A deep-learning-based surrogate model for Monte-Carlo simulations of the linear energy transfer in primary brain tumor patients treated with proton-beam radiotherapy.

OBJECTIVE: This study explores the use of neural networks (NNs) as surrogate models for Monte-Carlo (MC) simulations in predicting the dose-averaged linear energy transfer (LETd) of protons in proton-beam therapy based on the planned dose distribution and patient anatomy in the form of computed tomography (CT) images. As LETdis associated with variability in the relative biological effectiveness (RBE) of protons, we also evaluate the implications of using NN predictions for normal tissue complication probability (NTCP) models within a variable-RBE context. Approach: The predictive performance of three-dimensional NN architectures was evaluated using five-fold cross-validation on a cohort of brain tumor patients (n=151). The best-performing model was identified and externally validated on patients from a different center (n=107). LETdpredictions were compared to MC-simulated results in clinically relevant regions of interest. We assessed the impact on NTCP models by leveraging LETdpredictions to derive RBE-weighted doses, using the Wedenberg RBE model. Main results: We found NNs based solely on the planned dose profile, i.e. without additional usage of CT images, can approximate MC-based LETddistributions. Root mean squared errors (RMSE) for the median LETdwithin the brain, brainstem, CTV, chiasm, lacrimal glands (ipsilateral/contralateral) and optic nerves (ipsilateral/contralateral) were 0.36, 0.87, 0.31, 0.73, 0.68, 1.04, 0.69 and 1.24~keV/µm, respectively. Although model predictions showed statistically significant differences from MC outputs, these did not result in substantial changes in NTCP predictions, with RMSEs of at most 3.2 percentage points. Significance: The ability of NNs to predict LETdbased solely on planned dose profiles suggests a viable alternative to the compute-intensive MC simulations in a variable-RBE setting. This is particularly useful in scenarios where MC simulation data are unavailable, facilitating resource-constrained proton therapy treatment planning, retrospective patient data analysis and further investigations on the variability of proton RBE.

A multicenter, phase 1, Adult Brain Tumor Consortium trial of oral terameprocol for patients with recurrent high-grade glioma (GATOR).

Recurrent high-grade gliomas (rHGGs) have a dismal prognosis, where the maximum tolerated dose (MTD) of IV terameprocol (5 days/month), a transcriptional inhibitor of specificity protein 1 (Sp1)-regulated proteins, is 1,700 mg/day with median area under the plasma concentration-time curve (AUC) of 31.3 µg∗h/mL. Given potentially increased efficacy with sustained systemic exposure and challenging logistics of daily IV therapy, here we investigate oral terameprocol for rHGGs in a multicenter, phase 1 trial (GATOR). Using a 3 + 3 dose-escalation design, we enroll 20 patients, with median age 60 years (range 31-80), 70% male, and median one relapse (range 1-3). Fasting patients tolerate 1,200 mg/day (n = 3), 2,400 mg/day (n = 6), 3,600 mg/day (n = 3), and 6,000 mg/day (n = 2) oral doses without major toxicities. However, increased dosage does not lead to increased systemic exposure, including in fed state (6,000 mg/day, n = 4), with maximal AUC <5 µg∗h/mL. These findings warrant trials investigating approaches that provide sustained systemic levels of transcription inhibitors to exploit their therapeutic potential. This study was registered at ClinicalTrials.gov (NCT02575794).

Maternal obesogenic diet operates at the tumor cell of origin to increase incidence and decrease latency of Neurofibromatosis Type 1 optic pathway glioma.

