Robot-assisted 3D-TRUS guided prostate brachytherapy: system integration and validation

Current transperineal prostate brachytherapy uses transrectal ultrasound (TRUS) guidance and a template at a fixed position to guide needles along parallel trajectories. However, pubic arch interference (PAI) with the implant path obstructs part of the prostate from being targeted by the brachytherapy needles along parallel trajectories. To solve the PAI problem, some investigators have explored other insertion trajectories than parallel, i.e., oblique. However, parallel trajectory constraints in current brachytherapy procedure do not allow oblique insertion. In this paper, we describe a robot-assisted, three-dimensional (3D) TRUS guided approach to solve this problem. Our prototype consists of a commercial robot, and a 3D TRUS imaging system including an ultrasound machine, image acquisition apparatus and 3D TRUS image reconstruction, and display software. In our approach, we use the robot as a movable needle guide, i.e., the robot positions the needle before insertion, but the physician inserts the needle into the patient's prostate. In a later phase of our work, we will include robot insertion. By unifying the robot, ultrasound transducer, and the 3D TRUS image coordinate systems, the position of the template hole can be accurately related to 3D TRUS image coordinate system, allowing accurate and consistent insertion of the needle via the template hole into the targeted position in the prostate. The unification of the various coordinate systems includes two steps, i.e., 3D image calibration and robot calibration. Our testing of the system showed that the needle placement accuracy of the robot system at the "patient's" skin position was 0.15 mm+/-0.06 mm, and the mean needle angulation error was 0.07 degrees. The fiducial localization error (FLE) in localizing the intersections of the nylon strings for image calibration was 0.13 mm, and the FLE in localizing the divots for robot calibration was 0.37 mm. The fiducial registration error for image calibration was 0.12 mm and 0.52 mm for robot calibration. The target registration error for image calibration was 0.23 mm, and 0.68 mm for robot calibration. Evaluation of the complete system showed that needles can be used to target positions in agar phantoms with a mean error of 0.79 mm+/-0.32 mm.     

A simple technique for alignment of perineal needle template to ultrasound image grid for permanent prostate implants

Proper alignment of a needle template and ultrasound software grid is required to accurately deliver permanent prostate seed implants optimized using pretreatment volume studies. Correct alignment may also reduce tissue edema, morbidity, and the time and labor required to deliver permanent prostate seed implants. A technique has been developed to rapidly assess (and, if necessary, improve) the alignment using a custom-designed water phantom. Verification of needle positions can be conducted within 1 mm and requires less than ten minutes. We have instituted the technique as a part of our periodic quality assurance program.     

Prostate MR elastography with transperineal electromagnetic actuation and a fast fractionally encoded steady‐state gradient echo sequence

Our aim is to develop a clinically viable, fast‐acquisition, prostate MR elastography (MRE) system with transperineal excitation. We developed a new actively shielded electromagnetic transducer, designed to enable quick deployment and positioning within the scanner. The shielding of the transducer was optimized using simulations. We also employed a new rapid pulse sequence that encodes the three‐dimensional displacement field in the prostate gland using a fractionally encoded steady‐state gradient echo sequence, thereby shortening the acquisition time to a clinically acceptable 8–10 min. The methods were tested in two phantoms and seven human subjects (six volunteers and one patient with prostate cancer). The MRE acquisition time for 24 slices, with an isotropic resolution of 2 mm and eight phase offsets, was 8 min, and the total scan, including positioning and set‐up, was performed in 15–20 min. The phantom study demonstrated that the transducer does not interfere with the acquisition process and that it generates displacement amplitudes that exceed 100 µm even at frequencies as high as 300 Hz. In the in vivo human study, average wave amplitudes of 30 µm (46 µm at the apex) were routinely achieved within the prostate gland at 70 Hz. No pain or discomfort was reported. Results in a single patient suggest that MRE can identify cancer tumors, although this result is preliminary. The proposed methods allow the integration of prostate MRE with other multiparametric MRI methods. The results of this study clearly motivate the clinical evaluation of transperineal MRE in patients. Copyright © 2014 John Wiley & Sons, Ltd.     

