Frailty in patients with IDH-mutant gliomas: experience from a high-volume tumor center.

PURPOSE: Gliomas are increasingly diagnosed in an aging population, with treatment outcomes influenced by factors like tumor genetics and patient frailty. This study focused on IDH-mutant gliomas and assessed how frailty affects 30-day readmission and overall survival (OS). We aimed to address a gap in understanding the impact of frailty on this specific glioma subtype. METHODS: 136 patients with an IDH-mutant glioma between 2007 and 2021 were identified at our institution. High frailty was classified by scores ≥ 1 on the 5-factor modified frailty index (mFI-5) and ≥ 3 on the Charlson Comorbidity Index (CCI). Patient and tumor characteristics including age, sex, race, Karnofsky Performance Status (KPS), Body Mass Index (BMI), tumor type and location, type of operation, and therapy course were recorded. Outcomes measured included 30-day readmission and overall survival (OS). Analysis was conducted utilizing logistic regression and Kaplan-Meier curves. RESULTS: Of the 136 patients, 52 (38%) had high frailty: 18 with CCI ≥ 3, 34 with mFI-5 ≥ 1. High frailty correlated with increased BMI (CCI: 30.2, mFI-5: 30.1 kg/m2), more neurological deficits (CCI: 61%, mFI-5: 56%), and older age at surgery (CCI: 63, mFI-5: 48 years). Hospital readmission within 30 days occurred in 8 (5.9%) patients. Logistic regression indicated no significant difference in 30-day readmission rates (CCI: p = 0.30, mFI-5: p = 0.62) or median OS between high and low frailty groups. However, patients treated at our institution with newly diagnosed tumors with high mFI-5 had a 6.79 times higher adjusted death hazard than those with low mFI-5 (p = .049). CONCLUSION: Our analysis revealed that CCI and mFI-5 were not significantly associated with 30-day nor OS. However, in patients with non-recurrent tumors, there was a significant association of mFI-5 with OS. Further study of frailty with larger cohorts is warranted to enhance prognostication of outcome after neurosurgical treatment.

Examining the Effect of ALK and EGFR Mutations on Survival Outcomes in Surgical Lung Brain Metastasis Patients.

In the context of the post-genomic era, where targeted oncological therapies like monoclonal antibodies (mAbs) and tyrosine-kinase inhibitors (TKIs) are gaining prominence, this study investigates whether these therapies can enhance survival for lung carcinoma patients with specific genetic mutations-EGFR-amplified and ALK-rearranged mutations. Prior to this study, no research series had explored how these mutations influence patient survival in cases of surgical lung brain metastases (BMs). Through a multi-site retrospective analysis, the study examined patients who underwent surgical resection for BM arising from primary lung cancer at Emory University Hospital from January 2012 to May 2022. The mutational statuses were determined from brain tissue biopsies, and survival analyses were conducted. Results from 95 patients (average age: 65.8 ± 10.6) showed that while 6.3% had anaplastic lymphoma kinase (ALK)-rearranged mutations and 20.0% had epidermal growth factor receptor (EGFR)-amplified mutations-with 9.5% receiving second-line therapies-these mutations did not significantly correlate with overall survival. Although the sample size of patients receiving targeted therapies was limited, the study highlighted improved overall survival and progression-free survival rates compared to earlier trials, suggesting advancements in systemic lung metastasis treatment. The study suggests that as more targeted therapies emerge, the prospects for increased overall survival and progression-free survival in lung brain metastasis patients will likely improve.

Tumor microenvironment in a minipig model of spinal cord glioma.

BACKGROUND: Spinal cord glioma (SCG) is considered an orphan disease that lacks effective treatment options with margins that are surgically inaccessible and an overall paucity of literature on the topic. The tumor microenvironment is a critical factor to consider in treatment and modeling design, especially with respect to the unresectable tumor edge. Recently, our group developed a high-grade spinal cord glioma (SCG) model in Göttingen minipigs. METHODS: Immunofluorescence and ELISA were performed to explore the microenvironmental features and inflammation cytokines in this minipig SCG model. Protein carbonyl assay and GSH/GSSG assay were analyzed in the core and edge lesions in the minipig SCG model. The primary core and edge cells proliferation rate were shown in vitro, and the xenograft model in vivo. RESULTS: We identified an elevated Ki-67 proliferative index, vascular and pericyte markers, CD31 and desmin in the tumor edge as compared to the tumor core. In addition, we found that the tumor edge demonstrated increased pro-inflammatory and gliomagenic cytokines including TNF-α, IL-1ß, and IL-6. Furthermore, the mediation of oxidative stress is upregulated in the tumor edge. Hypoxic markers had statistically significant increased staining in the tumor core, but were notably still present in the tumor edge. The edge cells cultures derived from SCG biopsy also demonstrated an increased proliferative rate compared to core cell cultures in a xenotransplantation model. CONCLUSIONS: Our study demonstrates heterogeneity in microenvironmental features in our minipig model of high-grade SCG, with a phenotype at the edge showing increased oxidative stress, proliferation, inflammatory cytokines, neovascularization, and decreased but present staining for hypoxic markers. These findings support the utility of this model as a means for investigating therapeutic approaches targeting the more aggressive and surgically unresectable tumor border.