BACKGROUND: Pediatric low-grade glioma incidence has been rising in the U.S., mirroring the rising rates of pediatric and maternal obesity. Recently, children of obese mothers were demonstrated to develop brain tumors at higher rates. Importantly, obesity in the U.S. is largely driven by diet, given the prevalence of high fat and high sugar (HFHS) food choices. Since high-fat diet exposure can increase embryonic neuroglial progenitor cell (NPC) proliferation, the potential cells of origin for low-grade glioma, we hypothesized that in utero exposure to an obesogenic diet would modify pediatric brain penetrance and latency by affecting the tumor cell of origin. METHODS: We employed several murine models of the Neurofibromatosis type 1 (NF1) pediatric brain tumor predisposition syndrome, in which optic pathway gliomas (Nf1-OPGs) arise from NPCs in the embryonic third ventricular zone (TVZ). We exposed dams and offspring to an obesogenic HFHS diet or control chow and analysed fetal neurodevelopment at E19.5 and tumor formation at 6w-3mo. RESULTS: Progeny from HFHS diet-exposed dams demonstrated increased TVZ NPC proliferation and glial differentiation. Dietary switch cohorts confirmed that these effects were dependent upon maternal diet, rather than maternal weight. Obesogenic diet (Ob) similarly accelerated glioma formation in a high-penetrance Nf1-OPG strain and increased glioma penetrance in two low-penetrance Nf1-OPG strains. In contrast, Ob exposure in the postnatal period alone did not recapitulate these effects. CONCLUSIONS: These findings establish maternal obesogenic diet as a risk factor for murine Nf1-OPG formation, acting in part through in utero effects on the tumor cell of origin.

Diagnostic and Therapeutic Challenges of Rare Concurrent Intracranial Meningioma and Oligodendroglioma.

Introduction: Concurrent primary brain tumors are rare clinical entities, with a prevalence ranging from 0.1 to 0.5% of all diagnosed brain tumors. The co-occurrence of meningioma and oligodendroglioma is particularly uncommon, posing unique diagnostic and therapeutic challenges. We describe the case of a patient diagnosed with concurrent meningioma and oligodendroglioma and review the existing literature on this rare phenomenon. Case Presentation: A 55-year-old female patient with a history of seizures presented to the emergency department with worsening headaches, nausea, and vomiting. She had a known right frontoparietal intracranial mass but had previously declined surgery. Magnetic resonance imaging revealed extensive fluid-attenuated inversion recovery /T2 hyperintensity around the lesion, which had slowly increased over 5 years; the growth of the lesion was producing a mass effect with a significant midline shift. The patient underwent urgent hemicraniectomy with subsequent resection. Clinical evaluation, imaging studies, and histopathological examination were conducted to confirm the diagnosis. Genetic and molecular analyses were also performed to explore potential underlying mechanisms. Histopathological findings confirmed a diagnosis of an isocitrate dehydrogenase-mutated World Health Organization Grade II oligodendroglioma with 1p/19q codeletion, along with a Grade I meningioma. Conclusion: The coexistence of meningioma and oligodendroglioma represents a rare clinical event. Surgical management remains the cornerstone of treatment. Further investigation into the genetic and environmental factors that contribute to the co-occurrence of such tumors could pave the way for more targeted therapeutic strategies.

Intracranial Inflammatory Myofibroblastic Tumor: A Rare Case Report.

Introduction: Inflammatory pseudotumor encompasses a broad range of non-neoplastic and neoplastic entities, including inflammatory myofibroblastic tumors (IMTs). Because it is a rare mesenchymal tumor of unknown etiology and pathogenesis, and its clinical symptoms and radiologic features are not distinctive, intracranial IMT could be misdiagnosed as other extra-axial tumors. Here, we present a case of intracranial IMT suspected to be a brain abscess. Case Presentation: In this case, a 73-year-old woman presented headaches, nausea, and vertigo. Brain computed tomography (CT) and magnetic resonance imaging showed 4 × 3 cm sized oval rim-enhanced lesion on the left cerebellopontine angle. Considering the patient's history of otitis media and CT findings, we hypothesized that this lesion was a chronic brain abscess. The initial burr hole drain surgery was unsuccessful because there was no abscess, leading to a second radical excision surgery. Histopathological and immunohistochemical analyses eventually revealed a final diagnosis of intracranial IMT. Conclusion: Intracranial IMT is a rare disease with unknown pathogenesis. Diagnosis primarily depends on histopathological and immunohistochemistry analyses. As observed in our case, this disease may be mistaken for meningiomas, solitary fibrous tumors, or chronic abscesses due to its rare occurrence.

