Label-free delineation of brain tumors by coherent anti-Stokes Raman scattering microscopy in an orthotopic mouse model and human glioblastoma

Label-free optical imaging for brain cancer assessment

Advances in label-free optical imaging offer a promising avenue for brain cancer assessment, providing high-resolution, real-time insights without the need for radiation or exogeneous agents. These cost-effective and intricately detailed techniques overcome the limitations inherent in magnetic resonance imaging (MRI), computed tomography (CT), and positron emission tomography (PET) scans by offering superior resolution and more readily accessible imaging options. This comprehensive review explores a variety of such methods, including photoacoustic imaging (PAI), optical coherence tomography (OCT), Raman imaging, and IR microscopy. It focuses on their roles in the detection, diagnosis, and management of brain tumors. By highlighting recent advances in these imaging techniques, the review aims to underscore the importance of label-free optical imaging in enhancing early detection and refining therapeutic strategies for brain cancer.

Spectral insights: Navigating the frontiers of biomedical and microbiological exploration with Raman spectroscopy

Raman spectroscopy (RS), a powerful analytical technique, has gained increasing recognition and utility in the fields of biomedical and biological research. Raman spectroscopic analyses find extensive application in the field of medicine and are employed for intricate research endeavors and diagnostic purposes. Consequently, it enjoys broad utilization within the realm of biological research, facilitating the identification of cellular classifications, metabolite profiling within the cellular milieu, and the assessment of pigment constituents within microalgae. This article also explores the multifaceted role of RS in these domains, highlighting its distinct advantages, acknowledging its limitations, and proposing strategies for enhancement.

Advancements in Intraoperative Near-Infrared Fluorescence Imaging for Accurate Tumor Resection: A Promising Technique for Improved Surgical Outcomes and Patient Survival

Clear surgical margins for solid tumor resection are essential for preventing cancer recurrence and improving overall patient survival. Complete resection of tumors is often limited by a surgeon's ability to accurately locate malignant tissues and differentiate them from healthy tissue. Therefore, techniques or imaging modalities are required that would ease the identification and resection of tumors by real-time intraoperative visualization of tumors. Although conventional imaging techniques such as positron emission tomography (PET), computed tomography (CT), magnetic resonance imaging (MRI), or radiography play an essential role in preoperative diagnostics, these cannot be utilized in intraoperative tumor detection due to their large size, high cost, long imaging time, and lack of cancer specificity. The inception of several imaging techniques has paved the way to intraoperative tumor margin detection with a high degree of sensitivity and specificity. Particularly, molecular imaging using near-infrared fluorescence (NIRF) based nanoprobes provides superior imaging quality due to high signal-to-noise ratio, deep penetration to tissues, and low autofluorescence, enabling accurate tumor resection and improved survival rates. In this review, we discuss the recent developments in imaging technologies, specifically focusing on NIRF nanoprobes that aid in highly specific intraoperative surgeries with real-time recognition of tumor margins.

Dielectric Spectroscopy Shows a Permittivity Contrast between Meningioma Tissue and Brain White and Gray Matter-A Potential Physical Biomarker for Meningioma Discrimination

The effectiveness of surgical resection of meningioma, the most common primary CNS tumor, depends on the capability to intraoperatively discriminate between the meningioma tissue and the surrounding brain white and gray matter tissues. Aiming to find a potential biomarker based on tissue permittivity, dielectric spectroscopy of meningioma, white matter, and gray matter ex vivo tissues was performed using the open-ended coaxial probe method in the microwave frequency range from 0.5 to 18 GHz. The averages and the 95% confidence intervals of the measured permittivity for each tissue were compared. The results showed the absence of overlap between the 95% confidence intervals for meningioma tissue and for brain white and gray matter, indicating a significant difference in average permittivity (p ≤ 0.05) throughout almost the entire measured frequency range, with the most pronounced contrast found between 2 GHz and 5 GHz. The discovered contrast is relevant as a potential physical biomarker to discriminate meningioma tissue from the surrounding brain tissues by means of permittivity measurement, e.g., for intraoperative meningioma margin assessment. The permittivity models for each tissue, developed in this study as its byproducts, will allow more accurate electromagnetic modeling of brain tumor and healthy tissues, facilitating the development of new microwave-based medical devices and tools.

Raman Spectroscopy: A Tool for Molecular Fingerprinting of Brain Cancer

Brain cancer is one of those few cancers with very high mortality and low five-year survival rate. First and foremost reason for the woes is the difficulty in diagnosing and monitoring the progression of brain tumors both benign and malignant, noninvasively and in real time. This raises a need in this hour for a tool to diagnose the tumors in the earliest possible time frame. On the other hand, Raman spectroscopy which is well-known for its ability to precisely represent the molecular markers available in any sample given, including biological ones, with great sensitivity and specificity. This has led to a number of studies where Raman spectroscopy has been used in brain tumors in various ways. This review article highlights the fundamentals of Raman spectroscopy and its types including conventional Raman, SERS, SORS, SRS, CARS, etc. are used in brain tumors for diagnostics, monitoring, and even theragnostics, collating all the major works in the area. Also, the review explores how Raman spectroscopy can be even more effectively used in theragnostics and the clinical level which would make them a one-stop solution for all brain cancer needs in the future.

Discovering Glioma Tissue through Its Biomarkers' Detection in Blood by Raman Spectroscopy and Machine Learning

The most commonly occurring malignant brain tumors are gliomas, and among them is glioblastoma multiforme. The main idea of the paper is to estimate dependency between glioma tissue and blood serum biomarkers using Raman spectroscopy. We used the most common model of human glioma when continuous cell lines, such as U87, derived from primary human tumor cells, are transplanted intracranially into the mouse brain. We studied the separability of the experimental and control groups by machine learning methods and discovered the most informative Raman spectral bands. During the glioblastoma development, an increase in the contribution of lactate, tryptophan, fatty acids, and lipids in dried blood serum Raman spectra were observed. This overlaps with analogous results of glioma tissues from direct Raman spectroscopy studies. A non-linear relationship between specific Raman spectral lines and tumor size was discovered. Therefore, the analysis of blood serum can track the change in the state of brain tissues during the glioma development.

Raman Spectroscopy on Brain Disorders: Transition from Fundamental Research to Clinical Applications

Brain disorders such as brain tumors and neurodegenerative diseases (NDs) are accompanied by chemical alterations in the tissues. Early diagnosis of these diseases will provide key benefits for patients and opportunities for preventive treatments. To detect these sophisticated diseases, various imaging modalities have been developed such as computed tomography (CT), magnetic resonance imaging (MRI), and positron emission tomography (PET). However, they provide inadequate molecule-specific information. In comparison, Raman spectroscopy (RS) is an analytical tool that provides rich information about molecular fingerprints. It is also inexpensive and rapid compared to CT, MRI, and PET. While intrinsic RS suffers from low yield, in recent years, through the adoption of Raman enhancement technologies and advanced data analysis approaches, RS has undergone significant advancements in its ability to probe biological tissues, including the brain. This review discusses recent clinical and biomedical applications of RS and related techniques applicable to brain tumors and NDs.

