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.     

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.     

A feasibility study of mutual information based setup error estimation for radiotherapy.

We have investigated a fully automatic setup error estimation method that aligns DRRs (digitally reconstructed radiographs) from a three-dimensional planning computed tomography image onto two-dimensional radiographs that are acquired in a treatment room. We have chosen a MI (mutual information)-based image registration method, hoping for robustness to intensity differences between the DRRs and the radiographs. The MI-based estimator is fully automatic since it is based on the image intensity values without segmentation. Using 10 repeated scans of an anthropomorphic chest phantom in one position and two single scans in two different positions, we evaluated the performance of the proposed method and a correlation-based method against the setup error determined by fiducial marker-based method. The mean differences between the proposed method and the fiducial marker-based method were smaller than 1 mm for translational parameters and 0.8 degree for rotational parameters. The standard deviations of estimates from the proposed method due to detector noise were smaller than 0.3 mm and 0.07 degree for the translational parameters and rotational parameters, respectively.     

A computationally efficient method for automatic registration of orthogonal x-ray images with volumetric CT data

The paper presents a computationally efficient 3D-2D image registration algorithm for automatic pre-treatment validation in radiotherapy. The novel aspects of the algorithm include (a) a hybrid cost function based on partial digitally reconstructed radiographs (DRRs) generated along projected anatomical contours and a level set term for similarity measurement; and (b) a fast search method based on parabola fitting and sensitivity-based search order. Using CT and orthogonal x-ray images from a skull and a pelvis phantom, the proposed algorithm is compared with the conventional ray-casting full DRR based registration method. Not only is the algorithm shown to be computationally more efficient with registration time being reduced by a factor of 8, but also the algorithm is shown to offer 50% higher capture range allowing the initial patient displacement up to 15 mm (measured by mean target registration error). For the simulated data, high registration accuracy with average errors of 0.53 mm +/- 0.12 mm for translation and 0.61 +/- 0.29 degrees for rotation within the capture range has been achieved. For the tested phantom data, the algorithm has also shown to be robust without being affected by artificial markers in the image.     

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.     

Volume-of-change cone-beam CT for image-guided surgery

C-arm cone-beam CT (CBCT) can provide intraoperative 3D imaging capability for surgical guidance, but workflow and radiation dose are the significant barriers to broad utilization. One main reason is that each 3D image acquisition requires a complete scan with a full radiation dose to present a completely new 3D image every time. In this paper, we propose to utilize patient-specific CT or CBCT as prior knowledge to accurately reconstruct the aspects of the region that have changed by the surgical procedure from only a sparse set of x-rays. The proposed methods consist of a 3D-2D registration between the prior volume and a sparse set of intraoperative x-rays, creating digitally reconstructed radiographs (DRRs) from the registered prior volume, computing difference images by subtracting DRRs from the intraoperative x-rays, a penalized likelihood reconstruction of the volume of change (VOC) from the difference images, and finally a fusion of VOC reconstruction with the prior volume to visualize the entire surgical field. When the surgical changes are local and relatively small, the VOC reconstruction involves only a small volume size and a small number of projections, allowing less computation and lower radiation dose than is needed to reconstruct the entire surgical field. We applied this approach to sacroplasty phantom data obtained from a CBCT test bench and vertebroplasty data with a fresh cadaver acquired from a C-arm CBCT system with a flat-panel detector. The VOCs were reconstructed from a varying number of images (10-66 images) and compared to the CBCT ground truth using four different metrics (mean squared error, correlation coefficient, structural similarity index and perceptual difference model). The results show promising reconstruction quality with structural similarity to the ground truth close to 1 even when only 15-20 images were used, allowing dose reduction by the factor of 10-20.     

