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A growing body of evidence has revealed the potential utility of 5-aminolevulinic acid (5-ALA) as a surgical adjunct in selected lower-grade gliomas. However, a reliable means of identifying which lower-grade gliomas will fluoresce has not been established.To identify clinical and radiological factors predictive of intraoperative fluorescence in intermediate-grade gliomas. In addition, given that higher-grade gliomas are more likely to fluoresce than lower-grade gliomas, we also sought to develop a means of predicting glioma grade.We investigated a cohort of patients with grade II and grade III gliomas who received 5-ALA before resection at a single institution. Using a logistic regression-based model, we evaluated 14 clinical and molecular variables considered plausible determinants of fluorescence. We then distilled the most predictive features to develop a model for predicting both fluorescence and tumor grade. We also explored the relationship between intraoperative fluorescence and diagnostic molecular markers.One hundered seventy-nine subjects were eligible for inclusion. Our logistic regression classifier accurately predicted intraoperative fluorescence in our cohort with 91.9% accuracy and revealed enhancement as the singular variable in determining intraoperative fluorescence. There was a direct relationship between enhancement on MRI and the likelihood of observed fluorescence. Observed fluorescence correlated with MIB-1 index but not with isocitrate dehydrogenase (IDH) status, 1p19q codeletion, or methylguanine DNA methyltransferase promoter methylation.We demonstrate a strong correlation between enhancement on preoperative MRI and the likelihood of visible fluorescence during surgery in patients with intermediate-grade glioma. Our analysis provides a robust method for predicting 5-ALA-induced fluorescence in patients with grade II and grade III gliomas.

Descriptive statistics of patient population

Random forest model 2. A) Example decision tree from random forest model 2. B) Out-of-bag, low-grade, and high-grade tumor classification error across 500 grown decision trees. C) Image feature importance for model 2. Similar to model 1, nuclei density and TAM density are the most important predictors; however, nuclear morphology parameters and detection of anaplasia play a more important predictive role for classifying low-grade and high-grade tumors.

Accurate histopathologic diagnosis is essential for providing optimal surgical management of pediatric brain tumors. Current methods for intraoperative histology are time- and labor-intensive and often introduce artifact that limit interpretation. Stimulated Raman histology (SRH) is a novel label-free imaging technique that provides intraoperative histologic images of fresh, unprocessed surgical specimens. Here we evaluate the capacity of SRH for use in the intraoperative diagnosis of pediatric type brain tumors. SRH revealed key diagnostic features in fresh tissue specimens collected from 33 prospectively enrolled pediatric type brain tumor patients, preserving tumor cytology and histoarchitecture in all specimens. We simulated an intraoperative consultation for 25 patients with specimens imaged using both SRH and standard hematoxylin and eosin histology. SRH-based diagnoses achieved near-perfect diagnostic concordance (Cohen's kappa, κ > 0.90) and an accuracy of 92% to 96%. We then developed a quantitative histologic method using SRH images based on rapid image feature extraction. Nuclear density, tumor-associated macrophage infiltration, and nuclear morphology parameters from 3337 SRH fields of view were used to develop and validate a decision-tree machine-learning model. Using SRH image features, our model correctly classified 25 fresh pediatric type surgical specimens into normal versus lesional tissue and low-grade versus high-grade tumors with 100% accuracy. Our results provide insight into how SRH can deliver rapid diagnostic histologic data that could inform the surgical management of pediatric brain tumors.Significance: A new imaging method simplifies diagnosis and informs decision making during pediatric brain tumor surgery. Cancer Res; 78(1); 278–89. ©2017 AACR.

Random forest model 1. A) Example decision tree from random forest model 1. B) Out-of-bag, normal tissue, and tumor tissue classification error across 500 grown decision trees. C) Image feature importance for model 1.

Pipeline information from CellProfiler feature extraction method

Molecular classification has transformed the management of brain tumors by enabling more accurate prognostication and personalized treatment. However, timely molecular diagnostic testing for patients with brain tumors is limited, complicating surgical and adjuvant treatment and obstructing clinical trial enrollment. In this study, we developed DeepGlioma, a rapid ($< 90$ seconds), artificial-intelligence-based diagnostic screening system to streamline the molecular diagnosis of diffuse gliomas. DeepGlioma is trained using a multimodal dataset that includes stimulated Raman histology (SRH); a rapid, label-free, non-consumptive, optical imaging method; and large-scale, public genomic data. In a prospective, multicenter, international testing cohort of patients with diffuse glioma ($n=153$) who underwent real-time SRH imaging, we demonstrate that DeepGlioma can predict the molecular alterations used by the World Health Organization to define the adult-type diffuse glioma taxonomy (IDH mutation, 1p19q co-deletion and ATRX mutation), achieving a mean molecular classification accuracy of $93.3\pm 1.6\%$. Our results represent how artificial intelligence and optical histology can be used to provide a rapid and scalable adjunct to wet lab methods for the molecular screening of patients with diffuse glioma., Paper published in Nature Medicine

Background Hyperglycemia has been associated with worse survival in glioblastoma. Attempts to lower glucose yielded mixed responses which could be due to molecularly distinct GBM subclasses. Methods Clinical, laboratory, and molecular data on 89 IDH-wt GBMs profiled by clinical next-generation sequencing and treated with Stupp protocol were reviewed. IDH-wt GBMs were sub-classified into RTK I (Proneural), RTK II (Classical) and Mesenchymal subtypes using whole-genome DNA methylation. Average glucose was calculated by time-weighting glucose measurements between diagnosis and last follow-up. Results Patients were stratified into three groups using average glucose: tertile one (115 mg/dL). Comparison across glucose tertiles revealed no differences in performance status (KPS), dexamethasone dose, MGMT methylation, or methylation subclass. Overall survival (OS) was not affected by methylation subclass (P = .9) but decreased with higher glucose (P = .015). Higher glucose tertiles were associated with poorer OS among RTK I (P = .08) and mesenchymal tumors (P = .05), but not RTK II (P = .99). After controlling for age, KPS, dexamethasone, and MGMT status, glucose remained significantly associated with OS (aHR = 5.2, P = .02). Methylation clustering did not identify unique signatures associated with high or low glucose levels. Metabolomic analysis of 23 tumors showed minimal variation across metabolites without differences between molecular subclasses. Conclusion Higher average glucose values were associated with poorer OS in RTKI and Mesenchymal IDH-wt GBM, but not RTKII. There were no discernible epigenetic or metabolomic differences between tumors in different glucose environments, suggesting a potential survival benefit to lowering systemic glucose in selected molecular subtypes.

