van der Heyden Brent, Podesta Mark, Eekers Daniëlle Bp, Vaniqui Ana, Almeida Isabel P, Schyns Lotte Ejr, van Hoof Stefan J, Verhaegen Frank
1 Department of Radiation Oncology (MAASTRO), GROW-School for Oncology and Developmental Biology, Maastricht University Medical Centre , Maastricht , The Netherlands.
2 Proton Therapy Department South-East Netherlands (ZON-PTC) , Maastricht , The Netherlands.
Br J Radiol. 2019 Mar;92(1095):20180364. doi: 10.1259/bjr.20180364. Epub 2018 Jul 25.
: During the treatment planning of a preclinical small animal irradiation, which has time limitations for reasons of animal wellbeing and workflow efficiency, the time consuming organ at risk (OAR) delineation is performed manually. This work aimed to develop, demonstrate, and quantitatively evaluate an automated contouring method for six OARs in a preclinical irritation treatment workflow.
: Microcone beam CT images of nine healthy mice were contoured with an in-house developed multiatlas-based image segmentation (MABIS) algorithm for six OARs: kidneys, eyes, heart, and brain. The automatic contouring was compared with the manual delineation using three quantitative metrics: the Dice Similarity Coefficient (DSC), 95th percentile Hausdorff Distance, and the centre of mass displacement.
: A good agreement between manual and automatic contouring was found for OARs with sharp organ boundaries. For the brain and the heart, the median DSC was larger than 0.94, the median 95th Hausdorff Distance smaller than 0.44 mm, and the median centre of mass displacement smaller than 0.20 mm. Lower DSC values were obtained for the other OARs, but the median DSC was still larger than 0.74 for the left eye, 0.69 for the right eye, 0.89 for the left kidney and 0.80 for the right kidney.
: The MABIS algorithm was able to delineate six OARs with a relatively high accuracy. Segmenting OARs with sharp organ boundaries performed better than low contrast OARs.
: A MABIS algorithm is developed, evaluated, and demonstrated in a preclinical small animal irradiation research workflow.
在临床前小动物辐照治疗计划中，由于动物健康和工作流程效率的原因存在时间限制，有风险器官（OAR）的耗时轮廓描绘是手动进行的。这项工作旨在开发、演示并定量评估临床前辐照治疗工作流程中六种OAR的自动轮廓描绘方法。
使用内部开发的基于多图谱的图像分割（MABIS）算法，对九只健康小鼠的微锥束CT图像进行六种OAR的轮廓描绘：肾脏、眼睛、心脏和大脑。使用三种定量指标将自动轮廓描绘与手动描绘进行比较：骰子相似系数（DSC）、第95百分位数豪斯多夫距离和质心位移。
对于器官边界清晰的OAR，手动和自动轮廓描绘之间存在良好的一致性。对于大脑和心脏，DSC中位数大于0.94，第95百分位数豪斯多夫距离中位数小于0.44毫米，质心位移中位数小于0.20毫米。其他OAR获得的DSC值较低，但左眼的DSC中位数仍大于0.74，右眼为0.69，左肾为0.89，右肾为0.80。
MABIS算法能够以相对较高的精度描绘六种OAR。分割器官边界清晰的OAR比低对比度的OAR表现更好。
在临床前小动物辐照研究工作流程中开发、评估并演示了MABIS算法。
