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Abstract：
BACKGROUND: The identification and assessment of sentinel lymph nodes (SLNs) in breast cancer is important for optimised patient management. The aim of this study was to develop an interactive 3D breast SLN atlas and to perform statistical analyses of lymphatic drainage patterns and tumour prevalence.
METHODS: A total of 861 early-stage breast cancer patients who underwent preoperative lymphoscintigraphy and SPECT/CT were included. Lymphatic drainage and tumour prevalence statistics were computed using Bayesian inference, non-parametric bootstrapping, and regression techniques. Image registration of SPECT/CT to a reference patient CT was carried out on 350 patients, and SLN positions transformed relative to the reference CT. The reference CT was segmented to visualise bones and muscles, and SLN distributions compared with the European Society for Therapeutic Radiology and Oncology (ESTRO) clinical target volumes (CTVs). The SLN atlas and statistical analyses were integrated into a graphical user interface (GUI).
RESULTS: Direct lymphatic drainage to the axilla level I (anterior) node field was most common (77.2%), followed by the internal mammary node field (30.4%). Tumour prevalence was highest in the upper outer breast quadrant (22.9%) followed by the retroareolar region (12.8%). The 3D atlas had 765 SLNs from 335 patients, with 33.3-66.7% of axillary SLNs and 25.4% of internal mammary SLNs covered by ESTRO CTVs.
CONCLUSIONS: The interactive 3D atlas effectively displays breast SLN distribution and statistics for a large patient cohort. The atlas is freely available to download and is a valuable educational resource that could be used in future to guide treatment.
METHODS: A total of 861 early-stage breast cancer patients who underwent preoperative lymphoscintigraphy and SPECT/CT were included. Lymphatic drainage and tumour prevalence statistics were computed using Bayesian inference, non-parametric bootstrapping, and regression techniques. Image registration of SPECT/CT to a reference patient CT was carried out on 350 patients, and SLN positions transformed relative to the reference CT. The reference CT was segmented to visualise bones and muscles, and SLN distributions compared with the European Society for Therapeutic Radiology and Oncology (ESTRO) clinical target volumes (CTVs). The SLN atlas and statistical analyses were integrated into a graphical user interface (GUI).
RESULTS: Direct lymphatic drainage to the axilla level I (anterior) node field was most common (77.2%), followed by the internal mammary node field (30.4%). Tumour prevalence was highest in the upper outer breast quadrant (22.9%) followed by the retroareolar region (12.8%). The 3D atlas had 765 SLNs from 335 patients, with 33.3-66.7% of axillary SLNs and 25.4% of internal mammary SLNs covered by ESTRO CTVs.
CONCLUSIONS: The interactive 3D atlas effectively displays breast SLN distribution and statistics for a large patient cohort. The atlas is freely available to download and is a valuable educational resource that could be used in future to guide treatment.
摘要：
背景：乳腺癌前哨淋巴结（SLN）的识别和评估对于优化患者管理很重要。这项研究的目的是开发交互式3D乳房SLN图谱，并对淋巴引流模式和肿瘤患病率进行统计分析。
方法：共纳入861例术前淋巴显像和SPECT/CT的早期乳腺癌患者。使用贝叶斯推断计算淋巴引流和肿瘤患病率统计数据，非参数引导，和回归技术。对350例患者进行了SPECT/CT与参考患者CT的图像配准，和相对于参考CT变换的SLN位置。对参考CT进行分段以可视化骨骼和肌肉，和SLN分布与欧洲治疗放射学和肿瘤学学会（ESTRO）临床目标体积（CTV）相比。SLN图集和统计分析被集成到图形用户界面(GUI)中。
结果：最常见的是直接淋巴引流到腋窝I级（前）结野（77.2％），其次是乳腺内结区(30.4%)。上外乳腺象限的肿瘤患病率最高（22.9％），其次是乳晕后区域（12.8％）。3D图谱有335名患者的765个SLN，ESTROCTV覆盖33.3-66.7%的腋窝SLN和25.4%的内乳SLN。
结论：交互式3D图集有效地显示了大型患者队列的乳腺SLN分布和统计数据。该地图集可免费下载，是一种宝贵的教育资源，将来可用于指导治疗。
方法：共纳入861例术前淋巴显像和SPECT/CT的早期乳腺癌患者。使用贝叶斯推断计算淋巴引流和肿瘤患病率统计数据，非参数引导，和回归技术。对350例患者进行了SPECT/CT与参考患者CT的图像配准，和相对于参考CT变换的SLN位置。对参考CT进行分段以可视化骨骼和肌肉，和SLN分布与欧洲治疗放射学和肿瘤学学会（ESTRO）临床目标体积（CTV）相比。SLN图集和统计分析被集成到图形用户界面(GUI)中。
结果：最常见的是直接淋巴引流到腋窝I级（前）结野（77.2％），其次是乳腺内结区(30.4%)。上外乳腺象限的肿瘤患病率最高（22.9％），其次是乳晕后区域（12.8％）。3D图谱有335名患者的765个SLN，ESTROCTV覆盖33.3-66.7%的腋窝SLN和25.4%的内乳SLN。
结论：交互式3D图集有效地显示了大型患者队列的乳腺SLN分布和统计数据。该地图集可免费下载，是一种宝贵的教育资源，将来可用于指导治疗。