OBJECTIVE Intraoperative neuropathological assessment with conventional frozen sections supports the neurosurgeon in optimizing the surgical strategy. However, preparation and review of frozen sections can take as long as 45 minutes. Stimulated Raman histology (SRH) was introduced as a novel technique to provide rapid high-resolution digital images of unprocessed tissue samples directly in the operating room that are comparable to conventional histopathological images. Additionally, SRH images are simultaneously and easily accessible for neuropathological judgment. Recently, the first study showed promising results regarding the accuracy and feasibility of SRH compared with conventional histopathology. Thus, the aim of this study was to compare SRH with conventional H&E images and frozen sections in a large cohort of patients with different suspected central nervous system (CNS) tumors. METHODS The authors included patients who underwent resection or stereotactic biopsy of suspected CNS neoplasm, including brain and spinal tumors. Intraoperatively, tissue samples were safely collected and SRH analysis was performed directly in the operating room. To enable optimal comparison of SRH with H&E images and frozen sections, the authors created a digital databank that included images obtained with all 3 imaging modalities. Subsequently, 2 neuropathologists investigated the diagnostic accuracy, tumor cellularity, and presence of diagnostic histopathological characteristics (score 0 [not present] through 3 [excellent]) determined with SRH images and compared these data to those of H&E images and frozen sections, if available. RESULTS In total, 94 patients with various suspected CNS tumors were included, and the application of SRH directly in the operating room was feasible in all cases. The diagnostic accuracy based on SRH images was 99% when compared with the final histopathological diagnosis based on H&E images. Additionally, the same histopathological diagnosis was established in all SRH images (100%) when compared with that of the corresponding frozen sections. Moreover, the authors found a statistically significant correlation in tumor cellularity between SRH images and corresponding H&E images (p < 0.0005 and R = 0.867, Pearson correlation coefficient). Finally, excellent (score 3) or good (2) accordance between diagnostic histopathological characteristics and H&E images was present in 95% of cases. CONCLUSIONS The results of this retrospective analysis demonstrate the near-perfect diagnostic accuracy and capability of visualizing relevant histopathological characteristics with SRH compared with conventional H&E staining and frozen sections. Therefore, digital SRH histopathology seems especially useful for rapid intraoperative investigation to confirm the presence of diagnostic tumor tissue and the precise tumor entity, as well as to rapidly analyze multiple tissue biopsies from the suspected tumor margin. A real-time analysis comparing SRH images and conventional histological images at the time of surgery should be performed as the next step in future studies.

Patients with glioblastoma (GBM) need bold new approaches to their treatment, yet progress has been hindered by a relative inability to dynamically track treatment response, mechanisms of resistance, evolution of targetable mutations, and changes in mutational burden. We are writing on behalf of a multidisciplinary group of academic neuro-oncology professionals who met at the collaborative Christopher Davidson Forum at Washington University in St Louis in the fall of 2019. We propose a dramatic but necessary change to the routine management of patients with GBM to advance the field: to routinely biopsy recurrent GBM at the time of presumed recurrence. Data derived from these samples will identify true recurrence vs treatment effect, avoid treatments with little chance of success, enable clinical trial access, and aid in the scientific advancement of our understanding of GBM.

Image-guided core needle biopsy plays a central role in the diagnosis and management of a wide range of breast lesions. After collection, tissue cylinders are transported from a biopsy suite to a pathology laboratory for analysis. The existing workflow for microscopic diagnosis of tissue specimens precludes the option of using histologic data to inform clinical decision-making at the time of biopsy. Here, we introduce stimulated Raman histology (SRH), a rapid label-free optical imaging method that enables microscopic imaging of unprocessed breast biopsy specimens in the biopsy suite within minutes of sample collection. SRH has been thoroughly validated for use in the detection and diagnosis of brain tumors but its use has not been validated in breast lesions. In our study, we collected core needle biopsy specimens and allocated a 2mm portion of the tissue sample for SRH imaging. Each specimen was imaged with SRH and subsequently fixed in formalin, embedded, stained and sectioned in a conventional manner. A board-certified breast pathologist first analyzed the diagnostic features of the imaged specimens with SRH and then with conventional H&E-stained sections. In a pilot series of six patients, we found that SRH could differentiate between lesions that can mimic cancer such as a radial scar from neoplastic ones like invasive ductal carcinoma. SRH also demonstrated histologic differences between a benign tumor like a fibroadenoma and a malignant tumor like an invasive ductal carcinoma. We also observed diagnostic differences amongst benign processes such as radial scar and pseudoangiomatous stromal hyperplasia. Importantly, we showed that SRH is non-consumptive and the imaged tissue can be used for downstream histologic and immunohistochemical analysis. Our data provide proof of concept that SRH can reveal the diagnostic features of tissue collected in breast core needle biopsies, supporting further validation of this technology. Ultimately, we envision the use of SRH to create new, efficient workflows for managing patients with breast lesions, especially those in which fine needle aspiration is of limited value, and where rapid diagnosis of tissue biopsies could streamline care and increase patient satisfaction. Citation Format: Daniel Avram Orringer, Thomas Chen, Steve Pastore, Farbod Darvishian, Hildegard Toth, Freya Schnabel. Rapid beside diagnosis of breast core needle biopsies using stimulated raman histology [abstract]. In: Proceedings of the 2020 San Antonio Breast Cancer Virtual Symposium; 2020 Dec 8-11; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2021;81(4 Suppl):Abstract nr PS3-20.

