Alexandra J. Golby

Differential responses in the fusiform region to same-race and other-race faces.

Many studies have shown that people remember faces of their own race better than faces of other races. We investigated the neural substrates of same-race memory superiority using functional MRI (fMRI). European-American (EA) and African-American (AA) males underwent fMRI while they viewed photographs of AA males, EA males and objects under intentional encoding conditions. Recognition memory was superior for same-race versus other-race faces. Individually defined areas in the fusiform region that responded preferentially to faces had greater response to same-race versus other-race faces. Across both groups, memory differences between same-race and other-race faces correlated with activation in left fusiform cortex and right parahippocampal and hippocampal areas. These results suggest that differential activation in fusiform regions contributes to same-race memory superiority.

Robust nonrigid registration to capture brain shift from intraoperative MRI

We present a new algorithm to register 3-D preoperative magnetic resonance (MR) images to intraoperative MR images of the brain which have undergone brain shift. This algorithm relies on a robust estimation of the deformation from a sparse noisy set of measured displacements. We propose a new framework to compute the displacement field in an iterative process, allowing the solution to gradually move from an approximation formulation (minimizing the sum of a regularization term and a data error term) to an interpolation formulation (least square minimization of the data error term). An outlier rejection step is introduced in this gradual registration process using a weighted least trimmed squares approach, aiming at improving the robustness of the algorithm. We use a patient-specific model discretized with the finite element method in order to ensure a realistic mechanical behavior of the brain tissue. To meet the clinical time constraint, we parallelized the slowest step of the algorithm so that we can perform a full 3-D image registration in 35 s (including the image update time) on a heterogeneous cluster of 15 personal computers. The algorithm has been tested on six cases of brain tumor resection, presenting a brain shift of up to 14 mm. The results show a good ability to recover large displacements, and a limited decrease of accuracy near the tumor resection cavity.

Memory lateralization in medial temporal lobe epilepsy assessed by functional MRI.

Summary:  Purpose: To determine the utility of functional magnetic resonance imaging (fMRI) in preoperative lateralization of memory function in patients with medial temporal lobe epilepsy (MTLE).

Rapid, Label-Free Detection of Brain Tumors with Stimulated Raman Scattering Microscopy

Stimulated Raman scattering microscopy provides a rapid, label-free means of detecting tumor infiltration of brain tissue ex vivo and in vivo. Virtual Histology During brain tumor surgery, precision is key. Removing healthy tissue can cause neurologic deficits; leaving behind tumor tissue can allow cancer to spread and treatment to fail. To help the surgeon clearly see tumor versus normal tissue, Ji and colleagues developed a stimulated Raman scattering (SRS) microscopy method and demonstrated its ability to identify malignant human brain tissue. In SRS microscopy, laser beams are directed at the tissue sample to generate a series of output signals called “Raman spectra.” These spectra depend on the molecular composition of the tissue. Ji et al. implanted human brain cancer (glioblastoma) cells into mice, allowed them to infiltrate and grow into tumors, and then removed slices for SRS imaging. From the resulting spectra, the authors were able to differentiate the two major components of brain tissue—lipid-rich white matter and protein-rich cortex—as well as tumors, which are full of proteins. Intraoperatively, using an imaging window into mouse brains, the authors found that SRS microscopy could locate tumor infiltration in areas that appeared normal by eye, which suggests that this tool could be applied during surgery. Imaging fresh tissue slices ex vivo could also complement or perhaps replace standard hematoxylin and eosin (H&E) staining in the clinic because it avoids artifacts inherent in imaging frozen or fixed tissues. To this end, Ji and colleagues showed that SRS microscopy could identify hypercellular tumor regions in fresh surgical specimens from a patient with glioblastoma. Certain diagnostic features were present in these specimens and readily identified by SRS, including pseudopalisading necrosis and microvascular proliferation. The next step will be to apply SRS microscopy to a large collection of human specimens to see whether this technology may be useful in quickly distinguishing glioblastoma from healthy tissue, both outside and inside the operating room. Surgery is an essential component in the treatment of brain tumors. However, delineating tumor from normal brain remains a major challenge. We describe the use of stimulated Raman scattering (SRS) microscopy for differentiating healthy human and mouse brain tissue from tumor-infiltrated brain based on histoarchitectural and biochemical differences. Unlike traditional histopathology, SRS is a label-free technique that can be rapidly performed in situ. SRS microscopy was able to differentiate tumor from nonneoplastic tissue in an infiltrative human glioblastoma xenograft mouse model based on their different Raman spectra. We further demonstrated a correlation between SRS and hematoxylin and eosin microscopy for detection of glioma infiltration (κ = 0.98). Finally, we applied SRS microscopy in vivo in mice during surgery to reveal tumor margins that were undetectable under standard operative conditions. By providing rapid intraoperative assessment of brain tissue, SRS microscopy may ultimately improve the safety and accuracy of surgeries where tumor boundaries are visually indistinct.

