Gastric cancer and imaging biomarkers: Part 1 - a critical review of DW-MRI and CE-MDCT findings

Abstract

The current standard of care for gastric cancer imaging includes heterogeneity in image acquisition techniques and qualitative image interpretation. In addition to qualitative assessment, several imaging techniques, including diffusion-weighted magnetic resonance imaging (DW-MRI), contrast-enhanced multidetector computed tomography (CE-MDCT), dynamic-contrast enhanced MRI and 18F-fluorodeoxyglucose positron emission tomography, can allow quantitative analysis. However, so far there is no consensus regarding the application of functional imaging in the management of gastric cancer. The aim of this article is to specifically review two promising biomarkers for gastric cancer with reasonable spatial resolution: the apparent diffusion coefficient (ADC) from DW-MRI and textural features from CE-MDCT. We searched MEDLINE/ PubMed for manuscripts published from inception to 6 February 2018. Initially, we searched for (gastric cancer OR gastric tumour) AND diffusion weighted magnetic resonance imaging. Then, we searched for (gastric cancer OR gastric tumour) AND texture analysis AND computed tomography. We collated the results from the studies related to this query. There is evidence that: (1) the ADC is a promising biomarker for the evaluation of the aggressiveness (T and N stage), treatment response and prognosis of gastric cancer; (2) textural features are related to the degree of differentiation, Lauren classification, treatment response and prognosis of gastric cancer. We conclude that these imaging biomarkers hold promise as effective additional tools in the diagnostic pathway of gastric cancer and may facilitate the multidisciplinary work between the radiologist and clinician, and across different institutions, to provide a greater biological understanding of gastric cancer. KEY POINTS: • Quantitative imaging is the extraction of quantifiable features from medical images for the assessment of normal or pathological conditions and represents a promising area for gastric cancer. • Quantitative analysis from CE-MDCT and DW-MRI allows the extrapolation of multiple imaging biomarkers. • ADC from DW-MRI and CE- MDCT-based texture features are non-invasive, quantitative imaging biomarkers that hold promise in the evaluation of the aggressiveness, treatment response and prognosis of gastric cancer.

Keywords: Biomarkers; Gastric cancer; Magnetic resonance imaging; Tomography.

Fig. 1

Flow diagrams showing the outcome of the initial searches resulting in the full studies included in the review for diffusion-weighted magnetic resonance imaging (DW-MRI) (a) and contrast-enhanced multidetector computed tomography (CE-MDCT) (b)

Fig. 2

The arrows indicate a tumour of the lesser curvature on T2-weighted imaging (a) and on diffusion-weighted magnetic resonance imaging (DW-MRI) using different b values (b–e). The apparent diffusion coefficient (ADC) is calculated on the ADC map (f) from a small (red) or large (yellow) region of interest (red) on a single slice

Fig. 3

Image of a tumour of the gastro-oesophageal junction on T2-weighted (a and c) and diffusion-weighted (b and d) imaging before and after treatment. There has been a decrease in the conspicuity on DW-MRI (d) and an increase in the apparent diffusion coefficient (ADC) value after treatment (d)

Fig. 4

Tumour of the antrum (arrows) using water (a; axial view) and air filling (b; coronal view) on contrast-enhanced multidetector computed tomography. Air filling is more accurate when drawing the regions of interest (ROIs) for texture analysis (blue: primary tumour; orange: pathological lymph node)

Fig. 5

Comparison between a protocol without and with administration of anti-peristaltic agent on multidetector computed tomography. The image shows how the region of interest (ROI) delineation is more reproducible at different time points in the second scenario. Unenhanced (a and d), arterial (b and e) and portal (c and f) phases

Fig. 6

Contrast-enhanced multidetector computed tomography images of different gastric cancers (arrows) that have been acquired using a standard protocol, thus allowing accurate regions of interest for texture analysis (a, b, e, taken as an example)