Integrative assessment of brain and bone invasion in meningioma patients

Customised pre-operative cranioplasty to achieve maximal surgical resection of tumours with osseous involvement-a case series

PURPOSE

Surgical resection with bony margins would be the treatment of choice for tumours with osseous involvement such as meningiomas and metastasis. By developing and designing pre-operative customised 3D modelled implants, the patient can undergo resection of meningioma and repair of bone defect in the same operation. We present a generalisable method for designing pre-operative cranioplasty in patients to repair the bone defect after the resection of tumours.

MATERIALS AND METHODS

We included six patients who presented with a tumour that was associated with overlying bone involvement. They underwent placement of customised cranioplasty in the same setting. A customised implant using a pre-operative imaging was designed with a 2-cm margin to allow for any intra-operative requirements for extending the craniectomy.

RESULTS

Six patients were evaluated in this case series. Four patients had meningiomas, 1 patient had metastatic breast cancer on final histology, and 1 patient was found to have an intra-osseous arteriovenous malformation. Craniectomy based on margins provided by a cutting guide was fashioned. After tumour removal and haemostasis, the cranioplasty was then placed. All patients recovered well post-operatively with satisfactory cosmetic results. No wound infection was reported in our series.

CONCLUSION

Our series demonstrate the feasibility of utilising pre-designed cranioplasty for meningiomas and other tumours with osseous involvement. Following strict infection protocols, minimal intra-operative handling/modification of the implant, and close follow-up has resulted in good cosmetic outcomes with no implant-related infections.

The usefulness of [68 Ga]Ga-DOTA-JR11 PET/CT in patients with meningioma: comparison with MRI

PURPOSE

Clinical studies of PET imaging using SSTR2 agonists have demonstrated high accuracy and correlation with SSTR2 expression in meningiomas. However, the usefulness of the SSTR2 antagonist with [68 Ga]Ga-DOTA-JR11 is uncertain. To evaluate the diagnostic performance of [68 Ga]Ga-DOTA-JR11 PET/CT and to clarify tumor characteristics in patients with suspected meningiomas.

MATERIALS AND METHODS

Patients with suspected de novo or recurrent meningioma in complex locations or atypical images were enrolled from August 2021 to October 2022 in prospective study. All patients underwent contrast-enhanced MRI (CE-MRI), [68 Ga]Ga-DOTA-JR11 PET/CT, and histopathological evaluation. Tumor uptake of [68 Ga]Ga-DOTA-JR11 was measured by SUVmax and tumor-endocranium ratio (TBR). Diagnostic performance was compared between PET and MRI.

RESULTS

Of 36 (50.0 ± 13.0 years of age, 20 women) patients, 32 were histopathologically confirmed meningiomas and four with other tumors. [68 Ga]Ga-DOTA-JR11 uptake was significantly higher in meningioma patients than in those with other tumors (SUVmax: 13.6 ± 7.7 vs. 5.2 ± 3.0, P < 0.001; TBR: 64.2 ± 27.7 vs. 25.0 ± 18.9, P = 0.001). [68 Ga]Ga-DOTA-JR11 PET/CT detected 31 meningiomas, while CE-MRI detected 17 meningiomas of 25 initial diagnosis and 11 recurrent tumors; [68 Ga]Ga-DOTA-JR11 PET had an incremental diagnostic value of 24% (6/25) over MRI in the group of initial diagnosis. There was no statistically significant difference in diagnostic efficacy between PET and MRI (P = 0.45) for all 36 patients. In skull base meningiomas, PET provided a more definitive diagnosis of pituitary involvement (in 12, not in12), compared to MRI (in eight, possible in six, possible not in six, not in four). PET revealed bone involvement in all 14 patients proven by pathology, while MRI identified only 11.

CONCLUSIONS

[68 Ga]Ga-DOTA-JR11 PET/CT provided high image quality and presented an ideal diagnostic performance in detecting meningioma and evaluating the involvement of the pituitary and bone. The study provides valuable evidence for the use of [68 Ga]Ga-DOTA-JR11 PET/CT as a complementary imaging modality to CE-MRI in the evaluation of meningiomas.

