Lipid profiling of electrosurgical vapors for real-time assistance of soft tissue sarcoma resection.

BACKGROUND: Soft tissue sarcomas (STS) constitute a heterogeneous group of rare tumor entities. Treatment relies on challenging patient-tailored surgical resection. Real-time intraoperative lipid profiling of electrosurgical vapors by rapid evaporative ionization mass spectrometry (REIMS) may aid in achieving successful surgical R0 resection (i.e., microscopically negative-tumor margin resection). Here, we evaluate the ex vivo accuracy of REIMS to discriminate and identify various STS from normal surrounding tissue. METHODS: Twenty-seven patients undergoing surgery for STS at Maastricht University Medical Center+ were included in the study. Samples of resected STS specimens were collected and analyzed ex vivo using REIMS. Electrosurgical cauterization of tumor and surrounding was generated successively in both cut and coagulation modes. Resected specimens were subsequently processed for gold standard histopathological review. Multivariate statistical analysis (principal component analysis-linear discriminant analysis) and leave-one patient-out cross-validation were employed to compare the classifications predicted by REIMS lipid profiles to the pathology classifications. Electrosurgical vapors produced during sarcoma resection were analyzed in vivo using REIMS. RESULTS: In total, 1200 histopathologically-validated ex vivo REIMS lipid profiles were generated from 27 patients. Ex vivo REIMS lipid profiles classified STS and normal tissues with 95.5% accuracy. STS, adipose and muscle tissues were classified with 98.3% accuracy. Well-differentiated liposarcomas and adipose tissues could not be discriminated based on their respective lipid profiles. Distinction of leiomyosarcomas from other STS could be achieved with 96.6% accuracy. In vivo REIMS analyses generated intense mass spectrometric signals. CONCLUSION: Lipid profiling by REIMS is able to discriminate and identify STS with high accuracy and therefore constitutes a potential asset to improve surgical resection of STS in the future.

High-resolution ion mobility spectrometry-mass spectrometry for isomeric separation of prostanoids after Girard's reagent T derivatization.

RATIONALE: Isomeric separation of prostanoids is often a challenge and requires chromatography and time-consuming sample preparation. Multiple prostanoid isomers have distinct in vivo functions crucial for understanding the inflammation process, including prostaglandins E2 (PGE2 ) and D2 (PGD2 ). High-resolution ion mobility spectrometry (IMS) based on linear ion transport in low-to-moderate electric fields and nonlinear ion transport in strong electric fields emerges as a broad approach for rapid separations prior to mass spectrometry. METHODS: Derivatization with Girard's reagent T (GT) was used to overcome inefficient ionization of prostanoids in negative ionization mode due to poor deprotonation of the carboxylic acid group. Three high-resolution IMS techniques, namely linear cyclic IMS, linear trapped IMS, and nonlinear high-field asymmetric waveform IMS, were compared for the isomeric separation and endogenous detection of prostanoids present in intestinal tissue. RESULTS: Direct infusion of GT-derivatized prostanoids proved to increase the ionization efficiency in positive ionization mode by a factor of >10, which enabled detection of these molecules in endogenous concentration levels. The high-resolution IMS comparison revealed its potential for rapid isomeric analysis of biologically relevant prostanoids. Strengths and weaknesses of both linear and nonlinear IMS are discussed. Endogenous prostanoid detection in intestinal tissue extracts demonstrated the applicability of our approach in biomedical research. CONCLUSIONS: The applied derivatization strategy offers high sensitivity and improved stereoisomeric separation for screening of complex biological systems. The high-resolution IMS comparison indicated that the best sensitivity and resolution are achieved by linear and nonlinear IMS, respectively.

Harmonization of Rapid Evaporative Ionization Mass Spectrometry Workflows across Four Sites and Testing Using Reference Material and Local Food-Grade Meats.