Three-dimensional Elastic Image Registration Based on Strain Energy Minimization: Application to Prostate Magnetic Resonance Imaging

The use of magnetic resonance (MR) imaging in conjunction with an endorectal coil is currently the clinical standard for the diagnosis of prostate cancer because of the increased sensitivity and specificity of this approach. However, imaging in this manner provides images and spectra of the prostate in the deformed state because of the insertion of the endorectal coil. Such deformation may lead to uncertainties in the localization of prostate cancer during therapy. We propose a novel 3-D elastic registration procedure that is based on the minimization of a physically motivated strain energy function that requires the identification of similar features (points, curves, or surfaces) in the source and target images. The Gauss–Seidel method was used in the numerical implementation of the registration algorithm. The registration procedure was validated on synthetic digital images, MR images from prostate phantom, and MR images obtained on patients. The registration error, assessed by averaging the displacement of a fiducial landmark in the target to its corresponding point in the registered image, was 0.2 ± 0.1 pixels on synthetic images. On the prostate phantom and patient data, the registration errors were 1.0 ± 0.6 pixels (0.6 ± 0.4 mm) and 1.8 ± 0.7 pixels (1.1 ± 0.4 mm), respectively. Registration also improved image similarity (normalized cross-correlation) from 0.72 ± 0.10 to 0.96 ± 0.03 on patient data. Registration results on digital images, phantom, and prostate data in vivo demonstrate that the registration procedure can be used to significantly improve both the accuracy of localized therapies such as brachytherapy or external beam therapy and can be valuable in the longitudinal follow-up of patients after therapy.     

Phantom validation of coregistration of PET and CT for image-guided radiotherapy

Radiotherapy treatment planning integrating positron emission tomography (PET) and computerized tomography (CT) is rapidly gaining acceptance in the clinical setting. Although hybrid systems are available, often the planning CT is acquired on a dedicated system separate from the PET scanner. A limiting factor to using PET data becomes the accuracy of the CT/PET registration. In this work, we use phantom and patient validation to demonstrate a general method for assessing the accuracy of CT/PET image registration and apply it to two multi-modality image registration programs. An IAEA (International Atomic Energy Association) brain phantom and an anthropomorphic head phantom were used. Internal volumes and externally mounted fiducial markers were filled with CT contrast and 18F-fluorodeoxyglucose (FDG). CT, PET emission, and PET transmission images were acquired and registered using two different image registration algorithms. CT/PET Fusion (GE Medical Systems, Milwaukee, WI) is commercially available and uses a semi-automated initial step followed by manual adjustment. Automatic Mutual Information-based Registration (AMIR), developed at our institution, is fully automated and exhibits no variation between repeated registrations. Registration was performed using distinct phantom structures; assessment of accuracy was determined from registration of the calculated centroids of a set of fiducial markers. By comparing structure-based registration with fiducial-based registration, target registration error (TRE) was computed at each point in a three-dimensional (3D) grid that spans the image volume. Identical methods were also applied to patient data to assess CT/PET registration accuracy. Accuracy was calculated as the mean with standard deviation of the TRE for every point in the 3D grid. Overall TRE values for the IAEA brain phantom are: CT/PET Fusion = 1.71 +/- 0.62 mm, AMIR = 1.13 +/- 0.53 mm; overall TRE values for the anthropomorphic head phantom are: CT/PET Fusion = 1.66 +/- 0.53 mm, AMIR = 1.15 +/- 0.48 mm. Precision (repeatability by a single user) measured for CT/PET Fusion: IAEA phantom = 1.59 +/- 0.67 mm and anthropomorphic head phantom = 1.63 +/- 0.52 mm. (AMIR has exact precision and so no measurements are necessary.) One sample patient demonstrated the following accuracy results: CT/PET Fusion = 3.89 +/- 1.61 mm, AMIR = 2.86 +/- 0.60 mm. Semi-automatic and automatic image registration methods may be used to facilitate incorporation of PET data into radiotherapy treatment planning in relatively rigid anatomic sites, such as head and neck. The overall accuracies in phantom and patient images are < 2 mm and < 4 mm, respectively, using either registration algorithm. Registration accuracy may decrease, however, as distance from the initial registration points (CT/PET fusion) or center of the image (AMIR) increases. Additional information provided by PET may improve dose coverage to active tumor subregions and hence tumor control. This study shows that the accuracy obtained by image registration with these two methods is well suited for image-guided radiotherapy.     

