資料載入中.....
|
請使用永久網址來引用或連結此文件:
http://libir.tmu.edu.tw/handle/987654321/65271
|
| 題名: | Magnetic resonance radiomics features and prognosticators in different molecular subtypes of pediatric Medulloblastoma. |
| 作者: | 謝立群
Feng Chi Chang, ?Tai Tong Wong, Kuo Sheng Wu, Chia Feng Lu, Ting Wei Weng, Muh Lii Liang, Chih Chun Wu, Wan Yuo Guo,?Cheng Yu Chen,?Kevin Li Chun Hsieh |
| 貢獻者: | 醫學系放射線學科 |
| 日期: | 2021-07 |
| 上傳時間: | 2025-03-30 16:30:01 (UTC+8) |
| 摘要: | Abstract
Purpose: Medulloblastoma (MB) is a highly malignant pediatric brain tumor. In the latest classification, medulloblastoma is divided into four distinct groups: wingless (WNT), sonic hedgehog (SHH), Group 3, and Group 4. We analyzed the magnetic resonance imaging radiomics features to find the imaging surrogates of the 4 molecular subgroups of MB.
Material and methods: Frozen tissue, imaging data, and clinical data of 38 patients with medulloblastoma were included from Taipei Medical University Hospital and Taipei Veterans General Hospital. Molecular clustering was performed based on the gene expression level of 22 subgroup-specific signature genes. A total 253 magnetic resonance imaging radiomic features were generated from each subject for comparison between different molecular subgroups.
Results: Our cohort consisted of 7 (18.4%) patients with WNT medulloblastoma, 12 (31.6%) with SHH tumor, 8 (21.1%) with Group 3 tumor, and 11 (28.9%) with Group 4 tumor. 8 radiomics gray-level co-occurrence matrix texture (GLCM) features were significantly different between 4 molecular subgroups of MB. In addition, for tumors with higher values in a gray-level run length matrix feature-Short Run Low Gray-Level Emphasis, patients have shorter survival times than patients with low values of this feature (p = 0.04). The receiver operating characteristic analysis revealed optimal performance of the preliminary prediction model based on GLCM features for predicting WNT, Group 3, and Group 4 MB (area under the curve = 0.82, 0.72, and 0.78, respectively).
Conclusion: The preliminary result revealed that 8 contrast-enhanced T1-weighted imaging texture features were significantly different between 4 molecular subgroups of MB. Together with the prediction models, the radiomics features may provide suggestions for stratifying patients with MB into different risk groups. |
| 關聯: | PLoS One. 2021 Jul 29;16(7):e0255500 |
| 描述: | 【111-2 升等】臺北醫學大學教師升等專門著作
職別：專任教師
送審等級：副教授
著作送審 |
| 資料類型: | article |
| 顯示於類別: | [教師升等送審著作] 111
|
文件中的檔案:
| 檔案 |
描述 |
大小 | 格式 | 瀏覽次數 |
|---|
| index.html | | 0Kb | HTML | 0 | 檢視/開啟 |
|
在TMUIR中所有的資料項目都受到原著作權保護.
|
