Imaging Techniques for Gastric Cancer Diagnosis and Staging

The accurate diagnosis and staging of gastric cancer underpin effective treatment planning and prognostic evaluation. Modalities such as endoscopic ultrasonography (EUS), multidetector computed tomography (MDCT) and diffusion-weighted magnetic resonance imaging (DW-MRI) offer complementary insights into tumour depth, lymph node involvement and distant spread. Advances in dual-energy computed tomography (DECT) have yielded quantitative iodine maps that improve discrimination between early and advanced lesions, while positron emission tomography (PET) adds metabolic characterisation. Emerging approaches in radiomics and machine learning further enhance image interpretation by extracting high-dimensional features that correlate with histopathological and genomic profiles. Together, these techniques support a multidisciplinary strategy that balances anatomical detail, functional assessment and personalised risk stratification on a global scale.

Research from Nature Portfolio

Quantitative analysis of dual-energy spectral CT imaging has been shown to differentiate early from advanced gastric cancer by measuring iodine uptake, normalised iodine concentration and slope of the energy attenuation curve. These metrics correlate positively with cellular proliferation markers, indicating that dual-energy parameters may serve both as non-invasive staging biomarkers and as surrogates of tumour aggressiveness. The study demonstrated that advanced lesions exhibit higher iodine concentrations in venous and delayed phases, while normalised values reduce interpatient variability, thereby facilitating more precise preoperative assessment.

Imaging Techniques for Gastric Cancer Diagnosis and Staging publication trend

The graph below shows the total number of articles in imaging techniques for gastric cancer diagnosis and staging across all publications each year (not limited to Nature Index journals).

Technical terms

Dual-energy computed tomography (DECT): A CT technique that acquires images at two distinct energy spectra to generate quantitative material-specific maps and improve tissue characterisation.

Iodine concentration (IC): A quantitative measure of iodine uptake in tissue derived from DECT, reflecting tumour vascularity and perfusion.

Normalized iodine concentration (nIC): The ratio of tissue iodine concentration to a reference vascular structure, reducing variability and enhancing comparability.

Node-RADS: A structured reporting system that assigns categorical scores to lymph nodes based on combined size and morphological features to estimate metastatic likelihood.

Apparent diffusion coefficient (ADC): A parameter from DW-MRI representing the diffusivity of water molecules in tissue, used to assess cellular density and tumour aggressiveness.

References

1. Dual Energy Spectral CT Imaging in the assessment of Gastric Cancer and cell proliferation: A Preliminary Study. Scientific Reports (2018).
2. A quantitative model using multi-parameters in dual-energy CT to preoperatively predict serosal invasion in locally advanced gastric cancer. Insights into Imaging (2024).
3. Diagnostic performance of Node Reporting and Data System (Node-RADS) for regional lymph node staging of gastric cancer by CT. European Radiology (2023).