Predicting post-surgical functional status in high-grade glioma with resting state fMRI and machine learning.

PURPOSE: High-grade glioma (HGG) is the most common and deadly malignant glioma of the central nervous system. The current standard of care includes surgical resection of the tumor, which can lead to functional and cognitive deficits. The aim of this study is to develop models capable of predicting functional outcomes in HGG patients before surgery, facilitating improved disease management and informed patient care. METHODS: Adult HGG patients (N = 102) from the neurosurgery brain tumor service at Washington University Medical Center were retrospectively recruited. All patients completed structural neuroimaging and resting state functional MRI prior to surgery. Demographics, measures of resting state network connectivity (FC), tumor location, and tumor volume were used to train a random forest classifier to predict functional outcomes based on Karnofsky Performance Status (KPS < 70, KPS ≥ 70). RESULTS: The models achieved a nested cross-validation accuracy of 94.1% and an AUC of 0.97 in classifying KPS. The strongest predictors identified by the model included FC between somatomotor, visual, auditory, and reward networks. Based on location, the relation of the tumor to dorsal attention, cingulo-opercular, and basal ganglia networks were strong predictors of KPS. Age was also a strong predictor. However, tumor volume was only a moderate predictor. CONCLUSION: The current work demonstrates the ability of machine learning to classify postoperative functional outcomes in HGG patients prior to surgery accurately. Our results suggest that both FC and the tumor's location in relation to specific networks can serve as reliable predictors of functional outcomes, leading to personalized therapeutic approaches tailored to individual patients.

A Phase 1/2 Study of Disulfiram and Copper With Concurrent Radiation Therapy and Temozolomide for Patients With Newly Diagnosed Glioblastoma.

PURPOSE: This phase 1/2 study aimed to evaluate the safety and preliminary efficacy of combining disulfiram and copper (DSF/Cu) with radiation therapy (RT) and temozolomide (TMZ) in patients with newly diagnosed glioblastoma (GBM). METHODS AND MATERIALS: Patients received standard RT and TMZ with DSF (250-375 mg/d) and Cu, followed by adjuvant TMZ plus DSF (500 mg/d) and Cu. Pharmacokinetic analyses determined drug concentrations in plasma and tumors using high-performance liquid chromatography-mass spectrometry. RESULTS: Thirty-three patients, with a median follow-up of 26.0 months, were treated, including 12 IDH-mutant, 9 NF1-mutant, 3 BRAF-mutant, and 9 other IDH-wild-type cases. In the phase 1 arm, 18 patients were treated; dose-limiting toxicity probabilities were 10% (95% CI, 3%-29%) at 250 mg/d and 21% (95% CI, 7%-42%) at 375 mg/d. The phase 2 arm treated 15 additional patients at 250 mg/d. No significant difference in overall survival or progression-free survival was noted between IDH- and NF1-mutant cohorts compared with institutional counterparts treated without DSF/Cu. However, extended remission occurred in 3 BRAF-mutant patients. Diethyl-dithiocarbamate-copper, the proposed active metabolite of DSF/Cu, was detected in plasma but not in tumors. CONCLUSIONS: The maximum tolerated dose of DSF with RT and TMZ is 375 mg/d. DSF/Cu showed limited clinical efficacy for most patients. However, promising efficacy was observed in BRAF-mutant GBM, warranting further investigation.

Quality assurance for focused ultrasound-induced blood-brain barrier opening procedure using passive acoustic detection.

