Brain Tumor Tissue Research Articles

Toward standardized brain tumor tissue processing protocols in neuro-oncology: a perspective for gliomas and beyond.

Implementation of standardized protocols in neurooncology during the surgical resection of brain tumors is needed to advance the clinical treatment paradigms that use tissue for diagnosis, prognosis, bio-banking, and treatment. Currently recommendations on intraoperative tissue procurement only exist for diffuse gliomas but management of other brain tumor subtypes can also benefit from these protocols. Fresh tissue from surgical resection can now be used for intraoperative diagnostics and functional precision medicine assays. A multidisciplinary neuro-oncology perspective is critical to develop the best avenues for practical standardization. This perspective from the multidisciplinary Oncology Tissue Advisory Board (OTAB) discusses current advances, future directions, and the imperative of adopting standardized protocols for diverse brain tumor entities. There is a growing need for consistent operating room practices to enhance patient care, streamline research efforts, and optimize outcomes.

Development of microsurgical forceps equipped with haptic technology for in situ differentiation of brain tumors during microsurgery

The stiffness of human cancers may be correlated with their pathology, and can be used as a biomarker for diagnosis, malignancy prediction, molecular expression, and postoperative complications. Neurosurgeons perform tumor resection based on tactile sensations. However, it takes years of surgical experience to appropriately distinguish brain tumors from surrounding parenchymal tissue. Haptics is a technology related to the touch sensation. Haptic technology can amplify, transmit, record, and reproduce real sensations, and the physical properties (e.g., stiffness) of an object can be quantified. In the present study, glioblastoma (SF126-firefly luciferase-mCherry [FmC], U87-FmC, U251-FmC) and malignant meningioma (IOMM-Lee-FmC, HKBMM-FmC) cell lines were transplanted into nude mice, and the stiffness of tumors and normal brain tissues were measured using our newly developed surgical forceps equipped with haptic technology. We found that all five brain tumor tissues were stiffer than normal brain tissue (p < 0.001), and that brain tumor pathology (three types of glioblastomas, two types of malignant meningioma) was significantly stiffer than normal brain tissue (p < 0.001 for all). Our findings suggest that tissue stiffness may be a useful marker to distinguish brain tumors from surrounding parenchymal tissue during microsurgery, and that haptic forceps may help neurosurgeons to sense minute changes in tissue stiffness.

An attempt to identify brain tumour tissue in neurosurgery by mechanical indentation measurements

BackgroundThe intraoperative differentiation between tumour tissue, healthy brain tissue, and any sensitive structure of the central nervous system is carried out in modern neurosurgery using various multimodal technologies such as neuronavigation, fluorescent dyes, intraoperative ultrasound or the use of intraoperative MRI, but also the haptic experience of the neurosurgeon. Supporting the surgeon by developing instruments with integrated haptics could provide a further objective dimension in the intraoperative recognition of healthy and diseased tissue.MethodsIn this study, we describe intraoperative mechanical indentation measurements of human brain tissue samples of different tumours taken during neurosurgical operation and measured directly in the operating theatre, in a time frame of maximum five minutes. We present an overview of the Young’s modulus for the different brain tumour entities and potentially differentiation between them.ResultsWe examined 238 samples of 75 tumour removals. Neither a clear distinction of tumour tissue against healthy brain tissue, nor differentiation of different tumour entities was possible on solely the Young’s modulus. Correlation between the stiffness grading of the surgeon and our measurements could be found.ConclusionThe mechanical behaviour of brain tumours given by the measured Young’s modulus corresponds well to the stiffness assessment of the neurosurgeon and can be a great tool for further information on mechanical characteristics of brain tumour tissue. Nevertheless, our findings imply that the information gained through indentation is limited.

