Fully Automated Registration of Intraoperative Computed Tomography Image Data for Image-Guided Craniofacial Surgery

A novel bone registration method using impression molding and structured-light 3D scanning technology

Accurate bone registration is critical for computer navigation and robotic surgery. Existing registration systems are expensive, cumbersome, limited in accuracy and/or require intraoperative radiation. We recently reported a novel method of registration utilizing an inexpensive, compact, and X-ray-free structured-light 3D scanner. However, this technique is not always practical in a real surgical setting where soft tissue and blood can obstruct the continuous line-of-sight required for structured-light technology. We sought to remedy these limitations using a novel technique using rapid-setting impression molding to capture bone surface features and scan the undersurface of the mold with a structured-light scanner. The photonegative of this mold is compared to the preoperative computed tomography (CT)-scan to register the bone. A registration accuracy study was conducted on 36 CT-scanned femur sawbones, simulating typical exposure in hip/knee arthroplasty and bone tumor surgery. A cadaver experiment was also conducted to evaluate the feasibility of using the impression molding in a more realistic operating room setting. The registration accuracy of the proposed technique was 0.50 ± 0.19 mm. This was close to the reported accuracy of 0.43 ± 0.18 mm using a structured-light scanner without impression molding (p = 0.085). In comparison, historical values for "paired-point" and intraoperative CT image-based registration methods currently used in modern robotic/computer-navigation systems were 0.68 ± 0.14 mm (p = 0.004) and 0.86 ± 0.38 mm, respectively. The registration accuracy of the cadaver experiment was consistent with that of sawbone experiments. Although future studies are needed to extend to human subjects, this study shows that the impression molding method can produce comparable or better registration accuracy than the existing techniques.

Microscope-Based Augmented Reality with Intraoperative Computed Tomography-Based Navigation for Resection of Skull Base Meningiomas in Consecutive Series of 39 Patients

Background: The aim of surgery for skull base meningiomas is maximal resection with minimal damage to the involved cranial nerves and cerebral vessels; thus, implementation of technologies for improved orientation in the surgical field, such as neuronavigation and augmented reality (AR), is of interest. Methods: Included in the study were 39 consecutive patients (13 male, 26 female, mean age 64.08 ± 13.5 years) who underwent surgery for skull base meningiomas using microscope-based AR and automatic patient registration using intraoperative computed tomography (iCT). Results: Most common were olfactory meningiomas (6), cavernous sinus (6) and clinoidal (6) meningiomas, meningiomas of the medial (5) and lateral (5) sphenoid wing and meningiomas of the sphenoidal plane (5), followed by suprasellar (4), falcine (1) and middle fossa (1) meningiomas. There were 26 patients (66.6%) who underwent gross total resection (GTR) of the meningioma. Automatic registration applying iCT resulted in high accuracy (target registration error, 0.82 ± 0.37 mm). The effective radiation dose of the registration iCT scans was 0.58 ± 1.05 mSv. AR facilitated orientation in the resection of skull base meningiomas with encasement of cerebral vessels and compression of the optic chiasm, as well as in reoperations, increasing surgeon comfort. No injuries to critical neurovascular structures occurred. Out of 35 patients who lived to follow-up, 33 could ambulate at their last presentation. Conclusion: A microscope-based AR facilitates surgical orientation for resection of skull base meningiomas. Registration accuracy is very high using automatic registration with intraoperative imaging.

Report on a novel bone registration method: A rapid, accurate, and radiation-free technique for computer- and robotic-assisted orthopedic surgeries

Introduction

Computer- and robotic-assisted technologies have recently been introduced into orthopedic surgery to improve accuracy. Each requires intraoperative "bone registration," but existing methods are time consuming, often inaccurate, and/or require bulky and costly equipment that produces substantial radiation.

Methods

We developed a novel method of bone registration using a compact 3D structured light surface scanner that can scan thousands of points simultaneously without any ionizing radiation.Visible light is projected in a specific pattern onto a 3 × 3 cm² area of exposed bone, which deforms the pattern in a way determined by the local bone geometry. A quantitative analysis reconstructs this local geometry and compares it to the preoperative imaging, thereby effecting rapid bone registration.A registration accuracy study using our novel method was conducted on 24 CT-scanned femur Sawbones®. We simulated exposures typically seen during knee/hip arthroplasty and common bone tumor resections. The registration accuracy of our technique was quantified by measuring the discrepancy of known points (i.e., pre-drilled holes) on the bone.