Clinicopathological characteristics and prognostic factors of atypical meningiomas with bone invasion: a retrospective analysis of nine cases and literature review

BACKGROUND

Meningiomas are the most common primary neoplasms of the central nervous system in adults, arising from the arachnoid cap cells. Thus, grade 2 meningiomas are situated on the border between benignity and malignancy. Among the many prognostic factors that have been investigated in these tumors, bone invasion is one of them.

OBJECTIVE

The aim of our study was to identify whether bone invasion influences tumor recurrence and progression-free survival (PFS) in patients with atypical meningiomas (AMs).

PATIENTS, MATERIALS AND METHODS

Out of 81 patients with AMs followed over a period of five years, we identified nine patients with bone invasion. We analyzed their demographic, clinical, imaging, and pathological characteristics, such as age, gender, radiological aspects, morphological features, extent of resection, recurrence rate, and PFS over a follow-up period of 60 months. Bone invasion was determined based on preoperative, surgical, and pathological reports.

RESULTS

Out of the nine patients with bone invasion, four had convexity meningiomas, four had parasagittal meningiomas and one had a falcine meningioma. Regarding tumor recurrence∕progression, most patients (n=6) recurred within the first 24 months after surgery. Our study showed that the early recurrence/progression of tumor (at 12 months) correlated with extensive presence of malignancy criteria, especially with the presence of 15-18 mitoses∕10 high-power fields, as well as with large foci of spontaneous necrosis, but also with tumor bone infiltration, extensive bone lamellae destruction, and tumor infiltration of adjacent muscle with its atrophy due to tumor compression. Patients with bone invasion had a PFS of 29.3 months, compared to patients without invasion who had a higher PFS (49.3 months). Significant statistical associations were observed between bone invasion and tumor recurrence (p=0.002) and PFS (p=0.004).

CONCLUSIONS

Our study emphasizes the importance of a thorough histopathological examination of the surgical specimen, which can provide significant data for the assessment of the progression of an AM [World Health Organization (WHO) grade 2] with bone invasion. AM infiltration in adjacent bone and muscle increases the rate of tumor recurrence and decreases PFS over a follow-up period of 60 months.

Next-generation PET/CT imaging in meningioma-first clinical experiences using the novel SSTR-targeting peptide [18F]SiTATE

BACKGROUND

Somatostatin-receptor (SSTR)-targeted PET/CT provides important clinical information in addition to standard imaging in meningioma patients. [18F]SiTATE is a novel, 18F-labeled SSTR-targeting peptide with superior imaging properties according to preliminary data. We provide the first [18F]SiTATE PET/CT data of a large cohort of meningioma patients.

METHODS

Patients with known or suspected meningioma undergoing [18F]SiTATE PET/CT were included. Uptake intensity (SUV) of meningiomas, non-meningioma lesions, and healthy organs were assessed using a 50% isocontour volume of interest (VOI) or a spherical VOI, respectively. Also, trans-osseous extension on PET/CT was assessed.

RESULTS

A total of 107 patients with 117 [18F]SiTATE PET/CT scans were included. Overall, 231 meningioma lesions and 61 non-meningioma lesions (e.g., post-therapeutic changes) were analyzed. Physiological uptake was lowest in healthy brain tissue, followed by bone marrow, parotid, and pituitary (SUVmean 0.06 ± 0.04 vs. 1.4 ± 0.9 vs. 1.6 ± 1.0 vs. 9.8 ± 4.6; p < 0.001). Meningiomas showed significantly higher uptake than non-meningioma lesions (SUVmax 11.6 ± 10.6 vs. 4.0 ± 3.3, p < 0.001). Meningiomas showed significantly higher uptake than non-meningioma lesions (SUVmax 11.6±10.6 vs. 4.0±3.3, p<0.001). 93/231 (40.3%) meningiomas showed partial trans-osseous extension and 34/231 (14.7%) predominant intra-osseous extension. 59/231 (25.6%) meningioma lesions found on PET/CT had not been reported on previous standard imaging.

