Bhusal Chhatkuli Ritu, Demachi Kazuyuki, Uesaka Mitsuru, Nakagawa Keiichi, Haga Akihiro
Department of Nuclear Engineering and Management, School of Engineering, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo, Japan.
Department of Radiology, The University of Tokyo hospital, 7-3-1 Hongo, Bunkyo-ku, Tokyo, Japan.
J Radiat Res. 2019 Jan 1;60(1):109-115. doi: 10.1093/jrr/rry085.
Respiratory motion management is a huge challenge in radiation therapy. Respiratory motion induces temporal anatomic changes that distort the tumor volume and its position. In this study, a markerless tumor-tracking algorithm was investigated by performing phase recognition during stereotactic body radiation therapy (SBRT) using four-dimensional cone-beam computer tomography (4D-CBCT) obtained at patient registration, and in-treatment cone-beam projection images. The data for 20 treatment sessions (five lung cancer patients) were selected for this study. Three of the patients were treated with conventional flattening filter (FF) beams, and the other two were treated with flattening filter-free (FFF) beams. Prior to treatment, 4D-CBCT was acquired to create the template projection images for 10 phases. In-treatment images were obtained at near real time during treatment. Template-based phase recognition was performed for 4D-CBCT re-projected templates using prior 4D-CBCT based phase recognition algorithm and was compared with the results generated by the Amsterdam Shroud (AS) technique. Visual verification technique was used for the verification of the phase recognition and AS technique at certain tumor-visible angles. Offline template matching analysis using the cross-correlation indicated that phase recognition performed using the prior 4D-CBCT and visual verification matched up to 97.5% in the case of FFF, and 95% in the case of FF, whereas the AS technique matched 83.5% with visual verification for FFF and 93% for FF. Markerless tumor tracking based on phase recognition using prior 4D-CBCT has been developed successfully. This is the first study that reports on the use of prior 4D-CBCT based on normalized cross-correlation technique for phase recognition.
呼吸运动管理是放射治疗中的一项巨大挑战。呼吸运动会引起时间上的解剖结构变化，从而使肿瘤体积及其位置发生扭曲。在本研究中，通过在立体定向体部放射治疗（SBRT）期间，利用患者定位时获取的四维锥形束计算机断层扫描（4D-CBCT）以及治疗中的锥形束投影图像进行相位识别，对一种无标记肿瘤跟踪算法进行了研究。本研究选取了20个治疗疗程（5例肺癌患者）的数据。其中3例患者接受传统均整滤过器（FF）束治疗，另外2例接受无均整滤过器（FFF）束治疗。治疗前，采集4D-CBCT以创建10个相位的模板投影图像。在治疗期间近乎实时地获取治疗中的图像。使用基于先前4D-CBCT的相位识别算法对4D-CBCT重新投影的模板进行基于模板的相位识别，并与阿姆斯特丹覆盖物（AS）技术生成的结果进行比较。在某些肿瘤可见角度，使用视觉验证技术对相位识别和AS技术进行验证。使用互相关的离线模板匹配分析表明，在FFF情况下，使用先前4D-CBCT进行的相位识别与视觉验证的匹配率高达97.5%，在FF情况下为95%，而AS技术在FFF情况下与视觉验证的匹配率为83.5%，在FF情况下为93%。基于使用先前4D-CBCT的相位识别的无标记肿瘤跟踪已成功开发。这是第一项报道基于归一化互相关技术使用先前4D-CBCT进行相位识别的研究。