PURPOSE: Resting state functional magnetic resonance imaging (rsfMRI) is an emerging tool to explore the functional connectivity of different brain regions. We aimed to assess the disruption of functional connectivity of the Default Mode Network (DMN), Dorsal Attention Network(DAN) and Fronto-Parietal Network (FPN) in patients with glial tumors. METHODS: rsfMRI data acquired on 3T-MR of treatment-naive glioma patients prospectively recruited (2015–2019) and matched controls from the 1000 functional-connectomes-project were analyzed using the CONN functional toolbox. Seed-Based Connectivity Analysis (SBCA) and Independent Component Analysis (ICA, with 10 to 100 components) were performed to study reliably the three networks of interest. RESULTS: 35 patients with gliomas (17 WHO grade I-II, 18 grade III-IV) and 70 controls were included. Global increased DMN connectivity was consistently found with SBCA and ICA in patients compared to controls (Cluster1: Precuneus, height: p < 10(−6); Cluster2: subcallosum; height: p < 10(−5)). However, an area of decreased connectivity was found in the posterior corpus callosum, particularly in high-grade gliomas (height: p < 10(−5)). The DAN demonstrated small areas of increased connectivity in frontal and occipital regions (height: p < 10(−6)). For the FPN, increased connectivity was noted in the precuneus, posterior cingulate gyrus, and frontal cortex. No difference in the connectivity of the networks of interest was demonstrated between low- and high-grade gliomas, as well as when stratified by their IDH1-R132H (isocitrate dehydrogenase) mutation status. CONCLUSION: Altered functional connectivity is reliably found with SBCA and ICA in the DMN, DAN, and FPN in glioma patients, possibly explained by decreased connectivity between the cerebral hemispheres across the corpus callosum due to disruption of the connections.

INTRODUCTION: Label-free Raman-based imaging techniques create the possibility of bringing chemical and histologic data into the operation room. Relying on the intrinsic biochemical properties of tissues to generate image contrast and optical tissue sectioning, Raman-based imaging methods can be used to detect microscopic tumor infiltration and diagnose brain tumor subtypes. METHODS: Here, we review the application of three Raman-based imaging methods to neurosurgical oncology: Raman spec- troscopy, coherent anti-Stokes Raman scattering (CARS) microscopy, and stimulated Raman histology (SRH). RESULTS: Raman spectroscopy allows for chemical characterization of tissue and can differentiate normal and tumor-infiltrated tissue based on variations in macromolecule content, both ex vivo and in vivo. To improve signal-to-noise ratio compared to conventional Raman spectroscopy, a second pulsed excitation laser can be used to coherently drive the vibrational frequency of specific Raman active chemical bonds (i.e. symmetric stretching of –CH2 bonds). Coherent Raman imaging, including CARS and stimulated Raman scattering microscopy, has been shown to detect microscopic brain tumor infiltration in fresh brain tumor specimens with submicron image resolution. Advances in fiber-laser technology have allowed for the develop- ment of intraoperative SRH as well as artificial intelligence algorithms to facilitate interpretation of SRH images. With molecular diagnostics becoming an essential part of brain tumor classification, preliminary studies have demonstrated that Raman-based methods can be used to diagnose glioma molecular classes intraoperatively. CONCLUSIONS: These results demonstrate how label-free Raman-based imaging methods can be used to improve the man- agement of brain tumor patients by detecting tumor infiltration, guiding tumor biopsy/resection, and providing images for histopathologic and molecular diagnosis.

Background Detection of glioma recurrence remains a challenge in modern neuro-oncology. Noninvasive radiographic imaging is unable to definitively differentiate true recurrence versus pseudoprogression. Even in biopsied tissue, it can be challenging to differentiate recurrent tumor and treatment effect. We hypothesized that intraoperative stimulated Raman histology (SRH) and deep neural networks can be used to improve the intraoperative detection of glioma recurrence. Methods We used fiber laser–based SRH, a label-free, nonconsumptive, high-resolution microscopy method ( Results Using patch-level CNN predictions, the inference algorithm returns a single Bernoulli distribution for the probability of tumor recurrence for each surgical specimen or patient. The external SRH validation dataset consisted of 48 patients (recurrent, 30; pseudoprogression, 18), and we achieved a diagnostic accuracy of 95.8%. Conclusion SRH with CNN-based diagnosis can be used to improve the intraoperative detection of glioma recurrence in near-real time. Our results provide insight into how optical imaging and computer vision can be combined to augment conventional diagnostic methods and improve the quality of specimen sampling at glioma recurrence.

Intraoperative diagnosis is essential for providing safe and effective care during cancer surgery1. The existing workflow for intraoperative diagnosis based on hematoxylin and eosin staining of processed tissue is time, resource and labor intensive2,3. Moreover, interpretation of intraoperative histologic images is dependent on a contracting, unevenly distributed, pathology workforce4. In the present study, we report a parallel workflow that combines stimulated Raman histology (SRH)5-7, a label-free optical imaging method and deep convolutional neural networks (CNNs) to predict diagnosis at the bedside in near real-time in an automated fashion. Specifically, our CNNs, trained on over 2.5 million SRH images, predict brain tumor diagnosis in the operating room in under 150 s, an order of magnitude faster than conventional techniques (for example, 20-30 min)2. In a multicenter, prospective clinical trial (n = 278), we demonstrated that CNN-based diagnosis of SRH images was noninferior to pathologist-based interpretation of conventional histologic images (overall accuracy, 94.6% versus 93.9%). Our CNNs learned a hierarchy of recognizable histologic feature representations to classify the major histopathologic classes of brain tumors. In addition, we implemented a semantic segmentation method to identify tumor-infiltrated diagnostic regions within SRH images. These results demonstrate how intraoperative cancer diagnosis can be streamlined, creating a complementary pathway for tissue diagnosis that is independent of a traditional pathology laboratory.

