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前列腺肿瘤勾画的功能成像与病理学验证。

Validation of functional imaging with pathology for tumor delineation in the prostate.

机构信息

University Medical Center Utrecht, The Netherlands.

出版信息

Radiother Oncol. 2010 Feb;94(2):145-50. doi: 10.1016/j.radonc.2009.12.034. Epub 2010 Jan 28.

Abstract

INTRODUCTION

A study was performed to validate magnetic resonance (MR) based prostate tumor delineations with pathology.

MATERIAL AND METHODS

Five patients with biopsy proven prostate cancer underwent a T2 weighted (T2w), diffusion weighted MRI (DW-MRI) and dynamic contrast-enhanced MRI (DCE-MRI) scan before prostatectomy. Suspicious regions were delineated based on all available MR information. After prostatectomy whole-mount hematoxylin-eosin stained (H&E) sections were made. Tumor tissue was delineated on the H&E stained sections and compared with the MR based delineations. The registration accuracy between the MR images and H&E stained sections was estimated.

RESULTS

A tumor coverage of 44-89% was reached by the MR based tumor delineations. The application of a margin of approximately 5mm to the MR based tumor delineations yielded a tumor coverage of 85-100% in all patients. Errors created during the registration procedure were 2-3mm, which cannot completely explain the limited tumor coverage.

CONCLUSIONS

An accurate tissue processing and registration method was presented (registration error 2-3mm), which enables the validation of MR based tumor delineations with pathology. Reasonable tumor coverage of about 85% and larger was found when applying a margin of approximately 5 mm to the MR based tumor delineations.

摘要

介绍

本研究旨在通过病理验证磁共振(MR)前列腺肿瘤勾画的准确性。

材料与方法

五例经活检证实的前列腺癌患者在前列腺切除术前接受了 T2 加权(T2w)、扩散加权 MRI(DW-MRI)和动态对比增强 MRI(DCE-MRI)扫描。可疑区域基于所有可用的 MR 信息进行勾画。前列腺切除术后,制作全组织苏木精-伊红染色(H&E)切片。在 H&E 染色切片上勾画肿瘤组织,并与基于 MR 的勾画进行比较。估计了 MR 图像与 H&E 染色切片之间的配准精度。

结果

基于 MR 的肿瘤勾画可覆盖 44%-89%的肿瘤区域。在所有患者中,将大约 5mm 的边缘应用于基于 MR 的肿瘤勾画,可获得 85%-100%的肿瘤覆盖。配准过程中产生的误差为 2-3mm,这不能完全解释肿瘤覆盖范围有限的原因。

结论

提出了一种准确的组织处理和配准方法(配准误差为 2-3mm),可用于通过病理验证基于 MR 的肿瘤勾画。当将大约 5mm 的边缘应用于基于 MR 的肿瘤勾画时,可发现大约 85%且更大的肿瘤合理覆盖范围。

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