Lipid Alterations in Glioma: A Systematic Review

Gliomas are highly lethal tumours characterised by heterogeneous molecular features, producing various metabolic phenotypes leading to therapeutic resistance. Lipid metabolism reprogramming is predominant and has contributed to the metabolic plasticity in glioma. This systematic review aims to discover lipids alteration and their biological roles in glioma and the identification of potential lipids biomarker. This systematic review was conducted using the preferred reporting items for systematic reviews and meta-analyses (PRISMA) guidelines. Extensive research articles search for the last 10 years, from 2011 to 2021, were conducted using four electronic databases, including PubMed, Web of Science, CINAHL and ScienceDirect. A total of 158 research articles were included in this study. All studies reported significant lipid alteration between glioma and control groups, impacting glioma cell growth, proliferation, drug resistance, patients' survival and metastasis. Different lipids demonstrated different biological roles, either beneficial or detrimental effects on glioma. Notably, prostaglandin (PGE2), triacylglycerol (TG), phosphatidylcholine (PC), and sphingosine-1-phosphate play significant roles in glioma development. Conversely, the most prominent anti-carcinogenic lipids include docosahexaenoic acid (DHA), eicosapentaenoic acid (EPA), and vitamin D3 have been reported to have detrimental effects on glioma cells. Furthermore, high lipid signals were detected at 0.9 and 1.3 ppm in high-grade glioma relative to low-grade glioma. This evidence shows that lipid metabolisms were significantly dysregulated in glioma. Concurrent with this knowledge, the discovery of specific lipid classes altered in glioma will accelerate the development of potential lipid biomarkers and enhance future glioma therapeutics.

Intraoperative tissue classification methods in orthopedic and neurological surgeries: A systematic review

Accurate tissue differentiation during orthopedic and neurological surgeries is critical, given that such surgeries involve operations on or in the vicinity of vital neurovascular structures and erroneous surgical maneuvers can lead to surgical complications. By now, the number of emerging technologies tackling the problem of intraoperative tissue classification methods is increasing. Therefore, this systematic review paper intends to give a general overview of existing technologies. The review was done based on the PRISMA principle and two databases: PubMed and IEEE Xplore. The screening process resulted in 60 full-text papers. The general characteristics of the methodology from extracted papers included data processing pipeline, machine learning methods if applicable, types of tissues that can be identified with them, phantom used to conduct the experiment, and evaluation results. This paper can be useful in identifying the problems in the current status of the state-of-the-art intraoperative tissue classification methods and designing new enhanced techniques.

Clinical Spectroscopy: Lost in Translation?

This Focal Point Review paper discusses the developments of biomedical Raman and infrared spectroscopy, and the recent strive towards these technologies being regarded as reliable clinical tools. The promise of vibrational spectroscopy in the field of biomedical science, alongside the development of computational methods for spectral analysis, has driven a plethora of proof-of-concept studies which convey the potential of various spectroscopic approaches. Here we report a brief review of the literature published over the past few decades, with a focus on the current technical, clinical, and economic barriers to translation, namely the limitations of many of the early studies, and the lack of understanding of clinical pathways, health technology assessments, regulatory approval, clinical feasibility, and funding applications. The field of biomedical vibrational spectroscopy must acknowledge and overcome these hurdles in order to achieve clinical efficacy. Current prospects have been overviewed with comment on the advised future direction of spectroscopic technologies, with the aspiration that many of these innovative approaches can ultimately reach the frontier of medical diagnostics and many clinical applications.

Image-to-image translation of label-free molecular vibrational images for a histopathological review using the UNet+/seg-cGAN model

Translating images generated by label-free microscopy imaging, such as Coherent Anti-Stokes Raman Scattering (CARS), into more familiar clinical presentations of histopathological images will help the adoption of real-time, spectrally resolved label-free imaging in clinical diagnosis. Generative adversarial networks (GAN) have made great progress in image generation and translation, but have been criticized for lacking precision. In particular, GAN has often misinterpreted image information and identified incorrect content categories during image translation of microscopy scans. To alleviate this problem, we developed a new Pix2pix GAN model that simultaneously learns classifying contents in the images from a segmentation dataset during the image translation training. Our model integrates UNet+ with seg-cGAN, conditional generative adversarial networks with partial regularization of segmentation. Technical innovations of the UNet+/seg-cGAN model include: (1) replacing UNet with UNet+ as the Pix2pix cGAN's generator to enhance pattern extraction and richness of the gradient, and (2) applying the partial regularization strategy to train a part of the generator network as the segmentation sub-model on a separate segmentation dataset, thus enabling the model to identify correct content categories during image translation. The quality of histopathological-like images generated based on label-free CARS images has been improved significantly.

Discrimination of glioma patient-derived cells from healthy astrocytes by exploiting Raman spectroscopy

Glioblastoma multiforme (GBM) is one of the most common and aggressive brain tumors. It presents a very bad prognosis with a patients' overall survival of 12-15 months; treatment failure is mainly ascribable to tumor recurrence. The development of new tools, that could help the precise detection of the tumor border, is thus an urgent need. During the last decades, different vibrational spectroscopy techniques have been developed to distinguish cancer tissue from heathy tissue; in the present work, we compared GBM cells deriving from four patients with healthy human astrocytes using Raman spectroscopy. We have shown that the region between 1000 and 1300 cm^-1 is enough informative for this discrimination, indeed highlighting that peaks related to DNA/RNA and cytochrome c are increased in cancer cells. Finally, our model has been able to discriminate cancer cells from healthy cells with an average accuracy of 92.5%. We believe that this study might help to further understand which are the essential Raman peaks exploitable in the detection of cancer cells, with important perspectives under a diagnostic point of view.

Suppression of the non-linear background in a multimode fibre CARS endoscope

Multimode fibres show great potential for use as miniature endoscopes for imaging deep in tissue with minimal damage. When used for coherent anti-Stokes Raman scattering (CARS) microscopy with femtosecond excitation sources, a high band-width probe is required to efficiently focus the broadband laser pulses at the sample plane. Although graded-index (GRIN) fibres have a large bandwidth, it is accompanied by a strong background signal from four-wave mixing and other non-linear processes occurring inside the fibre. We demonstrate that using a composite probe consisting of a GRIN fibre with a spliced on step-index fibre reduces the intensity of the non-linear background by more than one order of magnitude without significantly decreasing the focusing performance of the probe. Using this composite probe we acquire CARS images of biologically relevant tissue such as myelinated axons in the brain with good contrast.

