| Item type |
itemtype_ver1(1) |
| 公開日 |
2022-05-27 |
| タイトル |
|
|
タイトル |
Radiomics analysis for differentiating of cervical lymphadenopathy between cancer of unknown primary and malignant lymphoma on unenhanced computed tomography |
|
言語 |
en |
| 著者 |
Tomita, Hayato
Yamashiro, Tsuneo
Iida, Gyo
Tsubakimoto, Maho
Mimura, Hidefumi
Murayama, Sadayuki
|
| 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 |
| 権利 |
|
|
言語 |
en |
|
権利情報Resource |
http://creativecommons.org/licenses/by-nc-nd/4.0/ |
|
権利情報 |
Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International |
| キーワード |
|
|
主題Scheme |
Other |
|
主題 |
texture |
| キーワード |
|
|
主題Scheme |
Other |
|
主題 |
cancer of unknown primary |
| キーワード |
|
|
主題Scheme |
Other |
|
主題 |
malignant lymphoma |
| キーワード |
|
|
主題Scheme |
Other |
|
主題 |
cervical lymphadenopathy |
| キーワード |
|
|
主題Scheme |
Other |
|
主題 |
machine learning |
| 内容記述 |
|
|
内容記述タイプ |
Abstract |
|
内容記述 |
To investigate the usefulness of texture analysis to discriminate between cervical lymph node (LN) metastasis from cancer of unknown primary (CUP) and cervical LN involvement of malignant lymphoma (ML) on unenhanced computed tomography (CT). Cervical LN metastases in 17 patients with CUP and cervical LN involvement in 17 patients with ML were assessed by 18F-FDG PET/CT. The texture features were obtained in the total cross-sectional area (CSA) of the targeted LN, following the contour of the largest cervical LN on unenhanced CT. Values for the max standardized uptake value (SUVmax) and the mean SUV value (SUVmean), and 34 texture features were compared using a Mann-Whitney U test. The diagnostic accuracy and area under the curve (AUC) of the combination of the texture features were evaluated by support vector machine (SVM) with nested cross-validation. The SUVmax and SUVmean did not differ significantly between cervical LN metastases from CUP and cervical LN involvement from ML. However, significant differences of 9 texture features of the total CSA were observed (p = 0.001 – 0.05). The best AUC value of 0.851 for the texture feature of the total CSA were obtained from the correlation in the gray-level co-occurrence matrix features. SVM had the best AUC and diagnostic accuracy of 0.930 and 84.8%. Radiomics analysis appears to be useful for differentiating cervical LN metastasis from CUP and cervical LN involvement of ML on unenhanced CT. |
|
言語 |
en |
| 出版者 |
|
|
出版者 |
Nagoya University Graduate School of Medicine, School of Medicine |
|
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_6501 |
|
資源タイプ |
departmental bulletin paper |
| 出版タイプ |
|
|
出版タイプ |
VoR |
|
出版タイプResource |
http://purl.org/coar/version/c_970fb48d4fbd8a85 |
| ID登録 |
|
|
ID登録 |
10.18999/nagjms.84.2.269 |
|
ID登録タイプ |
JaLC |
| 関連情報 |
|
|
関連タイプ |
isVersionOf |
|
|
識別子タイプ |
URI |
|
|
関連識別子 |
https://www.med.nagoya-u.ac.jp/medlib/nagoya_j_med_sci/842.html |
| 収録物識別子 |
|
|
収録物識別子タイプ |
PISSN |
|
収録物識別子 |
0027-7622 |
| 収録物識別子 |
|
|
収録物識別子タイプ |
EISSN |
|
収録物識別子 |
2186-3326 |
| 書誌情報 |
en : Nagoya Journal of Medical Science
巻 84,
号 2,
p. 269-285,
発行日 2022-05
|
06_Tomita.pdf (4.4 MB)
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