Commowick Olivier, Grégoire Vincent, Malandain Grégoire
INRIA Sophia Antipolis - ASCLEPIOS Team, Sophia Antipolis Cedex, France.
Radiother Oncol. 2008 May;87(2):281-9. doi: 10.1016/j.radonc.2008.01.018. Epub 2008 Feb 14.
Radiotherapy planning requires accurate delineations of the tumor and of the critical structures. Atlas-based segmentation has been shown to be very efficient to automatically delineate brain critical structures. We therefore propose to construct an anatomical atlas of the head and neck region.
Due to the high anatomical variability of this region, an atlas built from a single image as for the brain is not adequate. We address this issue by building a symmetric atlas from a database of manually segmented images. First, we develop an atlas construction method and apply it to a database of 45 Computed Tomography (CT) images from patients with node-negative pharyngo-laryngeal squamous cell carcinoma manually delineated for radiotherapy. Then, we qualitatively and quantitatively evaluate the results generated by the built atlas based on Leave-One-Out framework on the database.
We present qualitative and quantitative results using this atlas construction method. The evaluation was performed on a subset of 12 patients among the original CT database of 45 patients. Qualitative results depict visually well delineated structures. The quantitative results are also good, with an error with respect to the best achievable results ranging from 0.196 to 0.404 with a mean of 0.253.
These results show the feasibility of using such an atlas for radiotherapy planning. Many perspectives are raised from this work ranging from extensive validation to the construction of several atlases representing sub-populations, to account for large inter-patient variabilities, and populations with node-positive tumors.
放射治疗计划需要准确勾画肿瘤和关键结构。基于图谱的分割已被证明能非常有效地自动勾画脑部关键结构。因此,我们提议构建头颈部区域的解剖图谱。
由于该区域解剖结构的高度变异性,像脑部那样基于单一图像构建的图谱并不适用。我们通过从手动分割图像数据库构建对称图谱来解决这个问题。首先,我们开发一种图谱构建方法,并将其应用于一个包含45例计算机断层扫描(CT)图像的数据库,这些图像来自咽喉部鳞状细胞癌无淋巴结转移患者,为放射治疗进行了手动勾画。然后,我们基于数据库中的留一法框架,对构建的图谱生成的结果进行定性和定量评估。
我们展示了使用这种图谱构建方法得到的定性和定量结果。评估是在45例患者的原始CT数据库中的12例患者子集上进行的。定性结果直观地描绘了勾画良好的结构。定量结果也很好,相对于最佳可实现结果的误差范围为0.196至0.404,平均为0.25³。
这些结果表明使用这样的图谱进行放射治疗计划的可行性。这项工作引发了许多设想,从广泛验证到构建代表亚群体的多个图谱,以考虑患者间的巨大变异性,以及有淋巴结转移肿瘤的人群。