Role of advanced imaging techniques in the evaluation of oncological therapies in patients with colorectal liver metastases

Abstract

In patients with colorectal liver metastasis (CRLMs) unsuitable for surgery, oncological treatments, such as chemotherapy and targeted agents, can be performed. Cross-sectional imaging [computed tomography (CT), magnetic resonance imaging (MRI), 18-fluorodexoyglucose positron emission tomography with CT/MRI] evaluates the response of CRLMs to therapy, using post-treatment lesion shrinkage as a qualitative imaging parameter. This point is critical because the risk of toxicity induced by oncological treatments is not always balanced by an effective response to them. Consequently, there is a pressing need to define biomarkers that can predict treatment responses and estimate the likelihood of drug resistance in individual patients. Advanced quantitative imaging (diffusion-weighted imaging, perfusion imaging, molecular imaging) allows the in vivo evaluation of specific biological tissue features described as quantitative parameters. Furthermore, radiomics can represent large amounts of numerical and statistical information buried inside cross-sectional images as quantitative parameters. As a result, parametric analysis (PA) translates the numerical data contained in the voxels of each image into quantitative parameters representative of peculiar neoplastic features such as perfusion, structural heterogeneity, cellularity, oxygenation, and glucose consumption. PA could be a potentially useful imaging marker for predicting CRLMs treatment response. This review describes the role of PA applied to cross-sectional imaging in predicting the response to oncological therapies in patients with CRLMs.

Keywords: Colorectal cancer metastases; Computed tomography; Magnetic resonance imaging; Parametric imaging; Positron emission tomography; Prediction response.

Figure 1

Contrast enhanced computed tomography images from a patient with colon cancer. A: Baseline computed tomography (CT) demonstrates the presence of multiple liver metastases; B: After four cycles of combined chemotherapy (folinic acid + fluorouracil + irinotecan + cetuximab) the CT scan shows a reduction in both size and number of liver metastases, which was classified as a partial response with Response Evaluation Criteria in Solid Tumours criteria; C and D: The partial response was then confirmed after (C) 8 and (D) 12 chemotherapy cycles.

Figure 2

Schematic diagram showing how radiomics features can be extracted from medical images using a diffusion-weighted imaging image from an magnetic resonance imaging scan of a patient with colorectal liver metastasis as an example. The process begins on the left upper corner with image acquisition, followed by lesion segmentation on a dedicated software leading to a region of interest. The shape of the region of interest as well as the distribution and spatial relation of intensity values of each pixel are computationally analysed to extract radiomics features of different order.