BACKGROUND: Focused ultrasound (FUS) combined with microbubbles is a promising technique for noninvasive, reversible, and spatially targeted blood-brain barrier opening, with clinical trials currently ongoing. Despite the fast development of this technology, there is a lack of established quality assurance (QA) strategies to ensure procedure consistency and safety. To address this challenge, this study presents the development and clinical evaluation of a passive acoustic detection-based QA protocol for FUS-induced blood-brain barrier opening (FUS-BBBO) procedure. METHODS: Ten glioma patients were recruited to a clinical trial for evaluating a neuronavigation-guided FUS device. An acoustic sensor was incorporated at the center of the FUS device to passively capture acoustic signals for accomplishing three QA functions: FUS device QA to ensure the device functions consistently, acoustic coupling QA to detect air bubbles trapped in the acoustic coupling gel and water bladder of the transducer, and FUS procedure QA to evaluate the consistency of the treatment procedure. FINDINGS: The FUS device passed the device QA in 9/10 patient studies. 4/9 cases failed acoustic coupling QA on the first try. The acoustic coupling procedure was repeatedly performed until it passed QA in 3/4 cases. One case failed acoustic coupling QA due to time constraints. Realtime passive cavitation monitoring was performed for FUS procedure QA, which captured variations in FUS-induced microbubble cavitation dynamics among patients. INTERPRETATION: This study demonstrated that the proposed passive acoustic detection could be integrated with a clinical FUS system for the QA of the FUS-BBBO procedure. FUNDING: National Institutes of Health R01CA276174, R01MH116981, UG3MH126861, R01EB027223, R01EB030102, and R01NS128461.

Glioblastoma-Infiltrating CD8+ T Cells Are Predominantly a Clonally Expanded GZMK+ Effector Population.

Recent clinical trials have highlighted the limited efficacy of T cell-based immunotherapy in patients with glioblastoma (GBM). To better understand the characteristics of tumor-infiltrating lymphocytes (TIL) in GBM, we performed cellular indexing of transcriptomes and epitopes by sequencing and single-cell RNA sequencing with paired V(D)J sequencing, respectively, on TILs from two cohorts of patients totaling 15 patients with high-grade glioma, including GBM or astrocytoma, IDH-mutant, grade 4 (G4A). Analysis of the CD8+ TIL landscape reveals an enrichment of clonally expanded GZMK+ effector T cells in the tumor compared with matched blood, which was validated at the protein level. Furthermore, integration with other cancer types highlights the lack of a canonically exhausted CD8+ T-cell population in GBM TIL. These data suggest that GZMK+ effector T cells represent an important T-cell subset within the GBM microenvironment and may harbor potential therapeutic implications. SIGNIFICANCE: To understand the limited efficacy of immune-checkpoint blockade in GBM, we applied a multiomics approach to understand the TIL landscape. By highlighting the enrichment of GZMK+ effector T cells and the lack of exhausted T cells, we provide a new potential mechanism of resistance to immunotherapy in GBM. This article is featured in Selected Articles from This Issue, p. 897.

Optimal approaches to analyzing functional MRI data in glioma patients.

BACKGROUND: Resting-state fMRI is increasingly used to study the effects of gliomas on the functional organization of the brain. A variety of preprocessing techniques and functional connectivity analyses are represented in the literature. However, there so far has been no systematic comparison of how alternative methods impact observed results. NEW METHOD: We first surveyed current literature and identified alternative analytical approaches commonly used in the field. Following, we systematically compared alternative approaches to atlas registration, parcellation scheme, and choice of graph-theoretical measure as regards differentiating glioma patients (N = 59) from age-matched reference subjects (N = 163). RESULTS: Our results suggest that non-linear, as opposed to affine registration, improves structural match to an atlas, as well as measures of functional connectivity. Functionally- as opposed to anatomically-derived parcellation schemes maximized the contrast between glioma patients and reference subjects. We also demonstrate that graph-theoretic measures strongly depend on parcellation granularity, parcellation scheme, and graph density. COMPARISON WITH EXISTING METHODS AND CONCLUSIONS: Our current work primarily focuses on technical optimization of rs-fMRI analysis in glioma patients and, therefore, is fundamentally different from the bulk of papers discussing glioma-induced functional network changes. We report that the evaluation of glioma-induced alterations in the functional connectome strongly depends on analytical approaches including atlas registration, choice of parcellation scheme, and graph-theoretical measures.

First-in-human prospective trial of sonobiopsy in high-grade glioma patients using neuronavigation-guided focused ultrasound.

