Faculty Bibliography

As glioma cells infiltrate the brain they become associated with various microanatomic brain structures such as blood vessels, white matter tracts, and brain parenchyma. How these distinct invasion patterns coordinate tumor growth and influence clinical outcomes remain poorly understood. We have investigated how perivascular growth affects glioma growth patterning and response to antiangiogenic therapy within the highly vascularized brain. Orthotopically implanted rodent and human glioma cells are shown to commonly invade and proliferate within brain perivascular space. This form of brain tumor growth and invasion is also shown to characterize de novo generated endogenous mouse brain tumors, biopsies of primary human glioblastoma (GBM), and peripheral cancer metastasis to the human brain. Perivascularly invading brain tumors become vascularized by normal brain microvessels as individual glioma cells use perivascular space as a conduit for tumor invasion. Agent-based computational modeling recapitulated biological perivascular glioma growth without the need for neoangiogenesis. We tested the requirement for neoangiogenesis in perivascular glioma by treating animals with angiogenesis inhibitors bevacizumab and DC101. These inhibitors induced the expected vessel normalization, yet failed to reduce tumor growth or improve survival of mice bearing orthotopic or endogenous gliomas while exacerbating brain tumor invasion. Our results provide compelling experimental evidence in support of the recently described failure of clinically used antiangiogenics to extend the overall survival of human GBM patients.

Brain tumor surgery is one of the key factors in prolonging survival in patients with low- and high-grade gliomas. However, resections of these infiltrative lesions have historically been limited by the inability to accurately detect tumor margins. New methods in microscopy and dye injection have enabled more complete resections, but continue to lack biochemical specificity or high-resolution image acquisition. Stimulated Raman scattering microscopy represents an improvement over past techniques in the ability to differentiate intraparenchymal tissues on the basis of biochemical attributes, and is available for use in real-time, a feature that facilitates its translation to the surgical setting.

Presurgical language mapping for patients with lesions close to language areas is critical to neurosurgical decision-making for preservation of language function. As a clinical noninvasive imaging technique, functional MRI (fMRI) is used to identify language areas by measuring blood-oxygen-level dependent (BOLD) signal change while patients perform carefully timed language vs. control tasks. This task-based fMRI critically depends on task performance, excluding many patients who have difficulty performing language tasks due to neurologic deficits. On the basis of recent discovery of resting-state fMRI (rs-fMRI), we propose a "task-free" paradigm acquiring fMRI data when patients simply are at rest. This paradigm is less demanding for patients to perform and easier for technologists to administer. We investigated the feasibility of this approach in right-handed healthy control subjects. First, group independent component analysis (ICA) was applied on the training group (14 subjects) to identify group level language components based on expert rating results. Then, four empirically and structurally defined language network templates were assessed for their ability to identify language components from individuals' ICA output of the testing group (18 subjects) based on spatial similarity analysis. Results suggest that it is feasible to extract language activations from rs-fMRI at the individual subject level, and two empirically defined templates (that focuses on frontal language areas and that incorporates both frontal and temporal language areas) demonstrated the best performance. We propose a semi-automated language component identification procedure and discuss the practical concerns and suggestions for this approach to be used in clinical fMRI language mapping.

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.

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.

BACKGROUND:Incidence and predictors of neurosurgical interventions following nonsevere traumatic brain injury (TBI) with mildly abnormal head computed tomographic (CT) findings are poorly defined. Despite this, neurosurgical consultation is routinely requested in this patient population. Our objective was to determine incidence of neurosurgical intervention in this patient population and identify clinical and radiographic features predicting the subsequent need for these interventions. METHODS:We identified all consecutive adult patients with nonsevere TBI admitted from January 1, 2001, through December 31, 2010. The definitions of "mildly abnormal initial head CT findings" and "neurosurgical interventions" were determined a priori by author consensus. Cumulative incidence of neurosurgical interventions was determined, and multivariate logistic regression was used to identify independent predictors of neurosurgical intervention. RESULTS:Of 677 patients, 51 underwent neurosurgical intervention for a cumulative incidence of 7.5%. Only 1.6% required an intracranial procedure. In adjusted analysis, presence of coagulopathy (odds ratio [OR], 2.21; 95% confidence interval [CI], 1.13-4.3; p = 0.02), suspected cerebrospinal fluid leak (OR, 11.36; 95% CI, 2.83-45.58; p = 0.001), any basal cistern or sylvian fissure subarachnoid hemorrhage (OR, 2.94; 95% CI, 1.56-5.57; p = 0.001), depressed skull fracture (OR, 2.84; 95% CI, 1.29-6.28; p = 0.01), or unstable repeated head CT findings (OR, 2.81; 95% CI, 1.52-5.2; p = 0.001) remained an independent predictor of the need for subsequent neurosurgical intervention. CONCLUSION/CONCLUSIONS:Among patients with nonsevere TBI and mildly abnormal head imaging findings in which routine neurosurgical consultation is obtained, there is a low incidence of neurosurgical interventions. Our findings suggest that routine early neurosurgical consultation in this patient population may not be necessary; however, this should be tested in a prospective, comparative study. LEVEL OF EVIDENCE/METHODS:Prognostic study, level III; therapeutic study, level IV.

