WHO Grade I Meningioma Recurrence: Identifying High Risk Patients Using Histopathological Features and the MIB-1 Index

Gross Tumor and Intracranial Control Benefits with Fractionated Radiotherapy Compared with Stereotactic Radiosurgery for Patients with WHO Grade 2 Meningioma

OBJECTIVE

Surgical resection is the mainstay of treatment for WHO grade 2 meningioma. Fractionated radiation therapy (RT) is frequently used after surgery, though many centers utilize stereotactic radiosurgery (SRS) for recurrence or progression. Herein, we report disease control outcomes from an institutional cohort with adjuvant fractionated RT versus salvage SRS.

METHODS

We identified 32 patients from an institutional database with WHO grade 2 meningioma and residual/recurrent tumor treated with either SRS or fractionated RT. Patients were treated between 2007 and 2021 and had at least 1 year of follow-up. Kaplan-Meier estimators were used to determine gross tumor control (GTC) and intracranial control (IC). Univariate Cox proportional hazards models using biologically effective dose (BED) as a continuous parameter were used to assess for dose responses.

RESULTS

With a median follow-up of 5.5 years, 13 patients (41%) received SRS to a recurrent or progressive nodule, 2 (6%) fractionated RT to a recurrent or progressive nodule, and 17 (53%) adjuvant fractionated RT following subtotal resection. Five-year GTC was higher with fractionated RT versus SRS (82% vs. 38%, P = 0.03). Five-year IC was also better with fractionated RT versus SRS (82% vs. 11%, P < 0.001). On univariate analysis, increasing BED10 was significantly associated with better GTC (P = 0.039); increasing BED3 was not (P = 0.82).

CONCLUSIONS

In this patient cohort, GTC and IC were significantly higher in patients treated with adjuvant fractionated RT compared with salvage SRS. Increasing BED10 was associated with better GTC. Fractionated RT may provide a better therapeutic ratio than SRS for grade 2 meningiomas.

MRI features and tumor-infiltrating CD8 + T cells-based nomogram for 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.

Topographic Patterns of Intracranial Meningioma Recurrences-Systematic Review with Clinical Implication

BACKGROUND

While several risk factors for recurrences have been defined, the topographic pattern of meningioma recurrences after surgical resection has been scarcely investigated. The possibility of theoretically predicting the site of recurrence not only allows us to better understand the pathogenetic bases of the disease and consequently to drive the development of new targeted therapies, but also guides the decision-making process for treatment strategies and tailored follow-ups to decrease/prevent recurrence.

METHODS

The authors performed a comprehensive and detailed systematic literature review of the EMBASE and MEDLINE electronic online databases regarding the topographic pattern of recurrence after surgical treatment for intracranial meningiomas. Demographics and histopathological, neuroradiological and treatment data, pertinent to the topography of recurrences, as well as time to recurrences, were extracted and analyzed.

RESULTS

Four studies, including 164 cases of recurrences according to the inclusion criteria, were identified. All studies consider the possibility of recurrence at the previous dural site; three out of four, which are the most recent, consider 1 cm outside the previous dural margin to be the main limit to distinguish recurrences closer to the previous site from those more distant. Recurrences mainly occur within or close to the surgical bed; higher values of proliferation index are associated with recurrences close to the original site rather than within it.

CONCLUSIONS

Further studies, including genomic characterization of different patterns of recurrence, will better clarify the main features affecting the topography of recurrences. A comparison between topographic classifications of intracranial meningioma recurrences after surgery and after radiation treatment could provide further interesting information.

Meningioma recurrence: Time for an online prediction tool?

Background

Meningioma, the most common brain tumor, traditionally considered benign, has a relatively high risk of recurrence over a patient's lifespan. In addition, with the emergence of several clinical, radiological, and molecular variables, it is becoming evident that existing grading criteria, including Simpson's and World Health Organization classification, may not be sufficient or accurate. As web-based tools for widespread accessibility and usage become commonplace, such as those for gene identification or other cancers, it is timely for meningioma care to take advantage of evolving new markers to help advance patient care.

Methods

A scoping review of the meningioma literature was undertaken using the MEDLINE and Embase databases. We reviewed original studies and review articles from September 2022 to December 2023 that provided the most updated information on the demographic, clinical, radiographic, histopathological, molecular genetics, and management of meningiomas in the adult population.

Results

Our scoping review reveals a large body of meningioma literature that has evaluated the determinants for recurrence and aggressive tumor biology, including older age, female sex, genetic abnormalities such as telomerase reverse transcriptase promoter mutation, CDKN2A deletion, subtotal resection, and higher grade. Despite a large body of evidence on meningiomas, however, we noted a lack of tools to aid the clinician in decision-making. We identified the need for an online, self-updating, and machine-learning-based dynamic model that can incorporate demographic, clinical, radiographic, histopathological, and genetic variables to predict the recurrence risk of meningiomas.

Conclusion

Although a challenging endeavor, a recurrence prediction tool for meningioma would provide critical information for the meningioma patient and the clinician making decisions on long-term surveillance and management of meningiomas.

Predicting meningioma grades and pathologic marker expression via deep learning

OBJECTIVES

To establish a deep learning (DL) model for predicting tumor grades and expression of pathologic markers of meningioma.

METHODS

A total of 1192 meningioma patients from two centers who underwent surgical resection between September 2018 and December 2021 were retrospectively included. The pathological data and post-contrast T1-weight images for each patient were collected. The patients from institute I were subdivided into training, validation, and testing sets, while the patients from institute II served as the external testing cohort. The fine-tuned ResNet50 model based on transfer learning was adopted to classify WHO grade in the whole cohort and predict Ki-67 index, H3K27me3, and progesterone receptor (PR) status of grade 1 meningiomas. The predictive performance was evaluated by the accuracy and loss curve, confusion matrix, receiver operating characteristic curve (ROC), and area under curve (AUC).

RESULTS

The DL prediction model for each label achieved high predictive performance in two cohorts. For WHO grade prediction, the area under the curve (AUC) was 0.966 (95%CI 0.957-0.975) in the internal testing set and 0.669 (95%CI 0.643-0.695) in the external validation cohort. The AUC in predicting Ki-67 index, H3K27me3, and PR status were 0.905 (95%CI 0.895-0.915), 0.773 (95%CI 0.760-0.786), and 0.771 (95%CI 0.750-0.792) in the internal testing set and 0.591 (95%CI 0.562-0.620), 0.658 (95%CI 0.648-0.668), and 0.703 (95%CI 0.674-0.732) in the external validation cohort, respectively.

CONCLUSION

DL models can preoperatively predict meningioma grades and pathologic marker expression with favorable predictive performance.

CLINICAL RELEVANCE STATEMENT

Our DL model could predict meningioma grades and expression of pathologic markers and identify high-risk patients with WHO grade 1 meningioma, which would suggest a more aggressive operative intervention preoperatively and a more frequent follow-up schedule postoperatively.