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。     

2D/3D刚性图像配准在肿瘤放疗计划中的应用

目的:在肿瘤放疗中,2D/3D刚性图像配准技术是精确定位病人重要保证。方法:数字重建放射影像技术是2D/3D配准中最为关键的部分,一定程度上影响着配准效率。在对数字重建放射影像进行重点研究的基础上,实现了一种基于Bresenham方法的快速数字影像重建算法,并利用腹部CT体数据进行了2D/3D配准实验。实验以互信息、模式强度和梯度差分为相似性测度并采用了Powell-Brent优化算法。结果:在数字重建放射图像算法实验中,Bresemham方法相比于另外两种光线跟踪算法,时间仅需0.467 s。在2D/3D配准实验中,对三种相似性测度的实验结果进行了比较,互信息和梯度差分有较好的配准结果,模式强度仍存在不少问题。结论:实验结果表明,利用Bresenham方法产生的数字重建影像能使得配准具有较高精度,但配准时间仍然较长。     

Registration of DRRs and portal images for verification of stereotactic body radiotherapy: a feasibility study in lung cancer treatment

Image guidance has become a pre-requisite for hypofractionated radiotherapy where the applied dose per fraction is increased. Particularly in stereotactic body radiotherapy (SBRT) for lung tumours, one has to account for set-up errors and intrafraction tumour motion. In our feasibility study, we compared digitally reconstructed radiographs (DRRs) of lung lesions with MV portal images (PIs) to obtain the displacement of the tumour before irradiation. The verification of the tumour position was performed by rigid intensity based registration and three different merit functions such as the sum of squared pixel intensity differences, normalized cross correlation and normalized mutual information. The registration process then provided a translation vector that defines the displacement of the target in order to align the tumour with the isocentre. To evaluate the registration algorithms, 163 test images were created and subsequently, a lung phantom containing an 8 cm(3) tumour was built. In a further step, the registration process was applied on patient data, containing 38 tumours in 113 fractions. To potentially improve registration outcome, two filter types (histogram equalization and display equalization) were applied and their impact on the registration process was evaluated. Generated test images showed an increase in successful registrations when applying a histogram equalization filter whereas the lung phantom study proved the accuracy of the selected algorithms, i.e. deviations of the calculated translation vector for all test algorithms were below 1 mm. For clinical patient data, successful registrations occurred in about 59% of anterior-posterior (AP) and 46% of lateral projections, respectively. When patients with a clinical target volume smaller than 10 cm(3) were excluded, successful registrations go up to 90% in AP and 50% in lateral projection. In addition, a reliable identification of the tumour position was found to be difficult for clinical target volumes at the periphery of the lung, close to backbone or diaphragm. Moreover, tumour movement during shallow breathing strongly influences image acquisition for patient positioning. Recapitulating, 2D/3D image registration for lung tumours is an attractive alternative compared to conventional CT verification of the tumour position. Nevertheless, size and location of the tumour are limiting parameters for an accurate registration process.     

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.     

Registration of electronic portal images for patient set-up verification

Images acquired from an electronic portal imaging device are aligned with digitally reconstructed radiographs (DRRs) or other portal images to verify patient positioning during radiation therapy. Most of the currently available computer aided registration methods are based on the manual placement of corresponding landmarks. The purpose of the paper is twofold: (a) the establishment of a methodology for patient set-up verification during radiotherapy based on the registration of electronic portal images, and (b) the evaluation of the proposed methodology in a clinical environment. The estimation of set-up errors, using the proposed methodology, can be accomplished by matching the portal image of the current fraction of the treatment with the portal image of the baseline treatment (reference portal image) using a nearly automated technique. The proposed registration method is tested on a number of phantom data as well as on data from four patients. The phantom data included portal images that corresponded to various positions of the phantom on the treatment couch. For each patient, a set of 30 portal images was used. For the phantom data (for both transverse and lateral portal images), the maximum absolute deviations of the translational shifts were within 1.5 mm, whereas the in-plane rotation angle error was less than 0.5 degrees. The two-way Anova revealed no statistical significant variability both within observer and between-observer measurements (P > 0.05). For the patient data, the mean values obtained with manual and the proposed registration methods were within 0.5 mm. In conclusion, the proposed registration method has been incorporated within a system, called ESTERR-PRO. Its image registration capability achieves high accuracy and both intra- and inter-user reproducibility. The system is fully operational within the Radiotherapy Department of 'HYGEIA' Hospital in Athens and it could be easily installed in any other clinical environment since it requires standardized hardware specifications and minimal human intervention.     

