Comparison of the accuracy and proximal shunt failure rate of freehand placement versus intraoperative guidance in parietooccipital ventricular catheter placement.

OBJECTIVE The aim of this paper is to compare the accuracy of the freehand technique versus the use of intraoperative guidance (either ultrasound guidance or frameless stereotaxy) for placement of parietooccipital ventricular catheters and to determine factors associated with reduced proximal shunt failure. METHODS This retrospective cohort study included all patients from 2 institutions who underwent a ventricular cerebrospinal fluid (CSF) shunting procedure in which a new parietooccipital ventricular catheter was placed between January 2005 and December 2013. Data abstracted for each patient included age, sex, method of ventricular catheter placement, side of ventricular catheter placement, Evans ratio, and bifrontal ventricular span. Postoperative radiographic studies were reviewed for accuracy of ventricular catheter placement. Medical records were also reviewed for evidence of shunt failure requiring revision. Standard statistical methods were used for analysis. RESULTS A total of 257 patients were included in the study: 134 from the University of Michigan and 123 from Washington University in St. Louis. Accurate ventricular catheter placement was achieved in 81.2% of cases in which intraoperative guidance was used versus 67.3% when the freehand technique was used. Increasing age reduced the likelihood of accurate catheter placement (OR 0.983, 95% CI 0.971-0.995; p = 0.005), while the use of intraoperative guidance significantly increased the likelihood (OR 2.809, 95% CI 1.406-5.618; p = 0.016). During the study period, 108 patients (42.0%) experienced shunt failure, 79 patients (30.7%) had failure involving the proximal catheter, and 53 patients (20.6%) had distal failure (valve or distal catheter). Increasing age reduced the likelihood of being free from proximal shunt failure (OR 0.983, 95% CI 0.970-0.995; p = 0.008), while both the use of intraoperative guidance (OR 2.385, 95% CI 1.227-5.032; p = 0.011), and accurate ventricular catheter placement (OR 3.424, 95% CI 1.796-6.524; p = 0.009) increased the likelihood. CONCLUSIONS The use of intraoperative guidance during parietooccipital ventricular catheter placement as part of a CSF shunt system significantly increases the likelihood of accurate catheter placement and subsequently reduces the rate of proximal shunt failure.

Management of pediatric craniocervical arterial dissections.

PURPOSE: Craniocervical arterial dissections (CCADs) represent a preventable cause of acute ischemic stroke (AIS). Our objective was to describe clinical presentation, imaging features, treatment strategies, and report clinical and imaging outcomes of CCADs at a large pediatric tertiary referral center. METHODS: Electronic medical records were queried using variations of the word dissection for patients under 25 years of age with neuroimaging over a 13-year period. Medical and imaging records were reviewed to identify carotid, vertebral, or intracranial dissections. Demographics, presenting symptoms, presence of AIS, mechanism of injury, dissection location, dissection treatment, and complications stemming from treatment were collected. Clinical outcome was classified according to modified Rankin Scale (mRS) score. Imaging follow-up was obtained until the dissection healed or stabilized. RESULTS: A total 6,289 patients met initial search criteria. Of the 42 (0.7%) patients with CCADs, 23 (54.8%) had internal carotid artery (ICA) dissections, and 17 (40.5%) had vertebrobasilar (VB) dissections. More females had ICA dissections (p = 0.002), and more males had VB dissections (p = 0.01). CCADs associated with traumatic presentation occurred in 34 patients (81.0%), while 8 (19.0%) were spontaneous. Good outcomes (mRS 0-3) were noted for 36 patients, and 5 had poor outcomes (mRS 4-6). In the 17 patients with vessel occlusion, 50.0% had partial or complete recanalization at a mean follow-up of 23.9 months. CONCLUSIONS: CCAD is commonly related to trauma and presents with AIS. The majority of patients experience good clinical outcome. Recanalization of initial vessel occlusion occurs in half of cases at 2 years.

A road map for the treatment of pediatric diffuse midline glioma.

Recent clinical trials for H3K27-altered diffuse midline gliomas (DMGs) have shown much promise. We present a consensus roadmap and identify three major barriers: (1) refinement of experimental models to include immune and brain-specific components; (2) collaboration among researchers, clinicians, and industry to integrate patient-derived data through sharing, transparency, and regulatory considerations; and (3) streamlining clinical efforts including biopsy, CNS-drug delivery, endpoint determination, and response monitoring. We highlight the importance of comprehensive collaboration to advance the understanding, diagnostics, and therapeutics for DMGs.

