Evidence map›Paper›PMID 41661515›Full record

ReviewInsights into imaging2026

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

Rémi Grange, Mathilde Wagner, Nazim Benzerdjeb, Olivier Glehen, Vahan Kepenekian, Salim Si-Mohamed, Pascal Rousset

Abstract readReview
In one paragraph

Review in Insights into imaging, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

7 citing papers in PubMed.

  1. Review
  2. Liver metastases beyond classical imaging findings.Abdominal radiology (New York) · 2026
    Review
  3. Development of a nomogram for predicting extramural venous invasion in colon cancer using spectral CT multiparameter imaging.Cancer imaging : the official publication of the International Cancer Imaging Society · 2026
    Article
  4. Article
  5. Article
  6. Review
  7. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

Rémi GrangeDepartment of Radiology, University Hospital of Saint-Etienne, Saint-Priest-en-Jarez, France. Remgrange1@gmail.com.ORCID http://orcid.org/0000-0002-7465-2955
Mathilde WagnerDepartment of Radiology, Hopital Saint-Antoine, Paris, France.
Nazim BenzerdjebCICLY, EMR 3738, Lyon 1 University, Lyon, France.
Olivier GlehenCICLY, EMR 3738, Lyon 1 University, Lyon, France.
Vahan KepenekianCICLY, EMR 3738, Lyon 1 University, Lyon, France.
Salim Si-MohamedUniversity of Lyon, INSA-Lyon, Université Claude Bernard Lyon 1, UJM-Saint Etienne, CNRS, Inserm, CREATIS UMR 5220, U1206, F-69621, Villeurbanne, France.
Pascal RoussetCICLY, EMR 3738, Lyon 1 University, Lyon, France.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

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.

Indexed as

Colorectal cancerLiver metastasesPeritoneal metastasesSpectral CT

Identifiers

PMID41661515
PMCPMC12886653

What Socratic holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.