Brain Tumor Anatomy with Tractography Fluorescence and Confocal Endoscopy.

Tractography fluorescence and confocal endomicroscopy are complementary technologies to targeted tumor resection, and it is certain that as our technology for fluorescent probes continues to evolve, the confocal microscope will continue to be refined. Recent work suggests that intraoperative high-resolution augmented reality endomicroscopy, a real-time alternative to invasive biopsy and histopathology, has the potential to better quantify tumor burden at the final stages of surgery and ultimately to improve patient outcomes when combined with wide-field imaging approaches. Additional studies are needed to further elucidate the clinical benefits of these new technologies for brain tumor patients.

Patient-Centered Management of Brain Tumor-Related Epilepsy.

PURPOSE OF REVIEW: Brain tumor-related epilepsy is a heterogenous syndrome involving variability in incidence, timing, pathophysiology, and clinical risk factors for seizures across different brain tumor pathologies. Seizure risk and disability are dynamic over the course of disease and influenced by tumor-directed treatments, necessitating individualized patient-centered management strategies to optimize quality of life. RECENT FINDINGS: Recent translational findings in diffuse gliomas indicate a dynamic bidirectional relationship between glioma growth and hyperexcitability. Certain non-invasive measures of hyperexcitability are correlated with survival outcomes, however it remains uncertain how to define and measure clinically relevant hyperexcitability serially over time. The extent of resection, timing of pre-operative and/or post-operative seizures, and the likelihood of tumor progression are critical factors impacting the risk of seizure recurrence. Newer anti-seizure medications are generally well-tolerated with similar efficacy in this population, and several rapid-onset seizure rescue agents are in development and available. Seizures in patients with brain tumors are strongly influenced by the underlying tumor biology and treatment. An improved understanding of the interactions between tumor cells and the spectrum of hyperexcitability will facilitate targeted therapies. Multidisciplinary management of seizures should occur with consideration of tumor-directed therapy and prognosis, and anti-seizure medication decision-making tailored to the individual priorities and quality of life of the patient.

The Role of ArtificiaI Intelligence in Brain Tumor Diagnosis: An Evaluation of a Machine Learning Model.

This research study explores of the effectiveness of a machine learning image classification model in the accurate identification of various types of brain tumors. The types of tumors under consideration in this study are gliomas, meningiomas, and pituitary tumors. These are some of the most common types of brain tumors and pose significant challenges in terms of accurate diagnosis and treatment. The machine learning model that is the focus of this study is built on the Google Teachable Machine platform (Alphabet Inc., Mountain View, CA). The Google Teachable Machine is a machine learning image classification platform that is built from Tensorflow, a popular open-source platform for machine learning. The Google Teachable Machine model was specifically evaluated for its ability to differentiate between normal brains and the aforementioned types of tumors in MRI images. MRI images are a common tool in the diagnosis of brain tumors, but the challenge lies in the accurate classification of the tumors. This is where the machine learning model comes into play. The model is trained to recognize patterns in the MRI images that correspond to the different types of tumors. The performance of the machine learning model was assessed using several metrics. These include precision, recall, and F1 score. These metrics were generated from a confusion matrix analysis and performance graphs. A confusion matrix is a table that is often used to describe the performance of a classification model. Precision is a measure of the model's ability to correctly identify positive instances among all instances it identified as positive. Recall, on the other hand, measures the model's ability to correctly identify positive instances among all actual positive instances. The F1 score is a measure that combines precision and recall providing a single metric for model performance. The results of the study were promising. The Google Teachable Machine model demonstrated high performance, with accuracy, precision, recall, and F1 scores ranging between 0.84 and 1.00. This suggests that the model is highly effective in accurately classifying the different types of brain tumors. This study provides insights into the potential of machine learning models in the accurate classification of brain tumors. The findings of this study lay the groundwork for further research in this area and have implications for the diagnosis and treatment of brain tumors. The study also highlights the potential of machine learning in enhancing the field of medical imaging and diagnosis. With the increasing complexity and volume of medical data, machine learning models like the one evaluated in this study could play a crucial role in improving the accuracy and efficiency of diagnoses. Furthermore, the study underscores the importance of continued research and development in this field to further refine these models and overcome any potential limitations or challenges. Overall, the study contributes to the field of medical imaging and machine learning and sets the stage for future research and advancements in this area.

