宫颈癌自适应放疗中基于自配准与图谱库的自动勾画比较

目的 分析MIM软件在宫颈癌自适应放疗中基于自配准与图谱库的自动勾画的可行性与准确性。方法 选取60例宫颈癌患者的CT图像及勾画结果建立Atlas模板库。随机选取15例宫颈癌患者初次计划CT (pCT)与重新计划CT (rCT),由资深临床医师勾画CTV和危及器官。分别以刚性和形变两种配准方式将pCT的勾画传送到rCT图像上;并对各rCT图像行基于Atlas模板库的自动勾画,统计3种方法所需时间。利用Dice相似性系数(DSC)、交叉指数(OI)、Hausdorff平均距离(AHD)、质心距离(DC)评价勾画结果,并进行单因素方差分析。结果 Atlas组、刚性组和形变组完成1例所需平均时间分别为89.2、22.4、42.6 s。对于CTV和直肠的DSC、OI和AHD,刚性组和形变组与Atlas组之间不同(P<0.001),小肠的OI在刚性组和形变组与Atlas组之间有不同, CTV的DSC平均值分别为0.89(刚性组和形变组)、0.76(Atlas组)。对于膀胱、盆骨和股骨头,形变组的勾画结果最优。结论 形变组的勾画结果优于刚性组和Atlas组,3种勾画方式均能快速地完成靶区和危及器官的自动勾画。     

自由呼吸频率与运动幅度对CT与CBCT图像配准偏差分析

目的 探讨自由呼吸状态下,不同呼吸频率、运动幅度对CT扫描图像与CBCT图像的配准偏差。方法 使用QUASAR呼吸运动模体,改变运动频率和头脚方向上的运动幅度,模拟不同状态下的自由呼吸运动。在模体静止时、各种运动状态下分别行定位CT扫描和CBCT扫描,获取相应配准结果及CT定位靶区体积,进行定量分析。结果 以模体静止时的定位CT图像为参考进行配准,当运动幅度一定时,频率的变化对图像的配准误差无明显影响。运动幅度分别为5 mm、10 mm、20 mm、30 mm时,配准误差分别为（0.213±0.020） cm、（0.351±0.009） cm、（0.654±0.010） cm与（0.972±0.022）cm。当运动幅度为5 mm、10 mm时,定位靶区体积变化为-16.92%~18.78%。当运动幅度为20 mm、30 mm时,定位靶区体积变化为-16.44%~81.70%。结论 自由呼吸运动下频率变化对CBCT与定位CT图像之间的配准误差无明显影响。运动幅度为5 mm、10 mm时,配准误差小,定位靶区体积变化小;当运动幅度为20 mm、30 mm时,配准误差可超过0.5 cm,定位靶区体积变化可>20%。     

自由呼吸频率与运动幅度对CT与CBCT图像配准偏差分析

目的 探讨自由呼吸状态下,不同呼吸频率、运动幅度对CT扫描图像与CBCT图像的配准偏差。方法 使用QUASAR呼吸运动模体,改变运动频率和头脚方向上的运动幅度,模拟不同状态下的自由呼吸运动。在模体静止时、各种运动状态下分别行定位CT扫描和CBCT扫描,获取相应配准结果及CT定位靶区体积,进行定量分析。结果 以模体静止时的定位CT图像为参考进行配准,当运动幅度一定时,频率的变化对图像的配准误差无明显影响。运动幅度分别为5 mm、10 mm、20 mm、30 mm时,配准误差分别为（0.213±0.020） cm、（0.351±0.009） cm、（0.654±0.010） cm与（0.972±0.022）cm。当运动幅度为5 mm、10 mm时,定位靶区体积变化为-16.92%~18.78%。当运动幅度为20 mm、30 mm时,定位靶区体积变化为-16.44%~81.70%。结论 自由呼吸运动下频率变化对CBCT与定位CT图像之间的配准误差无明显影响。运动幅度为5 mm、10 mm时,配准误差小,定位靶区体积变化小;当运动幅度为20 mm、30 mm时,配准误差可超过0.5 cm,定位靶区体积变化可>20%。     

