BACKGROUND AND OBJECTIVE

Meningiomas represent the most prevalent benign intracranial tumors, comprising 13- 26% of primary intracranial neoplasms. These tumors derive their blood supply from both extracranial and intracranial circulation. Over recent decades, pre-operative embolization (POE) has emerged as a potential adjunctive therapy to surgery, aiming to reduce tumor vascularity. Our study seeks to explore the potential correlation between the extent of devascularization following POE of meningiomas and intraoperative blood loss.

This cross-sectional study involved nine meningioma patients at a tertiary hospital, involving chart review of patients across four years. These patients were referred for POE due to angiographic evidence of a hypervascular mass between January 2018 and January 2022. We collected demographic data, tumor characteristics (including location, size, and vascular supply), and intraoperative variables such as total operative time and blood loss. Statistical analyses aimed to uncover correlations between vascularization degree and various factors.

Our population consists predominantly of females (53.68%), with a mean age of 45.85 ± 13.65 years. Only one mortality was recorded (7.7%). Pre-operative embolization achieved devascularization in the majority (69.2%) of cases, with approximately two-thirds (66.7%) experiencing complete devascularization. Mean total operative time stood at 336.11 ± 301.88 minutes, with a mean post-operative blood loss of 985.56 ± 1013.72 milliliters. Additionally, for those with recorded recovery times, the mean recovery time was 14.32 ± 13.51 hours.

Mortality rates showed no association with sex, devascularization status, or number of feeding vessel zones. Furthermore, the extent of devascularization did not correlate with age, sex, number of feeding vessel zones, postoperative blood loss, total operative time, or recovery time (p >0.05).

In summary, this study represents a significant endeavor to elucidate factors influencing meningioma outcomes following pre-operative embolization. Despite limitations regarding patient numbers, our study offers valuable insights into operative parameters and embolization considerations for future analyses in our tertiary center.

Background and Objective: Meningiomas represent the most prevalent benign intracranial tumors, comprising 13- 26% of primary intracranial neoplasms. These tumors derive their blood supply from both extracranial and intracranial circulation. Over recent decades, pre-operative embolization (POE) has emerged as a potential adjunctive therapy to surgery, aiming to reduce tumor vascularity. Our study seeks to explore the potential correlation between the extent of devascularization following POE of meningiomas and intraoperative blood loss. Methods: This cross-sectional study involved nine meningioma patients at a tertiary hospital, involving chart review of patients across four years. These patients were referred for POE due to angiographic evidence of a hypervascular mass between January 2018 and January 2022. We collected demographic data, tumor characteristics (including location, size, and vascular supply), and intraoperative variables such as total operative time and blood loss. Statistical analyses aimed to uncover correlations between vascularization degree and various factors. Results: Our population consists predominantly of females (53.68%), with a mean age of 45.85 ± 13.65 years. Only one mortality was recorded (7.7%). Pre-operative embolization achieved devascularization in the majority (69.2%) of cases, with approximately two-thirds (66.7%) experiencing complete devascularization. Mean total operative time stood at 336.11 ± 301.88 minutes, with a mean post-operative blood loss of 985.56 ± 1013.72 milliliters. Additionally, for those with recorded recovery times, the mean recovery time was 14.32 ± 13.51 hours. : Mortality rates showed no association with sex, devascularization status, or number of feeding vessel zones. Furthermore, the extent of devascularization did not correlate with age, sex, number of feeding vessel zones, postoperative blood loss, total operative time, or recovery time (p >0.05). Conclusion In summary, this study represents a significant endeavor to elucidate factors influencing meningioma outcomes following pre-operative embolization. Despite limitations regarding patient numbers, our study offers valuable insights into operative parameters and embolization considerations for future analyses in our tertiary center.
Meningioma ; Radiology, Interventional

Humans ; Meningioma/surgery* ; Tomography, X-Ray Computed ; Meningeal Neoplasms/surgery*

