Xiaoyao Fan

Quantitative fluorescence in intracranial tumor: implications for ALA-induced PpIX as an intraoperative biomarker.

OBJECT Accurate discrimination between tumor and normal tissue is crucial for optimal tumor resection. Qualitative fluorescence of protoporphyrin IX (PpIX), synthesized endogenously following δ-aminolevulinic acid (ALA) administration, has been used for this purpose in high-grade glioma (HGG). The authors show that diagnostically significant but visually imperceptible concentrations of PpIX can be quantitatively measured in vivo and used to discriminate normal from neoplastic brain tissue across a range of tumor histologies. METHODS The authors studied 14 patients with diagnoses of low-grade glioma (LGG), HGG, meningioma, and metastasis under an institutional review board-approved protocol for fluorescence-guided resection. The primary aim of the study was to compare the diagnostic capabilities of a highly sensitive, spectrally resolved quantitative fluorescence approach to conventional fluorescence imaging for detection of neoplastic tissue in vivo. RESULTS A significant difference in the quantitative measurements of PpIX concentration occurred in all tumor groups compared with normal brain tissue. Receiver operating characteristic (ROC) curve analysis of PpIX concentration as a diagnostic variable for detection of neoplastic tissue yielded a classification efficiency of 87% (AUC = 0.95, specificity = 92%, sensitivity = 84%) compared with 66% (AUC = 0.73, specificity = 100%, sensitivity = 47%) for conventional fluorescence imaging (p < 0.0001). More than 81% (57 of 70) of the quantitative fluorescence measurements that were below the threshold of the surgeons visual perception were classified correctly in an analysis of all tumors. CONCLUSIONS These findings are clinically profound because they demonstrate that ALA-induced PpIX is a targeting biomarker for a variety of intracranial tumors beyond HGGs. This study is the first to measure quantitative ALA-induced PpIX concentrations in vivo, and the results have broad implications for guidance during resection of intracranial tumors.

Coregistered fluorescence-enhanced tumor resection of malignant glioma: relationships between δ-aminolevulinic acid–induced protoporphyrin IX fluorescence, magnetic resonance imaging enhancement, and neuropathological parameters: Clinical article

OBJECT The aim of this study was to investigate the relationships between intraoperative fluorescence, features on MR imaging, and neuropathological parameters in 11 cases of newly diagnosed glioblastoma multiforme (GBM) treated using protoporphyrin IX (PpIX) fluorescence-guided resection. METHODS In 11 patients with a newly diagnosed GBM, δ-aminolevulinic acid (ALA) was administered to enhance endogenous synthesis of the fluorophore PpIX. The patients then underwent fluorescence-guided resection, coregistered with conventional neuronavigational image guidance. Biopsy specimens were collected at different times during surgery and assigned a fluorescence level of 0-3 (0, no fluorescence; 1, low fluorescence; 2, moderate fluorescence; or 3, high fluorescence). Contrast enhancement on MR imaging was quantified using two image metrics: 1) Gd-enhanced signal intensity (GdE) on T1-weighted subtraction MR image volumes, and 2) normalized contrast ratios (nCRs) in T1-weighted, postGd-injection MR image volumes for each biopsy specimen, using the biopsy-specific image-space coordinate transformation provided by the navigation system. Subsequently, each GdE and nCR value was grouped into one of two fluorescence categories, defined by its corresponding biopsy specimen fluorescence assessment as negative fluorescence (fluorescence level 0) or positive fluorescence (fluorescence level 1, 2, or 3). A single neuropathologist analyzed the H & E-stained tissue slides of each biopsy specimen and measured three neuropathological parameters: 1) histopathological score (0-IV); 2) tumor burden score (0-III); and 3) necrotic burden score (0-III). RESULTS Mixed-model analyses with random effects for individuals show a highly statistically significant difference between fluorescing and nonfluorescing tissue in GdE (mean difference 8.33, p = 0.018) and nCRs (mean difference 5.15, p < 0.001). An analysis of association demonstrated a significant relationship between the levels of intraoperative fluorescence and histopathological score (χ(2) = 58.8, p < 0.001), between fluorescence levels and tumor burden (χ(2) = 42.7, p < 0.001), and between fluorescence levels and necrotic burden (χ(2) = 30.9, p < 0.001). The corresponding Spearman rank correlation coefficients were 0.51 (p < 0.001) for fluorescence and histopathological score, and 0.49 (p < 0.001) for fluorescence and tumor burden, suggesting a strongly positive relationship for each of these variables. CONCLUSIONS These results demonstrate a significant relationship between contrast enhancement on preoperative MR imaging and observable intraoperative PpIX fluorescence. The finding that preoperative MR image signatures are predictive of intraoperative PpIX fluorescence is of practical importance for identifying candidates for the procedure. Furthermore, this study provides evidence that a strong relationship exists between tumor aggressiveness and the degree of tissue fluorescence that is observable intraoperatively, and that observable fluorescence has an excellent positive predictive value but a low negative predictive value.

Glioblastoma Multiforme Treatment with Clinical Trials for Surgical Resection (Aminolevulinic Acid)

5-Aminolevulinic acid (5-ALA)-induced tumor fluorescence can be used to identify tissue for resection using an adapted operating microscope. A multi-institutional clinical trial comparing fluorescence-guided versus white light tumor resection reported significant improvement in completeness of resection and 6-month progression-free survival. The degree of 5-ALA-induced fluorescence correlates with histopathologic grade of tumor, degree of tumor cell infiltration, and proliferation indices. Quantitative methodologies for assessment of tissue fluorescence have significantly improved the ability to detect tumor tissue and intraoperative diagnostic performance. These developments extend the applicability of this technology to additional tumor histologies and provide the rationale for further instrumentation development.

