Evaluation of mechanical precision and alignment uncertainties for an integrated CT/LINAC system

A new integrated CT/LINAC combination, in which the CT scanner is inside the radiation therapy treatment room and the same patient couch is used for CT scanning and treatment (after a 180-degree couch rotation), should allow for accurate correction of interfractional setup errors. The purpose of this study was to evaluate the sources of uncertainties, and to measure the overall precision of this system. The following sources of uncertainty were identified: (1) the patient couch position on the LINAC side after a rotation, (2) the patient couch position on the CT side after a rotation, (3) the patient couch position as indicated by its digital readout, (4) the difference in couch sag between the CT and LINAC positions, (5) the precision of the CT coordinates, (6) the identification of fiducial markers from CT images, (7) the alignment of contours with structures in the CT images, and (8) the alignment with setup lasers. The largest single uncertainties (one standard deviation or 1 SD) were found in couch position on the CT side after a rotation (0.5 mm in the RL direction) and the alignment of contours with the CT images (0.4 mm in the SI direction). All other sources of uncertainty are less than 0.3 mm (1 SD). The overall precision of two setup protocols was investigated in a controlled phantom study. A protocol that relies heavily on the mechanical integrity of the system, and assumes a fixed relationship between the LINAC isocenter and the CT images, gave a predicted precision (1 SD) of 0.6, 0.7, and 0.6 mm in the SI, RL and AP directions, respectively. The second protocol reduces reliance on the mechanical precision of the total system, particularly the patient couch, by using radio-opaque fiducial markers to transfer the isocenter information from the LINAC side to the CT images. This protocol gave a slightly improved predicted precision of 0.5, 0.4, and 0.4 mm in the SI, RL and AP directions, respectively. The distribution of phantom position after CT-based correction confirmed these results. Knowledge of the individual sources of uncertainty will allow alternative setup protocols to be evaluated in the future without the need for significant additional measurements.     

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.     

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.     

应用锥形束CT研究儿童神经母细胞瘤放射治疗的摆位误差

目的：应用锥形束CT（CBCT）研究儿童腹部神经母细胞瘤放射治疗分次间（Interfraction）和分次内（Intrafraction）的摆位误差,探讨临床靶区（CTV）到计划靶区（PTV）的外放边界,为临床治疗计划的设计提供参考。方法：选取于2012年10月到2013年5月共10例接受放射治疗的儿童腹部神经母细胞瘤患者,所有患儿分别于治疗前以及治疗结束后进行CBCT扫描,CBCT扫描图像与计划CT图像进行配准,记录左右方向（Medial-Lateral,ML）,头脚方向（Superior-inferior,SI）以及胸背方向误差（Anterior-Posterior,AP）,从而得到分次间和分次内的摆位误差。结果：若按照每周一次图像验证,则摆位误差为：左右方向5.3mm,头脚方向5.7mm,胸背方向5.2mm。若按照每日CBCT图像验证,这种情况下的摆位误差仅为：左右方向2.1 mm,头脚方向1.7 mm,胸背方向1.4 mm。结论：每日CBCT图像扫描可以有效减少儿童神经母细胞瘤的摆位误差,缩小CTV到PTV的外放边界,减少正常组织的受照范围。正常组织受照范围的减少对患者特别是儿童患者有很大意义。在确定CTV到PTV的外放边界时,内边界（InternalMargin）的大小还需要进一步讨论。     

How does CT image noise affect 3D deformable image registration for image-guided radiotherapy planning?

PURPOSE: To measure the sensitivity of deformable image registration to image noise. Deformable image registration can be used to map organ contours and other treatment planning data from one CT to another. These CT studies can be acquired with either conventional fan-beam CT systems or more novel cone-beam CT techniques. However, cone-beam CT images can have higher noise levels than fan-beam CT, which might reduce registration accuracy. We have investigated the effect of image quality differences on the deformable registration of fan-beam CTs and CTs with simulated cone-beam noise. METHOD: Our study used three CT studies for each of five prostate patients. Each CT was contoured by three experienced radiation oncologists. For each patient, one CT was designated the source image and the other two were target images. A deformable image registration process was used to register each source CT to each target CT and then transfer the manually drawn treatment planning contours from the source CT to the target CTs. The accuracy of the automatically transferred contours (and thus of the deformable registration process) was assessed by comparing them to the manual contours on the target CTs, with the differences evaluated with respect to interobserver variability in the manual contours. Then each of the target CTs was modified to include increased noise characteristic of cone-beam CT and the tests were repeated. Changes in registration accuracy due to increased noise were detected by monitoring changes in the automatically transferred contours. RESULTS: We found that the additional noise caused no significant loss of registration accuracy at magnitudes that exceeded what would normally be found in an actual cone-beam CT. SUMMARY: We conclude that noise levels in cone-beam CTs that might reduce manual contouring accuracy do not reduce image registration and automatic contouring accuracy.     

