Improving automatic delineation for head and neck organs at risk by Deep Learning Contouring
Improving automatic delineation for head and neck organs at risk by Deep Learning Contouring
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DOI：
10.1016/j.radonc.2019.09.022
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发表时间：
2020-01-01
影响因子：
5.7
通讯作者：
Brouwer, Charlotte L.
中科院分区：
文献类型：
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作者：
van Dijk, Lisanne V.;Van den Bosch, Lisa;Brouwer, Charlotte L.
简介：充分的头颈部（HN）危及器官（OAR）勾画对于HN放射治疗和研究OAR辐射剂量与辐射引起的副作用之间的关系至关重要。目前临床使用的自动轮廓绘制算法，如基于图谱的轮廓绘制（ABAS），还有改进的余地。本研究的目的是使用一种综合评估方法来研究使用深度学习轮廓绘制（DLC）时HN OAR自动轮廓绘制的性能，与ABAS.Methods相比：对589名HN癌症患者训练DLC神经网络。通过为每种方法提供104名患者的独立验证队列，将DLC与ABAS进行比较，这些患者也已手动轮廓化。对于22个OAR轮廓（腺体、上消化道和中枢神经系统（CNS）相关结构）中的每一个，获得了骰子相似系数（DICE）以及绝对平均和最大剂量差异（竖条Delta平均剂量竖条和竖条Delta最大剂量竖条）性能指标。结果：DLC与ABAS相比，在22例OAR中的19例中，有19例的定量性能指标得到了等同或显著改善（DICE/竖条Delta平均剂量竖条/竖条Delta最大剂量竖条：0.59/4.2/4.1戈伊（ABAS）; 0.74/1.1/0.8戈伊（DLC））。改善主要是在腺和上消化道OAR。DLC大大减少了没有经验的观察者的描绘时间。主观评价表明，DLC轮廓通常优于ABAS轮廓，被认为更精确，并且更常与手动轮廓混淆。手动轮廓仍然优于DLC和ABAS;然而，DLC结果在本队列中手动编辑轮廓的观察者间变异性范围内或接近该变异性。结论：在大型HN癌症患者队列中训练的DLC，在大多数HN OAR中优于ABAS。(C)2019作者出版社：Elsevier B. V.
Introduction: Adequate head and neck (HN) organ-at-risk (OAR) delineation is crucial for HN radiotherapy and for investigating the relationships between radiation dose to OARs and radiation-induced side effects. The automatic contouring algorithms that are currently in clinical use, such as atlas-based contouring (ABAS), leave room for improvement. The aim of this study was to use a comprehensive evaluation methodology to investigate the performance of HN OAR auto-contouring when using deep learning contouring (DLC), compared to ABAS.Methods: The DLC neural network was trained on 589 HN cancer patients. DLC was compared to ABAS by providing each method with an independent validation cohort of 104 patients, which had also been manually contoured. For each of the 22 OAR contours - glandular, upper digestive tract and central nervous system (CNS)-related structures - the dice similarity coefficient (DICE), and absolute mean and max dose differences (vertical bar Delta mean-dose vertical bar and vertical bar Delta max-dose vertical bar) performance measures were obtained. For a subset of 7 OARs, an evaluation of contouring time, inter-observer variation and subjective judgement was performed.Results: DLC resulted in equal or significantly improved quantitative performance measures in 19 out of 22 OARs, compared to the ABAS (DICE/vertical bar Delta mean dose vertical bar/vertical bar Delta max dose vertical bar: 0.59/4.2/4.1 Gy (ABAS); 0.74/1.1/0.8 Gy (DLC)). The improvements were mainly for the glandular and upper digestive tract OARs. DLC significantly reduced the delineation time for the inexperienced observer. The subjective evaluation showed that DLC contours were more often preferable to the ABAS contours overall, were considered to be more precise, and more often confused with manual contours. Manual contours still outperformed both DLC and ABAS; however, DLC results were within or bordering the inter-observer variability for the manual edited contours in this cohort.Conclusion: The DLC, trained on a large HN cancer patient cohort, outperformed the ABAS for the majority of HN OARs. (C) 2019 The Authors. Published by Elsevier B.V.