Sheng Yang, Li Taoran, Zhang You, Lee W Robert, Yin Fang-Fang, Ge Yaorong, Wu Q Jackie
Department of Radiation Oncology, Duke University Medical Center, Durham, NC 27710, USA. Medical Physics Graduate Program, Duke University Medical Center, Durham, NC 27705, USA.
Phys Med Biol. 2015 Sep 21;60(18):7277-91. doi: 10.1088/0031-9155/60/18/7277. Epub 2015 Sep 8.
An atlas-based IMRT planning technique for prostate cancer was developed and evaluated. A multi-dose atlas was built based on the anatomy patterns of the patients, more specifically, the percent distance to the prostate and the concaveness angle formed by the seminal vesicles relative to the anterior-posterior axis. A 70-case dataset was classified using a k-medoids clustering analysis to recognize anatomy pattern variations in the dataset. The best classification, defined by the number of classes or medoids, was determined by the largest value of the average silhouette width. Reference plans from each class formed a multi-dose atlas. The atlas-guided planning (AGP) technique started with matching the new case anatomy pattern to one of the reference cases in the atlas; then a deformable registration between the atlas and new case anatomies transferred the dose from the atlas to the new case to guide inverse planning with full automation. 20 additional clinical cases were re-planned to evaluate the AGP technique. Dosimetric properties between AGP and clinical plans were evaluated. The classification analysis determined that the 5-case atlas would best represent anatomy patterns for the patient cohort. AGP took approximately 1 min on average (corresponding to 70 iterations of optimization) for all cases. When dosimetric parameters were compared, the differences between AGP and clinical plans were less than 3.5%, albeit some statistical significances observed: homogeneity index (p > 0.05), conformity index (p < 0.01), bladder gEUD (p < 0.01), and rectum gEUD (p = 0.02). Atlas-guided treatment planning is feasible and efficient. Atlas predicted dose can effectively guide the optimizer to achieve plan quality comparable to that of clinical plans.
开发并评估了一种基于图谱的前列腺癌调强放疗(IMRT)计划技术。基于患者的解剖模式构建了多剂量图谱,更具体地说,是基于到前列腺的距离百分比以及精囊相对于前后轴形成的凹陷角度。使用k-中心点聚类分析对一个包含70个病例的数据集进行分类,以识别数据集中的解剖模式变化。由类或中心点的数量定义的最佳分类由平均轮廓宽度的最大值确定。每个类别的参考计划构成了一个多剂量图谱。图谱引导计划(AGP)技术首先将新病例的解剖模式与图谱中的一个参考病例进行匹配;然后在图谱和新病例解剖结构之间进行可变形配准,将剂量从图谱转移到新病例,以实现完全自动化的逆向计划。另外20个临床病例被重新计划以评估AGP技术。评估了AGP计划和临床计划之间的剂量学特性。分类分析确定5个病例的图谱最能代表患者群体的解剖模式。所有病例的AGP平均耗时约1分钟(相当于70次优化迭代)。比较剂量学参数时,AGP计划和临床计划之间的差异小于3.5%,尽管观察到了一些统计学显著性差异:均匀性指数(p > 0.05)、适形性指数(p < 0.01)、膀胱等效均匀剂量(gEUD,p < 0.01)和直肠gEUD(p = 0.02)。图谱引导治疗计划是可行且有效的。图谱预测剂量可以有效地引导优化器实现与临床计划相当的计划质量。