Evaluation of deformable image registration and a motion model in CT images with limited features

Deformable image registration (DIR) is increasingly used in radiotherapy applications and provides the basis for a previously described model of patient-specific respiratory motion. We examine the accuracy of a DIR algorithm and a motion model with respiration-correlated CT (RCCT) images of software phantom with known displacement fields, physical deformable abdominal phantom with implanted fiducials in the liver and small liver structures in patient images. The motion model is derived from a principal component analysis that relates volumetric deformations with the motion of the diaphragm or fiducials in the RCCT. Patient data analysis compares DIR with rigid registration as ground truth: the mean ± standard deviation 3D discrepancy of liver structure centroid positions is 2.0 ± 2.2 mm. DIR discrepancy in the software phantom is 3.8 ± 2.0 mm in lung and 3.7 ± 1.8 mm in abdomen; discrepancies near the chest wall are larger than indicated by image feature matching. Marker's 3D discrepancy in the physical phantom is 3.6 ± 2.8 mm. The results indicate that visible features in the images are important for guiding the DIR algorithm. Motion model accuracy is comparable to DIR, indicating that two principal components are sufficient to describe DIR-derived deformation in these datasets.     

A dual modality phantom for cone beam CT and ultrasound image fusion in prostate implant

In transrectal ultrasound (TRUS) guided prostate seed brachytherapy, TRUS provides good delineation of the prostate while x-ray imaging, e.g., C-arm, gives excellent contrast for seed localization. With the recent availability of cone beam CT (CBCT) technology, the combination of the two imaging modalities may provide an ideal system for intraoperative dosimetric feedback during implantation. A dual modality phantom made of acrylic and copper wire was designed to measure the accuracy and precision of image coregistration between a C-arm based CBCT and 3D TRUS. The phantom was scanned with TRUS and CBCT under the same setup condition. Successive parallel transverse ultrasound (US) images were acquired through manual stepping of the US probe across the phantom at an increment of 1 mm over 7.5 cm. The CBCT imaging was done with three reconstructed slice thicknesses (0.4, 0.8, and 1.6 mm) as well as at three different tilt angles (0 degrees, 15 degrees, 30 degrees), and the coregistration between CBCT and US images was done using the Variseed system based on four fiducial markers. Fiducial localization error (FLE), fiducial registration error (FRE), and target registration error (TRE) were calculated for all registered image sets. Results showed that FLE were typically less than 0.4 mm, FRE were less than 0.5 mm, and TRE were typically less than 1 mm within the range of operation for prostate implant (i.e., < 6 cm to surface of US probe). An analysis of variance test showed no significant difference in TRE for the CBCT-US fusion among the three slice thicknesses (p = 0.37). As a comparison, the experiment was repeated with a US-conventional CT scanner combination. No significant difference in TRE was noted between the US-conventional CT fusion and that for all three CBCT image slice thicknesses (p = 0.21). CBCT imaging was also performed at three different C-arm tilt angles of 0 degrees, 15 degrees and 30 degrees and reconstructed at a slice thickness of 0.8 mm. There is no significant difference in TRE between 0 degrees and 15 degrees (p = 0.191) as well as between 0 degrees and 30 degrees (p = 0.275), which suggests that the C-arm may be tilted intraoperatively to acquire CBCT images without compromising the quality of image fusion. The results conclude a high degree of accuracy and precision for the CBCT-TRUS fusion, which could be useful toward achieving real time intraoperative dosimetry in prostate brachytherapy.     

