Evidence map›Paper›PMID 37891554›Full record

ArticleBMC medical imaging2023

Enhanced CT combined with texture analysis for differential diagnosis of pleomorphic adenoma and adenolymphoma.

Feifei Xia, Foqing Guo, Zhe Liu, Jie Zeng, Xuehua Ma, Chongqing Yu, Changxue Li

Abstract read
In one paragraph

Article in BMC medical imaging, 2023. 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

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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

1 citing paper in PubMed.

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4 · The record

Corrections and comments

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5 · Who and what money

Authors and funding

7 authors.

Feifei Xia *Department of Oral and Maxillofacial Surgery, the First Affiliated Hospital of Shihezi University, Shihezi, 832000, China.
Foqing Guo *Department of Oral and Maxillofacial Surgery, the First Affiliated Hospital of Shihezi University, Shihezi, 832000, China.
Zhe LiuDepartment of Oral and Maxillofacial Surgery, the First Affiliated Hospital of Shihezi University, Shihezi, 832000, China.
Jie ZengDepartment of Oral and Maxillofacial Surgery, the First Affiliated Hospital of Shihezi University, Shihezi, 832000, China.
Xuehua MaDepartment of Oral and Maxillofacial Surgery, the First Affiliated Hospital of Shihezi University, Shihezi, 832000, China.
Chongqing YuDepartment of Oral and Maxillofacial Surgery, the First Affiliated Hospital of Shihezi University, Shihezi, 832000, China.
Changxue LiDepartment of Oral and Maxillofacial Surgery, the First Affiliated Hospital of Shihezi University, Shihezi, 832000, China. 3541226598@qq.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveThis study sought to evaluate the worth of the general characteristics of enhanced CT images and the histogram parameters of each stage in distinguishing pleomorphic adenoma (PA) and adenolymphoma (AL).

methodsThe imaging features and histogram parameters of preoperative enhanced CT images in 20 patients with PA and 29 patients with AL were analyzed. Tumor morphology and histogram parameters of PA and AL were compared. Area under the curve (AUC), sensitivity, and subject operational feature specificity (ROC) analysis were used to determine the differential diagnostic effect of single-stage or multi-stage parameter combinations.

resultsThe difference in CT value and net enhancement value of arterial phase (AP) were significant (p < 0.05); Flat sweep phase (FSP), AP mean, percentiles, 10th, 50th, 90th, 99th and arterial period variance and venous phase (VP) kurtosis in the nine histogram parameters of each period (p < 0.05). An analysis of the ROC curve revealed a maximum area beneath the curve (AUC) in the 90th percentile of FSP for a single-parameter differential diagnosis to be 0.870. The diagnostic efficacy of the mean value of FSP + The 90th percentile of AP + Kurtosis of VP was the best in multi-parameter combination diagnosis, with an AUC of 0.925, and the sensitivity and specificity of 0.900 and 0.850, respectively.

conclusionThe histogram analysis of enhanced CT images is valuable for the differentiation of PA and AL. Moreover, the combination of single-stage parameters or multi-stage parameters can improve the differential diagnosis efficiency.

Indexed as

AdenolymphomaAdenoma, PleomorphicDiagnosis, DifferentialDiffusion Magnetic Resonance ImagingHumansRetrospective StudiesROC CurveTomography, X-Ray ComputedAdenolymphoma (AL)Enhancement CTPleomorphic adenoma (PA)Texture analysis

Identifiers

PMID37891554
PMCPMC10612226

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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.