Treatment Of Brain Tumors Research Articles

An Update on Recent Drug Delivery Systems Targeting Brain Diseases via the Transnasal Pathway.

To explore the potential of transnasal drug delivery systems (DDS) as an effective means of bypassing the bloodbrain barrier (BBB) for enhanced central nervous system (CNS) targeting, aiming to improve therapeutic outcomes for CNS disorders while reducing systemic side effects. A review of current and emerging DDS technologies, including polymer nanoparticles, liposomes, and micelles, was conducted to assess their suitability for precision-targeted delivery to the brain through the transnasal route. The investigated DDS demonstrate promising capabilities for CNS targeting via the nasal pathway, effectively preserving both the nasal mucosa and CNS integrity. These systems enhance drug precision within neural tissues, potentially improving therapeutic outcomes without harming adjacent tissues. Transnasal DDS offer a promising alternative to traditional delivery methods, with significant potential to advance the treatment of cerebrovascular diseases, neurodegenerative disorders, brain tumors, and psychiatric conditions. This approach represents an evolving frontier in neurotherapeutics, with the potential to transform CNS drug delivery practices.

Artificial Intelligence-based Enhanced Brain Tumor Prediction: A Comprehensive Investigation of Machine Learning and Deep Learning

Brain tumors pose a significant threat to patients’ quality of life and survival rates, with traditional diagnostic methods often falling short due to their time-consuming nature and susceptibility to high misdiagnosis rates. Recent progress in Artificial Intelligence (AI), especially in Machine Learning (ML) and Deep Learning (DL), offer promising alternatives for the prediction and diagnosis of brain tumors. AI models, including Support Vector Machine (SVM), Random Forests, Logistic Regression, Artificial Neural Network (ANN), Convolutional Neural Network (CNN), and Long Short-Term Memory (LSTM) models networks, have demonstrated superior performance in processing complex medical data, thereby enhancing predictive accuracy and aiding clinical decision-making. This review systematically evaluates the application of these AI techniques in brain tumor prediction, highlighting their strengths and limitations, as well as the challenges faced in terms of model interpretability, data applicability, and patient privacy. Furthermore, this paper explored future prospects for improving model interpretability, transfer learning and domain adaptation for enhancing model applicability, and federated learning for preserving patient privacy. By addressing these issues, Artificial Intelligence can significantly advance brain tumor diagnosis and treatment, ultimately improving patient outcomes.

Sleep disorders associated with cranial radiation - a systematic review.

Radiation is standard-of-care treatment for primary brain tumors but may have profound effects on sleep that have not yet been fully characterized. This systematic review aims to further our understanding of radiation therapy on risk of development of sleep disorders in patients with primary brain tumors (PBTs), as well as potential opportunities for prevention and treatment. A systematic search of PubMed, Embase, and Web of Science was performed (last Jan 2024) with predefined inclusion (PBT patients, radiation therapy, somnolence/circadian disruption) and exclusion (reviews/abstracts/cases/chapters, non-PBT cancer, lack of radiation) criteria, yielding 267 papers initially and 38 studies included. Data extraction and analysis (descriptive statistics, individual study summary) focused on incidence of sleep disturbances, radiation types/doses, and pharmacologic interventions. Risk of bias assessment was conducted with Effective Public Health Practice Project's Quality Assessment Tool for Quantitative Studies. The included 38 studies (n=2948 patients) demonstrated high incidence of sleep disturbances in patients with primary brain tumors throughout radiation therapy, but primarily from the end of radiation to 6 months after. Sleep symptoms were associated with radiation (dose-dependent), and pharmacotherapies were helpful in patients with formal sleep disorder diagnoses. Terminology and incidence reporting of sleep symptoms are inconsistent, and many studies had high risk of bias. This systematic review highlights the ongoing challenges with sleep symptoms/disorders related to cranial irradiation treatment in the primary brain tumor population. Further investigations on the interconnectedness of sleep disturbance constructs and possible pharmacotherapies to alleviate symptoms are warranted.