千伏级CBCT引导鼻咽癌IMRT中不同图像配准方式比较

目的 比较千伏级CBCT引导下鼻咽癌IMRT中不同图像配准方式对配准结果的影响。方法 搜集2012—2013年24例鼻咽癌IMRT患者560次治疗前初次摆位的千伏级CBCT图像做离线配准分析。分别选取骨与灰度的平移误差加旋转误差配准方式(Bone_T+R与Grey_T+R),以及单纯灰度平移误差配准方式(Grey_T),并对配准结果行配对t检验。结果 Bone_T+R在左右、上下、前后方向的靶区中心平移误差与旋转误差分别为(－0.11±1.35)、(0.40±2.09)、(0.95±1.56) mm与1.06°±0.67°、0.01°±1.28°、0.92°±1.00°;Grey_T+R的平移误差与旋转误差分别为(－0.02±1.06)、(0.68±1.92)、(0.81±1.46) mm与0.85°±0.61°、－0.05°±1.32°、0.91°±0.72°;Grey_T的平移误差分别为(0.58±1.02)、(0.52±1.89)、(0.44±1.43) mm。除Bone_T+R与Grey_T+R旋转误差在上下、前后方向上相近外(P=0.05、0.62),其余均不同(P=0.00~0.01)。结论 用千伏级CBCT引导鼻咽癌IMRT时,在三维方向上的配准结果因图像配准方式不同而有差别。选择自动配准方式时,若要纠正旋转误差建议选择Grey_T+R方式;不纠正旋转误差时建议可先选择Grey_T+R方式观察有否旋转误差>2°或3°(视各放疗中心要求而定),若有则需重新摆位,若无则重新选择Grey_T方式,必要时辅以手动修正。     

基于图像变换的CT图像校正算法在宫颈癌放疗剂量准确性评估中的应用

目的 定量评估宫颈癌放疗计划剂量准确性。方法 提出基于图像变换的CT图像校正算法,参考CBCT图像对宫颈癌临床计划CT图像进行校正,获取更能反映实际治疗体位的校正图像;将临床计划移植至校正图像重算剂量生成测试计划,并与临床计划进行剂量学参数比较分析,评估剂量准确性。结果 对比计划靶区覆盖均能满足临床要求(>98%),均匀性指数HI无较大差别(P=0.150);测试计划剂量分布适形性较临床计划差且具有显著性差异(P<0.05)。测试计划各危及器官的Dmax较临床计划高约30 cGy并具有显著性差异(P<0.05),V50较临床计划略高,而Dmean无较大差异。结论 基于图像变换的CT图像校正算法可用于对宫颈癌放疗剂量准确性进行定量评估,为临床解决类似问题提供参考。     

基于图像变换的CT图像校正算法在宫颈癌放疗剂量准确性评估中的应用

目的 定量评估宫颈癌放疗计划剂量准确性。方法 提出基于图像变换的CT图像校正算法,参考CBCT图像对宫颈癌临床计划CT图像进行校正,获取更能反映实际治疗体位的校正图像;将临床计划移植至校正图像重算剂量生成测试计划,并与临床计划进行剂量学参数比较分析,评估剂量准确性。结果 对比计划靶区覆盖均能满足临床要求(>98%),均匀性指数HI无较大差别(P=0.150);测试计划剂量分布适形性较临床计划差且具有显著性差异(P<0.05)。测试计划各危及器官的Dmax较临床计划高约30 cGy并具有显著性差异(P<0.05),V50较临床计划略高,而Dmean无较大差异。结论 基于图像变换的CT图像校正算法可用于对宫颈癌放疗剂量准确性进行定量评估,为临床解决类似问题提供参考。     