KEY POINTS

WHO grades and some pathologic markers of meningioma were associated with therapeutic strategies and clinical outcomes. A deep learning-based approach was employed to develop a model for predicting meningioma grades and the expression of pathologic markers. Preoperative prediction of meningioma grades and the expression of pathologic markers was beneficial for clinical decision-making.

Time to Recurrence of Intracranial Meningiomas from a Monoinstitutional Surgical Series

BACKGROUND

Meningiomas show variable tendency to recur. While risk factors of recurrence have been largely investigated in literature, a paucity of data is available on the time to recurrence. Our purpose was to identify main factors affecting the time to recurrence to assist preoperative treatment decision-making strategy and to define a tailored clinical and neuroradiological follow-up.

METHODS

Data of 35 patients with intracranial meningioma recurrences have been retrospectively reviewed. Demographic (patient age at initial diagnosis and sex), radiologic (meningioma location, pattern of regrowth and topography of recurrences at first reoperation), pathologic (WHO grade and Ki67-MIB1 at initial surgery and at first reoperation, progesterone receptor [PR] expression), and surgical (extent of resection at initial surgery according to Simpsons grading system, number of reoperations) factors were analyzed.

RESULTS

Time to recurrence ranged from 20 to 120 months. Extent of resection at initial surgery was Simpson grade I in 7 patients (20%), grade II in 10 (28.5%), grade III in 14 (40%), and grade IV in 4 (11.5%). Longer median time to recurrence was observed for skull base localization (P < 0.01), Simpson grades I and II versus grades III (P = 0.01) and IV (P = 0.02), values of Ki67-MIB1 ≤ 4% (P = 0.001), and PR > 60% (P = 0.03); conversely, sex, age, number of reoperations, unchanged/progression of Ki67, and/or World Health Organization grade between first surgery and reoperation did not correlate in statistically significant way with time to recurrence.

CONCLUSIONS

The extent of resection and the Ki67-MIB1 represent the most important factors predicting shorter recurrence time of intracranial meningiomas. Patients with incomplete (Simpson grades III and IV) resection and high Ki67-MIB1 values, especially at non-skull base localization and with low PR values, require a closer short-term clinical and radiologic follow-up in the first years after surgery.

The Evolving Classification of Meningiomas: Integration of Molecular Discoveries to Inform Patient Care

Meningioma classification and treatment have evolved over the past eight decades. Since Bailey, Cushing, and Eisenhart's description of meningiomas in the 1920s and 1930s, there have been continual advances in clinical stratification by histopathology, radiography and, most recently, molecular profiling, to improve prognostication and predict response to therapy. Precise and accurate classification is essential to optimizing management for patients with meningioma, which involves surveillance imaging, surgery, primary or adjuvant radiotherapy, and consideration for clinical trials. Currently, the World Health Organization (WHO) grade, extent of resection (EOR), and patient characteristics are used to guide management. While these have demonstrated reliability, a substantial number of seemingly benign lesions recur, suggesting opportunities for improvement of risk stratification. Furthermore, the role of adjuvant radiotherapy for grade 1 and 2 meningioma remains controversial. Over the last decade, numerous studies investigating the molecular drivers of clinical aggressiveness have been reported, with the identification of molecular markers that carry clinical implications as well as biomarkers of radiotherapy response. Here, we review the historical context of current practices, highlight recent molecular discoveries, and discuss the challenges of translating these findings into clinical practice.

Minimally Invasive Approaches in the Surgical Treatment of Intracranial Meningiomas: An Analysis of 54 Cases

BACKGROUND

Intracranial meningiomas, being a fairly common disease in the population, often require surgical treatment, which, in turn, can completely heal the patient. The localization of meningiomas often influences treatment even if they are asymptomatic. By modernizing approaches to surgical treatment, it is possible to minimize intra- and postoperative risks, while achieving complete removal of the tumor. One of these methods is minimally invasive neurosurgery, the development of which in recent years allows it to compete with standard surgical methods. The purpose of this study was the objectification of minimally invasive approaches, such as the calculation of the craniotomy area and the ratio of craniotomy area to the resected tumor volume.

METHODS

The retrospective study consisted of a group of 54 consecutive patients who were operated on in our neurosurgery clinic specialized on minimally invasive neurosurgery. Preoperative planning was carried out using the Surgical Theater visualization platform. Using this system, the tumor volume and craniotomy surface area were calculated. During the analysis, the symptoms before and after the surgery, classification of tumors, postoperative complications, further treatment and follow-up results were assessed.

RESULTS

Twelve (22.2%) patients were men and 42 (77.8%) were women. The mean age of the group was 64.2 years (median 67.5). The craniotomy area ranged from 202 to 2,108 mm² (mean 631 mm²). Tumor volume ranged from 0.85 to 110.1 cm3 (mean 21.6 cm3). The craniotomy size of minimally invasive approaches to the skull base was 3-5 times smaller than standard approaches. Skull base meningiomas accounted for 19 cases (35.2%), convexity meningiomas for 26 cases (48.1%), and falx and tentorium meningiomas for 9 cases (16.7%). Three complications were reported: postoperative hemorrhage, CSF leakage, and ophthalmoplegia. Relapse was detected in 2 patients with a mean follow-up of 26.3 months (median 20).

CONCLUSION

Minimally invasive approaches in the surgical treatment of intracranial meningiomas reduce the possibility of operating trauma by several times; they are safe and sufficient for complete removal of the tumor.

Epidemiology, Genetics, and DNA Methylation Grouping of Hyperostotic Meningiomas

BACKGROUND AND OBJECTIVES

Meningiomas are the most common primary intracranial tumors and are among the only tumors that can form lamellar, hyperostotic bone in the tumor microenvironment. Little is known about the epidemiology or molecular features of hyperostotic meningiomas.

METHODS

Using a retrospective database of 342 meningiomas treated with surgery at a single institution, we correlated clinical, tumor-related, targeted next-generation DNA sequencing (n = 39 total, 16 meningioma-induced hyperostosis [MIH]), and surgical variables with the presence of MIH using generalized linear models. Meningioma DNA methylation grouping was analyzed on a separate population of patients from the same institution with preoperative imaging studies sufficient for identification of MIH (n = 200).

RESULTS

MIH was significantly correlated with anterior fossa (44.3% of MIH vs 17.5% of non-MIH were in the anterior fossa P < .001, c2) or skull base location (62.5% vs 38.3%, P < .001, c2) and lower MIB-1 labeling index. Gross total resection was accomplished in 27.3% of tumors with MIH and 45.5% of nonhyperostotic meningiomas (P < .05, t test). There was no association between MIH and histological World Health Organization grade (P = .32, c2). MIH was significantly more frequent in meningiomas from the Merlin-intact DNA methylation group (P < .05). Somatic missense mutations in the WD-repeat-containing domain of the TRAF7 gene were the most common genetic alteration associated with MIH (n = 12 of 15, 80%, P < .01, c2).

CONCLUSION

In this article, we show that MIH has a predilection for the anterior skull base and affected tumors are less amenable to gross total resection. We find no association between MIH and histological World Health Organization grade, but show that MIH is more common in the Merlin-intact DNA methylation group and is significantly associated with TRAF7 somatic missense mutations. These data provide a framework for future investigation of biological mechanisms underlying MIH.