Rapid evaporative ionization mass spectrometry (REIMS) is a direct tissue metabolic profiling technique used to accurately classify tissues using pre-built mass spectral databases. The reproducibility of the analytical equipment, methodology and tissue classification algorithms has yet to be evaluated over multiple sites, which is an essential step for developing this technique for future clinical applications. In this study, we harmonized REIMS methodology using single-source reference material across four sites with identical equipment: Imperial College London (UK); Waters Research Centre (Hungary); Maastricht University (The Netherlands); and Queen's University (Canada). We observed that method harmonization resulted in reduced spectral variability across sites. Each site then analyzed four different types of locally-sourced food-grade animal tissue. Tissue recognition models were created at each site using multivariate statistical analysis based on the different metabolic profiles observed in the m/z range of 600-1000, and these models were tested against data obtained at the other sites. Cross-validation by site resulted in 100% correct classification of two reference tissues and 69-100% correct classification for food-grade meat samples. While we were able to successfully minimize between-site variability in REIMS signals, differences in animal tissue from local sources led to significant variability in the accuracy of an individual site's model. Our results inform future multi-site REIMS studies applied to clinical samples and emphasize the importance of carefully-annotated samples that encompass sufficient population diversity.

Evaluation of the Sensitivity of Metabolic Profiling by Rapid Evaporative Ionization Mass Spectrometry: Toward More Radical Oral Cavity Cancer Resections.

Radical resection for patients with oral cavity cancer remains challenging. Rapid evaporative ionization mass spectrometry (REIMS) of electrosurgical vapors has been reported for real-time classification of normal and tumor tissues for numerous surgical applications. However, the infiltrative pattern of invasion of oral squamous cell carcinomas (OSCC) challenges the ability of REIMS to detect low amounts of tumor cells. We evaluate REIMS sensitivity to determine the minimal amount of detected tumors cells during oral cavity cancer surgery. A total of 11 OSCC patients were included in this study. The tissue classification based on 185 REIMS ex vivo metabolic profiles from five patients was compared to histopathology classification using multivariate analysis and leave-one-patient-out cross-validation. Vapors were analyzed in vivo by REIMS during four glossectomies. Complementary desorption electrospray ionization-mass spectrometry imaging (DESI-MSI) was employed to map tissue heterogeneity on six oral cavity sections to support REIMS findings. REIMS sensitivity was assessed with a new cell-based assay consisting of mixtures of cell lines (tumor, myoblasts, keratinocytes). Our results depict REIMS classified tumor and soft tissues with 96.8% accuracy. In vivo REIMS generated intense mass spectrometric signals. REIMS detected 10% of tumor cells mixed with 90% myoblasts with 83% sensitivity and 82% specificity. DESI-MSI underlined distinct metabolic profiles of nerve features and a metabolic shift phosphatidylethanolamine PE(O-16:1/18:2))/cholesterol sulfate common to both mucosal maturation and OSCC differentiation. In conclusion, the assessment of tissue heterogeneity with DESI-MSI and REIMS sensitivity with cell mixtures characterized sensitive metabolic profiles toward in vivo tissue recognition during oral cavity cancer surgeries.

Uncovering the behaviour of ions in the gas-phase to predict the ion mobility separation of isomeric steroid compounds.

Bile acids are steroid compounds involved in biological mechanisms of neurodegenerative diseases making them potential biomarkers for diagnosis or treatment. These compounds exist as structural and conformational isomers, which hinder distinguishing them in physiological processes. We aimed to develop tandem mass spectrometry-ion mobility spectrometry (MS/MS-IMS) methodologies to explore and understand the behaviour of isomeric steroids in the gas-phase and rapidly separate them. Unlike previously published ion mobility data, various isomers were investigated in mixtures to better mimic complex (pre-) clinical samples. The experimental collision cross sections (CCS)s were compared to the theoretical CCS values for an in-depth analysis of isomeric ions' behaviour in the gas-phase. Based on density-functional theory, we identified the impact of adduct positioning on the 3D conformation of enantiomers, diastereomers and structural isomers. The curling of the large side chains hedged the small differences among the isomers and lowered the CCS values. On the other hand, fragmenting off the identical side branches as well as imposing the bending of the steroid ring resulted in ion mobility differentiation. Careful data evaluation revealed the tendency of isomers to form homo-cluster in the mixture solutions and assist the separation. Our fundamental and experimental findings enable the ion mobility separation of isomeric steroids to be predicted. The introduced rapid and optimal MS/MS-IMS analytical methodology can be applied to distinguish isomeric bile acids both in a solution and potentially in patients' tissue samples, and consequently, reveal their molecular pathways.

Quantitative mass spectrometry imaging of drugs and metabolites: a multiplatform comparison.

