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MRI texture analysis in predicting treatment response to neoadjuvant chemoradiotherapy in rectal cancer

To evaluate the importance of MRI texture analysis in prediction and early assessment of treatment response before and early neoadjuvant chemoradiotherapy (nCRT) in patients with locally advanced rectal cancer (LARC). This retrospective study comprised of 59 patients. The tumoral texture parameters...

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Detalles Bibliográficos
Autores principales: Meng, Yankai, Zhang, Chongda, Zou, Shuangmei, Zhao, Xinming, Xu, Kai, Zhang, Hongmei, Zhou, Chunwu
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Impact Journals LLC 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5844724/
https://www.ncbi.nlm.nih.gov/pubmed/29552288
http://dx.doi.org/10.18632/oncotarget.23813
Descripción
Sumario:To evaluate the importance of MRI texture analysis in prediction and early assessment of treatment response before and early neoadjuvant chemoradiotherapy (nCRT) in patients with locally advanced rectal cancer (LARC). This retrospective study comprised of 59 patients. The tumoral texture parameters were compared between pre- and early nCRT. Area Under receiver operating characteristic (ROC) Curves [AUCs] were used to compare the diagnostic performance of statistically significant difference parameters and logistic regression analysis predicted probabilities for discriminating responders and nonresponders. The Standard Deviation (SD), kurtosis and uniformity were statistically significantly difference between pre- and early nCRT (p = 0.0012, 0.0001, and < 0.0001, respectively). In pathological complete response (pCR) group, pre-uniformity and pre-Energy were significantly higher than that of nonresponders (p = 0.03 and p < 0.01, respectively), while the pre-entropy in nonresponder was reverse (p = 0.01). The diagnostic performance of pre-kurtosis and pre-Energy were higher in tumor regression grade (TRG) and pCR group (AUC = 0.67, 0.73, respectively). Logistic regression analysis showed that diagnostic performance for prediction responder and nonresponder did not significantly improve compared with to pre-uniformity, energy and entropy in pCR group (AUC = 0.76, p = 0.2794, 0.4222 and 0.3512, respectively). Texture parameters as imaging biomarkers have the potential to prediction and early assessment of tumoral treatment response to neoadjuvant chemoradiotherapy in patients with LARC.