Magnetic resonance-guided focused ultrasound (MRgFUS) is a novel and minimally invasive technology. Since the US Food and Drug Administration approved unilateral ventral intermediate nucleus-MRgFUS for medication-refractory essential tremor in 2016, studies on new indications, such as Parkinson's disease (PD), psychiatric diseases, and brain tumors, have been on the rise, and MRgFUS has become a promising method to treat such neurological diseases. Currently, as the second most common degenerative disease, PD is a research hotspot in the field of MRgFUS. The actions of MRgFUS on the brain range from thermoablation, blood-brain barrier (BBB) opening, to neuromodulation. Intensity is a key determinant of ultrasound actions. Generally, high intensity can be used to precisely thermoablate brain targets, whereas low intensity can be used as molecular therapies to modulate neuronal activity and open the BBB in conjunction with injected microbubbles. Here, we aimed to summarize advances in the application of MRgFUS for the treatment of PD, with a focus on thermal ablation, BBB opening, and neuromodulation, in the hope of informing clinicians of current applications.
Humans ; Parkinson Disease/therapy* ; Brain ; Blood-Brain Barrier ; Essential Tremor/surgery* ; Brain Neoplasms ; Magnetic Resonance Imaging/methods* ; Magnetic Resonance Spectroscopy

Lung cancer has the highest risk of brain metastasis (BM) among all solid carcinomas. The emergence of BM has a significant impact on the selection of oncologic treatment for patients. Immune checkpoint inhibitors (ICIs) are the most promising treatment option for patients without druggable mutations and have been shown to improve survival in patients with non-small cell lung cancer (NSCLC) BM in clinical trials with good safety. Moreover, ICI has shown certain effects in NSCLC BM, and the overall intracranial efficacy is comparable to extracranial efficacy. However, a proportion of patients showed discordant responses in primary and metastatic lesions, suggesting that multiple mechanisms may exist underlying ICI activity in BM. According to studies pertaining to tumor immune microenvironments, ICIs may be capable of provoking immunity in situ . Meanwhile, systematic immune cells activated by ICIs can migrate into the central nervous system and exert antitumor effects. This review summarizes the present evidence for ICI treatment efficacy in NSCLC BM and proposes the possible mechanisms of ICI treatment for NSCLC BMs based on existing evidence.
Humans ; Carcinoma, Non-Small-Cell Lung/drug therapy* ; Lung Neoplasms/drug therapy* ; Immune Checkpoint Inhibitors/therapeutic use* ; Brain Neoplasms/drug therapy* ; Carcinoma ; Tumor Microenvironment

BACKGROUND: Immune checkpoint inhibitors (ICIs) are increasingly used as first-line therapy for patients with advanced non-small cell lung cancer (NSCLC) harboring no actionable mutations; however, data on their efficacy among patients presenting with intracranial lesions are limited. This study aimed to explore the efficacy and safety of ICIs combined with chemotherapy in advanced NSCLC patients with measurable brain metastasis at initial diagnosis. METHODS: Our study retrospectively analyzed clinical data of a total of 211 patients diagnosed with driver gene mutation-negative advanced NSCLC with measurable, asymptomatic brain metastasis at baseline from Hunan Cancer Hospital between January 1, 2019 and September 30, 2021. The patients were stratified into two groups according to the first-line treatment regimen received: ICI combined with chemotherapy ( n = 102) or chemotherapy ( n = 109). Systemic and intracranial objective response rates (ORRs) and progression-free survival (PFS) were analyzed. Adverse events were also compared between the groups. RESULTS: Compared with the chemotherapy-based regimen, the ICI-containing regimen was associated with a significantly higher intracranial (44.1% [45/102] vs . 28.4% [31/109], χ2 = 5.620, P = 0.013) and systemic (49.0% [50/102] vs . 33.9% [37/109], χ2 = 4.942, P = 0.019) ORRs and longer intracranial (11.0 months vs . 7.0 months, P <0.001) and systemic (9.0 months vs . 5.0 months, P <0.001) PFS. Multivariable analysis consistently revealed an independent association between receiving ICI plus platinum-based chemotherapy as a first-line regimen and prolonged intracranial PFS (hazard ratio [HR] = 0.52, 95% confidence interval [CI]: 0.37-0.73, P <0.001) and systemic PFS (HR = 0.48, 95% CI: 0.35-0.66, P <0.001). No unexpected serious adverse effects were observed. CONCLUSION: Our study provides real-world clinical evidence that ICI combined with chemotherapy is a promising first-line treatment option for driver gene mutation-negative advanced NSCLC patients who present with brain metastasis at initial diagnosis. CLINICAL TRIAL REGISTRATION https://www.clinicaltrials.gov/ , OMESIA, NCT05129202.
Humans ; Carcinoma, Non-Small-Cell Lung/genetics* ; Lung Neoplasms/genetics* ; Immune Checkpoint Inhibitors/therapeutic use* ; Retrospective Studies ; Brain Neoplasms/genetics*