CONCLUSION

This is the first PET/CT study using an 18F-labeled SSTR-ligand in meningioma patients: [18F]SiTATE provides extraordinary contrast in meningioma compared to healthy tissue and non-meningioma lesions, which leads to a high detection rate of so far unknown meningioma sites and osseous involvement. Having in mind the advantageous logistic features of 18F-labeled compared to 68Ga-labeled compounds (e.g., longer half-life and large-badge production), [18F]SiTATE has the potential to foster a widespread use of SSTR-targeted imaging in neuro-oncology.

The efficacy of preoperative MRI features in the diagnosis of meningioma WHO grade and brain invasion

Objective

The preoperative MRI scans of meningiomas were analyzed based on the 2021 World Health Organization (WHO) Central Nervous System (CNS) Guidelines, and the efficacy of MRI features in diagnosing WHO grades and brain invasion was analyzed.

Materials and methods

The data of 675 patients with meningioma who underwent MRI in our hospital from 2006 to 2022, including 108 with brain invasion, were retrospectively analyzed. Referring to the WHO Guidelines for the Classification of Central Nervous System Tumors (Fifth Edition 2021), 17 features were analyzed, with age, sex and meningioma MRI features as risk factors for evaluating WHO grade and brain invasion. The risk factors were identified through multivariable logistic regression analysis, and their receiver operating characteristic (ROC) curves for predicting WHO grades and brain invasion were generated, and the area under the curve (AUC), sensitivity and specificity were calculated.

Results

Univariate analysis showed that sex, tumor size, lobulated sign, peritumoral edema, vascular flow void, bone invasion, tumor-brain interface, finger-like protrusion and mushroom sign were significant for diagnosing meningioma WHO grades, while these features and ADC value were significant for predicting brain invasion (P < 0.05). Multivariable logistic regression analysis showed that the lobulated sign, tumor-brain interface, finger-like protrusion, mushroom sign and bone invasion were independent risk factors for diagnosing meningioma WHO grades, while the above features, tumor size and ADC value were independent risk factors for diagnosing brain invasion (P < 0.05). The tumor-brain interface had the highest efficacy in evaluating WHO grade and brain invasion, with AUCs of 0.779 and 0.860, respectively. Combined, the variables had AUCs of 0.834 and 0.935 for determining WHO grade and brain invasion, respectively.

Conclusion

Preoperative MRI has excellent performance in diagnosing meningioma WHO grade and brain invasion, while the tumor-brain interface serves as a key factor. The preoperative MRI characteristics of meningioma can help predict WHO grade and brain invasion, thus facilitating complete lesion resection and improving patient prognosis.

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.

Nomogram based on MRI can preoperatively predict brain invasion in meningioma

Predicting brain invasion preoperatively should help to guide surgical decision-making and aid the prediction of meningioma grading and prognosis. However, only a few imaging features have been identified to aid prediction. This study aimed to develop and validate an MRI-based nomogram to predict brain invasion by meningioma. In this retrospective study, 658 patients were examined via routine MRI before undergoing surgery and were diagnosed with meningioma by histopathology. Least absolute shrinkage and selection operator (LASSO) regularization was used to determine the optimal combination of clinical characteristics and MRI features for predicting brain invasion by meningiomas. Logistic regression and receiver operating characteristic (ROC) curve analyses were used to determine the discriminatory ability. Furthermore, a nomogram was constructed using the optimal MRI features, and decision curve analysis was used to validate the clinical usefulness of the nomogram. Eighty-one patients with brain invasion and 577 patients without invasion were enrolled. According to LASSO regularization, tumour shape, tumour boundary, peritumoral oedema, and maximum diameter were independent predictors of brain invasion. The model showed good discriminatory ability for predicting brain invasion in meningiomas, with an AUC of 0.905 (95% CI, 0.871-0.940) vs 0.898 (95% CI, 0.849-0.947) and sensitivity of 93.0% vs 92.6% in the training vs validation cohorts. Our predictive model based on MRI features showed good performance and high sensitivity for predicting the risk of brain invasion in meningiomas and can be applied in the clinical setting.

