Development of stereotactic mass spectrometry for brain tumor surgery

Advancing rare cancer research by MALDI mass spectrometry imaging: Applications, challenges, and future perspectives in sarcoma

MALDI mass spectrometry imaging (MALDI imaging) uniquely advances cancer research, by measuring spatial distribution of endogenous and exogenous molecules directly from tissue sections. These molecular maps provide valuable insights into basic and translational cancer research, including tumor biology, tumor microenvironment, biomarker identification, drug treatment, and patient stratification. Despite its advantages, MALDI imaging is underutilized in studying rare cancers. Sarcomas, a group of malignant mesenchymal tumors, pose unique challenges in medical research due to their complex heterogeneity and low incidence, resulting in understudied subtypes with suboptimal management and outcomes. In this review, we explore the applicability of MALDI imaging in sarcoma research, showcasing its value in understanding this highly heterogeneous and challenging rare cancer. We summarize all MALDI imaging studies in sarcoma to date, highlight their impact on key research fields, including molecular signatures, cancer heterogeneity, and drug studies. We address specific challenges encountered when employing MALDI imaging for sarcomas, and propose solutions, such as using formalin-fixed paraffin-embedded tissues, and multiplexed experiments, and considerations for multi-site studies and digital data sharing practices. Through this review, we aim to spark collaboration between MALDI imaging researchers and clinical colleagues, to deploy the unique capabilities of MALDI imaging in the context of sarcoma.

Real-time glioblastoma tumor microenvironment assessment by SpiderMass for improved patient management

Glioblastoma is a highly heterogeneous and infiltrative form of brain cancer associated with a poor outcome and limited therapeutic effectiveness. The extent of the surgery is related to survival. Reaching an accurate diagnosis and prognosis assessment by the time of the initial surgery is therefore paramount in the management of glioblastoma. To this end, we are studying the performance of SpiderMass, an ambient ionization mass spectrometry technology that can be used in vivo without invasiveness, coupled to our recently established artificial intelligence pipeline. We demonstrate that we can both stratify isocitrate dehydrogenase (IDH)-wild-type glioblastoma patients into molecular sub-groups and achieve an accurate diagnosis with over 90% accuracy after cross-validation. Interestingly, the developed method offers the same accuracy for prognosis. In addition, we are testing the potential of an immunoscoring strategy based on SpiderMass fingerprints, showing the association between prognosis and immune cell infiltration, to predict patient outcome.

Saturated Fatty Acid Emulsions Open the Blood-Brain Barrier and Promote Drug Delivery in Rat Brains

We performed this study to evaluate whether saturated fatty acid (SFA) emulsions affect the BBB and determine the duration of BBB opening, thereby promoting drug delivery to the brain. Butyric, valeric, caproic, enanthic, and caprylic acid emulsions were infused into the carotid artery of the rat model. We evaluated the BBB opening and drug delivery over time. The trypan blue and doxorubicin delivery studies were repeated from 30 min to 6 h. In the 1 h rats in each group, transmission electron microscopy (TEM) was performed to morphologically evaluate tight junctions, and the delivery of temozolomide was assessed by desorption electrospray ionization mass spectrometry. The ipsilateral hemisphere was positive for trypan blue staining in all the five SFA emulsion groups. In the valeric, enanthic, and caprylic acid emulsion groups, RGB ratios were significantly higher at 30 min and decreased thereafter. Doxorubicin delivery increased in all emulsion groups at all time points. Tight junctions were observed to be open in all groups. TMZ delivery was significantly higher in the ipsilateral hemisphere. In conclusion, intra-arterially infused SFA emulsions opened the BBB and promoted drug delivery within 30 min, which decreased thereafter. Therefore, SFA emulsions may aid BBB research and promote drug delivery to the brain.

Unsaturated free fatty acid emulsion infusion into carotid artery enhances drug delivery to the rat brain

AIMS

To determine whether the blood-brain barrier (BBB) opens to enhance drug delivery during the acute stage of unsaturated fat embolism.

METHODS

We infused oleic, linoleic, and linolenic acid emulsions through the right common carotid artery of rats, followed by trypan blue for gross and lanthanum for electron microscopic (EM) examination. Doxorubicin and temozolomide were also administered, and then the rats were euthanized at 30 min, 1 h, and 2 h. Trypan blue hue was analyzed to semiquantitatively measure BBB opening. Desorption electrospray ionization-mass spectrometry (DESI-MS) imaging was used to evaluate drug delivery.

RESULTS

Trypan blue staining observed in each group 30 min after emulsion infusion increased at 1 h and decreased after 2 h in the oleic acid group. The linoleic and linolenic acid groups showed weak staining over time. The hue and trypan blue analysis results were corroborative. EM showed tight junction opening, whereas DESI-MS imaging showed increased doxorubicin and temozolomide signal intensities in ipsilateral hemispheres of all three groups.

CONCLUSION

We demonstrated that oleic, linoleic, and linolenic acid emulsions opened the BBB, promoting drug delivery to the brain. Hue analysis and DESI-MS imaging are appropriate for analysis of doxorubicin and temozolomide concentrations in brain tissue.

Surgical Treatment of Glioblastoma: State-of-the-Art and Future Trends

Glioblastoma (GBM) is a highly aggressive disease and is associated with poor prognosis despite treatment advances in recent years. Surgical resection of tumor remains the main therapeutic option when approaching these patients, especially when combined with adjuvant radiochemotherapy. In the present study, we conducted a comprehensive literature review on the state-of-the-art and future trends of the surgical treatment of GBM, emphasizing topics that have been the object of recent study.

Towards real-time intraoperative tissue interrogation for REIMS-guided glioma surgery

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REIMS can differentiate glioblastoma from normal brain with 99.2% sensitivity.

