Rigid Registration Method Research Articles

Ultrasound–fluoroscopy registration for prostate brachytherapy dosimetry

Prostate brachytherapy is a treatment for prostate cancer using radioactive seeds that are permanently implanted in the prostate. The treatment success depends on adequate coverage of the target gland with a therapeutic dose, while sparing the surrounding tissue. Since seed implantation is performed under transrectal ultrasound (TRUS) imaging, intraoperative localization of the seeds in ultrasound can provide physicians with dynamic dose assessment and plan modification. However, since all the seeds cannot be seen in the ultrasound images, registration between ultrasound and fluoroscopy is a practical solution for intraoperative dosimetry. In this manuscript, we introduce a new image-based nonrigid registration method that obviates the need for manual seed segmentation in TRUS images and compensates for the prostate displacement and deformation due to TRUS probe pressure. First, we filter the ultrasound images for subsequent registration using thresholding and Gaussian blurring. Second, a computationally efficient point-to-volume similarity metric, an affine transformation and an evolutionary optimizer are used in the registration loop. A phantom study showed final registration errors of 0.84 ± 0.45 mm compared to ground truth. In a study on data from 10 patients, the registration algorithm showed overall seed-to-seed errors of 1.7 ± 1.0 mm and 1.5 ± 0.9 mm for rigid and nonrigid registration methods, respectively, performed in approximately 30s per patient.

TU-A-218-05: Evaluation of Image Registration Using Landmark Matching and Texture Analysis

Purpose: To compare demons deformable registration with rigid and affineregistration methods by measuring registration accuracy and image texture changes introduced by each algorithm. Methods: Eleven temporally sequential pairs of clinical thoracic CT scans demonstrating no abnormal pathology were collected retrospectively from different patients. Rigid, affine, and demons registration methods were applied to all scan pairs using an appropriate choice of registration parameters. 150 landmarks were automatically selected in each baseline scan, and a semi‐automated approach was used to identify corresponding landmarks in the respective deformed follow‐up scans. Eleven first‐order texture features were calculated in 32x32‐pixel regions of interest (ROIs) randomly placed in the baseline scans and at anatomically matched locations in the demons‐, rigid‐, and affine‐ registered follow‐up scans. For each ROI pair, feature value differences between the three registered follow‐up scans and the baseline scan were calculated. Results: The average per‐patient Euclidean distance between baseline scan landmarks and registered follow‐up scan landmarks ranged from 0.01–0.50 mm (overall mean: 0.18 mm), 1.6–6.8 mm (overall mean: 3.95 mm), and 2.06–7.91 mm (overall mean: 4.82 mm) for demons, affine, and rigid registration methods, respectively. Across all eleven features, the variances in feature value change for rigid and affine registration methods were at least an order of magnitude larger than the corresponding feature‐ value‐change variances for demons registration. Conclusions: Demons registration achieved more accurate spatial alignment between temporally sequential CT scans than rigid or affine registration methods. Furthermore, the variance in texture feature value changes between baseline and registered follow‐up scan ROIs was smaller for demons than for rigid or affine registration methods. These advantages of demons registration observed with “normal” thoracic CT scans indicate that future studies may incorporate demons to combine serial CT scans such that automated methods may distinguish registration artifacts from actual pathologic change.

WE‐C‐BRA‐03: Best in Physics (Joint Imaging‐Therapy) ‐ Registration of Magnetic Resonance, Reconstructed 3D Ultrasound Imaging and Whole‐Mount Breast Pathology for Therapy Assessment of Breast Cancer