Raman Imaging and Fluorescence Lifetime Imaging Microscopy for Diagnosis of Cancer State and Metabolic Monitoring

Hurdles for effective tumor therapy are delayed detection and limited effectiveness of systemic drug therapies by patient-specific multidrug resistance. Non-invasive bioimaging tools such as fluorescence lifetime imaging microscopy (FLIM) and Raman-microspectroscopy have evolved over the last decade, providing the potential to be translated into clinics for early-stage disease detection, in vitro drug screening, and drug efficacy studies in personalized medicine. Accessing tissue- and cell-specific spectral signatures, Raman microspectroscopy has emerged as a diagnostic tool to identify precancerous lesions, cancer stages, or cell malignancy. In vivo Raman measurements have been enabled by recent technological advances in Raman endoscopy and signal-enhancing setups such as coherent anti-stokes Raman spectroscopy or surface-enhanced Raman spectroscopy. FLIM enables in situ investigations of metabolic processes such as glycolysis, oxidative stress, or mitochondrial activity by using the autofluorescence of co-enzymes NADH and FAD, which are associated with intrinsic proteins as a direct measure of tumor metabolism, cell death stages and drug efficacy. The combination of non-invasive and molecular-sensitive in situ techniques and advanced 3D tumor models such as patient-derived organoids or microtumors allows the recapitulation of tumor physiology and metabolism in vitro and facilitates the screening for patient-individualized drug treatment options.

Artificial intelligence-augmented, label-free molecular imaging method for tissue identification, cancer diagnosis, and cancer margin detection

Label-free high-resolution molecular and cellular imaging strategies for intraoperative use are much needed, but not yet available. To fill this void, we developed an artificial intelligence-augmented molecular vibrational imaging method that integrates label-free and subcellular-resolution coherent anti-stokes Raman scattering (CARS) imaging with real-time quantitative image analysis via deep learning (artificial intelligence-augmented CARS or iCARS). The aim of this study was to evaluate the capability of the iCARS system to identify and differentiate the parathyroid gland and recurrent laryngeal nerve (RLN) from surrounding tissues and detect cancer margins. This goal was successfully met.

Toward Quantitative in vivo Label-Free Tracking of Lipid Distribution in a Zebrafish Cancer Model

Cancer cells often adapt their lipid metabolism to accommodate the increased fatty acid demand for membrane biogenesis and energy production. Upregulation of fatty acid uptake from the environment of cancer cells has also been reported as an alternative mechanism. To investigate the role of lipids in tumor onset and progression and to identify potential diagnostic biomarkers, lipids are ideally imaged directly within the intact tumor tissue in a label-free way. In this study, we investigated lipid accumulation and distribution in living zebrafish larvae developing a tumor by means of coherent anti-Stokes Raman scattering microscopy. Quantitative textural features based on radiomics revealed higher lipid accumulation in oncogene-expressing larvae compared to healthy ones. This high lipid accumulation could reflect an altered lipid metabolism in the hyperproliferating oncogene-expressing cells.

Minimizing OCT quantification error via a surface-tracking imaging probe

OCT-based quantitative tissue optical properties imaging is a promising technique for intraoperative brain cancer assessment. The attenuation coefficient analysis relies on the depth-dependent OCT intensity profile, thus sensitive to tissue surface positions relative to the imaging beam focus. However, it is almost impossible to maintain a steady tissue surface during intraoperative imaging due to the patient's arterial pulsation and breathing, the operator's motion, and the complex tissue surface geometry of the surgical cavity. In this work, we developed an intraoperative OCT imaging probe with a surface-tracking function to minimize the quantification errors in optical attenuation due to the tissue surface position variations. A compact OCT imaging probe was designed and engineered to have a long working distance of ∼ 41 mm and a large field of view of 4 × 4 mm² while keeping the probe diameter small (9 mm) to maximize clinical versatility. A piezo-based linear motor was integrated with the imaging probe and controlled based upon real-time feedback of tissue surface position inferred from OCT images. A GPU-assisted parallel processing algorithm was implemented, enabling detection and tracking of tissue surface in real-time and successfully suppressing more than 90% of the typical physiologically induced motion range. The surface-tracking intraoperative OCT imaging probe could maintain a steady beam focus inside the target tissue regardless of the surface geometry or physiological motions and enabled to obtain tissue optical attenuation reliably for assessing brain cancer margins in challenging intraoperative settings.

Label-free brain tumor imaging using Raman-based methods

INTRODUCTION

Label-free Raman-based imaging techniques create the possibility of bringing chemical and histologic data into the operation room. Relying on the intrinsic biochemical properties of tissues to generate image contrast and optical tissue sectioning, Raman-based imaging methods can be used to detect microscopic tumor infiltration and diagnose brain tumor subtypes.

METHODS

Here, we review the application of three Raman-based imaging methods to neurosurgical oncology: Raman spectroscopy, coherent anti-Stokes Raman scattering (CARS) microscopy, and stimulated Raman histology (SRH).

RESULTS

Raman spectroscopy allows for chemical characterization of tissue and can differentiate normal and tumor-infiltrated tissue based on variations in macromolecule content, both ex vivo and in vivo. To improve signal-to-noise ratio compared to conventional Raman spectroscopy, a second pulsed excitation laser can be used to coherently drive the vibrational frequency of specific Raman active chemical bonds (i.e. symmetric stretching of -CH₂ bonds). Coherent Raman imaging, including CARS and stimulated Raman scattering microscopy, has been shown to detect microscopic brain tumor infiltration in fresh brain tumor specimens with submicron image resolution. Advances in fiber-laser technology have allowed for the development of intraoperative SRH as well as artificial intelligence algorithms to facilitate interpretation of SRH images. With molecular diagnostics becoming an essential part of brain tumor classification, preliminary studies have demonstrated that Raman-based methods can be used to diagnose glioma molecular classes intraoperatively.

CONCLUSIONS

These results demonstrate how label-free Raman-based imaging methods can be used to improve the management of brain tumor patients by detecting tumor infiltration, guiding tumor biopsy/resection, and providing images for histopathologic and molecular diagnosis.

Rise of Raman spectroscopy in neurosurgery: a review

SIGNIFICANCE

Although the clinical potential for Raman spectroscopy (RS) has been anticipated for decades, it has only recently been used in neurosurgery. Still, few devices have succeeded in making their way into the operating room. With recent technological advancements, however, vibrational sensing is poised to be a revolutionary tool for neurosurgeons.