Study of the Histological Features of the Stroma of High-Grade Gliomas Depending on the Status of the Mutation in the IDH1 Gene

High-grade gliomas are known for their aggressive nature and resistance to therapy. One characteristic feature of these tumors is the lack of a clear border between the tumor and normal brain tissue. Previous studies have shown that as gliomas dedifferentiate, the extracellular matrix (ECM) undergoes changes in its composition and architecture. This is due to increased production and overexpression of ECM components such as hyaluronic acid, fibulin-3, and collagen. However, it is not yet known what specific changes occur in the stroma of high-grade gliomas depending on the v in the IDH1 gene. In our study, we examined tumor tissue samples from 31 patients, 10 of whom had verified IDH-mutant astrocytoma (grade 4) and 21 had IDH-wildtype glioblastoma (grade 4). The presence or absence of mutations in the IDH1/2 genes was determined in all patients using immunohistochemistry (IHC) and polymerase chain reaction (PCR). To assess stromal changes, we used histochemical staining with Alcian blue and Mallory trichrome. Our results showed significant differences between the two groups according to Student’s t-test (p &lt; 0.05) for all stainings. The presence of mucus formation, collagen formation, and expression of vimentin by tumor cells in the stroma of IDH-wildtype grade 4 glioblastoma indicates an active epithelial-mesenchymal transition and changes in the extracellular matrix. These findings may explain the more unfavorable prognosis in patients with glioblastomas and could potentially serve as a therapeutic target in the complex treatment of malignant gliomas.

Self-Supervised Image Denoising of Third Harmonic Generation Microscopic Images of Human Glioma Tissue by Transformer-Based Blind Spot (TBS) Network.

Third harmonic generation (THG) microscopy shows great potential for instant pathology of brain tumor tissue during surgery. However, due to the maximal permitted exposure of laser intensity and inherent noise of the imaging system, the noise level of THG images is relatively high, which affects subsequent feature extraction analysis. Denoising THG images is challenging for modern deep-learning based methods because of the rich morphologies contained and the difficulty in obtaining the noise-free counterparts. To address this, in this work, we propose an unsupervised deep-learning network for denoising of THG images which combines a self-supervised blind spot method and a U-shape Transformer using a dynamic sparse attention mechanism. The experimental results on THG images of human glioma tissue show that our approach exhibits superior denoising performance qualitatively and quantitatively compared with previous methods. Our model achieves an improvement of 2.47-9.50 dB in SNR and 0.37-7.40 dB in CNR, compared to six recent state-of-the-art unsupervised learning models including Neighbor2Neighbor, Blind2Unblind, Self2Self+, ZS-N2N, Noise2Info and SDAP. To achieve an objective evaluation of our model, we also validate our model on public datasets including natural and microscopic images, and our model shows a better denoising performance than several recent unsupervised models such as Neighbor2Neighbor, Blind2Unblind and ZS-N2N. In addition, our model is nearly instant in denoising a THG image, which has the potential for real-time applications of THG microscopy.

Direct and Rapid Visualization of the Spatial Distribution of Cholesterol in Alzheimer's and Cancer Tissue via MALDI Mass Spectrometry Imaging.

Cholesterol is a vital component of the central nervous system and tissues, and understanding its spatial distribution is crucial for biology, pathophysiology, and diagnostics. However, direct imaging of cholesterol using matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI-MSI) remains challenging and time-consuming due to the difficulty in ionizing the sterol molecule. To tackle this issue, a MALDI-MSI method is established for direct and rapid analysis of the spatial distribution of cholesterol in Alzheimer's disease (AD), different cancer tissues and organs via MALDI-MSI. This excellent imaging performance depends on the study and systemic optimization of various conditions that affect the imaging of MALDI-MSI. In this case, we report the distribution and levels of cholesterol across specific structures of the AD mouse brain and different tumor tissue and organs. According to the results, the content of cholesterol in the AD mouse cerebellum, especially in the arborvitae, was significantly higher than that in the wild type (WT) model. Furthermore, we successfully visualize the distribution of cholesterol in other organs, such as the heart, liver, spleen, kidney, pancreas, as well as tumor tissues parenchyma and interstitium using MALDI-MSI. Notably, the attribution of cholesterol MS/MS hydrocarbon fragments was systematically investigated. Our presented optimization strategy and established MALDI-MSI method can be easily generalized for different animal tissues or live samples, thereby facilitating the potential for applications of MALDI-MSI in clinical, medical and biological research.