3D CEST MRI with an unevenly segmented RF irradiation scheme: A feasibility study in brain tumor imaging.

PURPOSE: To integrate 3D CEST EPI with an unevenly segmented RF irradiation module and preliminarily demonstrate it in the clinical setting. METHODS: A CEST MRI with unevenly segmented RF saturation was implemented, including a long primary RF saturation to induce the steady-state CEST effect, maintained with repetitive short secondary RF irradiation between readouts. This configuration reduces relaxation-induced blur artifacts during acquisition, allowing fast 3D spatial coverage. Numerical simulations were performed to select parameters such as flip angle (FA), short RF saturation duration (Ts2), and the number of readout segments. The sequence was validated experimentally with data from a phantom, healthy volunteers, and a brain tumor patient. RESULTS: Based on the numerical simulation and l-carnosine gel phantom experiment, FA, Ts2, and the number of segments were set to 20°, 0.3 s, and the range from 4 to 8, respectively. The proposed method minimized signal modulation in the human brain images in the kz direction during the acquisition and provided the blur artifacts-free CEST contrast over the whole volume. Additionally, the CEST contrast in the tumor tissue region is higher than in the contralateral normal tissue region. CONCLUSIONS: It is feasible to implement a highly accelerated 3D EPI CEST imaging with unevenly segmented RF irradiation.

Perfusion-Weighted Imaging: The Use of a Novel Perfusion Scoring Criteria to Improve the Assessment of Brain Tumor Recurrence versus Treatment Effects.

INTRODUCTION: Imaging surveillance of contrast-enhancing lesions after the treatment of malignant brain tumors with radiation is plagued by an inability to reliably distinguish between tumor recurrence and treatment effects. Magnetic resonance perfusion-weighted imaging (PWI)-among other advanced brain tumor imaging modalities-is a useful adjunctive tool for distinguishing between these two entities but can be clinically unreliable, leading to the need for tissue sampling to confirm diagnosis. This may be partially because clinical PWI interpretation is non-standardized and no grading criteria are used for assessment, leading to interpretation discrepancies. This variance in the interpretation of PWI and its subsequent effect on the predictive value has not been studied. Our objective is to propose structured perfusion scoring criteria and determine their effect on the clinical value of PWI. METHODS: Patients treated at a single institution between 2012 and 2022 who had prior irradiated malignant brain tumors and subsequent progression of contrast-enhancing lesions determined by PWI were retrospectively studied from CTORE (CNS Tumor Outcomes Registry at Emory). PWI was given two separate qualitative scores (high, intermediate, or low perfusion). The first (control) was assigned by a neuroradiologist in the radiology report in the course of interpretation with no additional instruction. The second (experimental) was assigned by a neuroradiologist with additional experience in brain tumor interpretation using a novel perfusion scoring rubric. The perfusion assessments were divided into three categories, each directly corresponding to the pathology-reported classification of residual tumor content. The interpretation accuracy in predicting the true tumor percentage, our primary outcome, was assessed through Chi-squared analysis, and inter-rater reliability was assessed using Cohen's Kappa. RESULTS: Our 55-patient cohort had a mean age of 53.5 ± 12.2 years. The percentage agreement between the two scores was 57.4% (κ: 0.271). Upon conducting the Chi-squared analysis, we found an association with the experimental group reads (p-value: 0.014) but no association with the control group reads (p-value: 0.734) in predicting tumor recurrence versus treatment effects. CONCLUSIONS: With our study, we showed that having an objective perfusion scoring rubric aids in improved PWI interpretation. Although PWI is a powerful tool for CNS lesion diagnosis, methodological radiology evaluation greatly improves the accurate assessment and characterization of tumor recurrence versus treatment effects by all neuroradiologists. Further work should focus on standardizing and validating scoring rubrics for PWI evaluation in tumor patients to improve diagnostic accuracy.

