Share:
Share this content in WeChat
X
Review
Research progress of neoadjuvant radiotherapy and chemotherapy for rectal cancer based on magnetic resonance imaging radiology
MA Ying  ZHAO Lianping  HUANG Gang 

Cite this article as: Ma Y, Zhao LP, Huang G. Research progress of neoadjuvant radiotherapy and chemotherapy for rectal cancer based on magnetic resonance imaging radiology. Chin J Magn Reson Imaging, 2020, 11(10): 947-949. DOI:10.12015/issn.1674-8034.2020.10.029.


[Abstract] Neoadjuvant chemoradiotherapy followed by total mesorectal excision is the standard treatment for locally advanced rectal cancer, so it is necessary to evaluate whether patients have a good response before treatment. Quantify MRI and functional imaging have limitations in prediction of response, while radiomics can predict the treatment efficacy by high-dimensional feature extraction. Therefore, this article reviews the methods and current status of quantify MRI andradiomics for predicting the efficacy of neoadjuvant chemoradiotherapy in patients with locally advanced rectal cancer.
[Keywords] rectal cancer;radiomics;neoadjuvant chemoradiotherapy;efficacy prediction;magnetic resonance imaging

MA Ying Clinical Medical College of Gansu University of Chinese Medicine, Lanzhou 730000, China

ZHAO Lianping Department of Radiology, Gansu Provincial Hospital, Lanzhou 730000, China

HUANG Gang* Department of Radiology, Gansu Provincial Hospital, Lanzhou 730000, China

*Correspondence to: Huang G, E-mail: keen0999@163.com

Conflicts of interest   None.

Received  2020-04-14
Accepted  2020-06-12
DOI: 10.12015/issn.1674-8034.2020.10.029
Cite this article as: Ma Y, Zhao LP, Huang G. Research progress of neoadjuvant radiotherapy and chemotherapy for rectal cancer based on magnetic resonance imaging radiology. Chin J Magn Reson Imaging, 2020, 11(10): 947-949. DOI:10.12015/issn.1674-8034.2020.10.029.

