass-forming pancreatitis from pancreatic ductal adenocarcinoma. Abdom Radiol. 2020;45(5):1524–1533.
  • Guo C, Zhuge X, Wang Q, et al. The differentiation of pancreatic neuroendocrine carcinoma from pancreatic ductal adenocarcinoma: the values of CT imaging features and texture analysis. Cancer Imaging. 2018;18(1):37.
  • Qiu W, Duan N, Chen X, et al. Pancreatic ductal adenocarcinoma: machine learning-based quantitative computed tomography texture analysis for prediction of histopathological grade. Cancer Manag Res. 2019;11:9253–9264.
  • Choi MH, Lee YJ, Yoon SB, et al. MRI of pancreatic ductal adenocarcinoma: texture analysis of T2-weighted images for predicting long-term outcome. Abdom Radiol. 2019;44(1):122–130.
  • Kim BR, Kim JH, Ahn SJ, et al. CT prediction of resectability and prognosis in patients with pancreatic ductal adenocarcinoma after neoadjuvant treatment using image findings and texture analysis. Eur Radiol. 2019;29(1):362–372.
  • Attiyeh MA, Chakraborty J, Doussot A, et al. Survival prediction in pancreatic ductal adenocarcinoma by quantitative computed tomography image analysis. Ann Surg Oncol. 2018;25(4):1034–1042.
  • Kaissis G, Ziegelmayer S, Lohöfer F, et al. A machine learning model for the prediction of survival and tumor subtype in pancreatic ductal adenocarcinoma from preoperative diffusion-weighted imaging. Eur Radiol Exp. 2019;3(1):41.
  • Dhillon J, Betancourt M. Pancreatic ductal adenocarcinoma. Monogr Clin Cytol. 2020;26:74–91.
  • Nsingwane Z, Candy G, Devar J, et al. Immunotherapeutic strategies in pancreatic ductal adenocarcinoma (PDAC): current perspectives and future prospects. Mol Biol Rep. 2020;47(8):6269–6280.
  • Adamska A, Domenichini A, Falasca M. Pancreatic ductal adenocarcinoma: current and evolving therapies. Int J Mol Sci. 2017;18(7):1338.
  • Springfeld C, Jäger D, Büchler MW, et al. Chemotherapy for pancreatic cancer. Presse Med. 2019;48(3 Pt 2):e159–e174.
  • Ning Z, Xie J, Chen Q, et al. HIFU is safe, effective, and feasible in pancreatic cancer patients: a monocentric retrospective study among 523 patients. OncoTargets Ther. 2019;12:1021–1029.
  • Guo J, Wang Y, Chen J, et al. Systematic review and trial sequential analysis of high-intensity focused ultrasound combined with chemotherapy versus chemotherapy in the treatment of unresectable pancreatic ductal adenocarcinoma. Int J Hyperthermia. 2021;38(1):1375–1383.
  • Lafond M, Lambin T, Drainville RA, et al. Pancreatic ductal adenocarcinoma: current and emerging therapeutic uses of focused ultrasound. Cancers. 2022;14(11):2557.
  • Sofuni A, Asai Y, Tsuchiya T, et al. Novel therapeutic method for unresectable pancreatic cancer-the impact of the long-term research in therapeutic effect of high-intensity focused ultrasound (HIFU) therapy. Curr Oncol. 2021;28(6):4845–4861.
  • Herreros-Villanueva M, Ruiz-Rebollo L, Montes M, et al. CA19-9 capability as predictor of pancreatic cancer resectability in a Spanish cohort. Mol Biol Rep. 2020;47(3):1583–1588.
  • Loosen SH, Neumann UP, Trautwein C, et al. Current and future biomarkers for pancreatic adenocarcinoma. Tumour Biol. 2017;39(6):1010428317692231.
  • Lambin P, Rios-Velazquez E, Leijenaar R, et al. Radiomics: extracting more information from medical images using advanced feature analysis. Eur J Cancer. 2012;48(4):441–446.
  • Verma V, Simone CB II, Krishnan S, et al. The rise of radiomics and implications for oncologic management. J Natl Cancer Inst. 2017;109(7):djx055.
  • Mayerhoefer ME, Materka A, Langs G, et al. Introduction to radiomics. J Nucl Med. 2020;61(4):488–495.
  • Giambelluca D, Cannella R, Vernuccio F, et al. PI-RADS 3 lesions: role of prostate MRI texture analysis in the identification of prostate cancer. Curr Probl Diagn Radiol. 2021;50(2):175–185.
  • Ma W, Ji Y, Qi L, et al. Breast cancer Ki67 expression prediction by DCE-MRI radiomics features. Clin Radiol. 2018;73(10):909.e1–909.e5.
  • Jain P, Khorrami M, Gupta A, et al. Novel non-invasive radiomic signature on CT scans predicts response to platinum-based chemotherapy and is prognostic of overall survival in small cell lung cancer. Front Oncol. 2021;11:744724.
  • Benedetti G, Mori M, Panzeri MM, et al. CT-derived radiomic features to discriminate histologic characteristics of pancreatic neuroendocrine tumors. La Radiol Med. 2021;126(6):745–760.
  • Lee S, Kim SH, Park HK, et al. Pancreatic ductal adenocarcinoma: rim enhancement at MR imaging predicts prognosis after curative resection. Radiology. 2018;288(2):456–466.
  • He Y, Hu B, Zhu C, et al. A novel multimodal radiomics model for predicting prognosis of resected hepatocellular carcinoma. Front Oncol. 2022;12:745258.
  • Cen C, Liu L, Li X, et al. Pancreatic ductal adenocarcinoma at CT: a combined nomogram model to preoperatively predict cancer stage and survival outcome. Front Oncol. 2021;11:594510.
  • Xie T, Wang X, Li M, et al. Pancreatic ductal adenocarcinoma: a radiomics nomogram outperforms clinical model and TNM staging for survival estimation after curative resection. Eur Radiol. 2020;30(5):2513–2524.
  • Liang W, Yang P, Huang R, et al. A combined nomogram model to preoperatively predict histologic grade in pancreatic neuroendocrine tumors. Clin Cancer Res. 2019;25(2):584–594.
  • Cheng SH, Cheng YJ, Jin ZY, et al. Unresectable pancreatic ductal adenocarcinoma: role of CT quantitative imaging biomarkers for predicting outcomes of patients treated with chemotherapy. Eur J Radiol. 2019;113:188–197.