Assessment of manual adjustment performed in clinical practice following deep learning contouring for head and neck organs at risk in radiotherapy.
Assessment of manual adjustment performed in clinical practice following deep learning contouring for head and neck organs at risk in radiotherapy.
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DOI：
10.1016/j.phro.2020.10.001
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发表时间：
2020-10
影响因子：
--
通讯作者：
Gooding MJ
中科院分区：
文献类型：
--
作者：
Brouwer CL;Boukerroui D;Oliveira J;Looney P;Steenbakkers RJHM;Langendijk JA;Both S;Gooding MJ
在放射治疗的开发和调试研究中，已广泛研究了自动轮廓绘制性能，并在此背景下评估了其对临床工作流程的影响。本研究旨在评价常规临床实践中自动轮廓绘制的手动调整，并确定自动轮廓绘制模型和临床用户交互方面的改进，以提高自动轮廓绘制的效率。共103例临床头颈癌病例，使用商业深度学习轮廓系统进行轮廓勾画，随后进行检查和编辑以供临床使用，这些病例回顾性地取自12个月期间（2019年4月至2020年4月）的临床数据。计算进行的调整量，并将所有病例登记到一个共同的参考框架中，以进行评估。计算调整的中位数、第10和第90百分位数，并使用结构的3D渲染图显示，以目视评估系统和随机调整。结果还与先前报告的观察者间变异进行了比较。根据编辑轮廓的放射治疗技师（RTT），对整个结构和局部子结构进行评估。所有结构的中位调整量均较低（<2 mm），尽管在某些结构中观察到较大的局部调整。中位数系统性地大于或等于零，表明自动轮廓绘制往往会分割所需轮廓。常规临床实践中的自动轮廓绘制性能评估已确定了技术上需要的系统性改进，但也强调了持续RTT培训的必要性，以确保遵守指南。
Auto-contouring performance has been widely studied in development and commissioning studies in radiotherapy, and its impact on clinical workflow assessed in that context. This study aimed to evaluate the manual adjustment of auto-contouring in routine clinical practice and to identify improvements regarding the auto-contouring model and clinical user interaction, to improve the efficiency of auto-contouring. A total of 103 clinical head and neck cancer cases, contoured using a commercial deep-learning contouring system and subsequently checked and edited for clinical use were retrospectively taken from clinical data over a twelve-month period (April 2019–April 2020). The amount of adjustment performed was calculated, and all cases were registered to a common reference frame for assessment purposes. The median, 10th and 90th percentile of adjustment were calculated and displayed using 3D renderings of structures to visually assess systematic and random adjustment. Results were also compared to inter-observer variation reported previously. Assessment was performed for both the whole structures and for regional sub-structures, and according to the radiation therapy technologist (RTT) who edited the contour. The median amount of adjustment was low for all structures (<2 mm), although large local adjustment was observed for some structures. The median was systematically greater or equal to zero, indicating that the auto-contouring tends to under-segment the desired contour. Auto-contouring performance assessment in routine clinical practice has identified systematic improvements required technically, but also highlighted the need for continued RTT training to ensure adherence to guidelines.
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影响因子：
--
作者：
Vaassen F;Hazelaar C;Vaniqui A;Gooding M;van der Heyden B;Canters R;van Elmpt W
通讯作者：
van Elmpt W
影响因子：
5.7
作者：
van Dijk, Lisanne V.;Van den Bosch, Lisa;Brouwer, Charlotte L.
通讯作者：
Brouwer, Charlotte L.
DOI：
10.1186/1748-717x-7-32
发表时间：
2012-03-13
期刊：
Radiation oncology (London, England)
影响因子：
--
作者：
Brouwer CL;Steenbakkers RJ;van den Heuvel E;Duppen JC;Navran A;Bijl HP;Chouvalova O;Burlage FR;Meertens H;Langendijk JA;van 't Veld AA
通讯作者：
van 't Veld AA
影响因子：
3.5
作者：
Cardenas, Carlos E.;Yang, Jinzhong;Brock, Kristy B.
通讯作者：
Brock, Kristy B.
DOI：
10.1109/tvcg.2012.310
发表时间：
2013-07-01
影响因子：
5.2
作者：
Tam, Gary K. L.;Cheng, Zhi-Quan;Rosin, Paul L.
通讯作者：
Rosin, Paul L.