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Starting from 5% glioblastoma, REIMS showed a 100% correct classification rate.

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Low-grade gliomas can be identified with a 97.5% sensitivity.

Introduction

Objectives

Methods

Results

Conclusion

Metabolomic Phenotyping of Gliomas: What Can We Get with Simplified Protocol for Intact Tissue Analysis?

Glioblastoma multiforme is one of the most malignant neoplasms among humans in their third and fourth decades of life, which is evidenced by short patient survival times and rapid tumor-cell proliferation after radiation and chemotherapy. At present, the diagnosis of gliomas and decisions related to therapeutic strategies are based on genetic testing and histological analysis of the tumor, with molecular biomarkers still being sought to complement the diagnostic panel. This work aims to enable the metabolomic characterization of cancer tissue and the discovery of potential biomarkers via high-resolution mass spectrometry coupled to liquid chromatography and a solvent-free sampling protocol that uses a microprobe to extract metabolites directly from intact tumors. The metabolomic analyses were performed independently from genetic and histological testing and at a later time. Despite the small cohort analyzed in this study, the results indicated that the proposed method is able to identify metabolites associated with different malignancy grades of glioma, as well as IDH and 1p19q codeletion mutations. A comparison of the constellation of identified metabolites and the results of standard tests indicated the validity of using the characterization of one comprehensive tumor phenotype as a reflection of all diagnostically meaningful information. Due to its simplicity, the proposed analytical approach was verified as being compatible with a surgical environment and applicable for large-scale studies.

Triolein emulsion enhances temozolomide brain delivery: an experimental study in rats

Purpose

To evaluate the enhancement of temozolomide (TMZ) delivery in the rat brain using a triolein emulsion.

Materials and Methods

Rats were divided into the five groups as following: group 1 (negative control), group 2 (treated with triolein emulsion and TMZ 20 mg/kg), and group 3 (TMZ 20 mg/kg treatment without triolein), group 4 (treated with triolein emulsion and TMZ 10 mg/kg), and group 5 (TMZ 10 mg/kg treatment without triolein). Triolein emulsion was infused into the right common carotid artery. One hour later, the TMZ concentration was evaluated quantitatively and qualitatively using high-performance liquid chromatography (HPLC-MS) and desorption electrospray ionization mass spectrometry (DESI-MS) imaging, respectively. The concentration ratios of the ipsilateral to contralateral hemisphere in each group were determined and the statistical analysis was conducted using an unpaired t-test.

Results

Quantitatively, the TMZ concentration ratio of the ipsilateral to the control hemisphere was 2.41 and 1.13 in groups 2 and 3, and were 2.49 and 1.14 in groups 4 and 5, respectively. Thus, the TMZ signal intensities of TMZ in group 2 and 4 were statistically high in the ipsilateral hemispheres. Qualitatively, the signal intensity of TMZ was remarkably high in the ipsilateral hemisphere in group 2 and 4.

Conclusions

The triolein emulsion efficiently opened the blood-brain barrier and could provide a potential new strategy to enhance the therapeutic effect of TMZ. HPLC-MS and DESI-MS imaging were shown to be suitable for analyses of enhancement of brain TMZ concentrations.

Lipid Profiling in Cancer Diagnosis with Hand-Held Ambient Mass Spectrometry Probes: Addressing the Late-Stage Performance Concerns

Untargeted lipid fingerprinting with hand-held ambient mass spectrometry (MS) probes without chromatographic separation has shown promise in the rapid characterization of cancers. As human cancers present significant molecular heterogeneities, careful molecular modeling and data validation strategies are required to minimize late-stage performance variations of these models across a large population. This review utilizes parallels from the pitfalls of conventional protein biomarkers in reaching bedside utility and provides recommendations for robust modeling as well as validation strategies that could enable the next logical steps in large scale assessment of the utility of ambient MS profiling for cancer diagnosis. Six recommendations are provided that range from careful initial determination of clinical added value to moving beyond just statistical associations to validate lipid involvements in disease processes mechanistically. Further guidelines for careful selection of suitable samples to capture expected and unexpected intragroup variance are provided and discussed in the context of demographic heterogeneities in the lipidome, further influenced by lifestyle factors, diet, and potential intersect with cancer lipid pathways probed in ambient mass spectrometry profiling studies.

Bringing Matrix-Assisted Laser Desorption/Ionization Mass Spectrometry Imaging to the Clinics

Matrix-assisted laser desorption/ionization (MALDI) mass spectrometry imaging (MSI) is an emerging analytical technique that promises to change tissue-based diagnostics. This article provides a brief introduction to MALDI MSI as well as clinical diagnostic workflows and opportunities to apply this powerful approach. It describes various MALDI MSI applications, from more clinically mature applications such as cancer to emerging applications such as infectious diseases and drug distribution. In addition, it discusses the analytical considerations that need to be considered when bringing these approaches to different diagnostic problems and settings.

Cancer Surgery 2.0: Guidance by Real-Time Molecular Technologies

In vivo cancer margin delineation during surgery remains a major challenge. Despite the availability of several image guidance techniques and intraoperative assessment, clear surgical margins and debulking efficiency remain scarce. For this reason, there is particular interest in developing rapid intraoperative tools with high sensitivity and specificity to help guide cancer surgery in vivo. Recently, several emerging technologies including intraoperative mass spectrometry have paved the way for molecular guidance in a clinical setting. We evaluate these techniques and assess their relevance for intraoperative surgical guidance and how they can transform the future of molecular cancer surgery, diagnostics, patient management and care.