Efficacy of perampanel by etiology in Japanese patients with epilepsy-subpopulation analysis of a prospective post-marketing observational study.

OBJECTIVE: To examine the efficacy and safety of perampanel (PER) in patients with post-stroke epilepsy (PSE), brain tumor-related epilepsy (BTRE), and post-traumatic epilepsy (PTE) using Japanese real-world data. METHODS: The prospective post-marketing observational study included patients with focal seizures with or without focal to bilateral tonic-clonic seizures who received PER combination therapy. The observation period was 24 or 52 weeks after the initial PER administration. The safety and efficacy analysis included 3716 and 3272 patients, respectively. This post hoc analysis examined responder rate (50% reduction in seizure frequency), seizure-free rate (proportion of patients who achieved seizure-free), and safety in patients included in the post-marketing study who had PSE, BTRE, and PTE in the 4 weeks prior to the last observation. RESULTS: Overall, 402, 272, and 186 patients were included in the PSE, BTRE, and PTE subpopulations, and 2867 controls in the "Other" population (etiologies other than PSE, BTRE, or PTE). Mean modal dose (the most frequently administered dose) values at 52 weeks were 3.38, 3.36, 3.64, and 4.04 mg/day for PSE, BTRE, PTE, and "Other," respectively; PER retention rates were 56.2%, 54.0%, 52.6%, and 59.7%, respectively. Responder rates (% [95% confidence interval]) were 82% (76.3%-86.5%), 78% (70.8%-83.7%), 67% (56.8%-75.6%), and 50% (47.9%-52.7%) for PSE, BTRE, PTE, and "Other," respectively, and seizure-free rates were 71% (64.5%-76.5%), 62% (54.1%-69.0%), 50% (40.6%-60.4%), and 28% (25.8%-30.1%), respectively. Adverse drug reactions tended to occur less frequently in the PSE (14.7%), BTRE (16.5%), and PTE (16.7%) subpopulations than in the "Other" population (26.3%). SIGNIFICANCE: In real-world clinical conditions, efficacy and tolerability for PER combination therapy were observed at low PER doses for the PSE, BTRE, and PTE subpopulations. PLAIN LANGUAGE SUMMARY: To find out how well the medication perampanel works and whether it is safe for people who have epilepsy after having had a stroke, brain tumor, or head injury, we used information from real-life medical situations in Japan. We looked at the data of about 3700 Japanese patients with epilepsy who were treated with perampanel. We found that perampanel was used at lower doses and better at controlling seizures, and had fewer side effects for patients with epilepsy caused by these etiologies than the control group.

Demystifying the potential of lipid-based nanocarriers in targeting brain malignancies.

