Stereovision to MR image registration for cortical surface displacement mapping to enhance image-guided neurosurgery

Model-based image updating in deep brain stimulation with assimilation of deep brain sparse data

BACKGROUND

Accuracy of electrode placement for deep brain stimulation (DBS) is critical to achieving desired surgical outcomes and impacts the efficacy of treating neurodegenerative diseases. Intraoperative brain shift degrades the accuracy of surgical navigation based on preoperative images.

PURPOSE

We extended a model-based image updating scheme to address intraoperative brain shift in DBS surgery and improved its accuracy in deep brain.

METHODS

We evaluated 10 patients, retrospectively, who underwent bilateral DBS surgery and classified them into groups of large and small deformation based on a 2 mm subsurface movement threshold and brain shift index of 5%. In each case, sparse brain deformation data were used to estimate whole brain displacements and deform preoperative CT (preCT) to generate updated CT (uCT). Accuracy of uCT was assessed using target registration errors (TREs) at the Anterior Commissure (AC), Posterior Commissure (PC), and four calcification points in the sub-ventricular area by comparing their locations in uCT with their ground truth counterparts in postoperative CT (postCT).

RESULTS

In the large deformation group, TREs were reduced from 2.5 mm in preCT to 1.2 mm in uCT (53% compensation); in the small deformation group, errors were reduced from 1.25 to 0.74 mm (41%). Average reduction of TREs at AC, PC and pineal gland were significant, statistically (p ⩽ 0.01).

CONCLUSIONS

With more rigorous validation of model results, this study confirms the feasibility of improving the accuracy of model-based image updating in compensating for intraoperative brain shift during DBS procedures by assimilating deep brain sparse data.

Perspective review on applications of optics in skull base surgery

The use of optic technology in skull base surgeries has the potential to revolutionize the field of medicine, particularly neurosurgery and neurology. Here, we briefly present the past, present, and future of skull-base surgery, with an emphasis on the applications of optical topography techniques. We discuss optical topography techniques such as functional near-infrared spectroscopy, optical diffusion tomography, and optical topographical imaging. Optical topography techniques are particularly advantageous when combined with other imaging methods. For instance, optical topography can be combined with techniques such as functional magnetic resonance imaging (fMRI) to combine the temporal resolution of optical topography with the spatial resolution of fMRI. Multimodal approaches will be critical to advance brain-related research as well as medicine. Structured light imaging techniques are also writing the future of 3-dimensional imaging. In short, optical topography can allow for non-invasive, high-resolution imaging that will provide real-time visualizations of the brain that are ideal for neurosurgery. From the limitations of traditional skull base surgeries to the newest developments in optical neuroimaging, here we will discuss the potential applications of optics in skull base procedures.

In situ tissue pathology from spatially encoded mass spectrometry classifiers visualized in real time through augmented reality

Integration between a hand-held mass spectrometry desorption probe based on picosecond infrared laser technology (PIRL-MS) and an optical surgical tracking system demonstrates in situ tissue pathology from point-sampled mass spectrometry data. Spatially encoded pathology classifications are displayed at the site of laser sampling as color-coded pixels in an augmented reality video feed of the surgical field of view. This is enabled by two-way communication between surgical navigation and mass spectrometry data analysis platforms through a custom-built interface. Performance of the system was evaluated using murine models of human cancers sampled in situ in the presence of body fluids with a technical pixel error of 1.0 ± 0.2 mm, suggesting a 84% or 92% (excluding one outlier) cancer type classification rate across different molecular models that distinguish cell-lines of each class of breast, brain, head and neck murine models. Further, through end-point immunohistochemical staining for DNA damage, cell death and neuronal viability, spatially encoded PIRL-MS sampling is shown to produce classifiable mass spectral data from living murine brain tissue, with levels of neuronal damage that are comparable to those induced by a surgical scalpel. This highlights the potential of spatially encoded PIRL-MS analysis for in vivo use during neurosurgical applications of cancer type determination or point-sampling in vivo tissue during tumor bed examination to assess cancer removal. The interface developed herein for the analysis and the display of spatially encoded PIRL-MS data can be adapted to other hand-held mass spectrometry analysis probes currently available.

Integration between a hand-held mass spectrometry desorption probe based on picosecond infrared laser technology (PIRL-MS) and an optical surgical tracking system demonstrates in situ tissue pathology from point-sampled mass spectrometry data.

Image Updating for Brain Shift Compensation During Resection

BACKGROUND

In open-cranial neurosurgery, preoperative magnetic resonance (pMR) images are typically coregistered for intraoperative guidance. Their accuracy can be significantly degraded by intraoperative brain deformation, especially when resection is involved.

