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• Clinical Article •
Predictive value of quantitative parameters from DCE-MRI histogram combined with ADC value for chemoradiotherapy efficacy in locally advanced cervical cancer
HE Yuqi  DU Yunxia  XU Wenxiang  LI Feixiang  SUN Yun  PENG Leping  WANG Lili  HUANG Gang 

Cite this article as: HE Y Q, DU Y X, XU W X, et al. Predictive value of quantitative parameters from DCE-MRI histogram combined with ADC value for chemoradiotherapy efficacy in locally advanced cervical cancer[J]. Chin J Magn Reson Imaging, 2025, 16(6): 93-99, 109. DOI:10.12015/issn.1674-8034.2025.06.014.


[Abstract] Objective To investigate the predictive value of quantitative histogram features from dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) combined with apparent diffusion coefficient (ADC) in assessing the efficacy of radiotherapy for locally advanced cervical cancer (LACC).Materials and Methods A retrospective analysis was conducted on the clinical and imaging data of 88 patients with concurrent chemoradiotherapy for LACC in Gansu Provincial People's Hospital from January 2017 to December 2023. Prospectively, 15 patients with LACC in Gansu Provincial People's Hospital from December 2023 to May 2024 were collected. According to response evaluation criteria in solid tumors (RECIST) v1.1 standard, the patients were divided into significant response group and non-significant tumors group. On the DCE-MRI images, the contour of the entire tumor at the largest layer of the tumor was selected as the region of interest (ROI) to obtain the original frequency tables of the transport constant (Ktrans), volume fraction (Ve), and rate constant (Kep). The IBM SPSS Statistics 27 software was imported to calculate the histogram characteristics. A total of 103 patients were divided into 88 cases in the training set and 15 cases in the validation set based on the hierarchical segmentation strategy of time series. Machine learning was used to screen the optimal histogram characteristics of quantitative parameters of DCE-MRI and calculate the perfusion parameter score (DCEscore). Meanwhile, measure the ADC value on the ADC diagram. DCE histogram feature model, ADC value and combined model were constructed to predict the efficacy of LACC chemoradiotherapy. Receiver operating characteristic (ROC) curves, calibration curves and decision curves were used to evaluate the model performance. The difference of clinical parameters and histogram features between the significant response group and the non-significant response group in LACC patients with radiotherapy and chemotherapy was compared and analyzed. Univariate and multivariate regression analysis was used to screen independent risk factors for radiotherapy and chemotherapy for cervical cancer.Results The area under the curve (AUC) of the training set and the validation set were 0.922 and 0.841, respectively, for the treatment of LACC patients based on the DCE-MRI quantitative parameter histogram feature model. ADC values to predict radiotherapy efficacy in LACC patients training set, validation set AUC of 0.835, 0.705. DCEscore combined with ADC values predicted the best efficacy of radiotherapy efficacy in LACC patients, with training set and validation set AUC of 0.943, 0.909. Among clinical parameters, body mass index (BMI) showed a statistically significant difference between the significant response group and the non-significant response group (P = 0.032). The results of univariate logistic regression analysis showed that BMI, DCEscore, and ADC were the influencing factors for the efficacy of radiotherapy for locally advanced cervical cancer (OR values of 1.264, 277.9, and 0.001, respectively; P values of 0.008, < 0.001, and 0.002, respectively), and multivariate logistic regression screened that the DCEscore and ADC values were the independent risk factors (OR 518.2, 0.002; P values < 0.001, 0.007, respectively).Conclusions The combined model based on DCE-MRI quantitative parameter histogram features combined with ADC values can predict the efficacy of radiotherapy and chemotherapy for cervical cancer before treatment, suggesting that DCE-MRI quantitative parameter histogram features combined with ADC values may provide a non-invasive evaluation method for precision medical treatment of locally advanced cervical cancer patients.
[Keywords] cervical cancer；chemoradiotherapy；dynamic contrast-enhanced magnetic resonance imaging；apparent diffusion coefficient；machine learning

HE Yuqi1   DU Yunxia1   XU Wenxiang1   LI Feixiang1   SUN Yun1   PENG Leping1   WANG Lili2   HUANG Gang2*  

1 The First Clinical Medical College of Gansu University of Chinese Medicine, Lanzhou 730000, China

2 Department of Radiology, Gansu Provincial Hospital, Lanzhou 730000, China

Corresponding author: HUANG G, E-mail: huang_g2024@163.com

Conflicts of interest   None.

Received  2024-10-26
Accepted  2025-05-10
DOI: 10.12015/issn.1674-8034.2025.06.014
Cite this article as: HE Y Q, DU Y X, XU W X, et al. Predictive value of quantitative parameters from DCE-MRI histogram combined with ADC value for chemoradiotherapy efficacy in locally advanced cervical cancer[J]. Chin J Magn Reson Imaging, 2025, 16(6): 93-99, 109. DOI:10.12015/issn.1674-8034.2025.06.014.

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