AIM

We give a summary of neurosurgical workflows and key translational milestones of RS in clinical use and provide the optics and data science background required to implement such devices.

APPROACH

We performed an extensive review of the literature, with a specific emphasis on research that aims to build Raman systems suited for a neurosurgical setting.

RESULTS

The main translatable interest in Raman sensing rests in its capacity to yield label-free molecular information from tissue intraoperatively. Systems that have proven usable in the clinical setting are ergonomic, have a short integration time, and can acquire high-quality signal even in suboptimal conditions. Moreover, because of the complex microenvironment of brain tissue, data analysis is now recognized as a critical step in achieving high performance Raman-based sensing.

CONCLUSIONS

The next generation of Raman-based devices are making their way into operating rooms and their clinical translation requires close collaboration between physicians, engineers, and data scientists.

Raman spectroscopy for rapid intra-operative margin analysis of surgically excised tumour specimens

Raman spectroscopy, a form of vibrational spectroscopy, has the ability to provide sensitive and specific biochemical analysis of tissue. This review article provides an in-depth analysis of the suitability of different Raman spectroscopy techniques in providing intra-operative margin analysis in a range of solid tumour pathologies. Surgical excision remains the primary treatment of a number of solid organ cancers. Incomplete excision of a tumour and positive margins on histopathological analysis is associated with a worse prognosis, the need for adjuvant therapies with significant side effects and a resulting financial burden. The provision of intra-operative margin analysis of surgically excised tumour specimens would be beneficial for a number of pathologies, as there are no widely adopted and accurate methods of margin analysis, beyond histopathology. The limitations of Raman spectroscopic studies to date are discussed and future work necessary to enable translation to clinical use is identified. We conclude that, although there remain a number of challenges in translating current techniques into a clinically effective tool, studies so far demonstrate that Raman Spectroscopy has the attributes to successfully perform highly accurate intra-operative margin analysis in a clinically relevant environment.

Coherent anti-Stokes Raman scattering imaging using silicon photomultipliers

Silicon photomultipliers (SiPMs) are an emerging solid-state alternative to photomultiplier tubes (PMTs) for low light detection, with similar gain but lower cost and lower operating voltage. We demonstrate coherent anti-Stokes Raman scattering (CARS) imaging in a side-by-side comparison of an uncooled SiPM with an uncooled multialkali PMT as well as a state-of-the-art cooled GaAsP PMT. We determine the optimum reverse-bias voltage for acquiring the best signal-to-noise ratio (SNR) for CARS imaging of lipids at ${2850}\;{{\rm cm}^{ - 1}}$2850cm^-1. We find that despite the higher dark counts, the SNR of CARS images acquired with the uncooled SiPM biased at an optimum voltage is better than that of the multialkali PMT and close to that of the cooled GaAsP PMT (${\sim}{1.5}$∼1.5 and ${\sim}{0.8}$∼0.8 times, respectively). This is due to the higher gain and lower excess noise factor related to the pulse height variability in the SiPM.

CARS-imaging guidance for fs-laser ablation precision surgery

Due to ageing populations the number of tumors is increasing worldwide. Successful surgical treatment requires complete resection of tumors to reduce recurrence rates. To reach this goal, novel methods combining in vivo tumor and tumor margin detection with low invasive precision surgical tools are needed. Coherent anti-Stokes Raman scattering (CARS) imaging is a highly promising optical tool for visualizing tumors based on characteristic changes in tissue morphology and molecular composition, while fs-laser ablation is to date the most precise surgical tool established in ophthalmology. In this contribution, CARS imaging has been combined with fs-laser ablation as a new approach for image-guided precision surgery for the first time. CARS guided fs-ablation has been applied to ablate brain, liver, skin, muscular and vascular tissues with μm-precision using sub-100 fs pulses of μJ level. We demonstrate superior imaging performance and contrast as well as detection of tissue margins by coherent Raman microscopy in comparison to laser reflectance imaging. The combination of CARS-image-guided tissue ablation is a promising tool for minimally invasive surgeries particularly in the vicinity of functional structures in the future.

Label-free multiphoton imaging allows brain tumor recognition based on texture analysis-a study of 382 tumor patients

Background

Label-free multiphoton microscopy has been suggested for intraoperative recognition and delineation of brain tumors. For any future clinical application, appropriate approaches for image acquisition and analysis have to be developed. Moreover, an evaluation of the reliability of the approach, taking into account inter- and intrapatient variability, is needed.

Methods

Coherent anti-Stokes Raman scattering (CARS), two-photon excited fluorescence (TPEF), and second-harmonic generation were acquired on cryosections of brain tumors of 382 patients and 28 human nontumor brain samples. Texture parameters of those images were calculated and used as input for linear discriminant analysis.

Results

The combined analysis of texture parameters of the CARS and TPEF signal proved to be most suited for the discrimination of nontumor brain versus brain tumors (low- and high-grade astrocytoma, oligodendroglioma, glioblastoma, recurrent glioblastoma, brain metastases of lung, colon, renal, and breast cancer and of malignant melanoma) leading to a correct rate of 96% (sensitivity: 96%, specificity: 100%). To approximate the clinical setting, the results were validated on 42 fresh, unfixed tumor biopsies. 82% of the tumors and, most important, all of the nontumor samples were correctly recognized. An image resolution of 1 µm was sufficient to distinguish brain tumors and nontumor brain. Moreover, the vast majority of single fields of view of each patient’s sample were correctly classified with high probabilities, which is important for clinical translation.

Conclusion

Label-free multiphoton imaging might allow fast and accurate intraoperative delineation of primary and secondary brain tumors in combination with endoscopic systems.

Fast and sensitive delineation of brain tumor with clinically compatible moxifloxacin labeling and confocal microscopy

Delineation of brain tumor margins during surgery is critical to maximize tumor removal while preserving normal brain tissue to obtain optimal clinical outcomes. Although various imaging methods have been developed, they have limitations to be used in clinical practice. We developed a high-speed cellular imaging method by using clinically compatible moxifloxacin and confocal microscopy for sensitive brain tumor detection and delineation. Moxifloxacin is a Food and Drug Administration (FDA) approved antibiotic and was used as a cell labeling agent through topical administration. Its strong fluorescence at short visible excitation wavelengths allowed video-rate cellular imaging. Moxifloxacin-based confocal microscopy (MBCM) was characterized in normal mouse brain specimens and visualized their cytoarchitecture clearly. Then, MBCM was applied to both brain tumor murine models and two malignant human brain tumors of glioblastoma and metastatic cancer. MBCM detected tumors in all the specimens by visualizing dense and irregular cell distributions, and tumor margins were easily delineated based on the cytoarchitecture. An image analysis method was developed for automated detection and delineation. MBCM demonstrated sensitive delineation of brain tumors through cytoarchitecture visualization and would have potentials for human applications, such as a surgery-guiding method for tumor removal.