The value of an apparent diffusion coefficient histogram model in predicting meningioma recurrence

OBJECTIVE

To investigate the predictive value of a model combining conventional MRI features and apparent diffusion coefficient (ADC) histogram parameters for meningioma recurrence.

MATERIALS AND METHODS

Seventy-two meningioma patients confirmed by surgical and pathological findings in our hospital (January 2017-June 2020) were retrospectively and divided into the recurrence and non-recurrence group. MaZda software was used to delineate the region of interest at the largest tumor level and generate histogram parameters. Univariate and multivariate logistic regression analysis were used to construct the nomogram for predicting recurrence. The predictive efficacy and diagnostic of this model were assessed by calibration and decision curve analysis, and receiver operating characteristic curve, respectively.

RESULTS

Maximum diameter, necrosis, enhancement uniformity, age, Simpson, tumor shape, and ADC first percentile (ADCp1) were significantly different between the two groups (p < 0.05), with the latter four being independent risk factors for recurrence. The model constructed combining the four factors had the best predictive efficacy, and the area under the curve, accuracy, sensitivity, specificity, positive predictive value, and negative predictive value were 0.965(0.892-0.994), 90.3%, 92.6%, 88.9%, 83.3%, and 95.2%, respectively. The calibration curve showed good agreement between the model-predicted and actual probabilities of recurrence. The decision curve analysis indicated good clinical availability of the model.

CONCLUSION

This model based on conventional MRI features and ADC histogram parameters can directly and reliably predict meningioma recurrence, providing a guiding basis for selecting treatment options and individualized treatment.

Location pattern of recurrence of fully resected grade 1 meningiomas

OBJECTIVE

Meningiomas can lead to significant morbidity and mortality and have recurrence potential. While previous studies have focused on calculating recurrence risk, the precise location of the recurrence has not been delineated. This study aimed to investigate the spatial clustering pattern of recurrence relative to the original surgical bed for surgically treated Simpson Grade I-III, WHO Grade 1 meningiomas.

METHODS

Patients diagnosed with grade 1 meningiomas and treated with surgical resection with subsequent recurrence were reviewed. Patient demographics, clinical outcomes, and radiographic characteristics were collected. Radiological images were analyzed to determine the location of recurrence relative to the initial tumor. We characterized recurrence as type A (within the surgical bed), type B (outside of the surgical bed, within 1 cm from the site), and type C (distal ≥ 1 cm of the resection site).

RESULTS

Forty-two cases met the inclusion criteria. Twelve patients (29%) were male, and 30 (71%) were female. Median age at first treatment was 47 years, with 5.2 ± 3.4 years until recurrence. Recurrence rate was 54.7% at 5 years and 90.4% at 10 years. Twenty-eight patients (66.7%) had a type A recurrence, 11 (26.1%) had a type B recurrence, and 3 (7.1%) had a type C recurrence.

CONCLUSIONS

Our series demonstrates that while lesions often recur within the original lesion site, a significant portion recurs beyond the surgical bed. This highlights the substantial possibility of recurrence outside the resection cavity for fully excised benign meningiomas, which may aid in understanding disease progression and in guiding adjuvant therapy.

Outcomes and predictors of response to fractionated radiotherapy as primary treatment for intracranial meningiomas

Background

Surgery is the primary treatment for most meningiomas. However, primary fractionated radiotherapy (fRT) remains an option for patients with larger meningiomas in challenging anatomic locations or patients at prohibitively high surgical risk. Outcome prediction for these patients is uncertain and cannot be guided by histopathology without available tumor tissue from surgery. Therefore, we aimed to assess the clinical factors that contribute to treatment failure in a large cohort of meningiomas consecutively treated with fRT as primary therapy, with the goal of identifying predictors of response.

Methods

Patients treated with primary fRT for intracranial meningiomas from 1998 to 2017 were reviewed. Those who received primary surgical resection, radiosurgery, previous fRT, or had <6 months of clinical follow-up were excluded. We applied logistic regression and Cox regression modeling to ascertain key predictors of treatment failure, progression-free survival (PFS), and adverse events (AE) following fRT.

Results

Our cohort included 137 meningiomas, 21 of which progressed after fRT (median PFS 3.45 years). Progressive meningiomas had a larger median gross tumor volume (GTV) compared to those that remained stable (19.1 cm³ vs 9.6 cm³, p = 2.86 × 10^-2). GTV > 11.27 cm³ was independently predictive of progression and larger GTV was associated with higher risk of significant (grades 3/4) AE following fRT. Cavernous sinus and optic nerve sheath meningiomas had overall excellent outcomes post-fRT.

Conclusions

We present a large cohort of meningiomas treated with primary fRT and find GTV and anatomic location to be key predictors of outcome, adding to the complex treatment considerations for this heterogeneous disease.

Volumetric Growth and Growth Curve Analysis of Residual Intracranial Meningioma

BACKGROUND

After meningioma surgery, approximately 1 in 3 patients will have residual tumor that requires ongoing imaging surveillance. The precise volumetric growth rates of these tumors are unknown.

OBJECTIVE

To identify the volumetric growth rates of residual meningioma, growth trajectory, and factors associated with progression.

METHODS

Patients with residual meningioma identified at a tertiary neurosurgery center between 2004 and 2020 were retrospectively reviewed. Tumor volume was measured using manual segmentation, after surgery and at every follow-up MRI scan. Growth rates were ascertained using a linear mixed-effects model and nonlinear regression analysis of growth trajectories. Progression was defined according to the Response Assessment in Neuro-Oncology (RANO) criteria (40% volume increase).

RESULTS

There were 236 patients with residual meningioma. One hundred and thirty-two patients (56.0%) progressed according to the RANO criteria, with 86 patients being conservatively managed (65.2%) after progression. Thirteen patients (5.5%) developed clinical progression. Over a median follow-up of 5.3 years (interquartile range, 3.5-8.6 years), the absolute growth rate was 0.11 cm 3 per year and the relative growth rate 4.3% per year. Factors associated with residual meningioma progression in multivariable Cox regression analysis were skull base location (hazard ratio [HR] 1.60, 95% CI 1.02-2.50) and increasing Ki-67 index (HR 3.43, 95% CI 1.19-9.90). Most meningioma exhibited exponential and logistic growth patterns (median R 2 value 0.84, 95% CI 0.60-0.90).

CONCLUSION

Absolute and relative growth rates of residual meningioma are low, but most meet the RANO criteria for progression. Location and Ki-67 index can be used to stratify adjuvant treatment and surveillance paradigms.

Docetaxel targets aggressive methylation profiles and serves as a radiosensitizer in high-risk meningiomas

BACKGROUND

Meningioma is the most common primary intracranial tumor in adults. A subset of these tumors recur and invade the brain, even after surgery and radiation, resulting in significant disability. There is currently no standard-of-care chemotherapy for meningiomas. As genomic DNA methylation profiling can prognostically stratify these lesions, we sought to determine whether any existing chemotherapies might be effective against meningiomas with high-risk methylation profiles.