Comparison of Dimensionality Reduction Methods in Mass Spectra of Astrocytoma and Glioblastoma Tissues

Recently developed methods of ambient ionization allow the collection of mass spectrometric datasets for biological and medical applications at an unprecedented pace. One of the areas that could employ such analysis is neurosurgery. The fast in situ identification of dissected tissues could assist the neurosurgery procedure. In this paper tumor tissues of astrocytoma and glioblastoma are compared. The vast majority of the data representation methods are hard to use, as the number of features is high and the amount of samples is limited. Furthermore, the ratio of features and samples number restricts the use of many machine learning methods. The number of features could be reduced through feature selection algorithms or dimensionality reduction methods. Different algorithms of dimensionality reduction are considered along with the traditional noise thresholding for the mass spectra. From our analysis, the Isomap algorithm appears to be the most effective dimensionality reduction algorithm for negative mode, whereas the positive mode could be processed with a simple noise reduction by a threshold. Also, negative and positive mode correspond to different sample properties: negative mode is responsible for the inner variability and the details of the sample, whereas positive mode describes measurement in general.

Application of Matrix-Assisted Laser Desorption/Ionization Mass Spectrometry Imaging for Food Analysis

Food contains various compounds, and there are many methods available to analyze each of these components. However, the large amounts of low-molecular-weight metabolites in food, such as amino acids, organic acids, vitamins, lipids, and toxins, make it difficult to analyze the spatial distribution of these molecules. Matrix-assisted laser desorption/ionization mass spectrometry (MALDI-MS) imaging is a two-dimensional ionization technology that allows the detection of small metabolites in tissue sections without requiring purification, extraction, separation, or labeling. The application of MALDI-MS imaging in food analysis improves the visualization of these compounds to identify not only the nutritional content but also the geographical origin of the food. In this review, we provide an overview of some recent applications of MALDI-MS imaging, demonstrating the advantages and prospects of this technology compared to conventional approaches. Further development and enhancement of MALDI-MS imaging is expected to offer great benefits to consumers, researchers, and food producers with respect to breeding improvement, traceability, the development of value-added foods, and improved safety assessments.

Surface-Enhanced Raman Spectroscopy Characterization of Breast Cell Phenotypes: Effect of Nanoparticle Geometry

The use of surface-enhanced Raman spectroscopy (SERS) to delineate between the breast epithelial cell lines MCF10A, SK-BR-3, and MDA-MB-231 is explored utilizing varied morphologies of gold nanoparticles. The nanoparticles studied had spherical, star-like, and quasi-fractal (nanocaltrop) morphologies and possessed varying degrees of surface inhomogeneity and complexity. The efficacy of Raman enhancement of these nanoparticles was a function of their size, their surface morphology, and the associated density of "hot spots," as well as their cellular uptake. The spherical and star-like nanoparticles provided strong signal enhancement that allowed for the discernment among the three cell phenotypes based solely on the acquired Raman spectra. The presence of overlapping Raman band spectral regions, as well as unique spectral bands, suggests that the underlying biological differences between these cells can be accessed without the need for tagging the nanoparticles or for specific cell targeting, demonstrating the potential ubiquity of this technique in imaging any cancer. This work provides clear evidence for the potential application of SERS as a tool for mapping cancerous lesions, possibly during surgery and under histopathological analysis.

Current and Future Trends on Diagnosis and Prognosis of Glioblastoma: From Molecular Biology to Proteomics

Glioblastoma multiforme is the most aggressive malignant tumor of the central nervous system. Due to the absence of effective pharmacological and surgical treatments, the identification of early diagnostic and prognostic biomarkers is of key importance to improve the survival rate of patients and to develop new personalized treatments. On these bases, the aim of this review article is to summarize the current knowledge regarding the application of molecular biology and proteomics techniques for the identification of novel biomarkers through the analysis of different biological samples obtained from glioblastoma patients, including DNA, microRNAs, proteins, small molecules, circulating tumor cells, extracellular vesicles, etc. Both benefits and pitfalls of molecular biology and proteomics analyses are discussed, including the different mass spectrometry-based analytical techniques, highlighting how these investigation strategies are powerful tools to study the biology of glioblastoma, as well as to develop advanced methods for the management of this pathology.

Glioblastoma Treatments: An Account of Recent Industrial Developments

The different drugs and medical devices, which are commercialized or under industrial development for glioblastoma treatment, are reviewed. Their different modes of action are analyzed with a distinction being made between the effects of radiation, the targeting of specific parts of glioma cells, and immunotherapy. Most of them are still at a too early stage of development to firmly conclude about their efficacy. Optune, which triggers antitumor activity by blocking the mitosis of glioma cells under the application of an alternating electric field, seems to be the only recently developed therapy with some efficacy reported on a large number of GBM patients. The need for early GBM diagnosis is emphasized since it could enable the treatment of GBM tumors of small sizes, possibly easier to eradicate than larger tumors. Ways to improve clinical protocols by strengthening preclinical studies using of a broader range of different animal and tumor models are also underlined. Issues related with efficient drug delivery and crossing of blood brain barrier are discussed. Finally societal and economic aspects are described with a presentation of the orphan drug status that can accelerate the development of GBM therapies, patents protecting various GBM treatments, the different actors tackling GBM disease, the cost of GBM treatments, GBM market figures, and a financial analysis of the different companies involved in the development of GBM therapies.

In Vivo Microscopy in Neurosurgical Oncology

Intraoperative neurosurgical histopathologic diagnoses rely on evaluation of rapid tissue preparations such as frozen sections and smears with conventional light microscopy. Although useful, these techniques are time consuming and therefore cannot provide real-time intraoperative feedback. In vivo molecular imaging techniques are emerging as novel methods for generating real-time diagnostic histopathologic images of tumors and their surrounding tissues. These imaging techniques rely on contrast generated by exogenous fluorescent dyes, autofluorescence of endogenous molecules, fluorescence decay of excited molecules, or light scattering. Large molecular imaging instruments are being miniaturized for clinical in vivo use. This review discusses pertinent imaging systems that have been developed for neurosurgical use and imaging techniques currently under development for neurosurgical molecular imaging.

