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조회216

조혜연Hye-Yeon Cho

서울대학교 의과대학

Anaesthesia, First published: 05 October 2022 | https://doi.org/10.1111/anae.15874 Deep-learning model associating lateral cervical radiographic features with Cormack-Lehane grade 3 or 4 glottic view

H.-Y. Cho,^1,2, K. Lee,^3,4, H.-J. Kong,^5,6, H.-L. Yang,^1,7, C.-W. Jung,^1,2, H.-P. Park,^1,2, J.Y. Hwang^3,8 and H.-C. Lee^1,2

¹ Clinical Instructor, ² Researcher, Department of Anaesthesiology and Pain Medicine, 5 Professor, Transdisciplinary Department of Medicine and Advanced Technology, 7 Professor, Biomedical Research Institute, Seoul National University Hospital, Seoul, Republic of Korea
³ Professor, Adjunct Professor, Department of Electrical Engineering and Computer Science, 8 Assistant Professor, Department of Interdisciplinary Studies of Artificial Intelligence Daegu Gyeongbuk Institute of Science and Technology, Daegu, Republic of Korea
⁴ Research Assistant Professor, 6 Professor, Department of Biomedical Engineering, Medical Big data Research Center, Seoul National University College of Medicine, Seoul, Republic of Korea

The authors H-YC and KL contributed equally to the work asfirst authors.
Correspondence to: H.-C. Lee

Abstract

Unanticipated difficult laryngoscopy is associated with serious airway-related complications. We aimed to develop and test a convolutional neural network-based deep-learning model that uses lateral cervical spine radiographs to predict Cormack-Lehane grade 3 or 4 direct laryngoscopy views of the glottis. We analysed the radiographs of 5939 thyroid surgery patients at our hospital, 253 (4%) of whom had grade 3 or 4 glottic views. We used 10 randomly sampled datasets to train a model. We compared the new model with six similar models (VGG, ResNet, Xception, ResNext, DenseNet and SENet). The Brier score (95%CI) of the new model, 0.023 (0.021-0.025), was lower ('better') than the other models: VGG, 0.034 (0.034-0.035); ResNet, 0.033 (0.033-0.035); Xception, 0.032 (0.031-0.033); ResNext, 0.033 (0.032-0.033); DenseNet, 0.030 (0.029-0.032); SENet, 0.031 (0.029-0.032), all p < 0.001. We calculated mean (95%CI) of the new model for: R² , 0.428 (0.388-0.468); mean squared error, 0.023 (0.021-0.025); mean absolute error, 0.048 (0.046-0.049); balanced accuracy, 0.713 (0.684-0.742); and area under the receiver operating characteristic curve, 0.965 (0.962-0.969). Radiographic features around the hyoid bone, pharynx and cervical spine were associated with grade 3 and 4 glottic views.

논문정보

형식Research article
게재일2022년 10월 (BRIC 등록일 2023-01-26)
연구진국내 연구진
분야 의약학 > 응용의학

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