Sonobiopsy is an emerging technology that combines focused ultrasound (FUS) with microbubbles to enrich circulating brain disease-specific biomarkers for noninvasive molecular diagnosis of brain diseases. Here, we report the first-in-human prospective trial of sonobiopsy in high-grade glioma patients to evaluate its feasibility and safety in enriching plasma circulating tumor biomarkers. A nimble FUS device integrated with a clinical neuronavigation system was used to perform sonobiopsy following an established clinical workflow for neuronavigation. Analysis of blood samples collected before and after FUS sonication showed that sonobiopsy enriched plasma circulating tumor DNA (ctDNA), including a maximum increase of 1.6-fold for the mononucleosome cell-free DNA (cfDNA) fragments (120-280 bp), 1.9-fold for the patient-specific tumor variant ctDNA level, and 5.6-fold for the TERT mutation ctDNA level. Histological analysis of surgically resected tumors confirmed the safety of the procedure. Transcriptome analysis of sonicated and nonsonicated tumor tissues found that FUS sonication modulated cell physical structure-related genes. Only 2 out of 17,982 total detected genes related to the immune pathways were upregulated. These feasibility and safety data support the continued investigation of sonobiopsy for noninvasive molecular diagnosis of brain diseases.

Predicting survival in glioblastoma with multimodal neuroimaging and machine learning.

PURPOSE: Glioblastoma (GBM) is the most common and aggressive malignant glioma, with an overall median survival of less than two years. The ability to predict survival before treatment in GBM patients would lead to improved disease management, clinical trial enrollment, and patient care. METHODS: GBM patients (N = 133, mean age 60.8 years, median survival 14.1 months, 57.9% male) were retrospectively recruited from the neurosurgery brain tumor service at Washington University Medical Center. All patients completed structural neuroimaging and resting state functional MRI (RS-fMRI) before surgery. Demographics, measures of cortical thickness (CT), and resting state functional network connectivity (FC) were used to train a deep neural network to classify patients based on survival (< 1y, 1-2y, >2y). Permutation feature importance identified the strongest predictors of survival based on the trained models. RESULTS: The models achieved a combined cross-validation and hold out accuracy of 90.6% in classifying survival (< 1y, 1-2y, >2y). The strongest demographic predictors were age at diagnosis and sex. The strongest CT predictors of survival included the superior temporal sulcus, parahippocampal gyrus, pericalcarine, pars triangularis, and middle temporal regions. The strongest FC features primarily involved dorsal and inferior somatomotor, visual, and cingulo-opercular networks. CONCLUSION: We demonstrate that machine learning can accurately classify survival in GBM patients based on multimodal neuroimaging before any surgical or medical intervention. These results were achieved without information regarding presentation symptoms, treatments, postsurgical outcomes, or tumor genomic information. Our results suggest GBMs have a global effect on the brain's structural and functional organization, which is predictive of survival.

Glioblastoma induces whole-brain spectral change in resting state fMRI: Associations with clinical comorbidities and overall survival.

Glioblastoma, a highly aggressive form of brain tumor, is a brain-wide disease. We evaluated the impact of tumor burden on whole brain resting-state functional magnetic resonance imaging (rs-fMRI) activity. Specifically, we analyzed rs-fMRI signals in the temporal frequency domain in terms of the power-law exponent and fractional amplitude of low-frequency fluctuations (fALFF). We contrasted 189 patients with newly-diagnosed glioblastoma versus 189 age-matched healthy reference participants from an external dataset. The patient and reference datasets were matched for age and head motion. The principal finding was markedly flatter spectra and reduced grey matter fALFF in the patients as compared to the reference dataset. We posit that the whole-brain spectral change is attributable to global dysregulation of excitatory and inhibitory balance and metabolic demand in the tumor-bearing brain. Additionally, we observed that clinical comorbidities, in particular, seizures, and MGMT promoter methylation, were associated with flatter spectra. Notably, the degree of change in spectra was predictive of overall survival. Our findings suggest that frequency domain analysis of rs-fMRI activity provides prognostic information in glioblastoma patients and offers a means of noninvasively studying the effects of glioblastoma on the whole brain.

Structural gray matter alterations in glioblastoma and high-grade glioma-A potential biomarker of survival.