A method to compare supra-pubic ultrasound and CT images of the prostate: technique and early clinical results

We describe a unique method that allows the comparison of spatially registered ultrasound (SRUS) images and computed tomography-derived contours (CTDCs) that were acquired with a minimal time lapse. As such, we have a tool that will provide validation of the spatial accuracy of the US system and that will allow comparison of anatomical boundaries derived via the two different imaging modalities. We describe the method by which the commercial US system is mechanically registered to a CT simulator and a unique data processing procedure. This data processing procedure circumvents the standard data acquisition and manual contouring sequence, thus reducing the time lapse from CT to US image acquisition to 10 minutes on average. Verification using a phantom demonstrated the method to be spatially accurate to within +/- 1 mm in the anterior-posterior (AP) and lateral directions and +/- 3 mm in the inferior-superior (IS) direction. Early clinical results gathered on 8 patients demonstrated alignment between the US and the CTDCs to be 0 mm in the AP and lateral directions and 2 mm in the IS direction, on average. The technique was used to compare the appearance of the prostate using US and CT imaging. The lateral dimension of the prostate indicated by the CTDCs was larger than that indicated by US imaging in all cases and on average by 0.9 cm. The height of the prostate in the AP direction was larger on average by 0.3 cm using CTDCs than US, and was larger by 5 mm or more in 3 out of 7 cases. The role of uncertainties in the determination of the CTDCs is examined as a possible cause and implications for treatment planning are described.     

A deformable image registration method to handle distended rectums in prostate cancer radiotherapy

In image-guided adaptive radiotherapy, it is important to have the capability to automatically and accurately delineate the rectal wall, which is a major dose-limiting organ in prostate cancer radiotherapy. As image registration is a process to find the spatial correspondence between two images, a major challenge in intensity-based deformable image registration is to deal with the situation where no correspondence exists for some objects between the two images to be registered. One example is the variation of rectal contents due to the presence and absence of bowel gas. The intensity-based deformable image registration methods alone cannot create the correct spatial transformation if there is no correspondence between the source and target images. In this study we implemented an automatic image intensity modification procedure to create artificial gas pockets in the planning computed tomography (CT) images. A diffusion-based deformable image registration algorithm was developed to use an adaptive smoothing algorithm to better handle large organ deformations. The process was tested in 15 prostate cancer cases and 30 daily CT images containing the largest distended rectums. The manually delineated rectums agreed well with the autodelineated rectums when using the image-intensity modification procedure.     

Comparison of mega-voltage cone-beam computed tomography prostate localization with online ultrasound and fiducial markers methods

The online image-guided localization data from 696 ultrasound (US), 598 mega-voltage cone-beam computed tomography (MV-CBCT), and 393 seed markers (SMs) couch alignments for patients undergoing intensity modulation radiotherapy of the prostate were analyzed. Daily US, MV-CBCT and SM images were acquired for 19, 17 and 12 patients, respectively, after each patient was immobilized in a vacuum cradle and setup to skin markers as the center of mass. The couch shifts applied in the lateral (left-right/LR), vertical (anterior-posterior/AP), and longitudinal (superior-inferior/SI) directions, along with the magnitude of the three-dimensional (3D) shift vector, were analyzed and compared for all three methods. The percentage of shifts larger than 5 mm in all directions was also compared. Clinical target volume-planning target volume (CTV-to-PTV) expansion margins were estimated based on the localization data with US, CB, and SM image guidance. Results show the US data have greater variability. Systematic and random shifts were -1.2 +/- 6.8 mm (LR), -2.8 +/- 5.1 mm (SI) and -1.0 +/- 5.9 mm (AP) for US, 1.0 +/- 3.9 mm (LR), -1.3 +/- 2.5 mm (SI) and -0.3 +/- 3.9 mm (AP) for CB, and -1.0 +/- 3.4 mm (LR), 0.0 +/- 3.4 mm (SI) and 0.5 +/- 4.1 mm (AP) for SM. The mean 3D shift distance was larger using US (8.8 +/- 6.2 mm) compared to CB and SM (5.3 +/- 3.4 mm and 5.2 +/- 3.7 mm, respectively). The percentage of US shifts larger than 5 mm were 34%, 31%, and 38% in the LR, SI, and AP directions, respectively, compared to 18%, 6%, and 16% for CB and 14%, 10%, and 20% for SM. MV-CBCT and SM localization data suggest a different distribution of prostate center-of-mass shifts with smaller variability, compared to US. The online MV-CBCT and SM image-guidance data show that for treatments that do not include daily prostate localization, one can use a CTV-to-PTV margin that is 4 mm smaller than the one suggested by US data, hence allowing more rectum and bladder sparing and potentially improving the therapeutic ratio.     