An intracerebral microdialysis study to determine the neuropharmacokinetics of eribulin in patients with metastatic or primary brain tumors.

Eribulin is an inhibitor of microtubule dynamics. It is not as highly protein bound as the taxanes and is less vulnerable to extrusion by P-glycoprotein in the blood-brain barrier (BBB). These features predict that eribulin could play an active role in managing brain tumors. Indeed, the small amount of published clinical data indicates eribulin may have some efficacy against breast cancer brain metastases. To better understand the potential of eribulin for treating brain tumors, we performed an intracerebral microdialysis study to determine the neuropharmacokinetics of eribulin in cancer patients undergoing tumor resection. After tumor removal, two microdialysis catheters were inserted into peritumoral brain tissue. Approximately 24h after surgery, a single dose of eribulin 1.4mg/m2 was administered intravenously. Dialysate samples were collected continuously for 72h, with plasma samples collected in parallel. Eribulin concentrations were analyzed by tandem mass spectrometry. Dialysate samples from 12 intracerebral microdialysis catheters placed in 7 study participants were included in the analysis. A statistically significant difference was observed between eribulin concentrations in brain tissue where BBB was disrupted versus intact, with a difference in mean maximum concentrations on log2 scale of 3.37 (std err = 0.59, p-value = 0.005). Nonetheless, overall brain to plasma ratios of eribulin only ranged from 0.13 to 1.99%. Although we could detect higher concentrations of eribulin in brain tissue where BBB was disrupted, intracerebral eribulin levels were not sufficient to predict eribulin would have consistent clinically meaningful activity against tumors in the brain. NCT02338037 (January 9, 2015).

Anatomy-guided resections for paralimbic tumors in the temporo-insular region: combining tumor and epilepsy surgery concepts.

Tumors in the temporo-mesial region often extend into the insula and vice versa. The present study investigated the results of a surgical strategy that combines principles of tumor and epilepsy surgery. We retrospectively analyzed 157 consecutive patients with intrinsic brain tumors in the temporo-mesial region, with varying degrees of extensions into the insula (44 patients, 28.0%). The surgical strategy utilized "anatomy-guided resection," targeting specific anatomical compartments infiltrated by the tumor (e.g., temporal pole, anterior temporo-mesial region = uncus and hippocampal head, posterior temporo-mesial, insula) rather than treating the tumor as a single mass. The most frequent histologies were ganglioglioma CNS WHO grade 1 (55 patients, 35.0%) and IDH1 wildtype glioblastoma (36 patients, 22.9%). Tumor infiltration was most commonly found in the anterior temporo-mesial compartment (145 patients, 92.4%). An anterior temporal lobectomy was part of the surgical strategy in 131 cases (83.4%). Seventy-six patients (48.4%) with drug-resistant epilepsy underwent a formal presurgical epilepsy work-up, including depth electrode placement in three cases. Complete resections were achieved in 117 patients (74.5%), with supramarginal resections performed in 89 cases (56.7%). Four patients experienced non-temporary neurological complications (CTCAE grade 3-5). At 6 months, 127 of 147 assessable patients (86.4%) were free from seizures or auras (ILAE class 1), excluding early postoperative seizures (<30 days). At 24 months, 122 of 144 assessable cases (84.7%) remained seizure-free (ILAE class 1). Kaplan-Meier estimates for 5-year overall survival were 98.5% for non-recurrent glioneuronal tumors. The 2-year overall survival estimates were 96.0% for 24 primary diffuse CNS WHO grade 2 and 3 gliomas and 55.2% for 30 patients undergoing first surgeries for glioblastomas/astrocytomas CNS WHO grade 4. Combining both epilepsy and tumor surgery concepts in the surgical treatment of intrinsic brain tumors involving the mesial temporal lobe, often extending into the insula, led to more extensive resections, improved seizure outcomes, and potentially even better patient survival outcomes.

Clinical trial design for novel targeted agents in neuro-oncology.

