Evidence map›Paper›PMID 36264313›Full record

ArticleEuropean radiology2023

Two nomograms based on radiomics models using triphasic CT for differentiation of adrenal lipid-poor benign lesions and metastases in a cancer population: an exploratory study.

Gongzheng Wang, Bing Kang, Jingjing Cui, Yan Deng, Yun Zhao, Congshan Ji, Ximing Wang

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Article in European radiology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed, 1 pooled it
1.4field-weighted citation impact, top 19% 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

The trial behind it

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3 · Its place in the literature

Who cites it

8 citing papers in PubMed, 1 synthesis or guideline pooled it, 10 citations in OpenAlex.

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4 · The record

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5 · Who and what money

Authors and funding

7 authors at 4 institutions in 1 country.

Gongzheng WangDepartment of Radiology, Shandong Provincial Hospital, Shandong University, Jinan, 250021, Shandong, China.
Bing KangDepartment of Radiology, Shandong Provincial Hospital, Shandong University, Jinan, 250021, Shandong, China.
Jingjing CuiUnited Imaging Intelligence (Beijing) Co., Ltd., Beijing, 100094, China.
Yan DengDepartment of Radiology, Qilu Hospital of Shandong University, Jinan, 250012, Shandong, China.
Yun ZhaoDepartment of Radiology, Qilu Hospital of Shandong University, Jinan, 250012, Shandong, China.
Congshan JiDepartment of Radiology, Shandong Provincial Hospital, Shandong University, Jinan, 250021, Shandong, China. allensdu@sina.com.
Ximing WangDepartment of Radiology, Shandong Provincial Hospital, Shandong University, Jinan, 250021, Shandong, China. wxming369@163.com.ORCID http://orcid.org/0000-0002-1213-1003
Shandong University · CNQilu Hospital of Shandong University · CNShandong Provincial Hospital · CNUnited Imaging Healthcare (China) · CN

Funding

Academic Promotion Program of Shandong First Medical University 2019QL023National Natural Science Foundation of China 81571672National Natural Science Foundation of China 81871354
6 · The paper itself

Abstract

objectivesTo investigate the effectiveness of CT-based radiomics nomograms in differentiating adrenal lipid-poor benign lesions and metastases in a cancer population.

methodsThis retrospective study enrolled 178 patients with cancer history from three medical centres categorised as those with adrenal lipid-poor benign lesions or metastases. Patients were divided into training, validation, and external testing cohorts. Radiomics features were extracted from triphasic CT images (unenhanced, arterial, and venous) to establish three single-phase models and one triphasic radiomics model using logistic regression. Unenhanced and triphasic nomograms were established by incorporating significant clinico-radiological factors and radscores. The models were evaluated by the receiver operating characteristic curve, Delong's test, calibration curve, and decision curve.

resultsLesion side, diameter, and enhancement ratio resulted as independent factors and were selected into nomograms. The areas under the curves (AUCs) of unenhanced and triphasic radiomics models in validation (0.878, 0.914, p = 0.381) and external testing cohorts (0.900, 0.893, p = 0.882) were similar and higher than arterial and venous models (validation: 0.842, 0.765; testing: 0.814, 0.806). Unenhanced and triphasic nomograms yielded similar AUCs in validation (0.903, 0.906, p = 0.955) and testing cohorts (0.928, 0.946, p = 0.528). The calibration curves showed good agreement and decision curves indicated satisfactory clinical benefits.

conclusionUnenhanced and triphasic CT-based radiomics nomograms resulted as a useful tool to differentiate adrenal lipid-poor benign lesions from metastases in a cancer population. They exhibited similar predictive efficacies, indicating that enhanced examinations could be avoided in special populations. KEY POINTS: • All four radiomics models and two nomograms using triphasic CT images exhibited favourable performances in three cohorts to characterise the cancer population's adrenal benign lesions and metastases. • Unenhanced and triphasic radiomics models had similar predictive performances, outperforming arterial and venous models. • Unenhanced and triphasic nomograms also exhibited similar efficacies and good clinical benefits, indicating that contrast-enhanced examinations could be avoided when identifying adrenal benign lesions and metastases.

Indexed as

Liver NeoplasmsNomogramsHumansLipidsRetrospective StudiesTomography, X-Ray ComputedLipidsAdrenal glandsNeoplasm metastasisNomogramsRadiomicsTomography

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PMID36264313
OpenAlexW4306862546

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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.