Drug targeting for brain malignancies is restricted due to the presence of the blood-brain barrier (BBB) and blood-brain tumor barrier (BBTB), which act as barriers between the blood and brain parenchyma. Certainly, the limited therapeutic options for brain malignancies have made notable progress with enhanced biological understanding and innovative approaches, such as targeted therapies and immunotherapies. These advancements significantly contribute to improving patient prognoses and represent a promising shift in the landscape of brain malignancy treatments. A more comprehensive understanding of the histology and pathogenesis of brain malignancies is urgently needed. Continued research focused on unraveling the intricacies of brain malignancy biology holds the key to developing innovative and tailored therapies that can improve patient outcomes. Lipid nanocarriers are highly effective drug delivery systems that significantly improve their solubility, bioavailability, and stability while also minimizing unwanted side effects. Surface-modified lipid nanocarriers (liposomes, niosomes, solid lipid nanoparticles, nanostructured lipid carriers, lipid nanocapsules, lipid-polymer hybrid nanocarriers, lipoproteins, and lipoplexes) are employed to improve BBB penetration and uptake through various mechanisms. This systematic review illuminates and covers various topics related to brain malignancies. It explores the different methods of drug delivery used in treating brain malignancies and delves into the benefits, limitations, and types of brain-targeted lipid-based nanocarriers. Additionally, this review discusses ongoing clinical trials and patents related to brain malignancy therapies and provides a glance into future perspectives for treating this condition.

Cervical Lymph Node Metastasis From Medulloblastoma in a Young Adult: Case Report and Literature Review.

Medulloblastoma, an embryonal tumor located in the posterior fossa of the brain, originates from the neuro-epidermal layer of the cerebellum. It is the most prevalent malignant tumor in children, while it is rare in adults and predominantly affects males. Multimodal therapeutic interventions, such as surgery, radiotherapy, and chemotherapy, have substantially enhanced the prognosis of this condition. Extraneural metastases are infrequent. We present a case of medulloblastoma relapse with nodal metastasis in a 28-year-old adult.

Exploring approaches to tackle cross-domain challenges in brain medical image segmentation: a systematic review.

Introduction: Brain medical image segmentation is a critical task in medical image processing, playing a significant role in the prediction and diagnosis of diseases such as stroke, Alzheimer's disease, and brain tumors. However, substantial distribution discrepancies among datasets from different sources arise due to the large inter-site discrepancy among different scanners, imaging protocols, and populations. This leads to cross-domain problems in practical applications. In recent years, numerous studies have been conducted to address the cross-domain problem in brain image segmentation. Methods: This review adheres to the standards of the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) for data processing and analysis. We retrieved relevant papers from PubMed, Web of Science, and IEEE databases from January 2018 to December 2023, extracting information about the medical domain, imaging modalities, methods for addressing cross-domain issues, experimental designs, and datasets from the selected papers. Moreover, we compared the performance of methods in stroke lesion segmentation, white matter segmentation and brain tumor segmentation. Results: A total of 71 studies were included and analyzed in this review. The methods for tackling the cross-domain problem include Transfer Learning, Normalization, Unsupervised Learning, Transformer models, and Convolutional Neural Networks (CNNs). On the ATLAS dataset, domain-adaptive methods showed an overall improvement of ~3 percent in stroke lesion segmentation tasks compared to non-adaptive methods. However, given the diversity of datasets and experimental methodologies in current studies based on the methods for white matter segmentation tasks in MICCAI 2017 and those for brain tumor segmentation tasks in BraTS, it is challenging to intuitively compare the strengths and weaknesses of these methods. Conclusion: Although various techniques have been applied to address the cross-domain problem in brain image segmentation, there is currently a lack of unified dataset collections and experimental standards. For instance, many studies are still based on n-fold cross-validation, while methods directly based on cross-validation across sites or datasets are relatively scarce. Furthermore, due to the diverse types of medical images in the field of brain segmentation, it is not straightforward to make simple and intuitive comparisons of performance. These challenges need to be addressed in future research.

Enhancing brain tumor detection in MRI with a rotation invariant Vision Transformer.

Background: The Rotation Invariant Vision Transformer (RViT) is a novel deep learning model tailored for brain tumor classification using MRI scans. Methods: RViT incorporates rotated patch embeddings to enhance the accuracy of brain tumor identification. Results: Evaluation on the Brain Tumor MRI Dataset from Kaggle demonstrates RViT's superior performance with sensitivity (1.0), specificity (0.975), F1-score (0.984), Matthew's Correlation Coefficient (MCC) (0.972), and an overall accuracy of 0.986. Conclusion: RViT outperforms the standard Vision Transformer model and several existing techniques, highlighting its efficacy in medical imaging. The study confirms that integrating rotational patch embeddings improves the model's capability to handle diverse orientations, a common challenge in tumor imaging. The specialized architecture and rotational invariance approach of RViT have the potential to enhance current methodologies for brain tumor detection and extend to other complex imaging tasks.

