Evidence map›Paper›PMID 40883616›Full record

ArticleEuropean radiology experimental2025

Virtual noncontrast images of adrenal lesions: a photon-counting CT prospective study.

Xin Bai, Lin Lu, Anli Tong, Jianhua Deng, Lili Xu, Xiaoxiao Zhang, Jiahui Zhang, Li Chen, Qianyu Peng, Erjia Guo and 8 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in European radiology experimental, 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. Review
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

18 authors.

Xin BaiDepartment of Radiology, State Key Laboratory of Complex Severe and Rare Disease, Peking Union Medical College Hospital, Peking Union Medical College, Chinese Academy of Medical Sciences, Beijing, China.
Lin LuDepartment of Endocrinology, State Key Laboratory of Complex Severe and Rare Disease, Peking Union Medical College Hospital, Peking Union Medical College, Chinese Academy of Medical Sciences, Beijing, China.
Anli TongDepartment of Endocrinology, State Key Laboratory of Complex Severe and Rare Disease, Peking Union Medical College Hospital, Peking Union Medical College, Chinese Academy of Medical Sciences, Beijing, China.
Jianhua DengDepartment of Urology, Peking Union Medical College Hospital, Peking Union Medical College, Chinese Academy of Medical Sciences, Beijing, China.
Lili XuDepartment of Radiology, State Key Laboratory of Complex Severe and Rare Disease, Peking Union Medical College Hospital, Peking Union Medical College, Chinese Academy of Medical Sciences, Beijing, China.
Xiaoxiao ZhangDepartment of Radiology, State Key Laboratory of Complex Severe and Rare Disease, Peking Union Medical College Hospital, Peking Union Medical College, Chinese Academy of Medical Sciences, Beijing, China.
Jiahui ZhangDepartment of Radiology, State Key Laboratory of Complex Severe and Rare Disease, Peking Union Medical College Hospital, Peking Union Medical College, Chinese Academy of Medical Sciences, Beijing, China.
Li ChenDepartment of Radiology, State Key Laboratory of Complex Severe and Rare Disease, Peking Union Medical College Hospital, Peking Union Medical College, Chinese Academy of Medical Sciences, Beijing, China.
Qianyu PengDepartment of Radiology, State Key Laboratory of Complex Severe and Rare Disease, Peking Union Medical College Hospital, Peking Union Medical College, Chinese Academy of Medical Sciences, Beijing, China.
Erjia GuoDepartment of Radiology, State Key Laboratory of Complex Severe and Rare Disease, Peking Union Medical College Hospital, Peking Union Medical College, Chinese Academy of Medical Sciences, Beijing, China.
Yongfei WuDepartment of Radiology, State Key Laboratory of Complex Severe and Rare Disease, Peking Union Medical College Hospital, Peking Union Medical College, Chinese Academy of Medical Sciences, Beijing, China.
Yun WangDepartment of Radiology, State Key Laboratory of Complex Severe and Rare Disease, Peking Union Medical College Hospital, Peking Union Medical College, Chinese Academy of Medical Sciences, Beijing, China.
Kai XuDepartment of Radiology, State Key Laboratory of Complex Severe and Rare Disease, Peking Union Medical College Hospital, Peking Union Medical College, Chinese Academy of Medical Sciences, Beijing, China.
Chao ZhangDepartment of Radiology, State Key Laboratory of Complex Severe and Rare Disease, Peking Union Medical College Hospital, Peking Union Medical College, Chinese Academy of Medical Sciences, Beijing, China.
Xi ZhaoSiemens Healthineers Digital Technology (Shanghai) Co. Ltd., Shanghai, China.
Zhengyu JinDepartment of Radiology, State Key Laboratory of Complex Severe and Rare Disease, Peking Union Medical College Hospital, Peking Union Medical College, Chinese Academy of Medical Sciences, Beijing, China.
Gumuyang ZhangDepartment of Radiology, State Key Laboratory of Complex Severe and Rare Disease, Peking Union Medical College Hospital, Peking Union Medical College, Chinese Academy of Medical Sciences, Beijing, China. zhang_stacey@163.com.ORCID http://orcid.org/0000-0002-6520-3138
Hao SunDepartment of Radiology, State Key Laboratory of Complex Severe and Rare Disease, Peking Union Medical College Hospital, Peking Union Medical College, Chinese Academy of Medical Sciences, Beijing, China. sunhao_robert@126.com.

Funding

Beijing Municipal Natural Science Foundation L232133National High-Level Hospital Clinical Research Funding 2022-PUMCH-A-033National High-Level Hospital Clinical Research Funding 2022-PUMCH-A-035National High-Level Hospital Clinical Research Funding 2022-PUMCH-B-068National High-Level Hospital Clinical Research Funding 2022-PUMCH-B-069National Key Research & Development Plan of China, Major Project of Prevention and Treatment for Common Diseases 2022YFC2505300, subproject 2022YFC2505304Peking Union Medical College Hospital Talent Cultivation Program (Category D) UHB11588
6 · The paper itself

Abstract

backgroundThe value of virtual noncontrast (VNC) images from photon-counting computed tomography (PCCT) for evaluating adrenal lesions and diagnosing adrenal adenomas remains to be clarified. MATERIALS AND

methodsParticipants with adrenal masses who underwent unenhanced and portal venous phase PCCT were prospectively included. Portal-venous phase images were reconstructed using conventional VNC (VNC

resultsThe study included 54 participants (27 females, mean age 45.3 years) with 68 adrenal lesions. Attenuation values on VNC were higher than those on TNC. TNC, VNC

conclusionVNC algorithms from PCCT overestimated CT attenuation of adrenal lesions. Higher thresholds showed better diagnostic performance for discriminating adrenal adenomas from non-adenomas than the established 10 HU. RELEVANCE STATEMENT: We investigated the application of VNC images from PCCT in adrenal disease. On VNC images, higher thresholds, superior to the accepted 10 HU, are needed for discriminating adenomas from non-adenomas, reducing the need for secondary examinations. KEY POINTS: This study investigated the value of VNC images from PCCT in adrenal lesions. VNC reconstruction overestimated the CT attenuation of adrenal lesions. Higher thresholds on VNC images were superior to the accepted 10 HU for differentiating adenomas from non-adenomas.

Indexed as

AdenomaAdrenal Gland NeoplasmsTomography, X-Ray ComputedAdultAgedFemaleHumansMaleMiddle AgedPhotonsProspective StudiesAdenomaAdrenal gland diseasesAdrenocortical adenomaTomography (x-ray computed)

Identifiers

PMID40883616
PMCPMC12396999

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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.