医学图像形变配准在图像引导放射治疗中的应用

本文详细介绍了形变图像配准技术在国内外的进展、形变图像配准的定义,根据不同划分标准进行的分类,以及在肿瘤诊断和肿瘤图像引导放射治疗的中的应用的举例。展示了形变图像配准技术在当前图像引导放疗领域中的重要性,特别是在自适应放疗方面,通过形变配准技术快速判断放疗过程中的解剖部位的变化、退缩,和位移情况。还可以领用形变配准技术进行在线的快速计划,进行快速剂量计算,来判断由于解剖部位的变化对剂量的影响程度,以及这种影响是否需要再计划。另外在肺和肝脏4DCT中形变配准的应用可准确计算肿瘤靶区在肺和肝脏中的由于呼吸运动产生的位移,用来指导放疗计划靶区的勾画和放疗计划的设计。本文还展望了形变配准在放射治疗计划系统的应用:利用形变配准的快速勾画功能快速勾画病人正常器官轮廓,以提高工作效率。本文还分析了形变配准目前存在的不足之处,以及在该领域中的优缺点和应用前景。     

锥形束CT与螺旋CT图像配准算法及其在放疗中的应用

目的：随着肿瘤放射治疗的发展,提高肿瘤放射治疗的精确度成为了重要的发展趋势。通过硬件与软件的共同发展,实现在线纠正治疗误差在医学图像帮助下完成放疗是现今临床研究的热点。图像引导放射治疗就是在这样理念的基础上发展出来的新型放疗模式。本文研究的目的就是阐述在现今临床普遍采用的锥形束CT与螺旋CT的图像配准在肿瘤放射治疗中的实际应用与重要性。通过研究总结出一套系统化的肿瘤放射治疗图像配准理论,发现最新研究热点、阐述最新研究不足,为今后进一步的发展图像引导放射治疗打下基础。方法：本文通过阐述基本医学图像配准理论,结合具体图像配准算法,应用于图像引导放射治疗,总结出一套系统化用于锥形束CT与螺旋CT图像配准的模式,从而获得更加快速准确的配准结果,改善图像引导放射治疗的效率。本文查阅了近几年计算机软件图像处理的大量文献,同时结合查阅大量图像引导放射治疗的文献,总结前人经验结合理论实践,综合阐述了一套应用于图像引导放射治疗的图像配准系统。结果：锥形束CT与螺旋CT的图像配准,在临床应用上多使用刚性图像配准,其有速度快便于计算的优势。但涉及到患者整体体位配准情况下,弹性图像配准在配准准确度上具有明显优势,需结合临床实际需求以及计算机运算能力的发展想结合选择合适的配准算法。结论：随着肿瘤放射治疗中图像引导技术的应用,螺旋CT定位图像与锥形束CT治疗图像的配准是图像引导放射治疗的关键技术,如何准确而且快速的获取配准结果成了精确放射治疗关注的焦点。螺旋CT定位图像与锥形束CT治疗图像的精确配准是精确放射治疗的前提,并在提高肿瘤剂量的同时,最大限度的保护正常组织,从而提高肿瘤放射治疗的疗效。本文主要综述了应用于精确放射治     

基于多分辨率GMI Demons算法的18F-FDG PET-CT图像配准在食道癌病例中的应用

18F-FDG PET和CT图像的精确配准在肿瘤的放射治疗中具有重要的临床研究意义,本研究采用全局刚性粗配准对食道癌病例中的PET和CT图像进行预处理,尽可能地减小摆位误差,然后使用基于互信息梯度的Demons算法(GMI Demons)进行局部形变配准,有效弥补内部器官误差,另外为了加快配准过程,保持图像的鲁棒性的同时避免局部极值,在形变配准前使用多分辨率图像金字塔结构。通过对10例食道癌病例的定量分析,最大互信息值结果说明经GMI Demons算法配准之后的图像精度比基于MI算法要提高8.046%±0.041%,配准前后临床上肿瘤靶区(GTV)大小的变化,说明经GMI Demons算法配准之后的GTV大小比基于MI算法配准之后的精度提高8.022%±0.044%。两种定量结果的一致性和通过对图像的定性分析,说明该配准策略可以快速地精确肿瘤靶区位置,在制定精确的放疗计划和实际的临床应用中具有研究意义。     

