Nonrigid image registration for head and neck cancer radiotherapy treatment planning with PET/CT

PURPOSE: Head and neck radiotherapy planning with positron emission tomography/computed tomography (PET/CT) requires the images to be reliably registered with treatment planning CT. Acquiring PET/CT in treatment position is problematic, and in practice for some patients it may be beneficial to use diagnostic PET/CT for radiotherapy planning. Therefore, the aim of this study was first to quantify the image registration accuracy of PET/CT to radiotherapy CT and, second, to assess whether PET/CT acquired in diagnostic position can be registered to planning CT. METHODS AND MATERIALS: Positron emission tomography/CT acquired in diagnostic and treatment position for five patients with head and neck cancer was registered to radiotherapy planning CT using both rigid and nonrigid image registration. The root mean squared error for each method was calculated from a set of anatomic landmarks marked by four independent observers. RESULTS: Nonrigid and rigid registration errors for treatment position PET/CT to planning CT were 2.77 +/- 0.80 mm and 4.96 +/- 2.38 mm, respectively, p = 0.001. Applying the nonrigid registration to diagnostic position PET/CT produced a more accurate match to the planning CT than rigid registration of treatment position PET/CT (3.20 +/- 1.22 mm and 4.96 +/- 2.38 mm, respectively, p = 0.012). CONCLUSIONS: Nonrigid registration provides a more accurate registration of head and neck PET/CT to treatment planning CT than rigid registration. In addition, nonrigid registration of PET/CT acquired with patients in a standardized, diagnostic position can provide images registered to planning CT with greater accuracy than a rigid registration of PET/CT images acquired in treatment position. This may allow greater flexibility in the timing of PET/CT for head and neck cancer patients due to undergo radiotherapy.     

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.     

Narrow band deformable registration of prostate magnetic resonance imaging, magnetic resonance spectroscopic imaging, and computed tomography studies

PURPOSE: Endorectal (ER) coil-based magnetic resonance imaging (MRI) and magnetic resonance spectroscopic imaging (MRSI) is often used to obtain anatomic and metabolic images of the prostate and to accurately identify and assess the intraprostatic lesions. Recent advancements in high-field (3 Tesla or above) MR techniques affords significantly enhanced signal-to-noise ratio and makes it possible to obtain high-quality MRI data. In reality, the use of rigid or inflatable endorectal probes deforms the shape of the prostate gland, and the images so obtained are not directly usable in radiation therapy planning. The purpose of this work is to apply a narrow band deformable registration model to faithfully map the acquired information from the ER-based MRI/MRSI onto treatment planning computed tomography (CT) images. METHODS AND MATERIALS: A narrow band registration, which is a hybrid method combining the advantages of pixel-based and distance-based registration techniques, was used to directly register ER-based MRI/MRSI with CT. The normalized correlation between the two input images for registration was used as the metric, and the calculation was restricted to those points contained in the narrow bands around the user-delineated structures. The narrow band method is inherently efficient because of the use of a priori information of the meaningful contour data. The registration was performed in two steps. First, the two input images were grossly aligned using a rigid registration. The detailed mapping was then modeled by free form deformations based on B-spline. The limited memory Broyden-Fletcher-Goldfarb-Shanno algorithm (L-BFGS), which is known for its superior performance in dealing with high-dimensionality problems, was implemented to optimize the metric function. The convergence behavior of the algorithm was studied by self-registering an MR image with 100 randomly initiated relative positions. To evaluate the performance of the algorithm, an MR image was intentionally distorted, and an attempt was then made to register the distorted image with the original one. The ability of the algorithm to recover the original image was assessed using a checkerboard graph. The mapping of ER-based MRI onto treatment planning CT images was carried out for two clinical cases, and the performance of the registration was evaluated. RESULTS: A narrow band deformable image registration algorithm has been implemented for direct registration of ER-based prostate MRI/MRSI and CT studies. The convergence of the algorithm was confirmed by starting the registration experiment from more than 100 different initial conditions. It was shown that the technique can restore an MR image from intentionally introduced deformations with an accuracy of approximately 2 mm. Application of the technique to two clinical prostate MRI/CT registrations indicated that it is capable of producing clinically sensible mapping. The whole registration procedure for a complete three-dimensional study (containing 256 x 256 x 64 voxels) took less than 15 min on a standard personal computer, and the convergence was usually achieved in fewer than 100 iterations. CONCLUSIONS: A deformable image registration procedure suitable for mapping ER-based MRI data onto planning CT images was presented. Both hypothetical tests and patient studies have indicated that the registration is reliable and provides a valuable tool to integrate the ER-based MRI/MRSI information to guide prostate radiation therapy treatment.     

