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Molecular Imaging and Biology
Published in: Molecular Imaging and Biology 4/2019

01-08-2019 | Research Article

Apparent Diffusion Coefficient Histogram Analysis for Assessing Tumor Staging and Detection of Lymph Node Metastasis in Epithelial Ovarian Cancer: Correlation with p53 and Ki-67 Expression

Authors: Feng Wang, Yuxiang Wang, Yan Zhou, Congrong Liu, Dong Liang, Lizhi Xie, Zhihang Yao, Jianyu Liu

Published in: Molecular Imaging and Biology | Issue 4/2019

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Abstract

Purpose

To investigate the potential of apparent diffusion coefficient (ADC) histogram parameters in epithelial ovarian cancer (EOC) for distinguishing different tumor stages and determining lymph node status and correlations between ADC values and p53 and Ki-67 expression.

Procedures

Forty-nine EOC patients underwent preoperative magnetic resonance imaging. Staging and lymph node status were determined postoperatively. ADC values were measured using histogram analysis and compared between groups. Relationships between ADCs and Ki-67 and p53 expression were explored.

Results

DC parameters differed significantly between stage I vs II, I vs III, and I vs IV. The parameters were significantly lower in the lymph node-positive group than in the lymph node-negative group, were significantly negatively correlated with Ki-67 labeling index, and were all significantly lower in the mutation-type p53 group than in the wild-type p53 group.

Conclusions

ADC histogram analysis can help discriminate stage I from advanced-stage EOC and predict lymph node metastasis. ADC parameters were correlated with Ki-67 labeling index; the parameters may help indicate p53 expression.
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Metadata
Title
Apparent Diffusion Coefficient Histogram Analysis for Assessing Tumor Staging and Detection of Lymph Node Metastasis in Epithelial Ovarian Cancer: Correlation with p53 and Ki-67 Expression
Authors
Feng Wang
Yuxiang Wang
Yan Zhou
Congrong Liu
Dong Liang
Lizhi Xie
Zhihang Yao
Jianyu Liu
Publication date
01-08-2019
Publisher
Springer International Publishing
Published in
Molecular Imaging and Biology / Issue 4/2019
Print ISSN: 1536-1632
Electronic ISSN: 1860-2002
DOI
https://doi.org/10.1007/s11307-018-1295-7

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