Background: Patients with glioblastoma (GBM) and high-grade glioma (HGG, World Health Organization [WHO] grade IV glioma) have a poor prognosis. Consequently, there is an unmet clinical need for accessible and noninvasively acquired predictive biomarkers of overall survival in patients. This study evaluated morphological changes in the brain separated from the tumor invasion site (ie, contralateral hemisphere). Specifically, we examined the prognostic value of widespread alterations of cortical thickness (CT) in GBM/HGG patients. Methods: We used FreeSurfer, applied with high-resolution T1-weighted MRI, to examine CT, evaluated prior to standard treatment with surgery and chemoradiation in patients (GBM/HGG, N = 162, mean age 61.3 years) and 127 healthy controls (HC; 61.9 years mean age). We then compared CT in patients to HC and studied patients' associated changes in CT as a potential biomarker of overall survival. Results: Compared to HC cases, patients had thinner gray matter in the contralesional hemisphere at the time of tumor diagnosis. patients had significant cortical thinning in parietal, temporal, and occipital lobes. Fourteen cortical parcels showed reduced CT, whereas in 5, it was thicker in patients' cases. Notably, CT in the contralesional hemisphere, various lobes, and parcels was predictive of overall survival. A machine learning classification algorithm showed that CT could differentiate short- and long-term survival patients with an accuracy of 83.3%. Conclusions: These findings identify previously unnoticed structural changes in the cortex located in the hemisphere contralateral to the primary tumor mass. Observed changes in CT may have prognostic value, which could influence care and treatment planning for individual patients.

Data-efficient resting-state functional magnetic resonance imaging brain mapping with deep learning.

OBJECTIVE: Resting-state functional MRI (RS-fMRI) enables the mapping of function within the brain and is emerging as an efficient tool for the presurgical evaluation of eloquent cortex. Models capable of reliable and precise mapping of resting-state networks (RSNs) with a reduced scanning time would lead to improved patient comfort while reducing the cost per scan. The aims of the present study were to develop a deep 3D convolutional neural network (3DCNN) capable of voxel-wise mapping of language (LAN) and motor (MOT) RSNs with minimal quantities of RS-fMRI data. METHODS: Imaging data were gathered from multiple ongoing studies at Washington University School of Medicine and other thoroughly characterized, publicly available data sets. All study participants (n = 2252 healthy adults) were cognitively screened and completed structural neuroimaging and RS-fMRI. Random permutations of RS-fMRI regions of interest were used to train a 3DCNN. After training, model inferences were compared using varying amounts of RS-fMRI data from the control data set as well as 5 patients with glioblastoma multiforme. RESULTS: The trained model achieved 96% out-of-sample validation accuracy on data encompassing a large age range collected on multiple scanner types and varying sequence parameters. Testing on out-of-sample control data showed 97.9% similarity between results generated using either 50 or 200 RS-fMRI time points, corresponding to approximately 2.5 and 10 minutes, respectively (96.9% LAN, 96.3% MOT true-positive rate). In evaluating data from patients with brain tumors, the 3DCNN was able to accurately map LAN and MOT networks despite structural and functional alterations. CONCLUSIONS: Functional maps produced by the 3DCNN can inform surgical planning in patients with brain tumors in a time-efficient manner. The authors present a highly efficient method for presurgical functional mapping and thus improved functional preservation in patients with brain tumors.

Efficacy of laser interstitial thermal therapy for biopsy-proven radiation necrosis in radiographically recurrent brain metastases.

Background: Laser interstitial thermal therapy (LITT) in the setting of post-SRS radiation necrosis (RN) for patients with brain metastases has growing evidence for efficacy. However, questions remain regarding hospitalization, local control, symptom control, and concurrent use of therapies. Methods: Demographics, intraprocedural data, safety, Karnofsky performance status (KPS), and survival data were prospectively collected and then analyzed on patients who consented between 2016-2020 and who were undergoing LITT for biopsy-proven RN at one of 14 US centers. Data were monitored for accuracy. Statistical analysis included individual variable summaries, multivariable Fine and Gray analysis, and Kaplan-Meier estimated survival. Results: Ninety patients met the inclusion criteria. Four patients underwent 2 ablations on the same day. Median hospitalization time was 32.5 hours. The median time to corticosteroid cessation after LITT was 13.0 days (0.0, 1229.0) and cumulative incidence of lesional progression was 19% at 1 year. Median post-procedure overall survival was 2.55 years [1.66, infinity] and 77.1% at one year as estimated by KaplanMeier. Median KPS remained at 80 through 2-year follow-up. Seizure prevalence was 12% within 1-month post-LITT and 7.9% at 3 months; down from 34.4% within 60-day prior to procedure. Conclusions: LITT for RN was not only again found to be safe with low patient morbidity but was also a highly effective treatment for RN for both local control and symptom management (including seizures). In addition to averting expected neurological death, LITT facilitates ongoing systemic therapy (in particular immunotherapy) by enabling the rapid cessation of steroids, thereby facilitating maximal possible survival for these patients.