Automated 2D-3D registration of portal images and CT data using line-segment enhancement

In prostate radiotherapy, setup errors with respect to the patient's bony anatomy can be reduced by aligning 2D megavoltage (MV) portal images acquired during treatment to a reference 3D kilovoltage (kV) CT acquired for treatment planning purposes. The purpose of this study was to evaluate a fully automated 2D-3D registration algorithm to quantify setup errors in 3D through the alignment of line-enhanced portal images and digitally reconstructed radiographs computed from the CT. The line-enhanced images were obtained by correlating the images with a filter bank of short line segments, or "sticks" at different orientations. The proposed methods were validated on (1) accurately collected gold-standard data consisting of a 3D kV cone-beam CT scan of an anthropomorphic phantom of the pelvis and 2D MV portal images in the anterior-posterior (AP) view acquired at 15 different poses and (2) a conventional 3D kV CT scan and weekly 2D MV AP portal images of a patient over 8 weeks. The mean (and standard deviation) of the absolute registration error for rotations around the right-lateral (RL), inferior-superior (IS), and posterior-anterior (PA) axes were 0.212 degree (0.214 degree), 0.055 degree (0.033 degree) and 0.041 degree (0.039 degree), respectively. The corresponding registration errors for translations along the RL, IS, and PA axes were 0.161 (0.131) mm, 0.096 (0.033) mm, and 0.612 (0.485) mm. The mean (and standard deviation) of the total registration error was 0.778 (0.543) mm. Registration on the patient images was successful in all eight cases as determined visually. The results indicate that it is feasible to automatically enhance features in MV portal images of the pelvis for use within a completely automated 2D-3D registration framework for the accurate determination of patient setup errors. They also indicate that it is feasible to estimate all six transformation parameters from a 3D CT of the pelvis and a single portal image in the AP view.     

Novel image registration quality evaluator (RQE) with an implementation for automated patient positioning in cranial radiation therapy

In external beam radiation therapy, digitally reconstructed radiographs (DRRs) and portal images are used to verify patient setup based either on a visual comparison or, less frequently, with automated registration algorithms. A registration algorithm can be trapped in local optima due to irregularity of patient anatomy, image noise and artifacts, and/or out-of-plane shifts, resulting in an incorrect solution. Thus, human observation, which is subjective, is still required to check the registration result. We propose to use a novel image registration quality evaluator (RQE) to automatically identify misregistrations as part of an algorithm-based decision-making process for verification of patient positioning. A RQE, based on an adaptive pattern classifier, is generated from a pair of reference and target images to determine the acceptability of a registration solution given an optimization process. Here we applied our RQE to patient positioning for cranial radiation therapy. We constructed two RQEs-one for the evaluation of intramodal registrations (i.e., portal-portal); the other for intermodal registrations (i.e., portal-DRR). Mutual information, because of its high discriminatory ability compared with other measures (i.e., correlation coefficient and partitioned intensity uniformity), was chosen as the test function for both RQEs. We adopted 1 mm translation and 1 degree rotation as the maximal acceptable registration errors, reflecting desirable clinical setup tolerances for cranial radiation therapy. Receiver operating characteristic analysis was used to evaluate the performance of the RQE, including computations of sensitivity and specificity. The RQEs showed very good performance for both intramodal and intermodal registrations using simulated and phantom data. The sensitivity and the specificity were 0.973 and 0.936, respectively, for the intramodal RQE using phantom data. Whereas the sensitivity and the specificity were 0.961 and 0.758, respectively, for the intermodal RQE using phantom data. Phantom experiments also indicated our RQEs detected out-of-plane deviations exceeding 2.5 mm and 2.50. A preliminary retrospective clinical study of the RQE on cranial portal imaging also yielded good sensitivity > or = 0.857) and specificity (> or = 0.987). Clinical implementation of a RQE could potentially reduce the involvement of the human observer for routine patient positioning verification, while increasing setup accuracy and reducing setup verification time.     

