Citations

Bulk messaging is an important population health tool used to engage patients in preventive care and chronic disease management, yet little is known about optimal formatting of the communication. One factor to consider is whether the signatory of the patient-facing communication is the patient’s own Primary Care Provider (PCP) or a generic care team signature. In this quasi-randomized, non-blinded study we compared identical generic bulk outreach messages directed toward patients with an upcoming appointment and invited them to self-schedule a Medicare Annual wellness visit prior to their scheduled PCP appointment. Twenty-eight PCPs (1582 patients) were assigned to the PCP signature group, and 22 PCPs (1289 patients) to the care team signature group. The primary outcome was patient engagement, defined as a reply to the outreach message. Demographic, utilization, and rates of reading the bulk outreach message were similar between groups. Reply rates were significantly higher in the PCP signature group compared with the care team signature group (39.2% vs. 25.2%; odds ratio 1.86; P < 0.001). These findings suggest that using a patient’s own PCP signature in bulk outreach can meaningfully increase engagement, likely leveraging the trust inherent in established PCP–patient relationships. These results may inform health system leaders and population health teams seeking to optimize digital outreach strategies.

Abstract Background DNA methylation profiling can be used to robustly predict postsurgical outcomes and response to radiotherapy (RT) for meningioma patients. To allow for seamless integration of these complementary models into clinical practice, a practical framework is needed. Methods We leveraged a cohort of nearly 2000 surgically-treated meningiomas with DNA methylation profiling and clinical outcomes data. Existing methylation-based prediction models were dichotomized to yield four risk groups: low and high recurrent risk, each with RT sensitive and resistant subgroups. Risk groups were correlated with progression-free survival in the context of existing biomarkers including extent of resection and WHO grade. Results We first demonstrated that all risk groups benefit from gross total resection. All “high-risk, RT sensitive” tumors (n = 306, 15.7%) also benefited from adjuvant RT: after GTR, median PFS increased from 4.68 (4.13-9.48) years to not reached (P = .003); after subtotal resection (STR), from 2.12 (1.59-3.02) to 4.09 (3.41-not reached) years (P = .004). “Low-risk, RT sensitive cases” (n = 1207, 61.8%) also benefited from RT after STR (median PFS 7.39 (6.66-12.8) vs. 16.53 (10.35-not reached) years, P = .03), suggesting that RT be considered in these patients. Neither “low-risk RT resistant” (n = 84, 4.3%) nor “high-risk RT resistant” (n = 356, 18.2%) cases benefited from RT, and the latter group was associated with universally poor outcomes. Conclusions We identify methylation-defined risk groups of meningioma for which additional benefit is gained from adjuvant RT, leading to a clinical decision-making framework for straightforward integration of molecular models into clinical practice.

Abstract High-grade glioma (HGG) continues to have a dismal prognosis owing in part to its heterogeneous and invasive nature both within and between patients. The most aggressive form of high-grade glioma, called glioblastoma, portends a median survival of around 15 months. Like many cancers, high-grade glioma rewires metabolism towards its own benefit, shifting away from the typical reliance of brain tissue on glucose towards other sources such as fatty acids and acetate. Using a cohort of image-localized high-grade glioma biopsies collected from diverse imageable regions with associated transcriptomics (58 patients, 202 biopsies), we are able to assess the spatial transcriptomic landscape of HGG. We have previously shown that the transcriptome of HGG can be characterized into a continuous transition between states, and we have shown that the cellular ecosystem follows a similar pattern, using a combination of trajectory inference and cellular deconvolution. These patterns are strongly associated with the non-enhancing and contrast-enhancing regions of the tumors, which are typically considered for treatment planning and progression assessment. Here, we applied differential expression of hallmark pathways to determine how metabolism factors into this paradigm. As expected, we find overall higher levels of metabolism-associated pathway expression in the contrast enhancing regions compared to the non-enhancing regions. Interestingly, we found metabolic expression differs between the ecologies associated with transcriptional subtypes of high-grade glioma. For example, fatty acid (p=0.003), xenobiotic (p&lt;0.0001) and heme (p&lt;0.0001) metabolism pathways were significantly upregulated for mesenchymal tumor samples, while significantly downregulated for proliferative tumor samples (p=0.02, p&lt;0.0001, p&lt;0.0001, respectively). As we continue to further understand the complex spatial and temporally heterogeneous landscape of these aggressive tumors, it is important to consider the metabolites on which they depend, to better inform prognosis and develop new treatments.