OBJECT/OBJECTIVE:The extent of resection (EOR) is a known prognostic factor in patients with glioblastoma. However, gross-total resection (GTR) is not always achieved. Understanding the factors that prevent GTR is helpful in surgical planning and when counseling patients. The goal of this study was to identify demographic, tumor-related, and technical factors that influence EOR and to define the relationship between the surgeon's impression of EOR and radiographically determined EOR. METHODS:The authors performed a retrospective review of the electronic medical records to identify all patients who underwent craniotomy for glioblastoma resection between 2006 and 2009 and who had both preoperative and postoperative MRI studies. Forty-six patients were identified and were included in the study. Image analysis software (FIJI) was used to perform volumetric analysis of tumor size and EOR based on preoperative and postoperative MRI. Using multivariate analysis, the authors assessed factors associated with EOR and residual tumor volume. Perception of resectability was described using bivariate statistics, and survival was described using the log-rank test and Kaplan-Meier curves. RESULTS:The EOR was less for tumors in eloquent areas (p = 0.014) and those touching ventricles (p = 0.031). Left parietal tumors had significantly greater residual volume (p = 0.042). The average EOR was 91.0% in this series. There was MRI-demonstrable residual tumor in 69.6% of cases (16 of 23) in which GTR was perceived by the surgeon. Expert reviewers agreed that GTR could be safely achieved in 37.0% of patients (17 of 46) in this series. Among patients with safely resectable tumors, radiographically complete resection was achieved in 23.5% of patients (4 of 17). An EOR greater than 90% was associated with a significantly greater 1-year survival (76.5%) than an EOR less than 90% (p = 0.005). CONCLUSIONS:The authors' findings confirm that tumor location affects EOR and suggest that EOR may also be influenced by the surgeon's ability to judge the presence of residual tumor during surgery. The surgeon's ability to judge completeness of resection during surgery is commonly inaccurate. The authors' study confirms the impact of EOR on 1-year survival.

Conventional histopathology with hematoxylin & eosin (H&E) has been the gold standard for histopathological diagnosis of a wide range of diseases. However, it is not performed in vivo and requires thin tissue sections obtained after tissue biopsy, which carries risk, particularly in the central nervous system. Here we describe the development of an alternative, multicolored way to visualize tissue in real-time through the use of coherent Raman imaging (CRI), without the use of dyes. CRI relies on intrinsic chemical contrast based on vibrational properties of molecules and intrinsic optical sectioning by nonlinear excitation. We demonstrate that multicolor images originating from CH(2) and CH(3) vibrations of lipids and protein, as well as two-photon absorption of hemoglobin, can be obtained with subcellular resolution from fresh tissue. These stain-free histopathological images show resolutions similar to those obtained by conventional techniques, but do not require tissue fixation, sectioning or staining of the tissue analyzed.

Neuronavigation has become an ubiquitous tool in the surgical management of brain tumors. This review describes the use and limitations of current neuronavigational systems for brain tumor biopsy and resection. Methods for integrating intraoperative imaging into neuronavigational datasets developed to address the diminishing accuracy of positional information that occurs over the course of brain tumor resection are discussed. In addition, the process of integration of functional MRI and tractography into navigational models is reviewed. Finally, emerging concepts and future challenges relating to the development and implementation of experimental imaging technologies in the navigational environment are explored.

First described for use in mapping the human visual cortex in 1991, functional magnetic resonance imaging (fMRI) is based on blood-oxygen level dependent (BOLD) changes in cortical regions that occur during specific tasks. Typically, an overabundance of oxygenated (arterial) blood is supplied during activation of brain areas. Consequently, the venous outflow from the activated areas contains a higher concentration of oxyhemoglobin, which changes the paramagnetic properties of the tissue that can be detected during a T2-star acquisition. fMRI data can be acquired in response to specific tasks or in the resting state. fMRI has been widely applied to studying physiologic and pathophysiologic diseases of the brain. This review will discuss the most common current clinical applications of fMRI as well as emerging directions.