Near-infrared II fluorescence-guided glioblastoma surgery targeting monocarboxylate transporter 4 combined with photothermal therapy

Surgery is crucial for glioma treatment, but achieving complete tumour removal remains challenging. We evaluated the effectiveness of a probe targeting monocarboxylate transporter 4 (MCT4) in recognising gliomas, and of near-infrared window II (NIR-II) fluorescent molecular imaging and photothermal therapy as treatment strategies. We combined an MCT4-specific monoclonal antibody with indocyanine green to create the probe. An orthotopic mouse model and a transwell model were used to evaluate its ability to guide tumour resection using NIR-II fluorescence and to penetrate the blood-brain barrier (BBB), respectively. A subcutaneous tumour model was established to confirm photothermal therapy efficacy. Probe specificity was assessed in brain tissue from mice and humans. Finally, probe effectiveness in photothermal therapy was investigated. MCT4 was differentially expressed in tumour and normal brain tissue. The designed probe exhibited precise tumour targeting. Tumour imaging was precise, with a signal-to-background (SBR) ratio of 2.8. Residual tumour cells were absent from brain tissue postoperatively (SBR: 6.3). The probe exhibited robust penetration of the BBB. Moreover, the probe increased the tumour temperature to 50°C within 5min of laser excitation. Photothermal therapy significantly reduced tumour volume and extended survival time in mice without damage to vital organs. These findings highlight the potential efficacy of our probe for fluorescence-guided surgery and therapeutic interventions. Jilin Province Department of Science and Technology (20200403079SF), Department of Finance (2021SCZ06) and Development and Reform Commission (20200601002JC); National Natural Science Foundation of China (92059207, 92359301, 62027901, 81930053, 81227901, U21A20386); and CAS Youth Interdisciplinary Team (JCTD-2021-08).

Size-Dependent Glioblastoma Targeting by Polymeric Nanoruler with Prolonged Blood Circulation.

Currently, there is no effective treatment for glioblastoma multiforme (GBM), the most frequent and malignant type of brain tumor. The blood-brain (tumor) barrier (BB(T)B), which is composed of tightly connected endothelial cells and pericytes (with partial vasculature collapse), hampers nanomedicine accumulation in tumor tissues. We aimed to explore the effect of nanomedicine size on passive targeting of GBM. A series of size-tunable poly(ethylene glycol) (PEG)-grafted copolymers (gPEGs) were constructed with hydrodynamic diameters of 8-30 nm. Biodistribution studies using orthotopic brain tumor-bearing mice revealed that gPEG brain tumor accumulation was maximized at 10 nm with ∼14 dose %/g of tumor, which was 19 times higher than that in the normal brain region and 4.2 times higher than that of 30-nm gPEG. Notably, 10-nm gPEG exhibited substantially higher brain tumor accumulation than 11-nm linear PEG owing to the prolonged blood circulation property of gPEGs, which is derived from a densely PEG-packed structure. 10 nm gPEG exhibited deeper penetration into the brain tumor tissue than the larger gPEGs did (>10 nm). This study demonstrates, for the first time, the great potential of a nanomedicine downsizing strategy for passive GBM targeting.

A COMPUTER-AIDED BRAIN GLIOMA IDENTIFICATION USING MRI BASED TEXTURE ANALYSIS

Brain gliomas are deadly tumors that are discovered after a stressful, lengthy, and difficult procedure. Radiology is a broad and varied field that detects brain tumors, but interpreting radiological pictures of the brain needs advanced training, experience, and subject-matter expertise. The endeavor is challenging due to the wide variation in brain tumor tissues among individuals and similar cases within normal tissues. Magnetic resonance imaging (MRI)-based computer-aided biomedical image processing solves the challenges associated with brain tumor localization and identification while simultaneously addressing the shortage of qualified radiologists. This study proposes a computer-aided brain glioma identification (CABGD) model for brain glioma identification using the texture analysis of brain MRIs. The proposed model makes use of machine learning classifiers and brain MRI data. There were 200 MRIs of both normal and glioma brains in the experimental dataset. Firstly, the MRI dataset was pre-processed to crop the MRIs, size equalization, and gray-level conversion. Next, noises were removed by applying filters. Two ROIs of the sizes (10 ×10) were taken on each MRI after the tumor region was segmented. After extracting COM texture features from each ROI, thirty optimal features were obtained through a compound supervised feature selection, blend of Fisher (FSHR), probabilistic model of error (POE), average correlation (AVC), and mutual information (MUI). The optimal feature brain MRI dataset was classified into glioma and normal brain by applying machine learning classifiers named Bayas Net (BN), logistic model tree (LMT), and partial decision tree (PART); the classification results of the NB, LMT, and PART classifiers were 79.75%, 82.75, and 85%, respectively.

