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      Continuous registration based on computed tomography for breathing motion compensation

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          Abstract

          Introduction

          Image guidance for intervention is applied for complex and difficult anatomical regions. Nowadays, it is typically used in neurosurgery, otolaryngology, orthopedics and dentistry. The application of the image-guided system for soft tissues is challenging due to various deformations caused by respiratory motion, tissue elasticity and peristalsis.

          Aim

          The main task for the presented approach is continuous registration of preoperative computed tomography (CT) and patient position in the operating room (OR) without touching the patient and compensation of breathing motion. This approach is being developed as a step to image-guided percutaneous liver RF tumor ablation.

          Material and methods

          Up to ten integrated radiological markers are placed on the patient's skin before CT scans. Then the anatomical model based on CT images is calculated. Point-to-point registration based on the Horn algorithm during a few breathing cycles is performed using a videometric tracking system. The transformation which corresponds to the minimum fiducial registration error (FRE) is found during the registration and it is treated as the initial transformation for calculating local deformation field of breathing motion compensation based on the spline approach.

          Results

          For manual registration of the abdominal phantom, the mean values of target registration error (TRE), fiducial localization error (FLE) and FRE are all below 4 mm for the rigid transformation and are below 1 mm for the affine transformation. For the patient's data they are all below 9 mm and 6 mm, respectively. For the automatic method, different marker configurations have been evaluated while dividing the respiratory cycle into inhale and exhale. Average median values for FRE, TRE rigid estimation and TRE based on spline deformation were 15.56 mm, 0.82 mm and 7.21 mm respectively.

          Conclusions

          In this application two registration methods of abdominal preoperative CT anatomical model and physical patient position in OR were presented and compared. The presented approach is being developed as a step to image-guided percutaneous liver radiofrequency ablation tumor ablation. Implementation of the automated registration method to clinical practice is easier because of shortening of preparation time in OR, no necessity of touching the patient, and no dependency on the physician's experience.

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          Most cited references15

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          Predicting error in rigid-body point-based registration.

          Guidance systems designed for neurosurgery, hip surgery, and spine surgery, and for approaches to other anatomy that is relatively rigid can use rigid-body transformations to accomplish image registration. These systems often rely on point-based registration to determine the transformation, and many such systems use attached fiducial markers to establish accurate fiducial points for the registration, the points being established by some fiducial localization process. Accuracy is important to these systems, as is knowledge of the level of that accuracy. An advantage of marker-based systems, particularly those in which the markers are bone-implanted, is that registration error depends only on the fiducial localization error (FLE) and is thus to a large extent independent of the particular object being registered. Thus, it should be possible to predict the clinical accuracy of marker-based systems on the basis of experimental measurements made with phantoms or previous patients. This paper presents two new expressions for estimating registration accuracy of such systems and points out a danger in using a traditional measure of registration accuracy. The new expressions represent fundamental theoretical results with regard to the relationship between localization error and registration error in rigid-body, point-based registration. Rigid-body, point-based registration is achieved by finding the rigid transformation that minimizes "fiducial registration error" (FRE), which is the root mean square distance between homologous fiducials after registration. Closed form solutions have been known since 1966. The expected value (FRE2) depends on the number N of fiducials and expected squared value of FLE, (FLE-2, but in 1979 it was shown that (FRE2) is approximately independent of the fiducial configuration C. The importance of this surprising result seems not yet to have been appreciated by the registration community: Poor registrations caused by poor fiducial configurations may appear to be good due to a small FRE value. A more critical and direct measure of registration error is the "target registration error" (TRE), which is the distance between homologous points other than the centroids of fiducials. Efforts to characterize its behavior have been made since 1989. Published numerical simulations have shown that (TRE2) is roughly proportional to (FLE2)/N and, unlike (FRE2), does depend in some way on C. Thus, FRE, which is often used as feedback to the surgeon using a point-based guidance system, is in fact an unreliable indicator of registration-accuracy. In this work we derive approximate expressions for (TRE2), and for the expected squared alignment error of an individual fiducial. We validate both approximations through numerical simulations. The former expression can be used to provide reliable feedback to the surgeon during surgery and to guide the placement of markers before surgery, or at least to warn the surgeon of potentially dangerous fiducial placements; the latter expression leads to a surprising conclusion: Expected registration accuracy (TRE) is worst near the fiducials that are most closely aligned! This revelation should be of particular concern to surgeons who may at present be relying on fiducial alignment as an indicator of the accuracy of their point-based guidance systems.
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            Fiducial point placement and the accuracy of point-based, rigid body registration.

