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24.07.2021 | Hollow Organ GI

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

verfasst von: Yuan Cheng, Yahong Luo, Yue Hu, Zhaohe Zhang, Xingling Wang, Qing Yu, Guanyu Liu, Enuo Cui, Tao Yu, Xiran Jiang

Erschienen in: Abdominal Radiology | Ausgabe 11/2021

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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.

Graphic abstract

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Titel: Multiparametric MRI-based Radiomics approaches on predicting response to neoadjuvant chemoradiotherapy (nCRT) in patients with rectal cancer
verfasst von: Yuan Cheng
Yahong Luo
Yue Hu
Zhaohe Zhang
Xingling Wang
Qing Yu
Guanyu Liu
Enuo Cui
Tao Yu
Xiran Jiang
Publikationsdatum: 24.07.2021
Verlag: Springer US
Erschienen in: Abdominal Radiology / Ausgabe 11/2021
Print ISSN: 2366-004X
Elektronische ISSN: 2366-0058
DOI: https://doi.org/10.1007/s00261-021-03219-0

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

Abstract

Purpose

Methods

Results

Conclusions

Graphic abstract

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Abstract

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Methods

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