Catalyst HD和皮肤标记线肺癌SBRT摆位精度比较

目的 比较光学表面引导放疗系统Catalyst HD和皮肤标记线两种摆位方式在肺癌立体定向放疗(SBRT)中的摆位精度。方法 选取24例SBRT病例,均采用仰卧位和真空垫固定,分别利用Catalyst HD(A组)和皮肤标记线(B组)进行摆位,并通过CBCT和定位CT刚性配准方式获取床左右(x轴向)、升降(y轴向)、进出(z轴向)、床旋转(Rtn)、进出倾斜(Pitch)、左右转动(Roll)配准误差。结果 A组和B组六维度配准误差取绝对值后平均值±标准差依次为(0.13±0.12) cm和(0.25±0.19) cm、(0.26±0.15) cm和(0.13±0.11) cm、(0.23±0.19) cm和(0.35±0.29) cm、(0.43°±0.40°)和(0.80°±0.69°)、(0.48°±0.47°)和(0.79°±0.64°)、(0.62°±0.60°)和(0.88°±0.70°)。上述六组数据正态性检验除B组x轴向外均不服从正态分布,两组差异均有统计学意义(P<0.05)。两组数据中超限误差(>0.5cm/2°)差异也有统计学意义(P<0.05)。结论 Catalyst HD方式六维度配准误差均低于标记点方式(y轴向除外),Catalyst HD方式摆位精度优于传统标记点,具有较好临床应用价值。     

Siemens Artiste加速器4种图像引导方式的放射剂量学研究

目的 对Artiste加速器image beam line (IBL)模式下2Dplanar、MV CBCT以及6 MV 2Dplanar和Somatom CT图像引导方式放射剂量进行测量,结合患者照射部位选择恰当图像引导方式。方法 利用IBA Dose 1静电计和FC65 指形电离室对头、胸、盆腔仿真模体在2Dplanar、MV CBCT及6 MV 2Dplanar图像引导模式下放射剂量进行测量,用IBA Dosimax plus A 系统测量Somatom CT 头、胸、盆腔扫描模式放射剂量,对测量结果进行分析。结果 在头颈部位,IBL模式 2Dplanar放射平均剂量为16.60 mGy, MV CBCT放射Dmean为58.73 mGy,6 MV 2Dplanar放射Dmean为19.83 mGy,Somatom CT的放射剂量为7~9 mGy;在胸部,IBL模式 2Dplanar放射Dmean为14.08 mGy,MV CBCT放射剂量为49.17 mGy,6 MV 2Dplanar放射Dmean为18.97 mGy,Somatom CT的放射剂量为9~11 mGy;在盆腔部位,IBL模式 2Dplanar放射Dmean为13.36 mGy, MV CBCT放射Dmean为45.65 mGy,6 MV 2Dplanar放射Dmean为17.52 mGy,Somatom CT的放射剂量为12~15 mGy。结论 头颈部,IBL 2Dplanar图像质量已达到配准要求,用IBL 2Dplanar即可;胸部使用Somatom CT进行图像引导较为恰当;盆腔部位,肠腔和膀胱充盈较好时IBL 2DPlanar进行引导即可,充盈欠佳时MV CBCT模式即可满足要求。     

MR增强延迟扫描成像在保乳术后俯卧位照射患者瘤床靶区勾画中的应用

目的 基于形变配准探讨保乳术后术腔血清肿不可见或低可见度(CVS≤2)患者行俯卧位照射时MR增强延迟扫描成像在瘤床(LC)勾画中的应用。方法 26例患者入组。分别在俯卧位CT定位图像、俯卧位MR定位T2WI成像及增强延迟2、5、10min的T1WI成像上勾画LC并分别定义为LCCT、LCT2、LC2T1、LC5T1和LC10T1。基于形变配准进行CT与MR图像LC间体积与位置的比较。结果 LCT2、LC2T1、LC5T1、LC10T1体积似均大于LCCT体积,且LC2T1、LC5T1与LCCT间体积差异有统计学意义(均P<0.05)。LC10T1与LCCT间的包含度(DI)、适形指数(CI)、相似度指数(DSC)、靶区中心距离(COM)均似优于LCT2与LCCT、LC2T1与LCCT及LC5T1与LCCT,但差异均无统计学意义(均P>0.05)。结论 基于俯卧位MR定位增强延迟扫描成像勾画低CVS患者LC靶区是可行的,无论是靶区体积大小还是靶区空间位置,基于T1WI增强延迟10min扫描所勾画LC靶区与基于俯卧位CT图像上金属钛夹所勾画的最接近。     