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.     

A frequency-based approach to locate common structure for 2D-3D intensity-based registration of setup images in prostate radiotherapy

In many radiotherapy clinics, geometric uncertainties in the delivery of 3D conformal radiation therapy and intensity modulated radiation therapy of the prostate are reduced by aligning the patient's bony anatomy in the planning 3D CT to corresponding bony anatomy in 2D portal images acquired before every treatment fraction. In this paper, we seek to determine if there is a frequency band within the portal images and the digitally reconstructed radiographs (DRRs) of the planning CT in which bony anatomy predominates over non-bony anatomy such that portal images and DRRs can be suitably filtered to achieve high registration accuracy in an automated 2D-3D single portal intensity-based registration framework. Two similarity measures, mutual information and the Pearson correlation coefficient were tested on carefully collected gold-standard data consisting of a kilovoltage cone-beam CT (CBCT) and megavoltage portal images in the anterior-posterior (AP) view of an anthropomorphic phantom acquired under clinical conditions at known poses, and on patient data. It was found that filtering the portal images and DRRs during the registration considerably improved registration performance. Without filtering, the registration did not always converge while with filtering it always converged to an accurate solution. For the pose-determination experiments conducted on the anthropomorphic phantom with the correlation coefficient, the mean (and standard deviation) of the absolute errors in recovering each of the six transformation parameters were Theta(x):0.18(0.19) degrees, Theta(y):0.04(0.04) degrees, Theta(z):0.04(0.02) degrees, t(x):0.14(0.15) mm, t(y):0.09(0.05) mm, and t(z):0.49(0.40) mm. The mutual information-based registration with filtered images also resulted in similarly small errors. For the patient data, visual inspection of the superimposed registered images showed that they were correctly aligned in all instances. The results presented in this paper suggest that robust and accurate registration can be achieved with intensity-based methods by focusing on rigid bony structures in the images while diminishing the influence of artifacts with similar frequencies as soft tissue.     

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.     

Quantifying the accuracy of automated structure segmentation in 4D CT images using a deformable image registration algorithm

Four-dimensional (4D) radiotherapy is the explicit inclusion of the temporal changes in anatomy during the imaging, planning, and delivery of radiotherapy. One key component of 4D radiotherapy planning is the ability to automatically ("auto") create contours on all of the respiratory phase computed tomography (CT) datasets comprising a 4D CT scan, based on contours manually drawn on one CT image set from one phase. A tool that can be used to automatically propagate manually drawn contours to CT scans of other respiratory phases is deformable image registration. The purpose of the current study was to geometrically quantify the difference between automatically generated contours with manually drawn contours. Four-DCT data sets of 13 patients consisting of ten three-dimensional CT image sets acquired at different respiratory phases were used for this study. Tumor and normal tissue structures [gross tumor volume (GTV), esophagus, right lung, left lung, heart and cord] were manually drawn on each respiratory phase of each patient. Large deformable diffeomorphic image registration was performed to map each CT set from the peak-inhale respiration phase to the CT image sets corresponding with subsequent respiration phases. The calculated displacement vector fields were used to deform contours automatically drawn on the inhale phase to the other respiratory phase CT image sets. The code was interfaced to a treatment planning system to view the resulting images and to obtain the volumetric, displacement, and surface congruence information; 692 automatically generated structures were compared with 692 manually drawn structures. The auto- and manual methods showed similar trends, with a smaller difference observed between the GTVs than other structures. The auto-contoured structures agree with the manually drawn structures, especially in the case of the GTV, to within published interobserver variations. For the GTV, fractional volumes agree to within 0.2+/-0.1, center of mass displacements agree to within 0.5+/-1.5 mm, and agreement of surface congruence is 0.0+/-1.1 mm. The surface congruence between automatic and manual contours for the GTV, heart, left lung, right lung and esophagus was less than 5 mm in 99%, 94%, 94%, 91% and 89%, respectively. Careful assessment of the performance of automatic algorithms is needed in the presence of 4D CT artifacts.     