Postoperative progression of intracranial grade II-III solitary fibrous tumor/hemangiopericytoma: predictive value of preoperative magnetic resonance imaging semantic features

BACKGROUND

Preoperative prediction of postoperative tumor progression of intracranial grade II-III hemangiopericytoma is the basis for clinical treatment decisions.

PURPOSE

To use preoperative magnetic resonance imaging (MRI) semantic features for predicting postoperative tumor progression in patients with intracranial grade II-III solitary fibrous tumor/hemangiopericytoma (SFT/HPC).

MATERIAL AND METHODS

We retrospectively analyzed the preoperative MRI data of 42 patients with intracranial grade II-III SFT/HPC, as confirmed by surgical resection and pathology in our hospital from October 2010 to October 2017, who were followed up for evaluation of recurrence, metastasis, or death. We applied strict inclusion and exclusion criteria and finally included 37 patients. The follow-up time was in the range of 8-120 months (mean = 57.1 months).

RESULTS

Single-factor survival analysis revealed that tumor grade (log-rank, P = 0.024), broad-based tumor attachment to the dura mater (log-rank, P = 0.009), a blurred tumor-brain interface (log-rank, P = 0.008), skull invasion (log-rank, P = 0.002), and the absence of postoperative radiotherapy (log-rank, P = 0.006) predicted postoperative intracranial SFT/HPC progression. Multivariate survival analysis revealed that tumor grade (P = 0.009; hazard ratio [HR] = 11.42; 95% confidence interval [CI] = 1.832-71.150), skull invasion (P = 0.014; HR = 5.72; 95% CI = 1.421-22.984), and the absence of postoperative radiotherapy (P = 0.001; HR = 0.05; 95% CI = 0.008-0.315) were independent predictors of postoperative intracranial SFT/HPC progression.

CONCLUSION

Broad-based tumor attachment to the dura mater, skull invasion, and blurring of the tumor-brain interface can predict postoperative intracranial SFT/HPC progression.

Diagnosis of Invasive Meningioma Based on Brain-Tumor Interface Radiomics Features on Brain MR Images: A Multicenter Study

Background

Meningioma invasion can be preoperatively recognized by radiomics features, which significantly contributes to treatment decision-making. Here, we aimed to evaluate the comparative performance of radiomics signatures derived from varying regions of interests (ROIs) in predicting BI and ascertaining the optimal width of the peritumoral regions needed for accurate analysis.

Methods

Five hundred and five patients from Wuhan Union Hospital (internal cohort) and 214 cases from Taihe Hospital (external validation cohort) pathologically diagnosed as meningioma were included in our study. Feature selection was performed from 1,015 radiomics features respectively obtained from nine different ROIs (brain-tumor interface (BTI)2-5mm; whole tumor; the amalgamation of the two regions) on contrast-enhanced T1-weighted imaging using least-absolute shrinkage and selection operator and random forest. Principal component analysis with varimax rotation was employed for feature reduction. Receiver operator curve was utilized for assessing discrimination of the classifier. Furthermore, clinical index was used to detect the predictive power.

Results

Model obtained from BTI4mm ROI has the maximum AUC in the training set (0.891 (0.85, 0.932)), internal validation set (0.851 (0.743, 0.96)), and external validation set (0.881 (0.833, 0.928)) and displayed statistically significant results between nine radiomics models. The most predictive radiomics features are almost entirely generated from GLCM and GLDM statistics. The addition of PEV to radiomics features (BTI4mm) enhanced model discrimination of invasive meningiomas.

Conclusions

The combined model (radiomics classifier with BTI4mm ROI + PEV) had greater diagnostic performance than other models and its clinical application may positively contribute to the management of meningioma patients.

