Surface registration for use in interactive, image-guided liver surgery.

OBJECTIVE: Liver surgery is difficult because of limited external landmarks, significant vascularity, and inexact definition of intra-hepatic anatomy. Intra-operative ultrasound (IOUS) has been widely used in an attempt to overcome these difficulties, but is limited by its two-dimensional nature, inter-user variability, and image obliteration with ablative or resectional techniques. Because the anatomy of the liver and intra-operative removal of hepatic ligaments make intrinsic or extrinsic point-based registration impractical, we have implemented a surface registration technique to map physical space into CT image space, and have tested the accuracy of this method on an anatomical liver phantom with embedded tumor targets. MATERIALS AND METHODS: Liver phantoms were created from anatomically correct molds with "tumors" embedded within the substance of the liver. Helical CT scans were performed with 3-mm slices. Using an optically active position sensor, the surface of the liver was digitized according to anatomical segments. A surface registration was performed and RMS errors of the locations of internal tumors are presented as verification. An initial point-based marker registration was performed and considered the "gold standard" for error measurement. RESULTS: Errors for surface registration were 2.9 mm for the entire surface and 2.8 mm for embedded targets. CONCLUSION: This is an initial study considering the use of surface registration for the purpose of physical-to-image registration in the area of liver surgery.     

Soft tissue scanning for patient registration in image-guided surgery.

Prior to an image-guided surgical intervention, a correlation between the patient's data set and the surgical site is required. This study introduces a markerless registration method for cranio-maxillofacial surgery that is based on a high-resolution laser scan of the patient's skin surface. The Surgical Segment Navigator SSN++ rejects contaminated surface measurements in a way similar to the bluescreen technique. Acquisition of the spatial position and the corresponding surface color of each laser-scanned point facilitates this bluescreen method, removing points with a defined surface color, e.g., blue or green points. The accuracy of the laser-scan-based registration was measured via additional intraoral titanium-markers. These markers served only to check the accuracy of the markerless registration process. In twelve patients, the stability and accuracy of the data set alignment was evaluated for high-(300,000 surface points), medium-, and low-resolution (down to 3,750 surface points) laser scanning. The accuracy of the registration technique was best for high-resolution laser scanning (mean deviation 1.1 mm; maximum deviation 1.8 mm). Low-resolution laser scans revealed inaccuracies up to 6 mm.     

Template-based registration for image-guided skull base surgery

OBJECTIVES: To evaluate whether patient-to-image registration with the use of a maxillary template is sufficiently accurate for image guided skull base surgery. STUDY DESIGN AND SETTING: In an experimental phantom study, pair-point registration of a skull phantom to its CT image data was performed with 243 different configurations of a maxillary template with markers. Then artificial skull mounted target markers were located with an infrared tracking device as used in navigation systems. RESULTS: The average target registration error was 1.57 mm in the anterior skull base (95% confidence interval, 1.53 to 1.61 mm), but 3.31 mm in the lateral skull base (95% confidence interval, 3.26 to 3.37 mm). CONCLUSIONS: Fiducial marker registration based on a maxillary template is sufficiently accurate for image-guided surgery in the anterior skull base, but not for the lateral skull base. SIGNIFICANCE: Template-based registration is an accurate yet noninvasive registration method for frontal skull base surgery.     

Ultrasound-to-computer-tomography registration for image-guided laparoscopic liver surgery

Background The application of image-guided surgery (IGS) to laparoscopic liver resection and ablation is currently limited, but it would assist in intraoperative decision making regarding oncologic margins, ablation probe placement, and ablation tracking.Methods Eight spherical surface targets on a liver phantom were imaged with an optically tracked laparoscopic ultrasound (US) probe. Ten US images of each target were registered to computer tomography (CT) images of the phantoms and then mapped to the CT scans. Accuracy of the registration was assessed by comparing the distance between the predicted target location and the position obtained directly from CT.Results The average localization error was 5.3 mm. The errors resulted primarily from inaccurate US probe tracking but were otherwise insensitive to the variability that arises from manually identifying targets in US and CT images.Conclusions The results obtained for US-to-CT registration in a phantom model suggest that further investigations into its clinical use are warranted and that other IGS technologies could be applied to laparoscopic liver surgery as well.     