图像引导HIFU治疗靶区精确定位

靶区精确定位是B超引导HIFU治疗的一个难题。本文利用患者术前采集的CT／MR图像序列与实时B超共同引导进行HIFU治疗靶区精确定位,在没有集成MR设备的HIFU治疗机器上利用了CT／MR图像靶区定位精确的优点。首先在CT／MR图像上进行靶区分割与三维表面重建,再利用三视图多模态医学图像配准技术,将重建的靶区信息映射到超声图像,实现了超声图像上靶区的精确定位。整个引导过程主要包括图像采集、预处理、分割、靶区重建以及多模态图像配准几个部分。这种融合CT／MR图像信息的定位技术有望更好地解决B超引导HIFU治疗中的靶区定位难题。     

基于图像变形配准的肺癌自适应放疗剂量学研究

目的:应用图像配准技术实现肺癌自适应放疗中剂量的累加,并评价放疗计划中靶区、正常组织和危及器官相应的剂量学改变。方法:选取9例接受自适应调强放射治疗的肺癌患者,这些患者在经过20次分次治疗后,重新采集CT图像,运用变形图像配准技术将2次CT图像进行剂量累加,得到累加剂量以及相关计量学参数,然后比较自适应放疗及常规的调强放射的剂量学差异。结果:经自适应放疗,大体肿瘤体积(GTV)体积相对于放疗前平均缩小53.2%,靶区肿瘤受照剂量相对于常规调强放疗计划平均提高0.41 Gy;肺组织V_(20)、V_(30)分别平均降低2.17%、3.32%;心脏V_(30)平均降低1.14%,V_(40)降低2.98%;脊髓最大受照剂量降低1.21 Gy。结论:肺癌放疗过程中,自适应放疗相对于常规调强放疗能提高靶区受照剂量,有效减少周围正常组织剂量,降低放疗副作用的发生。     

一种射野图像和参考图像的自动配准方法

目的:及时纠正放射治疗过程中患者的摆位误差,提高放射治疗效果.方法:本文对放疗中射野图像和参考图像的进行配准,应用Canny算子进行两幅图像的边缘提取,将提取的图像边缘作为配准的基准点,以射野图像与参考图像的最大互信息为配准准则,应用模拟退火法优化配准参数,搜索图像最大互信息.结果:本文对29例宫颈癌和前列腺癌患者的射野图像与参考图像进行了配准,结果表明该方法配准精度高,提高了配准的速度.结论:该配准方法适用于放疗临床摆位误差的在线分析.     

前列腺癌图像引导放射治疗精准度评估

目的:分析锥形束CT(CBCT)图像引导下不同图像配准方法,不同配准范围对配准精度的误差及膀胱直肠充盈程度对前列腺癌放疗精准度的影响。方法:回顾分析15例前列腺癌患者定位前和分次治疗前进行膀胱容积测量后,对计划CT和每次放疗摆位CBCT图像分别以不同配准方法(骨性配准和灰度配准)和不同范围(靶区或盆腔)进行图像配准,分析比较各组配准的治疗体位下靶区体积几何中心点、大体靶区相似性指数和计划体积结构以及危及器官覆盖率。同时分析膀胱、直肠体积与这3个评价参数的相关性。结果:对于配准盆腔区域,灰度配准精度好于骨性配准。骨性配准时,配准盆腔区域精度与配准靶区区域结果相近或较好。灰度配准时,配准盆腔区域精度好于配准靶区区域。选择配准盆腔区域灰度配准时,靶区几何中心点偏差最小,为(0.362±0.189)cm,靶区相似性指数最大,为0.707±0.089,计划结构体积、膀胱、直肠覆盖率最大,分别为(96.6±4.1)%、(85.4±17.2)%和(74.2±13.3)%。膀胱体积与3个评价参数呈负相关。直肠体积并没有明显规律。结论:前列腺癌放疗CBCT图像引导过程中,采用盆腔区域灰度配准是较好的选择,能最大限度地减小摆位误差,提高放疗精准度。分次治疗前尽量保证膀胱、直肠体积与CT定位时一致,对保证靶区受照剂量及减少膀胱、直肠的毒副反应具有明显意义。     

