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迈向使用三维光学成像和多模态数据配准的非侵入性颅内肿瘤照射。

Towards a noninvasive intracranial tumor irradiation using 3d optical imaging and multimodal data registration.

作者信息

Posada R, Daul Ch, Wolf D, Aletti P

机构信息

Centre de Recherche en Automatique de Nancy (CRAN UMR 7039), Nancy-Université, CNRS, CAV, 2 avenue de la Forêt de Haye, 54516 Vandoeuvre-Lès-Nancy, France.

出版信息

Int J Biomed Imaging. 2007;2007:62030. doi: 10.1155/2007/62030.

Abstract

Conformal radiotherapy (CRT) results in high-precision tumor volume irradiation. In fractioned radiotherapy (FRT), lesions are irradiated in several sessions so that healthy neighbouring tissues are better preserved than when treatment is carried out in one fraction. In the case of intracranial tumors, classical methods of patient positioning in the irradiation machine coordinate system are invasive and only allow for CRT in one irradiation session. This contribution presents a noninvasive positioning method representing a first step towards the combination of CRT and FRT. The 3D data used for the positioning is point clouds spread over the patient's head (CT-data usually acquired during treatment) and points distributed over the patient's face which are acquired with a structured light sensor fixed in the therapy room. The geometrical transformation linking the coordinate systems of the diagnosis device (CT-modality) and the 3D sensor of the therapy room (visible light modality) is obtained by registering the surfaces represented by the two 3D point sets. The geometrical relationship between the coordinate systems of the 3D sensor and the irradiation machine is given by a calibration of the sensor position in the therapy room. The global transformation, computed with the two previous transformations, is sufficient to predict the tumor position in the irradiation machine coordinate system with only the corresponding position in the CT-coordinate system. Results obtained for a phantom show that the mean positioning error of tumors on the treatment machine isocentre is 0.4 mm. Tests performed with human data proved that the registration algorithm is accurate (0.1 mm mean distance between homologous points) and robust even for facial expression changes.

摘要

适形放疗(CRT)可实现对肿瘤体积的高精度照射。在分次放疗(FRT)中,病变组织会在多个疗程中接受照射,这样与单次照射相比,相邻的健康组织能得到更好的保护。对于颅内肿瘤,在放疗设备坐标系中对患者进行定位的传统方法具有侵入性,并且仅允许在一个照射疗程中进行CRT。本文介绍了一种非侵入性定位方法,这是迈向CRT与FRT相结合的第一步。用于定位的3D数据是分布在患者头部的点云(通常在治疗期间获取的CT数据)以及通过固定在治疗室中的结构光传感器获取的分布在患者面部的点。通过对由两个3D点集表示的表面进行配准,可获得连接诊断设备(CT模态)坐标系与治疗室3D传感器(可见光模态)坐标系的几何变换。3D传感器坐标系与放疗设备之间的几何关系通过对治疗室中传感器位置的校准来确定。利用前两个变换计算得到的全局变换,仅根据CT坐标系中的相应位置就足以预测放疗设备坐标系中的肿瘤位置。对模型进行测试得到的结果表明,治疗机等中心处肿瘤的平均定位误差为0.4毫米。对人体数据进行的测试证明,配准算法准确(同源点之间的平均距离为0.1毫米),并且即使面部表情发生变化也很稳健。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/50a4/2267930/7db410861d8d/IJBI2007-62030.001.jpg

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