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  1. C. 医薬保健学域; 医学類・薬学類・医薬科学類・保健学類
  2. c 10. 学術雑誌掲載論文(医・保健)
  3. 1. 査読済論文(医学・保健)

Enhanced diagnostic accuracy for quantitative bone scan using an artificial neural network system: A Japanese multi-center database project

http://hdl.handle.net/2297/36499
http://hdl.handle.net/2297/36499
a1e25199-c05d-4f2b-804f-df278a9b47d0
名前 / ファイル ライセンス アクション
ME-PR-NAKAJIMA-K-2013EJNMMI-R.pdf ME-PR-NAKAJIMA-K-2013EJNMMI-R.pdf (2.0 MB)
Item type 学術雑誌論文 / Journal Article(1)
公開日 2017-10-03
タイトル
タイトル Enhanced diagnostic accuracy for quantitative bone scan using an artificial neural network system: A Japanese multi-center database project
言語
言語 eng
資源タイプ
資源タイプ識別子 http://purl.org/coar/resource_type/c_6501
資源タイプ journal article
著者 Nakajima, Kenichi

× Nakajima, Kenichi

WEKO 320
e-Rad 00167545
金沢大学研究者情報 00167545
研究者番号 00167545

Nakajima, Kenichi

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Nakajima, Yasuo

× Nakajima, Yasuo

WEKO 22810

Nakajima, Yasuo

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Horikoshi, Hiroyuki

× Horikoshi, Hiroyuki

WEKO 22811

Horikoshi, Hiroyuki

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Ueno, Munehisa

× Ueno, Munehisa

WEKO 22812

Ueno, Munehisa

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Wakabayashi, Hiroshi

× Wakabayashi, Hiroshi

WEKO 489
金沢大学研究者情報 60622818
研究者番号 60622818

Wakabayashi, Hiroshi

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Shiga, Tohru

× Shiga, Tohru

WEKO 22813

Shiga, Tohru

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Yoshimura, Mana

× Yoshimura, Mana

WEKO 22814

Yoshimura, Mana

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Ohtake, Eiji

× Ohtake, Eiji

WEKO 22815

Ohtake, Eiji

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Sugawara, Yoshifumi

× Sugawara, Yoshifumi

WEKO 22816

Sugawara, Yoshifumi

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Matsuyama, Hideyasu

× Matsuyama, Hideyasu

WEKO 22817

Matsuyama, Hideyasu

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Edenbrandt, Lars

× Edenbrandt, Lars

WEKO 22818

Edenbrandt, Lars

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書誌情報 EJNMMI Research

巻 3, 号 1, 発行日 2013-12-26
ISSN
収録物識別子タイプ ISSN
収録物識別子 2191-219X
DOI
関連タイプ isIdenticalTo
識別子タイプ DOI
関連識別子 10.1186/2191-219X-3-83
出版者
出版者 Springer Berlin (open access journals)
抄録
内容記述タイプ Abstract
内容記述 Background Artificial neural network (ANN)-based bone scan index (BSI), a marker of the amount of bone metastasis, has been shown to enhance diagnostic accuracy and reproducibility but is potentially affected by training databases. The aims of this study were to revise the software using a large number of Japanese databases and to validate its diagnostic accuracy compared with the original Swedish training database. Methods The BSI was calculated with EXINIbone (EB; EXINI Diagnostics) using the Swedish training database (n = 789). The software using Japanese training databases from a single institution (BONENAVI version 1, BN1, n = 904) and the revised version from nine institutions (version 2, BN2, n = 1,532) were compared. The diagnostic accuracy was validated with another 503 multi-center bone scans including patients with prostate (n = 207), breast (n = 166), and other cancer types. The ANN value (probability of abnormality) and BSI were calculated. Receiver operating characteristic (ROC) and net reclassification improvement (NRI) analyses were performed. Results The ROC analysis based on the ANN value showed significant improvement from EB to BN1 and BN2. In men (n = 296), the area under the curve (AUC) was 0.877 for EB, 0.912 for BN1 (p = not significant (ns) vs. EB) and 0.934 for BN2 (p = 0.007 vs. EB). In women (n = 207), the AUC was 0.831 for EB, 0.910 for BN1 (p = 0.016 vs. EB), and 0.932 for BN2 (p < 0.0001 vs. EB). The optimum sensitivity and specificity based on BN2 was 90% and 84% for men and 93% and 85% for women. In patients with prostate cancer, the AUC was equally high with EB, BN1, and BN2 (0.939, 0.949, and 0.957, p = ns). In patients with breast cancer, the AUC was improved from EB (0.847) to BN1 (0.910, p = ns) and BN2 (0.924, p = 0.039). The NRI using ANN between EB and BN1 was 17.7% (p = 0.0042), and that between EB and BN2 was 29.6% (p < 0.0001). With respect to BSI, the NRI analysis showed downward reclassification with total NRI of 31.9% (p < 0.0001). Conclusion In the software for calculating BSI, the multi-institutional database significantly improved identification of bone metastasis compared with the original database, indicating the importance of a sufficient number of training databases including various types of cancers. © 2013 Nakajima et al.
権利
権利情報 © 2013 Nakajima et al.; licensee Springer. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
著者版フラグ
出版タイプ VoR
出版タイプResource http://purl.org/coar/version/c_970fb48d4fbd8a85
関連URI
識別子タイプ URI
関連識別子 http://www.ejnmmires.com/content/3/1/83
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