利用 SPECT/CT 技术开发的乳腺癌前哨淋巴结交互式三维图谱。

IF 3.5 2区 医学 Q2 ONCOLOGY
Josephine Situ, Poppy Buissink, Annie Mu, David K V Chung, Rob Finnegan, Thiranja P Babarenda Gamage, Tharanga D Jayathungage Don, Cameron Walker, Hayley M Reynolds
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引用次数: 0

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非常重要。本研究旨在开发交互式三维乳腺前哨淋巴结图谱,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 名接受术前淋巴管造影和 SPECT/CT 检查的早期乳腺癌患者。采用贝叶斯推断、非参数自引导和回归技术计算淋巴引流和肿瘤患病率统计数据。对 350 名患者进行了 SPECT/CT 与参考患者 CT 的图像配准,并对 SLN 位置进行了相对于参考 CT 的转换。对参考 CT 进行分割以显示骨骼和肌肉,并将 SLN 分布与欧洲放射治疗与肿瘤学会 (ESTRO) 的临床目标体积 (CTV) 进行比较。SLN图谱和统计分析都集成到了图形用户界面(GUI)中:直接淋巴引流至腋窝 I 级(前方)结节区最为常见(77.2%),其次是乳腺内结节区(30.4%)。乳房外上象限的肿瘤发病率最高(22.9%),其次是乳晕后区域(12.8%)。三维图集中有来自 335 名患者的 765 个 SLN,ESTRO CTV 覆盖了 33.3%-66.7% 的腋窝 SLN 和 25.4% 的乳腺内 SLN:交互式三维图谱有效地显示了大量患者的乳腺SLN分布和统计数据。该图谱可免费下载,是一种宝贵的教育资源,今后可用于指导治疗。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
An interactive 3D atlas of sentinel lymph nodes in breast cancer developed using SPECT/CT.

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.

Conclusion: 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.

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来源期刊
Cancer Imaging
Cancer Imaging ONCOLOGY-RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING
CiteScore
7.00
自引率
0.00%
发文量
66
审稿时长
>12 weeks
期刊介绍: Cancer Imaging is an open access, peer-reviewed journal publishing original articles, reviews and editorials written by expert international radiologists working in oncology. The journal encompasses CT, MR, PET, ultrasound, radionuclide and multimodal imaging in all kinds of malignant tumours, plus new developments, techniques and innovations. Topics of interest include: Breast Imaging Chest Complications of treatment Ear, Nose & Throat Gastrointestinal Hepatobiliary & Pancreatic Imaging biomarkers Interventional Lymphoma Measurement of tumour response Molecular functional imaging Musculoskeletal Neuro oncology Nuclear Medicine Paediatric.
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