Biomarker-based clinical trials investigating targeted treatments for brain tumors have surged due to better access to biomarker testing and a deeper grasp of the molecular basis of tumor development. The design of clinical trials is crucial for evaluating safety, confirming effectiveness, and affirming the clinical advantage of novel agents, with the goal of approval by regulatory authorities to expand patient treatment options. Given some challenges unique to brain tumors, early-stage clinical trials for novel targeted agents must integrate pharmacokinetics and tissue-based pharmacodynamic assessments to establish timely go-no-go decisions for larger studies. Surgical window-of-opportunity trials can allow for the comparison of treated and untreated tumor samples, verifying target engagement and its modulatory effects for evidence of biological activity. Due to the challenges of achieving the required sample sizes to power efficacy analyses, later-stage trials of targeted therapies can include basket trials which test one drug on multiple tumor types, while umbrella trials evaluate several biomarkers within a single histology. Platform trials can also be leveraged to investigate multiple biomarker-driven hypotheses within a unified protocol and can incorporate Bayesian algorithms for adaptive randomization. Selecting appropriate endpoints, such as progression-free survival or overall response rate, is crucial and novel response assessment criteria need to be considered in the context of the tumor and therapy being investigated. Lastly, inclusivity in trials is essential to address health disparities and engage diverse patient populations to ensure real-world impact. Future trials should build upon the knowledge gained from both initial achievements and past setbacks in the field.

An update on the role of focused ultrasound in neuro-oncology

Purpose of review Brain tumor treatment presents challenges for patients and clinicians, with prognosis for many of the most common brain tumors being poor. Focused ultrasound (FUS) can be deployed in several ways to circumvent these challenges, including the need to penetrate the blood–brain barrier and spare healthy brain tissue. This article reviews current FUS applications within neuro-oncology, emphasizing ongoing or recently completed clinical trials. Recent findings Most clinical interest in FUS for neuro-oncology remains focused on exploring BBB disruption to enhance the delivery of standard-of-care therapeutics. More recently, the application of FUS for radiosensitization, liquid biopsy, and sonodynamic therapy is garnering increased clinical attention to assist in tumor ablation, early detection, and phenotypic diagnosis. Preclinical studies show encouraging data for the immunomodulatory effects of FUS, but these findings have yet to be tested clinically. Summary FUS is a burgeoning area of neuro-oncology research. Data from several forthcoming large clinical trials should help clarify its role in neuro-oncology care.

Early region-specific impact of adjuvant radiation therapy on cognition and quality of life in adult patients with primary brain tumors.

While treatments for primary brain tumors increase survival, they have cognitive sequelae. Neurocognition's anatomical distribution makes it susceptible to brain damage. This study aims to evaluate the contribution of radiotherapy on short-term cognitive impairment. Using a prospective database of cognitive rehabilitation in adults operated on for primary brain tumors, a retrospective sub-analysis of the contribution of radiotherapy was performed. Thirty-four subdivisions of 12 neurocognitive regions were delineated in 48 irradiated patients and 30 non-irradiated patients. In the first group, the correlation between radiation dose and deterioration was evaluated. In all patients, the impact of tumor and surgical changes on dysfunction was calculated and compared with dose-dependent response. The correlation between cognitive status and radiation dose is especially strong and significant in the left hemisphere and in specific subdivisions such as the posterior hippocampus or the dorsolateral prefrontal cortex, with the left prevailing over posterior dominance. Memory is the most affected domain 1month after radiotherapy, as attention is three months later. The hippocampus is involved in various cognitive domains in addition to memory. The prefrontal subregions and the genu of the corpus callosum are more affected by the relationship with disease and surgical changes than by radiation exposure. Patients ongoing a course of radiotherapy do not benefit from concurrent cognitive rehabilitation. There is a correlation between the dose of radiation received by several encephalic regions and degree of short-term domain-specific cognition decline, considering other factors of risk and cognitive rehabilitation.