Purpose: To develop a procedure to register 3D whole‐mount histology of the breast with multimodality imaging, including MRI and ultrasound. This work provides a platform for developing methods for therapy assessment in breast cancer using cell death characterized through quantitative ultrasound. Methods: Ultrasound scans, DCE‐MRI, MRI‐exvivo mastectomy sample and whole‐mount histological slices were obtained. The ultrasound scans were collected using a freehand 2D‐ultrasound probe and a tracking tool affixed to the probe for coordinate determination. These coordinates were used to reconstruct the 3D‐ ultrasound volume. All image data sets were rigidly registered, the tumor was contoured on each data set, and each set of contours was converted to a volumetric mesh. There are considerable deformations between imaging modalities due to different breast positions at the time of scanning and between imaging and pathology. Part of these deformations were estimated using the MRI exvivo scans of the breast collected before histological processing, and applying a biomechanical‐based model deformation algorithm to calculate the deformation map from DCE‐MRI‐invivo to MRI‐exvivo. Results: The rigid registration method resulted in large differences between the residual tumor volumes estimated from DCE‐MRI(147%), US(56%) and histology(100%), considering the histology representation as the ground truth. After applying the deformation map to the DCE‐MRI, the volume of the residual tumor in DCE‐MRI decreased by 30% approaching the representation of the residual tumor in histology and ultrasound. Modest improvements to the Dice Index were seen from DCE‐MRI‐to histology and from DCE‐MRI‐to‐US after applying the deformation map. Conclusions: The project provides metrics of comparison between the volumes of residual tumor assessed from ground truth histology and the volumes assessed from ultrasound and DCE‐MRI in breast cancer patients. Since tumors are stiffer than surrounding breast tissue, future work will need to consider including tumor elastic properties in calculating the deformation map from MRI‐invivo to MRI‐exvivo. Terry Fox New Frontiers Program Project in Ultrasound for Cancer Therapy. Dr. Brock has financial interest in deformable registration technology through the licensing of Morfeus to RaySearch Laboratories

Rigid and non-rigid medical image registration methods

Image registration is an important and usually necessary step in multi-dimensional multi-modality medical image analysis. Moreover, images from the same modality may be registered to study and analyse variability of a specific structure or information among a group of subjects to develop physiological models and computerised atlases. Multi-dimensional image registration is also an important step in therapeutic protocols including radiation treatment and evaluation. Recent advances in medical imaging and image analysis have accompanied with a number of rigid-body and non-rigidbody image registration methods and algorithms. This paper first briefly reviews some of the rigid and non-rigid image registration methods and then presents an integrated approach of rigid and elastic deformation methods suitable for dealing with registration of partially deformed and incomplete image datasets.

Comprehensive Approach to Coregistration of Autoradiography and Microscopy Images Acquired from a Set of Sequential Tissue Sections

Histopathologic validation of a PET tracer requires assessment of colocalization of the tracer with its intended biologic target. Using thin tissue section autoradiography, it is possible to visualize the spatial distribution of the PET tracer uptake and compare it with the distribution of the intended biologic target (as visualized with immunohistochemistry). The purpose of this study was to develop and evaluate an objective methodology for deformable coregistration of autoradiography and microscopy images acquired from a set of sequential tissue sections. Tumor-bearing animals were injected with 3'-deoxy-3'-(18)F-fluorothymidine ((18)F-FLT), (14)C-FDG, and other markers of tumor microenvironment including Hoechst 33342 (blood-flow surrogate). After sacrifice, tumors were excised, frozen, and sectioned. Multiple stacks of sequential 8 μm sections were collected from each tumor. From each stack, the middle (reference) sections were used to obtain images of (18)F-FLT and (14)C-FDG uptake distributions using dual-tracer autoradiography. Sections adjacent to the reference were used to acquire all histopathologic data (e.g., images of cell proliferation, hematoxylin and eosin). Hoechst images were acquired from all sections. To correct for deformations and misalignments induced by tissue processing and image acquisition, the Hoechst image of each nonreference section was deformably registered to the reference Hoechst image. This transformation was then applied to all images acquired from the same tissue section. In this way, all microscopy images were registered to the reference Hoechst image. The Hoechst-to-autoradiography image registration was done using rigid point-set registration based on external markers visible in both images. The mean error of Hoechst to (18)F-FLT autoradiography registration (both images acquired from the same section) was 30.8 ± 20.1 μm. The error of Hoechst-based deformable registration of histopathologic images (acquired from sequential tissue sections) was 23.1 ± 17.9 μm. Total error of registration of autoradiography images to the histopathologic images acquired from adjacent sections was evaluated at 44.9 μm. This coregistration precision supersedes current rigid registration methods with reported errors of 100-200 μm. Deformable registration of autoradiography and histopathology images acquired from sequential sections is feasible and accurate when performed using corresponding Hoechst images.