基于Contourlet变换的CT和锥形束CT图像配准算法

目的提出一种基于Contourlet变换,用于放射治疗定位的CT与锥形束CT（cone beam CT,CBCT）图像配准的方法。方法利用Contourlet变换多尺度多方向的分辨特性,将待配准图像进行Contourlet变换分解,分解后的高频方向子带合成梯度图像,采用归一化互信息作为相似性测度,把梯度图像与低频方向子带以加权函数结合,进行临床医学图像的刚性配准,有效弥补了互信息配准中缺少空间信息的不足。结果通过已知空间变换参数图像的配准结果验证了算法的准确性。配准后lO幅图像变换参数的误差极小,且均方根误差接近于0。结论该图像配准算法精确度高,并具有很好的鲁棒性,有助于提高图像引导放射治疗（image guid edradiation therapy,IGRT）中解剖组织结构和靶区的定位精度。     

光流法在放射治疗图像配准中的研究

光流法是一种可变形图像配准方法,已用来配准CT图像、四维CT（4D-CT）图像、锥形束CT（CBCT）图像、磁共振成像（MRI）图像、MRI／CT图像、PET／CT图像、SPECT图像。文章描述了光流法在放射治疗图像配准中的应用。这种技术可以使放射治疗更加有效地杀死癌细胞,同时使正常组织毒性反应更少,提高肿瘤靶区勾画的精确性,进而使肿瘤放射治疗更精确。     

图像引导精准定位跟踪系统KylinRay-IGRT

针对放疗过程的摆位误差以及动态肿瘤靶区定位跟踪难题,图像引导精准定位跟踪系统KylinRay-IGRT基于双X射线成像和红外引导,实现了治疗前对病人的摆位,以及治疗过程中对肿瘤运动的跟踪与控制。系统主要包含X射线图像实时采集、多维多模式图像配准和快速实时的红外定位引导等功能。本研究开展基于双X射线成像系统的摆位误差纠正和基于红外信号的定位与呼吸跟踪实验,对系统进行了功能性和正确性测试。结果表明KylinRay-IGRT的定位精度可满足临床需求,为进一步开展自适应放疗关键技术和算法提供研究平台和技术基础。     

基于3种配准方法的宫颈癌外照射放疗累积剂量研究

目的:拟基于3种配准方法（B样条弹性配准、仿射配准和刚性配准）,探讨宫颈癌外照射放疗累积剂量及其差异。 方法:选取2015年1月~2016年2月期间进行了两次放疗定位的10例宫颈癌病例。首先,以第二次扫描的CT图像为参考,采用归一化的互信息（MI）和平均绝对差（MAD）评价3种配准方法（B样条弹性配准、仿射配准和刚性配准）的精度。然后,分别采用上述3种方法,将第一次放疗的IMRT剂量,累积到第二次扫描的CT图像,得到3种配准方法的累积剂量DB、DF和DG,最后,以DB为基准,分别比较DF与DB、DG与DB的差异。 结果:配准精度:本文3种配准方法的MI值分别为1.27±0.02、1.24±0.03和1.24±0.02,MI值越大,精度则越高;MAD值分别为4.93±1.03、6.36±1.59和6.76±1.77,MAD值越小,精度则越高。累积剂量差异:DF与DB、DG与DB的MAD分别64.8±49.7和72.9±47.5,MAD值越小,剂量差异越小。DF与DB、DG与DB在直肠和膀胱的V50偏差较大,但是在本研究所选的DVH参数（直肠和膀胱的D50%、V50,CTV和GTV的D95%、Dmean）均没有统计学差异。 结论:对于不同分次的宫颈癌外照射CT图像进行配准,建议采用三维弹性配准方法,其配准精度较高,能获得较准确的即往放疗总剂量。     