3DCT联合4DCBCT在中下叶肺癌SABR放疗靶区外放边界中的应用研究

目的:利用四维锥形束CT（4DCBCT）扫描获取放疗靶区摆位误差和呼吸运动误差,计算肿瘤立体定向消融放射治疗（SABR）中计划靶区体积（PTV）外放边界大小。方法:回顾性分析19例中下叶肺癌SABR治疗患者,治疗前4DCBCT扫描,共72次扫描图像。根据4DCBCT与定位CT的配准结果,评估放疗靶区分次间摆位和呼吸运动误差,确定PTV外放边界大小。结果:放疗靶区摆位误差在左右、上下、前后3个方向上分别为（0.11±0.29）、（0.02±0.58）、（0.05±0.26） cm,放疗靶区呼吸运动误差在3个方向上分别为（-0.06±0.34）、（0.09±0.68）、（0.06±0.23） cm,利用ICRU83#报告公式计算PTV外放边界,在3个方向上分别为1.13、2.15、0.90 cm。结论:4DCBCT可有效评估放疗靶区摆位和呼吸运动误差,并确定中下叶肺癌SABR治疗中PTV外放边界大小。利用本方法计算的外放边界比原来RTOG提出的外放标准更加精确,可个体化评估放疗靶区外放边界。     

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.     

Quantification of accuracy of the automated nonlinear image matching and anatomical labeling (ANIMAL) nonlinear registration algorithm for 4D CT images of lung

The performance of the ANIMAL (Automated Nonlinear Image Matching and Anatomical Labeling) nonlinear registration algorithm for registration of thoracic 4D CT images was investigated. The algorithm was modified to minimize the incidence of deformation vector discontinuities that occur during the registration of lung images. Registrations were performed between the inhale and exhale phases for five patients. The registration accuracy was quantified by the cross-correlation of transformed and target images and distance to agreement (DTA) measured based on anatomical landmarks and triangulated surfaces constructed from manual contours. On average, the vector DTA between transformed and target landmarks was 1.6 mm. Comparing transformed and target 3D triangulated surfaces derived from planning contours, the average target volume (GTV) center-of-mass shift was 2.0 mm and the 3D DTA was 1.6 mm. An average DTA of 1.8 mm was obtained for all planning structures. All DTA metrics were comparable to inter observer uncertainties established for landmark identification and manual contouring.     

Influence of the number of elongated fiducial markers on the localization accuracy of the prostate

Implanting fiducial markers for localization purposes has become an accepted practice in radiotherapy for prostate cancer. While many correction strategies correct for translations only, advanced correction protocols also require knowledge of the rotation of the prostate. For this purpose, typically, three or more markers are implanted. Elongated fiducial markers provide more information about their orientation than traditional round or cylindrical markers. Potentially, fewer markers are required. In this study, we evaluate the effect of the number of elongated markers on the localization accuracy of the prostate. To quantify the localization error, we developed a model that estimates, at arbitrary locations in the prostate, the registration error caused by translational and rotational uncertainties of the marker registration. Every combination of one, two and three markers was analysed for a group of 24 patients. The average registration errors at the prostate surface were 0.3-0.8?mm and 0.4-1?mm for registrations on, respectively, three markers and two markers located on different sides of the prostate. Substantial registration errors (2.0-2.2?mm) occurred at the prostate surface contralateral to the markers when two markers were implanted on the same side of the prostate or only one marker was used. In conclusion, there is no benefit in using three elongated markers: two markers accurately localize the prostate if they are implanted at some distance from each other.     

The applicability of simultaneous TRUS-CT imaging for the evaluation of prostate seed implants