A pilot study of lymphoscintigraphy with tracer injection into the human brain.

Many groups have reported lymphatic and glymphatic structures in animal and human brains, but tracer injection into the human brain to demonstrate real-time lymphatic drainage and mapping has not been described. We enrolled patients undergoing standard-of-care resection or stereotactic biopsy for suspected intracranial tumors. Patients received peritumoral injections of 99mTc-tilmanocept followed by planar or tomographic imaging. Fourteen patients with suspected brain tumors were enrolled. One was excluded from analysis because of tracer leakage during injection. There was no drainage of 99mTc-tilmanocept to regional lymph nodes in any of the patients. On average, after correcting for radioactive decay, 70.7% (95% CI: 59.9%, 81.6%) of the tracer in the injection site and 78.1% (95% CI: 71.1%, 85.1%) in the whole-head on the day of surgery remained the morning after, with variable radioactivity in the subarachnoid space. The retained fraction was much greater than expected based on the clearance rate from non-brain injection sites. In this pilot study, the lymphatic tracer 99mTc-tilmanocept was injected into the brain parenchyma, and there was no drainage outside the brain to the cervical lymph nodes. Our work demonstrates an inefficiency of drainage from peritumoral brain parenchyma and highlights a therapeutic opportunity to improve immunosurveillance of the brain.

First-in-human prospective trial of sonobiopsy in glioblastoma patients using neuronavigation-guided focused ultrasound.

Sonobiopsy is an emerging technology that combines focused ultrasound (FUS) with microbubbles to enrich circulating brain disease-specific biomarkers for noninvasive molecular diagnosis of brain diseases. Here, we report the first-in-human prospective trial of sonobiopsy in glioblastoma patients to evaluate its feasibility and safety in enriching circulating tumor biomarkers. A nimble FUS device integrated with a clinical neuronavigation system was used to perform sonobiopsy following an established clinical workflow for neuronavigation. Analysis of blood samples collected before and after FUS sonication showed enhanced plasma circulating tumor biomarker levels. Histological analysis of surgically resected tumors confirmed the safety of the procedure. Transcriptome analysis of sonicated and unsonicated tumor tissues found that FUS sonication modulated cell physical structure-related genes but evoked minimal inflammatory response. These feasibility and safety data support the continued investigation of sonobiopsy for noninvasive molecular diagnosis of brain diseases.

Electroactive Spinal Instrumentation for Targeted Osteogenesis and Spine Fusion: A Computational Study.

BACKGROUND: Direct current electrical stimulation may serve as a promising nonpharmacological adjunct promoting osteogenesis and fusion. The aim of this study was to evaluate the utility of electroactive spine instrumentation in the focal delivery of therapeutic electrical stimulation to enhance lumbar bone formation and interbody fusion. METHODS: A finite element model of adult human lumbar spine (L4-L5) instrumented with single-level electroactive pedicle screws was simulated. Direct current electrical stimulation was routed through anodized electroactive pedicle screws to target regions of fusion. The electrical fields generated by electroactive pedicle screws were evaluated in various tissue compartments including isotropic tissue volumes, cortical, and trabecular bone. Electrical field distributions at various stimulation amplitudes (20-100 µA) and pedicle screw anodization patterns were analyzed in target regions of fusion (eg, intervertebral disc space, vertebral body, and pedicles). RESULTS: Electrical stimulation with electroactive pedicle screws at various stimulation amplitudes and anodization patterns enabled modulation of spatial distribution and intensity of electric fields within the target regions of lumbar spine. Anodized screws (50%) vs unanodized screws (0%) induced high-amplitude electric fields within the intervertebral disc space and vertebral body but negligible electric fields in spinal canal. Direct current electrical stimulation via anodized screws induced electrical fields, at therapeutic threshold of >1 mV/cm, sufficient for osteoinduction within the target interbody region. CONCLUSIONS: Selective anodization of electroactive pedicle screws may enable focal delivery of therapeutic electrical stimulation in the target regions in human lumbar spine. This study warrants preclinical and clinical testing of integrated electroactive system in inducing target lumbar fusion in vivo. CLINICAL RELEVANCE: The findings of this study provide a foundation for clinically investigating electroactive intrumentation to enhance spine fusion.