Surface-based registration accuracy of CT-based image-guided spine surgery

Registration is a critical and important process in maintaining the accuracy of CT-based image-guided surgery. The aim of this study was to evaluate the effects of the area of intraoperative data sampling and number of sampling points on the accuracy of surface-based registration in a CT-based spinal-navigation system, using an optical three-dimensional localizer. A cadaveric dry-bone phantom of the lumbar spine was used. To evaluate registration accuracy, three alumina ceramic balls were attached to the anterior and lateral aspects of the vertebral body. CT images of the phantom were obtained (1-mm slice thickness, at1-mm intervals) using a helical CT scanner. Twenty surface points were digitized from five zones defined on the basis of anatomical classification on the posterior aspects of the target vertebra. A total of 20 sets of sampling data were obtained. Evaluation of registration accuracy accounted for positional and rotational errors. Of the five zones, the area that was the largest and easiest to expose surgically and to digitize surface points was the lamina. The lamina was defined as standard zone. On this zone, the effect of the number of sampling points on the positional and rotational accuracy of registration was evaluated. And the effects of the additional area selected for intraoperative data sampling on the registration accuracy were evaluated. Using 20 surface points on the posterior side of the lamina, positional error was 0.96 mm±0.24 mm root-mean-square (RMS) and rotational error was 0.91°±0.38°RMS. The use of 20 surface points on the lamina usually allows surgeons to carry out sufficiently accurate registration to conduct computer-aided spine surgery. In the case of severe spondylosis, however, it might be difficult to digitize the surface points from the lamina, due to a hypertrophic facet joint or the deformity of the lamina and noisy sampling data. In such cases, registration accuracy can be improved by combining use of the 20 surface points on the lamina with surface points on other zones, such as on the both sides of the spinous process.Part of this study was presented at the CAOS USA 2000 meeting in Pittsburgh     

A review of image-guided spinal surgery

Image-guided spinal surgery has evolved rapidly in recent years. This review highlights the advances in image-guided spinal surgery during this evolution. The current literature regarding image-guided spinal surgery will be discussed. In addition, several aspects of image-guided spinal surgery will be focused on, including its learning curve and influence on operating room time, as well as its effect on surgeon radiation exposure. The accuracy of instrumentation placement with this technology and current applications will also be addressed.     

Accuracy requirements for image-guided spinal pedicle screw placement

STUDY DESIGN: Accuracy requirement analysis for image-guided pedicle screw placement. OBJECTIVES: To derive theoretical accuracy requirements for image-guided spinal pedicle screw placement. SUMMARY OF BACKGROUND DATA: Underlying causes of inaccuracy in image-guided surgical systems and methods for quantifying this inaccuracy have been studied. However, accuracy requirements for specific spinal surgical procedures have not been delineated. In particular, the accuracy requirements for image-guided spinal pedicle screw placement have not been previously reported. METHODS: A geometric model was developed relating spinal pedicle anatomy to accuracy requirements for image-guided surgery. This model was used to derive error tolerances for pedicle screw placement when using clinically relevant screw diameters in the cervical (3.5 mm), thoracic (5.0 mm), and thoracolumbar spine (6.5 mm). The error tolerances were represented as the permissible rotational and translational deviations from the ideal screw trajectory that would avoid pedicle wall perforation. The relevant dimensions of the pedicle model were extracted from existing morphometric data. RESULTS: As anticipated, accuracy requirements were greatest at spinal levels where the relevant screw diameter approximated the dimensions of the pedicle. These requirements were highest for T5, followed in descending order by T4, T7, T6, T3, T12, L1, T8, T11, C4, L2, C3, T10, C5, T2, T9, C6, L3, C2, T1, C7, L4, and L5. Maximum permissible translational/rotational error tolerances ranged from 0.0 mm/0.0 degrees at T5 to 3.8 mm/12.7 degrees at L5. CONCLUSIONS: These results, obtained by mathematical analysis, demonstrate that extremely high accuracy is necessary to place pedicle screws at certain levels of the spine without perforating the pedicle wall. These accuracy requirements exceed the accuracy of current image-guided surgical systems, based on clinical utility errors reported in the literature. In actual use, however, these systems have been shown to improve the accuracy of pedicle screw placement. This dichotomy indicates that other factors, such as the surgeon's visual and tactile feedback, may be operative.     

The impact of fiducial distribution on headset-based registration in image-guided sinus surgery.

OBJECTIVE: The objective of this study was to assess registration error due to fiducial configuration for the ENT headsets for the CBYON Suite (CBYON, Mountain View, CA) and InstaTrak (GEMS Navigation and Visualization, Waukesha, WI). STUDY DESIGN: Axial CT scans (1-mm slice thickness) were obtained of for 24 cadaveric heads using the CBYON headset and for 23 cadaveric heads using the GEMS headset. The CBYON and GEMS NAV software were used to calculate the fiducial registration error (FRE). Fiducial localization error (FLE) was estimated from FRE. Theoretical target registration error (TRE) was calculated at 11 targets. RESULTS: The FRE for CBYON and GEMS NAV was 0.69 mm and 0.27 mm, respectively. The theoretical TRE for CBYON and GEMS NAV was 0.41 mm and 0.30 mm, respectively. The theoretical TRE was greater at targets posterior in the sinus cavities. CONCLUSION: Theoretical TRE values for both ENT headsets are less than clinically observed TRE. Clinically observed TRE is likely due to repositioning accuracy. EBM rating: B-2.     