SU-F-BRA-01: Object-Based Analysis of Spatial Concordance Between Coregistered Images of Intratumoral Uptake of [18F]FLT and Distribution of Cell Proliferation Markers

Purpose: To propose a new objective method for deformable coregistration of multimodality images acquired with digital autoradiography (DAR) and microscopy in the context of PET tracer histopathological validation. To analyze the spatial concordance between the uptake pattern of 18F-fluorothymidine (FLT) as imaged with DAR and the distribution of cell proliferation as revealed by immunofluorescence microscopy imaging.Methods: Tumor-bearing mice were injected with FLT and other markers including bromodeoxyuridine (cell proliferation). After sacrifice, tumors were excised, frozen and sectioned. Multiple stacks of sequential 8μm sections were collected from each tumor. Selected sections were used for DAR to image FLT uptake distribution. Adjacent sections were used to acquire histopathological data. To correct for imperfections of the tissue cutting and collection, all images were deformably coregistered to the FLT DAR image based on biological images of tumor blood flow (Hoechst) that was acquired from each tissue section used. For each FLT DAR — cell proliferation microscopy image pair, object-based analysis was conducted, including overlap and relative operating characteristics (ROC) analysis. Results: Total registration error of proposed coregistration method was 44.86μm. This supersedes current rigid registration methods with reported errors of 100–200μm. In tumors with well-compartmentalized functional aspects, area under the ROC curve (AUCroc= 0.7) indicated FLT DAR image thresholding as an accurate method of detecting cell proliferation. For these tumors, Dice overlap index indicated maximum detection rates at thresholds between 20% and 40% of the maximum DAR intensity. For the tumors characterized by more heterogeneous distribution of cell proliferation across the tumor section, FLT DAR image thresholding could not predict cell proliferation beyond random chance. Conclusions: We developed a comprehensive method of obtaining and analyzing coregistered images of cell proliferation markers and intratumoral uptake of FLT. Tumor microenvironment heterogeneity is a significant factor affecting the utility of FLT for imaging cell proliferation.

Surface matching method for profile inspection with touch probe

This paper presents an efficient method for rigid registration of 3-D point sets, which intends to match the feature points inspected using touch probe with the points on designed CAD surface. The alignment error is defined as the least square problem, and the sphere radius of the inspection probe is considered. In this framework, the matching problem is converted into acquiring six Euler variables problem by solving nonlinear equations. Thus, a matrix transformation of parameter separation is presented to get the approximate resolution. Finally, iterative cycles are provided to calculate the nearest points on designed surface corresponding to the inspection points. Experiment verification is realized for the presented surface matching method of robot inspection system.

Rigid 3D–3D registration of TOF MRA integrating vessel segmentation for quantification of recurrence volumes after coiling cerebral aneurysm

A fast and reproducible quantification of the recurrence volume of coiled aneurysms is required to enable a more timely evaluation of new coils. This paper presents two registration schemes for the semi-automatic quantification of aneurysm recurrence volumes based on baseline and follow-up 3D MRA TOF datasets. The quantification of shape changes requires a previous definition of corresponding structures in both datasets. For this, two different rigid registration methods have been developed and evaluated. Besides a state-of-the-art rigid registration method, a second approach integrating vessel segmentations is presented. After registration, the aneurysm recurrence volume can be calculated based on the difference image. The computed volumes were compared to manually extracted volumes. An evaluation based on 20 TOF MRA datasets (baseline and follow-up) of ten patients showed that both registration schemes are generally capable of providing sufficient registration results. Regarding the quantification of aneurysm recurrence volumes, the results suggest that the second segmentation-based registration method yields better results, while a reduction of the computation and interaction time is achieved at the same time. The proposed registration scheme incorporating vessel segmentation enables an improved quantification of recurrence volumes of coiled aneurysms with reduced computation and interaction time.

