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MedRxiv : the Preprint Server For... Jun 2024Meningioma risk factors include older age, female sex, and African-American race. There are limited data exploring how meningioma risk in African-Americans varies across...
BACKGROUND
Meningioma risk factors include older age, female sex, and African-American race. There are limited data exploring how meningioma risk in African-Americans varies across the lifespan, interacts with sex, and differs by tumor grade.
METHODS
The Central Brain Tumor Registry of the United States (CBTRUS) is a population-based registry covering the entire U.S. population. Meningioma diagnoses from 2004-2019 were used to calculate incidence rate ratios (IRRs) for non-Hispanic Black individuals (NHB) compared to non-Hispanic white individuals (NHW) across 10-year age intervals, and stratified by sex and by WHO tumor grade.
RESULTS
53,890 NHB individuals and 322,373 NHW individuals with an intracranial meningioma diagnosis were included in analyses. Beginning in young adulthood, the NHB-to-NHW IRR was elevated for both grade 1 and grade 2/3 tumors. The IRR peaked in the seventh decade of life regardless of grade, and was higher for grade 2/3 tumors (IRR=1.57; 95% CI: 1.46-1.69) than grade 1 tumors (IRR=1.27; 95% CI: 1.25-1.30) in this age group. The NHB-to-NHW IRR was elevated in females (IRR=1.17; 95% CI: 1.16-1.18) and further elevated in males (IRR=1.28; 95% CI: 1.26-1.30), revealing synergistic interaction between NHB race/ethnicity and male sex (P =0.001).
CONCLUSIONS
Relative to NHW individuals, NHB individuals are at elevated risk of meningioma from young adulthood through old age. NHB race/ethnicity conferred higher risk of meningioma among men than women, and higher risk of developing WHO grade 2/3 tumors. Results identify meningioma as a significant source of racial disparities in neuro-oncology and may help to improve preoperative predictions of meningioma grade.
PubMed: 38947051
DOI: 10.1101/2024.06.13.24308882 -
World Neurosurgery Jun 2024To assess the utility of 3D printing positioning technology for resection of parasagittal meningioma.
OBJECTIVE
To assess the utility of 3D printing positioning technology for resection of parasagittal meningioma.
METHODS
Information related to clinical history, application of 3D printing positioning technology, neuroimaging, surgical related information and postoperative hospital days of consecutive patients with parasagittal meningioma between January 2020 and December 2022 were retrospectively collected. Patients were divided into two groups based on whether the 3D printing positioning technology was applied. The values between groups were statistically compared.
RESULTS
A total of 41 patients were enrolled. In cases using 3D printing positioning technology (14 patients), the location of craniotomy was much better and the postoperative hospital stay was much shorter.
CONCLUSION
The application of 3D printing positioning technology in parasagittal meningioma surgery could improve the location of craniotomy, and reduce the postoperative hospital stay. It is a low-cost positioning technology, and has the potential to be applied to other superficial intracranial tumors.
PubMed: 38945205
DOI: 10.1016/j.wneu.2024.06.134 -
Translational Oncology Jun 2024Tumor derived Extracellular vesicles (EVs) in circulating system may contain tumor-specific markers, and EV detection in body fluids could become an important tool for...
Tumor derived Extracellular vesicles (EVs) in circulating system may contain tumor-specific markers, and EV detection in body fluids could become an important tool for early tumor diagnosis, prognosis assessment. Meningiomas are the most common benign intracranial tumors, few studies have revealed specific protein markers for meningiomas from patients' body fluids. In this study, using proximity labeling technology and non-tumor patient plasma as a control, we detected protein levels of EVs in plasma samples from meningioma patients before and after surgery. Through bioinformatics analysis, we discovered that the levels of EV count and protein count in meningioma patients were significantly higher than those in healthy controls, and were significantly decreased postoperatively. Among EV proteins in meningioma patients, the levels of MUC1, SIGLEC11, E-Cadherin, KIT, and TASCTD2 were found not only significantly elevated than those in healthy controls, but also significantly decreased after tumor resection. Moreover, using publicly available GEO databases, we verified that the mRNA level of MUC1, SIGLEC11, and CDH1 in meningiomas were significantly higher in comparison with normal dura mater tissues. Additionally, by analyzing human meningioma specimens collected in this study, we validated the protein levels of MUC1 and SIGLEC11 were significantly increased in WHO grade 2 meningiomas and were positively correlated with tumor proliferation levels. This study indicates that meningiomas secret EV proteins into circulating system, which may serve as specific markers for diagnosis, malignancy predicting and tumor recurrent assessment.
