Home Dental Radiology CT evaluation of extranodal extension of cervical lymph node metastases in patients with oral squamous cell carcinoma using deep learning classification

CT evaluation of extranodal extension of cervical lymph node metastases in patients with oral squamous cell carcinoma using deep learning classification

by adminjay


  • 1.

    Kann BH, Aneja S, Loganadane GV, Kelly JR, Smith SM, Decker RH, et al. Pretreatment identification of head and neck cancer nodal metastasis and extranodal extension using deep learning neural networks. Sci Rep. 2018;8:14036.

  • 2.

    O’Sullivan B. Head and neck tumours. In: Brierley J, Gospodarowicz MK, Wittekind C, editors. UICC TNM classification of malignant tumours. 8th ed. Chichester: Wiley; 2017. p. 17–54.

  • 3.

    Amin M, Edge S, Greene F, Schilsky RL, Gaspar LE, Washington MK, et al. AJCC cancer staging manual. 8th ed. New York: Springer; 2017. p. P55–65.

  • 4.

    Aiken AH, Poliashenko S, Beitler JJ, Chen AY, Baugnon KL, Corey AS, et al. Accuracy of preoperative imaging in detecting nodal extracapsular spread in oral cavity squamous cell carcinoma. AJNR Am J Neuroradiol. 2015;36:1776–811.

  • 5.

    Zoumalan RA, Kleinberger AJ, Morris LG, Ranade A, Yee H, DeLacure MD, et al. Lymph node central necrosis on computed tomography as predictor of extracapsular spread in metastatic head and neck squamous cell carcinoma: pilot study. J Laryngol Otol. 2010;124:1284–8.

  • 6.

    Maxwell JH, Rath TJ, Byrd JK, Albergotti WG, Wang H, Duvvuri U, et al. Accuracy of computed tomography to predict extracapsular spread in p16-positive squamous cell carcinoma. Laryngoscope. 2015;125:1613–8.

  • 7.

    Chai RL, Rath TJ, Johnson JT, Ferris RL, Kubicek GJ, Duvvuri U, et al. Accuracy of computed tomography in the prediction of extracapsular spread of lymph node metastases in squamous cell carcinoma of the head and neck. JAMA Otolaryngol Head Neck Surg. 2013;139:1187–94.

  • 8.

    Aerts HJ, Velazquez ER, Leijenaar RT, Parmar C, Grossmann P, Carvalho S, et al. Decoding tumour phenotype by noninvasive imaging using a quantitative radiomics approach. Nat Commun. 2014;5:4006.

  • 9.

    Wong AJ, Kanwar A, Mohamed AS, Fuller CD. Radiomics in head and neck cancer: from exploration to application. Transl Cancer Res. 2016;5:371–82.

  • 10.

    LeCun Y, Bengio Y, Hinton G. Deep learning. Nature. 2015;521:436–44.

  • 11.

    Cireşan D, Meier U, Masci J, Schmidhuber J. Multi-column deep neural network for traffic sign classification. Neural Netw. 2012;32:333–8.

  • 12.

    Chang K, Bai HX, Zhou H, Su C, Bi WL, Agbodza E, et al. Residual convolutional neural network for the determination of IDH status in low- and high-grade gliomas from MR imaging. Clin Cancer Res. 2018;24:1073–81.

  • 13.

    Simonyan K, Zisserman A. Verd deep convolutional networks for large-scale image recognition. 2014. https://arxiv.org/abs/1409.1556

  • 14.

    Silver D, Schrittwieser J, Simonyan K, Antonoglou I, Huang A, Guez A, et al. Mastering the game of Go without human knowledge. Nature. 2017;550:354–9.

  • 15.

    Silver D, Huang A, Maddison CJ, Guez A, Sifre L, van den Driessche G, et al. Mastering the game of Go with deep neural networks and tree search. Nature. 2016;529:484–9.

  • 16.

    Ariji Y, Fukuda M, Kise Y, Nozawa M, Yanashita Y, Fujita H, et al. Contrast-enhanced computed tomography image assessment of cervical lymph node metastasis in patients with oral cancer by using a deep learning system of artificial intelligence. Oral Surg Oral Med Oral Pathol Oral Radiol. 2019 (in press). https://doi.org/10.1016/j.oooo.2018.10.002.

  • 17.

    Jose J, Coatesworth AP, Johnston C, MacLennan K. Cervical node metastases in squamous cell carcinoma of the upper aerodigestive tract: the significance of extracapsular spread and soft tissue deposits. Head Neck. 2003;25:451–6.

  • 18.

    Brasilino de Carvalho M. Quantitative analysis of the extent of extracapsular invasion and its prognostic significance: a prospective study of 170 cases of carcinoma of the larynx and hypopharynx. Head Neck. 1998;20:16-21.

  • 19.

    Bernier J, Cooper JS, Pajak TF, van Glabbeke M, Bourhis J, Forastiere A, et al. Defining risk levels in locally advanced head and neck cancers: a comparative analysis of concurrent postoperative radiation plus chemotherapy trials of the EORTC (#22931) and RTOG (# 9501). Head Neck. 2005;27:843–50.

  • 20.

    Carlton JA, Maxwell AW, Bauer LB, McElroy SM, Layfield LJ, Ahsan H, et al. Computed tomography detection of extracapsular spread of squamous cell carcinoma of the head and neck in metastatic cervical lymph nodes. Neuroradiol J. 2017;30:222–9.

  • 21.

    Prabhu RS, Magliocca KR, Hanasoge S, Aiken AH, Hudgins PA, Hall WA, et al. Accuracy of computed tomography for predicting pathologic nodal extracapsular extension in patients with head-and-neck cancer undergoing initial surgical resection. Int J Radiat Oncol Biol Phys. 2014;88:122–9.

  • 22.

    Johnson JT, Barnes EL, Myers EN, Schramm VL Jr, Borochovitz D, Sigler BA. The extracapsular spread of tumors in cervical node metastasis. Arch Otolaryngol. 1981;107:725–9.

  • 23.

    Don DM, Anzai Y, Lufkin RB, Fu YS, Calcaterra TC. Evaluation of cervical lymph node metastases in squamous cell carcinoma of the head and neck. Laryngoscope. 1995;105:669–74.

  • 24.

    Yousem DM, Som PM, Hackney DB, Schwaibold F, Hendrix RA. Central nodal necrosis and extracapsular neoplastic spread in cervical lymph nodes: MR imaging versus CT. Radiology. 1992;182:753–9.

  • 25.

    King AD, Tse GM, Yuen EH, To EW, Vlantis AC, Zee B, et al. Comparison of CT and MR imaging for the detection of extranodal neoplastic spread in metastatic neck nodes. Eur J Radiol. 2004;52:264–70.

  • 26.

    Misselt PN, Glazebrook KN, Reynolds C, Degnim AC, Morton MJ. Predictive value of sonographic features of extranodal extension in axillary lymph nodes. J Ultrasound Med. 2010;29:1705–9.



  • Source link

    Related Articles