Differentiation of Pelvic Osteosarcoma and Ewing Sarcoma Using Radiomic Analysis Based on T2-Weighted Images and Contrast-Enhanced T1-Weighted Images
المؤلفون المشاركون
Dai, Yi
Yin, Ping
Mao, Ning
Sun, Chao
Wu, Jiangfen
Cheng, Guanxun
Hong, Nan
المصدر
العدد
المجلد 2020، العدد 2020 (31 ديسمبر/كانون الأول 2020)، ص ص. 1-8، 8ص.
الناشر
Hindawi Publishing Corporation
تاريخ النشر
2020-05-12
دولة النشر
مصر
عدد الصفحات
8
التخصصات الرئيسية
الملخص EN
Objective.
To determine if osteosarcoma (OS) and Ewing sarcoma (EWS) of the pelvis based on MRI can be differentiated using radiomic analysis.
Materials and Methods.
In this study, 3.0 T magnetic resonance (MR) data of 66 patients (40 males and 26 females, mean age 27.6±13.9 years) with pathologically confirmed OS or EWS of the pelvis (35 with OS and 31 with EWS) taken from April 2013 to December 2017 were retrospectively reviewed.
T2-weighted fat-saturated (T2-FS) and contrast-enhanced T1-weighted (CET1) images were manually segmented, and imaging features were extracted.
Independent-sample t-test, Spearman’s test, and the least absolute shrinkage and selection operator (LASSO) method were used to select the most useful features from the original data set.
The performance of radiomic analysis was investigated by the area under the receiver operating characteristic (ROC) curve (AUC) analysis.
Results.
385 initial features were extracted from T2-FS and CET1 MR data.
Nine features from T2-FS and 7 features from CET1 were selected by using the LASSO method.
The radiomic analysis to differentiate OS and EWS of the pelvis based on T2-FS and CET1 images using the aforementioned selected features achieved AUC values of 0.881 (95% confidence interval (CI): 0.799–0.963) and 0.765 (95% CI: 0.652–0.878), respectively.
Conclusion.
Radiomic analysis showed potential in differentiating OS from EWS of the pelvis, in which T2-FS demonstrated better diagnostic value.
To differentiate OS from EWS of the pelvis using our multiparametric MRI-based radiomic analysis could preoperatively improve diagnostic accuracy and greatly contribute to therapy planning.
نمط استشهاد جمعية علماء النفس الأمريكية (APA)
Dai, Yi& Yin, Ping& Mao, Ning& Sun, Chao& Wu, Jiangfen& Cheng, Guanxun…[et al.]. 2020. Differentiation of Pelvic Osteosarcoma and Ewing Sarcoma Using Radiomic Analysis Based on T2-Weighted Images and Contrast-Enhanced T1-Weighted Images. BioMed Research International،Vol. 2020, no. 2020, pp.1-8.
https://search.emarefa.net/detail/BIM-1137950
نمط استشهاد الجمعية الأمريكية للغات الحديثة (MLA)
Dai, Yi…[et al.]. Differentiation of Pelvic Osteosarcoma and Ewing Sarcoma Using Radiomic Analysis Based on T2-Weighted Images and Contrast-Enhanced T1-Weighted Images. BioMed Research International No. 2020 (2020), pp.1-8.
https://search.emarefa.net/detail/BIM-1137950
نمط استشهاد الجمعية الطبية الأمريكية (AMA)
Dai, Yi& Yin, Ping& Mao, Ning& Sun, Chao& Wu, Jiangfen& Cheng, Guanxun…[et al.]. Differentiation of Pelvic Osteosarcoma and Ewing Sarcoma Using Radiomic Analysis Based on T2-Weighted Images and Contrast-Enhanced T1-Weighted Images. BioMed Research International. 2020. Vol. 2020, no. 2020, pp.1-8.
https://search.emarefa.net/detail/BIM-1137950
نوع البيانات
مقالات
لغة النص
الإنجليزية
الملاحظات
Includes bibliographical references
رقم السجل
BIM-1137950
قاعدة معامل التأثير والاستشهادات المرجعية العربي "ارسيف Arcif"
أضخم قاعدة بيانات عربية للاستشهادات المرجعية للمجلات العلمية المحكمة الصادرة في العالم العربي
تقوم هذه الخدمة بالتحقق من التشابه أو الانتحال في الأبحاث والمقالات العلمية والأطروحات الجامعية والكتب والأبحاث باللغة العربية، وتحديد درجة التشابه أو أصالة الأعمال البحثية وحماية ملكيتها الفكرية. تعرف اكثر