Rapid Label-Free Analysis of Brain Tumor Biopsies by Near Infrared Raman and Fluorescence Spectroscopy-A Study of 209 Patients

In brain surgery, novel technologies are continuously developed to achieve better tumor delineation and maximize the extent of resection. Raman spectroscopy is an optical method that enables to retrieve a molecular signature of tissue biochemical composition in order to identify tumor and normal tissue. Here, the translation of Raman spectroscopy to the surgical practice for discerning a variety of different tumor entities from non-neoplastic brain parenchyma was investigated. Fresh unprocessed biopsies obtained from brain tumor surgery were analyzed over 1.5 years including all patients that gave consent. Measurements were performed with a Raman microscope by medical personnel as routine activity. The Raman and fluorescence signals of the acquired spectra were analyzed by principal component analysis, followed by supervised classification to discriminate non-tumor tissue vs. tumor and distinguish tumor entities. Histopathology of the measured biopsies was performed as reference. Classification led to the correct recognition of all non-neoplastic biopsies (7/7) and of 97% of the investigated tumor biopsies (195/202). For instance, GBM was recognized as tumor with a correct rate of 94% if primary, and of 100% if recurrent. Astrocytoma and oligodendroglioma were recognized as tumor with correct rates of 86 and 90%, respectively. All brain metastases, meningioma and schwannoma were correctly recognized as tumor and distinguished from non-neoplastic brain tissue. Furthermore, metastases were discerned from glioma with correct rate of 90%. Oligodendroglioma and astrocytoma IDH1-mutant, which differ in the presence of 1p/19q codeletion, were discerned with a correct rate of 81%. These results demonstrate the feasibility of rapid brain tumors recognition and extraction of diagnostic information by Raman spectroscopy, using a protocol that can be easily included in the routine surgical workflow.

Identification of distinctive features in human intracranial tumors by label-free nonlinear multimodal microscopy

Nonlinear multimodal microscopy offers a series of label-free techniques with potential for intraoperative identification of tumor borders in situ using novel endoscopic devices. Here, we combined coherent anti-Stokes Raman scattering, two-photon excited fluorescence (TPEF) and second harmonic generation imaging to analyze biopsies of different human brain tumors, with the aim to understand whether the morphological information carried by single field of view images, similar to what delivered by present endoscopic systems, is sufficient for tumor recognition. We imaged 40 human biopsies of high and low grade glioma, meningioma, as well as brain metastases of melanoma, breast, lung and renal carcinoma, in comparison with normal brain parenchyma. Furthermore, five biopsies of schwannoma were analyzed and compared with nonpathological nerve tissue. Besides the high cellularity, the typical features of tumor, which were identified and quantified, are intracellular and extracellular lipid droplets, aberrant vessels, extracellular matrix collagen and diffuse TPEF. Each tumor type displayed a particular morphochemistry characterized by specific patterns of the above-mentioned features. Nonlinear multimodal microscopy performed on fresh unprocessed biopsies confirmed that the technique has the ability to visualize tumor structures and discern normal from neoplastic tissue likewise in conditions close to in situ.

Ultraviolet photoacoustic remote sensing microscopy

Traditional histopathology involves fixing, sectioning, and staining protocols that are time consuming and subject to staining variability. In this Letter, we present ultraviolet photoacoustic remote sensing microscopy, capable of imaging cell nuclei without the need for exogenous stains or labelling. Our reflection mode approach is non-contact and has the potential to provide useful histological information without laborious sample preparation steps. Tumor cell cultures and excised tissue samples were imaged with the 0.7 μm resolution and signal-to-noise ratios as high as 53 dB, with close agreement to traditional hematoxylin and eosin staining.

Quantitative Third Harmonic Generation Microscopy for Assessment of Glioma in Human Brain Tissue

Distinguishing tumors from normal brain cells is important but challenging in glioma surgery due to the lack of clear interfaces between the two. The ability of label-free third harmonic generation (THG) microscopy in combination with automated image analysis to quantitatively detect glioma infiltration in fresh, unprocessed tissue in real time is assessed. The THG images reveal increased cellularity in grades II-IV glioma samples from 23 patients, as confirmed by subsequent hematoxylin and eosin histology. An automated image quantification workflow is presented for quantitative assessment of the imaged cellularity as a reflection of the degree of glioma invasion. The cellularity is validated in three ways: 1) Quantitative comparison of THG imaging with fluorescence microscopy of nucleus-stained samples demonstrates that THG reflects the true tissue cellularity. 2) Thresholding of THG cellularity differentiates normal brain from glioma infiltration, with 96.6% sensitivity and 95.5% specificity, in nearly perfect (93%) agreement with pathologists. 3) In one patient, a good correlation between THG cellularity and preoperative magnetic resonance and positron emission tomography imaging is demonstrated. In conclusion, quantitative real-time THG microscopy accurately assesses glioma infiltration in ex vivo human brain samples, and therefore holds strong potential for improving the accuracy of surgical resection.

Optical molecular imaging of corpora amylacea in human brain tissue

Label-free multiphoton imaging constitutes a promising technique for clinical diagnosis and therapeutic monitoring. Corpora amylacea (CoA) are starch-like structures often found in the diseased brain, whose origin and role in nervous pathologies are still a matter of debate. Recently, CoA in the diseased human hippocampus were found to be second harmonic generation (SHG) active. Here, we show that CoA formed in other parts of the diseased brain and in brain neoplasms display a similar SHG activity. The SHG pattern of CoA depended on laser polarization, indicating that a radial structure is responsible for their nonlinear activity. Vibrational spectroscopy was used to study the biochemistry underlying the SHG activity. Infrared (IR) and Raman spectroscopy showed that CoA contain polyglucosans that are biochemically similar to glycogen, but with an unusual structure that is similar to amylopectin, which justifies the nonlinear activity of CoA. Our findings explain the SHG activity of CoA and demonstrate that CoA in the pathological brain are amenable to label-free multiphoton imaging. Further research will clarify whether intraoperative assessment of CoA can be diagnostically exploited.

Rapid intraoperative molecular genetic classification of gliomas using Raman spectroscopy

BACKGROUND

The molecular genetic classification of gliomas, particularly the identification of isocitrate dehydrogenase (IDH) mutations, is critical for clinical and surgical decision-making. Raman spectroscopy probes the unique molecular vibrations of a sample to accurately characterize its molecular composition. No sample processing is required allowing for rapid analysis of tissue. The aim of this study was to evaluate the ability of Raman spectroscopy to rapidly identify the common molecular genetic subtypes of diffuse glioma in the neurosurgical setting using fresh biopsy tissue. In addition, classification models were built using cryosections, formalin-fixed paraffin-embedded (FFPE) sections and LN-18 (IDH-mutated and wild-type parental cell) glioma cell lines.

