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.

Surgery is an essential component in the treatment of brain tumors. However, delineating tumor from normal brain remains a major challenge. Here 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 non-neoplastic tissue in an infiltrative human glioblastoma xenograft mouse model based on their different Raman spectra. We further demonstrated a correlation between SRS and H&E 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.

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 mass spectrometry (DESI-MS) imaging, multivariate statistical analysis, and machine learning. DESI-MS imaging was performed on thirty-six human glioma samples, including oligodendroglioma, astrocytoma and oligoastrocytoma, all of different histologic grades and varied tumor cell concentration. Grey 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 >97% cross-validation. Specimen classification in an independent validation set agreed with expert histopathology diagnosis for 81% of tested features. Together, our findings offer proof of concept that intra-operative 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.

Numerous observations in patients with unilateral lesions of the medial temporal lobe (MTL) and the prefrontal cortex indicate that memory processes are lateralized according to content. Left-sided lesions interfere with verbal memory processes, whereas right-sided lesions interfere with visuospatial (non-verbal) memory processes. However, functional imaging studies have resulted in contradictory data, some studies showing lateralization in the prefrontal cortex determined by stage of processing (encoding versus retrieval) and others suggesting that lateralization is dependent on the type of material. Few studies have examined this issue in the MTL. In order to test the hypothesis that the lateralization of encoding processes in the MTL and frontal regions is dependent on the verbalizability of the material, we performed behavioural and functional imaging studies. We demonstrated differing verbalizabilities of three classes of non-verbal stimuli (scenes > faces > abstract patterns) using a dual-task verbal interference behavioural paradigm. A functional neuroimaging study of encoding was carried out using these three types of stimuli, plus words. During whole-brain functional MRI at 1.5 T, eight normal right-handed adults were presented with alternating blocks of novel and repeated stimuli under intentional memory encoding conditions. Verbal encoding resulted in left-lateralized activation of the inferior prefrontal cortex and the MTL. Pattern encoding activated the right inferior prefrontal cortex and the right MTL. Scenes and faces resulted in approximately symmetrical activation in both regions. The data indicate that the lateralization of encoding processes is determined by the verbalizability of stimuli.

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.

Abstract-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.Index Terms-Brain shift, finite element model, intraoperative magnetic resonance imaging, nonrigid registration.

For many intraoperative decisions surgeons depend on frozen section pathology, a technique developed over 150 y ago. Technical innovations that permit rapid molecular characterization of tissue samples at the time of surgery are needed. Here, using desorption electrospray ionization (DESI) MS, we rapidly detect the tumor metabolite 2-hydroxyglutarate (2-HG) from tissue sections of surgically resected gliomas, under ambient conditions and without complex or time-consuming preparation. With DESI MS, we identify isocitrate dehydrogenase 1-mutant tumors with both high sensitivity and specificity within minutes, immediately providing critical diagnostic, prognostic, and predictive information. Imaging tissue sections with DESI MS shows that the 2-HG signal overlaps with areas of tumor and that 2-HG levels correlate with tumor content, thereby indicating tumor margins. Mapping the 2-HG signal onto 3D MRI reconstructions of tumors allows the integration of molecular and radiologic information for enhanced clinical decision making. We also validate the methodology and its deployment in the operating room: We have installed a mass spectrometer in our Advanced Multimodality Image Guided Operating (AMIGO) suite and demonstrate the molecular analysis of surgical tissue during brain surgery. This work indicates that metabolite-imaging MS could transform many aspects of surgical care.T he microscopic review of tissue biopsies frequently remains the sole source of intraoperative diagnostic information, and many important surgical decisions such as the extent of tumor resection are based on this information. This approach is timeconsuming, requiring nearly 30 min between the moment a tissue is biopsied and the time the pathologist's interpretation is communicated back to the surgeon. Even after the report of the final pathologic diagnosis is issued days later, a lot of diagnostic, prognostic, and predictive information is left undiscovered and unexamined within the tissue. Tools that provide more immediate feedback to the surgeon and the pathologist and that also rapidly extract detailed molecular information could transform the management of care for cancer patients.MS offers the possibility for the in-depth analysis of the proteins and lipids that comprise tissues (1, 2). We have recently shown that desorption electrospray ionization (DESI) MS is a powerful methodology for characterizing lipids within tumor specimens (3-6). The intensity profile of lipids ionized from within tumors can be used for classifying tumors and for providing valuable prognostic information such as tumor subtype and grade. Because DESI MS is performed in ambient conditions with minimal pretreatment of the samples (7,8), there is the potential to provide diagnostic information rapidly within the operating room (4, 6, 9). The ability to quickly acquire such valuable diagnostic information from lipids prompted us to determine whether we could use DESI MS to detect additional molecules of diagnostic value within tumors, such as their metabolites.Recently,...

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 λ 3 , the smallest eigenvalue of the diffusion tensor, in the left AF), and higher left hemisphere FA in CB (related to higher λ 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.