SignificanceAccurate identification between pathologic (e.g., tumors) and healthy brain tissue is a critical need in neurosurgery. However, conventional surgical adjuncts have significant limitations toward achieving this goal (e.g., image guidance based on pre-operative imaging becomes inaccurate up to 3 cm as surgery proceeds). Hyperspectral imaging (HSI) has emerged as a potential powerful surgical adjunct to enable surgeons to accurately distinguish pathologic from normal tissues.AimWe review HSI techniques in neurosurgery; categorize, explain, and summarize their technical and clinical details; and present some promising directions for future work.ApproachWe performed a literature search on HSI methods in neurosurgery focusing on their hardware and implementation details; classification, estimation, and band selection methods; publicly available labeled and unlabeled data; image processing and augmented reality visualization systems; and clinical study conclusions.ResultsWe present a detailed review of HSI results in neurosurgery with a discussion of over 25 imaging systems, 45 clinical studies, and 60 computational methods. We first provide a short overview of HSI and the main branches of neurosurgery. Then, we describe in detail the imaging systems, computational methods, and clinical results for HSI using reflectance or fluorescence. Clinical implementations of HSI yield promising results in estimating perfusion and mapping brain function, classifying tumors and healthy tissues (e.g., in fluorescence-guided tumor surgery, detecting infiltrating margins not visible with conventional systems), and detecting epileptogenic regions. Finally, we discuss the advantages and disadvantages of HSI approaches and interesting research directions as a means to encourage future development.ConclusionsWe describe a number of HSI applications across every major branch of neurosurgery. We believe these results demonstrate the potential of HSI as a powerful neurosurgical adjunct as more work continues to enable rapid acquisition with smaller footprints, greater spectral and spatial resolutions, and improved detection.
Fluorescence imaging has shown promise as an adjunct to improve the extent of resection in neurosurgery and oncologic
surgery. Nevertheless, current fluorescence imaging techniques do not account for the heterogeneous attenuation effects
of tissue optical properties. In this work, we present a novel imaging system that performs real time quantitative
fluorescence imaging using Single Snapshot Optical Properties (SSOP) imaging. We developed the technique and
performed initial phantom studies to validate the quantitative capabilities of the system for intraoperative feasibility.
Overall, this work introduces a novel real-time quantitative fluorescence imaging method capable of being used
intraoperatively for neurosurgical guidance.
A diffuse imaging method is presented that enables wide-field estimation of the depth of fluorescent molecular markers in turbid media by quantifying the deformation of the detected fluorescence spectra due to the wavelength-dependent light attenuation by overlying tissue. This is achieved by measuring the ratio of the fluorescence at two wavelengths in combination with normalization techniques based on diffuse reflectance measurements to evaluate tissue attenuation variations for different depths. It is demonstrated that fluorescence topography can be achieved up to a 5 mm depth using a near-infrared dye with millimeter depth accuracy in turbid media having optical properties representative of normal brain tissue. Wide-field depth estimates are made using optical technology integrated onto a commercial surgical microscope, making this approach feasible for real-world applications.
Fluorescence-guidance is a useful adjunct to maximize brain tumor resection but current commercial systems are limited by subjective assessment of fluorescence, low sensitivity and non-spectrally-resolved detection. We present a quantitative, spectrally-resolved system integrated onto a commercial neurosurgical microscope that performs spectrallyresolved detection and corrects for effects of tissue optical absorption and scattering on the detected fluorescence signal to image the true fluorophore concentration. Pre-clinical studies in rodent glioma models using multiple fluorophores (PpIX, fluorescein) and clinical studies demonstrate improved residual tumor tissue detection. This quantitative, spectrally-resolved technique opens the door to simultaneous image-guided surgery of multiple fluorophores in the visible and near infrared.