Stimulated Raman histology (SRH) images are created by the label-free, nondestructive imaging of tissue using stimulated Raman scattering (SRS) microscopy. In a matter of seconds, these images provide real-time histologic information on biopsied tissue in the operating room. SRS microscopy uses two lasers (pump beam and Stokes beam) to amplify the Raman signal of specific chemical bonds found in macromolecules (lipids, proteins, and nucleic acids) in these tissues. The concentrations of these macromolecules are used to produce image contrast. These images are acquired and displayed using an imaging system with five main components: (1) fiber coupled microscope, (2) dual-wavelength fiber-laser module, (3) laser control module, (4) microscope control module, and (5) a computer. This manuscript details how to assemble the dual-wavelength fiber-laser module and how to generate an SRH image.

Stimulated Raman histology (SRH) images are created by the label-free, nondestructive imaging of tissue using stimulated Raman scattering (SRS) microscopy. In a matter of seconds, these images provide real-time histologic information on biopsied tissue in the operating room. SRS microscopy uses two lasers (pump beam and Stokes beam) to amplify the Raman signal of specific chemical bonds found in macromolecules (lipids, proteins, and nucleic acids) in these tissues. The concentrations of these macromolecules are used to produce image contrast. These images are acquired and displayed using an imaging system with five main components: (1) fiber coupled microscope, (2) dual-wavelength fiber-laser module, (3) laser control module, (4) microscope control module, and (5) a computer. This manuscript details how to assemble the dual-wavelength fiber-laser module and how to generate an SRH image.

Description, Mutant IDH1 gliomas are infiltrated by nonsuppressive immature myeloid cells, resulting in enhanced response to immunotherapy., Mutant isocitrate-dehydrogenase 1 (mIDH1) synthesizes the oncometabolite 2-hydroxyglutarate (2HG), which elicits epigenetic reprogramming of the glioma cells’ transcriptome by inhibiting DNA and histone demethylases. We show that the efficacy of immune-stimulatory gene therapy (TK/Flt3L) is enhanced in mIDH1 gliomas, due to the reprogramming of the myeloid cells’ compartment infiltrating the tumor microenvironment (TME). We uncovered that the immature myeloid cells infiltrating the mIDH1 TME are mainly nonsuppressive neutrophils and preneutrophils. Myeloid cell reprogramming was triggered by granulocyte colony-stimulating factor (G-CSF) secreted by mIDH1 glioma stem/progenitor-like cells. Blocking G-CSF in mIDH1 glioma–bearing mice restores the inhibitory potential of the tumor-infiltrating myeloid cells, accelerating tumor progression. We demonstrate that G-CSF reprograms bone marrow granulopoiesis, resulting in noninhibitory myeloid cells within mIDH1 glioma TME and enhancing the efficacy of immune-stimulatory gene therapy.

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

Significance: Surgery is often paramount in the management of many solid organ malignancies because optimal resection is a major factor in disease-specific survival. Cancer surgery has multiple challenges including localizing small lesions, ensuring negative surgical margins around a tumor, adequately staging patients by discriminating positive lymph nodes, and identifying potential synchronous cancers. Intraoperative molecular imaging (IMI) is an emerging potential tool proposed to address these issues. IMI is the process of injecting patients with fluorescenttargeted contrast agents that highlight cancer cells prior to surgery. Over the last 5 to 7 years, enormous progress has been achieved in tracer development, near-infrared camera approvals, and clinical trials. Therefore, a second biennial conference was organized at the University of Pennsylvania to gather surgical oncologists, scientists, and experts to discuss new investigative findings in the field. Our review summarizes the discussions from the conference and highlights findings in various clinical and scientific trials.Aim: Recent advances in IMI were presented, and the importance of each clinical trial for surgical oncology was critically assessed. A major focus was to elaborate on the clinical endpoints that were being utilized in IMI trials to advance the respective surgical subspecialties.Approach: Principal investigators presenting at the Perelman School of Medicine Abramson Cancer Center's second clinical trials update on IMI were selected to discuss their clinical trials and endpoints.Results: Multiple phase III, II, and I trials were discussed during the conference. Since the approval of 5-ALA for commercial use in neurosurgical malignancies, multiple tracers and devices have been developed to address common challenges faced by cancer surgeons across numerous specialties. Discussants also presented tracers that are being developed for delineation of normal anatomic structures that can serve as an adjunct during surgical procedures.Conclusions: IMI is increasingly being recognized as an improvement to standard oncologic surgical resections and will likely advance the art of cancer surgery in the coming years. The endpoints in each individual surgical subspecialty are varied depending on how IMI helps each specialty solve their clinical challenges. (C) The Authors. Published by SPIE under a Creative Commons Attribution 4.0 Unported License.

Background: Accurate diagnosis of skull base tumors is essential for providing personalized surgical treatment strategies. Intraoperative diagnosis can be challenging due to tumor diversity and lack of intraoperative pathology resources. Objective: To develop an independent and parallel intraoperative pathology workflow that can provide rapid and accurate skull base tumor diagnoses using label-free optical imaging and artificial intelligence. Method: We used a fiber laser-based, label-free, non-consumptive, high-resolution microscopy method ($, Published as journal article

Pathology is finally profiting from the recent development of promising novel imaging techniques, as well as exploration of computational methods for extracting increased information from existing slides and conventional microscopy. This chapter focuses largely on the latter, looking at application of artificial intelligence (AI) methods for denoising, sharpening, super-resolution, and color mapping from unstained slides to generate virtually stained images. In addition, software-based tools have been developed to replicate histochemical and immunohistochemical results without having to perform the actual procedures. Finally, an example of an application of novel slide-free histology using stimulated Raman microscopy for intraoperative guidance during brain cancer surgery is presented remarkably; this method includes AI classification tools (cancer/not cancer) that surgeons can rely on directly.