GTP Signaling Links Metabolism, DNA Repair, and Responses to Genotoxic Stress.

How cell metabolism regulates DNA repair is incompletely understood. Here, we define a GTP-mediated signaling cascade that links metabolism to DNA repair and has significant therapeutic implications. GTP, but not other nucleotides, regulates the activity of Rac1, a guanine nucleotide-binding protein, which promotes the dephosphorylation of serine 323 on Abl-interactor 1 (Abi-1) by protein phosphatase 5 (PP5). Dephosphorylated Abi-1, a protein previously not known to activate DNA repair, promotes nonhomologous end joining. In patients and mouse models of glioblastoma, Rac1 and dephosphorylated Abi-1 mediate DNA repair and resistance to standard-of-care genotoxic treatments. The GTP-Rac1-PP5-Abi-1 signaling axis is not limited to brain cancer, as GTP supplementation promotes DNA repair and Abi-1-S323 dephosphorylation in nonmalignant cells and protects mouse tissues from genotoxic insult. This unexpected ability of GTP to regulate DNA repair independently of deoxynucleotide pools has important implications for normal physiology and cancer treatment. SIGNIFICANCE: A newly described GTP-dependent signaling axis is an unexpected link between nucleotide metabolism and DNA repair. Disrupting this pathway can overcome cancer resistance to genotoxic therapy while augmenting it can mitigate genotoxic injury of normal tissues. This article is featured in Selected Articles from This Issue, p. 5.

Efficient Inference of Spatially-Varying Gaussian Markov Random Fields With Applications in Gene Regulatory Networks.

In this paper, we study the problem of inferring spatially-varying Gaussian Markov random fields (SV-GMRF) where the goal is to learn a network of sparse, context-specific GMRFs representing network relationships between genes. An important application of SV-GMRFs is in inference of gene regulatory networks from spatially-resolved transcriptomics datasets. The current work on inference of SV-GMRFs are based on the regularized maximum likelihood estimation (MLE) and suffer from overwhelmingly high computational cost due to their highly nonlinear nature. To alleviate this challenge, we propose a simple and efficient optimization problem in lieu of MLE that comes equipped with strong statistical and computational guarantees. Our proposed optimization problem is extremely efficient in practice: we can solve instances of SV-GMRFs with more than 2 million variables in less than 2 minutes. We apply the developed framework to study how gene regulatory networks in Glioblastoma are spatially rewired within tissue, and identify prominent activity of the transcription factor HES4 and ribosomal proteins as characterizing the gene expression network in the tumor peri-vascular niche that is known to harbor treatment resistant stem cells.

Generation of 3D ex vivo mouse- and patient-derived glioma explant slice model for integration of confocal time-lapse imaging and spatial analysis.

Development of spatial-integrative pre-clinical models is needed for glioblastoma, which are heterogenous tumors with poor prognosis. Here, we present an optimized protocol to generate three-dimensional ex vivo explant slice glioma model from orthotopic tumors, genetically engineered mouse models, and fresh patient-derived specimens. We describe a step-by-step workflow for tissue acquisition, dissection, and sectioning of 300-µm tumor slices maintaining cell viability. The explant slice model allows the integration of confocal time-lapse imaging with spatial analysis for studying migration, invasion, and tumor microenvironment, making it a valuable platform for testing effective treatment modalities. For complete details on the use and execution of this protocol, please refer to Comba et al. (2022).1.

Subclonal evolution and expansion of spatially distinct THY1-positive cells is associated with recurrence in glioblastoma.

PURPOSE: Glioblastoma(GBM) is a lethal disease characterized by inevitable recurrence. Here we investigate the molecular pathways mediating resistance, with the goal of identifying novel therapeutic opportunities. EXPERIMENTAL DESIGN: We developed a longitudinal in vivo recurrence model utilizing patient-derived explants to produce paired specimens(pre- and post-recurrence) following temozolomide(TMZ) and radiation(IR). These specimens were evaluated for treatment response and to identify gene expression pathways driving treatment resistance. Findings were clinically validated using spatial transcriptomics of human GBMs. RESULTS: These studies reveal in replicate cohorts, a gene expression profile characterized by upregulation of mesenchymal and stem-like genes at recurrence. Analyses of clinical databases revealed significant association of this transcriptional profile with worse overall survival and upregulation at recurrence. Notably, gene expression analyses identified upregulation of TGFß signaling, and more than one-hundred-fold increase in THY1 levels at recurrence. Furthermore, THY1-positive cells represented <10% of cells in treatment-naïve tumors, compared to 75-96% in recurrent tumors. We then isolated THY1-positive cells from treatment-naïve patient samples and determined that they were inherently resistant to chemoradiation in orthotopic models. Additionally, using image-guided biopsies from treatment-naïve human GBM, we conducted spatial transcriptomic analyses. This revealed rare THY1+ regions characterized by mesenchymal/stem-like gene expression, analogous to our recurrent mouse model, which co-localized with macrophages within the perivascular niche. We then inhibited TGFBRI activity in vivo which decreased mesenchymal/stem-like protein levels, including THY1, and restored sensitivity to TMZ/IR in recurrent tumors. CONCLUSIONS: These findings reveal that GBM recurrence may result from tumor repopulation by pre-existing, therapy-resistant, THY1-positive, mesenchymal cells within the perivascular niche.