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.

Cortical surface shift estimation using stereovision and optical flow motion tracking via projection image registration.

Stereovision is an important intraoperative imaging technique that captures the exposed parenchymal surface noninvasively during open cranial surgery. Estimating cortical surface shift efficiently and accurately is critical to compensate for brain deformation in the operating room (OR). In this study, we present an automatic and robust registration technique based on optical flow (OF) motion tracking to compensate for cortical surface displacement throughout surgery. Stereo images of the cortical surface were acquired at multiple time points after dural opening to reconstruct three-dimensional (3D) texture intensity-encoded cortical surfaces. A local coordinate system was established with its z-axis parallel to the average surface normal direction of the reconstructed cortical surface immediately after dural opening in order to produce two-dimensional (2D) projection images. A dense displacement field between the two projection images was determined directly from OF motion tracking without the need for feature identification or tracking. The starting and end points of the displacement vectors on the two cortical surfaces were then obtained following spatial mapping inversion to produce the full 3D displacement of the exposed cortical surface. We evaluated the technique with images obtained from digital phantoms and 18 surgical cases - 10 of which involved independent measurements of feature locations acquired with a tracked stylus for accuracy comparisons, and 8 others of which 4 involved stereo image acquisitions at three or more time points during surgery to illustrate utility throughout a procedure. Results from the digital phantom images were very accurate (0.05 pixels). In the 10 surgical cases with independently digitized point locations, the average agreement between feature coordinates derived from the cortical surface reconstructions was 1.7-2.1mm relative to those determined with the tracked stylus probe. The agreement in feature displacement tracking was also comparable to tracked probe data (difference in displacement magnitude was <1mm on average). The average magnitude of cortical surface displacement was 7.9 ± 5.7 mm (range 0.3-24.4 mm) in all patient cases with the displacement components along gravity being 5.2 ± 6.0 mm relative to the lateral movement of 2.4 ± 1.6 mm. Thus, our technique appears to be sufficiently accurate and computationally efficiency (typically ∼15 s), for applications in the OR.

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

PURPOSE A surface registration method is presented to align intraoperative stereovision (iSV) with preoperative magnetic resonance (pMR) images, which utilizes both geometry and texture information to extract tissue displacements as part of the overall process of compensating for intraoperative brain deformation in order to maintain accurate neuronavigational image guidance during surgery. METHODS A sum-of-squared-difference rigid image registration was first executed to detect lateral shift of the cortical surface and was followed by a mutual-information-based block matching method to detect local nonrigid deformation caused by distention or collapse of the cortical surface. Ten (N = 10) surgical cases were evaluated in which an independent point measurement of a dominant cortical surface feature location was recorded with a tracked stylus in each case and compared to its surface-registered counterpart. The full three-dimensional (3D) displacement field was also extracted to drive a biomechanical brain deformation model, the results of which were reconciled with the reconstructed iSV surface as another form of evaluation. RESULTS Differences between the tracked stylus coordinates of cortical surface features and their surface-registered locations were 1.94 ± 0.59 mm on average across the ten cases. When the complete displacement map derived from surface registration was utilized, the resulting images generated from mechanical model updates were consistent in terms of both geometry (1-2 mm of model misfit) and texture, and were generated with less than 10 min of computational time. Analysis of the surface-registered 3D displacements indicate that the magnitude of motion ranged from 4.03 to 9.79 mm in the ten patient cases, and the amount of lateral shift was not related statistically to the direction of gravity (p = 0.73 ≫ 0.05) or the craniotomy size (p = 0.48 ≫ 0.05) at the beginning of surgery. CONCLUSIONS The iSV-pMR surface registration method utilizes texture and geometry information to extract both global lateral shift and local nonrigid movement of the cortical surface in 3D. The results suggest small differences exist in surface-registered locations when compared to positions measured independently with a coregistered stylus and when the full iSV surface was aligned with model-updated MR. The effectiveness and efficiency of the registration method is also minimally disruptive to 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.

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.

Efficient Stereo Image Geometrical Reconstruction at Arbitrary Camera Settings from a Single Calibration

Camera calibration is central to obtaining a quantitative image-to-physical-space mapping from stereo images acquired in the operating room (OR). A practical challenge for cameras mounted to the operating microscope is maintenance of image calibration as the surgeons field-of-view is repeatedly changed (in terms of zoom and focal settings) throughout a procedure. Here, we present an efficient method for sustaining a quantitative image-to-physical space relationship for arbitrary image acquisition settings (S) without the need for camera re-calibration. Essentially, we warp images acquired at S into the equivalent data acquired at a reference setting, S(0), using deformation fields obtained with optical flow by successively imaging a simple phantom. Closed-form expressions for the distortions were derived from which 3D surface reconstruction was performed based on the single calibration at S(0). The accuracy of the reconstructed surface was 1.05 mm and 0.59 mm along and perpendicular to the optical axis of the operating microscope on average, respectively, for six phantom image pairs, and was 1.26 mm and 0.71 mm for images acquired with a total of 47 arbitrary settings during three clinical cases. The technique is presented in the context of stereovision; however, it may also be applicable to other types of video image acquisitions (e.g., endoscope) because it does not rely on any a priori knowledge about the camera system itself, suggesting the method is likely of considerable significance.