Solvent effects on differentiation of mouse brain tissue using laser microdissection 'cut and drop' sampling with direct mass spectral analysis

RATIONALE

Laser microdissection-liquid vortex capture/electrospray ionization mass spectrometry (LMD-LVC/ESI-MS) has potential for on-line classification of tissue but an investigation into what analytical conditions provide best spectral differentiation has not been conducted. The effects of solvent, ionization polarity, and spectral acquisition parameters on differentiation of mouse brain tissue regions are described.

METHODS

Individual 40 × 40 μm microdissections from cortex, white, grey, granular, and nucleus regions of mouse brain tissue were analyzed using different capture/ESI solvents, in positive and negative ion mode ESI, using time-of-flight (TOF)-MS and sequential window acquisitions of all theoretical spectra (SWATH)-MS (a permutation of tandem-MS), and combinations thereof. Principal component analysis-linear discriminant analysis (PCA-LDA), applied to each mass spectral dataset, was used to determine the accuracy of differentiation of mouse brain tissue regions.

RESULTS

Mass spectral differences associated with capture/ESI solvent composition manifested as altered relative distributions of ions rather than the presence or absence of unique ions. In negative ion mode ESI, 80/20 (v/v) methanol/water yielded spectra with low signal/noise ratios relative to other solvents. PCA-LDA models acquired using 90/10 (v/v) methanol/chloroform differentiated tissue regions with 100% accuracy while data collected using methanol misclassified some samples. The combination of SWATH-MS and TOF-MS data improved differentiation accuracy.

CONCLUSIONS

Combined TOF-MS and SWATH-MS data differentiated white, grey, granular, and nucleus mouse tissue regions with greater accuracy than when solely using TOF-MS data. Using 90/10 (v/v) methanol/chloroform, tissue regions were perfectly differentiated. These results will guide future studies looking to utilize the potential of LMD-LVC/ESI-MS for tissue and disease differentiation.

Advances in Brain Tumor Surgery for Glioblastoma in Adults

Glioblastoma (GBM) is the most common primary intracranial neoplasia, and is characterized by its extremely poor prognosis. Despite maximum surgery, chemotherapy, and radiation, the histological heterogeneity of GBM makes total eradication impossible, due to residual cancer cells invading the parenchyma, which is not otherwise seen in radiographic images. Even with gross total resection, the heterogeneity and the dormant nature of brain tumor initiating cells allow for therapeutic evasion, contributing to its recurrence and malignant progression, and severely impacting survival. Visual delimitation of the tumor’s margins with common surgical techniques is a challenge faced by many surgeons. In an attempt to achieve optimal safe resection, advances in approaches allowing intraoperative analysis of cancer and non-cancer tissue have been developed and applied in humans resulting in improved outcomes. In addition, functional paradigms based on stimulation techniques to map the brain’s electrical activity have optimized glioma resection in eloquent areas such as the Broca’s, Wernike’s and perirolandic areas. In this review, we will elaborate on the current standard therapy for newly diagnosed and recurrent glioblastoma with a focus on surgical approaches. We will describe current technologies used for glioma resection, such as awake craniotomy, fluorescence guided surgery, laser interstitial thermal therapy and intraoperative mass spectrometry. Additionally, we will describe a newly developed tool that has shown promising results in preclinical experiments for brain cancer: optical coherence tomography.

Ambient Mass Spectrometry in Cancer Research

Ambient ionization mass spectrometry was developed as a sample preparation-free alternative to traditional MS-based workflows. Desorption electrospray ionization (DESI)-MS methods were demonstrated to allow the direct analysis of a broad range of samples including unaltered biological tissue specimens. In contrast to this advantageous feature, nowadays DESI-MS is almost exclusively used for sample preparation intensive mass spectrometric imaging (MSI) in the area of cancer research. As an alternative to MALDI, DESI-MSI offers matrix deposition-free experiment with improved signal in the lower (<500m/z) range. DESI-MSI enables the spatial mapping of tumor metabolism and has been broadly demonstrated to offer an alternative to frozen section histology for intraoperative tissue identification and surgical margin assessment. Rapid evaporative ionization mass spectrometry (REIMS) was developed exclusively for the latter purpose by the direct combination of electrosurgical devices and mass spectrometry. In case of the REIMS technology, aerosol particles produced by electrosurgical dissection are subjected to MS analysis, providing spectral information on the structural lipid composition of tissues. REIMS technology was demonstrated to give real-time information on the histological nature of tissues being dissected, deeming it an ideal tool for intraoperative tissue identification including surgical margin control. More recently, the method has also been used for the rapid lipidomic phenotyping of cancer cell lines as it was demonstrated in case of the NCI-60 cell line collection.

Ambient ionization mass spectrometric analysis of human surgical specimens to distinguish renal cell carcinoma from healthy renal tissue

