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An artificial intelligence algorithm that differentiates anterior ethmoidal artery location on sinus computed tomography scans

  • J Huang (a1), A-R Habib (a1), D Mendis (a1), J Chong (a1), M Smith (a1), M Duvnjak (a1), C Chiu (a1), N Singh (a1) (a2) and E Wong (a1) (a2)...



Deep learning using convolutional neural networks represents a form of artificial intelligence where computers recognise patterns and make predictions based upon provided datasets. This study aimed to determine if a convolutional neural network could be trained to differentiate the location of the anterior ethmoidal artery as either adhered to the skull base or within a bone ‘mesentery’ on sinus computed tomography scans.


Coronal sinus computed tomography scans were reviewed by two otolaryngology residents for anterior ethmoidal artery location and used as data for the Google Inception-V3 convolutional neural network base. The classification layer of Inception-V3 was retrained in Python (programming language software) using a transfer learning method to interpret the computed tomography images.


A total of 675 images from 388 patients were used to train the convolutional neural network. A further 197 unique images were used to test the algorithm; this yielded a total accuracy of 82.7 per cent (95 per cent confidence interval = 77.7–87.8), kappa statistic of 0.62 and area under the curve of 0.86.


Convolutional neural networks demonstrate promise in identifying clinically important structures in functional endoscopic sinus surgery, such as anterior ethmoidal artery location on pre-operative sinus computed tomography.


Corresponding author

Author for correspondence: Dr Eugene H Wong, Department of Otolaryngology, Head and Neck Surgery, Westmead Hospital, University of Sydney, Sydney, Australia E-mail:


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Dr E H Wong takes responsibility for the integrity of the content of the paper



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1White, DV, Sincoff, EH, Abdulrauf, SI. Anterior ethmoidal artery: microsurgical anatomy and technical considerations. Neurosurgery 2005;56:406–10
2Pernas, FG, Coughlin, AM, Hughes, SE, Riascos, R, Maeso, PA. A novel use of a landmark to avoid injury of the anterior ethmoidal artery during endoscopic sinus surgery. Am J Rhinol Allergy 2011;25:54–7
3Poteet, PS, Cox, MD, Wang, RA, Fitzgerald, RT, Kannan, A. Analysis of the relationship between the location of the anterior ethmoid artery and Keros classification. Otolaryngol Head Neck Surg 2017;157:320–4
4Yang, Y, Lu, Q, Liao, J, Dang, R. Morphological characteristics of the anterior ethmoidal artery in ethmoid roof and endoscopic localization. Skull Base 2009;19:311–17
5Error, M, Ashby, S, Orlandi, RR, Alt, JA. Single-blinded prospective implementation of a preoperative imaging checklist for endoscopic sinus surgery. Otolaryngol Head Neck Surg 2018;158:177–80
6O'Brien, WT Sr, Hamelin, S, Weitzel, EK. The preoperative sinus CT: avoiding a “CLOSE” call with surgical complications. Radiology 2016;281:1021
7Yamashita, R, Nishio, M, Do, RK, Togashi, K. Convolutional neural networks: an overview and application in radiology. Insights Imaging 2018;9:611–19
8Lakhani, P, Sundaram, B. Deep learning at chest radiography: automated classification of pulmonary tuberculosis by using convolutional neural networks. Radiology 2017;284:574–82
9Du, X, Li, W, Hu, B. Application of artificial intelligence in ophthalmology. Int J Ophthalmol 2018;11:1555–61
10Esteva, A, Kuprel, B, Novoa, RA, Ko, J, Swetter, SM, Blau, HM et al. Dermatologist-level classification of skin cancer with deep neural networks. Nature 2017;542:115–18
11Chowdhury, NI, Smith, TL, Chandra, RK, Turner, JH. Automated classification of osteomeatal complex inflammation on computed tomography using convolutional neural networks. Int Forum Allergy Rhinol 2019;9:4652
12Deutschmann, MW, Yeung, J, Bosch, M, Lysack, JT, Kingstone, M, Kilty, SJ et al. Radiologic reporting for paranasal sinus computed tomography: a multi-institutional review of content and consistency. Laryngoscope 2013;123:1100–5
13Baltrusaitis, T, Ahuja, C, Morency, LP. Multimodal machine learning: a survey and taxonomy. IEEE Trans Pattern Anal Mach Intell 2019;41:423–43


An artificial intelligence algorithm that differentiates anterior ethmoidal artery location on sinus computed tomography scans

  • J Huang (a1), A-R Habib (a1), D Mendis (a1), J Chong (a1), M Smith (a1), M Duvnjak (a1), C Chiu (a1), N Singh (a1) (a2) and E Wong (a1) (a2)...


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