METHODS

A previously published dataset of meningioma methylation profiles was used to screen for clinically significant CpG methylation events and associated cellular pathways. Based on these results, patient-derived meningioma cell lines were used to test candidate drugs in vitro and in vivo, including efficacy in conjunction with radiotherapy.

RESULTS

We identified 981 genes for which methylation of mapped CpG sites was related to progression-free survival in meningiomas. Associated molecular pathways were cross-referenced with FDA-approved cancer drugs, which nominated Docetaxel as a promising candidate for further preclinical analyses. Docetaxel arrested growth in 17 meningioma cell sources, representing all tumor grades, with a clinically favorable IC50 values ranging from 0.3 nM to 10.7 mM. The inhibitory effects of this medication scaled with tumor doubling time, with maximal benefit in fast-growing lesions. The combination of Docetaxel and radiation therapy increased markers of apoptosis and double-stranded DNA breaks, and extended the survival of mice engrafted with meningioma cells relative to either modality alone.

CONCLUSIONS

Global patterns of DNA methylation may be informative for the selection of chemotherapies against meningiomas, and existing drugs may enhance radiation sensitivity in high-risk cases.

Clinical, Histopathologic and Genetic Features of Rhabdoid Meningiomas

Rhabdoid meningiomas (RM) shows heterogeneous histological findings, and a wide variety of chromosomal copy number alterations (CNA) are associated with an unpredictable course of the disease. In this study, we analyzed a series of 305 RM samples from patients previously reported in the literature and 33 samples from 23 patients studied in our laboratory. Monosomy 22-involving the minimal but most common recurrent region loss of the 22q11.23 chromosomal region was the most observed chromosomal alteration, followed by losses of chromosomes 14, 1, 6, and 19, polysomies of chromosomes 17, 1q, and 20, and gains of 13q14.2, 10p13, and 21q21.2 chromosomal regions. Based on their CNA profile, RM could be classified into two genetic subgroups with distinct clinicopathologic features characterized by the presence of (1) chromosomal losses only and (2) combined losses and gains of several chromosomes. The latter displays a higher frequency of WHO grade 3 tumors and poorer clinical outcomes.

Supervised machine learning algorithms demonstrate proliferation index correlates with long-term recurrence after complete resection of WHO grade I meningioma

OBJECTIVE

Meningiomas are the most common primary intracranial tumor, and resection is a mainstay of treatment. It is unclear what duration of imaging follow-up is reasonable for WHO grade I meningiomas undergoing complete resection. This study examined recurrence rates, timing of recurrence, and risk factors for recurrence in patients undergoing a complete resection (as defined by both postoperative MRI and intraoperative impression) of WHO grade I meningiomas.

METHODS

The authors conducted a retrospective, single-center study examining recurrence risk for adult patients with a single intracranial meningioma that underwent complete resection. Uni- and multivariate nominal logistic regression and Cox proportional hazards analyses were performed to identify variables associated with recurrence and time to recurrence. Two supervised machine learning algorithms were then implemented to confirm factors within the cohort that were associated with recurrence.

RESULTS

The cohort consisted of 823 patients who met inclusion criteria, and 56 patients (6.8%) had recurrence on imaging follow-up. The median age of the cohort was 56 years, and 77.4% of patients were female. The median duration of head imaging follow-up for the entire cohort was 2.7 years, but for the subgroup of patients who had a recurrence, the median follow-up was 10.1 years. Estimated 1-, 5-, 10-, and 15-year recurrence-free survival rates were 99.8% (95% confidence interval [CI] 98.8%-99.9%), 91.0% (95% CI 87.7%-93.6%), 83.6% (95% CI 78.6%-87.6%), and 77.3% (95% CI 69.7%-83.4%), respectively, for the entire cohort. On multivariate analysis, MIB-1 index (odds ratio [OR] per 1% increase: 1.34, 95% CI 1.13-1.58, p = 0.0003) and follow-up duration (OR per year: 1.12, 95% CI 1.03-1.21, p = 0.012) were both associated with recurrence. Gradient-boosted decision tree and random forest analyses both identified MIB-1 index as the main factor associated with recurrence, aside from length of imaging follow-up. For tumors with an MIB-1 index < 8, recurrences were documented up to 8 years after surgery. For tumors with an MIB-1 index ≥ 8, recurrences were documented up to 12 years following surgery.

CONCLUSIONS

Long-term imaging follow-up is important even after a complete resection of a meningioma. Higher MIB-1 labeling index is associated with greater risk of recurrence. Imaging screening for at least 8 years in patients with an MIB-1 index < 8 and at least 12 years for those with an MIB-1 index ≥ 8 may be needed to detect long-term recurrences.

DNA methylation profiling of meningiomas highlights clinically distinct molecular subgroups

BACKGROUND

Introduction of the classification of brain tumours based on DNA methylation profile has significantly changed the diagnostic approach. Due to the paucity of data on the molecular profiling of meningiomas and their clinical implications, no effective therapies and new treatments have been implemented.

METHODS

DNA methylation profiling, copy number analysis, targeted sequencing and H3K27me3 expression was performed on 35 meningiomas and 5 controls.

RESULTS

Unsupervised hierarchical clustering (UHC) analysis revealed four distinct molecular subgroups: Malignant; Intermediate; Benign A, and Benign B. Molecular heterogeneity was observed within the same grade as the Intermediate, Benign A, and Benign B subgroups were composed of WHO grade 1 as well as grade 2 cases. There was association of mutations with distinct methylation subgroups (NF2, AKT1, SMO, TRAF7 and pTERT). Loss of chromosome 22q was observed across all subgroups. 1p/14q co-deletion was seen in 50% of malignant and intermediate while CDKN2A loss was predominantly observed in malignant subgroup (50%). Majority of malignant (75%) and a small proportion of other subgroups (Intermediate: 25%, Benign A: 38.5%, and Benign B: 20%) harboured H3K27me3 loss. 38,734 genes were dysregulated amongst the four subgroups. DKFZ classified 71% cases with acceptable score. On survival analysis, methylation profiling had significant impact on progression-free-survival in WHO grade1 and 2 meningiomas (p = 0.0051).

CONCLUSION

Genome-wide DNA methylation profiling highlights clinically distinct molecular subgroups and heterogeneity within the same grade of meningiomas. Molecular profiling can usher in a paradigm shift in meningioma classification, prognostic prediction, and treatment strategy.

Predictive Power of MIB-1 vs. Mitotic Count on Progression-Free Survival in Skull-Base Meningioma

Simple Summary

Meningiomas are mainly benign intracranial tumors. Nevertheless, risk of recurrence exists in long-term follow-up, so new prognostic markers are still need to be identified. MIB-1 is no diagnostic criterion in WHO classification of meningiomas by now. This retrospective study shows that MIB-1 as well as mitotic count are good predictors for progression-free survival in skull-base meningiomas. The implantation of MIB-1 may enable an improved classification of meningiomas regarding progression-free survival. Moreover, this analysis of skull-base meningiomas shows that current cut-offs may have to be adjusted for meningioma location.