Retrospective analysis of recurrence patterns and clinical outcome of grade II meningiomas following postoperative radiotherapy

BACKGROUND

Atypical meningiomas exhibit a high tendency for tumor recurrence even after multimodal therapy. Information regarding recurrence patterns after additive radiotherapy is scarce but could improve radiotherapy planning and therapy decision. We conducted an analysis of recurrence patterns with regard to target volumes and dose coverage assessing target volume definition and postulated areas of tumor re-growth origin. Prognostic factors contributing to relapse were evaluated.

METHODS

The clinical outcome of patients who had completed additive, somatostatin receptor (SSTR)-PET/CT-based fractionated intensity-modulated radiotherapy for atypical meningioma between 2007 and 2017 was analyzed. In case of tumor recurrence/progression, treatment planning was evaluated for coverage of the initial target volumes and the recurrent tumor tissue. We proposed a model evaluating the dose distribution in postulated areas of tumor re-growth origin. The median of proliferation marker MIB-1 was assessed as a prognostic factor for local progression and new distant tumor lesions.

RESULTS

Data from 31 patients who had received adjuvant (n = 11) or salvage radiotherapy (n = 20) were evaluated. Prescribed dose ranged from 54.0 to 60.0 Gy. Local control at five years was 67.9%. Analysis of treatment plans of the eight patients experiencing local failure proved sufficient extent of target volumes and coverage of the prescribed dose of at least 50.0 Gy as determined by mean dose, D98, D2, and equivalent uniform dose (EUD) of all initial target volumes, postulated growth-areas, and areas of recurrent tumor tissue. In all cases, local failure occurred in high-dose volumes. Tumors with a MIB-1 expression above the median (8%) showed a higher tendency for re-growth.

CONCLUSIONS

The model showed adequate target volume and relative dose distribution but absolute dose appears lower in recurrent tumors without reaching statistical significance. This might provide a rationale for dose escalation studies. Biological factors such as MIB-1 might aid patients' stratification for dose escalation.

CNS Invasion in Meningioma-How the Intraoperative Assessment Can Improve the Prognostic Evaluation of Tumor Recurrence

Simple Summary

Brain invasion has been integrated into the new WHO classification of meningiomas to improve the prognostic assessment regarding tumor recurrence. However, its role has been questioned. One of the reasons is that for complete histopathological assessment, tissue sampling of the complete brain–tumor interface is necessary, but not always surgically and technically feasible. Therefore, the additional intraoperative assessment of CNS invasion may be of value for a more precise assessment of this tumor characteristic. We therefore studied the prognostic impact of the histopathological and intraoperative assessment of CNS invasion regarding radiographic tumor recurrence and found that both factors by themselves do not reach a prognostic significance. However, if both factors are combined, CNS invasion is an independent negative prognostic factor. Our findings show the prognostic potential of a thorough assessment and underline the need for a standardization and documentation of meningioma tissue sampling for the optimal recurrence risk assessment.

Abstract

The detection of the infiltrative growth of meningiomas into CNS tissue has been integrated into the WHO classification as a stand-alone marker for atypical meningioma. However, its prognostic impact has been questioned. Infiltrative growth can also be detected intraoperatively. The prognostic impact of the intraoperative detection of the central nervous system tissue invasion of meningiomas was analyzed and compared to the histopathological assessment. The clinical data of 1517 cases with follow-up data regarding radiographic recurrence was collected. Histopathology and operative reports were reviewed and invasive growth was seen during resection in 23.7% (n = 345) while histopathology detected it in 4.8% (n = 73). The histopathological and intraoperative assessments were compatible in 63%. The prognostic impact of histopathological and intraoperative assessment was significant in the univariate but not in the multivariate analysis. Both methods of assessment combined reached statistical significance in the multivariate analysis (p = 0.0409). A score including all independent prognostic factors divided the cohort into three prognostic subgroups with a risk of recurrence of 33.8, 64.7 and 88.5%, respectively. The intraoperative detection of the infiltrative growth of primary meningiomas into the central nervous system tissue can complement the histopathological assessment of CNS invasion. The combined assessment is an independent prognostic factor regarding tumor recurrence and allows a risk-adapted tumor stratification.

