In-vivo lung biomechanical modeling for effective tumor motion tracking in external beam radiation therapy,Computers in Biology and Medicine

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In-vivo lung biomechanical modeling for effective tumor motion tracking in external beam radiation therapy
Computers in Biology and Medicine ( IF 7.7 ) Pub Date : 2021-01-20 , DOI: 10.1016/j.compbiomed.2021.104231
Parya Jafari ₁ , Sergio Dempsey ₁ , Douglas A Hoover ₂ , Elham Karami ₃ , Stewart Gaede ₄ , Ali Sadeghi-Naini ₅ , Ting Yim Lee ₆ , Abbas Samani ₇

Affiliation

School of Biomedical Engineering, Western University, London, ON, Canada.
Department of Radiation Oncology, London Regional Cancer Program, London, ON, Canada; Department of Oncology, Schulich School of Medicine and Dentistry, Western University, London, ON, Canada; Department of Medical Biophysics, Western University, London, ON, Canada.
Knowtions Research, Toronto, ON, Canada.
Department of Radiation Oncology, London Regional Cancer Program, London, ON, Canada; Department of Oncology, Schulich School of Medicine and Dentistry, Western University, London, ON, Canada; Department of Medical Biophysics, Western University, London, ON, Canada; Imaging Program, Lawson Health Research Institute, London, ON, Canada.
Department of Electrical Engineering & Computer Science, York University, Toronto, ON, Canada; Department of Radiation Oncology and Physical Sciences Platform, Odette Cancer Centre and Sunnybrook Research Institute, Sunnybrook Health Sciences Centre, Toronto, ON, Canada; Department of Medical Biophysics, University of Toronto, Toronto, ON, Canada.
Department of Medical Biophysics, Western University, London, ON, Canada; Imaging Program, Lawson Health Research Institute, London, ON, Canada; Imaging Research Laboratories, Robarts Research Institute, London, ON, Canada.
School of Biomedical Engineering, Western University, London, ON, Canada; Department of Medical Biophysics, Western University, London, ON, Canada; Department of Electrical and Computer Engineering, Western University, London, ON, Canada; Imaging Research Laboratories, Robarts Research Institute, London, ON, Canada.

Lung cancer is the most common cause of cancer-related death in both men and women. Radiation therapy is widely used for lung cancer treatment; however, respiratory motion presents challenges that can compromise the accuracy and/or effectiveness of radiation treatment. Respiratory motion compensation using biomechanical modeling is a common approach used to address this challenge. This study focuses on the development and validation of a lung biomechanical model that can accurately estimate the motion and deformation of lung tumor. Towards this goal, treatment planning 4D-CT images of lung cancer patients were processed to develop patient-specific finite element (FE) models of the lung to predict the patients' tumor motion/deformation. The tumor motion/deformation was modeled for a full respiration cycle, as captured by the 4D-CT scans. Parameters driving the lung and tumor deformation model were found through an inverse problem formulation. The CT datasets pertaining to the inhalation phases of respiration were used for validating the model's accuracy. The volumetric Dice similarity coefficient between the actual and simulated gross tumor volumes (GTVs) of the patients calculated across respiration phases was found to range between 0.80 ± 0.03 and 0.92 ± 0.01. The average error in estimating tumor's center of mass calculated across respiration phases ranged between 0.50 ± 0.10 (mm) and 1.04 ± 0.57 (mm), indicating a reasonably good accuracy of the proposed model. The proposed model demonstrates favorable accuracy for estimating the lung tumor motion/deformation, and therefore can potentially be used in radiation therapy applications for respiratory motion compensation.

中文翻译：

体内肺生物力学建模，可在外束放射治疗中有效跟踪肿瘤运动

在男性和女性中，肺癌都是与癌症相关的死亡的最常见原因。放射疗法被广泛用于肺癌的治疗。然而，呼吸运动提出了挑战，这些挑战可能损害放射治疗的准确性和/或有效性。使用生物力学模型进行呼吸运动补偿是解决这一挑战的常用方法。这项研究的重点是可以精确估计肺肿瘤运动和变形的肺生物力学模型的开发和验证。为了实现这一目标，对肺癌患者的治疗计划4D-CT图像进行了处理，以开发特定于患者的肺部有限元（FE）模型，以预测患者的肿瘤运动/变形。如4D-CT扫描所捕获的，针对完整的呼吸周期对肿瘤运动/变形进行建模。通过反问题公式可以找到驱动肺和肿瘤变形模型的参数。与呼吸的吸入阶段有关的CT数据集用于验证模型的准确性。发现在整个呼吸阶段计算出的患者实际和模拟总肿瘤体积（GTV）之间的体积Dice相似系数在0.80±0.03和0.92±0.01之间。在整个呼吸阶段计算的估计肿瘤质心的平均误差在0.50±0.10（mm）和1.04±0.57（mm）之间，表明所提出模型的准确性相当好。提出的模型证明了估计肺肿瘤运动/变形的准确度，因此可以潜在地用于放射治疗中以进行呼吸运动补偿。

更新日期：2021-01-29

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