Touch spray-mass spectrometry (TS-MS) is an ambient ionization technique (ionization of unprocessed samples in the open air) that may find intraoperative applications in quickly identifying the disease state of cancerous tissues and in defining surgical margins. In this study, TS-MS was performed on fresh kidney tissue (∼1-5 cm(3)), within 1 h of resection, from 21 human subjects afflicted by renal cell carcinoma (RCC). The preliminary diagnostic value of TS-MS data taken from freshly resected tissue was evaluated. Principal component analysis (PCA) of the negative ion mode (m/z 700-1000) data provided the separation between RCC (16 samples) and healthy renal tissue (13 samples). Linear discriminant analysis (LDA) on the PCA-compressed data estimated sensitivity (true positive rate) and specificity (true negative rate) of 98 and 95 %, respectively, based on histopathological evaluation. The results indicate that TS-MS might provide rapid diagnostic information in spite of the complexity of unprocessed kidney tissue and the presence of interferences such as urine and blood. Desorption electrospray ionization-MS imaging (DESI-MSI) in the negative ionization mode was performed on the tissue specimens after TS-MS analysis as a reference method. The DESI imaging experiments provided phospholipid profiles (m/z 700-1000) that also separated RCC and healthy tissue in the PCA space, with PCA-LDA sensitivity and specificity of 100 and 89 %, respectively. The TS and DESI loading plots indicated that different ions contributed most to the separation of RCC from healthy renal tissue (m/z 794 [PC 34:1 + Cl](-) and 844 [PC 38:4 + Cl](-) for TS vs. m/z 788 [PS 36:1 - H](-) and 810 [PS 38:4 - H](-) for DESI), while m/z 885 ([PI 38:4 - H](-)) was important in both TS and DESI. The prospect, remaining hurdles, and future work required for translating TS-MS into a method of intraoperative tissue diagnosis are discussed. Graphical abstract Touch spray-mass spectrometry used for lipid profiling of fresh human renal cell carcinoma. Left) Photograph of the touch spray probe pointed at the MS inlet. Right) Average mass spectra of healthy renal tissue (blue) and RCC (red).

Wide-field tissue polarimetry allows efficient localized mass spectrometry imaging of biological tissues

While mass spectrometers can detect chemical signatures within milliseconds of data acquisition time, the non-targeted nature of mass spectrometry imaging (MSI) necessitates probing the entire surface of the sample to reveal molecular composition even if the information is only sought from a sample subsection. This leads to long analysis times. Here, we used polarimetry to identify, within a biological tissue, areas of polarimetric heterogeneity indicative of cancer. We were then able to target our MS analysis using polarimetry results to either the cancer region itself or to the cancer margin. A tandem of polarimetry and Desorption Electrospray Ionization Mass Spectrometry Imaging (DESI-MSI) enables fast (10 fold compared to non-targeted imaging), and accurate pathology assessment (cancer typification in less than 2 minutes compared to 30 minutes for histopathology) of ex vivo tissue slices, without additional sample preparation. This workflow reduces the overall analysis time of MSI as a research tool.

Lipid and metabolite profiles of human brain tumors by desorption electrospray ionization-MS

Examination of tissue sections using desorption electrospray ionization (DESI)-MS revealed phospholipid-derived signals that differ between gray matter, white matter, gliomas, meningiomas, and pituitary tumors, allowing their ready discrimination by multivariate statistics. A set of lower mass signals, some corresponding to oncometabolites, including 2-hydroxyglutaric acid and N-acetyl-aspartic acid, was also observed in the DESI mass spectra, and these data further assisted in discrimination between brain parenchyma and gliomas. The combined information from the lipid and metabolite MS profiles recorded by DESI-MS and explored using multivariate statistics allowed successful differentiation of gray matter (n = 223), white matter (n = 66), gliomas (n = 158), meningiomas (n = 111), and pituitary tumors (n = 154) from 58 patients. A linear discriminant model used to distinguish brain parenchyma and gliomas yielded an overall sensitivity of 97.4% and a specificity of 98.5%. Furthermore, a discriminant model was created for tumor types (i.e., glioma, meningioma, and pituitary), which were discriminated with an overall sensitivity of 99.4% and a specificity of 99.7%. Unsupervised multivariate statistics were used to explore the chemical differences between anatomical regions of brain parenchyma and secondary infiltration. Infiltration of gliomas into normal tissue can be detected by DESI-MS. One hurdle to implementation of DESI-MS intraoperatively is the need for tissue freezing and sectioning, which we address by analyzing smeared biopsy tissue. Tissue smears are shown to give the same chemical information as tissue sections, eliminating the need for sectioning before MS analysis. These results lay the foundation for implementation of intraoperative DESI-MS evaluation of tissue smears for rapid diagnosis.

Recent advances in surgical planning & navigation for tumor biopsy and resection

This paper highlights recent advancements in imaging technologies for surgical planning and navigation in tumor biopsy and resection which need high-precision in detection and characterization of lesion margin in preoperative planning and intraoperative navigation. Multimodality image-guided surgery platforms brought great benefits in surgical planning and operation accuracy via registration of various data sets with information on morphology [X-ray, magnetic resonance (MR), computed tomography (CT)], function connectivity [functional magnetic resonance imaging (fMRI), diffusion tensor imaging (DTI), rest-status fMRI], or molecular activity [positron emission tomography (PET)]. These image-guided platforms provide a correspondence between the pre-operative surgical planning and intra-operative procedure. We envisage that the combination of advanced multimodal imaging, three-dimensional (3D) printing, and cloud computing will play increasingly important roles in planning and navigation of surgery for tumor biopsy and resection in the coming years.

Ambient Ionization Mass Spectrometry for Cancer Diagnosis and Surgical Margin Evaluation

BACKGROUND

There is a clinical need for new technologies that would enable rapid disease diagnosis based on diagnostic molecular signatures. Ambient ionization mass spectrometry has revolutionized the means by which molecular information can be obtained from tissue samples in real time and with minimal sample pretreatment. New developments in ambient ionization techniques applied to clinical research suggest that ambient ionization mass spectrometry will soon become a routine medical tool for tissue diagnosis.

CONTENT

This review summarizes the main developments in ambient ionization techniques applied to tissue analysis, with focus on desorption electrospray ionization mass spectrometry, probe electrospray ionization, touch spray, and rapid evaporative ionization mass spectrometry. We describe their applications to human cancer research and surgical margin evaluation, highlighting integrated approaches tested for ex vivo and in vivo human cancer tissue analysis. We also discuss the challenges for clinical implementation of these tools and offer perspectives on the future of the field.

