Histogram Analysis of Perfusion Parameters from Dynamic Contrast-Enhanced MR Imaging with Tumor Characteristics and Therapeutic Response in Locally Advanced Rectal Cancer

• Main Authors: Dong Myung Yeo, Soon Nam Oh, Moon Hyung Choi, Sung Hak Lee, Myung Ah Lee, Seung Eun Jung
• Format: Article
• Language: English
• Published: Hindawi Limited 2018-01-01
• Series: BioMed Research International
• Online Access: http://dx.doi.org/10.1155/2018/3724393

Purpose. To explore the role of histogram analysis of perfusion parameters from dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) based on entire tumor volume in discriminating tumor characteristics and predicting therapeutic response in rectal cancer. Materials and Methods. Thirty-seven DCE-MRIs of locally advanced rectal cancer patients who received chemoradiation therapy (CRT) before surgery were analyzed by pharmacokinetic model for quantification and histogram analysis of perfusion parameters. The results were correlated with tumor characteristics including EGFR expression, KRAS mutation, and CRT response based on the pathologic tumor regression grade (TRG). Results. The area under the contrast agent concentration-time curve (AUC) skewness was significantly lower in patients with node metastasis. The vp histogram parameters were significantly higher in group with perineural invasion (PNI). The receiver operating characteristics (ROC) curve analyses showed that mode vp revealed the best diagnostic performance of PNI. The values of Ktrans and kep were significantly higher in the group with KRAS mutation. ROC curve analyses showed that mean and mode Ktrans demonstrated excellent diagnostic performance of KRAS mutation. DCE-MRI parameters did not demonstrate statistical significance in correlating with TRG. Conclusion. These preliminary results suggest that a larger proportion of higher AUC skewness was present in LN metastasis group and a higher vp histogram value was present in rectal cancer with PNI. In addition, Ktrans and kep histogram parameters showed difference according to the KRAS mutation, demonstrating the utility of the histogram of perfusion parameters derived from DCE-MRI as potential imaging biomarkers of tumor characteristics and genetic features.