METHODS

Fresh tissue, straight from neurosurgical theatres, underwent Raman analysis and classification into astrocytoma, IDH-wild-type; astrocytoma, IDH-mutant; or oligodendroglioma. The genetic subtype was confirmed on a parallel section using immunohistochemistry and targeted genetic sequencing.

RESULTS

Fresh tissue samples from 62 patients were collected (36 astrocytoma, IDH-wild-type; 21 astrocytoma, IDH-mutated; 5 oligodendroglioma). A principal component analysis fed linear discriminant analysis classification model demonstrated 79%-94% sensitivity and 90%-100% specificity for predicting the 3 glioma genetic subtypes. For the prediction of IDH mutation alone, the model gave 91% sensitivity and 95% specificity. Seventy-nine cryosections, 120 FFPE samples, and LN18 cells were also successfully classified. Meantime for Raman data collection was 9.5 min in the fresh tissue samples, with the process from intraoperative biopsy to genetic classification taking under 15 min.

CONCLUSION

These data demonstrate that Raman spectroscopy can be used for the rapid, intraoperative, classification of gliomas into common genetic subtypes.

Microscopy and Cell Biology: New Methods and New Questions

Understanding the cellular basis of human health and disease requires the spatial resolution of microscopy and the molecular-level details provided by spectroscopy. This review highlights imaging methods at the intersection of microscopy and spectroscopy with applications in cell biology. Imaging methods are divided into three broad categories: fluorescence microscopy, label-free approaches, and imaging tools that can be applied to multiple imaging modalities. Just as these imaging methods allow researchers to address new biological questions, progress in biological sciences will drive the development of new imaging methods. We highlight four topics in cell biology that illustrate the need for new imaging tools: nanoparticle-cell interactions, intracellular redox chemistry, neuroscience, and the increasing use of spheroids and organoids. Overall, our goal is to provide a brief overview of individual imaging methods and highlight recent advances in the use of microscopy for cell biology.

Surgical Adjuncts to Increase the Extent of Resection: Intraoperative MRI, Fluorescence, and Raman Histology

In low-grade glioma surgery, depicting tumor margins is challenging. 7 - Bowden 2018 - Sodium Fluorescein Facilitates Guided Sampling of Diagnostic Tumor Tissue.pdf Several tools have emerged to assist surgical decision-making. Intraoperative MRI, albeit expensive and time-consuming, can provide useful information during surgery. Fluorescence-guidance with 5-aminolevulinic acid (5-ALA) helps provide real-time information during surgery regardless of brain-shift, assists in finding anaplastic foci in low-grade tumors, and enables diagnosis of malignant tissue. Raman histology has potential for detecting viable tumor in biopsied tissue and for identifying tumor infiltration in vivo. This article analyzes and discusses these surgical adjuncts.

Applications of Raman spectroscopy in cancer diagnosis

Novel approaches toward understanding the evolution of disease can lead to the discovery of biomarkers that will enable better management of disease progression and improve prognostic evaluation. Raman spectroscopy is a promising investigative and diagnostic tool that can assist in uncovering the molecular basis of disease and provide objective, quantifiable molecular information for diagnosis and treatment evaluation. This technique probes molecular vibrations/rotations associated with chemical bonds in a sample to obtain information on molecular structure, composition, and intermolecular interactions. Raman scattering occurs when light interacts with a molecular vibration/rotation and a change in polarizability takes place during molecular motion. This results in light being scattered at an optical frequency shifted (up or down) from the incident light. By monitoring the intensity profile of the inelastically scattered light as a function of frequency, the unique spectroscopic fingerprint of a tissue sample is obtained. Since each sample has a unique composition, the spectroscopic profile arising from Raman-active functional groups of nucleic acids, proteins, lipids, and carbohydrates allows for the evaluation, characterization, and discrimination of tissue type. This review provides an overview of the theory of Raman spectroscopy, instrumentation used for measurement, and variation of Raman spectroscopic techniques for clinical applications in cancer, including detection of brain, ovarian, breast, prostate, and pancreatic cancers and circulating tumor cells.

Histological coherent Raman imaging: a prognostic review

Histopathology plays a central role in diagnosis of many diseases including solid cancers. Efforts are underway to transform this subjective art to an objective and quantitative science. Coherent Raman imaging (CRI), a label-free imaging modality with sub-cellular spatial resolution and molecule-specific contrast possesses characteristics which could support the qualitative-to-quantitative transition of histopathology. In this work we briefly survey major themes related to modernization of histopathology, review applications of CRI to histopathology and, finally, discuss potential roles for CRI in the transformation of histopathology that is already underway.

Raman Spectroscopy and Imaging for Cancer Diagnosis

Raman scattering has long been used to analyze chemical compositions in biological systems. Owing to its high chemical specificity and noninvasive detection capability, Raman scattering has been widely employed in cancer screening, diagnosis, and intraoperative surgical guidance in the past ten years. In order to overcome the weak signal of spontaneous Raman scattering, coherent Raman scattering and surface-enhanced Raman scattering have been developed and recently applied in the field of cancer research. This review focuses on innovative studies of the use of Raman scattering in cancer diagnosis and their potential to transition from bench to bedside.

IDH1 mutation in human glioma induces chemical alterations that are amenable to optical Raman spectroscopy

INTRODUCTION

Mutations in the isocytrate dehydrogenase 1 (IDH1) gene are early genetic events in glioma pathogenesis and cause profound metabolic changes. Because this genotype is found in virtually every tumor cell, therapies targeting mutant IDH1 protein are being developed. The intraoperative administration of those therapies would require fast technologies for the determination of IDH1 genotype. As of today, there is no such diagnostic test available. Recently, infrared spectroscopy was shown to bridge this gap. Here, we tested Raman spectroscopy for analysis of IDH1 genotype in glioma, which constitutes an alternative contact-free technique with the potential of being applicable in situ.

METHODS

Human glioma samples (n = 36) were obtained during surgery and cryosections were prepared. IDH1 mutations were assessed using DNA sequencing and 100 Raman spectra were obtained for each sample.

RESULTS

Analysis of Raman spectra revealed increased intensities in spectral bands related to DNA in IDH1 mutant glioma while bands assigned to molecular vibrations of lipids were significantly decreased. Moreover, intensities of Raman bands assigned to proteins differed in IDH1 mutant and IDH1 wild-type glioma, suggesting alterations in the protein profile. The selection of five bands (498, 826, 1003, 1174 and 1337 cm^-1) allowed the classification of Raman spectra according to IDH1 genotype with a correct rate of 89%.