Classifying Human Brain Tumors by Lipid Imaging with Mass Spectrometry

Brain tissue biopsies are required to histologically diagnose brain tumors, but current approaches are limited by tissue characterization at the time of surgery. Emerging technologies such as mass spectrometry imaging can enable a rapid direct analysis of cancerous tissue based on molecular composition. Here, we illustrate how gliomas can be rapidly classified by desorption electrospray ionization-mass spectrometry (DESI-MS) imaging, multivariate statistical analysis, and machine learning. DESI-MS imaging was carried out on 36 human glioma samples, including oligodendroglioma, astrocytoma, and oligoastrocytoma, all of different histologic grades and varied tumor cell concentration. Gray and white matter from glial tumors were readily discriminated and detailed diagnostic information could be provided. Classifiers for subtype, grade, and concentration features generated with lipidomic data showed high recognition capability with more than 97% cross-validation. Specimen classification in an independent validation set agreed with expert histopathology diagnosis for 79% of tested features. Together, our findings offer proof of concept that intraoperative examination and classification of brain tissue by mass spectrometry can provide surgeons, pathologists, and oncologists with critical and previously unavailable information to rapidly guide surgical resections that can improve management of patients with malignant brain tumors.

OpenIGTLink: an open network protocol for image-guided therapy environment

With increasing research on system integration for image‐guided therapy (IGT), there has been a strong demand for standardized communication among devices and software to share data such as target positions, images and device status.

Non-rigid alignment of pre-operative MRI, fMRI, and DT-MRI with intra-operative MRI for enhanced visualization and navigation in image-guided neurosurgery.

OBJECTIVE The usefulness of neurosurgical navigation with current visualizations is seriously compromised by brain shift, which inevitably occurs during the course of the operation, significantly degrading the precise alignment between the pre-operative MR data and the intra-operative shape of the brain. Our objectives were (i) to evaluate the feasibility of non-rigid registration that compensates for the brain deformations within the time constraints imposed by neurosurgery, and (ii) to create augmented reality visualizations of critical structural and functional brain regions during neurosurgery using pre-operatively acquired fMRI and DT-MRI. MATERIALS AND METHODS Eleven consecutive patients with supratentorial gliomas were included in our study. All underwent surgery at our intra-operative MR imaging-guided therapy facility and have tumors in eloquent brain areas (e.g. precentral gyrus and cortico-spinal tract). Functional MRI and DT-MRI, together with MPRAGE and T2w structural MRI were acquired at 3 T prior to surgery. SPGR and T2w images were acquired with a 0.5 T magnet during each procedure. Quantitative assessment of the alignment accuracy was carried out and compared with current state-of-the-art systems based only on rigid registration. RESULTS Alignment between pre-operative and intra-operative datasets was successfully carried out during surgery for all patients. Overall, the mean residual displacement remaining after non-rigid registration was 1.82 mm. There is a statistically significant improvement in alignment accuracy utilizing our non-rigid registration in comparison to the currently used technology (p<0.001). CONCLUSIONS We were able to achieve intra-operative rigid and non-rigid registration of (1) pre-operative structural MRI with intra-operative T1w MRI; (2) pre-operative fMRI with intra-operative T1w MRI, and (3) pre-operative DT-MRI with intra-operative T1w MRI. The registration algorithms as implemented were sufficiently robust and rapid to meet the hard real-time constraints of intra-operative surgical decision making. The validation experiments demonstrate that we can accurately compensate for the deformation of the brain and thus can construct an augmented reality visualization to aid the surgeon.

