-
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 -
Frontiers in Surgery 2024Infrared thermography (IT) is a non-invasive real-time imaging technique with potential application in different areas of neurosurgery. Despite technological advances in...
INTRODUCTION
Infrared thermography (IT) is a non-invasive real-time imaging technique with potential application in different areas of neurosurgery. Despite technological advances in the field, intraoperative IT (IIT) has been an underestimated tool with scarce reports on its usefulness during intracranial tumor resection. We aimed to evaluate the usefulness of high-resolution IIT with static and dynamic thermographic maps for transdural lesion localization, and diagnosis, to assess the extent of resection, and the occurrence of perioperative acute ischemia.
METHODS
In a prospective study, 15 patients affected by intracranial tumors (six gliomas, four meningiomas, and five brain metastases) were examined with a high-resolution thermographic camera after craniotomy, after dural opening, and at the end of tumor resection.
RESULTS
Tumors were transdurally located with 93.3% sensitivity and 100% specificity ( < 0.00001), as well as cortical arteries and veins. Gliomas were consistently hypothermic, while metastases and meningiomas exhibited highly variable thermographic maps on static ( = 0.055) and dynamic ( = 0.015) imaging. Residual tumors revealed non-specific static but characteristic dynamic thermographic maps. Ischemic injuries were significantly hypothermic ( < 0.001).
CONCLUSIONS
High-resolution IIT is a non-invasive alternative intraoperative imaging method for lesion localization, diagnosis, assessing the extent of tumor resection, and identifying acute ischemia changes with static and dynamic thermographic maps.
PubMed: 38933651
DOI: 10.3389/fsurg.2024.1386722 -
Frontiers in Oncology 2024To review our single-institution experience in the surgical management of foramen magnum tumors via a far-lateral approach using an oblique straight incision.
OBJECTIVE
To review our single-institution experience in the surgical management of foramen magnum tumors via a far-lateral approach using an oblique straight incision.
METHODS
From October 2023 to January 2024, four cases of tumors in the foramen magnum area treated at the Capital Medical University-affiliated XuanWu hospital neurosurgery department were involved in this study. All cases were managed with a far-lateral approach using an oblique straight incision. We retrospectively reviewed the clinical and imaging data, as well as the surgical strategies employed.
RESULTS
Three cases of foramen magnum meningiomas and one case of glioma of the ventral medulla. All cases underwent a far-lateral approach using an oblique straight incision; all cases had a gross total resection, and the wounds healed well without cerebral fluid leakage or scalp hydrops. Except for one case of right foramen magnum meningioma, which had dysphagia and pneumothorax, the other cases were without any postoperative complications.
CONCLUSION
A far-lateral approach using an oblique straight incision can preserve muscle integrity and minimize subcutaneous exposure, allowing for complete anatomical reduction of muscles. This craniectomy method is simple and replicable, making it worthy of further clinical practice.
PubMed: 38933447
DOI: 10.3389/fonc.2024.1391002 -
Frontiers in Computational Neuroscience 2024The necessity of prompt and accurate brain tumor diagnosis is unquestionable for optimizing treatment strategies and patient prognoses. Traditional reliance on Magnetic...
BACKGROUND
The necessity of prompt and accurate brain tumor diagnosis is unquestionable for optimizing treatment strategies and patient prognoses. Traditional reliance on Magnetic Resonance Imaging (MRI) analysis, contingent upon expert interpretation, grapples with challenges such as time-intensive processes and susceptibility to human error.
OBJECTIVE
This research presents a novel Convolutional Neural Network (CNN) architecture designed to enhance the accuracy and efficiency of brain tumor detection in MRI scans.
METHODS
The dataset used in the study comprises 7,023 brain MRI images from figshare, SARTAJ, and Br35H, categorized into glioma, meningioma, no tumor, and pituitary classes, with a CNN-based multi-task classification model employed for tumor detection, classification, and location identification. Our methodology focused on multi-task classification using a single CNN model for various brain MRI classification tasks, including tumor detection, classification based on grade and type, and tumor location identification.
RESULTS
The proposed CNN model incorporates advanced feature extraction capabilities and deep learning optimization techniques, culminating in a groundbreaking paradigm shift in automated brain MRI analysis. With an exceptional tumor classification accuracy of 99%, our method surpasses current methodologies, demonstrating the remarkable potential of deep learning in medical applications.
CONCLUSION
This study represents a significant advancement in the early detection and treatment planning of brain tumors, offering a more efficient and accurate alternative to traditional MRI analysis methods.
PubMed: 38933391
DOI: 10.3389/fncom.2024.1418546 -
Journal of Clinical Medicine Jun 2024We sometimes encounter refractory meningioma cases that are difficult to control, even after achieving a high resection rate or following radiation therapy (RT). In...
We sometimes encounter refractory meningioma cases that are difficult to control, even after achieving a high resection rate or following radiation therapy (RT). In such cases, additional surgical resection might be attempted, but reports regarding outcomes of re-do surgery for recurrent meningiomas are scarce. This study was a retrospective review of patients who underwent re-do surgery for recurrent meningiomas. The risks of re-doing surgery were statistically analyzed. A comparative analysis between the patients who underwent primary surgery for intracranial meningiomas was also performed. Twenty-six patients underwent re-do surgeries for recurrent meningiomas. At first re-do surgery, gross total resection was achieved in 20 patients (77%). The disease-free survival rate after the first re-do surgery was calculated as 73/58/44% at 1, 2, and 5 years, respectively. A significant factor affecting longer disease-free survival was WHO Grade 1 diagnosis at first re-do surgery ( = 0.02). Surgery-related risks were observed in 10 patients presenting a significant risk factor for skull base location ( = 0.04). When comparing with the risk at primary surgery, the risks of surgical site infection ( = 0.04) and significant vessel injury ( < 0.01) were significantly higher for the re-do surgery. Re-do surgery could increase surgery-related risks compared to the primary surgery; however, it could remain a crucial option, while the indication should be carefully examined in each case.
PubMed: 38929885
DOI: 10.3390/jcm13123356