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Histogram analysis of apparent diffusion coefficients for predicting pelvic lymph node metastasis in patients with uterine cervical cancer

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Abstract

Objective

To investigate the value of apparent diffusion coefficient (ADC) histogram analysis in predicting pelvic lymph node (LN) metastasis in patients with cervical cancer undergoing surgery.

Materials and methods

A total of 162 cervical cancer patients who underwent radical abdominal hysterectomy with pelvic LN dissection performed with pelvic 3 T-MRI including diffusion-weighted imaging were enrolled in this study. The ADC histogram variables (minimum, mean, median, 97.5th percentile [ADC97.5], and maximum) of the tumors were developed using in-house software. For predicting pelvic LN metastasis, clinical and imaging variables were evaluated using logistic regression and receiver-operating characteristic (ROC) analyses.

Results

Pelvic LN metastasis was identified histopathologically in 50 patients (30.9%). In patients with LN metastasis, all ADC histogram variables were significantly different from those without LN metastasis (all p < 0.01). Univariate analysis demonstrated that long- and short-axis diameter of LN, MRI T-stage, squamous cell carcinoma antigen, tumor size, and the ADC97.5 were significantly associated with pelvic LN metastasis (all p < 0.05). However, multivariate analysis demonstrated that the ADC97.5 was the only independent predictor of pelvic LN metastasis (odds ratio, 0.996; p = 0.001). The area under the ROC curve of ADC97.5 was 0.782, which was the greatest among all variables. Interobserver agreement of all ADC histogram variables was fair to good.

Discussion

The ADC97.5 from histogram analysis may be a useful marker for the prediction of pelvic LN metastasis in patients with cervical cancer.

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Abbreviations

LN:

Lymph node

FIGO:

International Federation of Gynecology and Obstetrics

DWI:

Diffusion-weighted imaging

ADC:

Apparent diffusion coefficient

SCC:

Squamous cell carcinoma

THRIVE:

T1-weighted high-resolution isotropic volume examination

ROI:

Region of interest

ADC97.5 :

97.5th percentile ADC

ADCmean :

Mean ADC

ADCmax :

Maximum ADC

ADCmin :

Minimum ADC

ADCmedian :

Median ADC

ICC:

Intraclass correlation coefficient

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Acknowledgements

We thank Na Young Hwang MS and Insuk Sohn, Ph.D. of Statistics and Data Center, Samsung Medical Center, for help with statistical assistance.

Funding

This study was funded by Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education (NRF-2017R1A2B4006020).

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Authors and Affiliations

Authors

Contributions

Study concepts and design: CKK, JL. Acquisition of data: CKK, JL, and SYP. Analysis and interpretation of data: CKK, JL, and SYP. Drafting of manuscript: CKK and JL. Critical revision: CKK, JL, and SYP.

Corresponding author

Correspondence to Chan Kyo Kim.

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Conflict of interest

All the authors (J.L., C.K.K., and S.Y.P.) declare that they have no conflict of interest.

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All the procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional research committee and with the 1964 Helsinki Declaration and its later amendments or comparable ethical standards.

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Informed consent was obtained from all individual participants included in the study.

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Lee, J., Kim, C.K. & Park, S.Y. Histogram analysis of apparent diffusion coefficients for predicting pelvic lymph node metastasis in patients with uterine cervical cancer. Magn Reson Mater Phy 33, 283–292 (2020). https://doi.org/10.1007/s10334-019-00777-9

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  • DOI: https://doi.org/10.1007/s10334-019-00777-9

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