Characterizing MRI features of rectal cancers with different KRAS status

Abstract

Background: To investigate whether MRI findings, including texture analysis, can differentiate KRAS mutation status in rectal cancer. Methods: Totally, 158 patients with pathologically proved rectal cancers and preoperative pelvic MRI examinations were enrolled. Patients were stratified into two groups: KRAS wild-type group (KRAS wt group) and KRAS mutation group (KRAS mt group) according to genomic DNA extraction analysis. MRI findings of rectal cancers (including texture features) and relevant clinical characteristics were statistically evaluated to identify the differences between the two groups. The independent samples t test or Mann-Whitney U test were used for continuous variables. The differences of the remaining categorical polytomous variables were analyzed using the Chi-square test or Fisher exact test. A receiver operating characteristic (ROC) curve analysis was performed to evaluate the discriminatory power of MRI features. The area under the ROC curve (AUC) and the optimal cutoff values were calculated using histopathology diagnosis as a reference; meanwhile, sensitivity and specificity were determined. Results: Mean values of six texture parameters (Mean, Variance, Skewness, Entropy, gray-level nonuniformity, runlength nonuniformity) were significantly higher in KRAS mt group compared to KRAS wt group (p < 0.0001, respectively). The AUC values of texture features ranged from 0.703~0.813. In addition, higher T stage and lower ADC values were observed in the KRAS mt group compared to KRAS wt group (t = 7.086, p = 0.029; t = − 2.708, p = 0.008). Conclusion: The MRI findings of rectal cancer, especially texture features, showed an encouraging value for identifying KRAS status.

Radiogenomics in Colorectal Cancer

“…Xu et al reported that lower Max-ADC, Mean-ADC, pure diffusion, and higher pseudo-diffusion coefficient values were demonstrated in the KRAS mutant group [ 74 ]. They also reported that mean values of the six textural features (Mean, Variance, Skewness, Entropy, gray-level nonuniformity, run length nonuniformity) were significantly higher in KRAS mutant group compared to the KRAS wild type group ( p < 0.0001) [ 75 ]. Histogram metric of diffusion kurtosis imaging showed moderate diagnostic significance for KRAS status in the Cui et al study [ 76 ].…”

Imaging features associated with survival outcomes among colorectal cancer patients with and without KRAS mutation

“…KRAS mutation has been found to be associated with polypoid tumor growth patterns with higher staging and with fewer cases with flat tumor gross pattern in early staging [22,32,33,[52][53][54][55][56][57]. In this study, neither tumor size (including mean ATL, mean LTL, and mean ATL/ LTL) nor tumor morphology patterns differed significantly between CRC patients with and without KRAS mutation (P = 0.937, P = 0.723, and P = 0.888, respectively).…”

“…As far as imaging correlates between CRC and KRAS mutation, changes have been reported on magnetic resonance imaging (MRI) [30] between tumors with KRAS mutation than wild type. Published studies have found that the size of the primary rectal carcinomas differed significantly in patients with and without KRAS mutations [31]; certain MRI texture features were significantly associated with KRAS mutation status in patients with rectal cancer [32]. Rectal carcinoma with KRAS mutation were associated with higher N stage, polypoid mass with greater tumor length on MRI [33].…”

Radiomics and Magnetic Resonance Imaging of Rectal Cancer: From Engineering to Clinical Practice

“…Using T2-weighted MRI-based texture analysis, Oh et al identified three imaging features, which could preoperatively differentiate mutant from wild-type KRAS, yielding a sensitivity, specificity and accuracy of 84%, 80%, and 81.7%, respectively [ 75 ]. In a study involving 158 patients with pathologically proven RC, who had undergone preoperative MRI, the mean values of six texture parameters (mean, variance, skewness, entropy, gray-level nonuniformity, run-length nonuniformity) were significantly higher in KRAS-mutant patients than KRAS wild-type patients having AUC values of texture features ranging from 0.703 to 0.81, and higher T stage and lower ADC values occurring in KRAS-mutant cancers [ 76 ] ( Figure 7 ). Meng et al developed a radiomic model from MRI datasets of 345 patients with RC taking into account multiple factors, such as lymph node metastasis, tumor differentiation grade, a fraction of Ki-67-positive tumor cells, human epidermal growth factor receptor 2 (HER-2) expression and KRAS-2 gene mutation status, yielding an AUC of 0.699 for signatures evaluating Ki-67 and of 0.697 for an integrated evaluation model incorporating radiomics signature and MRI-reported lymph node status [ 27 ].…”

“… ROC curves corresponding to quantitative texture features derived from T2-weighted MR images for differentiating KRAS mutation status in rectal cancer. Adapted from [ 76 ]. …”