CONCLUSION

Raman spectroscopy constitutes a simple, rapid and safe procedure for determination of the IDH1 mutation that shows great promise for clinically relevant in situ diagnostics.

Glioblastoma cells labeled by robust Raman tags for enhancing imaging contrast

Complete removal of a glioblastoma multiforme (GBM), a highly malignant brain tumor, is challenging due to its infiltrative characteristics. Therefore, utilizing imaging agents such as fluorophores to increase the contrast between GBM and normal cells can help neurosurgeons to locate residual cancer cells during image guided surgery. In this work, Raman tag based labeling and imaging for GBM cells in vitro is described and evaluated. The cell membrane of a GBM adsorbs a substantial amount of functionalized Raman tags through overexpression of the epidermal growth factor receptor (EGFR) and "broadcasts" stronger pre-defined Raman signals than normal cells. The average ratio between Raman signals from a GBM cell and autofluorescence from a normal cell can be up to 15. In addition, the intensity of these images is stable under laser illuminations without suffering from the severe photo-bleaching that usually occurs in fluorescent imaging. Our results show that labeling and imaging GBM cells via robust Raman tags is a viable alternative method to distinguish them from normal cells. This Raman tag based method can be used solely or integrated into an existing fluorescence system to improve the identification of infiltrative glial tumor cells around the boundary, which will further reduce GBM recurrence. In addition, it can also be applied/extended to other types of cancer to improve the effectiveness of image guided surgery.

Near-resonance enhanced label-free stimulated Raman scattering microscopy with spatial resolution near 130 nm

High-resolution optical microscopes that can break 180 nm in spatial resolution set to conventional microscopies are much-needed tools. However, current optical microscopes have to rely on exogenous fluorescent labels to achieve high resolution in biological imaging. Herein, we report near-resonance enhanced label-free stimulated Raman scattering (SRS) microscopy with a lateral resolution near 130 nm, in which the high-resolution image contrast originates directly from a low concentration of endogenous biomolecules, with sensitivity gains of approximately 23 times. Moreover, by using a 0.3-m-long optical fiber, we developed hyperspectral SRS microscopy based on spectral focusing technology. Attributed to enhancements in spatial resolution and sensitivity, we demonstrated high-resolution imaging of three-dimensional structures in single cells and high-resolution mapping of large-scale intact mouse brain tissues in situ. By using enhanced high-resolution hyperspectral SRS, we chemically observed sphingomyelin distributed in the myelin sheath that insulates single axons. Our concept opens the door to biomedical imaging with ~130 nm resolution.

Optical molecular imaging for tumor detection and image-guided surgery

We have witnessed rapid development of fluorescence molecular imaging of solid tumors for cancer diagnosis and image-guided surgery in the past decade. Many biomarkers unique to cancer cells or tumor microenvironment, such as cell surface receptors, hypoxia, secreted proteases and extracellular acidosis have been characterized, and can be used to distinguish cancer from normal tissue. A variety of optical imaging probes have been developed to target these biomarkers to improve tumor contrast over the background tissue. Unlike conventional anatomical and molecular imaging technologies, fluorescent imaging method benefits from its safety, high-spatial resolution and real-time capability, and therefore, has become a highly adoptable imaging method for tumor detection and image-guided surgery in clinics. In this review, we summarize recent progress in 'always-ON' and stimuli-activatable fluorescent imaging probes, and discuss their potentials in tumor detection and image-guided surgery.

Chemical Analysis of Morphological Changes in Lysophosphatidic Acid-Treated Ovarian Cancer Cells

Ovarian cancer (OvCa) cells are reported to undergo biochemical changes at the cell surface in response to treatment with lysophosphatidic acid (LPA). Here we use scanning electron microscopy (SEM) and multiplex coherent anti-Stokes Raman scattering (CARS) imaging via supercontinuum excitation to probe morphological changes that result from LPA treatment. SEM images show distinct shedding of microvilli-like features upon treatment with LPA. Analysis of multiplex CARS images can distinguish between molecular components, such as lipids and proteins. Our results indicate that OvCa429 and SKOV3ip epithelial ovarian cancer cells undergo similar morphological and chemical responses to treatment with LPA. The microvilli-like structures on the surface of multicellular aggregates (MCAs) are removed by treatment with LPA. The CARS analysis shows a distinct decrease in protein and increase in lipid composition on the surface of LPA-treated cells. Importantly, the CARS signals from cellular sheddings from MCAs with LPA treatment are consistent with cleavage of proteins originally present. Mass spectrometry on the cellular sheddings show that a large number of proteins, both membrane and intracellular, are present. An increased number of peptides are detected for the mesenchymal cell line relative to the epithelial cell indicating a differential response to LPA treatment with cancer progression.

Cancer Immunotherapy Getting Brainy: Visualizing the Distinctive CNS Metastatic Niche to Illuminate Therapeutic Resistance

The advent of cancer immunotherapy (CIT) and its success in treating primary and metastatic cancer may offer substantially improved outcomes for patients. Despite recent advancements, many malignancies remain resistant to CIT, among which are brain metastases, a particularly virulent disease with no apparent cure. The immunologically unique niche of the brain has prompted compelling new questions in immuno-oncology such as the effects of tissue-specific differences in immune response, heterogeneity between primary tumors and distant metastases, and the role of spatiotemporal dynamics in shaping an effective anti-tumor immune response. Current methods to examine the immunobiology of metastases in the brain are constrained by tissue processing methods that limit spatial data collection, omit dynamic information, and cannot recapitulate the heterogeneity of the tumor microenvironment. In the current review, we describe how high-resolution, live imaging tools, particularly intravital microscopy (IVM), are instrumental in answering these questions. IVM of pre-clinical cancer models enables short- and long-term observations of critical immunobiology and metastatic growth phenomena to potentially generate revolutionary insights into the spatiotemporal dynamics of brain metastasis, interactions of CIT with immune elements therein, and influence of chemo- and radiotherapy. We describe the utility of IVM to study brain metastasis in mice by tracking the migration and growth of fluorescently-labeled cells, including cancer cells and immune subsets, while monitoring the physical environment within optical windows using imaging dyes and other signal generation mechanisms to illuminate angiogenesis, hypoxia, and/or CIT drug expression within the metastatic niche. Our review summarizes the current knowledge regarding brain metastases and the immune milieu, presents the current status of CIT and its prospects in targeting brain metastases to circumvent therapeutic resistance, and proposes avenues to utilize IVM to study CIT drug delivery and therapeutic efficacy in preclinical models that will ultimately facilitate novel drug discovery and innovative combination therapies.