Mass spectrometry imaging (MSI) provides insight into the molecular distribution of a broad range of compounds and, therefore, is frequently applied in the pharmaceutical industry. Pharmacokinetic and toxicological studies deploy MSI to localize potential drugs and their metabolites in biological tissues but currently require other analytical tools to quantify these pharmaceutical compounds in the same tissues. Quantitative mass spectrometry imaging (Q-MSI) is a field with challenges due to the high biological variability in samples combined with the limited sample cleanup and separation strategies available prior to MSI. In consequence, more selectivity in MSI instruments is required. This can be provided by multiple reaction monitoring (MRM) which uses specific precursor ion-product ion transitions. This targeted approach is in particular suitable for pharmaceutical compounds because their molecular identity is known prior to analysis. In this work, we compared different analytical platforms to assess the performance of MRM detection compared to other MS instruments/MS modes used in a Q-MSI workflow for two drug candidates (A and B). Limit of detection (LOD), linearity, and precision and accuracy of high and low quality control (QC) samples were compared between MS instruments/modes. MRM mode on a triple quadrupole mass spectrometer (QqQ) provided the best overall performance with the following results for compounds A and B: LOD 35.5 and 2.5 µg/g tissue, R2 0.97 and 0.98 linearity, relative standard deviation QC <13.6%, and 97-112% accuracy. Other MS modes resulted in LOD 6.7-569.4 and 2.6-119.1 µg/g tissue, R2 0.86-0.98 and 0.86-0.98 linearity, relative standard deviation QC < 19.4 and < 37.5%, and 70-356% and 64-398% accuracy for drug candidates A and B, respectively. In addition, we propose an optimized 3D printed mimetic tissue model to increase the overall analytical throughput of our approach for large animal studies. The MRM imaging platform was applied as proof-of-principle for quantitative detection of drug candidates A and B in four dog livers and compared to LC-MS. The Q-MSI concentrations differed <3.5 times with the concentrations observed by LC-MS. Our presented MRM-based Q-MSI approach provides a more selective and high-throughput analytical platform due to MRM specificity combined with an optimized 3D printed mimetic tissue model.

Batch Effects in MALDI Mass Spectrometry Imaging.

Mass spectrometry imaging (MSI) has become an indispensible tool for spatially resolved molecular investigation of tissues. One of the key application areas is biomedical research, where matrix-assisted laser desorption/ionization (MALDI) MSI is predominantly used due to its high-throughput capability, flexibility in the molecular class to investigate, and ability to achieve single cell spatial resolution. While many of the initial technical challenges have now been resolved, so-called batch effects, a phenomenon already known from other omics fields, appear to significantly impede reliable comparison of data from particular midsized studies typically performed in translational clinical research. This critical insight will discuss at what levels (pixel, section, slide, time, and location) batch effects can manifest themselves in MALDI-MSI data and what consequences this might have for biomarker discovery or multivariate classification. Finally, measures are presented that could be taken to recognize and/or minimize these potentially detrimental effects, and an outlook is provided on what is still needed to ultimately overcome these effects.

Real-time lipid patterns to classify viable and necrotic liver tumors.

Real-time tissue classifiers based on molecular patterns are emerging tools for fast tumor diagnosis. Here, we used rapid evaporative ionization mass spectrometry (REIMS) and multivariate statistical analysis (principal component analysis-linear discriminant analysis) to classify tissues with subsequent comparison to gold standard histopathology. We explored whether REIMS lipid patterns can identify human liver tumors and improve the rapid characterization of their underlying metabolic features. REIMS-based classification of liver parenchyma (LP), hepatocellular carcinoma (HCC), and metastatic adenocarcinoma (MAC) reached an accuracy of 98.3%. Lipid patterns of LP were more similar to those of HCC than to those of MAC and allowed clear distinction between primary and metastatic liver tumors. HCC lipid patterns were more heterogeneous than those of MAC, which is consistent with the variation seen in the histopathological phenotype. A common ceramide pattern discriminated necrotic from viable tumor in MAC with 92.9% accuracy and in other human tumors. Targeted analysis of ceramide and related sphingolipid mass features in necrotic tissues may provide a new classification of tumor cell death based on metabolic shifts. Real-time lipid patterns may have a role in future clinical decision-making in cancer precision medicine.

Ion Imaging of Native Protein Complexes Using Orthogonal Time-of-Flight Mass Spectrometry and a Timepix Detector.