SUMMARY

A variety of studies have showcased the value of ambient ionization mass spectrometry for rapid and accurate cancer diagnosis. Small molecules have been identified as potential diagnostic biomarkers, including metabolites, fatty acids, and glycerophospholipids. Statistical analysis allows tissue discrimination with high accuracy rates (>95%) being common. This young field has challenges to overcome before it is ready to be broadly accepted as a medical tool for cancer diagnosis. Growing research in new, integrated ambient ionization mass spectrometry technologies and the ongoing improvements in the existing tools make this field very promising for future translation into the clinic.

Molecular typing of Meningiomas by Desorption Electrospray Ionization Mass Spectrometry Imaging for Surgical Decision-Making

Meningiomas are the most frequent intracranial tumors. The majority is benign slow-growing tumors but they can be difficult to treat depending on their location and size. While meningiomas are well delineated on magnetic resonance imaging by their uptake of contrast, surgical limitations still present themselves from not knowing the extent of invasion of the dura matter by meningioma cells. The development of tools to characterize tumor tissue in real or near real time could prevent recurrence after tumor resection by allowing for more precise surgery, i.e. removal of tumor with preservation of healthy tissue. The development of ambient ionization mass spectrometry for molecular characterization of tissue and its implementation in the surgical decision-making workflow carry the potential to fulfill this need. Here, we present the characterization of meningioma and dura mater by desorption electrospray ionization mass spectrometry to validate the technique for the molecular assessment of surgical margins and diagnosis of meningioma from surgical tissue in real-time. Nine stereotactically resected surgical samples and three autopsy samples were analyzed by standard histopathology and mass spectrometry imaging. All samples indicated a strong correlation between results from both techniques. We then highlight the value of desorption electrospray ionization mass spectrometry for the molecular subtyping/subgrouping of meningiomas from a series of forty genetically characterized specimens. The minimal sample preparation required for desorption electrospray ionization mass spectrometry offers a distinct advantage for applications relying on real-time information such as surgical decision-making. The technology here was tested to distinguish meningioma from dura mater as an approach to precisely define surgical margins. In addition we classify meningiomas into fibroblastic and meningothelial subtypes and more notably recognize meningiomas with NF2 genetic aberrations.

Multimodal imaging for improved diagnosis and treatment of cancers

The authors review methods for image-guided diagnosis and therapy that increase precision in the detection, characterization, and localization of many forms of cancer to achieve optimal target definition and complete resection or ablation. A new model of translational, clinical, image-guided therapy research is presented, and the Advanced Multimodality Image-Guided Operating (AMIGO) suite is described. AMIGO was conceived and designed to allow for the full integration of imaging in cancer diagnosis and treatment. Examples are drawn from over 500 procedures performed on brain, neck, spine, thorax (breast, lung), and pelvis (prostate and gynecologic) areas and are used to describe how they address some of the many challenges of treating brain, prostate, and lung tumors. Cancer 2015;121:817-827. © 2014 American Cancer Society.

Intraoperative mass spectrometry mapping of an onco-metabolite to guide brain tumor surgery

For many intraoperative decisions surgeons depend on frozen section pathology, a technique developed over 150 y ago. Technical innovations that permit rapid molecular characterization of tissue samples at the time of surgery are needed. Here, using desorption electrospray ionization (DESI) MS, we rapidly detect the tumor metabolite 2-hydroxyglutarate (2-HG) from tissue sections of surgically resected gliomas, under ambient conditions and without complex or time-consuming preparation. With DESI MS, we identify isocitrate dehydrogenase 1-mutant tumors with both high sensitivity and specificity within minutes, immediately providing critical diagnostic, prognostic, and predictive information. Imaging tissue sections with DESI MS shows that the 2-HG signal overlaps with areas of tumor and that 2-HG levels correlate with tumor content, thereby indicating tumor margins. Mapping the 2-HG signal onto 3D MRI reconstructions of tumors allows the integration of molecular and radiologic information for enhanced clinical decision making. We also validate the methodology and its deployment in the operating room: We have installed a mass spectrometer in our Advanced Multimodality Image Guided Operating (AMIGO) suite and demonstrate the molecular analysis of surgical tissue during brain surgery. This work indicates that metabolite-imaging MS could transform many aspects of surgical care.

Development of a mass spectrometry sampling probe for chemical analysis in surgical and endoscopic procedures

A sampling probe based on ambient desorption ionization was designed for in vivo chemical analysis by mass spectrometry in surgical and endoscopic procedures. Sampling ionization of analytes directly from tissue was achieved by sealing the sampling tip against the tissue surface without allowing leakage of the auxiliary gas used for desorption ionization. The desorbed charged species were transferred over a long distance (up to 4 m) through a flexible tube of internal diameter as small as 1/16 in. to the inlet of the mass spectrometer used for analysis. The conditions used for desorption electrospray ionization (DESI) were optimized to achieve biocompatibility for clinical applications while obtaining adequate efficiency for the analysis. This optimization involved the removal of high voltage and use of pure water as a spray solvent instead of the organic solvents or aqueous mixtures normally used. Improved sensitivity was achieved under these conditions by increasing the gas flow rate in the transfer tube. The destructive effect on tissue surfaces associated with typical desorption ionization was avoided by altering the local gas dynamics in the sample area without compromising the overall analysis efficiency.