Computed Tomography–Magnetic Resonance Image Registration in Radiotherapy Treatment Planning

Magnetic resonance imaging (MRI) is being increasingly used in radiotherapy treatment planning (RTP). MRI has the potential to provide improved localisation of target volumes, leading to better tumour control rates and reduced normal tissue complications, due to capabilities including excellent soft-tissue discrimination and the ability to provide scans in which the image contrast is weighted according to different tissue properties. When computed tomography (CT)–MRI image registration is deployed, MR’s advantages are combined with CT’s geometrical security and its ability to provide electron density information. The quality of CT–MRI image registration can be favourably influenced by aspects of scan acquisition, including patient positioning/immobilisation and scan protocols. Appropriate protocols can ameliorate the possible presence of MR spatial distortions and other artefacts, but quality assurance of scanning remains essential. Here, the methods and quality assurance of CT–MR image registration are discussed. Developments in MRI scanner technology are progressively offering advantages for RTP, in terms of the possibility of better matching of patient positioning versus CT in a greater range of anatomical regions, while allowing thinner slices for better image quality in reformatted orthogonal planes.     

A new approach to quantifying lung damage after stereotactic body radiation therapy

Radiological pneumonitis and fibrosis are common after stereotactic body radiotherapy (SBRT) but current scoring systems are qualitative and subjective. We evaluated the use of CT density measurements and a deformable registration tool to quantitatively measure lung changes post-SBRT. Material and methods. Four-dimensional CT datasets from 25 patients were imported into an image analysis program. Deformable registration was done using a B-spline algorithm (VelocityAI) and evaluated by landmark matching. The effects of respiration, contrast, and CT scanner on density measurements were evaluated. The relationship between density and clinician-scored radiological pneumonitis was assessed. Results. Deformable registration resulted in more accurate image matching than rigid registration. CT lung density was maximal at end-expiration, and most deformation with breathing occurred in the lower thorax. Use of contrast increased mean lung density by 18 HU (range 16-20 HU; p = 0.004). Diagnostic scans had a lower mean lung density than planning scans (mean difference 57 HU in lung contralateral to tumor; p = 0.048). Post-treatment CT density measurements correlated strongly with clinician-scored radiological pneumonitis (r = 0.75; p < 0.001). Conclusions. Quantitative analysis of changes in lung density correlated strongly with physician-assigned radiologic pneumonitis scores. Deformable registration and CT density measurements permit objective assessment of treatment toxicity.     

Feasibility of a novel deformable image registration technique to facilitate classification, targeting, and monitoring of tumor and normal tissue

PURPOSE: To investigate the feasibility of a biomechanical-based deformable image registration technique for the integration of multimodality imaging, image guided treatment, and response monitoring. METHODS AND MATERIALS: A multiorgan deformable image registration technique based on finite element modeling (FEM) and surface projection alignment of selected regions of interest with biomechanical material and interface models has been developed. FEM also provides an inherent method for direct tracking specified regions through treatment and follow-up. RESULTS: The technique was demonstrated on 5 liver cancer patients. Differences of up to 1 cm of motion were seen between the diaphragm and the tumor center of mass after deformable image registration of exhale and inhale CT scans. Spatial differences of 5 mm or more were observed for up to 86% of the surface of the defined tumor after deformable image registration of the computed tomography (CT) and magnetic resonance images. Up to 6.8 mm of motion was observed for the tumor after deformable image registration of the CT and cone-beam CT scan after rigid registration of the liver. Deformable registration of the CT to the follow-up CT allowed a more accurate assessment of tumor response. CONCLUSIONS: This biomechanical-based deformable image registration technique incorporates classification, targeting, and monitoring of tumor and normal tissue using one methodology.     