Abstract

Although meningiomas are mainly non-aggressive and slow-growing tumors, there is a remarkable recurrence rate in a long-term follow-up. Proliferative activity and progression-free survival (PFS) differs significantly among the anatomic location of meningiomas. The aim of the present study was to investigate the predictive power of MIB-1 labeling index and mitotic count (MC) regarding the probability of PFS in the subgroup of skull-base meningiomas. A total of 145 patients were included in this retrospective study. Histopathological examinations and follow-up data were collected. Ideal cut-off values for MIB-1 and MC were ≥4.75 and ≥6.5, respectively. MIB-1 as well as MC were good predictors for PFS in skull-base meningiomas. Time-dependent analysis of MIB-1 and MC in prediction of recurrence of skull-base meningioma showed that their prognostic values were comparable, but different cut-offs for MC should be considered regarding the meningioma’s location. As the achievement of a gross total resection can be more challenging in skull-base meningiomas and second surgery implies a higher risk profile, the recurrence risk could be stratified according to these findings and guide decision-making for follow-ups vs. adjuvant therapies.

Low-Dose Acetylsalicylic Acid Treatment in Non-Skull-Base Meningiomas: Impact on Tumor Proliferation and Seizure Burden

MIB-1 index is an important predictor of meningioma progression and was found to be correlated with COX-2 expression. However, the impact of low-dose acetylsalicylic acid (ASA) on MIB-1 index and clinical symptoms is unclear. Between 2009 and 2022, 710 patients with clinical data, tumor-imaging data, inflammatory laboratory (plasma fibrinogen, serum C-reactive protein) data, and neuropathological reports underwent surgery for primary cranial WHO grade 1 and 2 meningioma. ASA intake was found to be significantly associated with a low MIB-1 labeling index in female patients ≥ 60 years. Multivariable analysis demonstrated that female patients ≥ 60 years with a non-skull-base meningioma taking ASA had a significantly lower MIB-1 index (OR: 2.6, 95%: 1.0–6.6, p = 0.04). Furthermore, the intake of ASA was independently associated with a reduced burden of symptomatic epilepsy at presentation in non-skull-base meningiomas in both genders (OR: 3.8, 95%CI: 1.3–10.6, p = 0.03). ASA intake might have an anti-proliferative effect in the subgroup of elderly female patients with non-skull-base meningiomas. Furthermore, anti-inflammatory therapy seems to reduce the burden of symptomatic epilepsy in non-skull-base meningiomas. Further research is needed to investigate the role of anti-inflammatory therapy in non-skull-base meningiomas.

MAC-spinal meningioma score: A proposal for a quick-to-use scoring sheet of the MIB-1 index in sporadic spinal meningiomas

Objective

MIB-1 index is an important predictor of meningioma progression. However, MIB-1 index is not available in the preoperative tailored medical decision-making process. A preoperative scoring sheet independently estimating MIB-1 indices in spinal meningioma (SM) patients has not been investigated so far.

Methods

Between 2000 and 2020, 128 patients with clinical data, tumor imaging data, inflammatory laboratory (plasma fibrinogen, serum C-reactive protein) data, and neuropathological reports (MIB-1, mitotic count, CD68 staining) underwent surgery for spinal WHO grade 1 and 2 meningioma.

Results

An optimal MIB-1 index cut-off value (≥5/<5) predicting recurrence was calculated by ROC curve analysis (AUC: 0.83; 95%CI: 0.71-0.96). An increased MIB-1 index (≥5%) was observed in 55 patients (43.0%) and multivariable analysis revealed significant associations with baseline Modified McCormick Scale ≥2, age ≥65, and absence of calcification. A four-point scoring sheet (MAC-Spinal Meningioma) based on Modified McCormick, Age, and Calcification facilitates prediction of the MIB-1 index (sensitivity 71.1%, specificity 60.0%). Among those patients with a preoperative MAC-Meningioma Score ≥3, the probability of a MIB-1 index ≥5% was 81.3%.

Conclusion

This novel score (MAC-Spinal Meningioma) supports the preoperative estimation of an increased MIB-1 index, which might support preoperative patient-surgeon consultation, surgical decision making and enable a tailored follow-up schedule or an individual watch-and-wait strategy.

Outcomes following surgical resection of cystic intracranial meningiomas

INTRODUCTION

Cystic meningiomas are rare, accounting for 2-7% of all intracranial meningiomas. Little is known regarding whether these meningiomas behave differently compared to solid meningiomas. We sought to study this relatively uncommon imaging appearance of meningioma and to evaluate its clinical significance.

METHODS

A single-institution retrospective cohort study of surgically-treated meningioma patients between 2000 and 2019 was conducted. Cystic meningioma was defined as a tumor with an intratumoral or peritumoral cyst present on preoperative imaging. Demographics, preoperative imaging, histopathology characteristics, operative data, and surgical outcomes were reviewed. Imaging variables, histopathology and outcomes were reported for cystic meningiomas and compared with non-cystic meningiomas. Univariate/multivariable analyses were conducted.

RESULTS

Of 737 total meningiomas treated surgically, 38 (5.2%) were cystic. Gross total resection (GTR) was achieved in 84.2% of cystic meningioma patients. Eighty-two percent of cystic meningiomas were WHO grade I (n = 31), 15.7% were grade II and 2.6% were grade III. Most cystic meningiomas had low Ki-67/MIB-1 proliferation index (n = 24, 63.2%). A total of 18.4% (n = 7) patients with cystic meningioma had recurrence compared to 12.2% (n = 80) of patients with non-cystic meningioma (p = 0.228). No significant difference in median time to recurrence was observed between cystic and non-cystic meningiomas (25.4, Q1:13.9, Q3:46.9 months vs. 13.4, Q1:8.6, Q3:35.5 months, p = 0.080).

CONCLUSIONS

A small portion of intracranial meningiomas have cystic characteristics on imaging. Cystic meningiomas are frequently WHO grade I, have low proliferation index, and had similar outcomes compared to non-cystic meningioma. Cysts in meningioma may not be a surrogate to determine aggressive meningioma behavior.

Efficient Prediction of Ki-67 Proliferation Index in Meningiomas on MRI: From Traditional Radiological Findings to a Machine Learning Approach

Background/aim This study aimed to explore the value of radiological and radiomic features retrieved from magnetic resonance imaging in the prediction of a Ki-67 proliferative index in meningioma patients using a machine learning model. Methods This multicenter, retrospective study included 371 patients collected from two centers. The Ki-67 expression was classified into low-expressed and high-expressed groups with a threshold of 5%. Clinical features and radiological features were collected and analyzed by using univariate and multivariate statistical analyses. Radiomic features were extracted from contrast-enhanced images, followed by three independent feature selections. Six predictive models were constructed with different combinations of features by using linear discriminant analysis (LDA) classifier. Results The multivariate analysis suggested that the presence of intratumoral necrosis (p = 0.032) and maximum diameter (p < 0.001) were independently correlated with a high Ki-67 status. The predictive models showed good performance with AUC of 0.837, accuracy of 0.810, sensitivity of 0.857, and specificity of 0.771 in the internal test and with AUC of 0.700, accuracy of 0.557, sensitivity of 0.314, and specificity of 0.885 in the external test. Conclusion The results of this study suggest that the predictive model can efficiently predict the Ki-67 index of meningioma patients to facilitate the therapeutic management.