[1]
国家卫生计生委医政医管局,中华医学会肿瘤学分会.中国结直肠癌诊疗规范(2017年版).中国实用外科杂志, 2018, 38(10): 1089-1103.
[2]
Sun PL, Li B, Ye QF. Effect of neoadjuvant cetuximab, capecitabine, and radiotherapy for locally advanced rectal cancer: Results of a phase ii study. Int J Colorectal Dis, 2012, 27(10): 1325-1332.
[3]
Cho SH, Kim GC, Jang YJ, et al. Locally advanced rectal cancer: Post-chemoradiotherapy adc histogram analysis for predicting a complete response. Acta Radiol, 2015, 56(9): 1042-1050.
[4]
van de Velde CJH, Boelens PG, Borras JM, et al. Eurecca colorectal: Multidisciplinary management: European consensus conference colon & rectum. Eur J Cancer, 2014, 50(1): 1-34.
[5]
De Felice F, Magnante AL, Musio D, et al. Diffusion-weighted magnetic resonance imaging in locally advanced rectal cancer treated with neoadjuvant chemoradiotherapy. Eur J Surg Oncol, 2017, 43(7): 1324-1329.
[6]
Lambin P, Rios-Velazquez E, Leijenaar R, et al. Radiomics: Extracting more information from medical images using advanced feature analysis. Eur J Cancer, 2012, 48(4): 441-446.
[7]
Gillies RJ, Kinahan PE, Hricak H. Radiomics: Images are more than pictures, they are data. Radiology, 2016, 278(2): 563-577.
[8]
Kiessling F. The changing face of cancer diagnosis: From computational image analysis to systems biology. Eur Radiol, 2018, 28(8): 3160-3164.
[9]
Ogura A, Konishi T, Cunningham C, et al. Neoadjuvant (chemo) radiotherapy with total mesorectal excision only is not sufficient to prevent lateral local recurrence in enlarged nodes: Results of the multicenter lateral node study of patients with low ct3/4 rectal cancer. J Clin Oncol, 2019, 37(1): 33-43.
[10]
Renehan AG, Malcomson L, Emsley R, et al. Watch-and-wait approach versus surgical resection after chemoradiotherapy for patients with rectal cancer (the oncore project): A propensity-score matched cohort analysis. Lancet Oncol, 2016, 17(2): 174-183.
[11]
São Julião GP, Karagkounis G, Fernandez LM, et al. Conditional survival in patients with rectal cancer and complete clinical response managed by watch and wait after chemoradiation: Recurrence risk over time. Ann Surg, DOI: 2019. DOI: 10.1097/SLA.0000000000003286.
[12]
Battersby NJ, Moran B, Yu S, et al. Mr imaging for rectal cancer: The role in staging the primary and response to neoadjuvant therapy. Expert Rev Gastroenterol Hepatol, 2014, 8(6): 703-719.
[13]
Gollins S, West N, Sebag-Montefiore D, et al. A prospective phase ii study of pre-operative chemotherapy then short-course radiotherapy for high risk rectal cancer. Copernicus, 2018, 119(6): 697-706.
[14]
Tarallo N, Angeretti MG, Bracchi E, et al. Magnetic resonance imaging in locally advanced rectal cancer: Quantitative evaluation of the complete response to neoadjuvant therapy. Pol J Radiol, 2018, 83: e600-e609.
[15]
Lambregts DMJ, Boellaard TN, Beets-Tan RGH. Response evaluation after neoadjuvant treatment for rectal cancer using modern mr imaging: A pictorial review. Insights Imaging, 2019, 10(1): 15.
[16]
Schurink NW, Lambregts DMJ, Beets-Tan RGH. Diffusion-weighted imaging in rectal cancer: Current applications and future perspectives. Br J Radiol, 2019, 92(1096): 20180655.
[17]
Jacobs L, Intven M, van Lelyveld N, et al. Diffusion-weighted mri for early prediction of treatment response on preoperative chemoradiotherapy for patients with locally advanced rectal cancer: A feasibility study. Ann Surg, 2016, 263(3): 522-528.
[18]
Xie H, Sun T, Chen M, et al. Effectiveness of the apparent diffusion coefficient for predicting the response to chemoradiation therapy in locally advanced rectal cancer: A systematic review and meta-analysis. Medicine (Baltimore), 2015, 94(6): e517.
[19]
Yu J, Xu Q, Song JC, et al. The value of diffusion kurtosis magnetic resonance imaging for assessing treatment response of neoadjuvant chemoradiotherapy in locally advanced rectal cancer. Eur Radiol, 2017, 27(5): 1848-1857.
[20]
Hu F, Tang W, Sun Y, et al. The value of diffusion kurtosis imaging in assessing pathological complete response to neoadjuvant chemoradiation therapy in rectal cancer: A comparison with conventional diffusion-weighted imaging. Oncotarget, 2017, 8(43): 75597-75606.