基于锥形束CT分析食管癌和肺癌患者摆位误差

【摘要】目的:应用锥形束CT（CBCT）观察食管癌和肺癌六维方向的摆位误差,分析六维床对食管癌平移和旋转方向校正的必要性及其临床意义。方法:选取2019年10月~2021年12月在中山大学肿瘤防治中心放疗的胸部肿瘤患者,食管癌组、肺癌组各85例,收集所有患者前3次CBCT扫描,通过六维方向与计划中的定位CT图像进行配准,获得头脚方向（SI）、左右方向（LR）、前后方向（AP）、绕Z轴旋转（RTN）、绕X轴旋转（PITCH）、绕Y轴旋转（ROLL）6个方向的摆位误差。原始数据取绝对值,采用Kolmogorov-Smirnov Z非参数秩和检验进行统计分析。结果:食管癌组和肺癌组在SI、LR、AP平移方向摆位误差取绝对值分别为:0.30（0.10, 0.50）、0.10（0.10, 0.30）、0.10（0.10, 0.20）和0.20（0.10, 0.40）、0.20（0.10, 0.30）、0.10（0.10, 0.30） cm;在RTN、PITCH、ROLL旋转方向的摆位误差取绝对值分别为0.50°（0.30°, 0.90°）、0.90°（0.40°, 1.60°）、0.90°（0.40°, 1.40°）和0.40°（0.10°, 0.70°）、0.70°（0.20°, 1.30°）、0.50°（0.10°, 1.00°）,食管癌组和肺癌组中SI、RTN、PITCH、ROLL方向比较,差异均有统计学意义（P<0.05）,而LR、AP方向比较,差异无统计学意义（P>0.05）。结论:基于CBCT引导下,六维配准技术配合六维床能降低胸部肿瘤患者放疗时摆位误差,特别是长靶区如食管癌方面,校正旋转摆位误差有明显优势。     

Scatter kernel estimation with an edge-spread function method for cone-beam computed tomography imaging

The clinical applications of kilovoltage x-ray cone-beam computed tomography (CBCT) have been compromised by the limited quality of CBCT images, which typically is due to a substantial scatter component in the projection data. In this paper, we describe an experimental method of deriving the scatter kernel of a CBCT imaging system. The estimated scatter kernel can be used to remove the scatter component from the CBCT projection images, thus improving the quality of the reconstructed image. The scattered radiation was approximated as depth-dependent, pencil-beam kernels, which were derived using an edge-spread function (ESF) method. The ESF geometry was achieved with a half-beam block created by a 3 mm thick lead sheet placed on a stack of slab solid-water phantoms. Measurements for ten water-equivalent thicknesses (WET) ranging from 0 cm to 41 cm were taken with (half-blocked) and without (unblocked) the lead sheet, and corresponding pencil-beam scatter kernels or point-spread functions (PSFs) were then derived without assuming any empirical trial function. The derived scatter kernels were verified with phantom studies. Scatter correction was then incorporated into the reconstruction process to improve image quality. For a 32 cm diameter cylinder phantom, the flatness of the reconstructed image was improved from 22% to 5%. When the method was applied to CBCT images for patients undergoing image-guided therapy of the pelvis and lung, the variation in selected regions of interest (ROIs) was reduced from >300 HU to <100 HU. We conclude that the scatter reduction technique utilizing the scatter kernel effectively suppresses the artifact caused by scatter in CBCT.     

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.     

Progressive attenuation fields: fast 2D-3D image registration without precomputation

Computation of digitally reconstructed radiograph (DRR) images is the rate-limiting step in most current intensity-based algorithms for the registration of three-dimensional (3D) images to two-dimensional (2D) projection images. This paper introduces and evaluates the progressive attenuation field (PAF), which is a new method to speed up DRR computation. A PAF is closely related to an attenuation field (AF). A major difference is that a PAF is constructed on the fly as the registration proceeds; it does not require any precomputation time, nor does it make any prior assumptions of the patient pose or limit the permissible range of patient motion. A PAF effectively acts as a cache memory for projection values once they are computed, rather than as a lookup table for precomputed projections like standard AFs. We use a cylindrical attenuation field parametrization, which is better suited for many medical applications of 2D-3D registration than the usual two-plane parametrization. The computed attenuation values are stored in a hash table for time-efficient storage and access. Using clinical gold-standard spine image data sets from five patients, we demonstrate consistent speedups of intensity-based 2D-3D image registration using PAF DRRs by a factor of 10 over conventional ray casting DRRs with no decrease of registration accuracy or robustness.     