From clinical target volume to biological target volume

The authors' experience with a point matching algorithm for image registration belonging to a commercially available software package for conformal radiotherapy, is reported. The algorithm IFS (Image Fusion System) permits the registration of two image data-sets in two different manners: by use of a stereotactic localization frame, dedicated to brain studies, and by means of point markers that may be internal anatomical landmarks or external fiducials fixed on the patient skin. Position errors were obtained by evaluating the stereotactic coordinates of seven sources detectable by Magnetic Resonance Imaging (MRI) and Computed Tomography (CT), for the first method. The comparison of the geometric centers of cylindrical rods enclosed in a second phantom was employed to evaluate the registration accuracy of the second algorithm. The mean differences in source identification between CT and MRI images are inferior to 1 mm with both techniques, if MRI distortion phenomenon and patient movements are excluded. The software utility of the IFS algorithm to draw, after fusion, a target ROI that is the synthesis of the two information modalities undergoing registration may be a useful tool for the optimization of a radiotherapy treatment planning.     

The Registration of Diagnostic versus Planning Fluorodeoxyglucose Positron Emission Tomography/Computed Tomography in Radiotherapy Planning for Non-small Cell Lung Cancer

AimsRadiotherapy for non-small cell lung cancer (NSCLC) increasingly utilises fluorodeoxyglucose positron emission tomography/computed tomography (PET/CT) fusion. However, it is unknown whether a PET/CT scan conducted in the treatment position results in more accurate registration to the radiotherapy planning CT (rCT) than a diagnostic PET/CT scan. The aim of this study was to compare the accuracy of registration of the CT components of the planning PET/CT scan (pCT) and diagnostic PET/CT scan (dCT) scan with the rCT.Materials and methodsTen patients with stage I–III NSCLC underwent an rCT immediately followed by a planning PET/CT scan, both carried out with arms placed above the head and immobilisation in the treatment position. All previously underwent a diagnostic FDG PET/CT, which was carried out with the arms above the head, but without custom immobilisation. dCT and pCT were registered to the rCT using a rigid body mutual information algorithm. Four observers identified 12 anatomical points on each scan and differences in their absolute location were analysed.ResultsAt the carina, the mean absolute error (MAE) for pCT–rCT compared with dCT–rCT was 4.37 versus 5.73 mm (P = 0.028). However, there was no significant difference in the root mean squared error (RMSE) for that point. There were no significant differences in MAE or RMSE for all other anatomical points. The MAE for all points was 4.11 versus 4.15 mm (P = NS) and RMSE was 4.40 versus 4.48 mm for pCT–rCT compared with dCT–rCT (P = NS).ConclusionsThere is an average of 4 mm of misregistration when registering the CT components of PET/CT scans to the rCT for NSCLC. Using a rigid registration technique, the registration of a diagnostic PET/CT is as good as the registration of a planning PET/CT.     