Comparisons of multiple automated anatomy‐based image‐guidance methods for patient setup before head/neck external beam radiotherapy

The purpose was to assess the variability in automated translational head/neck setup corrections computed from several different imaging modalities and rigid registration methods using patient anatomy. Shifts were calculated using three commercial and one in‐house automated rigid registration methods for nine head/neck patients who were imaged with three different image‐guidance systems. The mean difference between the daily isocenter shifts determined by the four methods ranged from 2.8 to 12.5 mm for all of the test cases. These differences are much greater than the variability observed for a rigid imaging phantom. Image‐guided setup procedures have an uncertainty that depends on the imaging modality, the registration algorithm, the image resolution and the image content. In the absence of an absolute ground truth, the variation in the shifts calculated by several different methods provides a useful estimate of that uncertainty.PACS number: 87,55,km, 87.57.nj, 87.59.‐e, 87.59.bd

Statistically Deformable 2D/3D Registration for Estimating Post-operative Cup Orientation from a Single Standard AP X-ray Radiograph

The widely used procedure of estimating post-operative cup orientation based on a single standard AP X-ray radiograph is known inaccurate, largely due to the wide variability in individual pelvic orientation relative to X-ray plate. CT-based 2D/3D rigid image registration methods have been developed to measure post-operative cup orientation. Although encouraging results have been reported, their extensive usage in clinical routine is still limited. This may be explained by their requirement of having a CT study of the patient at some point during treatment, which is not available for vast majority of Total Hip Arthroplasty procedures performed nowadays. To address this limitation, this article proposes a statistically deformable 2D/3D registration approach for estimating post-operative cup orientation. No CT study of the patient is required any more. Compared to ground truths established from post-operative CT images, the cup orientations measured by the present technique in a cadaver experiment showed differences of 1.7 +/- 1.4 degrees for anteversion and difference of 1.5 +/- 1.5 degrees for inclination. When the present technique was evaluated on patients' datasets, differences of 2.2 +/- 1.3 degrees and differences of 2.0 +/- 0.8 degrees were found for the anteversion and the inclination, respectively. The experimental results, though still preliminary, demonstrated the efficacy of the present approach.

TH-C-201C-10: Registration Using Nanotube Stationary Tomosynthesis: Comparison of 3D/3D to 3D/2D Methods

Purpose: To evaluate traditional 3D/3D and 3D/2D rigid registration strategies for tomosynthesisimages obtained from the Nanotube Stationary Tomosynthesis (NST) geometry. Method and Materials: NST is a multi‐source kV imager which is mounted on a linear accelerator gantry. The multiple sources allow imaging without gantry motion before and concurrent with radiation treatment. Due to the nature of the reconstructed images it is not immediately clear how to register tomosynthesisimages to planning CTs. Depending on the amount of angular sampling in the geometry better performance can be achieved with 3D/3D registration as is the case with cone‐beam CT or 3D/2D registration as is the case with portal imaging.Tomosynthesisimages contain angular sampling somewhere in between these two extremes. The question remains whether NST images should be considered a set of 2D projections or a 3D volume for the purpose of rigid registration. Simulated NST images were used to evaluate treatment time rigid registration for patient setup. Two GPU‐accelerated planning CT to tomosynthesis rigid registration methods were considered characterized by the domain in which the similarity metric is computed. Results: Simulated data sets suggest that evaluation of the similarity metric in projection space reduces mean target registration error (mTRE) and increases speed over reconstruction space methods. A rate limiting step of the 3D/3D method is the requirement for repeated iterative reconstructions. Conclusion: We have demonstrated that 3D/2D methods are faster and result in decreased mTRE over 3D/3D methods for rigid registration of NST images. It is suggested that 3D/2D methods will be faster in cases where a significant number of reconstructions must be generated. Conflict of Interest: This work is partially funded by a grant from Siemens Medical.