Bone Invasive Meningioma: Recent Advances and Therapeutic Perspectives

Meningioma is the most common primary neoplasm of the central nervous system (CNS). Generally, these tumors are benign and have a good prognosis. However, treatment can be challenging in cases with aggressive variants and poor prognoses. Among various prognostic factors that have been clinically investigated, bone invasion remains controversial owing to a limited number of assessments. Recent study reported that bone invasion was not associated with WHO grades, progression, or recurrence. Whereas, patients with longer-recurrence tended to have a higher incidence of bone invasion. Furthermore, bone invasion may be a primary preoperative predictor of the extent of surgical resection. Increasing such evidence highlights the potential of translational studies to understand bone invasion as a prognostic factor of meningiomas. Therefore, this mini-review summarizes recent advances in pathophysiology and diagnostic modalities and discusses future research directions and therapeutic strategies for meningiomas with bone invasion.

Synthesizing Molecular and Immune Characteristics to Move Beyond WHO Grade in Meningiomas: A Focused Review

No portion of this manuscript has previously been presented. Meningiomas, the most common primary intracranial tumors, are histologically categorized by the World Health Organization (WHO) grading system. While higher WHO grade is generally associated with poor clinical outcomes, a significant subset of grade I tumors recur or progress, indicating a need for more reliable models of meningioma behavior. Several groups have developed risk scores based on molecular or immunologic characteristics. These classification schemes show promise, with several models preliminarily demonstrating similar or superior accuracy to WHO grading. Improved understanding of immune system recognition and targeting of meningioma subtypes is necessary to advance the predictive power, as well as develop new therapies. Here, we characterize meningioma molecular drivers, predictive of recurrence and progression, and describe specific aspects of the immune response to meningiomas while highlighting critical questions and ongoing research. Relevant manuscripts of interest were identified using a systematic approach and synthesized into this focused review. Finally, we summarize the ongoing and completed clinical trials for immunotherapy in meningiomas and offer perspective on future directions.

Clinical significance of NF2 alteration in grade I meningiomas revisited; prognostic impact integrated with extent of resection, tumour location, and Ki-67 index

NF2 alteration is the most commonly-found genetic abnormality in meningiomas and is known to initiate events for aggressive-type meningiomas. Whereas the prognosis of meningiomas differs depending on their epigenomic/transcriptomic profile, the effect of NF2 alteration on the prognosis of benign meningiomas is not fully elucidated. This study aimed to probe the importance of NF2 alteration in prognosis of WHO grade I meningiomas. A long-term retrospective follow-up (5.3 ± 4.5 years) study involving 281 consecutive WHO grade I meningioma patients was performed. We assessed tumour recurrence in correlation with extent of resection (EOR), histopathological findings, tumour location, and NF2 alteration. "NF2 meningioma" was defined as meningiomas with presence of NF2 mutation and/or 22q loss. Overall, NF2 meningioma per se was not a predictor of prognosis in the whole cohort; however, it was a predictor of recurrence in supratentorial meningiomas, together with EOR and Ki-67. In a striking contrast, NF2 meningioma showed a better prognosis than non-NF2 meningioma in infratentorial lesion. Supratentorial NF2 meningiomas had higher Ki-67 and forkhead box protein M1 expression than those of others, possibly explaining the worse prognosis in this subtype. The combination of NF2 alteration, high Ki-67 and supratentorial location defines subgroup with the worst prognosis among WHO grade I meningiomas. Clinical connotation of NF2 alteration in terms of prognosis of WHO grade I meningioma differs in an opposite way between supratentorial and infratentorial tumors. Integrated anatomical, histopathological, and genomic classifications will provide the best follow-up schedule and proactive measures.

A Spotlight on the Role of Radiomics and Machine-Learning Applications in the Management of Intracranial Meningiomas: A New Perspective in Neuro-Oncology: A Review

Background: In recent decades, the application of machine learning technologies to medical imaging has opened up new perspectives in neuro-oncology, in the so-called radiomics field. Radiomics offer new insight into glioma, aiding in clinical decision-making and patients’ prognosis evaluation. Although meningiomas represent the most common primary CNS tumor and the majority of them are benign and slow-growing tumors, a minor part of them show a more aggressive behavior with an increased proliferation rate and a tendency to recur. Therefore, their treatment may represent a challenge. Methods: According to PRISMA guidelines, a systematic literature review was performed. We included selected articles (meta-analysis, review, retrospective study, and case–control study) concerning the application of radiomics method in the preoperative diagnostic and prognostic algorithm, and planning for intracranial meningiomas. We also analyzed the contribution of radiomics in differentiating meningiomas from other CNS tumors with similar radiological features. Results: In the first research stage, 273 papers were identified. After a careful screening according to inclusion/exclusion criteria, 39 articles were included in this systematic review. Conclusions: Several preoperative features have been identified to increase preoperative intracranial meningioma assessment for guiding decision-making processes. The development of valid and reliable non-invasive diagnostic and prognostic modalities could have a significant clinical impact on meningioma treatment.

Inflammatory Tumor Microenvironment in Cranial Meningiomas: Clinical Implications and Intraindividual Reproducibility

The MIB-1 index was demonstrated to be significantly correlated to meningioma recurrence. However, to date, the relationship of the intraindividual course of the MIB-1 index and the growth fraction, respectively, to clinical tumor recurrence has not been demonstrated in cranial WHO grade 1 and 2 meningiomas. In the present paper, we compare the MIB-1 indices of 16 solely surgically treated primary meningiomas and their recurrent tumors regarding the course of the MIB-1 indices, time to recurrence, reproducibility and factors influencing the intraindividual MIB-1 indices. Regression analyses revealed (1) a strong intra-lab reproducibility (r = 0.88) of the MIB-1 index at the second versus the first operation, corresponding to a constant intrinsic growth activity of an individual meningioma, (2) a significant inverse correlation of both primary (r = −0.51) and secondary (r = −0.70) MIB-1 indices to time to recurrence, and (3) male sex, low plasma fibrinogen and diffuse CD68⁺ macrophage infiltrates contribute to an increase in the MIB-1 index. A strong intraindividual reproducibility of the MIB-1 index and a direct relationship of the MIB-1 index to the time to recurrence were observed. Individual MIB-1 indices might be used for tailored follow-up imaging intervals. Further research on the role of macrophages and inflammatory burden in the regrowth potential of meningiomas are needed.

Risk Stratification to Define the Role of Radiotherapy for Benign and Atypical Meningioma: A Recursive Partitioning Analysis

BACKGROUND

The role of adjuvant radiotherapy (RT) for benign or atypical meningioma is controversial.