Feasibility and Acceptability of a Preoperative Multimodal Mobile Health Assessment in Spine Surgery Candidates.

BACKGROUND: Rapid growth in smartphone use has expanded opportunities to use mobile health (mHealth) technology to collect real-time patient-reported and objective biometric data. These data may have important implication for personalized treatments of degenerative spine disease. However, no large-scale study has examined the feasibility and acceptability of these methods in spine surgery patients. OBJECTIVE: To evaluate the feasibility and acceptability of a multimodal preoperative mHealth assessment in patients with degenerative spine disease. METHODS: Adults undergoing elective spine surgery were provided with Fitbit trackers and sent preoperative ecological momentary assessments (EMAs) assessing pain, disability, mood, and catastrophizing 5 times daily for 3 weeks. Objective adherence rates and a subjective acceptability survey were used to evaluate feasibility of these methods. RESULTS: The 77 included participants completed an average of 82 EMAs each, with an average completion rate of 86%. Younger age and chronic pulmonary disease were significantly associated with lower EMA adherence. Seventy-two (93%) participants completed Fitbit monitoring and wore the Fitbits for an average of 247 hours each. On average, participants wore the Fitbits for at least 12 hours per day for 15 days. Only worse mood scores were independently associated with lower Fitbit adherence. Most participants endorsed positive experiences with the study protocol, including 91% who said they would be willing to complete EMAs to improve their preoperative surgical guidance. CONCLUSION: Spine fusion candidates successfully completed a preoperative multimodal mHealth assessment with high acceptability. The intensive longitudinal data collected may provide new insights that improve patient selection and treatment guidance.

Preoperative functional connectivity by magnetic resonance imaging for refractory neocortical epilepsy.

Objective: Patients with refractory epilepsy experience extensive and invasive clinical testing for seizure onset zones treatable by surgical resection. However, surgical resection can fail to provide therapeutic benefit, and patients with neocortical epilepsy have the poorest therapeutic outcomes. This case series studied patients with neocortical epilepsy who were referred for surgical treatment. Prior to surgery, patients volunteered for resting-state functional magnetic resonance imaging (rs-fMRI) in addition to imaging for the clinical standard of care. This work examined the variability of functional connectivity in patients, estimated from rs-fMRI, for associations with surgical outcomes. Methods: This work examined pre-operative structural imaging, pre-operative rs-fMRI, and post-operative structural imaging from seven epilepsy patients. Review of the clinical record provided Engel classifications for surgical outcomes. A novel method assessed pre-operative rs-fMRI from patients using comparative rs-fMRI from a large cohort of healthy control subjects and estimated Gibbs distributions for functional connectivity in patients compared to healthy controls. Results: Three patients had Engel classification Ia, one patient had Engel classification IIa, and three patients had Engel classification IV. Metrics for variability of functional connectivity, including absolute differences of the functional connectivity of each patient from healthy control averages and probabilistic scores for absolute differences, were higher for patients classified as Engel IV, for whom epilepsy surgery provided no meaningful improvement. Significance: This work continues on-going efforts to use rs-fMRI to characterize abnormal functional connectivity in the brain. Preliminary evidence indicates that the topography of variant functional connectivity in epilepsy patients may be clinically relevant for identifying patients unlikely to have favorable outcomes after epilepsy surgery. Widespread topographic variations of functional connectivity also support the hypothesis that epilepsy is a disease of brain resting-state networks.