SU-GG-T-11: Dosimetric Impacts of Rotational Setup Errors on Head & Neck IMRT Treatments

Purpose: To investigate the dosimetric impact of the residual rotational setup errors on head&neck (HNC) IMRT with conventional clinical three translational setup corrections, and to evaluate the necessity of the full six degree (6D) setup correction. Methods and Materials: A total of 66 kV CBCTimage sets were acquired on the first day of treatment and weekly thereafter for 10 HNC patients. The CBCTimages were registered with the planning CTimages using two 3D rigid registration methods. Method1 determines the translational errors only and method2 determines 6D errors. To simulate the clinical setup correction, the 6D setup errors were simulated in the treatment planning system and then were corrected by using the corresponding translational data determined by method1. For each patient, dose distributions for 6 to 7 fractions with various setup uncertainties were generated, and plan sum was created to simulate the total dose distribution through an entire course and was compared with the original treatment plan. The first phase plan with prescription about 50 Gy was used in this study. Results: Without rotational corrections and with only translational corrections, for PTV, the plan sum showed that the average Vp (prescription dose coverage) was decreased by 5.9%, D95 (dose that covers 95% of target) was decreased 1.8 Gy. For CTV, though the Vp could be decreased by 8% for treatments on selected days, the plan sum showed that the average Vp was decreased by 1.7% and D98 was decreased 0.1 Gy. The average dose increase to spinal cord was 0.7 Gy. Conclusions: With conventional translational setup correction, the overall CTV prescription dose coverage decreases insignificantly because of the 5mm margin from CTV to PTV. The dose increase to spinal cord is not significant. So for HNC IMRT treatment with target margin, the six degree setup correction is not necessary.

Assessing the intrinsic precision of 3D/3D rigid image registration results for patient setup in the absence of a ground truth

To assess the precision and robustness of patient setup corrections computed from 3D/3D rigid registration methods using image intensity, when no ground truth validation is possible. Fifteen pairs of male pelvic CTs were rigidly registered using four different in-house registration methods. Registration results were compared for different resolutions and image content by varying the image down-sampling ratio and by thresholding out soft tissue to isolate bony landmarks. Intrinsic registration precision was investigated by comparing the different methods and by reversing the source and the target roles of the two images being registered. The translational reversibility errors for successful registrations ranged from 0.0 to 1.69 mm. Rotations were less than 1 degrees. Mutual information failed in most registrations that used only bony landmarks. The magnitude of the reversibility error was strongly correlated with the success/ failure of each algorithm to find the global minimum. Rigid image registrations have an intrinsic uncertainty and robustness that depends on the imaging modality, the registration algorithm, the image resolution, and the image content. In the absence of an absolute ground truth, the variation in the shifts calculated by several different methods provides a useful estimate of that uncertainty. The difference observed by reversing the source and target images can be used as an indication of robust convergence.

Comparison of anatomic coordinate systems with rigid multi-resolution 3D registration for the reproducible positioning of analysis volumes of interest in QCT

In this study we compared two approaches that have recently been used to minimize precision errors in 3D quantitative computed tomography (QCT) images of the hip and the spine in order to optimize the detection of longitudinal changes in bone mineral density (BMD). In 30 subjects we obtained baseline and 1 year follow-up 3D CT scans of the proximal femur and the spine. QCT analysis was applied to a variety of volumes of interest (VOIs) automatically positioned relative to anatomic coordinate systems (ACS). In the first approach (A1) baseline and follow-up scans were analyzed independently. In the second approach (A2) a 3D versor-based rigid intensity registration method was applied to match baseline and follow-up images, and the baseline ACS was mapped on the follow-up image using the registration transformation. Afterwards, the analysis VOIs were again independently calculated for baseline and follow-up images. There were no significant differences of percent BMD changes between baseline and follow-up images between A1 and A2 for any of the VOIs investigated. With advanced image processing methods a time-consuming 3D registration between baseline and follow-up images before the analysis does not improve analysis precision compared to the use of anatomical coordinate systems.

