Clinical evaluation of multi-atlas based segmentation of lymph node regions in head and neck and prostate cancer patients.
Clinical evaluation of multi-atlas based segmentation of lymph node regions in head and neck and prostate cancer patients.
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DOI：
10.1186/1748-717x-8-229
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发表时间：
2013-10-03
期刊：
影响因子：
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通讯作者：
Montelius A
中科院分区：
文献类型：
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作者：
Sjöberg C;Lundmark M;Granberg C;Johansson S;Ahnesjö A;Montelius A
已提出使用由专家分割的患者图像组成的选定图集病例的可变形配准的半自动分割，以促进淋巴结区域的描绘，以用于头颈和前列腺肿瘤的三维适形和强度调制放射治疗计划。我们的目的是调查与使用单个图谱分割相比，多个图谱的融合是否会减少临床工作量并提供更准确的分割建议，因为可以更完整地表示解剖变化。根据已发表的分割建议，使用 11 名头颈患者和 15 名前列腺患者构建了淋巴结区域图谱。使用商业配准软件（Velocity AI）通过变形配准创建单独的分割。根据回顾性数据，随机选择 10 名头颈患者和 10 名前列腺患者进行研究，这些患者均与寰椎患者不同。首先对每位患者进行三次描绘，(a) 由放射肿瘤学家手动描绘，(b) 自动使用所选图谱中的单个图谱分割建议，以及 (c) 使用概率加权融合算法自动融合数据库中所有病例的图谱建议。在随后的步骤中，放射肿瘤学家纠正了从步骤（b）和（c）获得的分割建议，而不使用方法（a）的结果作为参考。对于每种方法和每个单独的结构，分别记录编辑分段所花费的时间。最后，利用骰子相似系数和结构体积来评估不同方法描绘的结构之间的相似性。对于单一图集方法，与手动分割相比，头颈和骨盆淋巴结的时间分别减少了 29% 和 23%，而编辑融合图集方案则导致时间减少了 49% 和 34%。由于融合过程产生的模糊效果，融合图集提案的平均体积仅为头颈病例手动分割的 74%，前列腺病例的平均体积仅为 82%。编辑提案后，结果量差异不再具有统计显着性，尽管可以注意到提案的轻微影响，因为平均编辑量仍然略小于手动分割，分别为 9% 和 5%。与使用单个图集分割相比，基于多个图集融合的分割减少了描绘淋巴结区域所需的时间。与手动分割相比，尽管节省了大量时间，但仍保持了分割的质量。
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.