TRP-2 / gp100 DNA vaccine and PD-1 checkpoint blockade combination for the treatment of intracranial tumors.

Intracranial tumors present a significant therapeutic challenge due to their physiological location. Immunotherapy presents an attractive method for targeting these intracranial tumors due to relatively low toxicity and tumor specificity. Here we show that SCIB1, a TRP-2 and gp100 directed ImmunoBody® DNA vaccine, generates a strong TRP-2 specific immune response, as demonstrated by the high number of TRP2-specific IFNγ spots produced and the detection of a significant number of pentamer positive T cells in the spleen of vaccinated mice. Furthermore, vaccine-induced T cells were able to recognize and kill B16HHDII/DR1 cells after a short in vitro culture. Having found that glioblastoma multiforme (GBM) expresses significant levels of PD-L1 and IDO1, with PD-L1 correlating with poorer survival in patients with the mesenchymal subtype of GBM, we decided to combine SCIB1 ImmunoBody® with PD-1 immune checkpoint blockade to treat mice harboring intracranial tumors expressing TRP-2 and gp100. Time-to-death was significantly prolonged, and this correlated with increased CD4+ and CD8+ T cell infiltration in the tissue microenvironment (TME). However, in addition to PD-L1 and IDO, the GBM TME was found to contain a significant number of immunoregulatory T (Treg) cell-associated transcripts, and the presence of such cells is likely to significantly affect clinical outcome unless also tackled.

A kinome drug screen identifies multi-TKI synergies and ERBB2 signaling as a therapeutic vulnerability in MYC/TYR subgroup ATRTs.

BACKGROUND: Atypical Teratoid Rhabdoid Tumor (ATRT) is a rare, devastating, and largely incurable pediatric brain tumor. Although recent studies have uncovered three molecular subgroups of ATRTs with distinct disease patterns, and signaling features, the therapeutic profiles of ATRT subgroups remain incompletely elucidated. METHODS: We examined the effect of 465 kinase inhibitors on a panel of ATRT subgroup-specific cell lines. We then applied multi-omics analyses to investigate the underlying molecular mechanism of kinase inhibitor efficacy in ATRT subgroups. RESULTS: We observed that ATRT cell lines are broadly sensitive to inhibitors of the PI3K and MAPK signaling pathways, as well as CDKs, AURKA/B kinases, and PLK1. We identified two classes of multi-kinase inhibitors (MKIs) predominantly targeting receptors tyrosine kinase (RTKs) including PDGFR and EGFR/ERBB2 in MYC/TYR ATRT cells. The PDGFRB inhibitor, Dasatinib, synergistically affected MYC/TYR ATRT cell growth when combined with broad-acting PI3K and MAPK pathway inhibitors, including Rapamycin and Trametinib. We observed that MYC/TYR ATRT cells were also distinctly sensitive to various inhibitors of ERBB2 signaling. Transcriptional, H3K27Ac ChIPSeq, ATACSeq, and HiChIP analyses of primary MYC/TYR ATRTs revealed ERBB2 expression which correlated with differential methylation and activation of a distinct enhancer element by DNA looping. Significantly, we show the brain penetrant EGFR/ERBB2 inhibitor, Afatinib, specifically inhibited in vitro and in vivo growth of MYC/TYR ATRT cells. CONCLUSIONS: Taken together our studies suggest combined treatments with PDGFR and ERBB2-directed TKIs with inhibitors of the PI3K and MAPK pathways as an important new therapeutic strategy for the MYC/TYR subgroup of ATRTs.

Awake craniotomy in pediatric low-grade glioma: barriers and future directions.

