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合成MRI定量弛豫参数对不同病理类型腮腺肿瘤的鉴别诊断

张赞霞 李淑健 张勇 汪卫建 宋曼莉 王文豪 文宝红 程敬亮

郑州大学学报(医学版)2024,Vol.59Issue(2):252-255,4.
郑州大学学报(医学版)2024,Vol.59Issue(2):252-255,4.DOI:10.13705/j.issn.1671-6825.2023.03.012

合成MRI定量弛豫参数对不同病理类型腮腺肿瘤的鉴别诊断

Differential diagnosis value of synthetic MRI quantitative relaxation pa-rameter for parotid gland tumors

张赞霞 1李淑健 1张勇 1汪卫建 1宋曼莉 1王文豪 1文宝红 1程敬亮1

作者信息

  • 1. 郑州大学第一附属医院磁共振科 郑州 450052
  • 折叠

摘要

Abstract

Aim:To investigate the differential diagnostic value of quantitative relaxation parameters derived from syn-thetic MRI for common tumors of the parotid gland.Methods:A total of 59 patients with parotid gland tumors admitted to the First Affiliated Hospital of Zhengzhou University from May 2022 to January 2023 were selected.All patients underwent conventional MRI and synthetic MRI before treatment,and whole-tumor relaxation parameters including longitudinal relaxa-tion time(T1),transverse relaxation time(T2),and proton density(PD)of the tumors were measured.T1,T2,and PD were compared among the pleomorphic adenoma group,Warthin tumor group,and malignant tumor group.Bayes discriminant a-nalysis was applied to classify the 3 types of parotid gland tumors.Results:Significant differences in T1,T2,and PD were observed among the groups of pleomorphic adenoma,Warthin tumor,and malignant tumors(all P<0.001).T1 and PD of Warthin tumors were lower than those of malignant tumors and pleomorphic adenomas(P<0.05);T2 of pleomorphic adeno-mas were higher than those of malignant tumors and Warthin tumors(P<0.05).The accuracy of the diagnostic model es-tablished by Bayes discriminant analysis for self-validation was 61.0%,and that for cross-validation was 57.6%.Conclu-sion:Quantitative relaxation parameters based on synthetic MRI are helpful for the classification and identification of parotid pleomorphic adenomas,Warthin tumors,and malignant tumors.

关键词

腮腺肿瘤/合成磁共振成像/定量弛豫参数

Key words

parotid gland tumor/synthetic MRI/quantitative relaxation parameters

分类

医药卫生

引用本文复制引用

张赞霞,李淑健,张勇,汪卫建,宋曼莉,王文豪,文宝红,程敬亮..合成MRI定量弛豫参数对不同病理类型腮腺肿瘤的鉴别诊断[J].郑州大学学报(医学版),2024,59(2):252-255,4.

基金项目

工信部公共服务平台项目(2020-0103-3-1) (2020-0103-3-1)

郑州大学学报(医学版)

OA北大核心CSTPCD

1671-6825

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