Evidence map›Paper›PMID 42098885›Full record

ArticleCancer imaging : the official publication of the International Cancer Imaging Society2026

Analysis of colorectal liver metastases in photon-counting detector CT - optimizing imaging through spectral reconstruction.

Maximilian Moos, Tilman Emrich, Maximilian Nguyen, Sebastian Steinmetz, Roman Kloeckner, Felix Hahn, Paul Steiner, Constantin Scholz, Markus Moehler, Hauke Lang and 3 more

Abstract read
In one paragraph

Article in Cancer imaging : the official publication of the International Cancer Imaging Society, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

13 authors.

Maximilian MoosDepartment of Diagnostic and Interventional Radiology, University Medical Center of the Johannes Gutenberg University Mainz, Langenbeckstr. 1, 55131, Mainz, Germany. Maximilian.moos@unimedizin-mainz.de.
Tilman EmrichDepartment of Diagnostic and Interventional Radiology, University Medical Center of the Johannes Gutenberg University Mainz, Langenbeckstr. 1, 55131, Mainz, Germany.
Maximilian NguyenDepartment of Diagnostic and Interventional Radiology, University Medical Center of the Johannes Gutenberg University Mainz, Langenbeckstr. 1, 55131, Mainz, Germany.
Sebastian SteinmetzDepartment of Neuroradiology, University Medical Center of the Johannes Gutenberg University Mainz, Mainz, Germany.
Roman KloecknerInstitute of Interventional Radiology, University Hospital Schleswig-Holstein, Lübeck, Germany.
Felix HahnDepartment of Diagnostic and Interventional Radiology, University Medical Center of the Johannes Gutenberg University Mainz, Langenbeckstr. 1, 55131, Mainz, Germany.
Paul SteinerDepartment of Internal Medicine I, University Medical Center of the Johannes Gutenberg University Mainz, Mainz, Germany.
Constantin ScholzDepartment of General, Visceral and Transplant Surgery, University Medical Center of the Johannes Gutenberg University Mainz, Mainz, Germany.
Markus MoehlerDepartment of Internal Medicine I, University Medical Center of the Johannes Gutenberg University Mainz, Mainz, Germany.
Hauke LangDepartment of General, Visceral and Transplant Surgery, University Medical Center of the Johannes Gutenberg University Mainz, Mainz, Germany.
Tobias BäuerleDepartment of Diagnostic and Interventional Radiology, University Medical Center of the Johannes Gutenberg University Mainz, Langenbeckstr. 1, 55131, Mainz, Germany.
Tobias Jorg *Department of Diagnostic and Interventional Radiology, University Medical Center of the Johannes Gutenberg University Mainz, Langenbeckstr. 1, 55131, Mainz, Germany.
Lukas Müller *Department of Diagnostic and Interventional Radiology, University Medical Center of the Johannes Gutenberg University Mainz, Langenbeckstr. 1, 55131, Mainz, Germany.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeThe aim of this study was to evaluate the visibility of colorectal liver metastases (CRLM) using photon-counting detector computed tomography (PCD-CT) and to determine the optimal virtual monoenergetic image (VMI) and iodine map reconstructions for improved contrast detection between metastases and surrounding liver parenchyma. MATERIALS AND

methodsA total of 117 patients with 227 CRLM (up to three measurements per patient) who underwent abdominal PCD-CT for staging between 09/2022 and 08/2024 were retrospectively included. VMI were reconstructed at energy levels between 40 and 90 keV (in 10 keV increments), and scanner-generated iodine maps were additionally analysed. To quantify contrast between CRLM and liver parenchyma, the parenchyma-to-lesion ratio (PLR) was calculated for each VMI and iodine map. The contrast-to-noise ratio (CNR) was determined based on attenuation values of the metastases and the bilateral musculus erector spinae, as well as its standard deviation. For the iodine map, lesion and parenchyma iodine concentrations were used analogously. Subjective assessment of metastases visibility on the three best VMIs in PLR and CNR (40-60 keV) and iodine maps were independently performed by three radiologists.

resultsLesion and liver attenuation decreased steadily with higher keV levels. Iodine maps showed markedly higher iodine concentration in liver parenchyma than in metastases. The PLR was highest on the iodine map (3.29 ± 2.01), followed by 40 keV (2.19 ± 0.73). Regarding CNR, the 40 keV VMI showed the highest value (1.49 ± 1.70), followed by the iodine map (1.09 ± 0.99). CNR values decreased further at higher energies and significantly reduced at 70-90 keV. Paired superiority testing confirmed 40 keV as the best-performing VMI, showing significantly higher CNR than the iodine map, whereas PLR remained superior on the iodine map. Subjective ratings indicated that the 50 keV VMI provided the best visibility of CRLM. The iodine map consistently received lower subjective ratings across all criteria.

conclusionBoth iodine maps and low-keV VMIs, particularly at 40 keV, demonstrated high PLR and CNR values, contributing to improved depiction of CRLM in PCD-CT. The complementary use of these reconstructions may enhance lesion detection and overall diagnostic confidence.

Indexed as

Colorectal NeoplasmsLiver NeoplasmsRadiographic Image Interpretation, Computer-AssistedTomography, X-Ray ComputedAdultAgedAged, 80 and overContrast MediaFemaleHumansMaleMiddle AgedPhotonsRetrospective StudiesContrast MediaColorectal liver metastases (CRLM)Iodine mapPhoton-counting detector CTSpectral reconstructionVirtual monoenergetic image (VMI)

Identifiers

PMID42098885
PMCPMC13154852

What Socratic holds

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LicenceCC BY
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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.