Immune niches in brain metastases contain TCF1+ stem-like T cells, are associated with disease control and are modulated by preoperative SRS.

The CD8+ T-cell response is prognostic for survival outcomes in several tumor types. However, whether this extends to tumors in the brain, an organ with barriers to T cell entry, remains unclear. Here, we analyzed immune infiltration in 67 brain metastasis (BrM) and found high frequencies of PD1+ TCF1+ stem-like CD8+ T-cells and TCF1- effector-like cells. Importantly, the stem-like cells aggregate with antigen presenting cells in immune niches, and niches were prognostic for local disease control. Standard of care for BrM is resection followed by stereotactic radiosurgery (SRS), so to determine SRS's impact on the BrM immune response, we examined 76 BrM treated with pre-operative SRS (pSRS). pSRS acutely reduced CD8+ T cells at 3 days. However, CD8+ T cells rebounded by day 6, driven by increased frequency of effector-like cells. This suggests that the immune response in BrM can be regenerated rapidly, likely by the local TCF1+ stem-like population.

Preoperative validation of edema-corrected tractography in neurosurgical practice: translating surgeon insights into novel software implementation.

Background: Peritumoral edema alters diffusion anisotropy, resulting in false negatives in tractography reconstructions negatively impacting surgical decision-making. With supratotal resections tied to survival benefit in glioma patients, advanced diffusion modeling is critical to visualize fibers within the peritumoral zone to prevent eloquent fiber transection thereafter. A preoperative assessment paradigm is therefore warranted to systematically evaluate multi-subject tractograms along clinically meaningful parameters. We propose a novel noninvasive surgically-focused survey to evaluate the benefits of a tractography algorithm for preoperative planning, subsequently applied to Synaptive Medical's free-water correction algorithm developed for clinically feasible single-shell DTI data. Methods: Ten neurosurgeons participated in the study and were presented with patient datasets containing histological lesions of varying degrees of edema. They were asked to compare standard (uncorrected) tractography reconstructions overlaid onto anatomical images with enhanced (corrected) reconstructions. The raters assessed the datasets in terms of overall data quality, tract alteration patterns, and the impact of the correction on lesion definition, brain-tumor interface, and optimal surgical pathway. Inter-rater reliability coefficients were calculated, and statistical comparisons were made. Results: Standard tractography was perceived as problematic in areas proximal to the lesion, presenting with significant tract reduction that challenged assessment of the brain-tumor interface and of tract infiltration. With correction applied, significant reduction in false negatives were reported along with additional insight into tract infiltration. Significant positive correlations were shown between favorable responses to the correction algorithm and the lesion-to-edema ratio, such that the correction offered further clarification in increasingly edematous and malignant lesions. Lastly, the correction was perceived to introduce false tracts in CSF spaces and - to a lesser degree - the grey-white matter interface, highlighting the need for noise mitigation. As a result, the algorithm was modified by free-water-parameterizing the tractography dataset and introducing a novel adaptive thresholding tool for customizable correction guided by the surgeon's discretion. Conclusion: Here we translate surgeon insights into a clinically deployable software implementation capable of recovering peritumoral tracts in edematous zones while mitigating artifacts through the introduction of a novel and adaptive case-specific correction tool. Together, these advances maximize tractography's clinical potential to personalize surgical decisions when faced with complex pathologies.

Artificial neural networks predict the need for permanent cerebrospinal fluid diversion following posterior fossa tumor resection.

Background: Resection of posterior fossa tumors (PFTs) can result in hydrocephalus that requires permanent cerebrospinal fluid (CSF) diversion. Our goal was to prospectively validate a machine-learning model to predict postoperative hydrocephalus after PFT surgery requiring permanent CSF diversion. Methods: We collected preoperative and postoperative variables on 518 patients that underwent PFT surgery at our center in a retrospective fashion to train several statistical classifiers to predict the need for permanent CSF diversion as a binary class. A total of 62 classifiers relevant to our data structure were surveyed, including regression models, decision trees, Bayesian models, and multilayer perceptron artificial neural networks (ANN). Models were trained using the (N = 518) retrospective data using 10-fold cross-validation to obtain accuracy metrics. Given the low incidence of our positive outcome (12%), we used the positive predictive value along with the area under the receiver operating characteristic curve (AUC) to compare models. The best performing model was then prospectively validated on a set of 90 patients. Results: Twelve percent of patients required permanent CSF diversion after PFT surgery. Of the trained models, 8 classifiers had an AUC greater than 0.5 on prospective testing. ANNs demonstrated the highest AUC of 0.902 with a positive predictive value of 83.3%. Despite comparable AUC, the remaining classifiers had a true positive rate below 35% (compared to ANN, P < .0001). The negative predictive value of the ANN model was 98.8%. Conclusions: ANN-based models can reliably predict the need for ventriculoperitoneal shunt after PFT surgery.

