Keith D. Paulsen

Review of Neurosurgical Fluorescence Imaging Methodologies

Fluorescence imaging in neurosurgery has a long historical development, with various biomarkers and biochemical agents being used, and numerous technological approaches. This review focuses on contrast agents, summarizing endogenous fluorescence, exogenously stimulated fluorescence, and exogenous contrast agents, and then on tools used for imaging. It ends with a summary of key clinical trials that lead to consensus studies. The practical utility of protoporphyrin IX (PpIX) as stimulated by administration of δ-aminolevulinic acid has had substantial pilot clinical studies and basic science research completed. Recently, multicenter clinical trials using PpIX fluorescence to guide resection have shown efficacy for improved short-term survival. Exogenous agents are being developed and tested preclinically, and hopefully hold the potential for long-term survival benefit if they provide additional capabilities for resection of microinvasive disease or certain tumor subtypes that do not produce PpIX or help delineate low-grade tumors. The range of technologies used for measurement and imaging varies widely, with most clinical trials being carried out with either point probes or modified surgical microscopes. Currently, optimized probe approaches are showing efficacy in clinical trials, and fully commercialized imaging systems are emerging, which will clearly help to lead adoption into neurosurgical practice.

Combined fluorescence and reflectance spectroscopy for in vivo quantification of cancer biomarkers in low- and high-grade glioma surgery

Biomarkers are indicators of biological processes and hold promise for the diagnosis and treatment of disease. Gliomas represent a heterogeneous group of brain tumors with marked intra- and inter-tumor variability. The extent of surgical resection is a significant factor influencing post-surgical recurrence and prognosis. Here, we used fluorescence and reflectance spectral signatures for in vivo quantification of multiple biomarkers during glioma surgery, with fluorescence contrast provided by exogenously-induced protoporphyrin IX (PpIX) following administration of 5-aminolevulinic acid. We performed light-transport modeling to quantify multiple biomarkers indicative of tumor biological processes, including the local concentration of PpIX and associated photoproducts, total hemoglobin concentration, oxygen saturation, and optical scattering parameters. We developed a diagnostic algorithm for intra-operative tissue delineation that accounts for the combined tumor-specific predictive capabilities of these quantitative biomarkers. Tumor tissue delineation achieved accuracies of up to 94% (specificity = 94%, sensitivity = 94%) across a range of glioma histologies beyond current state-of-the-art optical approaches, including state-of-the-art fluorescence image guidance. This multiple biomarker strategy opens the door to optical methods for surgical guidance that use quantification of well-established neoplastic processes. Future work would seek to validate the predictive power of this proof-of-concept study in a separate larger cohort of patients.

Estimation of brain deformation for volumetric image updating in protoporphyrin IX fluorescence-guided resection.

Introduction: Fluorescence-guided resection (FGR) of brain tumors is an intuitive, practical and emerging technology for visually delineating neoplastic tissue exposed intraoperatively. Image guidance is the standard technique for producing 3-dimensional spatially coregistered information for surgical decision making. Both technologies together are synergistic: the former detects surface fluorescence as a biomarker of the current surgical margin while the latter shows coregistered volumetric neuroanatomy but can be degraded by intraoperative brain shift. We present the implementation of deformation modeling for brain shift compensation in protoporphyrin IX FGR, integrating these two sources of information for maximum surgical benefit. Methods: Two patients underwent FGR coregistered with conventional image guidance. Histopathological analysis, intraoperative fluorescence and image space coordinates were recorded for biopsy specimens acquired during surgery. A biomechanical brain deformation model driven by intraoperative ultrasound data was used to generate updated MR images. Results: Combined use of fluorescence signatures and updated MR image information showed substantially improved accuracy compared to fluorescence or the original (i.e., nonupdated) MR images, detecting only true positives and true negatives, and no instances of false positives or false negatives. Conclusion: Implementation of brain deformation modeling in FGR shows promise for increasing the accuracy of neurosurgical guidance in the delineation and resection of brain tumors.