INTRODUCTION: The goal of surgical management in pediatric low-grade gliomas (pLGGs) is gross total resection (GTR), as it is considered curative with favorable long-term outcomes. Achieving GTR can be challenging in the setting of eloquent-region gliomas, in which resection may increase risk of neurological deficits. Awake craniotomy (AC) with intraoperative neurofunctional mapping (IONM) offers a promising approach to achieve maximal resection while preserving neurological function. However, its adoption in pediatric cases has been hindered, and barriers to its adoption have not previously been elucidated. FINDINGS: This review includes two complementary investigations. First, a survey study was conducted querying pediatric neurosurgeons on their perceived barriers to the procedure in children with pLGG. Next, these critical barriers were analyzed in the context of existing literature. These barriers included the lack of standardized IONM techniques for children, inadequate surgical and anesthesia experience, concerns regarding increased complication risks, doubts about children's ability to tolerate the procedure, and perceived non-indications due to alternative monitoring tools. CONCLUSION: Efforts to overcome these barriers include standardizing IONM protocols, refining anesthesia management, enhancing patient preparation strategies, and challenging entrenched beliefs about pediatric AC. Collaborative interdisciplinary efforts and further studies are needed to establish safety guidelines and broaden the application of AC, ultimately improving outcomes for children with pLGG.

TULIPs decorate the three-dimensional genome of PFA ependymoma.

Posterior fossa group A (PFA) ependymoma is a lethal brain cancer diagnosed in infants and young children. The lack of driver events in the PFA linear genome led us to search its 3D genome for characteristic features. Here, we reconstructed 3D genomes from diverse childhood tumor types and uncovered a global topology in PFA that is highly reminiscent of stem and progenitor cells in a variety of human tissues. A remarkable feature exclusively present in PFA are type B ultra long-range interactions in PFAs (TULIPs), regions separated by great distances along the linear genome that interact with each other in the 3D nuclear space with surprising strength. TULIPs occur in all PFA samples and recur at predictable genomic coordinates, and their formation is induced by expression of EZHIP. The universality of TULIPs across PFA samples suggests a conservation of molecular principles that could be exploited therapeutically.

The feasibility of robot assisted laser interstitial thermal therapy (LITT) for brain tumors in octogenarians.

BACKGROUND: The use of robot assisted laser interstitial thermal therapy (LITT) is emerging as a viable treatment option for brain tumors patients aged between 80-90 years (octogenarians). Correspondingly the aim of this study was to describe the clinical feasibility of octogenarians undergoing LITT procedure for brain tumors at our institution. METHODS: A retrospective review was conducted of all robot assisted LITT procedures performed at our institution between 2013-2023 for octogenarians. Comparison of continuous variables was by student t-tests, and Kaplan-Meier estimates were used to estimate survival outcomes. RESULTS: A total of 20/311 (6%) LITT patients in the search cohort were octogenarians. Mean age was 82.6 years (range, 80.1-88.0) with 13 (65%) females. Brain tumor lesions most commonly were located on the left side (65%), and for ablation, all were single trajectories with mean number of 2.3 ablations. No operative complications were seen during hospitalization, with mean length of stay of 1.6 days and most common disposition destination being home (95%). There were no 30- or 90-day readmissions or emergency room presentations. Mean follow-up was 12.4 months without any complications in that time. The most common pathology in our cohort was glioblastoma (GBM, 55%). CONCLUSION: Robot assisted LITT is a safe and effective treatment option for brain tumors in octogenarians with a very low morbidity risk. Therefore, further investigations is required to understand how LITT can translate to therapeutic benefit in patients aged over 80 years old with brain tumors.

Optimizing outpatient neurosurgery: evaluating ambulatory surgery and same-day discharge following intracranial tumor surgery and endoscopic third ventriculostomy.