Development and validation of a prognostic gene expression signature for lower-grade glioma following surgery and adjuvant radiotherapy.

BACKGROUND AND PURPOSE: Standard of care for lower-grade glioma (LGG) is maximal safe resection and risk-adaptive adjuvant therapy. While patients who benefit the most from adjuvant chemotherapy have been elucidated in prospective randomized studies, comparable insights for adjuvant radiotherapy (RT) are lacking. We sought to identify and validate patterns of gene expression that are associated with differential outcomes among LGG patients treated by RT from two large genomics databases. MATERIALS AND METHODS: Patients from The Cancer Genome Atlas (TCGA) with LGG (WHO grade II-III glioma) treated by surgery and adjuvant RT were randomized 1:1 to a discovery cohort or an internal validation cohort. Using the discovery cohort only, associations between tumor RNA-seq expression and progression-free survival (PFS) as well as overall survival (OS) were evaluated with adjustment for clinicopathologic covariates. A Genomic Risk Score (GRS) was then constructed from the expression levels of top genes also screened for involvement in glioma carcinogenesis. The prognostic value of GRS was further assessed in the internal validation cohort of TCGA and a second distinct database, compiled by the Chinese Glioma Genome Association (CGGA). RESULTS: From TCGA, 289 patients with LGG received adjuvant RT alone (38 grade II, 30 grade III) or chemoradiotherapy (CRT) (51 grade II, 170 grade III) between 2009 and 2015. From CGGA, 178 patients with LGG received adjuvant RT alone (40 grade II, 13 grade III) or CRT (41 grade II, 84 grade III) between 2004 and 2016. The genes comprising GRS are involved in MAP kinase activity, T cell chemotaxis, and cell cycle transition: MAP3K15, MAPK10, CCL3, CCL4, and ADAMTS1. High GRS, defined as having a GRS in the top third, was significantly associated with poorer outcomes independent of age, sex, glioma histology, WHO grade, IDH mutation, 1p/19q co-deletion, and chemotherapy status in the discovery cohort (PFS HR 1.61, 95% CI 1.10-2.36, P = 0.014; OS HR 2.74, 95% CI 1.68-4.47, P < 0.001). These findings were replicated in the internal validation cohort (PFS HR 1.58, 95% CI 1.05-2.37, P = 0.027; OS HR 1.84, 95% CI 1.13-3.00, P = 0.015) and the CGGA external validation cohort (OS HR 1.72, 95% CI 1.27-2.34, P < 0.001). Association between GRS and outcomes was observed only among patients who underwent RT, in both TCGA and CGGA. CONCLUSION: This study successfully identified an expression signature of five genes that stratified outcomes among LGG patients who received adjuvant RT, with two rounds of validation leveraging independent genomics databases. Expression levels of the highlighted genes were associated with PFS and OS only among patients whose treatment included RT, but not among those with omission of RT, suggesting that expression of these genes may be predictive of radiation treatment response. While additional prospective studies are warranted, interrogation of these genes may be considered in the multidisciplinary management of LGG.

Distinct phenotypic states and spatial distribution of CD8+ T cell clonotypes in human brain metastases.

Metastatic disease in the brain is difficult to control and predicts poor prognosis. Here, we analyze human brain metastases and demonstrate their robust infiltration by CD8+ T cell subsets with distinct antigen specificities, phenotypic states, and spatial localization within the tumor microenvironment. Brain metastases are densely infiltrated by T cells; the majority of infiltrating CD8+ T cells express PD-1. Single-cell RNA sequencing shows significant clonal overlap between proliferating and exhausted CD8+ T cells, but these subsets have minimal clonal overlap with circulating and other tumor-infiltrating CD8+ T cells, including bystander CD8+ T cells specific for microbial antigens. Using spatial transcriptomics and spatial T cell receptor (TCR) sequencing, we show these clonally unrelated, phenotypically distinct CD8+ T cell populations occupy discrete niches within the brain metastasis tumor microenvironment. Together, our work identifies signaling pathways within CD8+ T cells and in their surrounding environment that may be targeted for immunotherapy of brain metastases.

