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タイトル: | Automated prediction of emphysema visual score using homology-based quantification of low-attenuation lung region |
著者: | Nishio, Mizuho Nakane, Kazuaki Kubo, Takeshi Yakami, Masahiro https://orcid.org/0000-0002-8487-405X (unconfirmed) Emoto, Yutaka Nishio, Mari Togashi, Kaori |
著者名の別形: | 西尾, 瑞穂 久保, 武 八上, 全弘 富樫, かおり |
発行日: | 25-May-2017 |
出版者: | Public Library of Science |
誌名: | PLOS ONE |
巻: | 12 |
号: | 5 |
論文番号: | e0178217 |
抄録: | [Objective]: The purpose of this study was to investigate the relationship between visual score of emphysema and homology-based emphysema quantification (HEQ) and evaluate whether visual score was accurately predicted by machine learning and HEQ. [Materials and methods]: A total of 115 anonymized computed tomography images from 39 patients were obtained from a public database. Emphysema quantification of these images was performed by measuring the percentage of low-attenuation lung area (LAA%). The following values related to HEQ were obtained: nb0 and nb1. LAA% and HEQ were calculated at various threshold levels ranging from -1000 HU to -700 HU. Spearman's correlation coefficients between emphysema quantification and visual score were calculated at the various threshold levels. Visual score was predicted by machine learning and emphysema quantification (LAA% or HEQ). Random Forest was used as a machine learning algorithm, and accuracy of prediction was evaluated by leave-one-patient-out cross validation. The difference in the accuracy was assessed using McNemar's test. [Results]: The correlation coefficients between emphysema quantification and visual score were as follows: LAA% (-950 HU), 0.567; LAA% (-910 HU), 0.654; LAA% (-875 HU), 0.704; nb0 (-950 HU), 0.552; nb0 (-910 HU), 0.629; nb0 (-875 HU), 0.473; nb1 (-950 HU), 0.149; nb1 (-910 HU), 0.519; and nb1 (-875 HU), 0.716. The accuracy of prediction was as follows: LAA%, 55.7% and HEQ, 66.1%. The difference in accuracy was statistically significant (p = 0.0290). [Conclusion]: LAA% and HEQ at -875 HU showed a stronger correlation with visual score than those at -910 or -950 HU. HEQ was more useful than LAA% for predicting visual score. |
著作権等: | © 2017 Nishio et al.This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
URI: | http://hdl.handle.net/2433/227727 |
DOI(出版社版): | 10.1371/journal.pone.0178217 |
PubMed ID: | 28542398 |
出現コレクション: | 学術雑誌掲載論文等 |
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