Extent of Hyperostotic Bone Resection in Convexity Meningioma to Achieve Pathologically Free Margins

OBJECTIVE

Hyperostosis in meningiomas can be present in 4.5% to 44% of cases. Radical resection should include aggressive removal of invaded bone. It is not clear however to what extent bone removal should be carried to achieve pathologically free margins, especially that in many cases, there is a T2 hyperintense signal that extends beyond the hyperostotic bone. In this study we try to investigate the perimeter of tumour cells outside the visible nidus of hyperostotic bone and to what extent they are present outside this nidus. This would serve as an initial step for setting guidelines on dealing with hyperostosis in meningioma surgery.

METHODS

This is a prospective case series that included 14 patients with convexity meningiomas and hyperostosis during the period from March 2017 to August 2018 in two university hospitals. Patients demographics, clinical, imaging characteristics, intraoperative and postoperative data were collected and analysed. In all cases, all visible abnormal bone was excised bearing in mind to also include the hyperintense diploe in magnetic resonance imaging (MRI) T2 weighted images after careful preoperative assessment. To examine bony tumour invasion, five marked bone biopsies were taken from the craniotomy flap for histopathological examinations. These include one from the centre of hyperostotic nidus and the other four from the corners at a 2-cm distance from the margin of the nidus.

RESULTS

Our study included five males (35.7%) and nine females (64.3%) with a mean age of 43.75 years (33-55). Tumor site was parietal in seven cases (50%), fronto-parietal in three cases (21.4%), parieto-occipital in two cases (14.2%), frontal region in one case and bicoronal (midline) in one case. Tumour pathology revealed a World Health Organization (WHO) grade I in seven cases (50%), atypical meningioma (WHO II) in five cases (35.7%) and anaplastic meningioma (WHO III) in two cases (14.2%). In all grade I and II meningiomas, bone biopsies harvested from the nidus revealed infiltration with tumour cells while all other bone biopsies from the four corners (2 cm from nidus) were free. In cases of anaplastic meningiomas, all five biopsies were positive for tumour cells.

CONCLUSION

Removal of the gross epicentre of hyperostotic bone with the surrounding 2 cm is adequate to ensure radical excision and free bone margins in grade I and II meningiomas. Hyperintense signal change in MRI T2 weighted images, even beyond visible hypersototic areas, doesn't necessarily represent tumour invasion.

Radiomic features of magnetic resonance images as novel preoperative predictive factors of bone invasion in meningiomas

PURPOSE

Bone invasion in meningiomas is a prognostic determinant, and a priori knowledge may alter surgical techniques. Here, we aim to predict bone invasion in meningiomas using radiomic signatures based on preoperative, contrast-enhanced T1-weighted (T1C) and T2-weighted (T2) magnetic resonance imaging (MRI).

METHODS

In this retrospective study, 490 patients diagnosed with meningiomas, including WHO grade I (448cases), grade II (38cases), and grade III (4cases), were enrolled and 213 out of 490 cases (43.5 %) had bone invasion. The patients were randomly divided into training (n = 343) and test (n = 147) datasets at a 7:3 ratio. For each patient, 1227 radiomic features were extracted from T1C and T2, respectively. Spearman's correlation and least absolute shrinkage and selection operator (LASSO) regression analyses were performed to select the most informative features. Subsequently, a 5-fold cross-validation was used to compare the performance of different classification algorithms, and logistic regression was chosen to predict the risk of bone invasion.