锥形束CT生成伪CT的深度学习方法

目的针对前列腺癌放疗, 研究锥形束CT(CBCT)生成伪CT的深度学习方法, 以满足自适应放疗的需要。方法纳入瓦里安On-Board Imager采集的74例前列腺癌患者的CBCT图像及其模拟定位CT图像, 并使用MIM软件进行形变配准。将数据按简单随机法分为训练集(59例)和测试集(15例)。使用U-net、Pix2PixGAN和CycleGAN学习CBCT到模拟定位CT的映射。以形变配准后CT作为参考图像, 评价平均绝对误差(MAE)、结构相似指数(SSIM)和峰值信噪比(PSNR)。另外单独分析了图像质量, 包括软组织分辨率、图像噪声和伪影等。结果使用U-net、Pix2PixGAN和CycleGAN生成图像的MAE分别为(29.4±16.1)、(37.1±14.4)、(34.3±17.3)HU。在图像质量方面, U-net和Pix2PixGAN生成的图像存在过度模糊的问题, 导致了图像失真;而CycleGAN生成的图像保留了CBCT图像结构且改善了图像质量。结论 CycleGAN能有效地提高CBCT图像质量, 有更大的潜力应用于自适应放疗中。     

Planification de la radiothérapie du cancer de la prostate par l’imagerie par résonance magnétique

PurposeMagnetic resonance imaging (MRI) plays an increasing role in radiotherapy dose planning. Indeed, MRI offers superior soft tissue contrast compared to computerized tomography (CT) and therefore could provide a better delineation of target volumes and organs at risk than CT for radiotherapy. Furthermore, an MRI-only radiotherapy workflow would suppress registration errors inherent to the registration of MRI with CT. However, the estimation of the electronic density of tissues using MRI images is still a challenging issue. The purpose of this work was to design and evaluate a pseudo-CT generation method for prostate cancer treatments.Materials and methodsA pseudo-CT was generated for ten prostate cancer patients using an elastic deformation based method. For each patient, dose delivered to the patient was calculated using both the planning CT and the pseudo-CT. Dose differences between CT and pseudo-CT were investigated.ResultsMean dose relative difference in the planning target volume is 0.9% on average and ranges from 0.1% to 1.7%. In organs at risks, this value is 1.8%, 0.8%, 0.8% and 1% on average in the rectum, the right and left femoral heads, and the bladder respectively.ConclusionThe dose calculated using the pseudo-CT is very close to the dose calculated using the CT for both organs at risk and PTV. These results confirm that pseudo-CT images generated using the proposed method could be used to calculate radiotherapy treatment doses on MRI images.     

Evaluation of similarity measures for reconstruction-based registration in image-guided radiotherapy and surgery

PURPOSE: A promising patient positioning technique is based on registering computed tomographic (CT) or magnetic resonance (MR) images to cone-beam CT images (CBCT). The extra radiation dose delivered to the patient can be substantially reduced by using fewer projections. This approach results in lower quality CBCT images. The purpose of this study is to evaluate a number of similarity measures (SMs) suitable for registration of CT or MR images to low-quality CBCTs. METHODS AND MATERIALS: Using the recently proposed evaluation protocol, we evaluated nine SMs with respect to pretreatment imaging modalities, number of two-dimensional (2D) images used for reconstruction, and number of reconstruction iterations. The image database consisted of 100 X-ray and corresponding CT and MR images of two vertebral columns. RESULTS: Using a higher number of 2D projections or reconstruction iterations results in higher accuracy and slightly lower robustness. The similarity measures that behaved the best also yielded the best registration results. The most appropriate similarity measure was the asymmetric multi-feature mutual information (AMMI). CONCLUSIONS: The evaluation protocol proved to be a valuable tool for selecting the best similarity measure for the reconstruction-based registration. The results indicate that accurate and robust CT/CBCT or even MR/CBCT registrations are possible if the AMMI similarity measure is used.     

Cone beam CT (CBCT) evaluation of inter- and intra-fraction motion for patients undergoing brain radiotherapy immobilized using a commercial thermoplastic mask on a robotic couch