Safely maximizing extent of resection has become the central goal in glioma surgery. Especially in eloquent cortex, the goal of maximal resection is balanced with neurological risk. As new technologies emerge in the field of neurosurgery, the standards for maximal safe resection have been elevated. Fluorescence-guided surgery, intraoperative magnetic resonance imaging, and microscopic imaging methods are among the most well-validated tools available to enhance the level of accuracy and safety in glioma surgery. Each technology uses a different characteristic of glioma tissue to identify and differentiate tumor tissue from normal brain and is most effective in the context of anatomic, connectomic, and neurophysiologic context. While each tool is able to enhance resection, multiple modalities are often used in conjunction to achieve maximal safe resection. This paper reviews the mechanism and utility of the major adjuncts available for use in glioma surgery, especially in tumors within eloquent areas, and puts forth the foundation for a unified approach to how leverage currently available technology to ensure maximal safe resection.

Mutation in isocitrate dehydrogenase (mIDH) is a gain of function mutation resulting in the production of the oncometabolite, R-2-hydroxyglutarate, that inhibits DNA and histone demethylases. The resultant hypermethylation phenotype reprograms the glioma cells’ transcriptome and elicits profound effects on glioma immunity. We report that in mouse models and human gliomas, mIDH1 in the context of ATRX and TP53 inactivation results in global expansion of the granulocytic myeloid cells’ compartment. Single-cell RNA-sequencing coupled with mass cytometry analysis revealed that these granulocytes are mainly non-immunosuppressive neutrophils and pre-neutrophils; with a small fraction of polymorphonuclear myeloid-derived suppressor cells. The mechanism of mIDH1 mediated pre-neutrophils expansion involves epigenetic reprogramming which leads to enhanced expression of the granulocyte colony-stimulating factor (G-CSF). Blocking G-CSF restored the inhibitory potential of PMN-MDSCs and enhanced tumor progression. Thus, G-CSF induces remodeling of the inhibitory PMN-MDSCs in mIDH1 glioma rendering them non-immunosuppressive; and having significant therapeutic implications.SIGNIFICANCEmIDH1 is the most common mutation in gliomas associated with improved prognosis. Gliomas harboring mIDH1, together with ATRX and TP53 inactivation, exhibit higher circulating levels of G-CSF, ensuing the recruitment and expansion of non-suppressive neutrophils, pre-neutrophils and small fraction of PMN-MDSCs to the TME leading to an immune permissive phenotype.

The discovery of a new mass involving the brain or spine typically prompts referral to a neurosurgeon to consider biopsy or surgical resection. Intraoperative decision-making depends significantly on the histologic diagnosis, which is often established when a small specimen is sent for immediate interpretation by a neuropathologist. Access to neuropathologists may be limited in resource-poor settings, which has prompted several groups to develop machine learning algorithms for automated interpretation. Most attempts have focused on fixed histopathology specimens, which do not apply in the intraoperative setting. The greatest potential for clinical impact probably lies in the automated diagnosis of intraoperative specimens. Successful future studies may use machine learning to automatically classify whole-slide intraoperative specimens among a wide array of potential diagnoses.

The postoperative management of patients who undergo brain tumor resection frequently occurs in an ICU. However, the routine admission of all patients to an ICU following surgery is controversial. This study seeks to identify the frequency with which patients undergoing elective supratentorial tumor resection require care, aside from frequent neurologic checks, that is specific to an ICU and to determine the frequency of new complications during ICU admission. Additionally, clinical predictors of ICU-specific care are identified, and a scoring system to discriminate patients most likely to require ICU-specific treatment is validated.Retrospective observational cohort study.Academic neurosurgical center.Two-hundred consecutive adult patients who underwent supratentorial brain tumor surgery. An additional 100 consecutive patients were used to validate the prediction score.None.Univariate statistics and multivariable logistic regression were used to identify clinical characteristics associated with ICU-specific treatment. Eighteen patients (9%) received ICU-specific care, and 19 (9.5%) experienced new complications or underwent emergent imaging while in the ICU. Factors significantly associated with ICU-specific care included nonelective admission, preoperative Glasgow Coma Scale, and volume of IV fluids. A simple clinical scoring system that included Karnofsky Performance Status less than 70 (1 point), general endotracheal anesthesia (1 point), and any early postoperative complications (2 points) demonstrated excellent ability to discriminate patients who required ICU-specific care in both the derivation and validation cohorts.Less than 10% of patients required ICU-specific care following supratentorial tumor resection. A simple clinical scoring system may aid clinicians in stratifying the risk of requiring ICU care and could inform triage decisions when ICU bed availability is limited.

Background and importance Neurocysticercosis (NCC) is an infectious helminthic disease often presenting in patients who have immigration or travel history from areas where NCC is endemic. Fourth ventricle cysts from NCC pose a unique treatment challenge, as there is little consensus on the best treatment. This case study describes the treatment of a patient with fourth ventricle neurocysticercosis (FVNCC), examines the therapeutic decision-making, and provides a video of a posterior fossa craniotomy (PFC) resection of a degenerative cyst. Clinical presentation The patient presented with headache, dizziness, nausea, and memory difficulties. A fourth ventricle cyst consistent with NCC was found on magnetic resonance imaging, and serum enzyme-linked immunosorbent assay (ELISA) confirmed the diagnosis. The cyst was removed utilizing an open PFC followed by antihelminthic therapy and corticosteroids. There was resolution of symptoms at 9 mo postoperatively. Conclusion Several treatment modalities have been proposed for isolated cysts in the fourth ventricle, including medication, ventriculoperitoneal shunt, endoscopic removal, and PFC. The treatment decision is complex, and there is little guidance on the best treatment choices. In this article, we describe treatment via PFC for an adherent FVNCC cyst.