Mass spectrometry imaging as a tool for surgical decision-making

Despite significant advances in image-guided therapy, surgeons are still too often left with uncertainty when deciding to remove tissue. This binary decision between removing and leaving tissue during surgery implies that the surgeon should be able to distinguish tumor from healthy tissue. In neurosurgery, current image-guidance approaches such as magnetic resonance imaging (MRI) combined with neuronavigation offer a map as to where the tumor should be, but the only definitive method to characterize the tissue at stake is histopathology. Although extremely valuable information is derived from this gold standard approach, it is limited to very few samples during surgery and is not practically used for the delineation of tumor margins. The development and implementation of faster, comprehensive, and complementary approaches for tissue characterization are required to support surgical decision-making--an incremental and iterative process with tumor removed in multiple and often minute biopsies. The development of atmospheric pressure ionization sources makes it possible to analyze tissue specimens with little to no sample preparation. Here, we highlight the value of desorption electrospray ionization as one of many available approaches for the analysis of surgical tissue. Twelve surgical samples resected from a patient during surgery were analyzed and diagnosed as glioblastoma tumor or necrotic tissue by standard histopathology, and mass spectrometry results were further correlated to histopathology for critical validation of the approach. The use of a robust statistical approach reiterated results from the qualitative detection of potential biomarkers of these tissue types. The correlation of the mass spectrometry and histopathology results to MRI brings significant insight into tumor presentation that could not only serve to guide tumor resection, but that is also worthy of more detailed studies on our understanding of tumor presentation on MRI.

Recursive feature elimination for brain tumor classification using desorption electrospray ionization mass spectrometry imaging

The metabolism and composition of lipids is of increasing interest for understanding and detecting disease processes. Lipid signatures of tumor type and grade have been demonstrated using magnetic resonance spectroscopy. Clinical management and ultimate prognosis of brain tumors depend largely on the tumor type, subtype, and grade. Mass spectrometry, a well-known analytical technique used to identify molecules in a given sample based on their mass, can significantly improve the problem of tumor type classification. This work focuses on the problem of identifying lipid features to use as input for classification. Feature selection could result in improvements in classifier performance, discovery of biomarkers, improved data interpretation, and patient treatment.

Neuronavigation in the surgical management of brain tumors: current and future trends

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.

Statistical spectroscopic tools for biomarker discovery and systems medicine

Metabolic profiling based on comparative, statistical analysis of NMR spectroscopic and mass spectrometric data from complex biological samples has contributed to increased understanding of the role of small molecules in affecting and indicating biological processes. To enable this research, the development of statistical spectroscopy has been marked by early beginnings in applying pattern recognition to nuclear magnetic resonance data and the introduction of statistical total correlation spectroscopy (STOCSY) as a tool for biomarker identification in the past decade. Extensions of statistical spectroscopy now compose a family of related tools used for compound identification, data preprocessing, and metabolic pathway analysis. In this Perspective, we review the theory and current state of research in statistical spectroscopy and discuss the growing applications of these tools to medicine and systems biology. We also provide perspectives on how recent institutional initiatives are providing new platforms for the development and application of statistical spectroscopy tools and driving the development of integrated "systems medicine" approaches in which clinical decision making is supported by statistical and computational analysis of metabolic, phenotypic, and physiological data.

Analysis of renal cell carcinoma as a first step for developing mass spectrometry-based diagnostics

Immediate diagnosis of human specimen is an essential prerequisites in medical routines. This study aimed to establish a novel cancer diagnostics system based on probe electrospray ionization-mass spectrometry (PESI-MS) combined with statistical data processing. PESI-MS uses a very fine acupuncture needle as a probe for sampling as well as for ionization. To demonstrate the applicability of PESI-MS for cancer diagnosis, we analyzed nine cases of clear cell renal cell carcinoma (ccRCC) by PESI-MS and processed the data by principal components analysis (PCA). Our system successfully delineated the differences in lipid composition between non-cancerous and cancerous regions. In this case, triacylglycerol (TAG) was reproducibly detected in the cancerous tissue of nine different individuals, the result being consistent with well-known profiles of ccRCC. Moreover, this system enabled us to detect the boundaries of cancerous regions based on the expression of TAG. These results strongly suggest that PESI-MS will be applicable to cancer diagnosis, especially when the number of data is augmented.

Increased frameless stereotactic accuracy with high-field intraoperative magnetic resonance imaging

BACKGROUND

Frameless stereotaxy commonly registers preoperative magnetic resonance imaging (MRI) to patients by using surface scalp anatomy or adhesive fiducial scalp markers. Patients' scalps may shift slightly between preoperative imaging and final surgical positioning with pinion placement, introducing error. This might be reduced when frameless stereotaxy is performed in a high-field intraoperative MRI (iMRI), as patients are positioned before imaging. This could potentially improve accuracy.

OBJECTIVE

To compare frameless stereotactic accuracy using a high-field iMRI with that using standard preoperative MRI.

METHODS

Data were obtained in 32 adult patients undergoing frameless stereotactic-guided brain tumor surgery. Stereotactic images were obtained with 1.5T MRI scanner either preoperatively (14 patients) or intraoperative (18 patients). System-generated accuracy measurements and distances from the actual center of each fiducial marker to that represented by neuronavigation were recorded. Finally, accuracy at multiple deep targets was assessed by using a life-sized human head stereotactic phantom in which fiducials were placed on deformable foam to mimic scalp.

RESULTS

: System-generated accuracy measurements were significantly better for the iMRI group (mean ± SEM = 1.04 ± 0.05 mm) than for the standard group (1.82 ± 0.09 mm; P < .001). Measured distances from the actual center of scalp fiducial markers to that represented by neuronavigation were also significantly smaller for iMRI (1.72 ± 0.10 mm) in comparison with the standard group (3.17 ± 0.22 mm; P < .001). Deep accuracy in the phantom model was significantly better with iMRI (1.67 ± 0.12 mm) than standard imaging (2.28 ± 0.14 mm; P = .003).

CONCLUSION

Frameless stereotactic accuracy is increased by using high-field iMRI compared with standard preoperative imaging.