Metabolomic Profiles of Human Glioma Inform Patient Survival.

Aims: Targeting tumor metabolism may improve the outcomes for patients with glioblastoma (GBM). To further preclinical efforts targeting metabolism in GBM, we tested the hypothesis that brain tumors can be stratified into distinct metabolic groups with different patient outcomes. Therefore, to determine if tumor metabolites relate to patient survival, we profiled the metabolomes of human gliomas and correlated metabolic information with clinical data. Results: We found that isocitrate dehydrogenase-wildtype (IDHwt) GBMs are metabolically distinguishable from IDH mutated (IDHmut) astrocytomas and oligodendrogliomas. Survival of patients with IDHmut gliomas was expectedly more favorable than those with IDHwt GBM, and metabolic signatures can stratify IDHwt GBMs subtypes with varying prognoses. Patients whose GBMs were enriched in amino acids had improved survival, while those whose tumors were enriched for nucleotides, redox molecules, and lipid metabolites fared more poorly. These findings were recapitulated in validation cohorts using both metabolomic and transcriptomic data. Innovation: Our results suggest the existence of metabolic subtypes of GBM with differing prognoses, and further support the concept that metabolism may drive the aggressiveness of human gliomas. Conclusions: Our data show that metabolic signatures of human gliomas can inform patient survival. These findings may be used clinically to tailor novel metabolically targeted agents for GBM patients with different metabolic phenotypes. Antioxid. Redox Signal. 39, 942-956.

GTP signaling links metabolism, DNA repair, and responses to genotoxic stress.

How cell metabolism regulates DNA repair is incompletely understood. Here, we define a GTP-mediated signaling cascade that links metabolism to DNA repair and has significant therapeutic implications. GTP, but not other nucleotides, regulates the activity of Rac1, a G protein, that promotes the dephosphorylation of serine 323 on Abl-interactor 1 (Abi-1) by protein phosphatase 5 (PP5). Dephosphorylated Abi-1, a protein previously not known to activate DNA repair, promotes non-homologous end joining. In patients and mouse models of glioblastoma, Rac1 and dephosphorylated Abi-1 mediate DNA repair and resistance to standard of care genotoxic treatments. The GTP-Rac1-PP5-Abi-1 signaling axis is not limited to brain cancer, as GTP supplementation promotes DNA repair and Abi-1-S323 dephosphorylation in non-malignant cells and protects mouse tissues from genotoxic insult. This unexpected ability of GTP to regulate DNA repair independently of deoxynucleotide pools has important implications for normal physiology and cancer treatment.

Rewiring of cortical glucose metabolism fuels human brain cancer growth.

The brain avidly consumes glucose to fuel neurophysiology. Cancers of the brain, such as glioblastoma (GBM), lose aspects of normal biology and gain the ability to proliferate and invade healthy tissue. How brain cancers rewire glucose utilization to fuel these processes is poorly understood. Here we perform infusions of 13 C-labeled glucose into patients and mice with brain cancer to define the metabolic fates of glucose-derived carbon in tumor and cortex. By combining these measurements with quantitative metabolic flux analysis, we find that human cortex funnels glucose-derived carbons towards physiologic processes including TCA cycle oxidation and neurotransmitter synthesis. In contrast, brain cancers downregulate these physiologic processes, scavenge alternative carbon sources from the environment, and instead use glucose-derived carbons to produce molecules needed for proliferation and invasion. Targeting this metabolic rewiring in mice through dietary modulation selectively alters GBM metabolism and slows tumor growth. Significance: This study is the first to directly measure biosynthetic flux in both glioma and cortical tissue in human brain cancer patients. Brain tumors rewire glucose carbon utilization away from oxidation and neurotransmitter production towards biosynthesis to fuel growth. Blocking these metabolic adaptations with dietary interventions slows brain cancer growth with minimal effects on cortical metabolism.