            To demonstrate that the shape of the configuration of fiducial points is an important factor governing target registration error (TRE) in point-based, rigid registration. We consider two clinical situations: cranial neurosurgery and pedicle screw placement. For cranial neurosurgery, we apply theoretical results concerning TRE prediction, which we have previously derived and validated, to three hypothetical fiducial marker configurations. We illustrate the profile of expected TRE for each configuration. For pedicle screw placement, we apply the same theory to a common anatomic landmark configuration (tips of spinous and transverse processes) used for pedicle screw placement, and we estimate the error rate expected in placement of the screw. In the cranial neurosurgery example, we demonstrate that relatively small values of TRE may be achieved by using widely spread fiducial markers and/or placing the centroid of the markers near the target. We also demonstrate that near-collinear marker configurations far from the target may result in large TRE values. In the pedicle screw placement example, we demonstrate that the screw must be approximately 4 mm narrower than the pedicle in which it is implanted to minimize the chance of pedicle violation during placement. The placement of fiducial points is an important factor in minimizing the error rate for point-based, rigid registration. By using as many points as possible, avoiding near-collinear configurations, and ensuring that the centroid of the fiducial points is as near as possible to the target, TREs can be minimized.
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              A physics-based coordinate transformation for 3-D image matching.

              Many image matching schemes are based on mapping coordinate locations, such as the locations of landmarks, in one image to corresponding locations in a second image. A new approach to this mapping (coordinate transformation), called the elastic body spline (EBS), is described. The spline is based on a physical model of a homogeneous, isotropic three-dimensional (3-D) elastic body. The model can approximate the way that some physical objects deform. The EBS as well as the affine transformation, the thin plate spline [1], [2] and the volume spline [3] are used to match 3-D magnetic resonance images (MRI's) of the breast that are used in the diagnosis and evaluation of breast cancer. These coordinate transformations are evaluated with different types of deformations and different numbers of corresponding (paired) coordinate locations. In all but one of the cases considered, using the EBS yields more similar images than the other methods.
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                Author and article information

                Journal
                Wideochir Inne Tech Malo Inwazyjne
                Wideochir Inne Tech Malo Inwazyjne
                WIITM
                Videosurgery and other Miniinvasive Techniques
                Termedia Publishing House
                1895-4588
                2299-0054
                18 December 2013
                December 2013
                : 8
                : 4
                : 265-272
                Affiliations
                [1 ]Silesian University of Technology, Katowice, Poland
                [2 ]Second Department of Clinical Radiology, Medical University of Warsaw, Warsaw, Poland
                [3 ]Chair and Department of General, Transplant and Liver Surgery, Medical University of Warsaw, Warsaw, Poland
                Author notes
                Address for correspondence: Dominik Spinczyk MD, PhD, Faculty of Biomedical Engineering, Silesian University of Technology, 66 Charlesa de Gaulle'a St, 41-800 Zabrze, Poland. phone: +48 72 186 43 51. e-mail: dspinczyk@ 123456polsl.pl
                Article
                21933
                10.5114/wiitm.2013.39505
                3908646
                bee9f1a6-9760-47f4-acdf-60c785594eae
                Copyright © 2013 Sekcja Wideochirurgii TChP

                This is an Open Access article distributed under the terms of the Creative Commons Attribution-Noncommercial 3.0 Unported License, permitting all non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

                History
                : 22 July 2013
                : 14 September 2013
                : 24 November 2013
                Categories
                Original Paper

                Surgery
                percutaneous ablation,preoperative anatomical model registration,respiratory motion compensation,image-guided intervention

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