Classifying human brain tumors by lipid imaging with mass spectrometry

Brain tissue biopsies are required to histologically diagnose brain tumors, but current approaches are limited by tissue characterization at the time of surgery. Emerging technologies such as mass spectrometry imaging can enable a rapid direct analysis of cancerous tissue based on molecular composition. Here, we illustrate how gliomas can be rapidly classified by desorption electrospray ionization-mass spectrometry (DESI-MS) imaging, multivariate statistical analysis, and machine learning. DESI-MS imaging was carried out on 36 human glioma samples, including oligodendroglioma, astrocytoma, and oligoastrocytoma, all of different histologic grades and varied tumor cell concentration. Gray and white matter from glial tumors were readily discriminated and detailed diagnostic information could be provided. Classifiers for subtype, grade, and concentration features generated with lipidomic data showed high recognition capability with more than 97% cross-validation. Specimen classification in an independent validation set agreed with expert histopathology diagnosis for 79% of tested features. Together, our findings offer proof of concept that intraoperative examination and classification of brain tissue by mass spectrometry can provide surgeons, pathologists, and oncologists with critical and previously unavailable information to rapidly guide surgical resections that can improve management of patients with malignant brain tumors.

Desorption electrospray ionization then MALDI mass spectrometry imaging of lipid and protein distributions in single tissue sections

Imaging mass spectrometry (MS) is a powerful technique for mapping the spatial distributions of a wide range of chemical compounds simultaneously from a tissue section. Co-localization of the distribution of individual molecular species, including particular lipids and proteins, and correlation with the morphological features of a single tissue section are highly desirable for comprehensive tissue analysis and disease diagnosis. We now report on the use, in turn, of desorption electrospray ionization (DESI), matrix assisted laser desorption ionization (MALDI), and then optical microscopy to image lipid and protein distributions in a single tissue section. This is possible through the use of histologically compatible DESI solvent systems, which allow for sequential analyses of the same section by DESI then MALDI. Hematoxylin and eosin (H&E) staining was performed on the same section after removal of the MALDI matrix. This workflow allowed chemical information to be unambiguously matched to histological features in mouse brain tissue sections. The lipid sulfatide (24:1), detected at m/z 888.8 by DESI imaging, was colocalized with the protein MBP isoform 8, detected at m/z 14117 by MALDI imaging, in regions corresponding to the corpus callosum substructure of the mouse brain, as confirmed in the H&E images. Correlation of lipid and protein distributions with histopathological features was also achieved for human brain cancer samples. Higher tumor cell density was observed in regions demonstrating higher relative abundances of oleic acid, detected by DESI imaging at m/z 281.4, and the protein calcyclin, detected by MALDI at m/z 10085, for a human glioma sample. Since correlation between molecular signatures and disease state can be achieved, we expect that this methodology will significantly enhance the value of MS imaging in molecular pathology for diagnosis.

Real time analysis of brain tissue by direct combination of ultrasonic surgical aspiration and sonic spray mass spectrometry

Direct combination of cavitron ultrasonic surgical aspirator (CUSA) and sonic spray ionization mass spectrometry is presented. A commercially available ultrasonic surgical device was coupled to a Venturi easy ambient sonic-spray ionization (V-EASI) source by directly introducing liquified tissue debris into the Venturi air jet pump. The Venturi air jet pump was found to efficiently nebulize the suspended tissue material for gas phase ion production. The ionization mechanism involving solely pneumatic spraying was associated with that of sonic spray ionization. Positive and negative ionization spectra were obtained from brain and liver samples reflecting the primary application areas of the surgical device. Mass spectra were found to feature predominantly complex lipid-type constituents of tissues in both ion polarity modes. Multiply charged peptide anions were also detected. The influence of instrumental settings was characterized in detail. Venturi pump geometry and flow parameters were found to be critically important in ionization efficiency. Standard solutions of phospholipids and peptides were analyzed in order to test the dynamic range, sensitivity, and suppression effects. The spectra of the intact tissue specimens were found to be highly specific to the histological tissue type. The principal component analysis (PCA) and linear discriminant analysis (LDA) based data analysis method was developed for real-time tissue identification in a surgical environment. The method has been successfully tested on post-mortem and ex vivo human samples including astrocytomas, meningeomas, metastatic brain tumors, and healthy brain tissue.

Desorption electrospray ionization mass spectrometry for lipid characterization and biological tissue imaging

Desorption electrospray ionization mass spectrometry (DESI-MS) imaging of biological samples allows untargeted analysis and structural characterization of lipids ionized from the near-surface region of a sample under ambient conditions. DESI is a powerful and sensitive MS ionization method for 2D and 3D imaging of lipids from direct and unmodified complex biological samples. This review describes the strengths and limitations of DESI-MS for lipid characterization and imaging together with the technical workflow and a survey of applications. Included are discussions of lipid mapping and biomarker discovery as well as a perspective on the future of DESI imaging.

A compressive sensing approach for glioma margin delineation using mass spectrometry

Surgery, and specifically, tumor resection, is the primary treatment for most patients suffering from brain tumors. Medical imaging techniques, and in particular, magnetic resonance imaging are currently used in diagnosis as well as image-guided surgery procedures. However, studies show that computed tomography and magnetic resonance imaging fail to accurately identify the full extent of malignant brain tumors and their microscopic infiltration. Mass spectrometry is a well-known analytical technique used to identify molecules in a given sample based on their mass. In a recent study, it is proposed to use mass spectrometry as an intraoperative tool for discriminating tumor and non-tumor tissue. Integration of mass spectrometry with the resection module allows for tumor resection and immediate molecular analysis. In this paper, we propose a framework for tumor margin delineation using compressive sensing. Specifically, we show that the spatial distribution of tumor cell concentration can be efficiently reconstructed and updated using mass spectrometry information from the resected tissue. In addition, our proposed framework is model-free, and hence, requires no prior information of spatial distribution of the tumor cell concentration.