头部立体放射治疗中两种固定方式的精度比较

目的:比较双面网和单面网两种固定方式对头部立体定向放射治疗病例摆位精度的影响。方法:选取40例头部立体定向放射治疗患者,分为对照组（传统单面网固定）和试验组（新型双面网固定）。获取患者治疗前锥形束CT图像,记录按照骨性标志配准误差并进行统计学分析。结果:两组摆位误差在左右（Lat）、进出（Lng）、升降（Vrt）、俯仰（Pitch）、翻转（Roll）、旋转（Rtn）各方向平均数±标准差表示为:对照组（0.26±0.15） cm、（0.13±0.10） cm、（0.19±0.13） cm、（1.40±0.75）°、（1.31±0.65）°、（1.00±0.60）°;试验组（0.07±0.08） cm、（0.14±0.13） cm、（0.09±0.09） cm、（0.73±0.62）°、（0.72±0.58）°、（0.66±0.52）°。两组数据使用曼恩-惠特尼U检验,Lat、Vrt、Pitch、Roll、Rtn方向有统计学差异（P<0.05）,Lng方向无统计学差异（P>0.05）。结论:相对于单面网,双面网固定方式在头部立体定向放射治疗中减小了患者的摆位误差,提高了治疗精度,可使患者获益。 【关键词】立体定向放射治疗;摆位误差;单面网;双面网     

Simulation of the artefact of an iodine seed placed at the needle tip in MRI-guided prostate brachytherapy

The purpose of this research is to study the influence of different needle materials on the artefact of a prostate brachytherapy iodine seed, placed at the needle tip, in MRI (magnetic resonance imaging)-guided prostate brachytherapy. For this research simulations were performed. The simulations showed that with the currently available MRI compatible titanium needles, determination of the exact seed position is difficult, because of the large artefact at the needle tip. This hampers accurate MRI-guided seed delivery. When a plastic needle is used, the image disturbance is caused by the artefact of the iodine seed alone. When a gradient echo sequence is used, the middle of the seed artefact corresponds well with to middle of the real seed position. With the scan parameters we used this deviation was less than 0.4 mm compared to 1.5 mm when a titanium needle is used.     

Automatic registration of the prostate for computed-tomography-guided radiotherapy

The recent development of integrated computed tomography (CT)/linear accelerator (LINAC) combinations, where the CT scanner and the LINAC use the same patient couch, and of kilovoltage cone-beam CT systems attached to the LINAC gantry, means that suitable hardware is now available for CT-guided localization of the prostate. Clinical implementation is, however, currently impeded by the lack of robust and accurate software tools to compare the position of the prostate in the CT images used for the treatment plan with its position in the daily CT images. Manual registration of the planning CT images with the daily CT images can be slow and can introduce significant inter-user variations. We have developed an automatic registration technique that is not adversely influenced by changes in prostate shape, size or orientation, presence of rectal gas, or bladder filling. The cost function used in the registration is the mean absolute difference in CT numbers voxel-by-voxel between the daily CT image and the planning CT image for a volume extracted from the planning CT images using the original physician-drawn gross tumor volume contours. To enhance soft tissue contrast in the prostate region and to reduce the impact of rectal gas calcifications and bone on the registration, voxels with CT numbers that represent gas or bone are filtered out from the calculation. The results of the automatic registration agreed with the mean results of seven human observers, with standard deviations of 0.5 mm, 0.5 mm, and 1.0 mm in the left/right (RL), anterior/posterior (AP), and superior/inferior (SI) directions, respectively, for a patient that was relatively easy to localize. Agreement (one standard deviation) for a patient that was difficult to localize was 0.6 mm, 1.4 mm, and 1.9 mm in the RL, AP, and SI directions, respectively. These results are better than the interuser uncertainties reported for a manual alignment technique and are close to the reported intrauser uncertainties. The results are independent of the shape of contours in the original treatment plan, reducing the impact of interobserver variations in contouring the prostate. The algorithm is fast and reliable, allowing the entire CT localization process to take place in 5-9 minutes. In 120 CT image sets from seven patients, the failure rate was found to be less than 1%. The use of this algorithm will facilitate the clinical implementation of CT-guided localization of the prostate.     