Deferoxamine Iron Chelation Increases δ-Aminolevulinic Acid Induced Protoporphyrin IX in Xenograft Glioma Model

Exogenous administration of δ‐aminolevulinic acid (δ‐ALA) leads to selective accumulation of protoporphyrin IX (PpIX) in brain tumors, and has shown promising results in increasing extent of resection in fluorescence‐guided resection (FGR) of brain tumors. However, this approach still suffers from heterogeneous staining and so some tumor margins may go undetected because of this variation in PpIX production. The aim of this study was to test the hypothesis that iron chelation therapy could increase the level of fluorescence in malignant glioma tumors. Mice implanted with xenograft U251‐GFP glioma tumor cells were given a 200 mg kg−1 dose of deferoxamine (DFO), once a day for 3 days prior to δ‐ALA administration. The PpIX fluorescence observed in the tumor regions was 1.9 times the background in animal group without DFO, and 2.9 times the background on average, in the DFO pre‐treated group. A 50% increase in PpIX fluorescence contrast in the DFO group was observed relative to the control group (t‐test P‐value = 0.0020). These results indicate that iron chelation therapy could significantly increase δ‐ALA‐induced PpIX fluorescence in malignant gliomas, pointing to a potential role of iron chelation therapy for more effective FGR of brain tumors.

Brain–skull contact boundary conditions in an inverse computational deformation model

Biomechanical models simulating brain motion under loading and boundary conditions in the operating room (OR) are gaining attention as alternatives for brain shift compensation during open cranial neurosurgeries. Although the significance of brain-skull boundary conditions (BCs) in these models has been explored in dynamic simulations, it has not been fully investigated in models representing the quasi-static brain motion that prevails during neurosurgery. In this study, we extend the application of a brain-skull contact BC by incorporating it into an inversion estimation scheme for the deformation field using the steepest gradient descent (SGD) framework. The technique allows parenchymal surface motion normal to the skull while maintaining stress-free BCs at the craniotomy and minimizing the effect of measurement noise. Application of the algorithm in five clinical cases using sparse data generated at the tumor boundary confirms the significance of brain-skull BCs in the model response. Specifically, the results demonstrate that the contact BC enhances model flexibility and achieves improved or comparable performance at the tumor boundary (recovering about 85% of the deformation) relative to that obtained when normal motion of the parenchymal surface is not allowed. It also significantly improves model estimation accuracy at the craniotomy (1.6mm on average), especially when the normal motion is large. The importance of the method is that model performance significantly improves when brain-skull contact influences the deformation field but does not degrade when the contact is less critical and simpler BCs would suffice. The computational cost of the technique is currently 3.9 min on average, but may be further reduced by applying an iterative solver to the linear systems of equations involved and/or by local refinement of the mesh in regions of interest.

Analytic expression of fluorescence ratio detection correlates with depth in multi-spectral sub-surface imaging

Here we derived analytical solutions to diffuse light transport in biological tissue based on spectral deformation of diffused near-infrared measurements. These solutions provide a closed-form mathematical expression which predicts that the depth of a fluorescent molecule distribution is linearly related to the logarithm of the ratio of fluorescence at two different wavelengths. The slope and intercept values of the equation depend on the intrinsic values of absorption and reduced scattering of tissue. This linear behavior occurs if the following two conditions are satisfied: the depth is beyond a few millimeters and the tissue is relatively homogeneous. We present experimental measurements acquired with a broad-beam non-contact multi-spectral fluorescence imaging system using a hemoglobin-containing diffusive phantom. Preliminary results confirm that a significant correlation exists between the predicted depth of a distribution of protoporphyrin IX molecules and the measured ratio of fluorescence at two different wavelengths. These results suggest that depth assessment of fluorescence contrast can be achieved in fluorescence-guided surgery to allow improved intra-operative delineation of tumor margins.

Cortical surface strain estimation using stereovision

We present a completely noninvasive technique to estimate soft tissue surface strain by differentiating three-dimensional displacements obtained from optical flow motion tracking using stereo images. The implementation of the strain estimation algorithm was verified with simulated data and its application was illustrated in three open cranial neurosurgical cases, where cortical surface strain induced by arterial blood pressure pulsation was evaluated. Local least squares smoothing was applied to the displacement field prior to strain estimation to reduce the effect of noise during differentiation. Maximum principal strains (epsilon1) of up to 7% were found in the exposed cortical area on average, and the largest strains (up to -18%) occurred near the craniotomy rim with the majority of epsilon1 perpendicular to the boundary, indicating relative stretching along this direction. The technique offers a new approach for soft tissue strain estimation for the purpose of biomechanical characterization.