Clinical and radiographic characteristics of diffuse astrocytic glioma, IDH-wildtype, with molecular features of glioblastoma: a single institution review.

PURPOSE: Genetic analyses of gliomas have identified key molecular features that impact treatment paradigms beyond conventional histomorphology. Despite at-times lower grade histopathologic appearances, IDH-wildtype infiltrating gliomas expressing certain molecular markers behave like higher-grade tumors. For IDH-wildtype infiltrating gliomas lacking traditional features of glioblastoma, these markers form the basis for the novel diagnosis of diffuse astrocytic glioma, IDH-wildtype (wt), with molecular features of glioblastoma (GBM), WHO grade-IV (DAG-G). However, given the novelty of this approach to diagnosis, literature detailing the exact clinical, radiographic, and histopathologic findings associated with these tumors remain in development. METHODS: Data for 25 patients matching the DAG-G diagnosis were obtained from our institution's retrospective database. Information regarding patient demographics, treatment regimens, radiographic imaging, and genetic pathology were analyzed to determine association with clinical outcomes. RESULTS: The initial radiographic findings, histopathology, and symptomatology of patients with DAG-G were similar to lower-grade astrocytomas (WHO grade 2/3). Overall survival (OS) and progression free survival (PFS) associated with our cohort, however, were similar to that of IDH-wt GBM, indicating a more severe clinical course than expected from other associated features (15.1 and 5.39 months respectively). CONCLUSION: Despite multiple features similar to lower-grade gliomas, patients with DAG-G experience clinical courses similar to GBM. Such findings reinforce the need for biopsy and subsequent analysis of molecular features associated with any astrocytoma regardless of presenting characteristics.

Modulation of the Complement System by Neoplastic Disease of the Central Nervous System.

The complement system is a highly conserved component of innate immunity that is involved in recognizing and responding to pathogens. The system serves as a bridge between innate and adaptive immunity, and modulation of the complement system can affect the entire host immune response to a foreign insult. Neoplastic diseases have been shown to engage the complement system in order to evade the immune system, gain a selective growth advantage, and co-opt the surrounding environment for tumor proliferation. Historically, the central nervous system has been considered to be an immune-privileged environment, but it is now clear that there are active roles for both innate and adaptive immunity within the central nervous system. Much of the research on the role of immunological modulation of neoplastic disease within the central nervous system has focused on adaptive immunity, even though innate immunity still plays a critical role in the natural history of central nervous system neoplasms. Here, we review the modulation of the complement system by a variety of neoplastic diseases of the central nervous system. We also discuss gaps in the current body of knowledge and comment on future directions for investigation.

Re-evaluating Biopsy for Recurrent Glioblastoma: A Position Statement by the Christopher Davidson Forum Investigators.

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.

Intracranial Myxoid Mesenchymal Tumor With EWSR1-ATF1 Fusion.

Angiomatoid fibrous histiocytoma (AFH) is a rare soft tissue tumor that arises primarily in the extremities of young adults. Recurrent gene fusions involving EWSR1 with members of the cAMP response element binding protein (CREB) family have been reported in a diverse group of tumors, including AFH. AFH-like lesions have been reported to occur intracranially and the reported cases show low proliferation indices, frequently have a connection with the dura, and show recurrent EWSR1 rearrangements. These tumors have been termed intracranial myxoid mesenchymal tumor with EWSR1-CREB family gene fusions. A literature search identified 11 reported cases of intracranial AFH-like lesions with an EWSR1 rearrangement. Here, we report a case of intracranial myxoid mesenchymal tumor with an EWSR1-ATF1 fusion in an adult patient, and review the existing literature on this recently described entity.

The Emerging Role of Biomarkers in Adaptive Modulation of Clinical Brain Stimulation.