PDOC-12 PEDIATRIC BRAIN TUMOR INCIDENCE, AND TREATMENT MODALITY AT KILIMANJARO CHRISTIAN MEDICAL CENTER

Abstract INTRODUCTION Pediatric brain tumors (PBT) a significant health concern, they are the primary cause of cancer-related deaths among children. PBTs in Low- and Middle-Income Countries are diagnosed late due to insufficient resources. This abstract describes Pediatric Brain tumor incidence and treatment modalities at Kilimanjaro Christian Medical Center (KCMC) Cancer Care Center (CCC), Moshi, Tanzania from December 2016 to March 2024. METHOD Data on pediatric patients treated at the CCC between Dec. 2016 and March 2024, were analyzed. Inclusion criteria were a primary brain tumor and patients aged 0-19 at the time of diagnosis. All patients were previously diagnosed by computer tomography/ magnetic resonance imaging. Variables retrospectively collected from patient’s medical records were: demographic characteristics (age, gender, Place of residence, and insurance status), previous history of malignant diseases, incidence date, and treatment modality. RESULTS Total of 748 cases of pedeatric cancer were diagnosed at CCC. Of all the pediatric cancers diagnosed, brain cancer accounted for 22(2.9%). Out of these cases of brain cancer, 63.6% were males and 36.4% were females.Majority of them came within the Kilimanjaro region. 41% were palliated while 59% had a curative intent at the time of diagnosis, 22.7% died between December 2016 to March 2024.Embryonal tumors were (40.9%) with a breakdown that includes 6 Medulloblastoma and 3 cases of Craniopharyngioma (teratoid/rhabdoid), gliomas (36.4%) with sub-types such as Ependymoma, Anaplastic Astrocytoma, Pilocytic Astrocytoma, Pineocytoma, Stem glioma, and Tectal glioma, unspecified cases (13.6%), and Pineoblastoma were (9.1%). Surgery was used in 40.9% of cases, radiotherapy in 31.8%, and chemotherapy in 72.7%. Chemoradiotherapy was used in 31.8% of cases. 13.6% of cases utilized a combined approach, including chemotherapy, radiotherapy, and surgery. CONCLUSION PBT incidence at KCMC is 2.9%, improving access to screening, accurate diagnosis and treatment modalities are essential in identifying and managing PBT in our setting.

Multi Graded Brain Tumor Classification using YOLOv7

In recent years, significant progress has been made in the field of diagnosis and classification of brain tumors, mainly attributed to advancements in artificial intelligence and medical imaging. The main objective of this study is to improve the detection and classification of brain tumors by applying and utilizing of artificial intelligence (AI) and recent advancements in medical imaging techniques. Automation of the process of tumor identification and then classification, in addition to tumor grading, will definitely improve all procedures of brain tumor treatment and enhance patient care. The proposed system combines convolutional neural networks (CNNs), which act as extract features, and the You Only Look Once Algorithm (YOLOv7) for effective object identification and accurate classification. The methodology described in this study involves employing a technique of multilayer classification, which integrates three distinct datasets. This comprehensive approach shows an exceptional levels of accuracy and precision. At the initial level, the model attains a 99.78% accuracy in distinguishing between tumor and nontumor cases. At the next level the system accurately sorts types of brain tumors (such, as glioma, meningioma and pituitary tumors) with an average accuracy of 99.35%. Moving on to the final stage it successfully distinguishes between low grade and high grade glioma tumors with a precision of 93.07%. Moreover the model shows accuracies ranging from 99.41%, to 99.61% when classifying types of brain tumors and nontumor cases. The proposed system has the ability to determine the boundaries of the tumor, and thus this has helped in calculating the sizes of tumors with high accuracy. Index Terms- Brain tumor, MRI, Convolutional Neural Network, YOLO, Tumor grading.