Primary melanocytic disease of the central nervous system is a rarely encountered condition currently without consensus on treatment and lacking major guidelines for management. Understanding the nature of the disease and differentiating primary melanocytic disease from the much more commonly encountered secondary (metastatic) melanoma is important in identifying the condition and pursuing appropriate treatment.

We hypothesized elderly patients with good Karnofsky Performance Status (KPS) treated with standard dose or dose-escalated radiation therapy (SDRT/DERT) and concurrent temozolomide (TMZ) would have favorable overall survival (OS) compared to historical elderly patients treated with hypofractionated RT (HFRT). From 2004 to 2015, 66 patients age ≥ 60 with newly diagnosed, pathologically proven glioblastoma were treated with SDRT/DERT over 30 fractions with concurrent/adjuvant TMZ at a single institution. Kaplan–Meier methods and the log-rank test were used to assess OS and progression-free survival (PFS). Multivariate analysis (MVA) was performed using Cox Proportional-Hazards. Median follow-up was 12.6 months. Doses ranged from 60 to 81 Gy (median 66). Median KPS was 90 (range 60–100) and median age was 67 years (range 60–81), with 29 patients ≥ 70 years old. 32% underwent gross total resection (GTR). MGMT status was known in 28%, 42% of whom were methylated. Median PFS was 8.3 months (95% CI 6.9–11.0) and OS was 12.7 months (95% CI 9.7–14.1). Patients age ≥ 70 with KPS ≥ 90 had a median OS of 12.4 months. Median OS was 27.1 months for MGMT methylated patients. On MVA controlling for age, dose, KPS, MGMT, GTR, and adjuvant TMZ, younger age (HR 0.9, 95% CI 0.8–0.9, p

Objective We aim to describe a novel, label-free, real-time imaging technique, coherent Raman scattering (CRS) microscopy, for histopathological evaluation of head and neck cancer. We evaluated the ability of CRS microscopy to delineate between tumor and nonneoplastic tissue in tissue samples from patients with head and neck cancer. Study Design Prospective case series. Setting Tertiary care medical center. Subjects and Methods Patients eligible were surgical candidates with biopsy-proven, previously untreated head and neck carcinoma and were consented preoperatively for participation in this study. Tissue was collected from 50 patients, and after confirmation of tumor and normal specimens by hematoxylin and eosin (H&E), there were 42 tumor samples and 42 normal adjacent controls. Results There were 42 confirmed carcinoma specimens on H&E, and CRS microscopy identified 37 as carcinoma. Of the 42 normal specimens, CRS microscopy identified 40 as normal. This resulted in a sensitivity of 88.1% and specificity of 95.2% in distinguishing between neoplastic and nonneoplastic images. Conclusion CRS microscopy is a unique label-free imaging technique that can provide rapid, high-resolution images and can accurately determine the presence of head and neck carcinoma. This holds potential for implementation into standard practice, allowing frozen margin evaluation even at institutions without a histopathology laboratory.

IDH mutation is of central importance in the diagnosis and treatment of gliomas. Fourier-transform infrared spectroscopy, in combination with a supervised machine-learning approach, can be used to detect metabolic alterations induced by IDH1 mutations in a fraction of the time of conventional techniques. Clin Cancer Res; 24(11); 2467–9. ©2018 AACR. See related article by Uckermann et al., p. 2530

Background Laser interstitial thermal therapy (LITT) is becoming an increasingly popular technique for the treatment of brain lesions. More minimally invasive that open craniotomy for lesion resection, LITT may be more appropriate for lesions that are harder to access through an open approach, deeper lesions, and for patients who may not tolerate open surgery. Methods A search of the current primary literature on LITT for brain lesions on PubMed was performed. These studies were reviewed and updates on the radiological, pathological, and long-term outcomes after LITT for brain metastases, primary brain tumors, and radiation necrosis as well as common complications are included. Results Larger extent of ablation and LITT as frontline treatment were potential predictors of favorable progression-free and overall survival for primary brain tumors. In brain metastases, larger extent of ablation was more significantly associated with survival benefit, whereas tumor size was a possible predictor. The most common complications after LITT are transient and permanent weakness, cerebral edema, hemorrhage, seizures, and hyponatremia. Conclusions Although the current literature is limited by small sample sizes and primarily retrospective studies, LITT is a safe and effective treatment for brain lesions in the correct patient population.

BackgroundNiemann–Pick disease type C is a fatal and progressive neurodegenerative disorder characterized by the accumulation of unesterified cholesterol in late endosomes and lysosomes. We sought to develop new therapeutics for this disorder by harnessing the body’s endogenous cholesterol scavenging particle, high-density lipoprotein (HDL).MethodsHere we design, optimize, and define the mechanism of action of synthetic HDL (sHDL) nanoparticles.ResultsWe demonstrate a dose-dependent rescue of cholesterol storage that is sensitive to sHDL lipid and peptide composition, enabling the identification of compounds with a range of therapeutic potency. Peripheral administration of sHDL toNpc1 I1061Thomozygous mice mobilizes cholesterol, reduces serum bilirubin, reduces liver macrophage size, and corrects body weight deficits. Additionally, a single intraventricular injection into adultNpc1 I1061Tbrains significantly reduces cholesterol storage in Purkinje neurons. Since endogenous HDL is also a carrier of sphingomyelin, we tested the same sHDL formulation in the sphingomyelin storage disease Niemann–Pick type A. Utilizing stimulated Raman scattering microscopy to detect endogenous unlabeled lipids, we show significant rescue of Niemann–Pick type A lipid storage.ConclusionsTogether, our data establish that sHDL nanoparticles are a potential new therapeutic avenue for Niemann–Pick diseases.

