Functional MRI for quantitative treatment response prediction in locally advanced rectal cancer

Abstract

Despite advances in multimodality treatment strategies for locally advanced rectal cancer and improvements in locoregional control, there is still a considerable variation in response to neoadjuvant chemoradiotherapy (CRT). Accurate prediction of response to neoadjuvant CRT would enable early stratification of management according to good responders and poor responders, in order to adapt treatment to improve therapeutic outcomes in rectal cancer. Clinical studies in diffusion-weighted imaging (DWI) and dynamic contrast-enhanced (DCE) MRI have shown promising results for the prediction of therapeutic response in rectal cancer. DWI allows for assessment of tumour cellularity. DCE-MRI enables evaluation of factors of the tumour microvascular environment and changes in perfusion in response to treatment. Studies have demonstrated that predictors of good response to CRT include lower tumour pre-CRT apparent diffusion coefficient (ADC), greater percentage increase in ADC during and post CRT, and higher pre-CRT K^trans. However, the mean ADC and K^trans values do not adequately reflect tumour heterogeneity. Multiparametric MRI using quantitative DWI and DCE-MRI in combination, and a histogram analysis technique can assess tumour heterogeneity and its response to treatment. This strategy has the potential to improve the accuracy of therapeutic response prediction in rectal cancer and warrants further investigation.

Figure 1.

Diffusion-weighted imaging (DWI) MRI histogram analysis—apparent diffusion coefficient (ADC) colour-coded maps and histograms of a patient with good response following neoadjuvant chemoradiotherapy for rectal cancer. Example of ADC histogram analysis using Siemens OncoTreat (WIP), Erlangen, Germany. This patient had histological American Joint Committee on Cancer (7th edition) tumour regression grade 1 (moderate response, single cells or small groups of cancer cells). A voxel-by-voxel technique was used to assess changes in the entire region of interest. (a, c, e) Representative axial colour-coded ADC maps for MRI pre-chemoradiotherapy (CRT), Week 3 of CRT and post CRT, respectively. (b, d, f) Colour-coded histograms for every voxel within the segmented region of interest for DWI-MRI pre-CRT, Week 3 of CRT and post-CRT, respectively. Colour code: blue voxels, ADC values <1000 × 10⁻⁶; green voxels, ADC values 1000 − 1500 × 10⁻⁶; red voxels, ADC values >1500 × 10⁻⁶. The histograms demonstrate an increase in the absolute ADC values of voxels over the time points.

Figure 2.

Dynamic contrast-enhanced (DCE) MRI histogram analysis—K^trans colour-coded maps and histogram of the same patient with good response following neoadjuvant chemoradiotherapy for rectal cancer. Example of K^trans histogram analysis using Siemens OncoTreat (WIP) for the same patient as in Figure 1. A voxel-by-voxel technique was used. (a, c, e) Representative axial colour-coded K^trans maps for MRI pre-chemoradiotherapy (CRT), Week 3 of CRT and post CRT, respectively. (b, d, f) Colour-coded histograms for every voxel within the segmented region of interest for DCE-MRI pre CRT, Week 3 of CRT and post CRT, respectively. Colour code: blue voxels, K^trans values <100 × 10⁻³; green voxels, K^trans values 100 − 500 × 10⁻³; red voxels, K^trans values >500 × 10⁻³. The histograms demonstrate a marked reduction in the absolute K^trans values of voxels over the time points.