Automatic target localization and verification for on-line image-guided stereotactic body radiotherapy of the spine

To facilitate image-guided stereotactic body radiotherapy (IG-SBRT) of spinal and paraspinal tumors, the authors have developed an on-line image registration system for automated target localization and patient position verification with high precision. When rotations are present in a patient's daily setup position, a setup error of a few millimeters can be introduced in localization of the isocenter by using surrounding bony structures. This setup error not only will deteriorate the dose coverage of the tumor, more importantly it will overdose the spinal cord. To resolve this issue, the image registration program developed by the authors detects translational shifts as well as rotational shifts using 3D CT image registration. Unacceptable rotations were corrected by either repositioning the patient or adjusting the treatment couch that was capable of rotational corrections when such a couch was available for clinical use. One pair of orthogonal digitally reconstructed radiographs (DRR) were generated from the daily pretreatment CT scan to compare with the corresponding DRRs generated from the planning CT scan to confirm the target shift correction. After the patient's position was corrected a pair of orthogonal portal images were taken for final verification. The accuracy of the image registration result was found to be within 0.1 mm on a head and neck phantom. Target shifts of a fraction of a millimeter were readily visible in our DRR comparison and portal image verification. The time needed to complete the image registration and DRR comparison was about 3 minutes. An integrated system that combines a high-speed CT scanner and a linear accelerator was used for imaging and treatment delivery. Application of the program in actual IG-SBRT cases demonstrated that it was accurate, fast, and reliable. It serves as a useful tool for image-guided radiotherapy where high precision of target localization is required.     

Effect of lateral target motion on image registration accuracy in CT-guided helical tomotherapy: A phantom study

Optimisation of imaging modes for kilovoltage CT (kVCT) used for treatment planning and megavoltage CT (MVCT) image guidance used in ungated helical tomotherapy was investigated for laterally moving targets. Computed tomography images of the QUASAR™ Respiratory Motion Phantom were acquired without target motion and for lateral motion of the target, with 2-cm peak-to-peak amplitude and a period of 4 s. Reference kVCT images were obtained using a 16-slice CT scanner in standard fast helical CT mode, untagged average CT mode and various post-processed 4D-CT modes (0% phase, average and maximum intensity projection). Three sets of MVCT images with different inter-slice spacings of were obtained on a Hi-Art tomotherapy system with the phantom displaced by a known offset position. Eight radiation therapists performed co-registration of MVCT obtained with 2-, 4- and 6-mm slice spacing and kVCT studies independently for all 15 CT imaging combinations. In the investigated case, the untagged average kVCT and 4-mm slice spacing for the MVCT yielded more accurate registration in the transverse plane. The average residual uncertainty of this combination of imaging procedures was 0.61 ± 0.16 mm in the longitudinal direction, 0.45 ± 0.14 mm in the anterior–posterior direction and insignificant in the lateral direction. Manual registration of MVCT–kVCT study pairs is necessary to account for a target in significant lateral motion with respect to bony structures.     

CT与MR多序列融合指导胶质瘤靶区勾画

目的:探讨CT与MR图像融合在脑胶质瘤术后放疗靶区勾画中的应用价值。方法:收集首诊为脑胶质瘤的30例患者进行术后IMRT,基于颅内外标记法的图像配准融合算法进行CT-MR图像融合,并分别根据CT图像及融合图像由资深放疗医师勾画靶区及危及器官,分组进行t检验比较其体积差异。计算CT及CT-MR图像上相应标记点的距离,并计算其体积重合度及中心位置距离。结果:采用颅内外标记法进行图像融合有着较高融合精度,融合误差均小于2 mm。Ⅲ-Ⅳ级胶质瘤组GTVCT比GTVMR+CT显著性减少,分别为GTVCT:（72.23±36.74） cm3,GTVMR+CT:（104.23±32.64） cm3（P=0.043<0.05）;CTVCT比CTVMR+CT也显著性降低,分别为CTVCT:（244.24±65.37） cm3,CTVMR+CT:（346.39±51.54） cm3 （P=0.047<0.05）。CT图像与融合图像的CTV中心位置变化最大,为（7.87±11.54） mm,其次为GTV、脑干,视交叉中心位置变化最小。结论:CT-MR图像融合有助于减少靶区勾画差异性,特别是对有水肿区存在及术后肿瘤残存者价值更大。     

Implementation and validation of a three-dimensional deformable registration algorithm for targeted prostate cancer radiotherapy