EPEN-18. MULTI-OMICS APPROACH REVEALED A TIGHT BLOOD-BRAIN BARRIER IN EPENDYMOMA

Abstract BACKGROUND A major challenge in the treatment of brain tumors is the limited penetration of many drugs through the blood-brain barrier (BBB). BBB characteristics include endothelial cells connected by tight junction proteins (e.g. Claudin5, ZO1, occludin) and the expression of efflux transporters (e.g. P-gp) with the physiological role to limit the accumulation of potentially toxic substances in brain tissue. Our study aims to enhance our understanding of the BBB composition across different molecular groups of ependymoma (EPN) with the goal of leveraging this knowledge to improve therapeutic strategies against these tumors. METHODS We applied a multi-omics approach integrating single-nuclear RNA sequencing and ultra-high content imaging to unravel BBB composition at both transcriptomic and proteomic levels. Patient-derived xenograft (PDX) models were utilized to explore differences in BBB penetration between tumor and healthy brain tissue following drug treatments. RESULTS Expression of tight junction and transporter proteins revealed strong dependencies specific to molecular groups, but were independent of the corresponding brain regions. Human tissue of ST-EPN-ZFTA exhibited highest expression of claudin5, while both ST-EPN-ZFTA and PF-EPN-A represented upregulation of occludin and ZO1 in comparison to healthy tissue. These findings on claudin5 and ZO1 were further confirmed in PDX models. Single-cell data analysis from patients localized the expression of relevant BBB factors to tumor-associated endothelial cells. Treatment of PDX models with drugs revealed disparities in drug penetration between EPN tumors and healthy brain regions. Notably, for most drugs BBB penetration was lower in ST-EPN-ZFTA tumors than healthy brain region. CONCLUSIONS Molecular BBB specifics may contribute to drug resistance of aggressive EPN particularly in ST-EPN-ZFTA tumors, which presented high tight junction expressions and lower drug penetration. This resource aims to improve BBB penetration prediction in EPN, to identify combination therapies targeting BBB components and to select innovative drug delivery approaches.

Advances in Hydrogels of Drug Delivery Systems for the Local Treatment of Brain Tumors.

The management of brain tumors presents numerous challenges, despite the employment of multimodal therapies including surgical intervention, radiotherapy, chemotherapy, and immunotherapy. Owing to the distinct location of brain tumors and the presence of the blood-brain barrier (BBB), these tumors exhibit considerable heterogeneity and invasiveness at the histological level. Recent advancements in hydrogel research for the local treatment of brain tumors have sought to overcome the primary challenge of delivering therapeutics past the BBB, thereby ensuring efficient accumulation within brain tumor tissues. This article elaborates on various hydrogel-based delivery vectors, examining their efficacy in the local treatment of brain tumors. Additionally, it reviews the fundamental principles involved in designing intelligent hydrogels that can circumvent the BBB and penetrate larger tumor areas, thereby facilitating precise, controlled drug release. Hydrogel-based drug delivery systems (DDSs) are posited to offer a groundbreaking approach to addressing the challenges and limitations inherent in traditional oncological therapies, which are significantly impeded by the unique structural and pathological characteristics of brain tumors.

A phase (Ph) 0/Ia study of brigimadlin concentration in brain tissue and a non-randomized, open-label, dose escalation study of brigimadlin in combination with radiotherapy (RT) in patients (pts) with newly diagnosed glioblastoma (GBM).