Combination of intensity-based image registration with 3D simulation in radiation therapy

Modern techniques of radiotherapy like intensity modulated radiation therapy (IMRT) make it possible to deliver high dose to tumors of different irregular shapes at the same time sparing surrounding healthy tissue. However, internal tumor motion makes precise calculation of the delivered dose distribution challenging. This makes analysis of tumor motion necessary. One way to describe target motion is using image registration. Many registration methods have already been developed previously. However, most of them belong either to geometric approaches or to intensity approaches. Methods which take account of anatomical information and results of intensity matching can greatly improve the results of image registration. Based on this idea, a combined method of image registration followed by 3D modeling and simulation was introduced in this project. Experiments were carried out for five patients 4DCT lung datasets. In the 3D simulation, models obtained from images of end-exhalation were deformed to the state of end-inhalation. Diaphragm motions were around -25 mm in the cranial-caudal (CC) direction. To verify the quality of our new method, displacements of landmarks were calculated and compared with measurements in the CT images. Improvement of accuracy after simulations has been shown compared to the results obtained only by intensity-based image registration. The average improvement was 0.97 mm. The average Euclidean error of the combined method was around 3.77 mm. Unrealistic motions such as curl-shaped deformations in the results of image registration were corrected. The combined method required less than 30 min. Our method provides information about the deformation of the target volume, which we need for dose optimization and target definition in our planning system.     

HIFU治疗中基于呼吸和脉搏信号的B超图像配准

目的：超声引导的HIFU治疗系统在临床治疗中,在同一治疗层面上,医生需要移动B超探头对比不同位置的图像定位靶区,本研究提出了一种基于呼吸和脉搏信号的动态B超图像配准方法。方法：根据呼吸和脉搏信号周期出现的特点,探头先运动到理想位置连续采集大概10 s的B超图像作为参考图像,同时记录每帧参考图像采集时刻的呼吸和脉搏信号作为参考信号。探头再返回到治疗位置通过DTW算法配准实时的呼吸和脉搏信号,找到配准信号对应的参考图像再补偿B超探头移动导致的图像位移,最终实现实时图像与参考图像的配准。结果：在实验中,通过调节B超探头与人体皮肤的距离,找到理想位置采集B超图像和呼吸脉搏信号作为参考数据,再回到治疗位置开始B超图像的配准,配准结果发现该技术具有很高的准确性和稳定性。结论：该技术能有效实现动态B超图像配准,也解决了模糊图像无法配准的难题。     

A finite element method to correct deformable image registration errors in low-contrast regions

Image-guided adaptive radiotherapy requires deformable image registration to map radiation dose back and forth between images. The purpose of this study is to develop a novel method to improve the accuracy of an intensity-based image registration algorithm in low-contrast regions. A computational framework has been developed in this study to improve the quality of the 'demons' registration. For each voxel in the registration's target image, the standard deviation of image intensity in a neighborhood of this voxel was calculated. A mask for high-contrast regions was generated based on their standard deviations. In the masked regions, a tetrahedral mesh was refined recursively so that a sufficient number of tetrahedral nodes in these regions can be selected as driving nodes. An elastic system driven by the displacements of the selected nodes was formulated using a finite element method (FEM) and implemented on the refined mesh. The displacements of these driving nodes were generated with the 'demons' algorithm. The solution of the system was derived using a conjugated gradient method, and interpolated to generate a displacement vector field for the registered images. The FEM correction method was compared with the 'demons' algorithm on the computed tomography (CT) images of lung and prostate patients. The performance of the FEM correction relating to the 'demons' registration was analyzed based on the physical property of their deformation maps, and quantitatively evaluated through a benchmark model developed specifically for this study. Compared to the benchmark model, the 'demons' registration has the maximum error of 1.2 cm, which can be corrected by the FEM to 0.4 cm, and the average error of the 'demons' registration is reduced from 0.17 to 0.11 cm. For the CT images of lung and prostate patients, the deformation maps generated by the 'demons' algorithm were found unrealistic at several places. In these places, the displacement differences between the 'demons' registrations and their FEM corrections were found in the range of 0.4 and 1.1 cm. The mesh refinement and FEM simulation were implemented in a single thread application which requires about 45 min of computation time on a 2.6 GHz computer. This study has demonstrated that the FEM can be integrated with intensity-based image registration algorithms to improve their registration accuracy, especially in low-contrast regions.     

