Distinguishing Lymphomatous and Cancerous Lymph Nodes in 18F-Fluorodeoxyglucose Positron Emission TomographyComputed Tomography by Radiomics Analysis
المؤلفون المشاركون
Ma, Xuelei
Ou, Xuejin
Zheng, Bo
Wu, Jiayi
Zhao, Zixuan
Cao, Peng
المصدر
Contrast Media & Molecular Imaging
العدد
المجلد 2020، العدد 2020 (31 ديسمبر/كانون الأول 2020)، ص ص. 1-15، 15ص.
الناشر
Hindawi Publishing Corporation
تاريخ النشر
2020-08-03
دولة النشر
مصر
عدد الصفحات
15
التخصصات الرئيسية
الملخص EN
Background.
The National Comprehensive Cancer Network guidelines recommend excisional biopsies for the diagnosis of lymphomas.
However, resection biopsies in all patients who are suspected of having malignant lymph nodes may cause unnecessary injury and increase medical costs.
We investigated the usefulness of 18F-fluorodeoxyglucose positron emission/computed tomography- (18F-FDG-PET/CT-) based radiomics analysis for differentiating between lymphomatous lymph nodes (LLNs) and cancerous lymph nodes (CLNs).
Methods.
Using texture analysis, radiomic parameters from the 18F-FDG-PET/CT images of 492 lymph nodes (373 lymphomatous lymph nodes and 119 cancerous lymph nodes) were extracted with the LIFEx package.
Predictive models were generated from the six parameters with the largest area under the receiver operating characteristics curve (AUC) in PET or CT images in the training set (70% of the data), using binary logistic regression.
These models were applied to the test set to calculate predictive variables, including the combination of PET and CT predictive variables (PREcombination).
The AUC, sensitivity, specificity, and accuracy were used to compare the differentiating ability of the predictive variables.
Results.
Compared with the pathological diagnosis of the patient’s primary tumor, the AUC, sensitivity, specificity, and accuracy of PREcombination in differentiating between LLNs and CLNs were 0.95, 91.67%, 94.29%, and 92.96%, respectively.
Moreover, PREcombination could effectively distinguish LLNs caused by various lymphoma subtypes (Hodgkin’s lymphoma and non-Hodgkin’s lymphoma) from CLNs, with the AUC, sensitivity, specificity, and accuracy being 0.85 and 0.90, 77.78% and 77.14%, 97.22% and 88.89%, and 90.74% and 83.10%, respectively.
Conclusions.
Radiomics analysis of 18F-FDG-PET/CT images may provide a noninvasive, effective method to distinguish LLN and CLN and inform the choice between fine-needle aspiration and excision biopsy for sampling suspected lymphomatous lymph nodes.
نمط استشهاد جمعية علماء النفس الأمريكية (APA)
Zheng, Bo& Wu, Jiayi& Zhao, Zixuan& Ou, Xuejin& Cao, Peng& Ma, Xuelei. 2020. Distinguishing Lymphomatous and Cancerous Lymph Nodes in 18F-Fluorodeoxyglucose Positron Emission TomographyComputed Tomography by Radiomics Analysis. Contrast Media & Molecular Imaging،Vol. 2020, no. 2020, pp.1-15.
https://search.emarefa.net/detail/BIM-1139245
نمط استشهاد الجمعية الأمريكية للغات الحديثة (MLA)
Zheng, Bo…[et al.]. Distinguishing Lymphomatous and Cancerous Lymph Nodes in 18F-Fluorodeoxyglucose Positron Emission TomographyComputed Tomography by Radiomics Analysis. Contrast Media & Molecular Imaging No. 2020 (2020), pp.1-15.
https://search.emarefa.net/detail/BIM-1139245
نمط استشهاد الجمعية الطبية الأمريكية (AMA)
Zheng, Bo& Wu, Jiayi& Zhao, Zixuan& Ou, Xuejin& Cao, Peng& Ma, Xuelei. Distinguishing Lymphomatous and Cancerous Lymph Nodes in 18F-Fluorodeoxyglucose Positron Emission TomographyComputed Tomography by Radiomics Analysis. Contrast Media & Molecular Imaging. 2020. Vol. 2020, no. 2020, pp.1-15.
https://search.emarefa.net/detail/BIM-1139245
نوع البيانات
مقالات
لغة النص
الإنجليزية
الملاحظات
Includes bibliographical references
رقم السجل
BIM-1139245
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