Timing of paired points and surface matching registration in three-dimensional (3D) image-guided spinal surgery

Image-guidance can increase the safety and accuracy of spinal instrumentation placement. However, many spine surgeons are reluctant to incorporate spinal image-guidance into their surgical practice due to the perception that it is time-consuming and tedious, especially the task of vertebral registration. The authors evaluated the time required for paired points and surface matching registration when using the BrainLAB (BrainLAB, Westchester, IL) image-guided spine application for spinal surgery cases. The time required to register vertebral segments using paired points and surface matching techniques was assessed in 13 consecutive patients undergoing spinal fusions by the senior author. Overall, 23 vertebral segments were registered spanning from T1 to S1. Note was made of the vertebral segments that required reregistration due to poor accuracy. The average time required to register a single vertebral segment using the paired points and surface matching technique was 117 seconds (1 min 57 s). Average accuracy obtained was 0.9 mm. Inaccurate registration occurred in 3/23 (13%) of the segments requiring a second attempt at registration. In 3/23 (13%) of segments, adequate navigation accuracy was maintained on an adjacent vertebral segment thereby allowing for instrumentation to be placed in that adjacent segment without having to register that segment. Though associated with a learning curve, image-guidance can be used effectively and efficiently in spinal surgery. Average time required for registration of a vertebral segment using the BrainLAB spine application in this study was less than 2 minutes. The average accuracy obtained was 0.9 mm.     

Laser surface scanning for patient registration in intracranial image-guided surgery

OBJECTIVE: To report our clinical experience with a new laser scanning-based technique of surface registration. We performed a prospective study to measure the calculated registration error and the application accuracy of laser surface registration for intracranial image-guided surgery in the clinical setting. METHODS: Thirty-four consecutive patients with different intracranial diseases were scheduled for intracranial image-guided surgery by use of a passive infrared surgical navigation system. Surface registration was performed by use of a Class I laser device that emits a visible laser beam. The Polaris camera system (Northern Digital, Waterloo, ON, Canada) detects the skin reflections of the laser, which the software uses to generate a virtual three-dimensional matrix of the anatomy of each patient. An advanced surface-matching algorithm then matches this virtual three-dimensional matrix to the three-dimensional magnetic resonance therapy data set. Registration error as calculated by the computer was noted. Application accuracy was assessed by use of the localization error for three distant anatomic landmarks. RESULTS: Laser surface registration was successful in all patients. For the surgical field, application accuracy was 2.4 +/- 1.7 mm (range, 1-9 mm). Application accuracy was higher for the surgical field of frontally located lesions (mean, 1.8 +/- 0.8 mm; n = 13) as compared with temporal, parietal, occipital, and infratentorial lesions (mean, 2.8 +/- 2.1 mm; n = 21). CONCLUSION: Laser scanning for surface registration is an accurate, robust, and easy-to-use method of patient registration for image-guided surgery.     

Accuracy of an image-guided navigation system for pelvic surgery based on a multimodality registration object: a cadaver study

Accurate registration of external landmarks is often required for computer-aided surgery. In the study reported here, we investigated the influence of a new externally fixated multimodality registration object (MRO) on the accuracy of an image-guided navigation system in a human cadaver pelvis. With the MRO placed on the ipsilateral anterior superior iliac spine (ASIS), 14 of 17 target points showed a mean deviation (1.1 mm) that was significantly lower than that registered with the MRO on the contralateral ASIS (2.5 mm). In addition, the distance of target points from the MRO and the deviation of target points were highly correlated. This MRO provides a feasible means for achieving improved registration in computer-aided surgery of the pelvis.     

Three-dimensional image registration of phantom vertebrae for image-guided surgery: a preliminary study.