OBJECTIVE

To produce model updated MR (uMR) images to compensate for brain shift that occurred during resection, and evaluate the performance of the image-updating process in terms of accuracy and computational efficiency.

METHODS

In 14 resection cases, intraoperative stereovision image pairs were acquired after dural opening and during resection to generate displacement maps of the surgical field. These data were assimilated by a biomechanical model to create uMR volumes of the evolving surgical field. A tracked stylus provided independent measurements of feature locations to quantify target registration errors (TREs) in the original coregistered pMR and uMR as surgery progressed.

RESULTS

Updated MR TREs were 1.66 ± 0.27 and 1.92 ± 0.49 mm in the 14 cases after dural opening and after partial resection, respectively, compared to 8.48 ± 3.74 and 8.77 ± 4.61 mm for pMR, respectively. The overall computational time for generating uMRs after partial resection was less than 10 min.

CONCLUSION

We have developed an image-updating system to compensate for brain deformation during resection using a computational model with data assimilation of displacements measured with intraoperative stereovision imaging that maintains TREs less than 2 mm on average.

Stereovision Co-Registration in Image-Guided Spinal Surgery: Accuracy Assessment Using Explanted Porcine Spines

BACKGROUND

Current methods of spine registration for image guidance have a variety of limitations related to accuracy, efficiency, and cost.

OBJECTIVE

To define the accuracy of stereovision-mediated co-registration of a spinal surgical field.

METHODS

A total of 10 explanted porcine spines were used. Dorsal soft tissue was removed to a variable degree. Bone screw fiducials were placed in each spine and high-resolution computed tomography (CT) scanning performed. Stereoscopic images were then obtained using a tracked, calibrated stereoscopic camera system; images were processed, reconstructed, and segmented in a semi-automated manner. A multistart registration of the reconstructed spinal surface with preoperative CT was performed. Target registration error (TRE) in the region of the laminae and facets was then determined, using bone screw fiducials not included in the original registration process. Each spine also underwent multilevel laminectomy, and TRE was then recalculated for varying amounts of bone removal.

RESULTS

The mean TRE of stereovision registration was 2.19 ± 0.69 mm when all soft tissue was removed and 2.49 ± 0.74 mm when limited soft tissue removal was performed. Accuracy of the registration process was not adversely affected by laminectomy.

CONCLUSION

Stereovision offers a promising means of registering an open, dorsal spinal surgical field. In this study, overall mean accuracy of the registration was 2.21 mm, even when bony anatomy was partially obscured by soft tissue or when partial midline laminectomy had been performed.

Use of Stereovision for Intraoperative Coregistration of a Spinal Surgical Field: A Human Feasibility Study

BACKGROUND

The use of image guidance during spinal surgery has been limited by several anatomic factors such as intervertebral segment motion and ineffective spine immobilization. In its current form, the surgical field is coregistered with a preoperative computed tomography (CT), often obtained in a different spinal confirmation, or with intraoperative cross-sectional imaging. Stereovision offers an alternative method of registration.

OBJECTIVE

To demonstrate the feasibility of stereovision-mediated coregistration of a human spinal surgical field using a proof-of-principle study, and to provide preliminary assessments of the technique's accuracy.

METHODS

A total of 9 subjects undergoing image-guided pedicle screw placement also underwent stereovision-mediated coregistration with preoperative CT imaging. Stereoscopic images were acquired using a tracked, calibrated stereoscopic camera system mounted on an operating microscope. Images were processed, reconstructed, and segmented in a semi-automated manner. A multistart registration of the reconstructed spinal surface with preoperative CT was performed. Registration accuracy, measured as surface-to-surface distance error, was compared between stereovision registration and a standard registration.

RESULTS

The mean surface reconstruction error of the stereovision-acquired surface was 2.20 ± 0.89 mm. Intraoperative coregistration with stereovision was performed with a mean error of 1.48 ± 0.35 mm compared to 2.03 ± 0.28 mm using a standard point-based registration method. The average computational time for registration with stereovision was 95 ± 46 s (range 33-184 s) vs 10to 20 min for standard point-based registration.

CONCLUSION

Semi-automated registration of a spinal surgical field using stereovision is possible with accuracy that is at least comparable to current landmark-based techniques.