This is an interim report on a first in human Phase I dose escalation trial of the combination of two adenoviral vectors expressing HSV1-TK or Flt3L for the treatment of newly diagnosed, resectable malignant gliomas. Lack of dendritic cells from the brain precludes anti-glioma immune responses. We combined tumor cytotoxicity (Ad-HSV1TK) with recruitment of dendritic cells to gliomas (Ad-Flt3L) to induce anti-glioma immunity. In experimental models this treatment induces powerful cytotoxic CD8 and CD4 T-dependent anti-glioma immunity, immunological memory, and the capacity to recognize neo-antigens. The trial was approved through a FDA-IND, and all institutional cttees. Treatment was administered intraoperatively following complete glioma resection in newly diagnosed tumors. The trial consisted of vector dose escalation, starting at 1x10^9 v.p., and increasing to 1x10^11 v.p. of each vector, through 6 cohorts of 3 patients each. Two cycles of 14 days of valacyclovir were administered to activate HSV1-TK cytotoxicity. Cycle 1 starts on Day 1–3 post surgery for 14 days, and Cycle 2 on Week 8–12. Standard radiation, i.e., 60 Gy in 2 Gy fractions over 6 weeks, with concurrent temozolomide, was followed by cyclic temozolomide. Examination of tumor samples at primary resection and first recurrence show an increase in the infiltration of inflammatory cells. The experimental treatment was well tolerated. An MTD was not reached. There were approx. 248 AEs, and 26 SAEs; these were not linked to treatment. As secondary outcome, median survival of contemporary controls was 604 days, and median survival of trial patients was 742 days. Our results show for the first time that reprogramming of the host’s brain immune system to recognize gliomas reveals a new approach for the treatment of highly malignant brain tumors. Clinical trial information: NCT01811992.

We evaluated whether dose-intensified chemoradiation alters patterns of failure and is associated with favorable survival in the temozolomide era. Between 2003 and 2015, 82 patients with newly diagnosed glioblastoma were treated with 66–81 Gy in 30 fractions using conventional magnetic resonance imaging. Progression-free (PFS) and overall survival (OS) were calculated using Kaplan–Meier methods. Factors associated with improved PFS, OS, and time to progression were assessed using multivariate Cox model and linear regression. Median follow-up was 23 months (95% CI 4–124 months). Sixty-one percent of patients underwent subtotal resection or biopsy, and 38% (10/26) of patients with available data had MGMT promoter methylation. Median PFS was 8.4 months (95% CI 7.3–11.0) and OS was 18.7 months (95% CI 13.1–25.3). Only 30 patients (44%) experienced central recurrence, 6 (9%) in-field, 16 (23.5%) marginal and 16 (23.5%) distant. On multivariate analysis, younger age (HR 0.95, 95% CI 0.93–0.97, p = 0.0001), higher performance status (HR 0.39, 95% CI 0.16–0.95, p = 0.04), gross total resection (GTR) versus biopsy (HR 0.37, 95% CI 0.16–0.85, p = 0.02) and MGMT methylation (HR 0.25, 95% CI 0.09–0.71, p = 0.009) were associated with improved OS. Only distant versus central recurrence (p = 0.03) and GTR (p = 0.02) were associated with longer time to progression. Late grade 3 neurologic toxicity was rare (6%) in patients experiencing long-term survival. Dose-escalated chemoRT resulted in lower rates of central recurrence and prolonged time to progression compared to historical controls, although a significant number of central recurrences were still observed. Advanced imaging and correlative molecular studies may enable targeted treatment advances that reduce rates of in- and out-of-field progression.

The ability to detect neuronal currents with high spatiotemporal resolution using magnetic resonance imaging (MRI) is important for studying human brain function in both health and disease. While significant progress has been made, we still lack evidence showing that it is possible to measure an MR signal time-locked to neuronal currents with a temporal waveform matching concurrently recorded local field potentials (LFPs). Also lacking is evidence that such MR data can be used to image current distribution in active tissue. Since these two results are lacking even in vitro, we obtained these data in an intact isolated whole cerebellum of turtle during slow neuronal activity mediated by metabotropic glutamate receptors using a gradient-echo EPI sequence (TR = 100 ms) at 4.7 T. Our results show that it is possible (1) to reliably detect an MR phase shift time course matching that of the concurrently measured LFP evoked by stimulation of a cerebellar peduncle, (2) to detect the signal in single voxels of 0.1 mm3, (3) to determine the spatial phase map matching the magnetic field distribution predicted by the LFP map, (4) to estimate the distribution of neuronal current in the active tissue from a group-average phase map, and (5) to provide a quantitatively accurate theoretical account of the measured phase shifts. The peak values of the detected MR phase shifts were 0.27–0.37°, corresponding to local magnetic field changes of 0.67–0.93 nT (for TE = 26 ms). Our work provides an empirical basis for future extensions to in vivo imaging of neuronal currents.

Optical imaging of fluorescently labelled tissue illuminated by ultraviolet light does not require microscope slides and makes for a rapid alternative to conventional histology.

Mutation in isocitrate dehydrogenase (mIDH) is the main genetic lesion that defines clinical glioma subtypes and prognosis. This gain of function mutation is associated with the production of the oncometabolite, R-2-hydroxyglutarate, that inhibits α-ketoglutarate dependent enzymes such as TET2 and the Jumonji-C domain containing demethylases. The resultant epigenetic modifications elicit profound effects on the tumor biology and on the glioma-infiltrating immune cells. Here, we report that in genetically engineered mouse glioma models(1), IDH1 mutation caused an expansion of tumor infiltration granulocytes. Upon phenotypic and functional characterization, we uncovered that granulocytes in mIDH1 glioma express low level of immunosuppressive molecules and did not inhibit T-cell function. Single-cell sequencing revealed that these granulocytes are heterogeneous and composed of three distinct populations; neutrophils, pre-neutrophils, and a small fraction of immunosuppressive PMN-MDSCs. Moreover, primary human gliomas showed a higher cellular fraction exhibiting the PMN-MDSCs gene signature in wtIDH1 tumors than the mIDH1 tumors. The mechanism by which mIDH1 mediates non-immune suppressive granulocytes expansion involves epigenetic reprogramming which leads to enhanced expression of granulocyte colony-stimulating factor (G-CSF) in stem-like cells. High G-CSF gene expression is correlated with favorable patient outcome solely in LGG-astrocytoma with mIDH1. Thus, G-CSF represents a potential therapeutic that can be harnessed to improve immunotherapeutic responses in wild type IDH1 glioma patients.