Patients receiving fractionated intensity-modulated radiation therapy (IMRT) for brain tumors are often immobilized with a thermoplastic mask; however, masks do not perfectly re-orient the patient due to factors including the maximum pressure which can be applied to the face, deformations of the mask assembly, patient compliance, etc. Consequently, ~3-5mm PTV margins (beyond the CTV) are often recommended. We aimed to determine if smaller PTV margins are feasible using mask immobilization coupled with 1) a gantry mounted CBCT image guidance system and 2) position corrections provided by a full six-degree of freedom (6-DOF) robotic couch. A cohort of 34 brain tumor patients was treated with fractionated IMRT. After the mask set-up, an initial CBCT was obtained and registered to the planning CT. The robotic couch corrected the misalignments in all 6-DOF and a pre-treatment verification CBCT was then obtained. The results indicated a repositioning alignment within our threshold of 1.5 mm (3D). Treatment was subsequently delivered. A post-treatment CBCT was obtained to quantify intra-fraction motion. Initial, pre-treatment and post-treatment CBCT image data was analyzed. A total of 505 radiation fractions were delivered to the 34 patients resulting in ~1800 CBCT scans. The initial median 3D (magnitude) set-up positioning error was 2.60 mm. Robotic couch corrections reduced the 3D median error to 0.53 mm prior to treatment. Intra-fraction movement was responsible for increasing the median 3D positioning error to 0.86 mm, with 8% of fractions having a 3D positioning error greater than 2 mm. Clearly CBCT image guidance coupled with a robotic 6-DOF couch dramatically improved the positioning accuracy for patients immobilized in a thermoplastic mask system; however, such intra-fraction motion would be too large for single fraction radiosurgery.     

图像配准条件对头颈部CBCT引导放疗精度影响

目的：明确头颈部CBCT引导放疗图像层厚与配准范围对自动配准精度的影响,为IGRT摆位修正提供参考依据。方法以1、3 mm层厚获取头颈部仿真模体的计划CT图像,并在加速器上模拟x、y、z方向摆位偏差,进行CBCT扫描和1、3 mm层厚重建图像。分别设置不同配准框范围（范围1：眼眶上缘至第七颈椎中间;范围2：颅顶至第七颈椎中间）对上述两种层厚CBCT与计划CT图像进行自动配准,评估配准精度。结果配准范围1在1、3 mm层厚图像配准误差为x方向（0．5±0．2）、（－0．7±0．2） mm （P＝0．00）,y方向（0．5±0．3）、（1．0±0．3） mm （P＝0．00）,z方向（－0．1±0．5）、（1．5±0．5） mm （P＝0．00）。配准范围2在3 mm层厚图像配准误差为x方向（－0．4±0．2） mm,y方向（0．5±0．2） mm,z方向（0．7±0．4） mm。结论在头颈部CBCT或CT图像配准中将颅顶包含进配准范围内能显著提高配准的精度。采用1 mm层厚图像配准的误差可以控制在1 mm内。     

Comparison of kilovoltage cone-beam computed tomography with megavoltage projection pairs for paraspinal radiosurgery patient alignment and position verification

PURPOSE: Implanted gold markers and megavoltage (MV) portal imaging are commonly used for setup verification of paraspinal tumors treated with high-dose, single-fraction radiotherapy. We investigated whether the use of kilovoltage cone-beam computed tomography (CBCT) imaging eliminates the need for marker implantation. METHODS AND MATERIALS: Patients with paraspinal disease who were eligible for single-fraction stereotactic body radiotherapy were accrued to an institutional review board-approved protocol. Each of 16 patients underwent implantation of fiducial markers near the target. The markers were visible on the MV images. Three MV image pairs were acquired for each patient (initial, verification, and final) and were registered to the reference images. Every MV pair was complemented by a CBCT scan. CBCT image registration was performed automatically by maximizing the mutual information using a region of interest that excluded the markers. The corrections, as determined from the MV images, were compared with these from CBCT and were used for actual patient setup. RESULTS: The mean and standard deviation of the absolute values of the differences between the CBCT and MV corrections were 1.0 +/- 0.7, 1.0 +/- 0.6, and 1.0 +/- 0.8 mm for the left-right, anteroposterior, and superoinferior directions, respectively. The absolute differences between the corresponding pre- and post-treatment kilovoltage CBCT image registration were 0.6 +/- 0.5, 0.6 +/- 0.5, and 1.0 +/- 0.8 mm. CONCLUSION: The setup corrections found using CBCT without the use of implanted markers were consistent with the marker registration on MV projections. CBCT has additional advantages, including better positioning precision and robust automatic three-dimensional registration, as well as eliminating the need for invasive marker implantation. We have adopted CBCT for the setup of all single-fraction paraspinal patients. Our data have also demonstrated that target displacements during treatment are insignificant.     