Validation of GAMOS Monte Carlo simulation for 131Cs brachytherapy source in water and dosimetric characterization of solid water, bone, and brain tissues

PurposeThe treatment of brain tumours using permanently implanted 131Cs has become more frequent since GammaTile brachytherapy platform was cleared by the U.S. Food and Drug Administration (FDA). Current treatment planning systems (TPS) (BrachyVision v11.0.47, Varian Medical Systems, Palo Alto, CA, USA) used clinically do not account for anatomical heterogeneities. GAMOS Monte Carlo simulation was validated for the dose deposited by 131Cs in water and used to accurately determine the dose deposited in simulated human tissues, including bone and brain tissue, as well as in Solid Water (SW) phantom material. MethodGAMOS was validated and benchmarked for dose deposited by 131Cs (CS-1 Rev2) in water. The evaluation performed included air-kerma strength, radial dose function, anisotropy function, and dose rate constant based on the recommendation of TG-43U1S2 protocol. Dosimetric simulation of the 131Cs brachytherapy source was also performed in SW, bone, and brain tissue using GAMOS. Conversion factors were calculated by the ratio of the dose rate constant from water to SW, bone, and brain tissue, respectively. ResultResults for dose in water were benchmarked with MCNP simulation and experiential data published in the TG-43U1S2. The dose rate constant in water was 1.039 ± 0.017 cGy h−1 U−1 which is consistent with the results used to determine the TG-43U1S2 consensus data. The conversion factor of water to SW, water to the bone, and water to brain tissue were 0.936, 1.15, and 0.964, respectively. ConclusionOther Monte Carlo (MC) simulation codes, such as MCNP, have been previously used in the literature to determine the dose deposited by 131Cs. In this work, doses deposited by 131Cs radioactive sources were successfully simulated using GAMOS MC simulation. To our knowledge, this is the first time that GAMOS was used to simulate the dose deposited by 131Cs seed. MC simulation of dose for brachytherapy sources is especially important to accurately estimate the dose deposited in high Z materials such as skull bone, which may be widely different than the dose calculated by the TG-43U1S2 formalism.

Therapeutic Effect of Boron Neutron Capture Therapy on Boronophenylalanine Administration via Cerebrospinal Fluid Circulation in Glioma Rat Models.

In recent years, various drug delivery systems circumventing the blood-brain barrier have emerged for treating brain tumors. This study aimed to improve the efficacy of brain tumor treatment in boron neutron capture therapy (BNCT) using cerebrospinal fluid (CSF) circulation to deliver boronophenylalanine (BPA) to targeted tumors. Previous experiments have demonstrated that boron accumulation in the brain cells of normal rats remains comparable to that after intravenous (IV) administration, despite BPA being administered via CSF at significantly lower doses (approximately 1/90 of IV doses). Based on these findings, BNCT was conducted on glioma model rats at the Kyoto University Research Reactor Institute (KUR), with BPA administered via CSF. This method involved implanting C6 cells into the brains of 8-week-old Wistar rats, followed by administering BPA and neutron irradiation after a 10-day period. In this study, the rats were divided into four groups: one receiving CSF administration, another receiving IV administration, and two control groups without BPA administration, with one subjected to neutron irradiation and the other not. In the CSF administration group, BPA was infused from the cisterna magna at 8 mg/kg/h for 2 h, while in the IV administration group, BPA was intravenously administered at 350 mg/kg via the tail vein over 1.5 h. Thermal neutron irradiation (5 MW) for 20 min, with an average fluence of 3.8 × 1012/cm2, was conducted at KUR's heavy water neutron irradiation facility. Subsequently, all of the rats were monitored under identical conditions for 7 days, with pre- and post-irradiation tumor size assessed through MRI and pathological examination. The results indicate a remarkable therapeutic efficacy in both BPA-administered groups (CSF and IV). Notably, the rats treated with CSF administration exhibited diminished BPA accumulation in normal tissue compared to those treated with IV administration, alongside maintaining excellent overall health. Thus, CSF-based BPA administration holds promise as a novel drug delivery mechanism in BNCT.