Relationship between intended sites of RF ablation and post-procedural scar in AF patients, using late gadolinium enhancement cardiovascular magnetic resonance

Radiofrequency (RF) ablation of the left atrium (LA) in patients with atrial fibrillation (AF) is guided by electroanatomic mapping systems. The cardiovascular magnetic resonance (CMR) late gadolinium enhancement (LGE) technique can detect scar after ablation. Direct comparisons between the locations of intended RF ablation sites and locations of scar formation in the LA have not been performed. This study sought to develop and use a method for comparing the sites of RF application with the sites of post-procedural scar formation in the LA. A method for rigid registration of CMR LGE images with electroanatomic mapping data (Carto data), visualization of the registered data sets, and quantification of the correlations was developed and used in 19 studies of patients with AF. The distance between the Carto points and the CMR LA surface was measured as the mean integration error. The distance between each Carto ablation and the nearest scar was measured. The gaps in sites of LGE and in Carto ablation were also assessed qualitatively, in 6 sectors of each PV. The custom registration method provided a mean integration error between Carto and CMR of 2.7 +/- 0.7 mm. The average distance between Carto and LGE scar was 3.6 +/- 1.3 mm. Qualitatively, 20% of sectors with sites of Carto ablation showed no evidence of LGE. There was a visual and quantitative correspondence between Carto ablation sites and LGE scar, but for 20% of Carto ablation sites there was no visible corresponding LGE.

MRI signal intensity based B‐Spline nonrigid registration for pre‐ and intraoperative imaging during prostate brachytherapy

To apply an intensity-based nonrigid registration algorithm to MRI-guided prostate brachytherapy clinical data and to assess its accuracy. A nonrigid registration of preoperative MRI to intraoperative MRI images was carried out in 16 cases using a Basis-Spline algorithm in a retrospective manner. The registration was assessed qualitatively by experts' visual inspection and quantitatively by measuring the Dice similarity coefficient (DSC) for total gland (TG), central gland (CG), and peripheral zone (PZ), the mutual information (MI) metric, and the fiducial registration error (FRE) between corresponding anatomical landmarks for both the nonrigid and a rigid registration method. All 16 cases were successfully registered in less than 5 min. After the nonrigid registration, DSC values for TG, CG, PZ were 0.91, 0.89, 0.79, respectively, the MI metric was -0.19 +/- 0.07 and FRE presented a value of 2.3 +/- 1.8 mm. All the metrics were significantly better than in the case of rigid registration, as determined by one-sided t-tests. The intensity-based nonrigid registration method using clinical data was demonstrated to be feasible and showed statistically improved metrics when compare to only rigid registration. The method is a valuable tool to integrate pre- and intraoperative images for brachytherapy.

SU‐FF‐T‐88: Image Registration for Real‐Time Dose Calculation of Adaptive Radiation Therapy

Purpose: To enhance the speed and accuracy of certain treatment plan in radiation therapy, a real‐time dose calculation strategy is performed based on Fast Fourier Transformation (FFT) and CT image registration. For this purpose, different registration methods are achieved by using Insight Segmentation and Registration Toolkit (ITK) in MATLAB. Method and materials: Our group developed an efficient method for kernel calculation for pencil beam convolution‐superposition based on FFT. In this paper, different image registration methods are developed in MATLAB by using ITK, such as rigid 3D, similarity 3D, Demons deformation and BSpline based Free Form. As ITK is written and used in a C++ template, smart pointer and generic structure, an open source wrapper MATITK is modified to facilitate the use of its image processing capabilities while working in the high‐level environment of MATLAB. The image registration methods are demonstrated on head and neck (H&N) CT image sets of 6 patients. The results of evaluation and visualization for the registration are presented. Results and discussion: Transformation similarity and computation complexity as evaluation criteria are compared between rigid and deformable registration methods. Judging from the mutual information histogram and mean square metric, the deformable registration will get more improvement on similarity than the rigid registration. Checkerboard composites of the reference and registered images are displayed. The computational time of deformable registration are 10∼20 times longer with the whole set of images because of the pre‐processing, complicated transformation matrix and more parameters. A similarity3D registration method is adopted for the image registration of H&N radiation therapy to trade off between registration effect and the time consumption. Conclusion: The image registration can greatly contribute to the automatic contour adjustment and dose deformation for adaptive radiation therapy. A GUI program will be designed for the customized deformation region to speed up deformable registration.