Wobbled splatting--a fast perspective volume rendering method for simulation of x-ray images from CT

3D/2D registration, the automatic assignment of a global rigid-body transformation matching the coordinate systems of patient and preoperative volume scan using projection images, is an important topic in image-guided therapy and radiation oncology. A crucial part of most 3D/2D registration algorithms is the fast computation of digitally rendered radiographs (DRRs) to be compared iteratively to radiographs or portal images. Since registration is an iterative process, fast generation of DRRs-which are perspective summed voxel renderings-is desired. In this note, we present a simple and rapid method for generation of DRRs based on splat rendering. As opposed to conventional splatting, antialiasing of the resulting images is not achieved by means of computing a discrete point spread function (a so-called footprint), but by stochastic distortion of either the voxel positions in the volume scan or by the simulation of a focal spot of the x-ray tube with non-zero diameter. Our method generates slightly blurred DRRs suitable for registration purposes at framerates of approximately 10 Hz when rendering volume images with a size of 30 MB.     

基于kV-CBCT图像验证非小细胞肺癌立体定向放疗的照射剂量

目的:基于千伏级锥形束CT（kV-CBCT）图像验证非小细胞肺癌（NSCLC）立体定向放疗（SBRT）的照射剂量。方法:收集20例行SBRT的NSCLC患者的100张CBCT图像。采用形变配准和非形变配准两种方法在CBCT图像上对单次照射剂量分布进行重新计算。使用剂量体积直方图对计划剂量和重新计算的照射剂量进行比较。结果:患者内靶区的平均覆盖率（V100%）相对差异较小;计划之间的适形度指数和梯度指数表现出很好的一致性。对于危及器官,在计划剂量和照射剂量之间仅在一名患者中发现有明显差异（P<0.05）。结论:CBCT图像能用来验证NSCLC的SBRT剂量,并提供相关的3D执行剂量的信息。     

Image quality and localization accuracy in C-arm tomosynthesis-guided head and neck surgery

The image quality and localization accuracy for C-arm tomosynthesis and cone-beam computed tomography (CBCT) guidance of head and neck surgery were investigated. A continuum in image acquisition was explored, ranging from a single exposure (radiograph) to multiple projections acquired over a limited arc (tomosynthesis) to a full semicircular trajectory (CBCT). Experiments were performed using a prototype mobile C-arm modified to perform 3D image acquisition (a modified Siemens PowerMobil). The tradeoffs in image quality associated with the extent of the source-detector arc (theta(tot)), the number of projection views, and the total imaging dose were evaluated in phantom and cadaver studies. Surgical localization performance was evaluated using three cadaver heads imaged as a function of theta(tot). Six localization tasks were considered, ranging from high-contrast feature identification (e.g., tip of a K-wire pointer) to more challenging soft-tissue delineation (e.g., junction of the hard and soft palate). Five head and neck surgeons and one radiologist participated as observers. For each localization task, the 3D coordinates of landmarks pinpointed by each observer were analyzed as a function of theta(tot). For all tomosynthesis angles, image quality was highest in the coronal plane, whereas sagittal and axial planes exhibited a substantial decrease in spatial resolution associated with out-of-plane blur and distortion. Tasks involving complex, lower-contrast features demonstrated steeper degradation with smaller tomosynthetic arc. Localization accuracy in the coronal plane was correspondingly high, maintained to < 3 mm down to theta(tot) approximately 30 degrees, whereas sagittal and axial localization degraded rapidly below theta(tot) approximately 60 degrees. Similarly, localization precision was better than approximately 1 mm within the coronal plane, compared to approximately 2-3 mm out-of-plane for tomosynthesis angles below theta(tot) approximately 45 degrees. An overall 3D localization accuracy of approximately 2.5 mm was achieved with theta(tot) approximately 90 degrees for most tasks. The high in-plane spatial resolution, short scanning time, and low radiation dose characteristic of tomosynthesis may enable the surgeon to collect near real-time images throughout the procedure with minimal interference to surgical workflow. Therefore, tomosynthesis could provide a useful addition to the image-guided surgery arsenal, providing on-demand, high quality image updates, complemented by CBCT at critical milestones in the surgical procedure.     

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.