3D interfractional patient position verification using 2D-3D registration of orthogonal images

Reproducible positioning of the patient during fractionated external beam radiation therapy is imperative to ensure that the delivered dose distribution matches the planned one. In this paper, we expand on a 2D-3D image registration method to verify a patient's setup in three dimensions (rotations and translations) using orthogonal portal images and megavoltage digitally reconstructed radiographs (MDRRs) derived from CT data. The accuracy of 2D-3D registration was improved by employing additional image preprocessing steps and a parabolic fit to interpolate the parameter space of the cost function utilized for registration. Using a humanoid phantom, precision for registration of three-dimensional translations was found to be better than 0.5 mm (1 s.d.) for any axis when no rotations were present. Three-dimensional rotations about any axis were registered with a precision of better than 0.2 degrees (1 s.d.) when no translations were present. Combined rotations and translations of up to 4 degrees and 15 mm were registered with 0.4 degrees and 0.7 mm accuracy for each axis. The influence of setup translations on registration of rotations and vice versa was also investigated and mostly agrees with a simple geometric model. Additionally, the dependence of registration accuracy on three cost functions, angular spacing between MDRRs, pixel size, and field-of-view, was examined. Best results were achieved by mutual information using 0.5 degrees angular spacing and a 10 x 10 cm2 field-of-view with 140 x 140 pixels. Approximating patient motion as rigid transformation, the registration method is applied to two treatment plans and the patients' setup errors are determined. Their magnitude was found to be < or = 6.1 mm and < or = 2.7 degrees for any axis in all of the six fractions measured for each treatment plan.     

Automatic registration of megavoltage to kilovoltage CT images in helical tomotherapy: an evaluation of the setup verification process for the special case of a rigid head phantom

Precise daily target localization is necessary to achieve highly conformal radiation delivery. In helical tomotherapy, setup verification may be accomplished just prior to delivering each fraction by acquiring a megavoltage CT scan of the patient in the treatment position. This daily image set may be manually or automatically registered to the image set on which the treatment plan was calculated, in order to determine any needed adjustments. The system was tested by acquiring 104 MVCT scans of an anthropomorphic head phantom to which translational displacements had been introduced with respect to the planning image set. Registration results were compared against an independent, optically guided positioning system. The total experimental uncertainty was within approximately 1 mm. Although the registration of phantom images is not fully analogous to the registration of patient images, this study confirms that the system is capable of phantom localization with sub-voxel accuracy. In seven registration problems considered, expert human observers were able to perform manual registrations with comparable or inferior accuracy to automatic registration by mutual information. The time to compute an automatic registration is considerably shorter than the time required for manual registration. However, human evaluation of automatic results is necessary in order to identify occasional outliers, and to ensure that the registration is clinically acceptable, especially in the case of deformable patient anatomy.     

光学表面监测系统引导实现左侧乳腺癌深吸气屏气治疗临床应用及评估

目的:通过分析摆位精度、摆位时间和心脏位置评估以光学表面监测系统（OSMS）引导实现左侧乳腺癌深吸气屏气（DIBH）治疗的临床价值。方法:30例左侧乳腺癌保乳术后患者,运用OSMS的“Move Couch”自动摆位功能,以OSMS引导摆位、DIBH和治疗监控,实现DIBH技术治疗。分析CBCT配准靶区六维绝对误差数据和心脏位置的误差数据,记录摆位时间。结果:绝对摆位误差在x、y、z平移方向和Rx、Ry、Rz旋转方向分别为（0.11±0.08）、（0.14±0.11）、（0.13±0.10） cm和（0.79±0.66）、（0.69±0.57）、（0.73±0.64）°。心脏位置在x、y、z方向平移误差分别为（0.01±0.30）、（0.05±0.34）、（0.01±0.09） cm。摆位时间为（4.1±1.2） min。结论:左侧乳腺癌DIBH放疗技术可将心脏向下、后方推移,远离放疗靶区,减少心脏受量。基于OSMS实施左侧乳腺癌DIBH治疗实现了较好的靶区和心脏位置准确性,OSMS的自动摆位功能可帮助提高摆位精度,减少摆位时间。     

A fast, accurate, and automatic 2D-3D image registration for image-guided cranial radiosurgery