Circumferential sulcus-guided resection technique for improved outcomes of low-grade gliomas.

OBJECTIVE: Many neurosurgeons resect nonenhancing low-grade gliomas (LGGs) by using an inside-out piecemeal resection (PMR) technique. At the authors' institution they have increasingly used a circumferential, perilesional, sulcus-guided resection (SGR) technique. This technique has not been well described and there are limited data on its effectiveness. The authors describe the SGR technique and assess the extent to which SGR correlates with extent of resection and neurological outcome. METHODS: The authors identified all patients with newly diagnosed LGGs who underwent resection at their institution over a 22-year period. Demographics, presenting symptoms, intraoperative data, method of resection (SGR or PMR), volumetric imaging data, and postoperative outcomes were obtained. Univariate analyses used ANOVA and Fisher's exact test. Multivariate analyses were performed using multivariate logistic regression. RESULTS: Newly diagnosed LGGs were resected in 519 patients, 208 (40%) using an SGR technique and 311 (60%) using a PMR technique. The median extent of resection in the SGR group was 84%, compared with 77% in the PMR group (p = 0.019). In multivariate analysis, SGR was independently associated with a higher rate of complete (100%) resection (27% vs 18%) (OR 1.7, 95% CI 1.1-2.6; p = 0.03). SGR was also associated with a statistical trend toward lower rates of postoperative neurological complications (11% vs 16%, p = 0.09). A subset analysis of tumors located specifically in eloquent brain demonstrated SGR to be as safe as PMR. CONCLUSIONS: The authors describe the SGR technique used to resect LGGs and show that SGR is independently associated with statistically significantly higher rates of complete resection, without an increase in neurological complications, than with PMR. SGR technique should be considered when resecting LGGs.

Spatiotemporal analysis of glioma heterogeneity reveals COL1A1 as an actionable target to disrupt tumor progression.

Intra-tumoral heterogeneity is a hallmark of glioblastoma that challenges treatment efficacy. However, the mechanisms that set up tumor heterogeneity and tumor cell migration remain poorly understood. Herein, we present a comprehensive spatiotemporal study that aligns distinctive intra-tumoral histopathological structures, oncostreams, with dynamic properties and a specific, actionable, spatial transcriptomic signature. Oncostreams are dynamic multicellular fascicles of spindle-like and aligned cells with mesenchymal properties, detected using ex vivo explants and in vivo intravital imaging. Their density correlates with tumor aggressiveness in genetically engineered mouse glioma models, and high grade human gliomas. Oncostreams facilitate the intra-tumoral distribution of tumoral and non-tumoral cells, and potentially the collective invasion of the normal brain. These fascicles are defined by a specific molecular signature that regulates their organization and function. Oncostreams structure and function depend on overexpression of COL1A1. Col1a1 is a central gene in the dynamic organization of glioma mesenchymal transformation, and a powerful regulator of glioma malignant behavior. Inhibition of Col1a1 eliminates oncostreams, reprograms the malignant histopathological phenotype, reduces expression of the mesenchymal associated genes, induces changes in the tumor microenvironment and prolongs animal survival. Oncostreams represent a pathological marker of potential value for diagnosis, prognosis, and treatment.

Rapid Automated Analysis of Skull Base Tumor Specimens Using Intraoperative Optical Imaging and Artificial Intelligence.

BACKGROUND: Accurate specimen analysis of skull base tumors is essential for providing personalized surgical treatment strategies. Intraoperative specimen interpretation can be challenging because of the wide range of skull base pathologies and lack of intraoperative pathology resources. OBJECTIVE: To develop an independent and parallel intraoperative workflow that can provide rapid and accurate skull base tumor specimen analysis using label-free optical imaging and artificial intelligence. METHODS: We used a fiber laser-based, label-free, nonconsumptive, high-resolution microscopy method (<60 seconds per 1 × 1 mm2), called stimulated Raman histology (SRH), to image a consecutive, multicenter cohort of patients with skull base tumor. SRH images were then used to train a convolutional neural network model using 3 representation learning strategies: cross-entropy, self-supervised contrastive learning, and supervised contrastive learning. Our trained convolutional neural network models were tested on a held-out, multicenter SRH data set. RESULTS: SRH was able to image the diagnostic features of both benign and malignant skull base tumors. Of the 3 representation learning strategies, supervised contrastive learning most effectively learned the distinctive and diagnostic SRH image features for each of the skull base tumor types. In our multicenter testing set, cross-entropy achieved an overall diagnostic accuracy of 91.5%, self-supervised contrastive learning 83.9%, and supervised contrastive learning 96.6%. Our trained model was able to segment tumor-normal margins and detect regions of microscopic tumor infiltration in meningioma SRH images. CONCLUSION: SRH with trained artificial intelligence models can provide rapid and accurate intraoperative analysis of skull base tumor specimens to inform surgical decision-making.