OBJECTIVE: Outpatient surgery and same-day discharge are developing fields that align with the evolving needs of modern healthcare, presenting a notable advantage by reducing patient susceptibility to nosocomial infections, thromboembolic complications, and medical errors. When paired with enhanced recovery after surgery protocols, they hold promise in safely transitioning certain patients undergoing cranial surgery to outpatient care. This study aimed to evaluate discharge on the same day of surgery after intracranial tumor resection and endoscopic third ventriculostomy (ETV) and to investigate potential associations with anesthesia methods, complications, and readmission rates. METHODS: A retrospective analysis of patients scheduled for planned discharge on the same day of surgery between August 2020 and October 2023 was conducted. Data included patient demographic characteristics, preoperative clinical deficits, diagnosis, findings on preoperative and postoperative MRI, lesion characteristics, complications, and readmission rates. RESULTS: A total of 202 patients were included in the study. The mean age was 56.8 years and 117 (57.9%) patients were female. Patients were admitted the evening before surgery to obtain preoperative clearance and undergo MRI. The most common diagnoses were metastasis (23.3%), meningioma (20.8%), glioblastoma (12.4%), and low-grade glioma (10.4%). Craniotomy (46.5%), stereotactic needle biopsy (35.1), and ETV (6.9%) were the most common procedures performed. Thirteen (6.4%) patients underwent awake craniotomy, and 189 (93.6%) surgical procedures were conducted under general anesthesia. Complications occurred in 1.5% of patients, with no permanent complications observed during a mean follow-up of 9.3 months. In total, 179 (88.6%) patients were successfully discharged on the same day of surgery. The median length of hospitalization was 26.8 hours, with the median length of postoperative stay being 7 hours. Twenty-three (11.4%) patients were deemed ineligible for discharge on postoperative day 0 and instead discharged on postoperative day 1. The reasons for these delays included further clinical monitoring (n = 12), social factors (n = 4), and patient preference (n = 7). Age was positively correlated with length of hospitalization (p = 0.006). In total, 6.4% of patients were readmitted within 1-30 days after discharge, with 2.5% readmitted to the department of neurosurgery. CONCLUSIONS: This study demonstrates the safety and feasibility of discharge on the same day of surgery, with a high success rate and low complication rates. Early discharge did not increase morbidity or readmission rates. Implementation of clear discharge protocols and thorough patient education are crucial for successful same-day discharge programs in neurosurgery.

Value of the Acute Physiology and Chronic Health Evaluation II (APACHE II) score in predicting hospital mortality for postoperative brain tumor patients in intensive care units in Japan: A retrospective case-control study.

OBJECTIVE: Acute Physiology and Chronic Health Evaluation II (APACHE II) is based on the data of intensive care unit (ICU) patients and often correlates with disease severity and prognosis. However, no prognostic predictors exist based on ICU admission data for patients with brain tumors, and no studies have reported an association between APACHE II and prognosis in patients with brain tumors. The Japanese Intensive Care Patients Database (JIPAD) was established to improve the quality of care delivered in intensive care medicine in Japan. We used JIPAD to examine factors associated with in-hospital mortality based on available data of postoperative patients with brain tumors admitted to the ICU. METHODS: Patients aged ≥16 years enrolled in JIPAD between April 2015 and March 2018 after surgical brain tumor resection or biopsy of brain tumors. We examined factors related to outcomes at discharge based on blood tests and medical procedures performed during ICU admission, tumor type, and APACHE II score. RESULTS: Among the 1454 patients (male:female ratio: 1:1.1, mean age: 62 years) in the study, 32 (2.2 %) died during hospital stay. In multivariate analysis, male sex (odds ratio [OR] 2.70, [95 % confidence interval, CI 1.22-6.00]), malignant tumor (OR 2.51 [95 % CI 1.13-5.55]), and APACHE II score ≥15 (OR 2.51 [95 % CI 3.08-14.3]) were significantly associated with in-hospital mortality. CONCLUSION: By picking up cases with a high risk of in-hospital death at an early stage, it is possible to improve methods of treatment and support for the patient's family.