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Predicting pathological complete response by comparing MRI-based radiomics pre- and postneoadjuvant radiotherapy for locally advanced rectal cancer

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Predicting pathological complete response by comparing MRI-based radiomics pre- and postneoadjuvant radiotherapy for locally advanced rectal cancer. / Li, Yuqiang; Liu, Wenxue; Pei, Qian; Zhao, Lilan; Güngör, Cenap; Zhu, Hong; Song, Xiangping; Li, Chenglong; Zhou, Zhongyi; Xu, Yang; Wang, Dan; Tan, Fengbo; Yang, Pei; Pei, Haiping.

In: CANCER MED-US, Vol. 8, No. 17, 12.2019, p. 7244-7252.

Research output: SCORING: Contribution to journal › SCORING: Journal article › Research › peer-review

Harvard

Li, Y, Liu, W, Pei, Q, Zhao, L, Güngör, C, Zhu, H, Song, X, Li, C, Zhou, Z, Xu, Y, Wang, D, Tan, F, Yang, P & Pei, H 2019, 'Predicting pathological complete response by comparing MRI-based radiomics pre- and postneoadjuvant radiotherapy for locally advanced rectal cancer', CANCER MED-US, vol. 8, no. 17, pp. 7244-7252. https://doi.org/10.1002/cam4.2636

APA

Li, Y., Liu, W., Pei, Q., Zhao, L., Güngör, C., Zhu, H., Song, X., Li, C., Zhou, Z., Xu, Y., Wang, D., Tan, F., Yang, P., & Pei, H. (2019). Predicting pathological complete response by comparing MRI-based radiomics pre- and postneoadjuvant radiotherapy for locally advanced rectal cancer. CANCER MED-US, 8(17), 7244-7252. https://doi.org/10.1002/cam4.2636

Vancouver

Li Y, Liu W, Pei Q, Zhao L, Güngör C, Zhu H et al. Predicting pathological complete response by comparing MRI-based radiomics pre- and postneoadjuvant radiotherapy for locally advanced rectal cancer. CANCER MED-US. 2019 Dec;8(17):7244-7252. https://doi.org/10.1002/cam4.2636

Bibtex

@article{8023a01d5bc24880b50fc55e6a2237f7,
title = "Predicting pathological complete response by comparing MRI-based radiomics pre- and postneoadjuvant radiotherapy for locally advanced rectal cancer",
abstract = "BACKGROUND: Total mesorectal excision following neoadjuvant chemoradiotherapy (nCRT) is recommended in the latest treatment of locally advanced rectal cancer (LARC).OBJECTIVE: To predict whether patients with LARC can achieve pathologic complete response (pCR), comparing MRI-based radiomics between before and after neoadjuvant radiotherapy (nRT) was performed.METHODS: One hundred and sixty-five MRI-based radiomics features in axial T2-weighted images were obtained quantitatively from Imaging Biomarker Explorer Software. The specific features of conventional and developing radiomics were selected with the analysis of least absolute shrinkage and selection operator logistic regression, of which the predictive performance was analyzed with receiver operating curve and calibration curve, and applied to an independent cohort.RESULTS: One hundred and thirty-one target patients were enrolled in the present study. A radiomics signature founded on seven radiomics features was generated in the primary cohort. A remarkable difference about Rad-score between pCR and non-pCR group occurred in both of primary (P < .001) or validation cohorts (P < .001). The value of area under the curves was 0.92 (95% CI, 0.86-0.99) and 0.87 (95% CI, 0.74-1.00) in the primary and validation cohorts, respectively. The Rad-score (OR = 23.581; P < .001) from multivariate logistic regression analysis was significant as an independent factor of pCR.CONCLUSION: Our predictive model based on radiomics features was an independent predictor for pCR in LARC and could be a candidate in clinical practice.",
author = "Yuqiang Li and Wenxue Liu and Qian Pei and Lilan Zhao and Cenap G{\"u}ng{\"o}r and Hong Zhu and Xiangping Song and Chenglong Li and Zhongyi Zhou and Yang Xu and Dan Wang and Fengbo Tan and Pei Yang and Haiping Pei",
note = "{\textcopyright} 2019 The Authors. Cancer Medicine published by John Wiley & Sons Ltd.",
year = "2019",
month = dec,
doi = "10.1002/cam4.2636",
language = "English",
volume = "8",
pages = "7244--7252",
journal = "CANCER MED-US",
issn = "2045-7634",
publisher = "John Wiley and Sons Ltd",
number = "17",