A thermo-responsive chemically crosslinked long-term-release chitosan hydrogel system increases the efficiency of synergy chemo-immunotherapy in treating brain tumors

Glioblastoma multiforme (GBM) is an aggressive and common brain tumor. The blood-brain barrier prevents several treatments from reaching the tumor. This study proposes a Chemo-Immunotherapy synergy treatment chemically crosslinked hydrogel system that is injected into the tumor to treat GBM. The strategy uses doxorubicin and BMS-1 with a thermo-responsive and chemically crosslinked hydrogel for extended drug release into the affected area. The hydrogels are produced by mixing with Chitosan (Chi), modified Pluronic F-127 (PF-127) with aldehyde end group and doxorubicin and then chemically crosslinking the aldehyde and amine bonds to increase the drug retention time. PF-127-CHO/Chi, which gels at body temperatures and chemically crosslinks between PF-127-CHO and Chitosan, increases the time that the drug remains in the affected area and prevents the hydrogel from swelling and compressing surrounding tissue. The drug is released from the chemically crosslinked hydrogels, prevents tumor progression and increases survival for subjects with GBM tumors. The Synergy Chemo-Immunotherapy also allows more efficient treatment of GBM than chemotherapy. The PF-127-CHO/Chi DOX and BMS-1 group have a tumor that is 43 times smaller than the untreated group. These results show that the proposed chemically crosslinking hydrogel is an efficient intratumoral delivery platform for the treatment of tumors.

Cost-effectiveness of proton beam therapy vs. conventional radiotherapy for patients with brain tumors in Sweden: results from a non-randomized prospective multicenter study

BackgroundThis study assessed the cost-effectiveness of proton beam therapy (PBT) compared to conventional radiotherapy (CRT) for treating patients with brain tumors in Sweden.MethodsData from a longitudinal non-randomized study performed between 2015 and 2020 was used, and included adult patients with brain tumors, followed during treatment and through a one-year follow-up. Clinical and demographic data were sourced from the longitudinal study and linked to Swedish national registers to get information on healthcare resource use. A cost-utility framework was used to evaluate the cost-effectiveness of PBT vs. CRT. Patients in PBT group (n = 310) were matched with patients in CRT group (n = 40) on relevant observables using propensity score matching with replacement. Costs were estimated from a healthcare perspective and included costs related to inpatient and specialized outpatient care, and prescribed medications. The health outcome was quality-adjusted life-years (QALYs), derived from the EORTC-QLQ-C30. Generalized linear models (GLM) and two-part models were used to estimate differences in costs and QALYs.ResultsPBT yielded higher total costs, 14,639 US$, than CRT, 13,308 US$, with a difference of 1,372 US$ (95% CI, -4,914–7,659) over a 58 weeks’ time horizon. Further, PBT resulted in non-significantly lower QALYs, 0.746 compared to CRT, 0.774, with a difference of -0.049 (95% CI, -0.195–0.097). The probability of PBT being cost-effective was < 30% at any willingness to pay.ConclusionsThese results suggest that PBT cannot be considered a cost-effective treatment for brain tumours, compared to CRT.Trial registrationNot applicable.

Pluronic F127-Complexed PEGylated Poly(glutamic acid)-Cisplatin Nanomedicine for Enhanced Glioblastoma Therapy.

Glioblastoma is one of the most aggressive and treatment-resistant forms of primary brain cancer, posing significant challenges in effective therapy. This study aimed to enhance the effectiveness of glioblastoma therapy by developing a unique nanomedicine composed of Pluronic F127-complexed PEGylated poly(glutamic acid)-cisplatin (PLG-PEG/PF127-CDDP). PLG-PEG/PF127-CDDP demonstrated an optimal size of 133.97±12.60nm, facilitating efficient cell uptake by GL261 glioma cells. In vitro studies showed significant cytotoxicity against glioma cells with a half-maximal (50%) inhibitory concentration (IC50) of 12.61µgmL-1 at 48h and a 72.53%±1.89% reduction in cell invasion. Furthermore, PLG-PEG/PF127-CDDP prolonged the circulation half-life of cisplatin to 9.75h in vivo, leading to a more than 50% reduction in tumor size on day 16 post-treatment initiation in a murine model of glioma. The treatment significantly elevated lactate levels in GL261 cells, indicating enhanced metabolic disruption. Therefore, PLG-PEG/PF127-CDDP offers a promising approach for glioblastoma therapy due to its effects on improving drug delivery efficiency, therapeutic outcomes, and safety while minimizing systemic side effects. This work underscores the potential of polymer-based nanomedicines in overcoming the challenges of treating brain tumors, paving the way for future clinical applications.