The authors developed a fast and accurate two-dimensional (2D)-three-dimensional (3D) image registration method to perform precise initial patient setup and frequent detection and correction for patient movement during image-guided cranial radiosurgery treatment. In this method, an approximate geometric relationship is first established to decompose a 3D rigid transformation in the 3D patient coordinate into in-plane transformations and out-of-plane rotations in two orthogonal 2D projections. Digitally reconstructed radiographs are generated offline from a preoperative computed tomography volume prior to treatment and used as the reference for patient position. A multiphase framework is designed to register the digitally reconstructed radiographs with the x-ray images periodically acquired during patient setup and treatment. The registration in each projection is performed independently; the results in the two projections are then combined and converted to a 3D rigid transformation by 2D-3D geometric backprojection. The in-plane transformation and the out-of-plane rotation are estimated using different search methods, including multiresolution matching, steepest descent minimization, and one-dimensional search. Two similarity measures, optimized pattern intensity and sum of squared difference, are applied at different registration phases to optimize accuracy and computation speed. Various experiments on an anthropomorphic head-and-neck phantom showed that, using fiducial registration as a gold standard, the registration errors were 0.33 +/- 0.16 mm (s.d.) in overall translation and 0.29 degrees +/- 0.11 degrees (s.d.) in overall rotation. The total targeting errors were 0.34 +/- 0.16 mm (s.d.), 0.40 +/- 0.2 mm (s.d.), and 0.51 +/- 0.26 mm (s.d.) for the targets at the distances of 2, 6, and 10 cm from the rotation center, respectively. The computation time was less than 3 s on a computer with an Intel Pentium 3.0 GHz dual processor.     

Patient position verification using CT images.

The use of ions in the radiotherapy of cancer patients requires an accurate patient positioning in order to exploit its potential benefits. Using CT images as the basis for the setup verification offers the advantage of a high in-plane resolution in combination with a geometrically accurate, volumetric information. Before each fraction a single CT slice is acquired at the isocenter level after the positioning procedure. This single slice is registered to the planning CT cube using automated image registration algorithms. Thus any erreonous translation or rotation can be detected and quantified. The registration process involves the interpolation of the volumetric data, the calculation of an energy function, and the minimization of this energy function. Several data interpolation functions as well as minimization algorithms were compared. CT studies with a head phantom were performed in which defined translations and rotations were simulated by moving a motor-driven treatment chair. Different slice thicknesses and anatomical sites were studied to investigate their potential influence on the registration accuracy. The accuracy of the registration was found to be a fraction of a voxel size for suitable combinations of algorithms (typically better than 0.16 mm/deg). A significant dependancy of the registration accuracy on the CT slice thickness and the anatomical site was found (the accuracy ranges from 0.05 mm/deg to 0.16 mm/deg depending on the site). The calculation time is dependant on the used algorithms and the magnitude of the setup error. For the standard combination of algorithms as proposed by the authors (Downhill Simplex minimization with Trilinear interpolation) the typical calculation time is about 20 s for a Sun UltraSPARC processor. Taking into account the mechanical accuracy of the setup device (motor-driven chair) the registration of CT images is thus a useful tool for detecting and quantifying any significant error in the patient position.     

Accuracy and feasibility of cone-beam computed tomography for stereotactic radiosurgery setup

