Suppr超能文献

基于定量磁共振成像的纹理分析在鼻咽癌中的应用:初步研究。

The utility of texture analysis based on quantitative synthetic magnetic resonance imaging in nasopharyngeal carcinoma: a preliminary study.

机构信息

Department of Diagnostic Radiology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100021, China.

MR Research China, GE Healthcare, Beijing, China.

出版信息

BMC Med Imaging. 2023 Jan 25;23(1):15. doi: 10.1186/s12880-023-00968-w.

Abstract

BACKGROUND

Magnetic resonance imaging (MRI) is commonly used for the diagnosis of nasopharyngeal carcinoma (NPC) and occipital clivus (OC) invasion, but a proportion of lesions may be missed using non-enhanced MRI. The purpose of this study is to investigate the diagnostic performance of synthetic magnetic resonance imaging (SyMRI) in differentiating NPC from nasopharyngeal hyperplasia (NPH), as well as evaluating OC invasion.

METHODS

Fifty-nine patients with NPC and 48 volunteers who underwent SyMRI examination were prospectively enrolled. Eighteen first-order features were extracted from VOIs (primary tumours, benign mucosa, and OC). Statistical comparisons were conducted between groups using the independent-samples t-test and the Mann-Whitney U test to select significant parameters. Multiple diagnostic models were then constructed using multivariate logistic analysis. The diagnostic performance of the models was calculated by receiver operating characteristics (ROC) curve analysis and compared using the DeLong test. Bootstrap and 5-folds cross-validation were applied to avoid overfitting.

RESULTS

The T1, T2 and PD map-derived models had excellent diagnostic performance in the discrimination between NPC and NPH in volunteers, with area under the curves (AUCs) of 0.975, 0.972 and 0.986, respectively. Besides, SyMRI models also showed excellent performance in distinguishing OC invasion from non-invasion (AUC: 0.913-0.997). Notably, the T1 map-derived model showed the highest diagnostic performance with an AUC, sensitivity, specificity, and accuracy of 0.997, 96.9%, 97.9% and 97.5%, respectively. By using 5-folds cross-validation, the bias-corrected AUCs were 0.965-0.984 in discriminating NPC from NPH and 0.889-0.975 in discriminating OC invasion from OC non-invasion.

CONCLUSIONS

SyMRI combined with first-order parameters showed excellent performance in differentiating NPC from NPH, as well as discriminating OC invasion from non-invasion.

摘要

背景

磁共振成像(MRI)常用于诊断鼻咽癌(NPC)和枕骨斜坡(OC)侵犯,但非增强 MRI 可能会漏诊一部分病变。本研究旨在探讨合成磁共振成像(SyMRI)在鉴别 NPC 与鼻咽增生(NPH)以及评估 OC 侵犯方面的诊断性能。

方法

前瞻性纳入 59 例 NPC 患者和 48 名志愿者行 SyMRI 检查。从 VOI(原发肿瘤、良性黏膜和 OC)中提取 18 个一阶特征。采用独立样本 t 检验和 Mann-Whitney U 检验对组间进行统计学比较,选择有统计学意义的参数。然后采用多变量逻辑分析构建多个诊断模型。采用受试者工作特征(ROC)曲线分析计算模型的诊断性能,并采用 DeLong 检验进行比较。应用 bootstrap 和 5 折交叉验证避免过拟合。

结果

志愿者中,T1、T2 和 PD 图衍生模型在鉴别 NPC 与 NPH 方面具有出色的诊断性能,曲线下面积(AUC)分别为 0.975、0.972 和 0.986。此外,SyMRI 模型在鉴别 OC 侵犯与非侵犯方面也具有出色的性能(AUC:0.913-0.997)。值得注意的是,T1 图衍生模型具有最高的诊断性能,AUC、敏感度、特异度和准确度分别为 0.997、96.9%、97.9%和 97.5%。采用 5 折交叉验证,在鉴别 NPC 与 NPH 方面,校正偏倚的 AUC 为 0.965-0.984,在鉴别 OC 侵犯与非侵犯方面,校正偏倚的 AUC 为 0.889-0.975。

结论

SyMRI 结合一阶参数在鉴别 NPC 与 NPH 以及鉴别 OC 侵犯与非侵犯方面具有出色的性能。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f152/9875491/8742b08e1c74/12880_2023_968_Fig1_HTML.jpg

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验