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使用动态对比增强磁共振成像区分前列腺恶性组织与正常组织的示踪剂动力学模型比较

Comparison of tracer kinetic models in differentiating malignant from normal prostate tissue using dynamic contrast-enhanced MRI.

作者信息

Zhang Hongjiang, Yang Jing, Wu Kunhua, Hou Zujun, Du Ji, Yan Jianhua, Zhao Ying

机构信息

Department of Magnetic Resonance Imaging (MRI), The First People's Hospital of Yunnan Province, The Affiliated Hospital of Kunming University of Science and Technology, Kunming, China.

Department of Radiology, FISCA Laboratory for Advanced Imaging, Nanjing, China.

出版信息

Front Oncol. 2024 Dec 6;14:1450388. doi: 10.3389/fonc.2024.1450388. eCollection 2024.

Abstract

PURPOSE

The aim of this study was to evaluate the diagnostic value of dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) derived kinetic parameters with high spatiotemporal resolution in discriminating malignant from normal prostate tissues.

METHODS

Fifty patients with suspicious of malignant diseases in prostate were included in this study. Regions of interest (ROI) were manually delineated by experienced radiologists. Voxel-wise kinetic parameters were produced with the following tracer kinetic models (TKMs): Tofts model, extended Tofts model (ETM), Brix's conventional two-compartment model (Brix), adiabatic tissue homogeneity model (ATH), and distributed parameter model (DP). The initial area under the signal-time curve (IAUC) with an uptake integral approach was also included. Mann-Whitney U test and receiver operating characteristic (ROC) curves were used to evaluate the capability of distinguishing tumor lesions from normal tissues. A p-value of 0.05 or less is considered statistically significant. ROI based parameters correlation analysis between DP and ETM were performed.

RESULTS

624 lesions and 269 normal tissue ROIs were obtained. Thirty parameters were derived from the six kinetic models. Except for PS from Brix, statistically significant differences between lesions and normal tissues (P<0.05) were observed in other parameters.Ve from DP, ATH and Brix and PS from ATH have AUC values less than 0.6 in the ROC analysis. MTT, Vp and PS from DP, Ktrans from ETM and Tofts, E and PS from ATH, IAUC parameters and F from Brix have AUC values larger than 0.8. Ve and Vp from DP and ETM are correlated (r> 0.65). The correlation coefficient between Ktrans from ETM and PS from DP is 0.751.

CONCLUSION

MTT, Vp and PS from DP, Ktrans from ETM and Tofts, E and PS from ATH, F from Brix and IAUC parameters can be used to differentiate malignant lesions from normal tissues in the prostate.

摘要

目的

本研究旨在评估具有高时空分辨率的动态对比增强磁共振成像(DCE-MRI)衍生的动力学参数在鉴别前列腺恶性组织与正常组织方面的诊断价值。

方法

本研究纳入了50例怀疑患有前列腺恶性疾病的患者。感兴趣区域(ROI)由经验丰富的放射科医生手动划定。采用以下示踪剂动力学模型(TKM)生成体素级动力学参数:Tofts模型、扩展Tofts模型(ETM)、Brix传统双室模型(Brix)、绝热组织均匀性模型(ATH)和分布参数模型(DP)。还包括采用摄取积分法的信号-时间曲线下初始面积(IAUC)。使用Mann-Whitney U检验和受试者操作特征(ROC)曲线来评估区分肿瘤病变与正常组织的能力。p值小于或等于0.05被认为具有统计学意义。对DP和ETM之间基于ROI的参数进行相关性分析。

结果

共获得624个病变和269个正常组织ROI。从六个动力学模型中得出了30个参数。除了Brix模型的PS外,其他参数在病变组织与正常组织之间均观察到有统计学意义的差异(P<0.05)。DP、ATH和Brix模型的Ve以及ATH模型的PS在ROC分析中的AUC值小于0.6。DP模型的MTT、Vp和PS,ETM和Tofts模型的Ktrans,ATH模型的E和PS,IAUC参数以及Brix模型的F的AUC值大于0.8。DP和ETM模型的Ve和Vp具有相关性(r>0.65)。ETM模型的Ktrans与DP模型的PS之间的相关系数为0.751。

结论

DP模型的MTT、Vp和PS,ETM和Tofts模型的Ktrans,ATH模型的E和PS,Brix模型的F以及IAUC参数可用于区分前列腺的恶性病变与正常组织。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7372/11659129/8f53741f53d9/fonc-14-1450388-g001.jpg

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