PURPOSE: Daily prostate deformation hinders accurate calculation of dose, especially to intraprostatic targets. We implemented a three-dimensional deformable registration algorithm to aid dose tracking for targeted prostate radiotherapy. METHODS AND MATERIALS: The algorithm registers two computed tomography (CT) scans by iteratively minimizing their differences in image intensity. For validation, we measured the accuracy in registering (a) a pelvic CT set to its mathematically deformed counterpart, (b) CT scans of a deformable pelvic phantom with and without an endorectal balloon inflated, to simulate intraprostatic targets, 23 CT-opaque seeds were embedded in the prostate, and (c) two pelvic CT scans of a patient obtained on 2 separate days. RESULTS: The mean (SD) error in registering the pelvic CT set to its transformed set was 0.5 mm (1.5), with correlation coefficient improvement from 0.626 to 0.991. Using the deformable pelvic phantom, the correlation coefficient improved from 0.543 to 0.816 after registration. The mean (SD) error in tracking the intraprostatic seeds was 0.8 mm (0.5). The correlation coefficient improved from 0.610 to 0.944 after registration of the two patient CT sets. CONCLUSION: The algorithm had an accuracy of about 1 mm. It could be used for optimizing dose calculation and delivery for prostate radiotherapy.     

C T与MRI影像配准方法配准效果的比较

目的：研究CT与MRI影像体表标记点法图像配准和交互式自动配准法图像配准的临床应用,探讨配准的评价方法,对比两种配准方法的配准效果。方法：选取需进行放射治疗的头颈部患者和胸部肿瘤患者病例各11例。两组患者均采用相同放疗体位和面罩固定方法,同时对患者进行CT和MRI定位扫描。采集CT和MRI时图像均采用同一套体表标记点。将获得的两套影像通过Dicom网络导入 Eclipse11．0放射治疗计划系统。对同一病例的CT和MRI 图像分别采用体表点标记法、交互式自动配准法进行图像配准。使用MRI图像的灰度值与 CT图像的（HU）值归一离轴曲线（Profile）和感兴趣区域体积中心位置偏差来评估配准效果。结果：对于头颈部位的病例,使用体表标记点法配准,感兴趣区体积中心位置偏差范围为（0．19±0．05）mm,CT值与MRI灰度值离轴曲线匹配良好。交互式自动配准方法感兴趣区体积中心位置偏差范围为（0．20±0．04）mm,CT值与MRI灰度值离轴曲线匹配良好。对于胸部组病例,使用体表标记点法配准偏差范围为（0．34±0．08）mm,离轴曲线匹配较差。交互式自动配准感兴趣区体积中心位置偏差范围为（0．23±0．06） mm,离轴曲线匹配良好。结论：对于头颈肿瘤组病例,两种方法均能得到较好的配准结果。交互式自动法在胸部肿瘤组更具优势,因为软件自动配准、人为因素影响较小,能更好的消除因体位变动带来的偏差,更适合放疗计划配准应用。     

HDR后装治疗CT图像至IMRT CT图像变形配准算法研究

目的 研究将高剂量率(HDR)后装治疗CT图像至IMRT的CT图像变形配准及剂量叠加的方法。方法 对含施源器的HDR CT图像进行分割,通过求解Navier-Stokes方程实现对施源器区域收缩变形以去除施源器;然后再利用基于Demons的图像变形配准方法,将去除施源器后的CTHDR图像及其剂量变形至CTIMRT图像域,完成HDR-IMRT CT图像变形配准及剂量累加。结果 利用宫颈癌患者放疗期间CTHDR和CTIMRT图像和相应剂量分布图像对算法进行验证,结果表明相对于一般变形配准算法,本算法能有效消除HDR CT图像中施源器对变形配准影响,得到精确的HDR-IMRT累加剂量分布。结论 ART中对总剂量监测和评价可让医生根据患者实际受量,新优化放疗计划,以实现放射剂量的精确投照。本算法可有效实现宫颈癌患者HDR-IMRT剂量的精确累加,其精度能满足实际临床的需要。     

