Olutayo Olubiyi

Label-Free Neurosurgical Pathology with Stimulated Raman Imaging

The goal of brain tumor surgery is to maximize tumor removal without injuring critical brain structures. Achieving this goal is challenging as it can be difficult to distinguish tumor from nontumor tissue. While standard histopathology provides information that could assist tumor delineation, it cannot be performed iteratively during surgery as freezing, sectioning, and staining of the tissue require too much time. Stimulated Raman scattering (SRS) microscopy is a powerful label-free chemical imaging technology that enables rapid mapping of lipids and proteins within a fresh specimen. This information can be rendered into pathology-like images. Although this approach has been used to assess the density of glioma cells in murine orthotopic xenografts models and human brain tumors, tissue heterogeneity in clinical brain tumors has not yet been fully evaluated with SRS imaging. Here we profile 41 specimens resected from 12 patients with a range of brain tumors. By evaluating large-scale stimulated Raman imaging data and correlating this data with current clinical gold standard of histopathology for 4,422 fields of view, we capture many essential diagnostic hallmarks for glioma classification. Notably, in fresh tumor samples, we observe additional features, not seen by conventional methods, including extensive lipid droplets within glioma cells, collagen deposition in gliosarcoma, and irregularity and disruption of myelinated fibers in areas infiltrated by oligodendroglioma cells. The data are freely available in a public resource to foster diagnostic training and to permit additional interrogation. Our work establishes the methodology and provides a significant collection of reference images for label-free neurosurgical pathology. Cancer Res; 76(12); 3451-62. ©2016 AACR.

3T MR-guided in-bore transperineal prostate biopsy: A comparison of robotic and manual needle-guidance templates

To demonstrate the utility of a robotic needle‐guidance template device as compared to a manual template for in‐bore 3T transperineal magnetic resonance imaging (MRI)‐guided prostate biopsy.

Reconstruction of the arcuate fasciculus for surgical planning in the setting of peritumoral edema using two-tensor unscented Kalman filter tractography

Background Diffusion imaging tractography is increasingly used to trace critical fiber tracts in brain tumor patients to reduce the risk of post-operative neurological deficit. However, the effects of peritumoral edema pose a challenge to conventional tractography using the standard diffusion tensor model. The aim of this study was to present a novel technique using a two-tensor unscented Kalman filter (UKF) algorithm to track the arcuate fasciculus (AF) in brain tumor patients with peritumoral edema. Methods Ten right-handed patients with left-sided brain tumors in the vicinity of language-related cortex and evidence of significant peritumoral edema were retrospectively selected for the study. All patients underwent 3-Tesla magnetic resonance imaging (MRI) including a diffusion-weighted dataset with 31 directions. Fiber tractography was performed using both single-tensor streamline and two-tensor UKF tractography. A two-regions-of-interest approach was applied to perform the delineation of the AF. Results from the two different tractography algorithms were compared visually and quantitatively. Results Using single-tensor streamline tractography, the AF appeared disrupted in four patients and contained few fibers in the remaining six patients. Two-tensor UKF tractography delineated an AF that traversed edematous brain areas in all patients. The volume of the AF was significantly larger on two-tensor UKF than on single-tensor streamline tractography (p < 0.01). Conclusions Two-tensor UKF tractography provides the ability to trace a larger volume AF than single-tensor streamline tractography in the setting of peritumoral edema in brain tumor patients.

Automated white matter fiber tract identification in patients with brain tumors

We propose a method for the automated identification of key white matter fiber tracts for neurosurgical planning, and we apply the method in a retrospective study of 18 consecutive neurosurgical patients with brain tumors. Our method is designed to be relatively robust to challenges in neurosurgical tractography, which include peritumoral edema, displacement, and mass effect caused by mass lesions. The proposed method has two parts. First, we learn a data-driven white matter parcellation or fiber cluster atlas using groupwise registration and spectral clustering of multi-fiber tractography from healthy controls. Key fiber tract clusters are identified in the atlas. Next, patient-specific fiber tracts are automatically identified using tractography-based registration to the atlas and spectral embedding of patient tractography. Results indicate good generalization of the data-driven atlas to patients: 80% of the 800 fiber clusters were identified in all 18 patients, and 94% of the 800 fiber clusters were found in 16 or more of the 18 patients. Automated subject-specific tract identification was evaluated by quantitative comparison to subject-specific motor and language functional MRI, focusing on the arcuate fasciculus (language) and corticospinal tracts (motor), which were identified in all patients. Results indicate good colocalization: 89 of 95, or 94%, of patient-specific language and motor activations were intersected by the corresponding identified tract. All patient-specific activations were within 3mm of the corresponding language or motor tract. Overall, our results indicate the potential of an automated method for identifying fiber tracts of interest for neurosurgical planning, even in patients with mass lesions.