OBJECTIVE

To identify prognostic factors and a subgroup that could be potentially indicated for adjuvant RT.

METHODS

A total of 336 patients with benign and 157 patients with atypical meningioma underwent surgical resection between January 2015 and December 2019. We retrospectively analyzed 407 patients who did not receive adjuvant RT to stratify risk groups for recurrence. A recursive partitioning analysis (RPA) with the prognostic factors for their failure-free survival (FFS) divided the patients into risk groups.

RESULTS

The 3-year FFS with surgical resection only was 76.5%. Identified prognostic factors for FFS were skull base location, tumor size, brain invasion, a Ki-67 proliferation index of ≥5%, and subtotal resection. The RPA-classified patients were divided into 4 risk groups: very low, low, intermediate, and high, and their 3-year FFS were 98.9%, 78.5%, 59.8%, and 34.2%, respectively. Intermediate-risk and high-risk groups comprise the patients with meningioma of sizes ≥2 cm after subtotal resection or meningioma of sizes >3 cm, located in the skull base or with brain invasion, respectively. After combining with patients treated with adjuvant RT, no FFS benefit was found in the very low-risk and low-risk groups after adjuvant RT, whereas significantly improved FFS was found in the intermediate-risk and high-risk groups (P < .05).

CONCLUSION

The RPA classification revealed a subgroup of patients who could be potentially indicated for adjuvant RT even after gross total resection or for whom adjuvant RT could be deferred.

Proliferative Potential, and Inflammatory Tumor Microenvironment in Meningioma Correlate with Neurological Function at Presentation and Anatomical Location-From Convexity to Skull Base and Spine

Simple Summary

The World Health Organization (WHO) classification grades meningiomas exclusively due to their histopathological features. Meningiomas are predominantly benign intracranial entities, and surgical resection represents the therapy of choice. However, risk of progression and tailored scheduling of follow-up appointments are significantly influenced by various items, such as immunohistochemistry (e.g., MIB-1 index). Emerging evidence focuses attention on the anatomic location of meningiomas, especially regarding the differentiation between skull base and non-skull base meningiomas. In the present study, we therefore investigated demographic, histopathological, and laboratory variables regarding their association with the anatomic location. We found that spinal meningiomas have a significantly lower proliferative activity, less density of macrophage infiltrates, and a longer time to tumor progression. Moreover, increased MIB-1 indices are significantly associated with location-specific baseline symptoms (e.g., convexity: seizure burden, medial skull base: decreased vision, spinal: ambulatory ability). Therefore, anatomic location might be considered as a future subclassification in the grading of the prognosis of meningiomas.

Abstract

Emerging evidence emphasizes the prognostic importance of meningioma location. The present investigation evaluates whether progression-free survival (PFS), proliferative potential, World Health Organization (WHO) grades, and inflammatory burden differ between anatomical locations (skull base, non-skull base, and spinal) meningiomas. Five-hundred-forty-one patients underwent Simpson grade I or II resection for WHO grade 1 or 2 meningiomas. Univariable analysis revealed that spinal meningioma patients are significantly older, had a worse baseline Karnofsky Performance Status (KPS), higher acute-phase protein levels, lower incidence of WHO grade 2, lower mitotic counts, lower MIB-1 index, and less CD68⁺ macrophage infiltrates. Multivariable analysis identified WHO grade 2 (OR: 2.1, 95% CI: 1.1–3.7, p = 0.02) and cranial location (OR: 3.0, 95% CI: 1.8–4.9, p = 0.001) as independent predictors of diffuse CD68⁺ macrophage infiltrates. The mean PFS in cranial meningiomas was 115.9 months (95% CI: 107.5–124.3), compared to 162.2 months (95% CI: 150.5–174.0; log-rank test: p = 0.02) in spinal meningiomas. Multivariable Cox regression analysis revealed cranial location as an independent predictor (HR: 4.7, 95% CI: 1.0–21.3, p = 0.04) of shortened PFS. Increased MIB-1 indices ≥5% were significantly associated with location-specific deficits at presentation, such as decreased vision and seizure burden. Spinal meningiomas have a significantly longer PFS time and differ from the cranial meningiomas regarding MIB-1 index and density of tumor-associated macrophages.

BAP1-deficient meningioma presenting with trabecular architecture and cytokeratin expression: a report of two cases and review of the literature

AIMS

BRCA (BReast CAncer gene)-associated protein 1 (BAP1), encoded by the BAP1 gene, a tumour suppressor that is lost in several cancers. Importantly, such mutations have been shown to be susceptible to poly (ADP-ribose) polymerase (PARP) inhibition in preclinical studies, offering hope for targeted therapy. While rare, BAP1 loss has been observed in a subset of rhabdoid and papillary meningioma and is associated with earlier recurrence. We seek to add to the literature on this rare disease and advocate for more routine BAP1 testing.

METHODS

We present a report of two cases of BAP1-deficient meningioma and review the available literature on this rare entity.

RESULTS

Both cases present with a distinct trabecular architecture without rhabdoid or papillary features. Interestingly, both also presented with radiographic and histopathological findings unusual for meningioma. While immunohistochemistry and genetic sequencing confirmed BAP1 loss, DNA methylation analysis was required to confirm the final diagnosis.

CONCLUSIONS

We suggest that BAP1-deficient meningioma should be considered in the differential diagnosis of extra-axial central nervous system (CNS) tumours with atypical imaging or histopathological features and that BAP1 loss may constitute a clinically important meningioma subtype with opportunities for targeted therapy.

Increased proliferation is associated with CNS invasion in meningiomas

INTRODUCTION

Meningiomas are the most common benign intracranial neoplasms. CNS invasion in meningiomas has been integrated into the 2016 WHO classification of CNS tumors as a stand-alone criterion for atypia. Since then, its prognostic impact has been debated based on contradictory results from retrospective analyses. The aim of the study was to elucidate whether histopathological evidence of CNS invasion is associated with increased proliferative potential.

METHODS

We have conducted a quantified measurement of the proliferation marker Ki67 and analyzed its association with CNS invasion determined by histology together with other established prognostic markers of progression. Routine, immunohistochemical staining for Ki67 were digitalized and automatic quantification was done using Image J software.

RESULTS

Overall, 1718 meningiomas were assessed. Histopathological CNS invasion was seen in 108 cases (6.7%). Uni- and multivariate analysis revealed a significantly higher Ki67 proliferation rate in meningiomas with CNS invasion (p < 0.0001 and p = 0.0098, respectively).

CONCLUSIONS

Meningiomas with histopathological CNS invasion show a higher proliferative activity.

Machine Learning Using Multiparametric Magnetic Resonance Imaging Radiomic Feature Analysis to Predict Ki-67 in World Health Organization Grade I Meningiomas

BACKGROUND

Although World Health Organization (WHO) grade I meningiomas are considered "benign" tumors, an elevated Ki-67 is one crucial factor that has been shown to influence tumor behavior and clinical outcomes. The ability to preoperatively discern Ki-67 would confer the ability to guide surgical strategy.

