Evidence map›Paper›PMID 37566275›Full record

ArticleEuropean radiology2024

Feasibility of spectral CT-derived extracellular volume fraction for differentiating aldosterone-producing from nonfunctioning adrenal nodules.

Yang Peng, Guanglei Tang, Mengya Sun, Shuang Yu, Yanglei Cheng, Yu Wang, Weiwei Deng, Yanbing Li, Jian Guan

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Article in European radiology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
1.6field-weighted citation impact, top 15% of its field
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

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3 · Its place in the literature

Who cites it

6 citing papers in PubMed, 8 citations in OpenAlex.

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4 · The record

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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

9 authors at 2 institutions in 1 country.

Yang PengDepartment of Radiology, The First Affiliated Hospital, Sun Yat-Sen University, No.58 Zhongshanerlu Road, Guangzhou, Guangdong, People's Republic of China.
Guanglei TangDepartment of Radiology, The First Affiliated Hospital, Sun Yat-Sen University, No.58 Zhongshanerlu Road, Guangzhou, Guangdong, People's Republic of China.
Mengya SunDepartment of Radiology, The First Affiliated Hospital, Sun Yat-Sen University, No.58 Zhongshanerlu Road, Guangzhou, Guangdong, People's Republic of China.
Shuang YuDepartment of Endocrinology, The First Affiliated Hospital, Sun Yat-Sen University, No.58 Zhongshanerlu Road, Guangzhou, Guangdong, People's Republic of China.
Yanglei ChengDepartment of Endocrinology, The First Affiliated Hospital, Sun Yat-Sen University, No.58 Zhongshanerlu Road, Guangzhou, Guangdong, People's Republic of China.
Yu WangDepartment of Interventional Oncology, The First Affiliated Hospital, Sun Yat-Sen University, No.58 Zhongshanerlu Road, Guangzhou, Guangdong, People's Republic of China.
Weiwei DengClinical & Technical Support, Philips Healthcare, China, 200072, Shanghai, People's Republic of China.
Yanbing LiDepartment of Endocrinology, The First Affiliated Hospital, Sun Yat-Sen University, No.58 Zhongshanerlu Road, Guangzhou, Guangdong, People's Republic of China. liyb@mail.sysu.edu.cn.
Jian GuanDepartment of Radiology, The First Affiliated Hospital, Sun Yat-Sen University, No.58 Zhongshanerlu Road, Guangzhou, Guangdong, People's Republic of China. guanj6@sysu.edu.cn.ORCID http://orcid.org/0000-0002-7209-0346
Sun Yat-sen University · CNPhilips (China) · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveTo assess the feasibility of spectral CT-derived extracellular volume (ECV) for differentiating aldosterone-producing nodules (APN) from nonfunctioning adrenal nodules (NFN).

methodsSixty-nine patients with biochemically and histologically confirmed unilateral APN (34) and NFN (35) as well as 23 patients with bilateral APN (19) and NFN (27) confirmed biochemically and by adrenal vein sampling (AVS) were enrolled in this retrospective study from October 2020 to April 2022. All patients underwent contrast-enhanced spectral CT of the adrenal glands with a 10-min delayed phase. The haematocrit level was measured within 2 days of CT. An iodine density map was derived from the delayed CT. The ECV fractions of the APN and NFN were calculated and compared in the test cohort of 69 patients with unilateral adrenal nodules. The optimal cut-off value was determined to evaluate the diagnostic efficacy of the ECV fraction for differentiating APN from NFN in the validation cohort of 23 patients with bilateral adrenal nodules.

resultsThe ECV fractions of the APN (11.17 ± 4.57%) were significantly lower (p < 0.001) than that of the NFN (24.79 ± 6.01%) in the test cohort. At cut-off ECV value of 17.16%, the optimal area under the receiver operating characteristic curve was 0.974 (95% confidence interval: 0.942-1) with 91.4% sensitivity, 93.9% specificity, and 92.8% accuracy in the test cohort and 89.5% sensitivity, 96.3% specificity, and 93.5% accuracy in the validation cohort for differentiating APN from NFN.

conclusionThe spectral CT-derived ECV fraction can differentiate APN from NFN with high diagnostic performance. CLINICAL RELEVANCE STATEMENT: Spectral CT-derived extracellular volume fraction could accurately differentiate between adrenal aldosterone-producing nodules and nonfunctioning nodules. It might serve as a noninvasive alternative to adrenal vein sampling in primary aldosteronism patients with bilateral adrenal nodules. KEY POINTS: • Conventional CT cannot differentiate aldosterone-producing adrenal nodules from nonfunctioning nodules. • Extracellular volume of adrenal aldosterone-producing nodules was significantly lower than that of nonfunctioning nodules and normal adrenal glands. It can accurately differentiate between aldosterone-producing and nonfunctioning adrenal nodules. • Extracellular volume may be a novel, noninvasive biomarker alternative to adrenal vein sampling for determining the functional status of bilateral adrenal nodules in patients with primary aldosteronism.

Indexed as

AldosteroneHyperaldosteronismAdrenal GlandsFeasibility StudiesHumansRetrospective StudiesTomography, X-Ray ComputedAldosteroneAdrenal gland neoplasmsHyperaldosteronismTomography, X-ray computed

Identifiers

PMID37566275
OpenAlexW4385751280

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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.