Therapeutic brain stimulation has proven efficacious for treatment of nervous system diseases, exerting widespread influence via disease-specific neural networks. Activation or suppression of neural networks could theoretically be assessed by either clinical symptom modification (ie, tremor, rigidity, seizures) or development of specific biomarkers linked to treatment of symptomatic disease states. For example, biomarkers indicative of disease state could aid improved intraoperative localization of electrode position, optimize device efficacy or efficiency through dynamic control, and eventually serve to guide automatic adjustment of stimulation settings. Biomarkers to control either extracranial or intracranial stimulation span from continuous physiological brain activity, intermittent pathological activity, and triggered local phenomena or potentials, to wearable devices, blood flow, biochemical or cardiac signals, temperature perturbations, optical or magnetic resonance imaging changes, or optogenetic signals. The goal of this review is to update new approaches to implement control of stimulation through relevant biomarkers. Critical questions include whether adaptive systems adjusted through biomarkers can optimize efficiency and eventually efficacy, serve as inputs for stimulation adjustment, and consequently broaden our fundamental understanding of abnormal neural networks in pathologic states. Neurosurgeons are at the forefront of translating and developing biomarkers embedded within improved brain stimulation systems. Thus, criteria for developing and validating biomarkers for clinical use are important for the adaptation of device approaches into clinical practice.

Automating neurosurgical tumor resection surgery: Volumetric laser ablation of cadaveric porcine brain with integrated surface mapping.

OBJECTIVE: Current surgical instruments for soft tissue resection including neurosurgical procedures rely on the accuracy and precision of the human operator and are fundamentally constrained by the human hand. Automated surgical action with the integration of intraoperative data sources can enable highly accurate and fast tissue manipulation using laser ablation. This study presents the first experiments with a prototype designed for automated tumor resection via laser ablation. We demonstrate targeted soft tissue resection in porcine brain with an integrated device that combines 3D scanning capabilities with a steerable surgical laser and discuss implications for future automated robotic neurosurgical procedures. STUDY DESIGN AND METHODS: A device consisting of a two-axis galvanometer for steering a cutting laser and a 3D surface profiler is used to perform volumetric removal of tissue of ex vivo porcine brain. Three-dimensional surface profiles are gathered between cuts and used to estimate ablation rate. RESULTS: Volumetric ablation of porcine brain tissue is performed and subsequently surface profiled. The average ablation rates across the area cutting areas were 2.6 mm3 /s and 3.7 mm3 /s for the initial and subsequent cuts, respectively. A Kruskal-Wallis and post-hoc Tukey test show statistical significance between the initial and subsequent cuts. Accuracy between cuts when benchmarked against a human surgeon varied from 47 to 88%. CONCLUSION: A feed-forward volumetric resection is demonstrated with sensing and cutting housed within a single device, thereby opening the potential for automated soft tissue resection as necessary during the surgical removal of pathologic tissues. High variance around target cut depths motivates future work in developing a closed-loop ablation tool as well as characterization of laser-tissue interactions for predictive modelling. Objective Lasers Surg. 50:1017-1024, 2018. © 2018 Wiley Periodicals, Inc.

Biomarkers and Stimulation Algorithms for Adaptive Brain Stimulation.

The goal of this review is to describe in what ways feedback or adaptive stimulation may be delivered and adjusted based on relevant biomarkers. Specific treatment mechanisms underlying therapeutic brain stimulation remain unclear, in spite of the demonstrated efficacy in a number of nervous system diseases. Brain stimulation appears to exert widespread influence over specific neural networks that are relevant to specific disease entities. In awake patients, activation or suppression of these neural networks can be assessed by either symptom alleviation (i.e., tremor, rigidity, seizures) or physiological criteria, which may be predictive of expected symptomatic treatment. Secondary verification of network activation through specific biomarkers that are linked to symptomatic disease improvement may be useful for several reasons. For example, these biomarkers could aid optimal intraoperative localization, possibly improve efficacy or efficiency (i.e., reduced power needs), and provide long-term adaptive automatic adjustment of stimulation parameters. Possible biomarkers for use in portable or implanted devices span from ongoing physiological brain activity, evoked local field potentials (LFPs), and intermittent pathological activity, to wearable devices, biochemical, blood flow, optical, or magnetic resonance imaging (MRI) changes, temperature changes, or optogenetic signals. First, however, potential biomarkers must be correlated directly with symptom or disease treatment and network activation. Although numerous biomarkers are under consideration for a variety of stimulation indications the feasibility of these approaches has yet to be fully determined. Particularly, there are critical questions whether the use of adaptive systems can improve efficacy over continuous stimulation, facilitate adjustment of stimulation interventions and improve our understanding of the role of abnormal network function in disease mechanisms.