Value of perfusion parameters from golden-angle radial sparse parallel dynamic contrast-enhanced magnetic resonance imaging in predicting pathological complete response after neoadjuvant chemoradiotherapy for locally advanced rectal cancer

Abstract

PURPOSE: Non-invasive methods for predicting pathological complete response (pCR) after neoadjuvant chemoradiotherapy (nCRT) can provide distinct leverage in the management of patients with locally advanced rectal cancer (LARC). This study aimed to investigate whether including the golden- angle radial sparse parallel (GRASP) dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) perfusion parameter (Ktrans), in addition to tumor regression grading (TRG) and apparent diffusion coefficient (ADC) values, can improve the predictive ability for pCR. METHODS: Patients with LARC who underwent nCRT and subsequent surgery were included. The imaging parameters were compared between patients with and without pCR. Receiver operating characteristic (ROC) curve analysis was used to evaluate the predictive ability of these parameters for pCR. RESULTS: A total of 111 patients were included in the study. A pCR was obtained in 32 patients (28.8%). MRI-based TRG (mrTRG) showed a negative correlation with pCR (r = −0.61, P < 0.001), and the average ADC value showed a positive correlation with pCR (r = 0.62, P < 0.001). Before nCRT, Ktrans in the pCR group was significantly higher than in the non-pCR group (1.30 ± 0.24 vs. 0.88 ± 0.34, P < 0.001), but no difference was identified after nCRT. Following ROC curve analysis, the area under the curve (AUC) of mrTRG (level 1–2), average ADC value, and Ktrans value for predicting pCR were 0.738 [95% confidence interval (CI): 0.65–0.82], 0.78 (95% CI: 0.69–0.86), and 0.84 (95% CI: 0.77–0.92), respectively. The model combining the three parameters had significantly higher predictive ability for pCR (AUC: 0.94, 95% CI: 0.88–0.98). CONCLUSION: The use of a combination of the GRASP DCE-MRI Ktrans with mrTRG and ADC can lead to a better pCR predictive performance.

Keywords

• rectal cancer
• locally advanced
• magnetic resonance imaging
• neoadjuvant chemoradiotherapy
• tumor regression grading
• complete response