The effect of age on arteriovenous malformations in children and young adults undergoing magnetic resonance imaging.

OBJECTIVE: Arteriovenous malformations (AVMs) are the most frequently encountered structural cause of spontaneous intracerebral hemorrhage in childhood, excluding hemorrhages of prematurity. The goal of our study was to examine the relationship between age and AVM prevalence on imaging in children, which to date has not been well described. METHODS: We queried the electronic and radiographic records of 14,936 consecutive patients aged 25 years or less who had undergone brain magnetic resonance imaging (MRI) at a single institution over an 11-year period to identify those with a cerebral AVM. We collected age, gender, and other demographic characteristics for all patients. For all patients with a cerebral AVM, we recorded the location, size, drainage pattern, Spetzler-Martin grade, medical history, and presence of neurological symptoms. RESULTS: Cerebral AVMs were identified in 55 patients (0.37%). The prevalence of AVMs detected on MRI significantly increased with age (p = 0.001). AVMs were found in 0.34% of boys (25 of 7,447) and 0.40% of girls (30 of 7,489). AVMs were most commonly identified in the frontal lobes (36%), followed by parietal (20%) and temporal lobes (13%). Sixty percent (n = 33) of AVMs were less than 3 cm in size, 35% (n = 19) were 3-6 cm in size, and 5.5% (n = 3) were greater than 6 cm in size. As for Spetzler-Martin grade of the AVMs, 25.5% were grade I, 18.2% were grade II, 36.4% were grade III, 16.4% were grade IV, and 3.6% were grade V. CONCLUSIONS: AVMs are seen more frequently on MRI with advancing age in children and young adults.

Incidental findings on cranial imaging in nonagenarians.

OBJECT: The aim of this article was to report on the nature and prevalence of incidental imaging findings in a consecutive series of patients older than 90 years of age who underwent intracranial imaging for any reason. METHODS: The authors retrospectively reviewed the electronic medical and imaging records of consecutive patients who underwent brain MR imaging at a single institution over a 153-month interval and were at least 90 but less than 100 years of age at the time of the imaging study. The prevalence of lesions by type in this consecutive series of MR imaging evaluations was calculated for all patients. The authors reviewed the medical record to evaluate whether a change in management was recommended based on MR imaging findings. They evaluated patient age at the time of death and the time interval between MR imaging and death. RESULTS: The authors identified 177 patients who met the study criteria. The group included 119 women (67%) and 58 (33%) men. Their mean age was 92.3 ± 1.8 years. Evidence of acute ischemic changes or cerebrovascular accident (CVA) was found in 36 patients (20%). Fifteen patients (8%) had an intracranial tumor. Intracranial aneurysms were incidentally identified in 6 patients (3%). Chronic subdural hematomas were found in 3 patients (2%). Overall, 25 patients (14%) had some change in medical management as a result of the MR imaging findings. The most common MR imaging finding that resulted in a change in medical management was an acute CVA (p < 0.0001). The mean time to death from date of MR imaging was 2.5 ± 2.3 years. CONCLUSIONS: Intracranial imaging is rarely performed in patients older than 90 years. In cases of suspected stroke, MR imaging findings may influence treatment decisions. Brain MR imaging studies ordered for other indications in this age group rarely influence treatment decisions. Incidentally discovered lesions in this age group are generally not treated.

Stem cells for the treatment of glioblastoma: a 20-year perspective.

Glioblastoma, the deadliest form of primary brain tumor, remains a disease without cure. Treatment resistance is in large part attributed to limitations in the delivery and distribution of therapeutic agents. Over the last 20 years, numerous preclinical studies have demonstrated the feasibility and efficacy of stem cells as antiglioma agents, leading to the development of trials to test these therapies in the clinic. In this review we present and analyze these studies, discuss mechanisms underlying their beneficial effect and highlight experimental progress, limitations and the emergence of promising new therapeutic avenues. We hope to increase awareness of the advantages brought by stem cells for the treatment of glioblastoma and inspire further studies that will lead to accelerated implementation of effective therapies.