Image fusion, target localization, and setup accuracy of cone-beam computed tomography (CBCT) for stereotactic radiosurgery (SRS) were investigated in this study. A Rando head phantom rigidly attached to a stereotactic Brown-Roberts-Wells (BRW) frame was utilized to study the geometric accuracy of CBCT. Measurements of distances and angular separations between selected pairs of multiple radio-opaque targets embedded in the head phantom from a conventional simulation CT provided comparative data for geometric accuracy analysis. Localization accuracy of the CBCT scan was investigated from an analysis of BRW localization of four cylindrical objects (9 mm in diameter and 25 mm in length) independently computed from CBCT and conventional CT scans. Image fusion accuracy was quantitatively evaluated from BRW localization of multiple simulated targets from the CBCT and conventional CT scan. Finally, a CBCT setup procedure for stereotactic radiosurgery treatments was proposed and its accuracy was assessed using orthogonal target verification imaging. Our study showed that CBCT did not present any significant geometric distortions. Stereotactic coordinates of the four cylindrical objects as determined from the CBCT differed from those determined from the conventional CT on average by 0.30 mm with a standard deviation (SD) of 0.09 mm. The mean image registration accuracy of CBCT with conventional CT was 0.28 mm (SD = 0.10 mm). Setup uncertainty of our proposed CBCT setup procedure was on the same order as the conventional framed-based stereotactic systems reported in the literature (mean = 1.34 mm, SD = 0.33 mm). In conclusion, CBCT can be used to guide SRS treatment setup with accuracy comparable to the currently used frame-based stereotactic radiosurgery systems provided that intra-treatment patient motion is prevented.     

Automated 2D-3D registration of a radiograph and a cone beam CT using line-segment enhancement

The objective of this study was to develop a fully automated two-dimensional (2D)-three-dimensional (3D) registration framework to quantify setup deviations in prostate radiation therapy from cone beam CT (CBCT) data and a single AP radiograph. A kilovoltage CBCT image and kilovoltage AP radiograph of an anthropomorphic phantom of the pelvis were acquired at 14 accurately known positions. The shifts in the phantom position were subsequently estimated by registering digitally reconstructed radiographs (DRRs) from the 3D CBCT scan to the AP radiographs through the correlation of enhanced linear image features mainly representing bony ridges. Linear features were enhanced by filtering the images with "sticks," short line segments which are varied in orientation to achieve the maximum projection value at every pixel in the image. The mean (and standard deviations) of the absolute errors in estimating translations along the three orthogonal axes in millimeters were 0.134 (0.096) AP(out-of-plane), 0.021 (0.023) ML and 0.020 (0.020) SI. The corresponding errors for rotations in degrees were 0.011 (0.009) AP, 0.029 (0.016) ML (out-of-plane), and 0.030 (0.028) SI (out-of-plane). Preliminary results with megavoltage patient data have also been reported. The results suggest that it may be possible to enhance anatomic features that are common to DRRs from a CBCT image and a single AP radiography of the pelvis for use in a completely automated and accurate 2D-3D registration framework for setup verification in prostate radiotherapy. This technique is theoretically applicable to other rigid bony structures such as the cranial vault or skull base and piecewise rigid structures such as the spine.     

Validation of an accelerated 'demons' algorithm for deformable image registration in radiation therapy

A greyscale-based fully automatic deformable image registration algorithm, originally known as the 'demons' algorithm, was implemented for CT image-guided radiotherapy. We accelerated the algorithm by introducing an 'active force' along with an adaptive force strength adjustment during the iterative process. These improvements led to a 40% speed improvement over the original algorithm and a high tolerance of large organ deformations. We used three methods to evaluate the accuracy of the algorithm. First, we created a set of mathematical transformations for a series of patient's CT images. This provides a 'ground truth' solution for quantitatively validating the deformable image registration algorithm. Second, we used a physically deformable pelvic phantom, which can measure deformed objects under different conditions. The results of these two tests allowed us to quantify the accuracy of the deformable registration. Validation results showed that more than 96% of the voxels were within 2 mm of their intended shifts for a prostate and a head-and-neck patient case. The mean errors and standard deviations were 0.5 mm+/-1.5 mm and 0.2 mm+/-0.6 mm, respectively. Using the deformable pelvis phantom, the result showed a tracking accuracy of better than 1.5 mm for 23 seeds implanted in a phantom prostate that was deformed by inflation of a rectal balloon. Third, physician-drawn contours outlining the tumour volumes and certain anatomical structures in the original CT images were deformed along with the CT images acquired during subsequent treatments or during a different respiratory phase for a lung cancer case. Visual inspection of the positions and shapes of these deformed contours agreed well with human judgment. Together, these results suggest that the accelerated demons algorithm has significant potential for delineating and tracking doses in targets and critical structures during CT-guided radiotherapy.