Native mass spectrometry (native MS) has emerged as a powerful technique to study the structure and stoichiometry of large protein complexes. Traditionally, native MS has been performed on modified time-of-flight (TOF) systems combined with detectors that do not provide information on the arrival coordinates of each ion at the detector. In this study, we describe the implementation of a Timepix (TPX) pixelated detector on a modified orthogonal TOF (O-TOF) mass spectrometer for the analysis and imaging of native protein complexes. In this unique experimental setup, we have used the impact positions of the ions at the detector to visualize the effects of various ion optical parameters on the flight path of ions. We also demonstrate the ability to unambiguously detect and image individual ion events, providing the first report of single-ion imaging of protein complexes in native MS. Furthermore, the simultaneous space- and time-sensitive nature of the TPX detector was critical in the identification of the origin of an unexpected TOF signal. A signal that could easily be mistaken as a fragment of the protein complex was explicitly identified as a secondary electron signal arising from ion-surface collisions inside the TOF housing. This work significantly extends the mass range previously detected with the TPX and exemplifies the value of simultaneous space- and time-resolved detection in the study of ion optical processes and ion trajectories in TOF mass spectrometers.

Lipid Analysis of Fracture Hematoma With MALDI-MSI: Specific Lipids are Associated to Bone Fracture Healing Over Time.

Background: Fracture healing is a complex process, involving cell-cell interactions, various cytokines, and growth factors. Although fracture treatment improved over the last decades, a substantial part of all fractures shows delayed or absent healing. The fracture hematoma (fxh) is known to have a relevant role in this process, while the exact mechanisms by which it influences fracture healing are poorly understood. To improve strategies in fracture treatment, regulatory pathways in fracture healing need to be investigated. Lipids are important molecules in cellular signaling, inflammation, and metabolism, as well as key structural components of the cell. Analysis of the lipid spectrum in fxh may therefore reflect important events during the early healing phase. This study aims to develop a protocol for the determination of lipid signals over time, and the identification of lipids that contribute to these signals, with matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI-MSI) in fxh in healthy fracture healing. Methods: Twelve fxh samples (6 porcine; 6 human) were surgically removed, snap frozen, sectioned, washed, and analyzed using MALDI-MSI in positive and negative ion mode at different time points after fracture (porcine: 72 h; human samples: range 1-19 days). A tissue preparation protocol for lipid analysis in fxh has been developed with both porcine and human fxh. Data were analyzed through principal component- and linear discriminant analyses. Results: A protocol for the preparation of fxh sections was developed and optimized. Although hematoma is a heterogeneous tissue, the intra-variability within fxh was smaller than the inter-variability between fxh. Distinctive m/z values were detected that contributed to the separation of three different fxh age groups: early (1-3 days), middle (6-10 days), and late (12-19 days). Identification of the distinctive m/z values provided a panel of specific lipids that showed a time dependent expression within fxh. Conclusion: This study shows that MALDI-MSI is a suitable analytical tool for lipid analysis in fxh and that lipid patterns within fxh are time-dependent. These lipid patterns within fxh may serve as a future diagnostic tool. These findings warrant further research into fxh analysis using MALDI-MSI and its possible clinical implications in fracture treatment.

Stromal vapors for real-time molecular guidance of breast-conserving surgery.

Achieving radical tumor resection while preserving disease-free tissue during breast-conserving surgery (BCS) remains a challenge. Here, mass spectrometry technologies were used to discriminate stromal tissues reported to be altered surrounding breast tumors, and build tissue classifiers ex vivo. Additionally, we employed the approach for in vivo and real-time classification of breast pathology based on electrosurgical vapors. Breast-resected samples were obtained from patients undergoing surgery at MUMC+. The specimens were subsequently sampled ex vivo to generate electrosurgical vapors analyzed by rapid evaporative ionization mass spectrometry (REIMS). Tissues were processed for histopathology to assign tissue components to the mass spectral profiles. We collected a total of 689 ex vivo REIMS profiles from 72 patients which were analyzed using multivariate statistical analysis (principal component analysis-linear discriminant analysis). These profiles were classified as adipose, stromal and tumor tissues with 92.3% accuracy with a leave-one patient-out cross-validation. Tissue recognition using this ex vivo-built REIMS classification model was subsequently tested in vivo on electrosurgical vapors. Stromal and adipose tissues were classified during one BCS. Complementary ex vivo analyses were performed by REIMS and by desorption electrospray ionization mass spectrometry (DESI-MS) to study the potential of breast stroma to guide BCS. Tumor border stroma (TBS) and remote tumor stroma (RTS) were classified by REIMS and DESI-MS with 86.4% and 87.8% accuracy, respectively. We demonstrate the potential of stromal molecular alterations surrounding breast tumors to guide BCS in real-time using REIMS analysis of electrosurgical vapors.