Abstract INTRODUCTION Preserving language during tumor resection is critical but challenged by the time-intensive, complex nature of direct electrical stimulation (DES). High-gamma electrocorticography (ECoG) captures real-time, task-induced cortical responses, yet its spatiotemporal concordance with DES across language tasks remains underexplored. OBJECTIVE To evaluate how early and late high-gamma ECoG responses align with DES across auditory, object, action, and descriptive naming tasks. METHODS Seventeen patients (14 gliomas, 3 metastases) underwent awake craniotomy. ECoG was recorded, and bipolar DES was applied on the same subdural grid across the four tasks using adjacent contacts. Early (100–200 ms) and late (&gt;200 ms) high-gamma activity (30–150 Hz) and DES-positive sites were co-registered with a standard MNI-152 brain. The spatial overlap was quantified using Dice-Sørensen (D-S) coefficients with accuracy assessed by ECoG–DES contact proximity (exact/adjacent, &lt;1 cm) across tumor, peritumoral (&lt;2 cm), and whole-grid ROIs. Patient language outcomes were determined from longitudinal neurologic exams. RESULTS DES-positive sites were identified in 15/17 (88%) patients, primarily during auditory and action naming. Auditory naming elicited gamma activity in all patients, with early and late responses, reflecting sensory and extended semantic processes, observed in 10/17(59%) cases, showing strong concordance with DES (early: D-S= 0.63, 95% CI: 0.51–0.74; early + late: D-S = 0.66, 95% CI: 0.54–0.77). Non-auditory tasks showed predominantly late gamma responses, with modest DES overlap (object: D-S= 0.34; action: D-S= 0.42; descriptive: D-S= 0.37) suggesting border distributed cortical networks. Accuracy in all tasks ranged from 76–95% within the whole grid; auditory naming achieved 83% sensitivity and 82% specificity in peritumoral ROI. At 6 months, 14/17 (82%) patients had no speech deficits; 8/9 with preoperative deficits improved while 2 had a new deficit. CONCLUSION Gamma activity during auditory naming reliably predicts DES-defined language eloquence for safe maximal resection of brain tumors.

Abstract BACKGROUND Intraoperative electrocorticography (ECoG) may aid localization of language function and help guide eloquent brain tumor resection. However, relevance of ECoG findings to language outcomes remains unclear. METHODS Fifteen patients with brain tumors (Mdn age=60; 67% high-grade glioma) underwent awake craniotomy and intraoperative language mapping. Time-frequency ECoG gamma activity was visualized in real-time followed by direct electrical stimulation (DES) across 3 paradigms (NeuroMapper Tasks: Object, Action, Auditory). Early and late ECoG gamma modulations and positive DES sites were co-registered with postoperative MRI. A subset (N=11) completed expressive language testing (Phonemic and Semantic Fluency, Confrontation Naming) prior to and &lt;2 months following surgery. Correlational analyses and Mann-Whitney U tests examined relationships between test results and surgical impact upon expressive task-elicited gamma activity (Object and Action Naming). RESULTS Across tasks, positive DES sites were identified in 93% of cases (Auditory, 73%; Action, 71%, Object, 57%). No positive DES sites were resected. Early and/or late gamma activations were elicited in all patients, resected in 40%, and within 1 cm of surgical impact in 90%. Four patients (36%) showed reliable decline on at least 1 outcome, which was associated with Action Naming activity &lt;1 cm of surgical impact (phi=.67, p=.035). On individual tests, Confrontation Naming and Phonemic Fluency decline were rare (9% and 18%), though Semantic Fluency declined in 36% of patients. Change in Semantic Fluency was associated with resection of Object Naming gamma sites (Z=-1.83, p=.044) and presence of Action Naming gamma features near surgical impact (Z=-2.25, p=.014). CONCLUSIONS Despite preservation DES sites and sparing of basic confrontation naming ability, verbal fluency declined in a substantial group of patients. Decline was associated with gamma features resected or near surgical impact. While preliminary, findings suggest task-based ECoG can augment DES in informing risk of surgically-acquired language decline.

Abstract High-grade gliomas (HGGs) are aggressive, infiltrative brain tumors with poor survival outcomes and limited therapeutic options. Their spatial and molecular heterogeneity necessitates large, well-curated datasets integrating imaging, clinical, and genomic information to enable precision medicine and drive novel treatment development. Using the Medtronic StealthStation neuronavigation system, we collected over 1,000 spatially localized intraoperative biopsy samples from more than 250 patients undergoing resection for glioma at Mayo Clinic and partnering sites. Each biopsy site was recorded with 3D coordinates, labeled in real time, flash-frozen, and annotated with metadata including collection time, anatomical location, and surgical plan. Samples were processed and entered into a secure database along with the corresponding sampling coordinates, frozen pathology, whole-exome and RNA sequencing data, 5-ALA fluorescence status, patient demographics, and T1, T1Gd, T2, and T2-FLAIR MRI. This multimodal dataset supports radiogenomic research by enabling precise mapping of imaging features to molecular characteristics. A subset of this data, including 268 biopsies from 52 patients (25 male, 27 female) with reported intraoperative 5-ALA fluorescence, was used to develop a radiomics model predicting locoregional patterns of 5-ALA positivity based on preoperative MRI. Image features were extracted from the biopsy sample coordinates across multiple MRI sequences and paired with corresponding 5-ALA fluorescence status to train the model for regional fluorescence prediction. The final model achieved 83% accuracy on the training set and 86% on the validation set using a 70-15-15 data split; this included 208 samples for training and 42 for validation, stratified by patient to ensure no overlap of samples from the same individual across sets. These findings demonstrate the feasibility of predicting 5-ALA fluorescence using radiomic features from standard preoperative MRI, offering a promising noninvasive strategy for improving intraoperative decision-making and enabling more precise, personalized resections in patients with high-grade gliomas.