Pharmacological Features and Therapeutic Implications of Plumbagin in Cancer and Metabolic Disorders: A Narrative Review.

Plumbagin (PLB) is a naphthoquinone extracted from Plumbago indica. In recent times, there has been a growing body of evidence suggesting the potential importance of naphthoquinones, both natural and artificial, in the pharmacological world. Numerous studies have indicated that PLB plays a vital role in combating cancers and other disorders. There is substantial evidence indicating that PLB may have a significant role in the treatment of breast cancer, brain tumours, lung cancer, hepatocellular carcinoma, and other conditions. Moreover, its potent anti-oxidant and anti-inflammatory properties offer promising avenues for the treatment of neurodegenerative and cardiovascular diseases. A number of studies have identified various pathways that may be responsible for the therapeutic efficacy of PLB. These include cell cycle regulation, apoptotic pathways, ROS induction pathways, inflammatory pathways, and signal transduction pathways such as PI3K/AKT/mTOR, STAT3/PLK1/AKT, and others. This review aims to provide a comprehensive analysis of the diverse pharmacological roles of PLB, examining the mechanisms through which it operates and exploring its potential applications in various medical conditions. In addition, we have conducted a review of the various formulations that have been reported in the literature with the objective of enhancing the efficacy of the compound. However, the majority of the reviewed data are based on in vitro and in vivo studies. To gain a comprehensive understanding of the safety and efficacy of PLB in humans and to ascertain its potential integration into therapeutic regimens for cancer and chronic diseases, rigorous clinical trials are essential. Finally, by synthesizing current research and identifying gaps in knowledge, this review seeks to enhance our understanding of PLB and its therapeutic prospects, paving the way for future studies and clinical applications.

A theoretical study on evaluating brain tumor changes in tumor treating fields therapy by impedance detection.

TTFields is a novel FDA-approved technology utilized for treating glioblastoma multiforme (GBM) within the brain. Presently, the effectiveness of therapy is evaluated through MRI imaging at random two-month intervals. Electrical impedance is an important and effective parameter for reflecting changes in tissue properties. In TTFields treatment for brain tumors, electrodes attached to the scalp deliver electric field energy to the tumor region. We hypothesize that these electrodes can also serve as sensors to detect impedance changes caused by tumor alterations in real time, thus continuously assessing the effectiveness of the treatment. In this work, we propose and scrutinize this hypothesis by conducting an in silico study to confirm the potential feasibility of the proposed concept. Our results indicate that the impedance amplitude change measured between opposing TTFields electrode arrays utilizing voltage and frequency of 50 V and 200 kHz (typical TTFields treatment parameters), has enough resolution (> 1mm) and Signal-to-Noise Ratio (> 40 dB) to evaluate tumor size change in the head. The impedance detection technique may be a significant augmentation to TTFields cancer treatment, enabling the continuous evaluation of safety and efficacy throughout the procedure.

Cost of medical care for malignant brain tumors at hospitals in the Japan Clinical Oncology Group brain-tumor study group.

This study aimed to investigate what treatment are selected for malignant brain tumors, particularly glioblastoma (GBM) and primary central nervous system lymphoma (PCNSL), in real-world Japan and the costs involved. We conducted a questionnaire survey regarding treatment selections for newly diagnosed GBM and PCNSL treated between July 2021 and June 2022 among 47 institutions in the Japan Clinical Oncology Group-Brain Tumor Study Group. We calculated the total cost and cost per month of the initial therapy for newly diagnosed GBM or PCNSL. The most used regimen (46.8%) for GBM in patients aged ≤74years was 'Surgery + radiotherapy concomitant with temozolomide'. This regimen's total cost was 7.50 million JPY (Japanese yen). Adding carmustine wafer implantation (used in 15.0%), TTFields (used in 14.1%), and bevacizumab (BEV) (used in 14.5%) to the standard treatment of GBM increased the cost by 1.24 million JPY for initial treatment, and 1.44 and 0.22 million JPY per month, respectively. Regarding PCNSL, 'Surgery (biopsy) + rituximab, methotrexate, procarbazine, and vincristine (R-MPV) therapy' was the most used regimen (42.5%) for patients of all ages. This regimen incurred 1.07 million JPY per month. The three PCNSL regimens based on R-MPV therapy were in ultra-high-cost medical care (exceeding 1 million JPY per month). Treatment of malignant brain tumors is generally expensive, and cost-ineffective treatments such as BEV are frequently used. We believe that the results of this study can be used to design future economic health studies examining the cost-effectiveness of malignant brain tumors.

