Evidence map›Paper›PMID 40370653›Full record

ArticleProceedings of SPIE--the International Society for Optical Engineering2025

Contrast-guided Virtual Monoenergetic Image Synthesis via Adversarial Learning for Coronary CT Angiography using Photon Counting Detector CT.

Shaojie Chang, Madeleine Wilson, Emily K Koons, Hao Gong, Scott S Hsieh, Lifeng Yu, Cynthia H McCollough, Shuai Leng

Abstract read
In one paragraph

Article in Proceedings of SPIE--the International Society for Optical Engineering, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

8 authors.

Shaojie ChangDepartment of Radiology, Mayo Clinic, Rochester, MN, USA 55905.
Madeleine WilsonDepartment of Radiology, Mayo Clinic, Rochester, MN, USA 55905.
Emily K KoonsDepartment of Radiology, Mayo Clinic, Rochester, MN, USA 55905.
Hao GongDepartment of Radiology, Mayo Clinic, Rochester, MN, USA 55905.
Scott S HsiehDepartment of Radiology, Mayo Clinic, Rochester, MN, USA 55905.
Lifeng YuDepartment of Radiology, Mayo Clinic, Rochester, MN, USA 55905.
Cynthia H McColloughDepartment of Radiology, Mayo Clinic, Rochester, MN, USA 55905.
Shuai LengDepartment of Radiology, Mayo Clinic, Rochester, MN, USA 55905.

Funding

Comprehensive characterization of coronary atherosclerotic disease using photon-counting-detector dual-source CT and its impact on patient managementR01EB028590 · NIBIB · MAYO CLINIC ROCHESTER · PI LENG, SHUAI, MCCOLLOUGH, CYNTHIA H · 2020 to 2023
$2.6M
NIBIB NIH HHS R01 EB028590
6 · The paper itself

Abstract

Coronary CT angiography (cCTA) is a non-invasive diagnostic test for coronary artery disease (CAD) that often faces challenges with dense calcifications and stents due to blooming artifacts, leading to stenosis overestimation. Virtual monoenergetic images (VMIs) from photon counting detector CT (PCD-CT) provide distinct clinical benefits. Lower keV VMIs enhance iodine and bone contrasts but struggle with blooming artifacts, while higher keV VMIs effectively reduce beam hardening, blooming, and metal artifacts but diminish contrast, presenting a trade-off among different keV levels. To address this, we introduce a contrast-guided virtual monoenergetic image synthesis framework (CITRINE) utilizing adversarial learning to synthesize images by integrating beneficial spectral characteristics from various keV levels. In this study, CITRINE is trained and validated with cardiac PCD-CT images using 100 keV and 70 keV VMIs as examples, showcasing its ability to synthesize images that combine the reduced blooming artifacts of 100 keV VMIs with the high contrast-to-noise features of 70 keV VMIs. CITRINE's performance was evaluated on three patient cCTA cases quantitatively and qualitatively in terms of image quality and assessments of percent diameter luminal stenosis. The synthesized images showed reduced blooming artifacts, similar to those observed at 100 keV VMI, and exhibited high iodine contrast in the coronary lumen, comparable to that of 70 keV VMI. Notably, compared to the original 70 keV VMI, CITRINE images achieved approximately 25% reduction in percent diameter stenosis while maintaining consistent contrast levels. These results confirm CITRINE's effectiveness in improving diagnostic accuracy and efficiency in cCTA by leveraging the full potential of multi-energy and PCD-CT technologies.

Indexed as

cardiac CTPhoton counting detectorstenosis assessment

Identifiers

PMID40370653
PMCPMC12076251

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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.