Distinguishing Lymphomatous and Cancerous Lymph Nodes in 18F-Fluorodeoxyglucose Positron Emission TomographyComputed Tomography by Radiomics Analysis

Joint Authors

Ma, Xuelei
Ou, Xuejin
Zheng, Bo
Wu, Jiayi
Zhao, Zixuan
Cao, Peng

Source

Contrast Media & Molecular Imaging

Issue

Vol. 2020, Issue 2020 (31 Dec. 2020), pp.1-15, 15 p.

Publisher

Hindawi Publishing Corporation

Publication Date

2020-08-03

Country of Publication

Egypt

No. of Pages

15

Main Subjects

Diseases
Medicine

Abstract 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.

American Psychological Association (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

Modern Language Association (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

American Medical Association (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

Data Type

Journal Articles

Language

English

Notes

Includes bibliographical references

Record ID

BIM-1139245