A Fast Medical 3D Image Registration Method Based on a Parametric Representation

Three dimensional medical image registration is a fundamental technique which applied various medical treatments such as image diagnosis, treatment planning, image guided surgery, etc. In radiation therapy for cancer treatment, quick alignment method around target lesion is required. To align CT images, similarity measurement like normalized cross correlation or mutual information should be calculated. The computational cost must reduce for achieving the online image registration.In this paper, we propose a novel quick rigid registration method which makes it possible to align the three dimensional images using the parametric eigenspace method. By projecting each CT slice image into the eigenspace as a set of low dimensional vectors, image similarity can be calculated very rapidly. The experiments using CT images of the same patient, it is found that the alignment accuracy is almost the same as the method using normalized cross correlation, and the computation time is less than one second.

3D Volumetric Visualization with Automatic Rigid and Deformable Hybrid Image Registration for Adaptive Radiotherapy

To provide more clinically convenient image fusions for adaptive radiotherapy (ART), an automatic rigid and deformable image registration framework (AIRF) is developed for multimodal visualization of multiple chronological images and multiple radiotherapy (RT) plans. Our hybrid image registration framework, AIRF, uses a faster but less accurate rigid registration method to provide an initial registration, followed by a slower but more accurate deformable registration method to fine tune the final registration. A multi-resolution approach is also employed in the image registration process to further improve the registration accuracy, robustness and efficiency. Volume visualization is provided to guide the automatic image registration process because it can reduce the global positioning error that results from a partial 3D visual presentation in the three conventional orthogonal planar views (axial, sagittal, and coronal). The AIRF can automatically align multiple volumetric images of patients taken over an extended period of time and can merge multiple radiotherapy plans based on different planning computed tomography (CT) images. It offers illustrative 3D volumetric visualization, hybrid rigid and deformable image registration, and automatic transfer of RT dose distribution and RT structure models such as treatment targets and organs at risk (OARs) onto chronological images. The AIRF can automatically register multiple volumetric image datasets of patients taken over an extended period of time and can merge multiple RT plans based on different planning CT images for 4D or adaptive radiotherapy.

Can Positron Emission Tomography (PET) or PET/Computed Tomography (CT) Acquired in a Nontreatment Position Be Accurately Registered to a Head-and-Neck Radiotherapy Planning CT?

To quantify the uncertainties associated with incorporating diagnostic positron emission tomography/CT (PET/CT) and PET into the radiotherapy treatment-planning process using different image registration tools, including automated and manual rigid body registration methods, as well as deformable image registration. The PET/CTs and treatment-planning CTs from 12 patients were used to evaluate image registration accuracy. The PET/CTs also were used without the contemporaneously acquired CTs to evaluate the registration accuracy of stand-alone PET. Registration accuracy for relevant normal structures was quantified using an overlap index and differences in the center of mass (COM) positions. For tumor volumes, the registration accuracy was measured using COM positions only. Registration accuracy was better with PET/CT than with PET alone. The COM displacements ranged from 3.2 +/- 0.6 mm (mean +/- 95% confidence interval, for brain) to 8.4 +/- 2.6 mm (spinal cord) for registration with PET/CT data, compared with 4.8 +/- 1.7 mm (brain) and 9.9 +/- 3.1 mm (spinal cord) with PET alone. Deformable registration improved accuracy, with minimum and maximum errors of 1.1 +/- 0.8 mm (brain) and 5.4 +/- 1.4 mm (mandible), respectively. It is possible to incorporate PET and/or PET/CT acquired in diagnostic positions into the treatment-planning process through the use of advanced image registration algorithms, but precautions must be taken, particularly when delineating tumor volumes in the neck. Acquisition of PET/CT in the treatment-planning position would be the ideal method to minimize registration errors.