Results

Our technique demonstrated a registration accuracy of 0.44 ± 0.22 mm. This compared favorably with literature-reported values of 0.68 ± 0.14 mm (p-value = 0.001) for the paired-point technique¹³ and 0.86 ± 0.38 mm for the intraoperative CT based techniques ¹⁴ (not enough reported data to calculate p-value).

Conclusion

We have developed a novel method of bone registration for computer and robotic-assisted surgery using 3D surface scanning technology that is rapid, compact, and radiation-free. We have demonstrated increased accuracy compared to existing methods (using historical controls).

Reliable navigation registration in cranial and spine surgery based on intraoperative computed tomography

OBJECTIVE

Low registration errors are an important prerequisite for reliable navigation, independent of its use in cranial or spinal surgery. Regardless of whether navigation is used for trajectory alignment in biopsy or implant procedures, or for sophisticated augmented reality applications, all depend on a correct registration of patient space and image space. In contrast to fiducial, landmark, or surface matching–based registration, the application of intraoperative imaging allows user-independent automatic patient registration, which is less error prone. The authors’ aim in this paper was to give an overview of their experience using intraoperative CT (iCT) scanning for automatic registration with a focus on registration accuracy and radiation exposure.

METHODS

A total of 645 patients underwent iCT scanning with a 32-slice movable CT scanner in combination with navigation for trajectory alignment in biopsy and implantation procedures (n = 222) and for augmented reality (n = 437) in cranial and spine procedures (347 craniotomies and 42 transsphenoidal, 56 frameless stereotactic, 59 frame-based stereotactic, and 141 spinal procedures). The target registration error was measured using skin fiducials that were not part of the registration procedure. The effective dose was calculated by multiplying the dose length product with conversion factors.

RESULTS

Among all 1281 iCT scans obtained, 1172 were used for automatic patient registration (645 initial registration scans and 527 repeat iCT scans). The overall mean target registration error was 0.86 ± 0.38 mm (± SD) (craniotomy, 0.88 ± 0.39 mm; transsphenoidal, 0.92 ± 0.39 mm; frameless, 0.74 ± 0.39 mm; frame-based, 0.84 ± 0.34 mm; and spinal, 0.80 ± 0.28 mm). Compared with standard diagnostic scans, a distinct reduction of the effective dose could be achieved using low-dose protocols for the initial registration scan with mean effective doses of 0.06 ± 0.04 mSv for cranial, 0.50 ± 0.09 mSv for cervical, 4.12 ± 2.13 mSv for thoracic, and 3.37 ± 0.93 mSv for lumbar scans without impeding registration accuracy.

CONCLUSIONS

Reliable automatic patient registration can be achieved using iCT scanning. Low-dose protocols ensured a low radiation exposure for the patient. Low-dose scanning had no negative effect on navigation accuracy.

Intraoperative computed tomography as reliable navigation registration device in 200 cranial procedures

BACKGROUND

Registration accuracy is a main factor influencing overall navigation accuracy. Standard fiducial- or landmark-based patient registration is user dependent and error-prone. Intraoperative imaging offers the possibility for user-independent patient registration. The aim of this paper is to evaluate our initial experience applying intraoperative computed tomography (CT) for navigation registration in cranial neurosurgery, with a special focus on registration accuracy and effective radiation dose.

METHODS

A total of 200 patients (141 craniotomy, 19 transsphenoidal, and 40 stereotactic burr hole procedures) were investigated by intraoperative CT applying a 32-slice movable CT scanner, which was used for automatic navigation registration. Registration accuracy was measured by at least three skin fiducials that were not part of the registration process.

RESULTS

Automatic registration resulted in high registration accuracy (mean registration error: 0.93 ± 0.41 mm). Implementation of low-dose scanning protocols did not impede registration accuracy (registration error applying the full dose head protocol: 0.87 ± 0.36 mm vs. the low dose sinus protocol 0.72 ± 0.43 mm) while a reduction of the effective radiation dose by a factor of 8 could be achieved (mean effective radiation dose head protocol: 2.73 mSv vs. sinus protocol: 0.34 mSv).