High grade gliomas (HGG) such as glioblastoma lack effective treatment with poor prognosis of median overall survival (OS) around 14-16 months with standard of care. Initiation of effective immune response against cancer requires functional dendritic cells, which are absent from the central nervous system, resulting in lack of anti-HGG immune responses. An effective anti-glioma immune response can be achieved by combining glioma cytotoxicity with HSV1-TK and valacyclovir, and recruitment of dendritic cells to the brain with Flt3L. This dual approach makes endogenous tumor antigens available to infiltrating dendritic cells in its microenvironment by causing: (i) dendritic cells' infiltration of gliomas, (ii) CD8+, CD4+ T cell immune cytotoxicity and memory, and (iii) the systemic immune system to recognize tumor neoantigens. We report the first in human phase I dose escalation trial of adenoviral vectors expressing HSV1-TK and Flt3L (NCT01811992). Injection of dose escalated HSV1-TK and Flt3L adenovectors (range 1x10^9 vp - 1x10^11 vp) to the tumor bed post-resection of newly diagnosed HGG was followed by two cycles of 14-day course of valacyclovir starting 1-3 days and 10-12 weeks post-op combined with standard of care upfront radiation, concurrent and adjuvant temozolomide. Key inclusion criteria were ages 18-75, KPS ≥70, and suspected newly diagnosed HGG amenable to gross total resection. Enrollment and vector injection occurred after frozen pathology confirmed HGG. Out of 18 patients, six are still alive. The primary endpoint of maximal tolerated dose was not reached and the experimental treatment was well tolerated without dose limiting toxicity. The secondary endpoint of OS is promising with median of 21.9 months (range 5.4-52.7). Five out of six patients (83%) who had re-resection at the time of suspected radiographic progression had treatment effect rather than true progression, and increase in markers for dendritic cells, CD4+ T cells, and macrophages were noted, indicating successful immunity recruitment consistent with pre-clinical findings. Updated survival data, as well as comparison to matched controls, and detailed toxicities will be presented at the time of the meeting. In conclusion, the use of dual adenoviral vectors expressing Flt3L and HSV1-TK is safe and well tolerated in newly diagnosed HGG patients. Our results indicate promising preliminary survival outcome and histological evidence of immune infiltration. Future studies to assess treatment efficacy is warranted. Citation Format: Pedro Lowenstein, Daniel Orringer, Yoshie Umemura, Oren Sagher, Jason Heth, Shawn Hervey-Jumper, Aaron Mammoser, Denise Leung, Ted Lawrence, Mishell Kim, Daniel Wahl, Paul McKeever, Sandra Camelo-Piragua, Andrew Lieberman, Sriram Venneti, Kait Verbal, Karen Sagher, Patrick Dunn, Daniel Zamler, Andrea Comba, David Altshuler, Lili Zhao, Karin Muraszko, Larry Junck, Maria G. Castro. First in human phase I trial of adenoviral vectors expressing Flt3L and HSV1-TK to treat newly diagnosed high-grade glioma by reprogramming the brain immune system [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr CT105.

OBJECTIVEPituitary adenomas occur in a heterogeneous patient population with diverse perioperative risk factors, endocrinopathies, and other tumor-related comorbidities. This heterogeneity makes predicting postoperative outcomes challenging when using traditional scoring systems. Modern machine learning algorithms can automatically identify the most predictive risk factors and learn complex risk-factor interactions using training data to build a robust predictive model that can generalize to new patient cohorts. The authors sought to build a predictive model using supervised machine learning to accurately predict early outcomes of pituitary adenoma surgery.METHODSA retrospective cohort of 400 consecutive pituitary adenoma patients was used. Patient variables/predictive features were limited to common patient characteristics to improve model implementation. Univariate and multivariate odds ratio analysis was performed to identify individual risk factors for common postoperative complications and to compare risk factors with model predictors. The study population was split into 300 training/validation patients and 100 testing patients to train and evaluate four machine learning models using binary classification accuracy for predicting early outcomes.RESULTSThe study included a total of 400 patients. The mean ± SD patient age was 53.9 ± 16.3 years, 59.8% of patients had nonfunctioning adenomas and 84.7% had macroadenomas, and the mean body mass index (BMI) was 32.6 ± 7.8 (58.0% obesity rate). Multivariate odds ratio analysis demonstrated that age < 40 years was associated with a 2.86 greater odds of postoperative diabetes insipidus and that nonobese patients (BMI < 30) were 2.2 times more likely to develop postoperative hyponatremia. Using broad criteria for a poor early postoperative outcome—major medical and early surgical complications, extended length of stay, emergency department admission, inpatient readmission, and death—31.0% of patients met criteria for a poor early outcome. After model training, a logistic regression model with elastic net (LR-EN) regularization best predicted early postoperative outcomes of pituitary adenoma surgery on the 100-patient testing set—sensitivity 68.0%, specificity 93.3%, overall accuracy 87.0%. The receiver operating characteristic and precision-recall curves for the LR-EN model had areas under the curve of 82.7 and 69.5, respectively. The most important predictive variables were lowest perioperative sodium, age, BMI, highest perioperative sodium, and Cushing’s disease.CONCLUSIONSEarly postoperative outcomes of pituitary adenoma surgery can be predicted with 87% accuracy using a machine learning approach. These results provide insight into how predictive modeling using machine learning can be used to improve the perioperative management of pituitary adenoma patients.