2017 Background: MDM2 inhibits tumor suppressor p53. Brigimadlin, a potent MDM2–p53 antagonist, restores wild-type (wt) p53 function and has shown early efficacy in pts with solid tumors (LoRusso et al Cancer Disc 2023). GBM is an area of unmet need with 5-year survival &lt;10%. In p53 wt GBM pt-derived xenograft models, brigimadlin promotes tumor cell apoptosis and extends survival in combination with RT. Methods: NCT05376800 is a Ph 0/Ia open-label, single-arm trial that aims to measure brigimadlin concentration in brain tumor tissue in pts with histologically or radiologically newly diagnosed GBM eligible for resection (Ph 0) and determine the maximum tolerated dose of brigimadlin plus RT in pts with TP53wt, IDH wt, MGMT promoter unmethylated GBM (Ph Ia). In Ph 0, pts received one brigimadlin dose (30 mg or 45 mg) ~12–24 h before resection. Ph 0 primary endpoints are the measured total concentration and the calculated unbound concentration of brigimadlin in brain tissue homogenate from non-contrast enhancing (NCE) and contrast enhancing (CE) regions. The predefined threshold for trial continuation is 0.5 nmol/L (corresponding to IC50 in GBM cell lines) unbound brigimadlin in CE samples in ≥50% of pts. Brigimadlin concentration was measured using LC/MS and corrected for amount of brigimadlin in residual blood. Unbound concentration was calculated using an in vitro estimate of unbound fraction (fu): 0.654% (rat brain slice). fu in human plasma was 0.22%. Kp,uu (ratio of unbound concentration in brain vs plasma) was calculated. Biomarker testing was performed. Results: Data are available for 11 pts (brigimadlin 30 mg: n=6; 45 mg: n=5). In the 30 mg group, median total brigimadlin concentration in NCE samples was 267 nmol/L (4 samples, range 86–316 nmol/L) and 332 nmol/L (6 samples, range 272–952 nmol/L) in CE samples. In the 45 mg group, median total brigimadlin concentration in NCE samples was 197 nmol/L (5 samples, range 140–347 nmol/L) and 603 nmol/L (5 samples, range 441–905 nmol/L) in CE samples. Unbound concentration exceeded the 0.5 nmol/L threshold in most cases (Table). Post-brigimadlin, an increase in selected p53 target gene expression was observed in CE vs NCE tissue. Conclusions: Unbound brigimadlin concentrations in CE regions in all pts receiving the low dose of 30 mg brigimadlin exceeded the 0.5 nmol/L threshold. Kp,uu in most patients was close to 1 in CE regions. Biomarker data support target engagement in brain tissue. Our findings support continued investigation of brigimadlin in GBM. Recruitment is ongoing. Updated data will be presented. Clinical trial information: NCT05376800 . [Table: see text]

Expression and prognostic significance of microsomal triglyceride transfer protein in brain tumors: a retrospective cohort study.

Glioblastoma (GBM) is the most common malignant brain tumor and has poor survival. An elevated cholesterol level is involved occurrence and progression of brain tumors. Microsomal triglyceride transfer protein (MTTP) is a target for lowering lipids, and its inhibition helps to improve hyperlipidemia. However, whether the altered expression of MTTP affects the development and prognosis of brain tumors is currently unidentified. The purpose of this study is to determine MTTP as a prognostic marker for brain tumors. Data for patients with brain cancers and control brain tissue were acquired from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO). The datasets were analyzed using Mann-Whitney U-test or t-test to compare the expression of MTTP in normal and brain tumor tissues. To examine whether MTTP affected the prognosis of patients with brain tumors, log-rank test and multivariable Cox proportional hazard regression were conducted. The expression of MTTP was significantly upregulated in brain tumors and was correlated with age, tumor stage, and isocitrate dehydrogenase (IDH) mutation. Importantly, increased MTTP expression in brain tumors is associated with poor patient survival. High MTTP expression is associated with brain tumor development, tumor stage, and prognosis. Therefore, MTTP is an independent prognostic indicator for brain tumors, which can serve as one of the possible targets for adjuvant treatment of GBM.