BACKGROUND: Breast cancer is one of the most common cancer in women and a proportion of patients experiences brain metastases with poor prognosis. The study aimed to construct a novel predictive clinical model to evaluate the overall survival (OS) of patients with postoperative brain metastasis of breast cancer (BCBM) and validate its effectiveness. METHODS: From 2010 to 2020, a total of 310 female patients with BCBM were diagnosed in The Affiliated Cancer Hospital of Xinjiang Medical University, and they were randomly assigned to the training cohort and the validation cohort. Data of another 173 BCBM patients were collected from the Surveillance, Epidemiology, and End Results Program (SEER) database as an external validation cohort. In the training cohort, the least absolute shrinkage and selection operator (LASSO) Cox regression model was used to determine the fundamental clinical predictive indicators and the nomogram was constructed to predict OS. The model capability was assessed using receiver operating characteristic, C-index, and calibration curves. Kaplan-Meier survival analysis was performed to evaluate clinical effectiveness of the risk stratification system in the model. The accuracy and prediction capability of the model were verified using the validation and SEER cohorts. RESULTS: LASSO Cox regression analysis revealed that lymph node metastasis, molecular subtype, tumor size, chemotherapy, radiotherapy, and lung metastasis were statistically significantly correlated with BCBM. The C-indexes of the survival nomogram in the training, validation, and SEER cohorts were 0.714, 0.710, and 0.670, respectively, which showed good prediction capability. The calibration curves demonstrated that the nomogram had great forecast precision, and a dynamic diagram was drawn to increase the maneuverability of the results. The Risk Stratification System showed that the OS of low-risk patients was considerably better than that of high-risk patients ( P < 0.001). CONCLUSION The nomogram prediction model constructed in this study has a good predictive value, which can effectively evaluate the survival rate of patients with postoperative BCBM.
Female ; Humans ; Breast Neoplasms/surgery* ; Retrospective Studies ; Prognosis ; Brain Neoplasms/surgery* ; Nomograms

Humans ; Stroke Volume ; Incidence ; Goals ; Meningioma/complications* ; Postoperative Complications/epidemiology* ; Fluid Therapy/adverse effects* ; Meningeal Neoplasms/complications*

Patients with glioblastoma (GBM) generally have a bad prognosis and short overall survival after being treated with surgery, chemotherapy or radiotherapy due to the histological heterogeneity, strong invasive ability and rapid postoperative recurrence of GBM. The components of GBM cell-derived exosome (GBM-exo) can regulate the proliferation and migration of GBM cell via cytokines, miRNAs, DNA molecules and proteins, promote the angiogenesis via angiogenic proteins and non-coding RNAs, mediate tumor immune evasion by targeting immune checkpoints with regulatory factors, proteins and drugs, and reduce drug resistance of GBM cells through non-coding RNAs. GBM-exo is expected to be an important target for the personalized treatment of GBM and a marker for diagnosis and prognosis of this kind of disease. This review summarizes the preparation methods, biological characteristics, functions and molecular mechanisms of GBM-exo on cell proliferation, angiogenesis, immune evasion and drug resistance of GBM to facilitate developing new strategies for the diagnosis and treatment of GBM.
Humans ; Glioblastoma/genetics* ; Exosomes/metabolism* ; MicroRNAs/metabolism* ; Prognosis ; Cell Proliferation ; Brain Neoplasms/genetics* ; Cell Line, Tumor

Recently, deep learning has achieved impressive results in medical image tasks. However, this method usually requires large-scale annotated data, and medical images are expensive to annotate, so it is a challenge to learn efficiently from the limited annotated data. Currently, the two commonly used methods are transfer learning and self-supervised learning. However, these two methods have been little studied in multimodal medical images, so this study proposes a contrastive learning method for multimodal medical images. The method takes images of different modalities of the same patient as positive samples, which effectively increases the number of positive samples in the training process and helps the model to fully learn the similarities and differences of lesions on images of different modalities, thus improving the model's understanding of medical images and diagnostic accuracy. The commonly used data augmentation methods are not suitable for multimodal images, so this paper proposes a domain adaptive denormalization method to transform the source domain images with the help of statistical information of the target domain. In this study, the method is validated with two different multimodal medical image classification tasks: in the microvascular infiltration recognition task, the method achieves an accuracy of (74.79 ± 0.74)% and an F1 score of (78.37 ± 1.94)%, which are improved as compared with other conventional learning methods; for the brain tumor pathology grading task, the method also achieves significant improvements. The results show that the method achieves good results on multimodal medical images and can provide a reference solution for pre-training multimodal medical images.
Humans ; Algorithms ; Brain/diagnostic imaging* ; Brain Neoplasms/diagnostic imaging* ; Recognition, Psychology