Department of Radiology, Oncology and Radiation Sciences, Uppsala University, Uppsala SE-751 85, Sweden.
Radiat Oncol. 2013 Oct 3;8:229. doi: 10.1186/1748-717X-8-229.
Semi-automated segmentation using deformable registration of selected atlas cases consisting of expert segmented patient images has been proposed to facilitate the delineation of lymph node regions for three-dimensional conformal and intensity-modulated radiotherapy planning of head and neck and prostate tumours. Our aim is to investigate if fusion of multiple atlases will lead to clinical workload reductions and more accurate segmentation proposals compared to the use of a single atlas segmentation, due to a more complete representation of the anatomical variations.
Atlases for lymph node regions were constructed using 11 head and neck patients and 15 prostate patients based on published recommendations for segmentations. A commercial registration software (Velocity AI) was used to create individual segmentations through deformable registration. Ten head and neck patients, and ten prostate patients, all different from the atlas patients, were randomly chosen for the study from retrospective data. Each patient was first delineated three times, (a) manually by a radiation oncologist, (b) automatically using a single atlas segmentation proposal from a chosen atlas and (c) automatically by fusing the atlas proposals from all cases in the database using the probabilistic weighting fusion algorithm. In a subsequent step a radiation oncologist corrected the segmentation proposals achieved from step (b) and (c) without using the result from method (a) as reference. The time spent for editing the segmentations was recorded separately for each method and for each individual structure. Finally, the Dice Similarity Coefficient and the volume of the structures were used to evaluate the similarity between the structures delineated with the different methods.
For the single atlas method, the time reduction compared to manual segmentation was 29% and 23% for head and neck and pelvis lymph nodes, respectively, while editing the fused atlas proposal resulted in time reductions of 49% and 34%. The average volume of the fused atlas proposals was only 74% of the manual segmentation for the head and neck cases and 82% for the prostate cases due to a blurring effect from the fusion process. After editing of the proposals the resulting volume differences were no longer statistically significant, although a slight influence by the proposals could be noticed since the average edited volume was still slightly smaller than the manual segmentation, 9% and 5%, respectively.
Segmentation based on fusion of multiple atlases reduces the time needed for delineation of lymph node regions compared to the use of a single atlas segmentation. Even though the time saving is large, the quality of the segmentation is maintained compared to manual segmentation.
半自动化分割采用可变形注册选择的图谱病例,由专家分割的患者图像组成,旨在促进头颈部和前列腺肿瘤的三维适形和调强放疗计划的淋巴结区域勾画。我们的目的是研究融合多个图谱是否会导致临床工作量减少,并与使用单个图谱分割相比,由于更完整地表示解剖变异,从而导致更准确的分割建议。
根据发表的分割建议,使用 11 例头颈部患者和 15 例前列腺患者构建淋巴结图谱。使用商业注册软件(Velocity AI)通过可变形注册创建个体分割。从回顾性数据中随机选择 10 例头颈部患者和 10 例前列腺患者作为研究对象,这些患者均与图谱患者不同。每位患者首先进行三次勾画,(a)由放射肿瘤学家手动勾画,(b)使用来自选定图谱的单个图谱分割建议自动勾画,(c)使用数据库中所有病例的图谱提案通过概率加权融合算法自动融合。在随后的步骤中,放射肿瘤学家在不使用方法(a)的结果作为参考的情况下,对步骤(b)和(c)中获得的分割提案进行编辑。分别记录每种方法和每个单独结构的编辑分割时间。最后,使用 Dice 相似系数和结构体积来评估不同方法勾画的结构之间的相似性。
对于单个图谱方法,与手动分割相比,头颈部和骨盆淋巴结的时间减少分别为 29%和 23%,而融合图谱提案的编辑导致时间减少分别为 49%和 34%。由于融合过程中的模糊效应,融合图谱提案的平均体积仅为头颈部病例的手动分割的 74%,前列腺病例的 82%。在编辑提案后,体积差异不再具有统计学意义,尽管由于编辑后的平均体积仍然略小于手动分割,分别为 9%和 5%,因此仍能注意到提案的轻微影响。
基于多个图谱融合的分割与使用单个图谱分割相比,减少了淋巴结区域勾画所需的时间。尽管节省时间很大,但与手动分割相比,分割质量得以保持。