Evidence map›Paper›PMID 39775026›Full record

ArticleAbdominal radiology (New York)2025

Optimal virtual monoenergy for the detection of pancreatic adenocarcinoma during the pancreatic parenchymal phase on photon counting CT.

Andrew Ruff, Xiaochun Li, Judith D Goldberg, Mark Ehrhart, Luke Ginocchio, Paul Smereka, Thomas O'Donnell, Bari Dane

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Article in Abdominal radiology (New York), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

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4citing papers in PubMed
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1 · What the graph read from it

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3 · Its place in the literature

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4 citing papers in PubMed.

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5 · Who and what money

Authors and funding

8 authors.

Andrew RuffNew York University, New York, USA.
Xiaochun LiNew York University, New York, USA.
Judith D GoldbergNew York University, New York, USA.
Mark EhrhartUniversity of New Mexico, Albuquerque, USA.
Luke GinocchioNew York University, New York, USA.
Paul SmerekaNew York University, New York, USA.
Thomas O'DonnellSiemens Healthineers (United States), Malvern, USA.
Bari DaneNew York University, New York, USA. bari.dane@nyulangone.org.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeAs the pancreas is a low contrast visibility organ, pancreatic ductal adenocarcinoma detection is challenging due to subtle attenuation differences between tumor and pancreatic parenchyma. Photon counting CT (PCCT) has superior iodine contrast-to-noise ratio than conventional CT and also affords the creation of low keV virtual monoenergetic images, both of which increase adenocarcinoma conspicuity. The purpose therefore was to identify the optimal virtual monoenergy for visualizing PDAC during the pancreatic parenchymal phase of enhancement at PCCT using both quantitative and qualitative analyses.

methodsConsecutive patients with pancreatic parenchymal phase PCCT source data were retrospectively identified by PACS search. For the quantitative analysis, region of interest (ROI) measurements were drawn in the pancreatic head, body, tail, pancreatic adenocarcinoma (if present), and psoas muscles on 40-120 keV virtual monoenergetic images in 10 keV increments. Based on the quantitative analysis results and vendor recommendations, four virtual monoenergies(40 keV, 55 keV, 70 keV, and 85 keV) were selected for additional qualitative analysis. Three radiologists blinded to four virtual monoenergies assessed overall image quality, image noise, pancreatic enhancement, and pancreatic mass conspicuity on 5-point Likert scales.

results54 patients (28/54 male, mean[SD] age: 62 [13] years) were included. Quantitatively, 40 keV had the highest pancreatic parenchymal CNR and attenuation difference between the adenocarcinoma and parenchyma, but also the highest noise (HUsd). Qualitatively, 70 keV had the best overall image quality (Mean [SE]: 3.7[0.1]) and lower noise than 40 and 55 keV (3.6[0.08] vs. 1.8[0.07] and 2.7[0.05], respectively, p < .001). 40 keV had the greatest pancreatic enhancement (mean[SE] 4.6[0.11]). Adenocarcinoma conspicuity ratings were greatest at 40 keV and 55 keV, and not significantly different from each other (mean[SE] 4.4[0.13] and 4.3[0.14], respectively, Tukey adj-p =.20). 55 keV had greater overall image quality and lower noise than 40 keV (mean[SE] 3.4[0.08] vs. 2.5[0.08], Tukey adj-p < .001 and 2.7[0.05] vs. 1.8[0.07], Tukey adj-p < .001 respectively).

conclusion55 keV pancreatic parenchymal phase virtual monoenergetic images afford optimal pancreatic assessment at PCCT for the visualization of pancreatic adenocarcinoma. Routinely viewing 55 keV virtual monoenergetic images at PCCT may improve PDAC detection.

Indexed as

AdenocarcinomaCarcinoma, Pancreatic DuctalPancreatic NeoplasmsTomography, X-Ray ComputedAgedAged, 80 and overContrast MediaFemaleHumansMaleMiddle AgedPhotonsRadiographic Image Interpretation, Computer-AssistedRetrospective StudiesContrast MediaComputed tomographyPancreatic adenocarcinomaPhoton-counting CTVirtual monoenergetic reformat

Identifiers

PMID39775026

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