食管癌锥形束CT配准标志和配准方法探讨

目的 探讨食管癌图像引导放疗(IGRT)时锥形束CT扫描后的6个自由度(6DF)的配准标志和配准方法 .方法 选择IGRT前扫描的30组食管癌的锥形束CT图像和相应计划CT图像,并确定和勾画用于6DF图像配准的配准标志.以手动配准为基准,对比骨配准、灰度配准、手动配准和骨配准+手动配准的优劣.结果 IGRT治疗前运用勾画出的食管癌靶区旁骨性标志和椎管标志可进行快速而准确的6DF配准.骨配准+手动配准与手动配准在v旋转方向上不同-0.55°、-0.88°(t=2.55,P=0.020);骨配准与手动配准在x轴平移及v旋转方向上均不同,分别为0.12、-2.33mm及(t=5.75,P=0.000)-0.35°、-0.88°(t=3.00,P=0.007);灰度配准与手动配准在x轴平移及w旋转方向上均也不同,分别为7.20、-2.33mm(t=3.10,P=0.006)及-0.10°、-0.59°(t=2.81,P=0.011).骨配准+手动配准符合率最高(85.55%),骨配准和灰度配准相似(74.45%和74.45%).配准时间为手动配准(6.00～10.00 min)>骨配准+手动配准(1.00～5.00 min)>灰度配准(0.75～1.50 min)>骨配准(0.50～0.83 min).结论 食管癌患者在IGRT治疗前的配准需要配准标志,结合配准时间和配准准确性,骨配准+手动配准方法 最佳.     

Automatic prostate localization on cone-beam CT scans for high precision image-guided radiotherapy

PURPOSE: Previously, we developed an automatic three-dimensional gray-value registration (GR) method for fast prostate localization that could be used during online or offline image-guided radiotherapy. The method was tested on conventional computed tomography (CT) scans. In this study, the performance of the algorithm to localize the prostate on cone-beam CT (CBCT) scans acquired on the treatment machine was evaluated. METHODS AND MATERIALS: Five to 17 CBCT scans of 32 prostate cancer patients (332 scans in total) were used. For 18 patients (190 CBCT scans), the CBCT scans were acquired with a collimated field of view (FOV) (craniocaudal). This procedure improved the image quality considerably. The prostate (i.e., prostate plus seminal vesicles) in each CBCT scan was registered to the prostate in the planning CT scan by automatic 3D gray-value registration (normal GR) starting from a registration on the bony anatomy. When these failed, registrations were repeated with a fixed rotation point locked at the prostate apex (fixed apex GR). Registrations were visually assessed in 3D by one observer with the help of an expansion (by 3.6 mm) of the delineated prostate contours of the planning CT scan. The percentage of successfully registered cases was determined from the combined normal and fixed apex GR assessment results. The error in gray-value registration for both registration methods was determined from the position of one clearly defined calcification in the prostate gland (9 patients, 71 successful registrations). Results: The percentage of successfully registered CBCT scans that were acquired with a collimated FOV was about 10% higher than for CBCT scans that were acquired with an uncollimated FOV. For CBCT scans that were acquired with a collimated FOV, the percentage of successfully registered cases improved from 65%, when only normal GR was applied, to 83% when the results of normal and fixed apex GR were combined. Gray-value registration mainly failed (or registrations were difficult to assess) because of streaks in the CBCT scans caused by moving gas pockets in the rectum during CBCT image acquisition (i.e., intrafraction motion). The error in gray-value registration along the left-right, craniocaudal, and anteroposterior axes was 1.0, 2.4, and 2.3 mm (1 SD) for normal GR, and 1.0, 2.0, and 1.7 mm (1 SD) for fixed apex GR. The systematic and random components of these SDs contributed approximately equally to these SDs, for both registration methods. Conclusions: The feasibility of automatic prostate localization on CBCT scans acquired on the treatment machine using an adaptation of the previously developed three-dimensional gray-value registration algorithm, has been validated in this study. Collimating the FOV during CBCT image acquisition improved the CBCT image quality considerably. Artifacts in the CBCT images caused by large moving gas pockets during CBCT image acquisition were the main cause for unsuccessful registration. From this study, we can conclude that CBCT scans are suitable for online and offline position verification of the prostate, as long as the amount of nonstationary gas is limited.