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一种联合磁共振成像和波谱分析用于前列腺癌诊断的定性方法。

A qualitative approach to combined magnetic resonance imaging and spectroscopy in the diagnosis of prostate cancer.

机构信息

Department of Radiology, Ghent University Hospital, De Pintelaan 185, 9000 Ghent, Belgium.

出版信息

Eur J Radiol. 2010 Feb;73(2):352-6. doi: 10.1016/j.ejrad.2008.10.034. Epub 2008 Dec 11.

Abstract

PURPOSE

To investigate the feasibility and diagnostic value of a whole prostate qualitative approach to combined magnetic resonance imaging and spectroscopy (MRI+MRS) in the detection of prostate cancer in patients with elevated PSA.

MATERIALS AND METHODS

Three hundred and fifty six subjects (mean serum PSA 11.47ng/ml, range 0.40-133ng/ml) were examined with fast-T2-weighted images (MRI) and 3D-magnetic resonance spectroscopy (MRS). Both modalities were qualitatively analyzed on a whole prostate basis by a single radiologist using a 4-point diagnostic scale. Prostate cancer was histopathologically proven in 220 patients and non-evidence of cancer was determined after at least 12 months clinical follow-up in 136 subjects.

RESULTS

Receiver operating curve analysis revealed a significantly better diagnostic performance of MRI+MRS (A(z)=0.857) than MRI alone (A(z)=0.801) and MRS alone (A(z)=0.810). The sensitivity, specificity and accuracy of MRI+MRS for detection of prostate cancer were 72.3%, 92.6%, and 80.1%, respectively.

CONCLUSIONS

Spectral evaluation with a whole prostate qualitative approach is feasible in routine clinical practice. The combination of MRI and MRS yields superior diagnostic results than either modality alone.

摘要

目的

探讨在 PSA 升高的患者中,使用基于整个前列腺的磁共振成像和磁共振波谱(MRI+MRS)的整体前列腺定性方法检测前列腺癌的可行性和诊断价值。

材料与方法

对 356 例患者(平均血清 PSA 为 11.47ng/ml,范围为 0.40-133ng/ml)进行快速 T2 加权成像(MRI)和 3D 磁共振波谱(MRS)检查。由一位放射科医生使用 4 分制诊断量表对两种模态进行整体前列腺的定性分析。220 例患者经组织病理学证实为前列腺癌,136 例患者至少经过 12 个月的临床随访后未发现癌症。

结果

受试者工作特征曲线分析显示,MRI+MRS 的诊断性能明显优于 MRI 单独检查(A(z)=0.801)和 MRS 单独检查(A(z)=0.810)(A(z)=0.857)。MRI+MRS 检测前列腺癌的灵敏度、特异度和准确度分别为 72.3%、92.6%和 80.1%。

结论

在常规临床实践中,基于整个前列腺的波谱评估是可行的。MRI 和 MRS 的联合使用比任何单一模态的诊断结果都更优。

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