PubMed: 38943923
DOI: 10.1016/j.tranon.2024.102046 -
Cancer Imaging : the Official... Jun 2024This study was based on MRI features and number of tumor-infiltrating CD8 + T cells in post-operative pathology, in predicting meningioma recurrence risk.
OBJECTIVE
This study was based on MRI features and number of tumor-infiltrating CD8 + T cells in post-operative pathology, in predicting meningioma recurrence risk.
METHODS
Clinical, pathological, and imaging data of 102 patients with surgically and pathologically confirmed meningiomas were retrospectively analyzed. Patients were divided into recurrence and non-recurrence groups based on follow-up. Tumor-infiltrating CD8 + T cells in tissue samples were quantitatively assessed with immunohistochemical staining. Apparent diffusion coefficient (ADC) histogram parameters from preoperative MRI were quantified in MaZda. Considering the high correlation between ADC histogram parameters, we only chose ADC histogram parameter that had the best predictive efficacy for COX regression analysis further. A visual nomogram was then constructed and the recurrence probability at 1- and 2-years was determined. Finally, subgroup analysis was performed with the nomogram.
RESULTS
The risk factors for meningioma recurrence were ADCp1 (hazard ratio [HR] = 0.961, 95% confidence interval [95% CI]: 0.937 ~ 0.986, p = 0.002) and CD8 + T cells (HR = 0.026, 95%CI: 0.001 ~ 0.609, p = 0.023). The resultant nomogram had AUC values of 0.779 and 0.784 for 1- and 2-years predicted recurrence rates, respectively. The survival analysis revealed that patients with low CD8 + T cells counts or ADCp1 had higher recurrence rates than those with high CD8 + T cells counts or ADCp1. Subgroup analysis revealed that the AUC of nomogram for predicting 1-year and 2-year recurrence of WHO grade 1 and WHO grade 2 meningiomas was 0.872 (0.652) and 0.828 (0.751), respectively.
CONCLUSIONS
Preoperative ADC histogram parameters and tumor-infiltrating CD8 + T cells may be potential biomarkers in predicting meningioma recurrence risk.
CLINICAL RELEVANCE STATEMENT
The findings will improve prognostic accuracy for patients with meningioma and potentially allow for targeted treatment of individuals who have the recurrent form.
Topics: Humans; Meningioma; Nomograms; Male; Female; Neoplasm Recurrence, Local; Middle Aged; CD8-Positive T-Lymphocytes; Retrospective Studies; Meningeal Neoplasms; Lymphocytes, Tumor-Infiltrating; Aged; Adult; Magnetic Resonance Imaging; Risk Factors; Prognosis
PubMed: 38943200
DOI: 10.1186/s40644-024-00731-6 -
Journal of Clinical Neuroscience :... Jun 2024Patients with spinal meningioma may present preoperatively with paralysis and sensory deficits. However, there is a paucity of detailed evaluations and a lack of...
BACKGROUND
Patients with spinal meningioma may present preoperatively with paralysis and sensory deficits. However, there is a paucity of detailed evaluations and a lack of consensus regarding imaging findings that are predictive of neurological symptoms in patients with spinal meningioma.
METHODS
Herein, a total of 55 patients who underwent surgical resection of spinal meningiomas in eight hospitals between 2011 and 2021 were enrolled. Patient characteristics, degree of muscle weakness, sensory disturbances, and the presence of bowel/bladder dysfunction (BBD) before surgical treatment were evaluated using medical records. Patients with American Spinal Injury Impairment Scale grades A-C and the presence of BBD were classified into the paralysis (+) group. Patients with sensory disturbances were assigned to the sensory disturbance (+) group. Based on magnetic resonance (MR) and computed tomography images, the tumor location was classified according to the spinal level and its attachment to the dura mater. To evaluate tumor size, the tumor occupation ratio (OR) was calculated using the area and distance measurement method in horizontal MR images, and the maximum length and area of the tumor in the sagittal plane were measured.
RESULTS
Of all patients, 85 % were women. The mean age of patients at surgery was 69.7 years. Twenty-eight (51 %) and 41 (75 %) patients were classified into the paralysis (+) and sensory disturbance (+) groups, respectively. The average tumor length and area in the sagittal plane were 19.6 mm and 203 mm, respectively; OR-area and diameters were 70.3 % and 72.3 %, respectively. In univariate analyses, tumor length and area in the sagittal plane were significant risk factors for paralysis. OR-diameter, symptom duration, and a low MIB-1 index correlated with sensory disturbances. Multivariate logistic regression analysis demonstrated that the area and length of the tumor in the sagittal plane were significantly correlated with paralysis, whereas the OR-diameter and symptom duration significantly correlated with sensory disturbances. The cut-off values for the area and length of the tumor in the sagittal plane to predict paralysis were 243 mm and 20.1 mm, respectively.
