Whole solid tumor volume histogram parameters for predicting the recurrence in patients with epithelial ovarian carcinoma: a feasibility study on quantitative DCE-MRI

Author:

Li Hai Ming123,Tang Wei12,Feng Feng4,Zhao Shu Hui5,Gu Wei Yong6,Zhang Guo Fu7,Qiang Jin Wei3

Affiliation:

1. Department of Radiology, Fudan University Shanghai Cancer Center, Shanghai, PR China

2. Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, PR China

3. Department of Radiology, Jinshan Hospital, Fudan University, Shanghai, PR China

4. Department of Radiology, Nantong Cancer Hospital, Nantong University, Nantong, Jiangsu, PR China

5. Department of Radiology, Xinhua Hospital, Shanghai Jiao Tong University, Shanghai, PR China

6. Department of Pathology, Obstetrics & Gynecology Hospital, Fudan University, Shanghai, PR China

7. Department of Radiology, Obstetrics & Gynecology Hospital, Fudan University, Shanghai, PR China

Abstract

Background Preoperative prediction of the recurrence of epithelial ovarian carcinoma (EOC) can guide the clinical treatment and improve the prognosis. However, there are still no reliable predictive biomarkers. Purpose To evaluate whether whole solid tumor volume histogram parameters measured from quantitative dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) can predict the recurrence in patients with EOC. Material and Methods We followed up 56 patients with surgical and histopathologically diagnosed EOC who underwent quantitative DCE-MRI scans. The differences of the histogram parameters between patients with and without recurrence were compared. Mann–Whitney U test, Pearson’s Chi-squared test, or Fisher’s exact test, and receiver operating characteristic (ROC) curves were used for statistical analysis. Results All histogram parameters of Ktrans, kep, and ve were not significantly different between EOC patients with and without recurrence ( P>0.05). For 30 patients with high-grade serous ovarian carcinoma (HGSOC), the histogram parameters of Ktrans (mean and 5th, 10th, 25th, 50th, 75th percentiles) and kep (mean and 50th percentile) in 12 patients with recurrence were significantly lower than those in 18 patients without recurrence (all P<0.05). ROC curves showed that the 5th percentile of Ktrans had the largest area under the curve (AUC) of 0.792 for predicting the recurrence in patients with HGSOC. When the threshold value was ≤0.0263/min, the sensitivity, specificity, and accuracy were 100%, 66.7%, and 80%, respectively. Conclusion Instead of predicting the recurrence of EOC, whole solid tumor volume quantitative DCE-MRI histogram parameters could predict the recurrence of HGSOC and may be potential biomarkers for the prediction of HGSOC recurrence.

Funder

Shanghai Health and Family Planning Commission Youth Fund Project

Shanghai Municipal Commission of Science and Technology

Imaging Foundation of Fudan University Shanghai Cancer Center

National Natural Science Foundations of China

Shanghai Municipal Health Commission

Publisher

SAGE Publications

Subject

Radiology Nuclear Medicine and imaging,General Medicine,Radiological and Ultrasound Technology

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