Lay abstract Glioblastoma is the deadliest and most common form of brain tumor, for which there is no cure. It is very difficult to deliver medicine to the tumor cells, because they spread out widely into the normal brain, and local blood vessels represent a barrier that most medicines cannot cross. It was shown, in many studies over the last 20 years, that stem cells are attracted toward the tumor and that they can deliver many kinds of therapeutic agents directly to brain cancer cells and shrink the tumor. In this review we analyze these studies and present new discoveries that can be used to make stem cell therapies for glioblastoma more effective to prolong the life of patients with brain tumors.

Uncovering Spatiotemporal Heterogeneity of High-Grade Gliomas: From Disease Biology to Therapeutic Implications.

Glioblastomas (GBM) are the most common and aggressive tumors of the central nervous system. Rapid tumor growth and diffuse infiltration into healthy brain tissue, along with high intratumoral heterogeneity, challenge therapeutic efficacy and prognosis. A better understanding of spatiotemporal tumor heterogeneity at the histological, cellular, molecular, and dynamic levels would accelerate the development of novel treatments for this devastating brain cancer. Histologically, GBM is characterized by nuclear atypia, cellular pleomorphism, necrosis, microvascular proliferation, and pseudopalisades. At the cellular level, the glioma microenvironment comprises a heterogeneous landscape of cell populations, including tumor cells, non-transformed/reactive glial and neural cells, immune cells, mesenchymal cells, and stem cells, which support tumor growth and invasion through complex network crosstalk. Genomic and transcriptomic analyses of gliomas have revealed significant inter and intratumoral heterogeneity and insights into their molecular pathogenesis. Moreover, recent evidence suggests that diverse dynamics of collective motion patterns exist in glioma tumors, which correlate with histological features. We hypothesize that glioma heterogeneity is not stochastic, but rather arises from organized and dynamic attributes, which favor glioma malignancy and influences treatment regimens. This review highlights the importance of an integrative approach of glioma histopathological features, single-cell and spatially resolved transcriptomic and cellular dynamics to understand tumor heterogeneity and maximize therapeutic effects.

A validated integrated clinical and molecular glioblastoma long-term survival-predictive nomogram.

BACKGROUND: Glioblastoma (GBM) is the most common primary malignant brain tumor in adulthood. Despite multimodality treatments, including maximal safe resection followed by irradiation and chemotherapy, the median overall survival times range from 14 to 16 months. However, a small subset of GBM patients live beyond 5 years and are thus considered long-term survivors. METHODS: A retrospective analysis of the clinical, radiographic, and molecular features of patients with newly diagnosed primary GBM who underwent treatment at The University of Texas MD Anderson Cancer Center was conducted. Eighty patients had sufficient quantity and quality of tissue available for next-generation sequencing and immunohistochemical analysis. Factors associated with survival time were identified using proportional odds ordinal regression. We constructed a survival-predictive nomogram using a forward stepwise model that we subsequently validated using The Cancer Genome Atlas. RESULTS: Univariate analysis revealed 3 pivotal genetic alterations associated with GBM survival: both high tumor mutational burden (P = .0055) and PTEN mutations (P = .0235) negatively impacted survival, whereas IDH1 mutations positively impacted survival (P < .0001). Clinical factors significantly associated with GBM survival included age (P < .0001), preoperative Karnofsky Performance Scale score (P = .0001), sex (P = .0164), and clinical trial participation (P < .0001). Higher preoperative T1-enhancing volume (P = .0497) was associated with shorter survival. The ratio of TI-enhancing to nonenhancing disease (T1/T2 ratio) also significantly impacted survival (P = .0022). CONCLUSIONS: Our newly devised long-term survival-predictive nomogram based on clinical and genomic data can be used to advise patients regarding their potential outcomes and account for confounding factors in nonrandomized clinical trials.

Rapid, label-free detection of diffuse glioma recurrence using intraoperative stimulated Raman histology and deep neural networks.

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 (<60 sec per 1 × 1 mm2) to image a cohort of patients (n = 35) with suspected recurrent gliomas who underwent biopsy or resection. The SRH images were then used to train a convolutional neural network (CNN) and develop an inference algorithm to detect viable recurrent glioma. Following network training, the performance of the CNN was tested for diagnostic accuracy in a retrospective cohort (n = 48). 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.