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Accurate model-based segmentation of gynecologic brachytherapy catheter collections in MRI-images

机译:基于模型的基于模型的MRI图像中的妇科近距离放射治疗导管收集分割

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Highlights ? Segmentation and catheter identification in MRI images for brachytherapy. ? ONE CLICK user interaction per catheter. ? Coupling of mechanical model and image features. ? Outlier detection and correction. ? 93% accuracy and 0.29? mm precision error. Graphical abstract Display Omitted Abstract The gynecological cancer mortality rate, including cervical, ovarian, vaginal and vulvar cancers, is more than 20,000 annually in the US alone. In many countries, including the US, external-beam radiotherapy followed by high dose rate brachytherapy is the standard-of-care. The superior ability of MR to visualize soft tissue has led to an increase in its usage in planning and delivering brachytherapy treatment. A technical challenge associated with the use of MRI imaging for brachytherapy, in contrast to that of CT imaging, is the visualization of catheters that are used to place radiation sources into cancerous tissue. We describe here a precise, accurate method for achieving catheter segmentation and visualization. The algorithm, with the assistance of manually provided tip locations, performs segmentation using image-features, and is guided by a catheter-specific, estimated mechanical model. A final quality control step removes outliers or conflicting catheter trajectories. The mean Hausdorff error on a 54 patient, 760 catheter reference database was 1.49? mm; 51 of the outliers deviated more than two catheter widths (3.4? mm) from the gold standard, corresponding to catheter identification accuracy of 93% in a Syed–Neblett template. In a multi-user simulation experiment for evaluating RMS precision by simulating varying manually-provided superior tip positions, 3 σ maximum errors were 2.44? mm. The average segmentation time for a single catheter was 3?s on a standard PC. The segmentation time, accuracy and precision, are promising indicators of the value of this method for clinical translation of MR-guidance in gynecologic brachytherapy and other catheter-based interventional procedures.
机译:强调 ?近距离放射治疗MRI图像中的分段和导管鉴定。还一个点击每个导管的用户交互。还机械模型和图像特征的耦合。还异常检测和校正。还93%的准确度和0.29? mm精度错误。图形摘要显示略论摘要妇科癌症死亡率,包括宫颈癌,卵巢,阴道和外阴癌,仅在美国每年超过20,000。在许多国家,包括美国,外梁放射疗法,随后具有高剂量率近距离放射治疗的标准。先生以可视化软组织的优越能力导致其在规划和提供近距离治疗方面的使用量增加。与CT成像相比,与使用MRI成像的使用MRI成像的技术挑战是导管的可视化,用于将辐射源放入癌组织中。我们在这里描述了实现导管分割和可视化的精确,准确的方法。该算法在手动提供的尖端位置的帮助下,使用图像特征执行分割,并且由导管特定的估计的机械模型引导。最终质量控制步骤消除了异常值或冲突的导管轨迹。 54例患者的平均豪斯多夫错误,760个导管参考数据库为1.49?毫米; 51的异常值偏离了来自金标准的两次以上的导管宽度(3.4Ωmm),对应于系统中的导管识别精度为93%。在多用户仿真实验中,通过模拟手动提供的卓越尖端位置来评估rms精度,3σ最大误差为2.44?毫米。单个导管的平均分割时间在标准PC上为3?s。分割时间,准确性和精度,是该方法对妇科近距离放射治疗和其他基于导管的介入程序的临床翻译方法的价值的有望指标。

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