Verification of in-treatment tumor position using kilovoltage cone-beam computed tomography: a preliminary study

Three-dimensional tumor position during rotational dose delivery was evaluated by acquiring in-treatment kilovoltage (kV) cone-beam CT (CBCT) to ensure treatment quality. The CBCT projection data of a phantom were acquired during rotational megavoltage (MV) dose delivery up to 6 Gy to evaluate image quality under MV beam irradiation. A lung tumor patient was treated with a total dose of 48 Gy in four fractions, each fraction including seven coplanar and noncoplanar beams, as well as a full-angle rotational beam. Tumor registration was performed between a planning CT image and a CBCT image immediately after patient setup. The patient couch was adjusted according to the registration results, and then the registration was repeated three times: immediately before treatment, during treatment, and immediately after treatment. The phantom image quality of the kV CBCT was not visually degraded up to the rotational MV dose of 6 Gy. Tumor position during rotational dose delivery was verified for the first time using kV CBCT.     

A novel 3D volumetric voxel registration technique for volume-view-guided image registration of multiple imaging modalities

PURPOSE: To provide more clinically useful image registration with improved accuracy and reduced time, a novel technique of three-dimensional (3D) volumetric voxel registration of multimodality images is developed. METHODS AND MATERIALS: This technique can register up to four concurrent images from multi-modalities with volume view guidance. Various visualization effects can be applied, facilitating global and internal voxel registration. Fourteen computed tomography/magnetic resonance (CT/MR) image sets and two computed tomography/positron emission tomography (CT/PET) image sets are used. For comparison, an automatic registration technique using maximization of mutual information (MMI) and a three-orthogonal-planar (3P) registration technique are used. RESULTS: Visually sensitive registration criteria for CT/MR and CT/PET have been established, including the homogeneity of color distribution. Based on the registration results of 14 CT/MR images, the 3D voxel technique is in excellent agreement with the automatic MMI technique and is indicatory of a global positioning error (defined as the means and standard deviations of the error distribution) using the 3P pixel technique: 1.8 degrees +/- 1.2 degrees in rotation and 2.0 +/- 1.3 (voxel unit) in translation. To the best of our knowledge, this is the first time that such positioning error has been addressed. CONCLUSION: This novel 3D voxel technique establishes volume-view-guided image registration of up to four modalities. It improves registration accuracy with reduced time, compared with the 3P pixel technique. This article suggests that any interactive and automatic registration should be safe-guarded using the 3D voxel technique.     

Cone-beam CT based image-guidance for extracranial stereotactic radiotherapy of intrapulmonary tumors

Cone-beam CT (CB-CT) based image-guidance was evaluated for extracranial stereotactic radiotherapy of intrapulmonary tumors. A total of 21 patients (25 lesions: prim. NSCLC n = 6; pulmonary metastases n = 19) were treated with stereotactic radiotherapy (1 to 8 fractions). Prior to every fraction a CB-CT was acquired in treatment position, errors between planned and actual tumor position were measured and corrected. Intra- and inter-observer variability of manual evaluation of tumor position error was investigated and this manual method was compared with automatic image registration. Based on CB-CTs from 66 fractions the discrepancy (3-D vector) between planned and actual tumor position was 7.7 mm +/-1.3 mm. Tumor position error relative to the bony anatomy was 5.3 mm +/-1.2 mm, the correlation between bony anatomy and tumor position was poor. Intra-observer and inter-observer variability of manual evaluation of tumor position error was 0.9 mm +/-0.8 mm and 2.3 mm +/-1.1 mm, respectively. Automatic image registration showed highly reproducible results (<1 mm). However, compared with manual registration a systematic error was found in direction of predominant tumor breathing motion (2.5 mm vs 1.4 mm). Image-guidance using CB-CT was validated for high precision radiotherapy of intrapulmonary tumors. It was shown that both the planning reference and the verification image study have to consider tumor breathing motion.     

