Suppr超能文献

多中心研究评估弥散 MRI 对前列腺癌诊断的改善作用。

Evaluation of Dispersion MRI for Improved Prostate Cancer Diagnosis in a Multicenter Study.

机构信息

1 Department of Electrical Engineering, Eindhoven University of Technology, Groene Loper 19, 5612AZ Eindhoven, The Netherlands.

2 Department of Radiology and Nuclear Medicine, Amsterdam University Medical Centers, The Netherlands.

出版信息

AJR Am J Roentgenol. 2018 Nov;211(5):W242-W251. doi: 10.2214/AJR.17.19215.

Abstract

OBJECTIVE

The purpose of this study is to compare dispersion MRI and Tofts model (TM) for analysis of quantitative dynamic contrast-enhanced (DCE) MRI (DCE-MRI) for localization of prostate cancer and to assess the correlation between quantitative DCE-MRI parameters and tumor grade.

MATERIALS AND METHODS

This retrospective multicenter study included 80 patients with biopsy-proven prostate cancer who underwent DCE-MRI followed by radical prostatectomy. DCE-MRI parameters were extracted from dispersion MRI analysis (the dispersion parameter [k], the flux rate [k], and the intravascular mean transit time) and TM analysis (the forward volume transfer constant [K], k, and the extravascular extracellular volume fraction [v]). ROIs representing benign and malignant tissue were drawn on each DCE-MRI slice according to the histopathologic findings, and the diagnostic performance of the estimated parameters for the diagnosis of prostate cancer was evaluated using fivefold cross-validation and ROC curve analysis. Further analysis was conducted for the two most relevant parameters (i.e., k [for dispersion MRI] and k [for TM]), to investigate the correlation between DCE-MRI parameters and tumor grade.

RESULTS

DCE-MRI parameters were significantly different between benign and malignant prostate tissue (p < 0.0001). The dispersion MRI parameter k outperformed all other DCE-MRI parameters for prostate cancer diagnosis, showing the highest area under the ROC curve value (p < 0.0001). Only a weak linear correlation (Pearson r = 0.18; p < 0.05) was found between the dispersion parameter and the Gleason grade group.

CONCLUSION

Dispersion MRI outperformed TM analysis, improving the diagnostic performance of quantitative DCE-MRI for prostate cancer localization. Of the DCE-MRI parameters, k (for dispersion MRI) and k (for TM) provided only poor characterization of tumor grade.

摘要

目的

本研究旨在比较弥散 MRI 和 Tofts 模型(TM)在分析前列腺癌定位的定量动态对比增强(DCE)MRI(DCE-MRI)中的应用,并评估定量 DCE-MRI 参数与肿瘤分级之间的相关性。

材料与方法

本回顾性多中心研究纳入 80 例经活检证实的前列腺癌患者,这些患者均接受 DCE-MRI 检查和根治性前列腺切除术。从弥散 MRI 分析中提取 DCE-MRI 参数(弥散参数[k]、流速[k]和血管内平均通过时间)和 TM 分析(前向容积转移常数[K]、k 和细胞外间隙分数[v])。根据组织病理学结果,在每个 DCE-MRI 切片上绘制代表良性和恶性组织的 ROI,并使用五重交叉验证和 ROC 曲线分析评估估计参数对前列腺癌的诊断性能。进一步对两个最相关的参数(即弥散 MRI 的 k 和 TM 的 k)进行分析,以研究 DCE-MRI 参数与肿瘤分级之间的相关性。

结果

DCE-MRI 参数在良性和恶性前列腺组织之间存在显著差异(p<0.0001)。弥散 MRI 参数 k 优于其他所有 DCE-MRI 参数,对前列腺癌的诊断具有最高的 ROC 曲线下面积值(p<0.0001)。仅发现弥散参数与 Gleason 分级组之间存在微弱的线性相关性(Pearson r=0.18;p<0.05)。

结论

弥散 MRI 优于 TM 分析,可提高定量 DCE-MRI 对前列腺癌定位的诊断性能。在 DCE-MRI 参数中,k(弥散 MRI)和 k(TM)仅能对肿瘤分级进行粗略描述。

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