Focused Ultrasound-mediated Liquid Biopsy in a Tauopathy Mouse Model.

Background Neurodegenerative disorders (such as Alzheimer disease) characterized by the deposition of various pathogenic forms of tau protein in the brain are collectively referred to as tauopathies. Identification of the molecular drivers and pathways of neurodegeneration is critical to individualized targeted treatment of these disorders. However, despite important advances in fluid biomarker detection, characterization of these molecular subtypes is limited by the blood-brain barrier. Purpose To evaluate the feasibility and safety of focused ultrasound-mediated liquid biopsy (sonobiopsy) in the detection of brain-derived protein biomarkers in a transgenic mouse model of tauopathy (PS19 mice). Materials and Methods Sonobiopsy was performed by sonicating the cerebral hemisphere in 2-month-old PS19 and wild-type mice, followed by measurement of plasma phosphorylated tau (p-tau) species (30 minutes after sonication in the sonobiopsy group). Next, spatially targeted sonobiopsy was performed by sonicating either the cerebral cortex or the hippocampus in 6-month-old PS19 mice. To detect changes in plasma neurofilament light chain (a biomarker of neurodegeneration) levels, blood samples were collected before and after sonication (15 and 45-60 minutes after sonication). Histologic staining was performed to evaluate tissue damage after sonobiopsy. The Shapiro-Wilk test, unpaired and paired t tests, and the Mann-Whitney U test were used. Results In the 2-month-old mice, sonobiopsy significantly increased the normalized levels of plasma p-tau species compared with the conventional blood-based liquid biopsy (p-tau-181-to-mouse tau [m-tau] ratio: 1.7-fold increase, P = .006; p-tau-231-to-m-tau ratio: 1.4-fold increase, P = .048). In the 6-month-old PS19 mice, spatially targeted sonobiopsy resulted in a 2.3-fold increase in plasma neurofilament light chain after sonication of the hippocampus and cerebral cortex (P < .001). After optimization of the sonobiopsy parameters, no excess microhemorrhage was observed in the treated cerebral hemisphere compared with the contralateral side. Conclusion This study showed the feasibility of sonobiopsy to release phosphorylated tau species and neurofilament light chain to the blood circulation, potentially facilitating diagnosis of neurodegenerative disorders. © RSNA, 2023 Supplemental material is available for this article. See also the editorial by Fowlkes in this issue.

Characterization of the Targeting Accuracy of a Neuronavigation-Guided Transcranial FUS System In Vitro, In Vivo, and In Silico.

Focused ultrasound (FUS)-enabled liquid biopsy (sonobiopsy) is an emerging technique for the noninvasive and spatiotemporally controlled diagnosis of brain cancer by inducing blood-brain barrier (BBB) disruption to release brain tumor-specific biomarkers into the blood circulation. The feasibility, safety, and efficacy of sonobiopsy were demonstrated in both small and large animal models using magnetic resonance-guided FUS devices. However, the high cost and complex operation of magnetic resonance-guided FUS devices limit the future broad application of sonobiopsy in the clinic. In this study, a neuronavigation-guided sonobiopsy device is developed and its targeting accuracy is characterized in vitro, in vivo, and in silico. The sonobiopsy device integrated a commercially available neuronavigation system (BrainSight) with a nimble, lightweight FUS transducer. Its targeting accuracy was characterized in vitro in a water tank using a hydrophone. The performance of the device in BBB disruption was verified in vivo using a pig model, and the targeting accuracy was quantified by measuring the offset between the target and the actual locations of BBB opening. The feasibility of the FUS device in targeting glioblastoma (GBM) tumors was evaluated in silico using numerical simulation by the k-Wave toolbox in glioblastoma patients. It was found that the targeting accuracy of the neuronavigation-guided sonobiopsy device was 1.7 ± 0.8 mm as measured in the water tank. The neuronavigation-guided FUS device successfully induced BBB disruption in pigs with a targeting accuracy of 3.3 ± 1.4 mm. The targeting accuracy of the FUS transducer at the GBM tumor was 5.5 ± 4.9 mm. Age, sex, and incident locations were found to be not correlated with the targeting accuracy in GBM patients. This study demonstrated that the developed neuronavigation-guided FUS device could target the brain with a high spatial targeting accuracy, paving the foundation for its application in the clinic.