[21]
Bates DDB, Mazaheri Y, Lobaugh S, et al. Evaluation of diffusion kurtosis and diffusivity from baseline staging mri as predictive biomarkers for response to neoadjuvant chemoradiation in locally advanced rectal cancer. Abdom Radiol (NY), 2019, 44(11): 3701-3708.
[22]
Tong T, Sun Y, Gollub MJ, et al. Dynamic contrast-enhanced mri: Use in predicting pathological complete response to neoadjuvant chemoradiation in locally advanced rectal cancer. J Magn Reson Imaging, 2015, 42(3): 673-680.
[23]
Lambin P, Leijenaar RTH, Deist TM, et al. Radiomics: The bridge between medical imaging and personalized medicine. Nat Rev Clin Oncol, 2017, 14(12): 749-762.
[24]
Shayesteh SP, Alikhassi A, Farhan F, et al. Prediction of response to neoadjuvant chemoradiotherapy by mri-based machine learning texture analysis in rectal cancer patients. J Gastrointest Cancer, 2020, 51(2): 601-609.
[25]
Cui Y, Yang X, Shi Z, et al. Radiomics analysis of multiparametric mri for prediction of pathological complete response to neoadjuvant chemoradiotherapy in locally advanced rectal cancer. Eur Radiol, 2019, 29(3): 1211-1220.
[26]
van Griethuysen JJM, Lambregts DMJ. Radiomics performs comparable to morphologic assessment by expert radiologists for prediction of response to neoadjuvant chemoradiotherapy on baseline staging mri in rectal cancer. Abdominal Radiology, 2020, 45(3): 632-643.
[27]
Li Y, Liu W. Predicting pathological complete response by comparing mri-based radiomics pre- and postneoadjuvant radiotherapy for locally advanced rectal cancer. Cancer Med, 2019, 8(17): 7244-7252.
[28]
Larue RT, Defraene G, De Ruysscher D, et al. Quantitative radiomics studies for tissue characterization: A review of technology and methodological procedures. Br J Radiol, 2017, 90(1070): 20160665.
[29]
Yi X, Pei Q, Zhang Y, et al. Mri-based radiomics predicts tumor response to neoadjuvant chemoradiotherapy in locally advanced rectal cancer. Front Oncol, 2019, 9: 552.
[30]
Aerts HJ, Velazquez ER, Leijenaar RT, et al. Decoding tumour phenotype by noninvasive imaging using a quantitative radiomics approach. Nat Commun, 2014, 5: 4006.
[31]
Nardone V, Reginelli A, Scala F, et al. Magnetic-resonance-imaging texture analysis predicts early progression in rectal cancer patients undergoing neoadjuvant chemoradiation. Gastroenterol Res Prac, 2019, 2019: 8505798.
[32]
Li Y, Liu W, Pei Q, et al. Predicting pathological complete response by comparing mri-based radiomics pre- and postneoadjuvant radiotherapy for locally advanced rectal cancer. Cancer Med, 2019, 8(17): 7244-7252.
[33]
Cui Y, Yang X, Shi Z, et al. Radiomics analysis of multiparametric mri for prediction of pathological complete response to neoadjuvant chemoradiotherapy in locally advanced rectal cancer. Eur Radiol, 2019, 29(3): 1211-1220.
[34]
Giannini V, Mazzetti S, Bertotto I, et al. Predicting locally advanced rectal cancer response to neoadjuvant therapy with (18)f-fdg pet and mri radiomics features. Eur J Nuclear Med Molecular Imaging, 2019, 46(4): 878-888.
[35]
Bulens P, Couwenberg A, Intven M, et al. Predicting the tumor response to chemoradiotherapy for rectal cancer: Model development and external validation using mri radiomics. Radiother Oncol, DOI: 2019. DOI: 10.1016/j.radonc.2019.07.033.
[36]
Vickers AJ. Prediction models: Revolutionary in principle, but do they do more good than harm?. J Clin Oncol, 2011, 29(22): 2951-2952.
[37]
Bibault JE, Giraud P, Housset M, et al. Deep learning and radiomics predict complete response after neo-adjuvant chemoradiation for locally advanced rectal cancer. Sci Rep, 2018, 8(1): 12611.
[38]
Shi L, Zhang Y, Nie K, et al. Machine learning for prediction of chemoradiation therapy response in rectal cancer using pre-treatment and mid-radiation multi-parametric MRI. Magn Reson Imaging, 2019, 61: 33-40.

PREV Progress of Gd-EOB-DTPA in the diagnosis and evaluation of HCC
NEXT Research progress of functional magnetic resonance imaging in chronic kidney disease
  



Tel & Fax: +8610-67113815    E-mail: editor@cjmri.cn