Dual vision Transformer-DSUNET with feature fusion for brain tumor segmentation

Brain tumors are one of the leading causes of cancer death; screening early is the best strategy to diagnose and treat brain tumors. Magnetic Resonance Imaging (MRI) is extensively utilized for brain tumor diagnosis; nevertheless, achieving improved accuracy and performance, a critical challenge in most of the previously reported automated medical diagnostics, is a complex problem. The study introduces the Dual Vision Transformer-DSUNET model, which incorporates feature fusion techniques to provide precise and efficient differentiation between brain tumors and other brain regions by leveraging multi-modal MRI data. The impetus for this study arises from the necessity of automating the segmentation process of brain tumors in medical imaging, a critical component in the realms of diagnosis and therapy strategy. The BRATS 2020 dataset is employed to tackle this issue, an extensively utilized dataset for segmenting brain tumors. This dataset encompasses multi-modal MRI images, including T1-weighted, T2-weighted, T1Gd (contrast-enhanced), and FLAIR modalities. The proposed model incorporates the dual vision idea to comprehensively capture the heterogeneous properties of brain tumors across several imaging modalities. Moreover, feature fusion techniques are implemented to augment the amalgamation of data originating from several modalities, enhancing the accuracy and dependability of tumor segmentation. The Dual Vision Transformer-DSUNET model's performance is evaluated using the Dice Coefficient as a prevalent metric for quantifying segmentation accuracy. The results obtained from the experiment exhibit remarkable performance, with Dice Coefficient values of 91.47 % for enhanced tumors, 92.38 % for core tumors, and 90.88 % for edema. The cumulative Dice score for the entirety of the classes is 91.29 %. In addition, the model has a high level of accuracy, roughly 99.93 %, which underscores its durability and efficacy in segmenting brain tumors. Experimental findings demonstrate the integrity of the suggested architecture, which has quickly improved the detection accuracy of many brain diseases.

An Overview of Current Progress and Challenges in Brain Cancer Therapy Using Advanced Nanoparticles.

Brain tumors pose significant challenges in terms of complete cure and early-stage prognosis. The complexity of brain tumors, including their location, infiltrative nature, and intricate tumor microenvironment (TME), contributes to the difficulties in achieving a complete cure. The primary objective of brain cancer therapy is to effectively treat brain tumors and improve the patient's quality of life. Nanoparticles (NPs) have emerged as promising tools in this regard. They can be designed to deliver therapeutic drugs to the brain tumor site while also incorporating imaging agents. The NPs with the 10-200 nm range can cross the blood-brain barrier (BBB) and blood-brain tumor barrier (BBTB) and facilitate drug bioavailability. NPs can be designed by several methods to improve the pharmaceutical and pharmacological aspects of encapsulated therapeutic agents. NPs can be developed in various dosage forms to suit different administration routes in brain cancer therapy. The unique properties and versatility of NPs make them essential tools in the fight against brain tumors, offering new opportunities to improve patient outcomes and care. Having the ability to target brain tumors directly, overcome the BBB, and minimize systemic side effects makes NPs valuable tools in improving patient outcomes and care. The review highlights the challenges associated with brain tumor treatment and emphasizes the importance of early detection and diagnosis. The use of NPs for drug delivery and imaging in brain tumors is a promising approach to improving patient outcomes and quality of life. The versatility and unique properties of NPs make them valuable tools in the fight against brain tumors, and NPs have the potential to revolutionize healthcare.