CONCLUSIONS
Preoperative paralysis in patients with spinal meningiomas was significantly associated with sagittal tumor size than with high tumor occupancy in the horizontal plane. Sensory disturbances were associated with high occupancy in the horizontal plane. Patients with spinal meningiomas > 20 mm in length or 243 mm in area in the sagittal plane are at risk of developing paralysis and could be considered for surgery even in the absence of paralysis.
PubMed: 38941916
DOI: 10.1016/j.jocn.2024.06.021 -
Computer Methods and Programs in... Jun 2024To develop a clinically reliable deep learning model to differentiate glioblastoma (GBM) from solitary brain metastasis (SBM) by providing predictive uncertainty...
BACKGROUND AND OBJECTIVES
To develop a clinically reliable deep learning model to differentiate glioblastoma (GBM) from solitary brain metastasis (SBM) by providing predictive uncertainty estimates and interpretability.
METHODS
A total of 469 patients (300 GBM, 169 SBM) were enrolled in the institutional training set. Deep ensembles based on DenseNet121 were trained on multiparametric MRI. The model performance was validated in the external test set consisting of 143 patients (101 GBM, 42 SBM). Entropy values for each input were evaluated for uncertainty measurement; based on entropy values, the datasets were split to high- and low-uncertainty groups. In addition, entropy values of out-of-distribution (OOD) data from unknown class (257 patients with meningioma) were compared to assess uncertainty estimates of the model. The model interpretability was further evaluated by localization accuracy of the model.
RESULTS
On external test set, the area under the curve (AUC), accuracy, sensitivity and specificity of the deep ensembles were 0.83 (95 % confidence interval [CI] 0.76-0.90), 76.2 %, 54.8 % and 85.2 %, respectively. The performance was higher in the low-uncertainty group than in the high-uncertainty group, with AUCs of 0.91 (95 % CI 0.83-0.98) and 0.58 (95 % CI 0.44-0.71), indicating that assessment of uncertainty with entropy values ascertained reliable prediction in the low-uncertainty group. Further, deep ensembles classified a high proportion (90.7 %) of predictions on OOD data to be uncertain, showing robustness in dataset shift. Interpretability evaluated by localization accuracy provided further reliability in the "low-uncertainty and high-localization accuracy" subgroup, with an AUC of 0.98 (95 % CI 0.95-1.00).
CONCLUSIONS
Empirical assessment of uncertainty and interpretability in deep ensembles provides evidence for the robustness of prediction, offering a clinically reliable model in differentiating GBM from SBM.
PubMed: 38941861
DOI: 10.1016/j.cmpb.2024.108288 -
Case Reports in Infectious Diseases 2024Coadministering two different classes of antibiotics as empirical therapy can be critical in treating healthcare-associated infections in hospitals. Herein, we report a...
Coadministering two different classes of antibiotics as empirical therapy can be critical in treating healthcare-associated infections in hospitals. Herein, we report a case of acute kidney injury (AKI) caused by coadministration of vancomycin with high-dose meropenem that manifested as a rapid increase in serum creatinine levels and an associated increase in vancomycin trough concentrations. The patient was diagnosed with meningioma at 50 years and was followed up regularly. The patient underwent surgery and antibiotic treatment between 63 and 66 years for suspected meningitis and pneumonia. Coadministration of vancomycin with high-dose meropenem (6.0 g/day) caused AKI; however, no AKI occurred when vancomycin was administered alone or with a low dose of meropenem (1.5 or 3.0 g/day). To our knowledge, this report is the first to show that administering different dosages of meropenem in combination with vancomycin may contribute to the risk of developing AKI. We suggest that coadministered vancomycin and high-dose meropenem (6.0 g/day) may increase the risk of AKI. Our report adds to the limited literature documenting the coadministration of vancomycin with varying doses of meropenem and its impact on the risk of AKI and highlights the importance of investigating AKI risk in response to varying dosages of meropenem when it is coadministered with vancomycin.
PubMed: 38939108
DOI: 10.1155/2024/7956014 -
Journal of Neurointerventional Surgery Jun 2024Liquid embolization in neuroendovascular procedures carries the risk of embolizing an inappropriate vessel. Operators must pay close attention to multiple vessels during...
BACKGROUND
Liquid embolization in neuroendovascular procedures carries the risk of embolizing an inappropriate vessel. Operators must pay close attention to multiple vessels during the procedure to avoid ischemic complications. We report our experience with real time artificial intelligence (AI) assisted liquid embolization and evaluate its performance.