Charge-switchable cell-penetrating peptides for rerouting nanoparticles to glioblastoma treatment

Glioblastoma (GB) is one of the most lethal types of neoplasms with unique anatomic, physiologic, and pathologic features that usually persist after exposure to standard therapeutic modalities. It is biologically aggressive, and the existence of the blood-brain barrier (BBB) limits the efficacy of standard therapies. In this work, we hypothesize the potential of surface-functionalized ultra-small nanostructured lipid carriers (usNLCs) with charge-switchable cell-penetrating peptides (CPPs) to overcome this biological barrier and improve targeted delivery to brain tumor tissues. The big question is: what is the potential of CPPs in directing nanoparticles toward brain tumor tissue? To answer this question, the usNLCs were functionalized with distinct biomolecules [five CPPs, c(RGDfK) and transferrin, Tf] through electrostatic interaction and its ability as a targeting approach to BBB (HBMEC) and glioma cells (U87 cells) evaluated in terms of physicochemical properties, cellular uptake, permeability in a 2D-BBB model, and tumor growth inhibition. Monte Carlo simulations elucidated CPP adsorption patterns. The permeability studies revealed that targeted usNLCs, especially usNLCsTf and usNLCsCPP4, exhibited an increased permeability coefficient compared to the non-targeted usNLCs. Functionalized usNLCs evidenced enhanced uptake in BBB cells, with smaller CPPs showing higher internalization (CPP1 and CPP2). Similarly, functionalized usNLCs exhibited more significant cytotoxicity in glioma cells, with specific CPPs promoting favorable internalization. Analysis of the endocytic pathway indicated that usNLCsCPPs were mainly internalized by direct translocation and caveolae-mediated endocytosis. Optimal usNLCs with dual targeting capabilities to both BBB and GB cells provide a promising therapeutic strategy for GB.

Magnet-Guided Temozolomide and Ferucarbotran Loaded Nanoparticles to Enhance Therapeutic Efficacy in Glioma Model.

Background. The aim of the study was to synthesize liposomal nanoparticles loaded with temozolomide and ferucarbotran (LTF) and to evaluate the theranostic effect of LTF in the glioma model. Methods. We synthesized an LTF that could pass through the Blood Brain Barrier (BBB) and localize in brain tumor tissue with the help of magnet guidance. We examined the chemical characteristics. Cellular uptake and cytotoxicity studies were conducted in vitro. A biodistribution and tumor inhibition study was conduted using an in vivo glioma model. Results. The particle size and surface charge of LTF show 108 nm and -38 mV, respectively. Additionally, the presence of ferucarbotran significantly increased the contrast agent effect of glioma compared to the control group in MR imaging. Magnet-guided LTF significantly reduced the tumor size compared to control and other groups. Furthermore, compared to the control group, our results demonstrate a significant inhibition in brain tumor size and an increase in lifespan. Conclusions. These findings suggest that the LTF with magnetic guidance represents a novel approach to address current obstacles, such as BBB penetration of nanoparticles and drug resistance. Magnet-guided LTF is able to enhance therapeutic efficacy in mouse brain glioma.

2D 1H sLASER Long-TE and 3D 31P Chemical Shift Imaging at 3 T for Monitoring Fasting-Induced Changes in Brain Tumor Tissue.