Red-light excitation of protoporphyrin IX fluorescence for subsurface tumor detection

OBJECTIVE The objective of this study was to detect 5-aminolevulinic acid (ALA)-induced tumor fluorescence from glioma below the surface of the surgical field by using red-light illumination. METHODS To overcome the shallow tissue penetration of blue light, which maximally excites the ALA-induced fluorophore protoporphyrin IX (PpIX) but is also strongly absorbed by hemoglobin and oxyhemoglobin, a system was developed to illuminate the surgical field with red light (620-640 nm) matching a secondary, smaller absorption peak of PpIX and detecting the fluorescence emission through a 650-nm longpass filter. This wide-field spectroscopic imaging system was used in conjunction with conventional blue-light fluorescence for comparison in 29 patients undergoing craniotomy for resection of high-grade glioma, low-grade glioma, meningioma, or metastasis. RESULTS Although, as expected, red-light excitation is less sensitive to PpIX in exposed tumor, it did reveal tumor at a depth up to 5 mm below the resection bed in 22 of 24 patients who also exhibited PpIX fluorescence under blue-light excitation during the course of surgery. CONCLUSIONS Red-light excitation of tumor-associated PpIX fluorescence below the surface of the surgical field can be achieved intraoperatively and enables detection of subsurface tumor that is not visualized under conventional blue-light excitation. Clinical trial registration no.: NCT02191488 (clinicaltrials.gov).

Hyperspectral data processing improves PpIX contrast during fluorescence guided surgery of human brain tumors

Fluorescence guided surgery (FGS) using aminolevulinic-acid (ALA) induced protoporphyrin IX (PpIX) provides intraoperative visual contrast between normal and malignant tissue during resection of high grade gliomas. However, maps of the PpIX biodistribution within the surgical field based on either visual perception or the raw fluorescence emissions can be masked by background signals or distorted by variations in tissue optical properties. This study evaluates the impact of algorithmic processing of hyperspectral imaging acquisitions on the sensitivity and contrast of PpIX maps. Measurements in tissue-simulating phantoms showed that (I) spectral fitting enhanced PpIX sensitivity compared with visible or integrated fluorescence, (II) confidence-filtering automatically determined the lower limit of detection based on the strength of the PpIX spectral signature in the collected emission spectrum (0.014–0.041 μg/ml in phantoms), and (III) optical-property corrected PpIX estimates were more highly correlated with independent probe measurements (r = 0.98) than with spectral fitting alone (r = 0.91) or integrated fluorescence (r = 0.82). Application to in vivo case examples from clinical neurosurgeries revealed changes to the localization and contrast of PpIX maps, making concentrations accessible that were not visually apparent. Adoption of these methods has the potential to maintain sensitive and accurate visualization of PpIX contrast over the course of surgery.

Intraoperative Imaging Modalities and Compensation for Brain Shift in Tumor Resection Surgery

Intraoperative brain shift during neurosurgical procedures is a well-known phenomenon caused by gravity, tissue manipulation, tumor size, loss of cerebrospinal fluid (CSF), and use of medication. For the use of image-guided systems, this phenomenon greatly affects the accuracy of the guidance. During the last several decades, researchers have investigated how to overcome this problem. The purpose of this paper is to present a review of publications concerning different aspects of intraoperative brain shift especially in a tumor resection surgery such as intraoperative imaging systems, quantification, measurement, modeling, and registration techniques. Clinical experience of using intraoperative imaging modalities, details about registration, and modeling methods in connection with brain shift in tumor resection surgery are the focuses of this review. In total, 126 papers regarding this topic are analyzed in a comprehensive summary and are categorized according to fourteen criteria. The result of the categorization is presented in an interactive web tool. The consequences from the categorization and trends in the future are discussed at the end of this work.

Intraoperative image updating for brain shift following dural opening

OBJECTIVE Preoperative magnetic resonance images (pMR) are typically coregistered to provide intraoperative navigation, the accuracy of which can be significantly compromised by brain deformation. In this study, the authors generated updated MR images (uMR) in the operating room (OR) to compensate for brain shift due to dural opening, and evaluated the accuracy and computational efficiency of the process. METHODS In 20 open cranial neurosurgical cases, a pair of intraoperative stereovision (iSV) images was acquired after dural opening to reconstruct a 3D profile of the exposed cortical surface. The iSV surface was registered with pMR to detect cortical displacements that were assimilated by a biomechanical model to estimate whole-brain nonrigid deformation and produce uMR in the OR. The uMR views were displayed on a commercial navigation system and compared side by side with the corresponding coregistered pMR. A tracked stylus was used to acquire coordinate locations of features on the cortical surface that served as independent positions for calculating target registration errors (TREs) for the coregistered uMR and pMR image volumes. RESULTS The uMR views were visually more accurate and well aligned with the iSV surface in terms of both geometry and texture compared with pMR where misalignment was evident. The average misfit between model estimates and measured displacements was 1.80 ± 0.35 mm, compared with the average initial misfit of 7.10 ± 2.78 mm between iSV and pMR, and the average TRE was 1.60 ± 0.43 mm across the 20 patients in the uMR image volume, compared with 7.31 ± 2.82 mm on average in the pMR cases. The iSV also proved to be accurate with an average error of 1.20 ± 0.37 mm. The overall computational time required to generate the uMR views was 7-8 minutes. CONCLUSIONS This study compensated for brain deformation caused by intraoperative dural opening using computational model-based assimilation of iSV cortical surface displacements. The uMR proved to be more accurate in terms of model-data misfit and TRE in the 20 patient cases evaluated relative to pMR. The computational time was acceptable (7-8 minutes) and the process caused minimal interruption of surgical workflow.

