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Multiparametric MRI-based Radiomics approaches on predicting response to neoadjuvant chemoradiotherapy (nCRT) in patients with rectal cancer

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Abstract

Purpose

To investigate the value of multiparametric MRI-based radiomics on predicting response to nCRT in patients with rectal cancer.

Methods

This study enrolled 193 patients with pathologically confirmed LARC who received nCRT treatment between Apr. 2014 and Jun. 2018. All patients underwent baseline T1-weighted (T1W), T2-weighted (T2W) and T2-weighted fat-suppression (T2FS) MRI scans before neoadjuvant chemoradiotherapy. Radiomics features were extracted and selected from the MRI data to establish the radiomics signature. Important clinical predictors were identified by Mann–Whitney U test and Chi-square test. The nomogram integrating the radiomics signature and important clinical predictors was constructed using multivariate logistic regression. Prediction capabilities of each model were assessed with receiver operating characteristic (ROC) curve analysis. Performance of the nomogram was evaluated by its calibration and potential clinical usefulness.

Results

For the prediction of good response (GR) and pathologic complete response (pCR), the developed radiomics signature comprising 10 and 7 features, respectively, were significantly associated with the therapeutic response to nCRT. The nomogram incorporating the radiomics signature and important clinical predictors (CEA and CA19-9 for predicting GR; CEA, posttreatment length and posttreatment thickness for predicting pCR) achieved favorable prediction efficacy, with AUCs of 0.918 (95% confidence interval [CI]: 0.867–0.971, Sen = 0.972, Spe = 0.828) and 0.944 (95% CI: 0.891–0.997, Sen = 0.943, Spe = 0.828) in the training and validation cohort for predicting GR, respectively; with AUCs of 0.959 (95% CI: 0.927–0.991, Sen = 1.000, Spe = 0.833) and 0.912 (95% CI: 0.843–0.982, Sen = 1.000, Spe = 0.815) in the training and validation cohort for predicting pCR, respectively. Decision curve analysis confirmed potential clinical usefulness of our nomogram.

Conclusions

This study demonstrated that the MRI-based radiomics nomogram is predictive of response to nCRT and can be considered as a promising tool for facilitating treatment decision-making for patients with LARC.

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Data availability

The data and material that support the findings of this study are available from the corresponding author upon reasonable request.

Code availability

The code that supports the findings of this study is available from the corresponding author upon reasonable request.

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Funding

The study was funded by Climbing Fund of National Cancer Center (NCC201806B011), Shenyang Municipal Science and Technology Project (F16-206–9-23), National Natural Science Foundation of China (81872363), Major Technology Plan Project of Shenyang (17–230-9–07), Supporting Fund for Big data in Health Care (HMB201903101), Special foundation for the central government guides the development of local science and technology of Liaoning Province (2018416029), Education Department Foundation of Liaoning (LQNK201744), Key Program of Ministry of Science and Technology of China [2017YFC1309100], China National Natural Science Foundation (31770147) and Medical-Engineering Joint Fund for Cancer Hospital of China Medical University and Dalian University of technology (LD202029).

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Authors and Affiliations

  1. Department of Biomedical Engineering, School of Fundamental Sciences, China Medical University, Shenyang, 110122, People’s Republic of China

    Yuan Cheng, Yue Hu & Xiran Jiang

  2. Department of Radiology, Cancer Hospital of China Medical University, Liaoning Cancer Hospital and Institute, Shenyang, 110042, People’s Republic of China

    Yahong Luo, Zhaohe Zhang, Xingling Wang, Qing Yu, Guanyu Liu & Tao Yu

  3. School of Computer Science and Engineering, Shenyang University, Shenyang, 110044, People’s Republic of China

    Enuo Cui

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  1. Yuan Cheng
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Contributions

XJ, YL and YC: study design. ZZ and YC: data collection. YC, YH, XW, QY, GL and EC: data analysis and interpretation. XJ and YC: manuscript writing. TY and YL: funding acquisition. All authors contributed to the article and approved the submitted version.

Corresponding author

Correspondence to Xiran Jiang.

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Conflict of interest

The authors declare that they have no conflict of interest. Yuan Cheng, Yahong Luo and Yue Hu have made equal intellectual contributions to the manuscript.

Ethical approval

The studies involving human participants were reviewed and approved by the Cancer Hospital of China Medical University review board approved this retrospective study. Written informed consent for participation was not required for this study in accordance with the national legislation and the institutional requirements.

Consent to participate

The ethics committee of our hospital approved our retrospective study (No.2018010), and waived the requirement of informed consent.

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Cheng, Y., Luo, Y., Hu, Y. et al. Multiparametric MRI-based Radiomics approaches on predicting response to neoadjuvant chemoradiotherapy (nCRT) in patients with rectal cancer. Abdom Radiol 46, 5072–5085 (2021). https://doi.org/10.1007/s00261-021-03219-0

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