Emerging evidence suggests that fasting could play a key role in cancer treatment. Its metabolic effects on gliomas require further investigation. To design a multi-voxel 1H/31P MR-spectroscopic imaging (MRSI) protocol for noninvasive metabolic monitoring of cerebral, fasting-induced changes on an individual patient/tumor level, and to assess its technical reliability/reproducibility. Prospective. MRS phantom. Twenty-two patients (mean age = 61, 6 female) with suspected WHO grade II-IV glioma examined before and after 72-hour-fasting prior to biopsy/resection. 3-T, 1H decoupled 3D 31P MRSI, 2D 1H sLASER MRSI at an echo time of 144 msec, 2D 1H MRSI (as water reference), T1-weighted, T1-weighted contrast-enhanced, T2-weighted, and FLAIR. sLASER and PRESS sequences were used for phantom measurements. Phantom measurements and spectral simulations were performed with various echo-times for protocol optimization. In vivo spectral analyses were conducted using LCModel and AMARES, obtaining quality/fitting parameters (linewidth, signal-to-noise-ratio, and uncertainty measures of fitting) and metabolite intensities. The volume of glioma sub-regions was calculated and correlated with MRS findings. Ex-vivo spectra of necrotic tumor tissues were obtained using high-resolution magic-angle spinning (HR-MAS) technique. Wilcoxon signed-rank test, Bland-Altman plots, and coefficient of variation were used for repeatability analysis of quality/fitting parameters and metabolite concentrations. Spearman ρ correlation for the concentration of ketone bodies with volumes of glioma sub-regions was determined. A P-value <0.05 was considered statistically significant. 1H and 31P repeatability measures were highly consistent between the two sessions. β-hydroxybutyrate and acetoacetate were detectable (fitting-uncertainty <50%) in glioma sub-regions of all patients who completed the 72-hour-fasting cycle. β-hydroxybutyrate accumulation was significantly correlated with the necrotic/non-enhancing tumor core volume (ρ = 0.81) and validated using ex-vivo 1H HR-MAS. We propose a comprehensive MRS protocol that may be used for monitoring cerebral, fasting-induced changes in patients with glioma. 1 TECHNICAL EFFICACY: Stage 4.

Microscope-integrated optical coherence tomography for in vivo human brain tumor detection with artificial intelligence.

It has been shown that optical coherence tomography (OCT) can identify brain tumor tissue and potentially be used for intraoperative margin diagnostics. However, there is limited evidence on its use in human in vivo settings, particularly in terms of its applicability and accuracy of residual brain tumor detection (RTD). For this reason, a microscope-integrated OCT system was examined to determine in vivo feasibility of RTD after resection with automated scan analysis. Healthy and diseased brain was 3D scanned at the resection edge in 18 brain tumor patients and investigated for its informative value in regard to intraoperative tissue classification. Biopsies were taken at these locations and labeled by a neuropathologist for further analysis as ground truth. Optical OCT properties were obtained, compared, and used for separation with machine learning. In addition, two artificial intelligence-assisted methods were utilized for scan classification, and all approaches were examined for RTD accuracy and compared to standard techniques. In vivo OCT tissue scanning was feasible and easily integrable into the surgical workflow. Measured backscattered light signal intensity, signal attenuation, and signal homogeneity were significantly distinctive in the comparison of scanned white matter to increasing levels of scanned tumor infiltration (p < 0.001) and achieved high values of accuracy (85%) for the detection of diseased brain in the tumor margin with support vector machine separation. A neuronal network approach achieved 82% accuracy and an autoencoder approach 85% accuracy in the detection of diseased brain in the tumor margin. Differentiating cortical gray matter from tumor tissue was not technically feasible in vivo. In vivo OCT scanning of the human brain has been shown to contain significant value for intraoperative RTD, supporting what has previously been discussed for ex vivo OCT brain tumor scanning, with the perspective of complementing current intraoperative methods for this purpose, especially when deciding to withdraw from further resection toward the end of the surgery.

The Role of Selected Matrix Metalloproteinases in the Pathogenesis of Gliomas

Abstract The progression of tumor formation is a multifactorial process that involves changes at different levels. Within this intricate molecular and cellular landscape of tumorigenesis, specific enzymes, namely matrix metalloproteinases (MMPs), emerge as pivotal contributors. They may influence this process at the level of tissue remodelling, angiogenesis, changes in cell signalling, invasion and metastasis, but may also serve as prognostic markers or therapeutic targets. Although the function of MMPs has been known for a long time, their specific role in the pathogenesis of brain tumors has only begun to be investigated in the last three decades. Deregulation of MMPs expression, frequently observed in brain tumor tissue, is associated with malignant phenotype, dependent on the grade of malignancy and associated with a worse prognosis. They participate in tissue remodelling under physiological and pathological conditions, which predetermines their action especially in the process of invasion and migration of tumor cells into the surrounding tissue. Related to their potential in tumor progression, they are also being investigated as possible targets in anticancer therapy. It would be very difficult to characterize in detail the role of all known MMPs in the context of brain tumor pathogenesis, so we have selected those that have an essential effect in this issue.

