Evidence map›Paper›PMID 42690280›Full record

ArticleRadiologie (Heidelberg, Germany)2026

Improved virtual non-contrast images in liver dual-energy CT with deep learning algorithm for image reconstruction.

Chuangbo Yang, Xinxin Meng, Yeming Su, Min Zhang, Nan Yu, Guangming Ma, Zhanli Ren

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Article in Radiologie (Heidelberg, Germany), 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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1 · What the graph read from it

What it found

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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

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

7 authors.

Chuangbo YangAffiliated Hospital of Shaanxi University of Chinese Medicine, 712000, Xianyang, Shaanxi, China.
Xinxin MengShaanxi University of Chinese Medicine, 712000, Xianyang, Shaanxi, China.
Yeming SuShaanxi University of Chinese Medicine, 712000, Xianyang, Shaanxi, China.
Min ZhangAffiliated Hospital of Shaanxi University of Chinese Medicine, 712000, Xianyang, Shaanxi, China.
Nan YuAffiliated Hospital of Shaanxi University of Chinese Medicine, 712000, Xianyang, Shaanxi, China.
Guangming MaAffiliated Hospital of Shaanxi University of Chinese Medicine, 712000, Xianyang, Shaanxi, China.
Zhanli RenAffiliated Hospital of Shaanxi University of Chinese Medicine, 712000, Xianyang, Shaanxi, China. rzl19900220@163.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundWe aimed to explore the use of deep learning image reconstruction (DLIR) to improve virtual non-contrast (VNC) images from enhanced dual-energy computed tomography (DECT). MATERIALS AND

methodsA total of 91 patients undergoing treatment for liver lesions from September to December 2024 were analyzed. All patients underwent true non-contrast (TNC) and dual-phase enhanced DECT with medium-level DLIR (DLIR-M). The VNC images were generated from arterial phase (VNC

resultsThere was no difference in CT values among the three groups (P > 0.05); VNC

conclusionVirtual non-contrast images generated in liver DECT with DLIR provide similar CT values to TNC images. The VNC ADVANCES IN KNOWLEDGE: Virtual non-contrast images with DLIR generated from DECT can improve image quality and reduce radiation dose.

Indexed as

Deep learningDual-energy CTImage qualityLow-doseVirtual non-contrast

Identifiers

PMID42690280

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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 OpenQuestion graph.