RESULTS

Eight radiomic features were selected from T1C and T2 respectively, and three models were built using radiomic features. The radiomic models derived from T1C alone or a combination of T1C and T2 had the best performance in predicting risk of bone invasion, with areas under the curve in the training dataset of 0.714 [95 % CI, 0.660-0.768] and 0.722 [95 % CI, 0.668-0.776] and in the test datasets of 0.715 [95 % CI, 0.632-0.798] and 0.713 [95 % CI, 0.628-0.798], respectively.

CONCLUSIONS

The radiomic model may aid clinicians with preoperative prediction of bone invasion by meningiomas, which can help in predicting prognosis and devising surgical strategies.

A radiomics model for preoperative prediction of brain invasion in meningioma non-invasively based on MRI: A multicentre study

Background

Prediction of brain invasion pre-operatively rather than postoperatively would contribute to the selection of surgical techniques, predicting meningioma grading and prognosis. Here, we aimed to predict the risk of brain invasion in meningioma pre-operatively using a nomogram by incorporating radiomic and clinical features.

Methods

In this case-control study, 1728 patients from Beijing Tiantan Hospital (training cohort: n = 1070) and Lanzhou University Second Hospital (external validation cohort: n = 658) were diagnosed with meningiomas by histopathology. Radiomic features were extracted from the T1-weighted post-contrast and T2-weighted magnetic resonance imaging. The least absolute shrinkage and selection operator was used to select the most informative features of different modalities. The support vector machine algorithm was used to predict the risk of brain invasion. Furthermore, a nomogram was constructed by incorporating radiomics signature and clinical risk factors, and decision curve analysis was used to validate the clinical usefulness of the nomogram.

Findings

Sixteen features were significantly correlated with brain invasion. The clinicoradiomic model derived from the fusing MRI sequences and sex resulted in the best discrimination ability for risk prediction of brain invasion, with areas under the curves (AUCs) of 0•857 (95% CI, 0•831–0•887) and 0•819 (95% CI, 0•775–0•863) and sensitivities of 72•8% and 90•1% in the training and validation cohorts, respectively.

Interpretation

Our clinicoradiomic model showed good performance and high sensitivity for risk prediction of brain invasion in meningioma, and can be applied in patients with meningiomas.

Funding

This work was supported by the 10.13039/501100001809National Natural Science Foundation of China (81772006, 81922040); the 10.13039/501100004739Youth Innovation Promotion Association CAS (grant numbers 2019136); special fund project for doctoral training program of 10.13039/100012899Lanzhou University Second Hospital (grant numbers YJS-BD-33).

Novel histopathological classification of meningiomas based on dural invasion

AIMS

Histological invasion into the adjacent brain parenchyma is frequently investigated in meningioma because it is an important morphological criterion for grade II meningioma according to the 2016 WHO classification. However, few studies have focused on dural invasion of meningiomas. Herein, we propose a novel histopathological classification based on dural invasion of meningiomas.

METHODS

Forty-nine cases with WHO grade I meningiomas who underwent Simpson grade I removal were collected. After the meningeal layer (ML) and periosteal layer (PL) of dura mater were visualised by Masson's trichrome stain, we evaluated the depth (to the ML and PL) and the patterns (1, expanding; 2, infiltrating) of dural invasion of meningiomas using serial paraffin sections. Invasion-associated markers, including Ki-67, matrix metalloproteinase (MMP)-1, MMP-9 and MMP-13, aquaporin 1 and Na-K-2Cl cotransporter, were quantitatively analysed by immunohistochemistry.

RESULTS

Thirty-five cases (71.4%) showed the dural invasion. In 27 of these 35 cases (77.1%), dural invasion was localised in ML. Type 1 (expanding type) and type 2 (infiltrating type) invasions were observed in 23 and 12 cases, respectively. The recurrence rate in cases with type 2 invasion was significantly higher than that in cases with type 1 invasion. The percentage of MMP-1-positive tumour cells was also significantly higher in cases with dural invasion than those without, suggesting involvement of MMP-1 in dural invasion.

CONCLUSIONS

We quantitatively evaluated the depth and patterns of dural invasion in meningiomas. The patterns of dural invasion were associated with meningioma recurrence.