Spatial heterogeneity of nanomedicine investigated by multiscale imaging of the drug, the nanoparticle and the tumour environment.

Genetic and phenotypic tumour heterogeneity is an important cause of therapy resistance. Moreover, non-uniform spatial drug distribution in cancer treatment may cause pseudo-resistance, meaning that a treatment is ineffective because the drug does not reach its target at sufficient concentrations. Together with tumour heterogeneity, non-uniform drug distribution causes "therapy heterogeneity": a spatially heterogeneous treatment effect. Spatial heterogeneity in drug distribution occurs on all scales ranging from interpatient differences to intratumour differences on tissue or cellular scale. Nanomedicine aims to improve the balance between efficacy and safety of drugs by targeting drug-loaded nanoparticles specifically to tumours. Spatial heterogeneity in nanoparticle and payload distribution could be an important factor that limits their efficacy in patients. Therefore, imaging spatial nanoparticle distribution and imaging the tumour environment giving rise to this distribution could help understand (lack of) clinical success of nanomedicine. Imaging the nanoparticle, drug and tumour environment can lead to improvements of new nanotherapies, increase understanding of underlying mechanisms of heterogeneous distribution, facilitate patient selection for nanotherapies and help assess the effect of treatments that aim to reduce heterogeneity in nanoparticle distribution. In this review, we discuss three groups of imaging modalities applied in nanomedicine research: non-invasive clinical imaging methods (nuclear imaging, MRI, CT, ultrasound), optical imaging and mass spectrometry imaging. Because each imaging modality provides information at a different scale and has its own strengths and weaknesses, choosing wisely and combining modalities will lead to a wealth of information that will help bring nanomedicine forward.

Clinical use of mass spectrometry (imaging) for hard tissue analysis in abnormal fracture healing.

Common traumas to the skeletal system are bone fractures and injury-related articular cartilage damage. The healing process can be impaired resulting in non-unions in 5-10% of the bone fractures and in post-traumatic osteoarthritis (PTOA) in up to 75% of the cases of cartilage damage. Despite the amount of research performed in the areas of fracture healing and cartilage repair as well as non-unions and PTOA, still, the outcome of a bone fracture or articular cartilage damage cannot be predicted. Here, we discuss known risk factors and key molecules involved in the repair process, together with the main challenges associated with the prediction of outcome of these injuries. Furthermore, we review and discuss the opportunities for mass spectrometry (MS) - an analytical tool capable of detecting a wide variety of molecules in tissues - to contribute to extending molecular understanding of impaired healing and the discovery of predictive biomarkers. Therefore, the current knowledge and challenges concerning MS imaging of bone and cartilage tissue as well as in vivo MS are discussed. Finally, we explore the possibilities of in situ, real-time MS for the prediction of outcome during surgery of bone fractures and injury-related articular cartilage damage.

Tissue classification by rapid evaporative ionization mass spectrometry (REIMS): comparison between a diathermic knife and CO2 laser sampling on classification performance.

The increasing need for rapid, in situ, and robust tissue profiling approaches in the context of intraoperative diagnostics has led to the development of a large number of ambient ionization-based surface sampling strategies. This paper compares the performances of a diathermic knife and a CO2 laser handpiece, both clinically approved, coupled to a rapid evaporative ionization mass spectrometry (REIMS) source for quasi-instantaneous tissue classification. Several fresh meat samples (muscle, liver, bone, bone marrow, cartilage, skin, fat) were obtained from different animals. Overall, the laser produced cleaner cuts and more reproducible and higher spectral quality signals when compared with the diathermic knife (CV laser = 9-12%, CV diathermic = 14-23%). The molecular profiles were subsequently entered into a database and PCA/LDA classification/prediction models were built to assess if the data generated with one sampling modality can be employed to classify the data generated with the other handpiece. We demonstrate that the correct classification rate of the models increases (+ 25%) with the introduction of a model based on peak lists that are tissue-specific and common to the two handpieces, compared with considering solely the whole molecular profile. This renders it possible to use a unique and universal database for quasi-instantaneous tissue recognition which would provide similar classification results independent of the handpiece used. Furthermore, the laser was able to generate aerosols rich in lipids from hard tissues such as bone, bone marrow, and cartilage. Combined, these results demonstrate that REIMS is a valuable and versatile tool for instantaneous identification/classification of hard tissue and coupling to different aerosol-generating handpieces expands its field of application. Graphical abstract.

