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14.04.2017 | Original Article | Ausgabe 10/2017

European Journal of Nuclear Medicine and Molecular Imaging 10/2017

[18]Fluorodeoxyglucose Positron Emission Tomography for the Textural Features of Cervical Cancer Associated with Lymph Node Metastasis and Histological Type

Zeitschrift:
European Journal of Nuclear Medicine and Molecular Imaging > Ausgabe 10/2017
Autoren:
Wei-Chih Shen, Shang-Wen Chen, Ji-An Liang, Te-Chun Hsieh, Kuo-Yang Yen, Chia-Hung Kao
Wichtige Hinweise

Electronic supplementary material

The online version of this article (doi:10.​1007/​s00259-017-3697-1) contains supplementary material, which is available to authorized users.
Shang-Wen Chen and Wei-Chih Shen are equally contributory to this article.

Abstract

Background

In this study, we investigated the correlation between the lymph node (LN) status or histological types and textural features of cervical cancers on 18F-fluorodeoxyglucose positron emission tomography/computed tomography.

Methods

We retrospectively reviewed the imaging records of 170 patients with International Federation of Gynecology and Obstetrics stage IB–IVA cervical cancer. Four groups of textural features were studied in addition to the maximum standardized uptake value (SUVmax), metabolic tumor volume, and total lesion glycolysis (TLG). Moreover, we studied the associations between the indices and clinical parameters, including the LN status, clinical stage, and histology. Receiver operating characteristic curves were constructed to evaluate the optimal predictive performance among the various textural indices. Quantitative differences were determined using the Mann–Whitney U test. Multivariate logistic regression analysis was performed to determine the independent factors, among all the variables, for predicting LN metastasis.

Results

Among all the significant indices related to pelvic LN metastasis, homogeneity derived from the gray-level co-occurrence matrix (GLCM) was the sole independent predictor. By combining SUVmax, the risk of pelvic LN metastasis can be scored accordingly. The TLGmean was the independent feature of positive para-aortic LNs. Quantitative differences between squamous and nonsquamous histology can be determined using short-zone emphasis (SZE) from the gray-level size zone matrix (GLSZM).

Conclusion

This study revealed that in patients with cervical cancer, pelvic or para-aortic LN metastases can be predicted by using textural feature of homogeneity from the GLCM and TLGmean, respectively. SZE from the GLSZM is the sole feature associated with quantitative differences between squamous and nonsquamous histology.

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Zusatzmaterial
Appendix 1. Indices calculated from the textural analysis. The performance of a texture index in predicting the PLN metastasis was evaluated by the area under the ROC curve. To evaluate the performance of a discretization method, the average and standard deviation of all areas of each texture index acquired from all parameters of the discretization method were calculated. (DOCX 18 kb)
259_2017_3697_MOESM1_ESM.docx
Appendix 2. Textural indices that showed a varying trend between patients with FIGO stages I and II and III–IVA. (DOCX 18 kb)
259_2017_3697_MOESM2_ESM.docx
Appendix 3. According to pelvic lymph node (PLN) metastasis, (a) the scatterplot of the MTV and homogeneity and (b) that of the TLGmean and homogeneity of the primary tumors. The largest tumor with an MTV of 449.962.3 mm3 with PLN metastasis was excluded from the scatterplot (a), as detailed on the y-axis. (DOCX 3742 kb)
259_2017_3697_MOESM3_ESM.docx
ESM 1 (XLSX 19 kb)
259_2017_3697_MOESM4_ESM.xlsx
Literatur
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