Multifrequency (0 to 0.3 mm−1), multiwavelength (633, 680, 720, 800, and 820 nm) spatial frequency domain imaging (SFDI) of 5-aminolevulinic acid-induced protoporphyrin IX (PpIX) was used to recover absorption, scattering, and fluorescence properties of glioblastoma multiforme spheroids in tissue-simulating phantoms and in vivo in a mouse model. Three-dimensional tomographic reconstructions of the frequency-dependent remitted light localized the depths of the spheroids within 500 μm, and the total amount of PpIX in the reconstructed images was constant to within 30% when spheroid depth was varied. In vivo tumor-to-normal contrast was greater than ∼ 1.5 in reduced scattering coefficient for all wavelengths and was ∼ 1.3 for the tissue concentration of deoxyhemoglobin (ctHb). The study demonstrates the feasibility of SFDI for providing enhanced image guidance during surgical resection of brain tumors.
Biomarkers are indicators of biological processes and hold promise for the diagnosis and treatment of disease. Gliomas represent a heterogeneous group of brain tumors with marked intra- and inter-tumor variability. The extent of surgical resection is a significant factor influencing post-surgical recurrence and prognosis. Here, we used fluorescence and reflectance spectral signatures for in vivo quantification of multiple biomarkers during glioma surgery, with fluorescence contrast provided by exogenously-induced protoporphyrin IX (PpIX) following administration of 5-aminolevulinic acid. We performed light-transport modeling to quantify multiple biomarkers indicative of tumor biological processes, including the local concentration of PpIX and associated photoproducts, total hemoglobin concentration, oxygen saturation, and optical scattering parameters. We developed a diagnostic algorithm for intra-operative tissue delineation that accounts for the combined tumor-specific predictive capabilities of these quantitative biomarkers. Tumor tissue delineation achieved accuracies of up to 94% (specificity = 94%, sensitivity = 94%) across a range of glioma histologies beyond current state-of-the-art optical approaches, including state-of-the-art fluorescence image guidance. This multiple biomarker strategy opens the door to optical methods for surgical guidance that use quantification of well-established neoplastic processes. Future work would seek to validate the predictive power of this proof-of-concept study in a separate larger cohort of patients.
Maximizing the extent of brain tumor resection correlates with improved survival and quality of life outcomes in
patients. Optimal surgical resection requires accurate discrimination between normal and abnormal, cancerous tissue. We
present our recent experience using quantitative optical spectroscopy in 5-aminolevulinic acid (ALA)-induced
protoporphyrin IX (PpIX) fluorescence-guided resection. Exogenous administration of ALA leads to preferential
accumulation in tumor tissue of the fluorescent compound, PpIX, which can be used for in vivo surgical guidance. Using
the state of the art approach with a fluorescence surgical microscope, we have been able to visualize a subset of brain
tumors, but the sensitivity and accuracy of fluorescence detection for tumor tissue with this system are low. To take full
advantage of the biological selectivity of PpIX accumulation in brain tumors, we used a quantitative optical spectroscopy
system for in vivo measurements of PpIX tissue concentrations. We have shown that, using our quantitative approach for
determination of biomarker concentrations, ALA-induced PpIX fluorescence-guidance can achieve accuracies of greater
than 90% for most tumor histologies. Here we show multivariate analysis of fluorescence and diffuse reflectance signals
in brain tumors with comparable diagnostic performance to our previously reported quantitative approach. These results
are promising, since they show that technological improvements in current fluorescence-guided surgical technologies
and more biologically relevant approaches are required to take full advantage of fluorescent biomarkers, achieve better
tumor identification, increase extent of resection, and subsequently, lead to improve survival and quality of life in
patients.