Intraoperative Magnetic Resonance Imaging in Intracranial Glioma Resection: A Single-Center, Retrospective Blinded Volumetric Study

BACKGROUND Intraoperative magnetic resonance imaging (IoMRI) was devised to overcome brain shifts during craniotomies. Yet, the acceptance of IoMRI is limited. OBJECTIVE To evaluate impact of IoMRI on intracranial glioma resection outcome including overall patient survival. METHODS A retrospective review of records was performed on a cohort of 164 consecutive patients who underwent resection surgery for newly diagnosed intracranial gliomas either with or without IoMRI technology performed by 2 neurosurgeons in our center. Patient follow-up was at least 5 years. Extent of resection (EOR) was calculated using pre- and postoperative contrast-enhanced and T2-weighted MR-images. Adjusted analysis was performed to compare gross total resection (GTR), EOR, permanent surgery-associated neurologic deficit, and overall survival between the 2 groups. RESULTS Overall median EOR was 92.1%, and 97.45% with IoMRI use and 89.9% without IoMRI, with crude (unadjusted) P < 0.005. GTR was achieved in 49.3% of IoMRI cases, versus in only 21.4% of no-IoMRI cases, P < 0.001. GTR achieved was more with the use of IoMRI among gliomas located in both eloquent and noneloquent brain areas, P = 0.017 and <0.001, respectively. Permanent surgery-associated neurologic deficit was not (statistically) more significant with no-IoMRI, P = 0.284 (13.8% vs. 6.7%). In addition, the IoMRI group had better 5-year overall survival, P < 0.001. CONCLUSION This study shows that the use of IoMRI was associated with greater rates of EOR and GTR, and better overall 5-year survival in both eloquent brain areas located and non-eloquent brain areas located gliomas, with no increased risk of neurologic complication.

MALDI mass spectrometry imaging analysis of pituitary adenomas for near-real-time tumor delineation

Significance This study presents the use of matrix-assisted laser desorption/ionization (MALDI) mass spectrometry imaging (MSI) to detect and delineate pituitary tumors. Using MALDI MSI, it is possible to determine the peptide and protein hormone composition of pituitary tumor resection samples in fewer than 30 min. Surgeons could therefore have access to critical information for surgical decision-making in a near-real-time manner and be able to localize and discriminate pituitary tumor from nonpathological pituitary gland. This study supports the inclusion of MALDI MSI in the clinical workflow for the surgical resection of pituitary tumors, potentially allowing for improved surgical precision and patient outcomes. We present a proof of concept study designed to support the clinical development of mass spectrometry imaging (MSI) for the detection of pituitary tumors during surgery. We analyzed by matrix-assisted laser desorption/ionization (MALDI) MSI six nonpathological (NP) human pituitary glands and 45 hormone secreting and nonsecreting (NS) human pituitary adenomas. We show that the distribution of pituitary hormones such as prolactin (PRL), growth hormone (GH), adrenocorticotropic hormone (ACTH), and thyroid stimulating hormone (TSH) in both normal and tumor tissues can be assessed by using this approach. The presence of most of the pituitary hormones was confirmed by using MS/MS and pseudo-MS/MS methods, and subtyping of pituitary adenomas was performed by using principal component analysis (PCA) and support vector machine (SVM). Our proof of concept study demonstrates that MALDI MSI could be used to directly detect excessive hormonal production from functional pituitary adenomas and generally classify pituitary adenomas by using statistical and machine learning analyses. The tissue characterization can be completed in fewer than 30 min and could therefore be applied for the near-real-time detection and delineation of pituitary tumors for intraoperative surgical decision-making.

Corticospinal tract modeling for neurosurgical planning by tracking through regions of peritumoral edema and crossing fibers using two-tensor unscented Kalman filter tractography

PurposeThe aim of this study was to present a tractography algorithm using a two-tensor unscented Kalman filter (UKF) to improve the modeling of the corticospinal tract (CST) by tracking through regions of peritumoral edema and crossing fibers.MethodsTen patients with brain tumors in the vicinity of motor cortex and evidence of significant peritumoral edema were retrospectively selected for the study. All patients underwent 3-T magnetic resonance imaging (MRI) including functional MRI (fMRI) and a diffusion-weighted data set with 31 directions. Fiber tracking was performed using both single-tensor streamline and two-tensor UKF tractography methods. A two-region-of-interest approach was used to delineate the CST. Results from the two tractography methods were compared visually and quantitatively. fMRI was applied to identify the functional fiber tracts.ResultsSingle-tensor streamline tractography underestimated the extent of tracts running through the edematous areas and could only track the medial projections of the CST. In contrast, two-tensor UKF tractography tracked fanning projections of the CST despite peritumoral edema and crossing fibers. Based on visual inspection, the two-tensor UKF tractography delineated tracts that were closer to motor fMRI activations, and it was apparently more sensitive than single-tensor streamline tractography to define the tracts directed to the motor sites. The volume of the CST was significantly larger on two-tensor UKF than on single-tensor streamline tractography (

Radiation dose during CT-guided percutaneous cryoablation of renal tumors: Effect of a dose reduction protocol

p < 0.001