}

RIS

TY - JOUR

T1 - Predicting pathological complete response by comparing MRI-based radiomics pre- and postneoadjuvant radiotherapy for locally advanced rectal cancer

AU - Li, Yuqiang

AU - Liu, Wenxue

AU - Pei, Qian

AU - Zhao, Lilan

AU - Güngör, Cenap

AU - Zhu, Hong

AU - Song, Xiangping

AU - Li, Chenglong

AU - Zhou, Zhongyi

AU - Xu, Yang

AU - Wang, Dan

AU - Tan, Fengbo

AU - Yang, Pei

AU - Pei, Haiping

N1 - © 2019 The Authors. Cancer Medicine published by John Wiley & Sons Ltd.

PY - 2019/12

Y1 - 2019/12

N2 - BACKGROUND: Total mesorectal excision following neoadjuvant chemoradiotherapy (nCRT) is recommended in the latest treatment of locally advanced rectal cancer (LARC).OBJECTIVE: To predict whether patients with LARC can achieve pathologic complete response (pCR), comparing MRI-based radiomics between before and after neoadjuvant radiotherapy (nRT) was performed.METHODS: One hundred and sixty-five MRI-based radiomics features in axial T2-weighted images were obtained quantitatively from Imaging Biomarker Explorer Software. The specific features of conventional and developing radiomics were selected with the analysis of least absolute shrinkage and selection operator logistic regression, of which the predictive performance was analyzed with receiver operating curve and calibration curve, and applied to an independent cohort.RESULTS: One hundred and thirty-one target patients were enrolled in the present study. A radiomics signature founded on seven radiomics features was generated in the primary cohort. A remarkable difference about Rad-score between pCR and non-pCR group occurred in both of primary (P < .001) or validation cohorts (P < .001). The value of area under the curves was 0.92 (95% CI, 0.86-0.99) and 0.87 (95% CI, 0.74-1.00) in the primary and validation cohorts, respectively. The Rad-score (OR = 23.581; P < .001) from multivariate logistic regression analysis was significant as an independent factor of pCR.CONCLUSION: Our predictive model based on radiomics features was an independent predictor for pCR in LARC and could be a candidate in clinical practice.

AB - BACKGROUND: Total mesorectal excision following neoadjuvant chemoradiotherapy (nCRT) is recommended in the latest treatment of locally advanced rectal cancer (LARC).OBJECTIVE: To predict whether patients with LARC can achieve pathologic complete response (pCR), comparing MRI-based radiomics between before and after neoadjuvant radiotherapy (nRT) was performed.METHODS: One hundred and sixty-five MRI-based radiomics features in axial T2-weighted images were obtained quantitatively from Imaging Biomarker Explorer Software. The specific features of conventional and developing radiomics were selected with the analysis of least absolute shrinkage and selection operator logistic regression, of which the predictive performance was analyzed with receiver operating curve and calibration curve, and applied to an independent cohort.RESULTS: One hundred and thirty-one target patients were enrolled in the present study. A radiomics signature founded on seven radiomics features was generated in the primary cohort. A remarkable difference about Rad-score between pCR and non-pCR group occurred in both of primary (P < .001) or validation cohorts (P < .001). The value of area under the curves was 0.92 (95% CI, 0.86-0.99) and 0.87 (95% CI, 0.74-1.00) in the primary and validation cohorts, respectively. The Rad-score (OR = 23.581; P < .001) from multivariate logistic regression analysis was significant as an independent factor of pCR.CONCLUSION: Our predictive model based on radiomics features was an independent predictor for pCR in LARC and could be a candidate in clinical practice.

U2 - 10.1002/cam4.2636

DO - 10.1002/cam4.2636

M3 - SCORING: Journal article

C2 - 31642204

VL - 8

SP - 7244

EP - 7252

JO - CANCER MED-US

JF - CANCER MED-US

SN - 2045-7634

IS - 17

ER -