METHODS
An AI-based system (Neuro-Vascular Assist, iMed technologies, Tokyo, Japan) was used in eight endovascular liquid embolization procedures in two institutions. The software automatically detects liquid embolic agent on biplane fluoroscopy images in real time and notifies operators when the agent reaches a predefined area. Safety, efficacy, and accuracy of the notifications were evaluated using recorded videos.
RESULTS
Onyx or n-butyl-2-cyanoacrylate (NBCA) was used in the treatment of arteriovenous malformation, dural arteriovenous fistula, meningioma, and chronic subdural hematoma. The mean number of true positive and false negative notifications per case was 31.8 and 2.8, respectively. No false positive notifications occurred. The precision and recall of the notifications were 100% and 92.0%, respectively. In 28.3% of the true positive notifications, the operator immediately paused agent injection after receiving the notification, which demonstrates the potential effectiveness of the AI-based system. No adverse events were associated with the notifications.
CONCLUSIONS
To the best of our knowledge, this is the first report of real time AI assistance with liquid embolization procedures in humans. The system demonstrated high notification accuracy, safety, and potential clinical usefulness in liquid embolization procedures. Further research is warranted to validate its impact on clinical outcomes. AI-based real time surgical support has the potential to advance neuroendovascular treatment.
PubMed: 38937087
DOI: 10.1136/jnis-2024-022001 -
World Neurosurgery Jun 2024Meningioma calcification is thought to predict lessened growth potential and aggression. However, historical studies have mostly focused on correlating calcification of...
BACKGROUND
Meningioma calcification is thought to predict lessened growth potential and aggression. However, historical studies have mostly focused on correlating calcification of small (diameter < 2.5 cm) meningiomas, rather than analyzing traits of calcified meningiomas across all sizes.
OBJECTIVE
To investigate the pathologic and clinical implications of meningioma calcification.
METHODS
We utilized a historical database of 342 consecutive, newly diagnosed intracranial meningiomas with preoperative CT and MRI scans treated at a single institution from 2005 to 2019. We correlated the presence of calcification with patient demographics, grade, MIB-1 index, location, volume, Simpson grade, and recurrence with both univariate and multivariate generalized linear models.
RESULTS
On univariate analysis, no single variable correlated with tumor calcification. Notably, neither tumor WHO grade (p = 0.91) nor MIB-1index (p = 0.62) predicted calcification. After accounting for demographic characteristics and tumor volume and location, there was no significant association between WHO grade (p = 0.52) and MIB-1index (p = 0.54) and calcification. Calcification had no influence on rate resection grade (p = 0.59) or recurrence (p = 0.80).
CONCLUSION
In this series, calcified meningiomas exhibited equal WHO grading distribution, proliferation indexes, and immediate surgical outcomes than their noncalcified counterparts. These findings question the historical role of using meningioma calcification as an independent guide to their management.
PubMed: 38936608
DOI: 10.1016/j.wneu.2024.06.120 -
Clinical Neurology and Neurosurgery Mar 2024Primary intraosseous meningioma of the skull (PIMS) is a rare type of primary extradural meningioma (PEM) involving cranial bone. The existing literature strongly...
BACKGROUND
Primary intraosseous meningioma of the skull (PIMS) is a rare type of primary extradural meningioma (PEM) involving cranial bone. The existing literature strongly suggest the importance of radiological feacures in pathological diagnosis of PIMS. Thereby, the aim of this study is to investigate the association between imaging classification and histopathological grading in PIMS.
METHODS
In this retrospective study, we retrospectively analyzed the computed tomography scan/magnetic resonance imaging and pathological data pertaining to patients with pathologically proven PIMS. The association between radiological features, imaging classification, and histopathological grading was analyzed using logistic regression analysis.
RESULTS
In this study, data of 25 patients with PIMS were assessed. The univariate logistic regression analysis results showed significant correlation between histopathological grading and imaging classification (OR: 22.5; 95% CI: 2.552-198.378; p = 0.005), intra- and extracalvarial extension (OR: 7.2; 95% CI: 1.066-48.639; p = 0.043), and tumor margin (OR: 7.19; 95% CI: 1.06-47.61; p = 0.043). According to the results of multivariate logistic regression analysis, imaging classification was the strongest independent risk factor for high-grade PIMS, and the risk of aggressiveness of osteoblastic type of PIMS was 16.664 times higher than that of osteolytic type of PIMS (OR: 16.664; 95% CI: 1.15-241.508; p = 0.039).
CONCLUSIONS
Imaging classification is an independent risk factor for high-grade PIMS.
PubMed: 38936174
DOI: 10.1016/j.clineuro.2024.108239