To study dose-effect relations of prostate implants with I-125 seeds, accurate knowledge of the dose distribution in the prostate is essential. Commonly, a post-implant computed tomography (CT) scan is used to determine the geometry of the implant and to delineate the contours of the prostate. However, the delineation of the prostate on CT slices is very cumbersome due to poor contrast between the prostate capsule and surrounding tissues. Transrectal Ultrasound (TRUS) on the other hand offers good visualization of the prostate but poor visualization of the implanted seeds. The purpose of this study was to investigate the applicability of combining CT with 3D TRUS by means of image fusion. The advantage of fused TRUS-CT imaging is that both prostate contours and implanted seeds will be well visible. In our clinic, post-implant imaging was realized by simultaneously acquiring a TRUS scan and a CT scan. The TRUS transducer was inserted while the patient was on the CT couch and the CT scan was made directly after the TRUS scan, with the probe still in situ. With the TRUS transducer being visible on both TRUS and CT images, the geometrical relationship between both image sets could be defined by registration on the transducer. Having proven the applicability of simultaneous imaging, the accuracy of this registration method was investigated by additional registration on visible seeds, after preregistration on the transducer. In 4 out of 23 investigated cases an automatic grey value registration on seeds failed for each of the investigated cost functions, and in 2 cases for both cost functions, due to poor visibility of the seeds on the TRUS scan. The average deviations of the seed registration with respect to the transducer registration were negligible. However, in a few individual cases the deviations were significant and probably due to movement of the patient between TRUS and CT scan. In case of a registration on the transducer it is important to avoid patient movement in-between the TRUS and CT scan and to keep the time in-between the scans as short as possible. It can be concluded that fusion of a CT scan and a simultaneously made TRUS scan by means of a three-dimensional (3D) transducer is feasible and accurate when performing a registration on the transducer, if necessary, fine-tuned by a registration on seeds. These fused images are likely to be of great value for post-implant dose distribution evaluations.     

Automatic segmentation of phase-correlated CT scans through nonrigid image registration using geometrically regularized free-form deformation

Conventional radiotherapy is planned using free-breathing computed tomography (CT), ignoring the motion and deformation of the anatomy from respiration. New breath-hold-synchronized, gated, and four-dimensional (4D) CT acquisition strategies are enabling radiotherapy planning utilizing a set of CT scans belonging to different phases of the breathing cycle. Such 4D treatment planning relies on the availability of tumor and organ contours in all phases. The current practice of manual segmentation is impractical for 4D CT, because it is time consuming and tedious. A viable solution is registration-based segmentation, through which contours provided by an expert for a particular phase are propagated to all other phases while accounting for phase-to-phase motion and anatomical deformation. Deformable image registration is central to this task, and a free-form deformation-based nonrigid image registration algorithm will be presented. Compared with the original algorithm, this version uses novel, computationally simpler geometric constraints to preserve the topology of the dense control-point grid used to represent free-form deformation and prevent tissue fold-over. Using mean squared difference as an image similarity criterion, the inhale phase is registered to the exhale phase of lung CT scans of five patients and of characteristically low-contrast abdominal CT scans of four patients. In addition, using expert contours for the inhale phase, the corresponding contours were automatically generated for the exhale phase. The accuracy of the segmentation (and hence deformable image registration) was judged by comparing automatically segmented contours with expert contours traced directly in the exhale phase scan using three metrics: volume overlap index, root mean square distance, and Hausdorff distance. The accuracy of the segmentation (in terms of radial distance mismatch) was approximately 2 mm in the thorax and 3 mm in the abdomen, which compares favorably to the accuracies reported elsewhere. Unlike most prior work, segmentation of the tumor is also presented. The clinical implementation of 4D treatment planning is critically dependent on automatic segmentation, for which is offered one of the most accurate algorithms yet presented.     

In-bore setup and software for 3T MRI-guided transperineal prostate biopsy

MRI-guided prostate biopsy in conventional closed-bore scanners requires transferring the patient outside the bore during needle insertion due to the constrained in-bore space, causing a safety hazard and limiting image feedback. To address this issue, we present our custom-made in-bore setup and software to support MRI-guided transperineal prostate biopsy in a wide-bore 3 T MRI scanner. The setup consists of a specially designed tabletop and a needle-guiding template with a Z-frame that gives a physician access to the perineum of the patient at the imaging position and allows the physician to perform MRI-guided transperineal biopsy without moving the patient out of the scanner. The software and Z-frame allow registration of the template, target planning and biopsy guidance. Initially, we performed phantom experiments to assess the accuracy of template registration and needle placement in a controlled environment. Subsequently, we embarked on our clinical trial (N = 10). The phantom experiments showed that the translational errors of the template registration along the right-left (RP) and anterior-posterior (AP) axes were 1.1 ± 0.8 and 1.4 ± 1.1 mm, respectively, while the rotational errors around the RL, AP and superior-inferior axes were (0.8 ± 1.0)°, (1.7 ± 1.6)° and (0.0 ± 0.0)°, respectively. The 2D root-mean-square (RMS) needle-placement error was 3 mm. The clinical biopsy procedures were safely carried out in all ten clinical cases with a needle-placement error of 5.4 mm (2D RMS). In conclusion, transperineal prostate biopsy in a wide-bore 3T scanner is feasible using our custom-made tabletop setup and software, which supports manual needle placement without moving the patient out of the magnet.