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Prognostic value of ADC quantification for clinical outcome in uterine cervical cancer treated with concurrent chemoradiotherapy

  • Kyo-won Gu
  • Chan Kyo KimEmail author
  • Chel Hun Choi
  • Young Cheol Yoon
  • Won Park
Urogenital

Abstract

Objectives

To investigate the prognostic value of diffusion-weighted imaging (DWI) in predicting clinical outcome in patients with cervical cancer after concurrent chemoradiotherapy (CCRT).

Methods

We enrolled 124 cervical cancer patients who received definitive CCRT and underwent 3 T-MRI before and 1 month after initiating treatment. The mean apparent diffusion coefficient (ADC) value was measured on the tumor and the changes in ADC percentage (ΔADCmean) between the two time points were calculated. The Cox proportion hazard model was used to evaluate the associations between imaging or clinical variables and progression-free survival (PFS), cancer-specific survival (CSS), and overall survival (OS).

Results

In multivariate analysis, ΔADCmean was the only independent predictor of PFS (hazard ratio [HR] = 0.2379, p = 0.005), CSS (HR = 0.310, p = 0.024), and OS (HR = 0.217, p = 0.002). Squamous cell carcinoma antigen, histology, and pretreatment tumor size were significantly independent predictors of PFS. Tumor size response was significantly independent predictor of CSS and OS. Using the cutoff values of ΔADCmean, the PFS was significantly lower for ΔADCmean < 27.8% (p = 0.001). The CSS and OS were significantly lower for ΔADCmean < 16.1% (p = 0.002 and p < 0.001, respectively).

Conclusion

The percentage change in tumor ADC may be a useful predictor of disease progression and survival in patients with cervical cancer treated with CCRT.

Key Points

• DWI is widely used as a potential marker of tumor viability.

• Percentage change in tumor ADC (ΔADC mean ) was an independent marker of PFS, CSS, and OS.

• Survival was better in patients with ≥ ΔADC mean cutoff value than with < the cutoff value.

Keywords

Diffusion-weighted imaging Cervical cancer Concurrent chemoradiotherapy Treatment outcome Magnetic resonance imaging 

Abbreviations

ADC

Apparent diffusion coefficient

CCRT

Concurrent chemoradiotherapy

CI

Confidence interval

CSS

Cancer-specific survival

DWI

Diffusion-weighted imaging

EBRT

External-beam radiotherapy

FIGO

International Federation of Gynecology and Obstetrics

HR

Hazard ratio

ICC

Intraclass correlation coefficient

ICR

Intracavitary brachytherapy

LN

Lymph node

MRI

Magnetic resonance imaging

OS

Overall survival

PFS

Progression-free survival

ROI

Region of interest

SCC

Squamous cell carcinoma

T2WI

T2-weighted imaging

THRIVE

T1-weighted high-resolution isotropic volume examination

ΔADCmean

Percentage change of mean ADC between two time points

Notes

Acknowledgements

We thank Hye Seung Kim, MS, and Insuk Sohn, PhD, of the Statistics and Data Center, Samsung Medical Center, for statistical assistance.

Funding

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

Compliance with ethical standards

Guarantor

The scientific guarantor of this publication is Chan Kyo Kim.

Conflict of interest

The authors of this manuscript declare no relationships with any companies, whose products or services may be related to the subject matter of the article.

Statistics and biometry

Hye Seung Kim, MD and Insuk Sohn, PhD kindly provided statistical advice for this manuscript.

Informed consent

Written informed consent was waived by the Institutional Review Board.

Ethical approval

Institutional Review Board approval was obtained.

Methodology

• retrospective

• diagnostic or prognostic study

• performed at one institution

Supplementary material

330_2019_6204_MOESM1_ESM.docx (1.7 mb)
Supplementary Figure 1 (DOCX 1781 kb)

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Copyright information

© European Society of Radiology 2019

Authors and Affiliations

  1. 1.Department of Radiology and Center for Imaging Science, Samsung Medical CenterSungkyunkwan University School of MedicineSeoulRepublic of Korea
  2. 2.Department of Medical Device Management and Research, SAIHSTSungkyunkwan UniversitySeoulRepublic of Korea
  3. 3.Department of Digital Health, SAIHSTSungkyunkwan UniversitySeoulRepublic of Korea
  4. 4.Departments of Obstetrics and Gynecology, Samsung Medical CenterSungkyunkwan University School of MedicineSeoulRepublic of Korea
  5. 5.Department of Radiation Oncology, Samsung Medical CenterSungkyunkwan University School of MedicineSeoulRepublic of Korea

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