OBJECTIVE: Applications of three-dimensional ultrasound (3D US) are emerging throughout the field of medicine. In this study, tracked, free-hand 3D phantom US images were mapped to computed tomograms (CT) as a development for image-guided surgery (IGS) of the spine. In the operating room, the registration of tracked 3D US images to other imaging modalities, such as CT, could allow the surgeon to identify more precisely the surgical target area prior to the incision. An independent quantitative measure of registration accuracy using a fiducial marker system was provided. METHODS: Three-dimensional free-hand US images of a phantom spine were created by tracking the transducer with an optical sensing system. Two sets of images were acquired from three lumbar vertebrae using 4.5- and 7.5-MHz transducers. These images were then segmented for the extraction of the posterior vertebral surface. Next, a surface-based registration of US to the corresponding segmented CT images was performed. Registration errors were computed as the distance between a set of target points transformed using the experimental transformation and the same set of target points transformed using fiducial markers as a gold standard. RESULTS: Results indicated that alignment of these image sets is feasible using only part of the vertebral surface. In particular, the regions of the spinous process and laminae were used for registration. Target registration errors (TREs) were found to be lowest using the highest resolution CT images. Using the CT scans with 2-mm slice thickness, the TRE was calculated to be 1.33 +/- 0.30 mm for the 7.5-MHz US data set and 2.81 +/- 0.10 mm for the 4.5-MHz US data set. Moreover, residual errors in these surface alignments were 0.69 +/- 0.18 mm and 0.61 +/- 0.20 mm for the 4.5- and 7.5-MHz sets, respectively. CONCLUSION: A rigid, surface-based registration of CT images to phantom spinal US images, acquired with a free-hand, tracked transducer, is achievable with a limited, easily obtainable portion of the vertebral surface.     

Automated fiducial marker detection for patient registration in image-guided neurosurgery.

OBJECTIVE: The registration of applied fiducial markers within the preoperative data is often left to the surgeon, who has to identify and tag the center of each marker. This is both time-consuming and a potential source of error. For this reason, the development of an automated procedure was desirable. In this study, we have investigated the accuracy of a software algorithm for detecting fiducial markers within the navigation data set. The influence of adjustable values for accuracy and threshold on the sensitivity and specificity of the detection process, as well as the time gain, was investigated. PATIENTS AND METHODS: One hundred MP-RAGE MRI data sets of patients with different pathologies who were scheduled for image-guided surgery were used in this study. A total of 591 applied fiducial markers were to be detected using the algorithm of the software VVPlanning 1.3 (BrainLAB, Heimstetten, Germany) on a Pentium II standard PC. The size value of a marker in the y-direction is called "accuracy" and depends on the slice thickness. "Threshold" describes the gray level above which the algorithm starts searching for pixel clusters. The threshold value was changed stepwise on the basis of a constant "accuracy" value. The "accuracy" value was changed on the basis of that threshold value at which all markers were detected correctly. RESULTS: The time needed for automatic detection varied between 12 s and 25 s. An optimum value for adjustable marker size was found to be 1.1 mm, with 8 undetected markers (1.35%) and 7 additionally detected structures (1.18%) out of 591. The mean gray level (Threshold) for all data sets above which marker detection was correct was 248.9. The automatic detection of markers was good for higher gray levels, with 11 missed markers (1.86%). Starting the algorithm at lower gray levels led to a decreased incidence of missed markers (0.17%), but increased the incidence of additionally detected structures to 27.92%. CONCLUSION: The automatic marker-detection algorithm is a robust, fast and objective instrument for reliable fiducial marker registration when used with optimum settings for both threshold and accuracy.     

Endoscopic image-guided transethmoid pituitary surgery.

OBJECTIVE: We describe a new endoscopic transethmoid approach for pituitary surgery and to compare it with other surgical techniques. Study Design and Setting: Eleven patients undergoing pituitary surgery from September 2000 through January 2002 underwent an image-guided endoscopic transethmoid procedure to remove pituitary tumors. Ease of approach, resection, exposure of the surgical field, and operative complications were documented. RESULTS: Endoscopic ethmoidectomy permits enhanced exposure and simplified tumor resection. The use of one nostril to stabilize the endoscope and the other to pass instruments affords a bimanual procedure that avoids the difficulty of small nares and keeping the scope fixed while exchanging instruments. Operative morbidity was low with no significant complications in this pilot study. CONCLUSIONS: This approach opens a generous operative exposure while safely allowing room to endoscopically maneuver and affords direct access should revision surgery be needed. SIGNIFICANCE: This procedure uses a technique familiar to otolaryngologists and may be used for pituitary and other skull base tumors.     

神经根封闭定位在多间隙腰椎管狭窄症手术中的应用

<正>自2008年2月至2010年2月,对筛选的18例多间隙腰椎管狭窄症的患者,术前采用C形臂X线透视下神经根封闭的定位方法,确定责任手术间隙,定位准确,行椎管微减压术后效果满意,现总结如下。