Label-Free Molecular Imaging of Biological Cells and Tissues by Linear and Nonlinear Raman Spectroscopic Approaches

Raman spectroscopy is an emerging technique in bioanalysis and imaging of biomaterials owing to its unique capability of generating spectroscopic fingerprints. Imaging cells and tissues by Raman microspectroscopy represents a nondestructive and label-free approach. All components of cells or tissues contribute to the Raman signals, giving rise to complex spectral signatures. Resonance Raman scattering and surface-enhanced Raman scattering can be used to enhance the signals and reduce the spectral complexity. Raman-active labels can be introduced to increase specificity and multimodality. In addition, nonlinear coherent Raman scattering methods offer higher sensitivities, which enable the rapid imaging of larger sampling areas. Finally, fiber-based imaging techniques pave the way towards in vivo applications of Raman spectroscopy. This Review summarizes the basic principles behind medical Raman imaging and its progress since 2012.

Assessing the efficacy of coherent anti-Stokes Raman scattering microscopy for the detection of infiltrating glioblastoma in fresh brain samples

Coherent anti-Stokes Raman scattering (CARS) microscopy is an emerging technique for identification of brain tumors. However, tumor identification by CARS microscopy on bulk samples and in vivo has been so far verified retrospectively on histological sections, which only provide a gross reference for the interpretation of CARS images without matching at cellular level. Therefore, fluorescent labels were exploited for direct assessment of the interpretation of CARS images of solid and infiltrative tumors. Glioblastoma cells expressing green fluorescent protein (GFP) were used for induction of tumors in mice (n = 7). The neoplastic nature of cells imaged by CARS microscopy was unequivocally verified by addressing two-photon fluorescence of GFP on fresh brain slices and in vivo. In fresh unfixed biopsies of human glioblastoma (n = 10), the fluorescence of 5-aminolevulinic acid-induced protoporphyrin IX was used for identification of tumorous tissue. Distinctive morphological features of glioblastoma cells, i.e. larger nuclei, evident nuclear membrane and nucleolus, were identified in the CARS images of both mouse and human brain tumors. This approach demonstrates that the chemical contrast provided by CARS allows the localization of infiltrating tumor cells in fresh tissue and that the cell morphology in CARS images is useful for tumor recognition. Experimental glioblastoma expressing green fluorescent protein.

Raman technologies in cancer diagnostics

Despite significant effort, cancer still remains a leading cause of death worldwide. In order to reduce its burden, the development and improvement of noninvasive strategies for early detection and diagnosis of cancer are urgently needed. Raman spectroscopy, an optical technique that relies on inelastic light scattering arising from molecular vibrations, is one such strategy, as it can noninvasively probe cancerous markers using only endogenous contrast. In this review, spontaneous, coherent and surface enhanced Raman spectroscopies and imaging, as well as the fundamental principles governing the successful use of these techniques, are discussed. Methods for spectral data analysis are also highlighted. Utilization of the discussed Raman techniques for the detection and diagnosis of cancer in vitro, ex vivo and in vivo is described. The review concludes with a discussion of the future directions of Raman technologies, with particular emphasis on their clinical translation.

Raman spectroscopy and regenerative medicine: a review

The field of regenerative medicine spans a wide area of the biomedical landscape-from single cell culture in laboratories to human whole-organ transplantation. To ensure that research is transferrable from bench to bedside, it is critical that we are able to assess regenerative processes in cells, tissues, organs and patients at a biochemical level. Regeneration relies on a large number of biological factors, which can be perturbed using conventional bioanalytical techniques. A versatile, non-invasive, non-destructive technique for biochemical analysis would be invaluable for the study of regeneration; and Raman spectroscopy is a potential solution. Raman spectroscopy is an analytical method by which chemical data are obtained through the inelastic scattering of light. Since its discovery in the 1920s, physicists and chemists have used Raman scattering to investigate the chemical composition of a vast range of both liquid and solid materials. However, only in the last two decades has this form of spectroscopy been employed in biomedical research. Particularly relevant to regenerative medicine are recent studies illustrating its ability to characterise and discriminate between healthy and disease states in cells, tissue biopsies and in patients. This review will briefly outline the principles behind Raman spectroscopy and its variants, describe key examples of its applications to biomedicine, and consider areas of regenerative medicine that would benefit from this non-invasive bioanalytical tool.

Optical technologies for intraoperative neurosurgical guidance

Biomedical optics is a broadly interdisciplinary field at the interface of optical engineering, biophysics, computer science, medicine, biology, and chemistry, helping us understand light-tissue interactions to create applications with diagnostic and therapeutic value in medicine. Implementation of biomedical optics tools and principles has had a notable scientific and clinical resurgence in recent years in the neurosurgical community. This is in great part due to work in fluorescence-guided surgery of brain tumors leading to reports of significant improvement in maximizing the rates of gross-total resection. Multiple additional optical technologies have been implemented clinically, including diffuse reflectance spectroscopy and imaging, optical coherence tomography, Raman spectroscopy and imaging, and advanced quantitative methods, including quantitative fluorescence and lifetime imaging. Here we present a clinically relevant and technologically informed overview and discussion of some of the major clinical implementations of optical technologies as intraoperative guidance tools in neurosurgery.

Improving the accuracy of brain tumor surgery via Raman-based technology

Despite advances in the surgical management of brain tumors, achieving optimal surgical results and identification of tumor remains a challenge. Raman spectroscopy, a laser-based technique that can be used to nondestructively differentiate molecules based on the inelastic scattering of light, is being applied toward improving the accuracy of brain tumor surgery. Here, the authors systematically review the application of Raman spectroscopy for guidance during brain tumor surgery. Raman spectroscopy can differentiate normal brain from necrotic and vital glioma tissue in human specimens based on chemical differences, and has recently been shown to differentiate tumor-infiltrated tissues from noninfiltrated tissues during surgery. Raman spectroscopy also forms the basis for coherent Raman scattering (CRS) microscopy, a technique that amplifies spontaneous Raman signals by 10,000-fold, enabling real-time histological imaging without the need for tissue processing, sectioning, or staining. The authors review the relevant basic and translational studies on CRS microscopy as a means of providing real-time intraoperative guidance. Recent studies have demonstrated how CRS can be used to differentiate tumor-infiltrated tissues from noninfiltrated tissues and that it has excellent agreement with traditional histology. Under simulated operative conditions, CRS has been shown to identify tumor margins that would be undetectable using standard bright-field microscopy. In addition, CRS microscopy has been shown to detect tumor in human surgical specimens with near-perfect agreement to standard H & E microscopy. The authors suggest that as the intraoperative application and instrumentation for Raman spectroscopy and imaging matures, it will become an essential component in the neurosurgical armamentarium for identifying residual tumor and improving the surgical management of brain tumors.