Deformable registration of the planning image (kVCT) and the daily images (MVCT) for adaptive radiation therapy

The incorporation of daily images into the radiotherapy process leads to adaptive radiation therapy (ART), in which the treatment is evaluated periodically and the plan is adaptively modified for the remaining course of radiotherapy. Deformable registration between the planning image and the daily images is a key component of ART. In this paper, we report our researches on deformable registration between the planning kVCT and the daily MVCT image sets. The method is based on a fast intensity-based free-form deformable registration technique. Considering the noise and contrast resolution differences between the kVCT and the MVCT, an 'edge-preserving smoothing' is applied to the MVCT image prior to the deformable registration process. We retrospectively studied daily MVCT images from commercial TomoTherapy machines from different clinical centers. The data set includes five head-neck cases, one pelvis case, two lung cases and one prostate case. Each case has one kVCT image and 20-40 MVCT images. We registered the MVCT images with their corresponding kVCT image. The similarity measures and visual inspections of contour matches by physicians validated this technique. The applications of deformable registration in ART, including 'deformable dose accumulation', 'automatic re-contouring' and 'tumour growth/regression evaluation' throughout the course of radiotherapy are also studied.     

Accelerating reconstruction of reference digital tomosynthesis using graphics hardware

The successful implementation of digital tomosynthesis (DTS) for on-board image guided radiation therapy (IGRT) requires fast DTS image reconstruction. Both target and reference DTS image sets are required to support an image registration application for IGRT. Target images are usually DTS image sets reconstructed from on-board projections, which can be accomplished quickly using the conventional filtered backprojection algorithm. Reference images are DTS image sets reconstructed from digitally reconstructed radiographs (DRRs) previously generated from conventional planning CT data. Generating a set of DRRs from planning CT is relatively slow using the conventional ray-casting algorithm. In order to facilitate DTS reconstruction within a clinically acceptable period of time, we implemented a high performance DRR reconstruction algorithm on a graphics processing unit of commercial PC graphics hardware. The performance of this new algorithm was evaluated and compared with that which is achieved using the conventional software-based ray-casting algorithm. DTS images were reconstructed from DRRs previously generated by both hardware and software algorithms. On average, the DRR reconstruction efficiency using the hardware method is improved by a factor of 67 over the software method. The image quality of the DRRs was comparable to those generated using the software-based ray-casting algorithm. Accelerated DRR reconstruction significantly reduces the overall time required to produce a set of reference DTS images from planning CT and makes this technique clinically practical for target localization for radiation therapy.     

电子射野影像装置用于放射治疗的研究进展

用于放射治疗的电子射野影像装置(EPID)探测器主要有荧光屏摄像机系统、扫描矩阵电离室系统和有源矩阵平板探测器系统.基于非晶硅的有源矩阵平板探测器EPID,由于其具有使用方便、分辨率高、采集效率高及性能稳定等特点,已成为近年来用于放射治疗的主流探测器系统.EPID最初主要用于放射治疗的患者靶区位置和射野的验证,后逐步用于放疗设备本身的质量控制.目前的研究方向主要是用于放射治疗的剂量验证.相信通过深入了解EPID特性,开发相应的算法及软件后,其用于放疗设备的常规质量保证、实现在线位置验证和剂量验证等将成为一种常规方法.