Patient Registration Using Intraoperative Stereovision in Image-guided Open Spinal Surgery

Despite its widespread availability and success in open cranial neurosurgery, image-guidance technology remains more limited in use in open spinal procedures, in large part, because of patient registration challenges. In this study, we evaluated the feasibility of using intraoperative stereovision (iSV) for accurate, efficient, and robust patient registration in an open spinal fusion surgery. Geometrical surfaces of exposed vertebrae were first reconstructed from iSV. A classical multistart registration was then executed between point clouds generated from iSV and preoperative computed tomography images of the spine. With two pairs of feature points manually identified to facilitate the registration, an average registration accuracy of 1.43 mm in terms of surface-to-surface distance error was achieved in eight patient cases using a single iSV image pair sampling 2-3 vertebral segments. The iSV registration error was consistently smaller than the conventional landmark approach for every case (average of 2.02 mm with the same error metric). The large capture ranges (average of 23.8 mm in translation and 46.0° in rotation) found in the iSV patient registration suggest the technique may offer sufficient robustness for practical application in the operating room. Although some manual effort was still necessary, the manually-derived inputs for iSV registration only needed to be approximate as opposed to be precise and accurate for the manual efforts required in landmark registration. The total computational cost of the iSV registration was 1.5 min on average, significantly less than the typical ∼30 min required for the landmark approach. These findings support the clinical feasibility of iSV to offer accurate, efficient, and robust patient registration in open spinal surgery, and therefore, its potential to further increase the adoption of image guidance in this surgical specialty.

Intraoperative fiducial-less patient registration using volumetric 3D ultrasound: a prospective series of 32 neurosurgical cases

OBJECT

Fiducial-based registration (FBR) is used widely for patient registration in image-guided neurosurgery. The authors of this study have developed an automatic fiducial-less registration (FLR) technique to find the patient-to-image transformation by directly registering 3D ultrasound (3DUS) with MR images without incorporating prior information. The purpose of the study was to evaluate the performance of the FLR technique when used prospectively in the operating room and to compare it with conventional FBR.

METHODS

In 32 surgical patients who underwent conventional FBR, preoperative T1-weighted MR images (pMR) with attached fiducial markers were acquired prior to surgery. After craniotomy but before dural opening, a set of 3DUS images of the brain volume was acquired. A 2-step registration process was executed immediately after image acquisition: 1) the cortical surfaces from pMR and 3DUS were segmented, and a multistart sum-of-squared-intensity-difference registration was executed to find an initial alignment between down-sampled binary pMR and 3DUS volumes; and 2) the alignment was further refined by a mutual information-based registration between full-resolution grayscale pMR and 3DUS images, and a patient-to-image transformation was subsequently extracted.

RESULTS

To assess the accuracy of the FLR technique, the following were quantified: 1) the fiducial distance error (FDE); and 2) the target registration error (TRE) at anterior commissure and posterior commissure locations; these were compared with conventional FBR. The results showed that although the average FDE (6.42 ± 2.05 mm) was higher than the fiducial registration error (FRE) from FBR (3.42 ± 1.37 mm), the overall TRE of FLR (2.51 ± 0.93 mm) was lower than that of FBR (5.48 ± 1.81 mm). The results agreed with the intent of the 2 registration techniques: FBR is designed to minimize the FRE, whereas FLR is designed to optimize feature alignment and hence minimize TRE. The overall computational cost of FLR was approximately 4-5 minutes and minimal user interaction was required.

CONCLUSIONS

Because the FLR method directly registers 3DUS with MR by matching internal image features, it proved to be more accurate than FBR in terms of TRE in the 32 patients evaluated in this study. The overall efficiency of FLR in terms of the time and personnel involved is also improved relative to FBR in the operating room, and the method does not require additional image scans immediately prior to surgery. The performance of FLR and these results suggest potential for broad clinical application.