A phantom study of the accuracy of CT, MR and PET image registrations with a block matching-based algorithm

PURPOSE: The aim of the present study was to quantitatively assess the performance of a block matching-based automatic registration algorithm integrated within the commercial treatment planning system designated ISOgray from Dosisoft. The accuracy of the process was evaluated by a phantom study on computed tomography (CT), magnetic resonance (MR) and positron emission tomography (PET) images. MATERIALS AND METHODS: Two phantoms were used to carry out this study: the cylindrical Jaszczak phantom and the anthropomorphic Liqui-Phil Head Phantom (the Phantom Laboratory), containing fillable spheres. External fiducial markers were used to quantify the accuracy of 41 CT/CT, MR/CT and PET/CT automatic registrations with images of the rotated and tilted phantoms. RESULTS: The study first showed that a cylindrical phantom was not adapted for the evaluation of the performance of a block matching-based registration software. Secondly, the Liqui-Phil Head Phantom study showed that the algorithm was able to perform automatic registrations of CT/CT and MR/CT images with differences of up to 40 degrees in phantom rotation and of up to 20-30 degrees for PET/CT with accuracy below the image voxel size. CONCLUSION: The study showed that the block matching-based automatic registration software under investigation was robust, reliable and yielded very satisfactory results. This phantom-based test can be integrated into a periodical quality assurance process and used for any commissioning of image registration software for radiation therapy.     

A Comparison of clinical target volumes determined by CT and MRI for the radiotherapy planning of base of skull meningiomas

Purpose: To assess the utility of image registration and to compare the localization of clinical target volumes (CTV) using CT and MRI for patients with base of skull meningiomas undergoing radiotherapy.

Methods and Materials: Seven patients were imaged using CT and a T1-weighted MR volumetric sequence. Following image registration using a chamfer-matching algorithm, transaxial MR slices were reconstructed to match the planning CT slices. The accuracy of the image fusion was assessed in a preliminary study with matching accuracy better than 1.5 mm. The CTV in each patient was separately segmented by two independent observers for both CT and reconstructed MR image sets. Scalar and vector assessments were made of the difference in radial extent between the two outlines on each transaxial plane for all patients. A positive vector value corresponded to a greater extension of the tumor on MR compared to CT and vice versa. Scalar measurements compared the modulus of the differences between MR and CT, regardless of which volume was more extensive. Qualitative comparisons were also performed.

Results: Interobserver difference was small with a mean (± 1SD) volume difference of 1.5 ± 1.5 cm³ for CT and 0.5 ± 1.0 cm³ for MRI. The mean CT- and MR- CTVs were 17.6 ±10.8 and 19.6 ±14.2 cm³ respectively. The mean overlap and composite volumes were 13.8 ±10.1 and 23.3 ±14.8 cm³ respectively. Average scalar differences in the left, right, anterior, and posterior directions were 6.0 ± 7.0, 3.3 ± 2.5, 4.9 ± 3.9, and 4.5 ± 5.0 mm respectively. The average vector differences were 3.3 ± 8.5, −0.3 ± 3.8, 1.1 ± 5.8, 1.5 ± 6.4 mm (for left, right, anterior, and posterior directions respectively). Qualitatively, MR appeared to discern more tumor involvement in soft tissue regions adjacent to the skull base whereas CT appeared to provide larger target volumes within bony regions.

Conclusions: MRI appeared to define CTVs that were larger but not inclusive of CT-defined CTVs. Although the average vector differences were small, the differences on individual borders could be large. In some instances, the CT or MR volumes were vastly different, each providing separate information. Therefore, the use of MRI and CT is complementary. Until accurate histological confirmation of disease extent is available, it is prudent to consider composite CT/MR volumes for the radiotherapy planning of base of skull meningiomas.