Evidence map›Paper›PMID 38802736›Full record

ArticleBMC medical imaging2024

A study on the application of radiomics based on cardiac MR non-enhanced cine sequence in the early diagnosis of hypertensive heart disease.

Ze-Peng Ma, Shi-Wei Wang, Lin-Yan Xue, Xiao-Dan Zhang, Wei Zheng, Yong-Xia Zhao, Shuang-Rui Yuan, Gao-Yang Li, Ya-Nan Yu, Jia-Ning Wang and 1 more

Abstract read
In one paragraph

Article in BMC medical imaging, 2024. 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

11 authors.

Ze-Peng MaDepartment of Radiology, Affiliated Hospital of Hebei University/ Clinical Medical College, Hebei University, Baoding, 071000, China.
Shi-Wei WangCollege of Quality and Technical Supervision, Hebei University, Baoding, 071002, China.
Lin-Yan XueCollege of Quality and Technical Supervision, Hebei University, Baoding, 071002, China.
Xiao-Dan ZhangDepartment of Ultrasound, Affiliated Hospital of Hebei University, 212 Yuhua East Road, Baoding, 071000, China. zxd201505@126.com.
Wei ZhengCollege of Electronic and Information Engineering, Hebei University, Baoding, 071002, China.
Yong-Xia ZhaoDepartment of Radiology, Affiliated Hospital of Hebei University/ Clinical Medical College, Hebei University, Baoding, 071000, China.
Shuang-Rui YuanDepartment of Radiology, Affiliated Hospital of Hebei University/ Clinical Medical College, Hebei University, Baoding, 071000, China.
Gao-Yang LiDepartment of Radiology, Affiliated Hospital of Hebei University/ Clinical Medical College, Hebei University, Baoding, 071000, China.
Ya-Nan YuDepartment of Radiology, Affiliated Hospital of Hebei University/ Clinical Medical College, Hebei University, Baoding, 071000, China.
Jia-Ning WangDepartment of Radiology, Affiliated Hospital of Hebei University/ Clinical Medical College, Hebei University, Baoding, 071000, China.
Tian-Le ZhangDepartment of Radiology, Affiliated Hospital of Hebei University/ Clinical Medical College, Hebei University, Baoding, 071000, China.

Funding

Baoding Science and Technology Plan Project 2241ZF298Medical Science Foundation of Hebei University 2023B03Medical Science Research Project of Health Commission of Hebei Province 20231477Postgraduate's Innovation Fund Project of Hebei University HBU2023BS001the Youth Research Fund of Affiliated Hospital of Hebei University 2021Q021
6 · The paper itself

Abstract

backgroundThe prevalence of hypertensive heart disease (HHD) is high and there is currently no easy way to detect early HHD. Explore the application of radiomics using cardiac magnetic resonance (CMR) non-enhanced cine sequences in diagnosing HHD and latent cardiac changes caused by hypertension.

methods132 patients who underwent CMR scanning were divided into groups: HHD (42), hypertension with normal cardiac structure and function (HWN) group (46), and normal control (NOR) group (44). Myocardial regions of the end-diastolic (ED) and end-systolic (ES) phases of the CMR short-axis cine sequence images were segmented into regions of interest (ROI). Three feature subsets (ED, ES, and ED combined with ES) were established after radiomic least absolute shrinkage and selection operator feature selection. Nine radiomic models were built using random forest (RF), support vector machine (SVM), and naive Bayes. Model performance was analyzed using receiver operating characteristic curves, and metrics like accuracy, area under the curve (AUC), precision, recall, and specificity.

resultsThe feature subsets included first-order, shape, and texture features. SVM of ED combined with ES achieved the highest accuracy (0.833), with a macro-average AUC of 0.941. AUCs for HHD, HWN, and NOR identification were 0.967, 0.876, and 0.963, respectively. Precisions were 0.972, 0.740, and 0.826; recalls were 0.833, 0.804, and 0.863, respectively; and specificities were 0.989, 0.863, and 0.909, respectively.

conclusionsRadiomics technology using CMR non-enhanced cine sequences can detect early cardiac changes due to hypertension. It holds promise for future use in screening for latent cardiac damage in early HHD.

Indexed as

Early DiagnosisHypertensionMagnetic Resonance Imaging, CineAdultAgedBayes TheoremFemaleHeart DiseasesHumansImage Interpretation, Computer-AssistedMaleMiddle AgedRadiomicsROC CurveSupport Vector MachineCardiac magnetic resonanceHypertensive heart diseaseLatent heart damageNon-enhanced cine sequenceRadiomics

Identifiers

PMID38802736
PMCPMC11129462

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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.