CONCLUSION

Intraoperative CT allows highly reliable navigation registration with low radiation exposure.

Vision-based markerless registration using stereo vision and an augmented reality surgical navigation system: a pilot study

Background

This study evaluated the use of an augmented reality navigation system that provides a markerless registration system using stereo vision in oral and maxillofacial surgery.

Method

A feasibility study was performed on a subject, wherein a stereo camera was used for tracking and markerless registration. The computed tomography data obtained from the volunteer was used to create an integral videography image and a 3-dimensional rapid prototype model of the jaw. The overlay of the subject’s anatomic site and its 3D-IV image were displayed in real space using a 3D-AR display. Extraction of characteristic points and teeth matching were done using parallax images from two stereo cameras for patient-image registration.

Results

Accurate registration of the volunteer’s anatomy with IV stereoscopic images via image matching was done using the fully automated markerless system, which recognized the incisal edges of the teeth and captured information pertaining to their position with an average target registration error of < 1 mm. These 3D-CT images were then displayed in real space with high accuracy using AR. Even when the viewing position was changed, the 3D images could be observed as if they were floating in real space without using special glasses.

Conclusion

Teeth were successfully used for registration via 3D image (contour) matching. This system, without using references or fiducial markers, displayed 3D-CT images in real space with high accuracy. The system provided real-time markerless registration and 3D image matching via stereo vision, which, combined with AR, could have significant clinical applications.

Electronic supplementary material

The online version of this article (doi:10.1186/s12880-015-0089-5) contains supplementary material, which is available to authorized users.

Intraoperative patient registration using volumetric true 3D ultrasound without fiducials

PURPOSE

Accurate patient registration is crucial for effective image-guidance in open cranial surgery. Typically, it is accomplished by matching skin-affixed fiducials manually identified in the operating room (OR) with their counterparts in the preoperative images, which not only consumes OR time and personnel resources but also relies on the presence (and subsequent fixation) of the fiducials during the preoperative scans (until the procedure begins). In this study, the authors present a completely automatic, volumetric image-based patient registration technique that does not rely on fiducials by registering tracked (true) 3D ultrasound (3DUS) directly with preoperative magnetic resonance (MR) images.

METHODS

Multistart registrations between binary 3DUS and MR volumes were first executed to generate an initial starting point without incorporating prior information on the US transducer contact point location or orientation for subsequent registration between grayscale 3DUS and MR via maximization of either mutual information (MI) or correlation ratio (CR). Patient registration was then computed through concatenation of spatial transformations.

RESULTS

In ten (N = 10) patient cases, an average fiducial (marker) distance error (FDE) of 5.0 mm and 4.3 mm was achieved using MI or CR registration (FDE was smaller with CR vs MI in eight of ten cases), which are comparable to values reported for typical fiducial- or surface-based patient registrations. The translational and rotational capture ranges were found to be 24.0 mm and 27.0° for binary registrations (up to 32.8 mm and 36.4°), 12.2 mm and 25.6° for MI registrations (up to 18.3 mm and 34.4°), and 22.6 mm and 40.8° for CR registrations (up to 48.5 mm and 65.6°), respectively. The execution time to complete a patient registration was 12-15 min with parallel processing, which can be significantly reduced by confining the 3DUS transducer location to the center of craniotomy in MR before registration (an execution time of 5 min is achievable).

CONCLUSIONS

Because common features deep in the brain and throughout the surgical volume of interest are used, intraoperative fiducial-less patient registration is possible on-demand, which is attractive in cases where preoperative patient registration is compromised (e.g., from loss∕movement of skin-affixed fiducials) or not possible (e.g., in cases of emergency when external fiducials were not placed in time). CR registration was more robust than MI (capture range about twice as big) and appears to be more accurate, although both methods are comparable to or better than fiducial-based registration in the patient cases evaluated. The results presented here suggest that 3DUS image-based patient registration holds promise for clinical application in the future.