Spectral CT imaging in colorectal cancer: current applications, limitations, and future perspectives

Colorectal cancer (CRC) is the third most common malignancy worldwide, and early detection is vital to prevent metastasis and postoperative recurrence. This review summarizes current applications of spectral computed tomography (CT) in CRC, including its principles, spectral parameters used for evaluating primary and metastatic lesions, and key findings from recent literature. A systematic search of PubMed, Web of Science, and Google Scholar identified English-language studies published between April 2018 and April 2025 using the keywords: "spectral CT," "spectral imaging," "dual-layer spectral CT," "dual-energy spectral CT," "colorectal cancer," and "colon cancer." Spectral CT has shown promise in improving CRC detection and T staging accuracy, increasing sensitivity for lesion characterization, and aiding prognostic assessment after chemotherapy using baseline spectral parameters. Early evidence suggests it may also help predict lymph node metastasis and identify patients at risk of early postoperative metastases or surgical complications. Spectral parameters have been correlated with KRAS mutation, Ki-67 index, microsatellite instability, lymphovascular, perineural, and extramural vascular invasion, as well as microvessel density. However, most studies remain small and observational, highlighting the need for validation in larger, multicenter cohorts. Standardization and the time-intensive nature of image segmentation currently limit widespread adoption. Nevertheless, spectral CT is expected to play an increasing role in CRC evaluation by providing quantitative, predictive imaging biomarkers. Integration with artificial intelligence, particularly deep learning and automated segmentation, will likely expand both research and clinical applications. CRITICAL RELEVANCE STATEMENT: This article explores the current applications of spectral CT in colorectal cancer by outlining the fundamentals of spectral CT, the spectral parameters used to assess, stage, and predict the prognosis of primary and metastatic disease, as well as the main findings from the current literature. KEY POINTS: Spectral CT may be helpful in the detection of colorectal primary tumors, lymph node metastases, and liver metastases, as well as in predicting treatment response. Spectral CT offers a non-invasive method to assess genetic mutations and prognostic factors associated with colorectal primaries. The lack of standardization in technology and measurement methods limits its applicability in clinical practice.

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Publication Details

Journal
Insights into Imaging
Published
2026-02-09
DOI
https://doi.org/10.1186/s13244-026-02212-9
Citations
1
Primary Topic
Advanced X-ray and CT Imaging
Type
article
Field-Weighted Citation Impact
21.28
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article

Spectral CT imaging in colorectal cancer: current applications, limitations, and future perspectives

Pascal Rousset, V. Kepenekian, Mathilde Wagner, N. Benzerdjeb et al.
1 citations
Insights into Imaging
Advanced X-ray and CT Imaging
21.28
article

Spectral CT imaging in colorectal cancer: current applications, limitations, and future perspectives

Pascal Rousset, V. Kepenekian, Mathilde Wagner, N. Benzerdjeb, Rémi Grange, Salim Aymeric Si-Mohamed, Olivier Glehen
article en
1 citations

Abstract

Colorectal cancer (CRC) is the third most common malignancy worldwide, and early detection is vital to prevent metastasis and postoperative recurrence. This review summarizes current applications of spectral computed tomography (CT) in CRC, including its principles, spectral parameters used for evaluating primary and metastatic lesions, and key findings from recent literature. A systematic search of PubMed, Web of Science, and Google Scholar identified English-language studies published between April 2018 and April 2025 using the keywords: "spectral CT," "spectral imaging," "dual-layer spectral CT," "dual-energy spectral CT," "colorectal cancer," and "colon cancer." Spectral CT has shown promise in improving CRC detection and T staging accuracy, increasing sensitivity for lesion characterization, and aiding prognostic assessment after chemotherapy using baseline spectral parameters. Early evidence suggests it may also help predict lymph node metastasis and identify patients at risk of early postoperative metastases or surgical complications. Spectral parameters have been correlated with KRAS mutation, Ki-67 index, microsatellite instability, lymphovascular, perineural, and extramural vascular invasion, as well as microvessel density. However, most studies remain small and observational, highlighting the need for validation in larger, multicenter cohorts. Standardization and the time-intensive nature of image segmentation currently limit widespread adoption. Nevertheless, spectral CT is expected to play an increasing role in CRC evaluation by providing quantitative, predictive imaging biomarkers. Integration with artificial intelligence, particularly deep learning and automated segmentation, will likely expand both research and clinical applications. CRITICAL RELEVANCE STATEMENT: This article explores the current applications of spectral CT in colorectal cancer by outlining the fundamentals of spectral CT, the spectral parameters used to assess, stage, and predict the prognosis of primary and metastatic disease, as well as the main findings from the current literature. KEY POINTS: Spectral CT may be helpful in the detection of colorectal primary tumors, lymph node metastases, and liver metastases, as well as in predicting treatment response. Spectral CT offers a non-invasive method to assess genetic mutations and prognostic factors associated with colorectal primaries. The lack of standardization in technology and measurement methods limits its applicability in clinical practice.

Insights into ImagingVol. 17(1)
Université Claude Bernard Lyon 1 (FR), Centre National de la Recherche Scientifique (FR), Inserm (FR), Lyon College (US), Sorbonne Université (FR), Hospices Civils de Lyon (FR), Hôpital Saint-Antoine (FR), Institute Cancer De La Loire Lucien Neuwirth (FR), Hôpital Lyon Sud (FR), Hôpital Louis Pradel (FR), Institut National des Sciences Appliquées de Lyon (FR)
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Openalex Percentile: Top 1%
Advanced X-ray and CT Imaging
21.28
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