Multi-parametric MRI of rectal cancer - do quantitative functional MR measurements correlate with radiologic and...

The purpose of this study is two-fold. First, to evaluate, whether functional rectal MRI techniques can be analyzed in a reproducible manner by different readers and second, to assess whether different clinical and pathologic T and N stages can be differentiated by functional MRI measurements.

54 patients (38 men, 16 female; mean age 63.2 ± 12.2 years) with pathologically proven rectal cancer were included in this retrospective IRB-approved study. All patients were referred for a multi-parametric MRI protocol on a 3 Tesla MR-system, consisting of a high-resolution, axial T2 TSE sequence, DWI and perfusion imaging (plasma flow -s PFTumor) prior to any treatment. Two experienced radiologists evaluated the MRI measurements, blinded to clinical data and outcome. Inter-reader correlation and the association of functional MRI parameters with c- and p-staging were analyzed.

The inter-reader correlation for lymph node (ρ 0.76-0.94; p<0.0002) and primary tumor (ρ 0.78-0.92; p<0.0001) apparent diffusion coefficient and plasma flow (PF) values was good to very good. PFTumor values decreased with cT stage with significant differences identified between cT2 and cT3 tumors (229 versus 107.6 ml/100ml/min; p=0.05). ADCTumor values did not differ significantly. No substantial discrepancies in lymph node ADCLn values or short axis diameter were found among cN1-3 stages, whereas PFLn values were distinct between cN1 versus cN2 stages (p=0.03). In the patients without neoadjuvant RCT no statistically significant differences in the assessed functional parameters on the basis of pathologic stage were found.

This study illustrates that ADC as well as MR perfusion values can be analyzed with good interobserver agreement in patients with rectal cancer. Moreover, MR perfusion parameters may allow accurate differentiation of tumor stages. Both findings suggest that functional MRI parameters may help to discriminate T and N stages for clinical decision making.