Astrogliotic tissue displays markedly increased levels of ALA-induced PpIX fluorescence, making it useful for
fluorescence-guided resection in glioma surgery. In patients with temporal lobe epilepsy (TLE) and corresponding
animal models, there are areas of astrogliosis that often co-localize with the epileptic focus, which can be resected to
eliminate seizures in the majority of treated patients. If this epileptogenic tissue can exhibit PpIX fluorescence that is
sufficiently localized, it could potentially help identify margins in epilepsy surgery. We tested the hypothesis that
ALA-induced PpIX fluorescence could visually accentuate epileptogenic tissue, using an established animal model
of chronic TLE. An acute dose of pilocarpine was used to induce chronic seizure activity in a rat. This rat and a
normal control were given ALA, euthanized, and brains examined post-mortem for PpIX fluorescence and
neuropathology. Preliminary evidence indicates increased PpIX fluorescence in areas associated with chronic
epileptic changes and seizure generation in TLE, including the hippocampus and parahippocampal areas. In
addition, strong PpIX fluorescence was clearly observed in layer II of the piriform cortex, a region known for
epileptic reorganization and involvement in the generation of seizures in animal studies. We are further investigating
whether ALA-induced PpIX fluorescence can consistently identify epileptogenic zones, which could warrant the
extension of this technique to clinical studies for use as an adjuvant guidance technology in the resection of epileptic
tissue.
In image-guided neurosurgery, preoperative images are typically used for surgical planning and intraoperative guidance.
The accuracy of preoperative images can be significantly compromised by intraoperative brain deformation. To
compensate for brain shift, biomechanical finite element models have been used to assimilate intraoperative data to
simulate brain deformation. The clinical feasibility of the approach strongly depends on its accuracy and efficiency. In
order to facilitate and streamline data flow, we have developed graphical user interfaces (GUIs) to provide efficient
image updates in the operating room (OR). The GUIs are organized in a top-down hierarchy with a main control panel
that invokes and monitors a series of sub-GUIs dedicated to perform tasks involved in various aspects of computations of
whole-brain deformation. These GUIs are used to segment brain, generate case-specific brain meshes, and assign and
visualize case-specific boundary conditions (BC). Registration between intraoperative ultrasound (iUS) images acquired
pre- and post-durotomy is also facilitated by a dedicated GUI to extract sparse displacement data used to drive a
biomechanical model. Computed whole-brain deformation is then used to morph preoperative MR images (pMR) to
generate a model-updated image set (i.e., uMR) for intraoperative guidance (accuracy of 1-2 mm). These task-driven
GUIs have been designed to be fault-tolerant, user-friendly, and with sufficient automation. In this paper, we present the
modular components of the GUIs and demonstrate the typical workflow through a clinical patient case.
Recent evidence suggests a correlation between extent of tumor resection and patient prognosis, making maximal tumor
resection a clinical ideal for neurosurgeons. Our group is currently undertaking a clinical study using fluorescence-based
detection of tumor coupled with a standard 3-D image guidance system to study the effectiveness of fluorescence-based
detection in the neurosurgical operating room. For fluorescence-based detection, we used 5-aminolevulinic acid to
induce accumulation of protoporphyrin IX in malignant tissues. In this paper, we chose one prototypical, highly
fluorescent case of glioblastoma multiforme, a high-grade glioma, to highlight some of the key findings and
methodology used in our study of fluorescence-based detection and resection of brain tumors.
We present the methods that are being used in the scope of an on-going clinical trial designed to assess the usefulness of
ALA-PpIX fluorescence imaging when used in conjunction with pre-operative MRI. The overall objective is to develop
imaging-based neuronavigation approaches to aid in maximizing the completeness of brain tumor resection, thereby
improving patient survival rate. In this paper we present the imaging methods that are used, emphasizing technical
aspects relating to the fluorescence optical microscope, including initial validation approaches based on phantom and
small-animal experiments. The surgical workflow is then described in detail based on a high-grade glioma resection we
performed.
Access to the requested content is limited to institutions that have purchased or subscribe to SPIE eBooks.
You are receiving this notice because your organization may not have SPIE eBooks access.*
*Shibboleth/Open Athens users─please
sign in
to access your institution's subscriptions.
To obtain this item, you may purchase the complete book in print or electronic format on
SPIE.org.
INSTITUTIONAL Select your institution to access the SPIE Digital Library.
PERSONAL Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.