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New computer-aided diagnosis of dementia using positron emission tomography: brain regional sensitivity-mapping method
http://hdl.handle.net/10271/2903
http://hdl.handle.net/10271/2903f568a6d2-2cbb-4bf4-a586-7cf9d16ab2df
名前 / ファイル | ライセンス | アクション |
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論文本文 (448.3 kB)
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Item type | 学位論文 / Thesis or Dissertation(1) | |||||
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公開日 | 2015-11-20 | |||||
タイトル | ||||||
タイトル | New computer-aided diagnosis of dementia using positron emission tomography: brain regional sensitivity-mapping method | |||||
言語 | en | |||||
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_db06 | |||||
資源タイプ | doctoral thesis | |||||
アクセス権 | ||||||
アクセス権 | open access | |||||
アクセス権URI | http://purl.org/coar/access_right/c_abf2 | |||||
その他のタイトル | ||||||
その他のタイトル | ポジトロン断層撮像を用いた新しい認知症診断支援:脳領野感度分布図法 | |||||
言語 | ja | |||||
著者 |
Kakimoto, Akihiro
× Kakimoto, Akihiro |
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書誌情報 |
en : PLoS ONE 巻 6, 号 9, p. e25033, 発行日 2011 |
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出版者 | ||||||
出版者 | PLOS (Public Library of Science) | |||||
言語 | en | |||||
権利 | ||||||
言語 | en | |||||
権利情報 | Copyright: 2011 Kakimoto et al. | |||||
抄録 | ||||||
内容記述タイプ | Abstract | |||||
内容記述 | Purpose: We devised a new computer-aided diagnosis method to segregate dementia using one estimated index (Total Z score) derived from the Brodmann area (BA) sensitivity map on the stereotaxic brain atlas. The purpose of this study is to investigate its accuracy to differentiate patients with Alzheimer’s disease (AD) or mild cognitive impairment (MCI) from normal adults (NL). Methods: We studied 101 adults (NL: 40, AD: 37, MCI: 24) who underwent 18FDG positron emission tomography (PET) measurement. We divided NL and AD groups into two categories: a training group with (Category A) and a test group without (Category B) clinical information. In Category A, we estimated sensitivity by comparing the standard uptake value per BA (SUVR) between NL and AD groups. Then, we calculated a summated index (Total Z score) by utilizing the sensitivitydistribution maps and each BA z-score to segregate AD patterns. To confirm the validity of this method, we examined the accuracy in Category B. Finally, we applied this method to MCI patients. Results: In Category A, we found that the sensitivity and specificity of differentiation between NL and AD were all 100%. In Category B, those were 100% and 95%, respectively. Furthermore, we found this method attained 88% to differentiate ADconverters from non-converters in MCI group. Conclusions: The present automated computer-aided evaluation method based on a single estimated index provided good accuracy for differential diagnosis of AD and MCI. This good differentiation power suggests its usefulness not only for dementia diagnosis but also in a longitudinal study. |
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言語 | en | |||||
学位名 | ||||||
言語 | ja | |||||
学位名 | 博士(医学) | |||||
学位の区分 | ||||||
内容記述タイプ | Other | |||||
内容記述 | doctoral | |||||
言語 | en | |||||
学位の分野 | ||||||
内容記述タイプ | Other | |||||
内容記述 | 医学系研究科 | |||||
言語 | ja | |||||
学位授与機関 | ||||||
学位授与機関識別子Scheme | kakenhi | |||||
学位授与機関識別子 | 13802 | |||||
言語 | ja | |||||
学位授与機関名 | 浜松医科大学 | |||||
学位授与年月日 | ||||||
学位授与年月日 | 2015-03-16 | |||||
学位授与番号 | ||||||
学位授与番号 | 甲第695号 | |||||
EISSN | ||||||
収録物識別子タイプ | EISSN | |||||
収録物識別子 | 1932-6203 | |||||
PubMed番号 | ||||||
識別子タイプ | PMID | |||||
関連識別子 | 21966405 | |||||
出版社DOI | ||||||
識別子タイプ | DOI | |||||
関連識別子 | https://doi.org/10.1371/journal.pone.0025033 | |||||
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 |