OBJECTIVE

In this study, we develop a machine learning (ML) algorithm using radiomic feature analysis to predict Ki-67 in WHO grade I meningiomas.

METHODS

A retrospective analysis was performed for a cohort of 306 patients who underwent surgical resection of WHO grade I meningiomas. Preoperative magnetic resonance imaging was used to perform radiomic feature extraction followed by ML modeling using least absolute shrinkage and selection operator wrapped with support vector machine through nested cross-validation on a discovery cohort (n = 230), to stratify tumors based on Ki-67 <5% and ≥5%. The final model was independently tested on a replication cohort (n = 76).

RESULTS

An area under the receiver operating curve (AUC) of 0.84 (95% CI: 0.78-0.90) with a sensitivity of 84.1% and specificity of 73.3% was achieved in the discovery cohort. When this model was applied to the replication cohort, a similar high performance was achieved, with an AUC of 0.83 (95% CI: 0.73-0.94), sensitivity and specificity of 82.6% and 85.5%, respectively. The model demonstrated similar efficacy when applied to skull base and nonskull base tumors.

CONCLUSION

Our proposed radiomic feature analysis can be used to stratify WHO grade I meningiomas based on Ki-67 with excellent accuracy and can be applied to skull base and nonskull base tumors with similar performance achieved.

Past medical history of tumors other than meningioma is a negative prognostic factor for tumor recurrence in meningiomas WHO grade I

Background

Prognostic markers for meningioma recurrence are needed to guide patient management. Apart from rare hereditary syndromes, the impact of a previous unrelated tumor disease on meningioma recurrence has not been described before.

Methods

We retrospectively searched our database for patients with meningioma WHO grade I and complete resection provided between 2002 and 2016. Demographical, clinical, pathological, and outcome data were recorded. The following covariates were included in the statistical model: age, sex, clinical history of unrelated tumor disease, and localization (skull base vs. convexity). Particular interest was paid to the patients’ past medical history. The study endpoint was date of tumor recurrence on imaging. Prognostic factors were obtained from multivariate proportional hazards models.

Results

Out of 976 meningioma patients diagnosed with a meningioma WHO grade I, 416 patients fulfilled our inclusion criteria. We encountered 305 women and 111 men with a median age of 57 years (range: 21–89 years). Forty-six patients suffered from a tumor other than meningioma, and no TERT mutation was detected in these patients. There were no differences between patients with and without a positive oncological history in terms of age, tumor localization, or mitotic cell count. Clinical history of prior tumors other than meningioma showed the strongest association with meningioma recurrence (p = 0.004, HR = 3.113, CI = 1.431–6.771) both on uni- and multivariate analysis.

Conclusion

Past medical history of tumors other than meningioma might be associated with an increased risk of meningioma recurrence. A detailed pre-surgical history might help to identify patients at risk for early recurrence.

FORGE: A Novel Scoring System to Predict the MIB-1 Labeling Index in Intracranial Meningiomas

Simple Summary

Meningiomas are predominantly benign intracranial tumors, and surgical therapy represents the treatment of choice. However, the risk of recurrence and scheduling of follow-up intervals are significantly influenced by immunohistochemical items such as the MIB-1 labeling index. To date, it is not possible to integrate this essential information into the pre- or intraoperative surgical decision making. In the present study, we therefore analyzed baseline variables associated with the MIB-1 labeling index. We found four easily identifiable and routinely recorded risk factors for an increased MIB-1 index and developed a simple and quick-to-use score that allows us to estimate the risk of an elevated MIB-1 index prior to the surgical resection. Furthermore, this score seems to predict the progression-free survival in intracranial meningiomas. We believe that this score might us to more reliably guide patients in preoperative surgical strategy planning and postoperative follow-up scheduling.

Abstract

The MIB-1 index is an essential predictor of progression-free-survival (PFS) in meningioma. To date, the MIB-1 index is not available in preoperative treatment planning. A preoperative score estimating the MIB-1 index in patients with intracranial meningiomas has not been investigated so far. Between 2013 and 2019, 208 patients with tumor morphology data, MIB-1 index data, and plasma fibrinogen and serum C-reactive protein (CRP) data underwent surgery for intracranial WHO grade I and II meningioma. An optimal MIB-1 index cut-off value (≥6/<6) in the prediction of recurrence was determined by ROC curve analysis (AUC: 0.71; 95% CI: 0.55–0.87). A high MIB-1 index (≥6%) was present in 50 cases (24.0%) and was significantly associated with male sex, peritumoral edema, low baseline CRP, and low fibrinogen level in the multivariate analysis. A scoring system (“FORGE”) based on sex, peritumoral edema, preoperative CRP value, and plasma fibrinogen level supports prediction of the MIB-1 index (sensitivity 62%, specificity 79%). The MIB-1 labeling index and the FORGE score are significantly associated with an increased risk of poor PFS time. We suggest a novel score (“FORGE”) to preoperatively estimate the risk of an increased MIB-1 index (≥6%), which might help in surgical decision making and follow-up interval determination and inform future trials investigating inflammatory burden and proliferative activity.

Biomarkers for differentiating grade II meningiomas from grade I: a systematic review

INTRODUCTION

There are a number of prognostic markers (methylation, CDKN2A/B) described to be useful for the stratification of meningiomas. However, there are currently no clinically validated biomarkers for the preoperative prediction of meningioma grade, which is determined by the histological analysis of tissue obtained from surgery. Accurate preoperative biomarkers would inform the pre-surgical assessment of these tumours, their grade and prognosis and refine the decision-making process for treatment. This review is focused on the more controversial grade II tumours, where debate still surrounds the need for adjuvant therapy, repeat surgery and frequency of follow up.

METHODS

We evaluated current literature for potential grade II meningioma clinical biomarkers, focusing on radiological, biochemical (blood assays) and immunohistochemical markers for diagnosis and prognosis, and how they can be used to differentiate them from grade I meningiomas using the post-2016 WHO classification. To do this, we conducted a PUBMED, SCOPUS, OVID SP, SciELO, and INFORMA search using the keywords; 'biomarker', 'diagnosis', 'atypical', 'meningioma', 'prognosis', 'grade I', 'grade 1', 'grade II' and 'grade 2'.

RESULTS

We identified 1779 papers, 20 of which were eligible for systematic review according to the defined inclusion and exclusion criteria. From the review, we identified radiological characteristics (irregular tumour shape, tumour growth rate faster than 3cm³/year, high peri-tumoural blood flow), blood markers (low serum TIMP1/2, high serum HER2, high plasma Fibulin-2) and histological markers (low H3K27me3, low SMARCE1, low AKAP12, high ARIDB4) that may aid in differentiating grade II from grade I meningiomas.

CONCLUSION

Being able to predict meningioma grade at presentation using the radiological and blood markers described may influence management as the likely grade II tumours will be followed up or treated more aggressively, while the histological markers may prognosticate progression or post-treatment recurrence. This to an extent offers a more personalised treatment approach for patients.