Reshaping Lipid Biochemistry by Pushing Barriers in Structural Lipidomics.

Lipidomics is a rapidly growing field with numerous examples showing the importance of lipid molecules throughout biology. It has also shed light onto the vast and complex functions performed by many lipids that possess an immense diversity in molecular structures. Mass spectrometry (MS) is the tool of choice for analyzing lipids and has been the key catalyst driving the field forward. However, MS does not yet permit true molecular lipidomics wherein the identification and quantification of lipids having defined molecular structures can be routinely achieved. Here we describe recent advances in MS-based lipidomics that allow access to higher levels of molecular information in lipidomics experiments. These advances will form a key piece of the puzzle as the field moves towards systems characterization of lipids at the molecular level.

Targeted Drug and Metabolite Imaging: Desorption Electrospray Ionization Combined with Triple Quadrupole Mass Spectrometry.

Mass spectrometry imaging (MSI) has proven to be a valuable tool for drug and metabolite imaging in pharmaceutical toxicology studies and can reveal, for example, accumulation of drug candidates in early drug development. However, the lack of sample cleanup and chromatographic separation can hamper the analysis due to isobaric interferences. Multiple reaction monitoring (MRM) uses unique precursor ion-product ion transitions to add specificity which leads to higher selectivity. Here, we present a targeted imaging platform where desorption electrospray ionization is combined with a triple quadrupole (QqQ) system to perform MRM imaging. The platform was applied to visualize (i) lipids in mouse brain tissue sections and (ii) a drug candidate and metabolite in canine liver tissue. All QqQ modes were investigated to show the increased detection time provided by MRM as well as the possibility to perform dual polarity imaging. This is very beneficial for lipid imaging because some phospholipid classes ionize in opposite polarity (e.g., phosphatidylcholine/sphingomyelin in positive ion mode and phosphatidylserine/phosphatidylethanolamine in negative ion mode). Drug and metabolite images were obtained to show its strength in drug distribution studies. Multiple MRM transitions were used to confirm the local presence and selective detection of pharmaceutical compounds.

Mass Spectrometry Imaging and Integration with Other Imaging Modalities for Greater Molecular Understanding of Biological Tissues.

Over the last two decades, mass spectrometry imaging (MSI) has been increasingly employed to investigate the spatial distribution of a wide variety of molecules in complex biological samples. MSI has demonstrated its potential in numerous applications from drug discovery, disease state evaluation through proteomic and/or metabolomic studies. Significant technological and methodological advancements have addressed natural limitations of the techniques, i.e., increased spatial resolution, increased detection sensitivity especially for large molecules, higher throughput analysis and data management. One of the next major evolutions of MSI is linked to the introduction of imaging mass cytometry (IMC). IMC is a multiplexed method for tissue phenotyping, imaging signalling pathway or cell marker assessment, at sub-cellular resolution (1 µm). It uses MSI to simultaneously detect and quantify up to 30 different antibodies within a tissue section. The combination of MSI with other molecular imaging techniques can also provide highly relevant complementary information to explore new scientific fields. Traditionally, classical histology (especially haematoxylin and eosin-stained sections) is overlaid with molecular profiles obtained by MSI. Thus, MSI-based molecular histology provides a snapshot of a tissue microenvironment and enables the correlation of drugs, metabolites, lipids, peptides or proteins with histological/pathological features or tissue substructures. Recently, many examples combining MSI with other imaging modalities such as fluorescence, confocal Raman spectroscopy and MRI have emerged. For instance, brain pathophysiology has been studied using both MRI and MSI, establishing correlations between in and ex vivo molecular imaging techniques. Endogenous metabolite and small peptide modulation were evaluated depending on disease state. Here, we review advanced 'hot topics' in MSI development and explore the combination of MSI with established molecular imaging techniques to improve our understanding of biological and pathophysiological processes.