Simulation of brain tumor resection in image-guided neurosurgery

Preoperative magnetic resonance images are typically used for neuronavigation in image-guided neurosurgery. However, intraoperative brain deformation (e.g., as a result of gravitation, loss of cerebrospinal fluid, retraction, resection, etc.) significantly degrades the accuracy in image guidance, and must be compensated for in order to maintain sufficient accuracy for navigation. Biomechanical finite element models are effective techniques that assimilate intraoperative data and compute whole-brain deformation from which to generate model-updated MR images (uMR) to improve accuracy in intraoperative guidance. To date, most studies have focused on early surgical stages (i.e., after craniotomy and durotomy), whereas simulation of more complex events at later surgical stages has remained to be a challenge using biomechanical models. We have developed a method to simulate partial or complete tumor resection that incorporates intraoperative volumetric ultrasound (US) and stereovision (SV), and the resulting whole-brain deformation was used to generate uMR. The 3D ultrasound and stereovision systems are complimentary to each other because they capture features deeper in the brain beneath the craniotomy and at the exposed cortical surface, respectively. In this paper, we illustrate the application of the proposed method to simulate brain tumor resection at three temporally distinct surgical stages throughout a clinical surgery case using sparse displacement data obtained from both the US and SV systems. We demonstrate that our technique is feasible to produce uMR that agrees well with intraoperative US and SV images after dural opening, after partial tumor resection, and after complete tumor resection. Currently, the computational cost to simulate tumor resection can be up to 30 min because of the need for re-meshing and the trial-and-error approach to refine the amount of tissue resection. However, this approach introduces minimal interruption to the surgical workflow, which suggests the potential for its clinical application with further improvement in computational efficiency.

Real-time Interpolation for True 3-Dimensional Ultrasound Image Volumes

We compared trilinear interpolation to voxel nearest neighbor and distance‐weighted algorithms for fast and accurate processing of true 3‐dimensional ultrasound (3DUS) image volumes. In this study, the computational efficiency and interpolation accuracy of the 3 methods were compared on the basis of a simulated 3DUS image volume, 34 clinical 3DUS image volumes from 5 patients, and 2 experimental phantom image volumes. We show that trilinear interpolation improves interpolation accuracy over both the voxel nearest neighbor and distance‐weighted algorithms yet achieves real‐time computational performance that is comparable to the voxel nearest neighbor algrorithm (1–2 orders of magnitude faster than the distance‐weighted algorithm) as well as the fastest pixel‐based algorithms for processing tracked 2‐dimensional ultrasound images (0.035 seconds per 2‐dimesional cross‐sectional image [76,800 pixels interpolated, or 0.46 ms/1000 pixels] and 1.05 seconds per full volume with a 1‐mm3 voxel size [4.6 million voxels interpolated, or 0.23 ms/1000 voxels]). On the basis of these results, trilinear interpolation is recommended as a fast and accurate interpolation method for rectilinear sampling of 3DUS image acquisitions, which is required to facilitate subsequent processing and display during operating room procedures such as image‐guided neurosurgery.

Adaptive spatial calibration of a 3D ultrasound system.

PURPOSE The authors present a method devised to calibrate the spatial relationship between a 3D ultrasound scanhead and its tracker completely automatically and reliably. The user interaction is limited to collecting ultrasound data on which the calibration is based. METHODS The method of calibration is based on images of a fixed plane of unknown location with respect to the 3D tracking system. This approach has, for advantage, to eliminate the measurement of the plane location as a source of error. The devised method is sufficiently general and adaptable to calibrate scanheads for 2D images and 3D volume sets using the same approach. The basic algorithm for both types of scanheads is the same and can be run unattended fully automatically once the data are collected. The approach was devised by seeking the simplest and most robust solutions for each of the steps required. These are the identification of the plane intersection within the images or volumes and the optimization method used to compute a calibration transformation matrix. The authors use adaptive algorithms in these two steps to eliminate data that would otherwise prevent the convergence of the procedure, which contributes to the robustness of the method. RESULTS The authors have run tests amounting to 57 runs of the calibration on two a scanhead that produce 3D imaging volumes, at all the available scales. The authors evaluated the system on two criteria: Robustness and accuracy. The program converged to useful values unattended for every one of the tests (100%). Its accuracy, based on the measured location of a reference plane, was estimated to be 0.7 +/- 0.6 mm for all tests combined. CONCLUSIONS The system presented is robust and allows unattended computations of the calibration parameters required for freehand tracked ultrasound based on either 2D or 3D imaging systems.