Ambient mass spectrometry for the intraoperative molecular diagnosis of human brain tumors

The main goal of brain tumor surgery is to maximize tumor resection while preserving brain function. However, existing imaging and surgical techniques do not offer the molecular information needed to delineate tumor boundaries. We have developed a system to rapidly analyze and classify brain tumors based on lipid information acquired by desorption electrospray ionization mass spectrometry (DESI-MS). In this study, a classifier was built to discriminate gliomas and meningiomas based on 36 glioma and 19 meningioma samples. The classifier was tested and results were validated for intraoperative use by analyzing and diagnosing tissue sections from 32 surgical specimens obtained from five research subjects who underwent brain tumor resection. The samples analyzed included oligodendroglioma, astrocytoma, and meningioma tumors of different histological grades and tumor cell concentrations. The molecular diagnosis derived from mass-spectrometry imaging corresponded to histopathology diagnosis with very few exceptions. Our work demonstrates that DESI-MS technology has the potential to identify the histology type of brain tumors. It provides information on glioma grade and, most importantly, may help define tumor margins by measuring the tumor cell concentration in a specimen. Results for stereotactically registered samples were correlated to preoperative MRI through neuronavigation, and visualized over segmented 3D MRI tumor volume reconstruction. Our findings demonstrate the potential of ambient mass spectrometry to guide brain tumor surgery by providing rapid diagnosis, and tumor margin assessment in near–real time.

Tract-based morphometry for white matter group analysis.

We introduce an automatic method that we call tract-based morphometry, or TBM, for measurement and analysis of diffusion MRI data along white matter fiber tracts. Using subject-specific tractography bundle segmentations, we generate an arc length parameterization of the bundle with point correspondences across all fibers and all subjects, allowing tract-based measurement and analysis. In this paper we present a quantitative comparison of fiber coordinate systems from the literature and we introduce an improved optimal match method that reduces spatial distortion and improves intra- and inter-subject variability of FA measurements. We propose a method for generating arc length correspondences across hemispheres, enabling a TBM study of interhemispheric diffusion asymmetries in the arcuate fasciculus (AF) and cingulum bundle (CB). The results of this study demonstrate that TBM can detect differences that may not be found by measuring means of scalar invariants in entire tracts, such as the mean diffusivity (MD) differences found in AF. We report TBM results of higher fractional anisotropy (FA) in the left hemisphere in AF (caused primarily by lower lambda(3), the smallest eigenvalue of the diffusion tensor, in the left AF), and higher left hemisphere FA in CB (related to higher lambda(1), the largest eigenvalue of the diffusion tensor, in the left CB). By mapping the significance levels onto the tractography trajectories for each structure, we demonstrate the anatomical locations of the interhemispheric differences. The TBM approach brings analysis of DTI data into the clinically and neuroanatomically relevant framework of the tract anatomy.

Functional magnetic resonance imaging-integrated neuronavigation: correlation between lesion-to-motor cortex distance and outcome.

OBJECTIVE:The integration of functional magnetic resonance imaging (fMRI) data into neuronavigation is a new concept for surgery adjacent to the motor cortex. However, the clinical value remains to be defined. In this study, we investigated the correlation between the lesion-to-fMRI activation distance and the occurrence of a new postoperative deficit. METHODS:fMRI-integrated “functional” neuronavigation was used for surgery around the motor strip in 54 patients. During standardized paradigms for hand, foot, and tongue movements, echo-planar imaging T2* blood oxygen level-dependent sequences were acquired and processed with BrainVoyager 2000 software (Brain Innovation, Maastricht, The Netherlands). Neuronavigation was performed with the VectorVision2 system (BrainLAB, Heimstetten, Germany). For outcome analysis, patient age, histological findings, size of lesion, distance to the fMRI areas, preoperative and postoperative Karnofsky index, postoperative motor deficit, and type of resection were analyzed. RESULTS:In 45 patients, a gross total resection (>95%) was performed, and for 9 lesions (low-grade glioma, 4; glioblastoma, 5), a subtotal resection (80–95%) was achieved. The neurological outcome improved in 16 patients (29.6%), was unchanged in 29 patients (53.7%), and deteriorated in 9 patients (16.7%). Significant predictors of a new neurological deficit were a lesion-to-activation distance of less than 5 mm (P < 0.01) and incomplete resection (P < 0.05). CONCLUSION:fMRI-integrated neuronavigation is a useful concept to assess the risk of a new motor deficit after surgery. Our data suggest that a lesion-to-activation distance of less than 5 mm is associated with a higher risk of neurological deterioration. Within a 10-mm range, cortical stimulation should be performed. For a lesion-to-activation distance of more than 10 mm, a complete resection can be achieved safely. The visualization of fiber tracks is desirable to complete the representation of the motor system.