Loss of methylthioadenosine phosphorylase immunoreactivity correlates with poor prognosis and elevated uptake of 11C-methionine in IDH-mutant astrocytoma.

The proximate localization of MTAP, which encodes methylthioadenosine phosphorylase, and CDKN2A/B on Chromosome 9q21 has allowed the loss of MTAP expression as a surrogate for homozygous deletion of CDKN2A/B. This study aimed to determine whether MTAP status correlates with clinical outcomes and 11C-methionine uptake in astrocytomas with IDH mutations. We conducted immunohistochemistry for MTAP in 30 patients with astrocytoma, IDH-mutant who underwent 11C-methionine positron emission tomography scans prior to surgical resection. The tumor-to-normal (T/N) ratio of 11C-methionine uptake was calculated using the mean standardized uptake value (SUV) for tumor and normal brain tissues. Cox regression analysis was used for multivariate survival analysis. Among IDH-mutant astrocytomas, 26.7% (8/30) exhibited the loss of cytoplasmic MTAP expression, whereas 73.3% (22/30) tumors retained MTAP expression. The median progression-free survival (PFS) was significantly shorter in patients with MTAP loss than those with MTAP retention (1.88years vs. 6.80years, p = 0.003). The median overall survival (OS) was also shorter in patients with MTAP loss than in MTAP-retaining counterparts (5.23years vs. 10.69years, p = 0.019). Multivariate analysis identified MTAP status (hazard ratio (HR), 0.081) and extent of resection (HR, 0.104) as independent prognostic factors for PFS. Astrocytomas lacking cytoplasmic MTAP expression showed a significantly higher median T/N ratio for 11C-methionine uptake than tumors retaining MTAP (2.12 vs. 1.65, p = 0.012). Our study revealed that the loss of MTAP expression correlates with poor prognosis and an elevated T/N ratio of 11C-methionine uptake in astrocytoma, IDH-mutant.

506 Deep Learning-Based Image-to-Image Translation to Identify Macrophage Infiltration in High-Grade Glioma Using Label-Free Stimulated Raman Histology

INTRODUCTION: 5-Aminolevulinic acid (5-ALA) is the most widely used fluorophore in image-guided glioma surgery, and previous work at our institution demonstrated that 5-ALA highlights tumor-associated macrophages (TAMs) in two-photon microscopy images of brain tumor tissue. Using a unique, paired dataset of stimulated Raman histology (SRH) and two-photon images that share one-to-one spatial resolution, we propose a deep-learning approach to identify macrophages from intraoperative SRH images without requiring fluorescent labels. METHODS: We compiled a dataset of 9,554 non-overlapping, 300-by-300 pixel fields of view from paired SRH and two-photon images representing 40 cases of high-grade glioma. A deep generative adversarial network (pix2pix), consisting of a U-Net generator and PatchGAN discriminator, was trained to generate synthetic two-photon images from each SRH patch. The model was trained for 200 epochs, and similarity between the synthetic and real distributions was assessed qualitatively while training and quantitatively using FrÉchet inception distance (FID). RESULTS: Our model was successfully trained to generate synthetic two-photon images nearly indistinguishable from ground truth examples. The FID between a held-out test set of real and synthetic images was 8.58, compared to a mean FID of 9.26 ± 0.24 between randomly sampled sets of real images. Our model consistently inferred the location of brightly fluorescing TAMs in held-out, previously unseen test images. CONCLUSIONS: We used deep learning to visualize TAMs in label-free SRH images. Analysis of TAM infiltration has the potential to identify patients most likely to benefit from immunotherapy clinical trials. Ongoing work will leverage additional deep-learning approaches to automatically identify and quantify TAM infiltration with SRH, enabling rapid patient-specific analysis of the glioma immune microenvironment.