The Conventional Dendritic Cell 1 Subset Primes CD8+ T Cells and Traffics Tumor Antigen to Drive Antitumor Immunity in the Brain.

The central nervous system (CNS) antigen-presenting cell (APC) that primes antitumor CD8+ T-cell responses remains undefined. Elsewhere in the body, the conventional dendritic cell 1 (cDC1) performs this role. However, steady-state brain parenchyma cDC1 are extremely rare; cDCs localize to the choroid plexus and dura. Thus, whether the cDC1 play a function in presenting antigen derived from parenchymal sources in the tumor setting remains unknown. Using preclinical glioblastoma (GBM) models and cDC1-deficient mice, we explored the presently unknown role of cDC1 in CNS antitumor immunity. We determined that, in addition to infiltrating the brain tumor parenchyma itself, cDC1 prime neoantigen-specific CD8+ T cells against brain tumors and mediate checkpoint blockade-induced survival benefit. We observed that cDC, including cDC1, isolated from the tumor, the dura, and the CNS-draining cervical lymph nodes harbored a traceable fluorescent tumor antigen. In patient samples, we observed several APC subsets (including the CD141+ cDC1 equivalent) infiltrating glioblastomas, meningiomas, and dura. In these same APC subsets, we identified a tumor-specific fluorescent metabolite of 5-aminolevulinic acid, which fluorescently labeled tumor cells during fluorescence-guided GBM resection. Together, these data elucidate the specialized behavior of cDC1 and suggest that cDC1 play a significant role in CNS antitumor immunity.

Neoadjuvant stereotactic radiosurgery for brain metastases: a new paradigm.

OBJECTIVE: For patients with surgically accessible solitary metastases or oligometastatic disease, treatment often involves resection followed by postoperative stereotactic radiosurgery (SRS). This strategy has several potential drawbacks, including irregular target delineation for SRS and potential tumor "seeding" away from the resection cavity during surgery. A neoadjuvant (preoperative) approach to radiation therapy avoids these limitations and offers improved patient convenience. This study assessed the efficacy of neoadjuvant SRS as a new treatment paradigm for patients with brain metastases. METHODS: A retrospective review was performed at a single institution to identify patients who had undergone neoadjuvant SRS (specifically, Gamma Knife radiosurgery) followed by resection of a brain metastasis. Kaplan-Meier survival and log-rank analyses were used to evaluate risks of progression and death. Assessments were made of local recurrence and leptomeningeal spread. Additionally, an analysis of the contemporary literature of postoperative and neoadjuvant SRS for metastatic disease was performed. RESULTS: Twenty-four patients who had undergone neoadjuvant SRS followed by resection of a brain metastasis were identified in the single-institution cohort. The median age was 64 years (range 32-84 years), and the median follow-up time was 16.5 months (range 1 month to 5.7 years). The median radiation dose was 17 Gy prescribed to the 50% isodose. Rates of local disease control were 100% at 6 months, 87.6% at 12 months, and 73.5% at 24 months. In 4 patients who had local treatment failure, salvage therapy included repeat resection, laser interstitial thermal therapy, or repeat SRS. One hundred thirty patients (including the current cohort) were identified in the literature who had been treated with neoadjuvant SRS prior to resection. Overall rates of local control at 1 year after neoadjuvant SRS treatment ranged from 49% to 91%, and rates of leptomeningeal dissemination from 0% to 16%. In comparison, rates of local control 1 year after postoperative SRS ranged from 27% to 91%, with 7% to 28% developing leptomeningeal disease. CONCLUSIONS: Neoadjuvant SRS for the treatment of brain metastases is a novel approach that mitigates the shortcomings of postoperative SRS. While additional prospective studies are needed, the current study of 130 patients including the summary of 106 previously published cases supports the safety and potential efficacy of preoperative SRS with potential for improved outcomes compared with postoperative SRS.