Meningioma Consistency Research Articles

Predicting Consistency of Meningioma by Magnetic Resonance Imaging.

Objective Meningioma consistency is important because it affects the difficulty of surgery. To predict preoperative consistency, several methods have been proposed; however, they lack objectivity and reproducibility. We propose a new method for prediction based on tumor to cerebellar peduncle T2-weighted imaging intensity (TCTI) ratios. Design The magnetic resonance (MR) images of 20 consecutive patients were evaluated preoperatively. An intraoperative consistency scale was applied to these lesions prospectively by the operating surgeon based on Cavitron Ultrasonic Surgical Aspirator (Valleylab, Boulder, Colorado, United States) intensity. Tumors were classified as A, very soft; B, soft/intermediate; or C, fibrous. Using T2-weighted MR sequence, the TCTI ratio was calculated. Tumor consistency grades and TCTI ratios were then correlated. Results Of the 20 tumors evaluated prospectively, 7 were classified as very soft, 9 as soft/intermediate, and 4 as fibrous. TCTI ratios for fibrous tumors were all ≤ 1; very soft tumors were ≥ 1.8, except for one outlier of 1.66; and soft/intermediate tumors were > 1 to < 1.8. Conclusion We propose a method using quantifiable region-of-interest TCTIs as a uniform and reproducible way to predict tumor consistency. The intraoperative consistency was graded in an objective and clinically significant way and could lead to more efficient tumor resection.

Diffusion tensor magnetic resonance imaging for predicting the consistency of intracranial meningiomas.

The ability of preoperative MRI-sequences to predict the consistency of intracranial meningiomas has not yet been clearly defined. We aim to demonstrate that diffusion tensor imaging (DTI) improves the prediction of intracranial meningiomas consistency. We prospectively studied 110 meningioma patients operated on in a single center from March 1st to the 25th of May 2012. Demographic data, location and size of the tumor, peritumoral edema, T1WI, T2WI, proton density weighted (PDWI), fluid-attenuated inversion recover (FLAIR) sequences, and arterial spin labeling (ASL) perfusion were studied and compared with the gray matter signal to predict meningioma consistency. Diffusion tensor imaging (DTI) with fractional anisotropy (FA) and mean diffusivity (MD) maps were included in the preoperative MRI. Meningioma consistency was evaluated by the operating surgeon who was unaware of the neuroradiological findings. In univariate analysis, meningioma size (diameter > 2cm) and supratentorial or sphenoidal wing location were more frequently associatedwith hard-consistency meningiomas (p < 0.05). In addition, isointense signal on MD maps (p = 0.009), hyperintense signal on FA maps, and FA value > 0.3 (p = 0.00001) were associated with hard-consistency tumors. Age and sex, T1WI, T2WI, PDWI, FLAIR, or ASL perfusion sequences and peritumoral edema were not significantly associated with meningioma consistency. In logistic regression analysis, the most accurate model (AUC: 0.9459) for predicting a hard-consistency meningioma shows that an isointense signal in MD-maps, a hyperintense signal in FA-maps, and an FA value of more than 0.3 have a significant predictive value. FA value and MD and FA maps are useful for prediction of meningioma consistency and, therefore, may be considered in the preoperative routine MRI examination of all patients with intracranial meningiomas.

Usefulness of the apparent diffusion coefficient (ADC) for predicting the consistency of intracranial meningiomas

Meningioma consistency is an important factor for surgical treatment. Tumor cellularity and fibrous tissue contribute to the consistency of tumors, and it is proposed that the minimum apparent diffusion coefficient (ADC) value is significantly correlated with meningioma consistency. Twenty-seven consecutive patients with 28 meningiomas were retrospectively enrolled. Minimum ADC values in meningiomas with a hard consistency were significantly lower than those with a soft consistency. The minimum ADC value might have clinical use as a predictor of meningioma consistency.

A proposed grading system for standardizing tumor consistency of intracranial meningiomas

Tumor consistency plays an important and underrecognized role in the surgeon's ability to resect meningiomas, especially with evolving trends toward minimally invasive and keyhole surgical approaches. Aside from descriptors such as "hard" or "soft," no objective criteria exist for grading, studying, and conveying the consistency of meningiomas. The authors designed a practical 5-point scale for intraoperative grading of meningiomas based on the surgeon's ability to internally debulk the tumor and on the subsequent resistance to folding of the tumor capsule. Tumor consistency grades and features are as follows: 1) extremely soft tumor, internal debulking with suction only; 2) soft tumor, internal debulking mostly with suction, and remaining fibrous strands resected with easily folded capsule; 3) average consistency, tumor cannot be freely suctioned and requires mechanical debulking, and the capsule then folds with relative ease; 4) firm tumor, high degree of mechanical debulking required, and capsule remains difficult to fold; and 5) extremely firm, calcified tumor, approaches density of bone, and capsule does not fold. Additional grading categories included tumor heterogeneity (with minimum and maximum consistency scores) and a 3-point vascularity score. This grading system was prospectively assessed in 50 consecutive patients undergoing craniotomy for meningioma resection by 2 surgeons in an independent fashion. Grading scores were subjected to a linear weighted kappa analysis for interuser reliability. Fifty patients (100 scores) were included in the analysis. The mean maximal tumor diameter was 4.3 cm. The distribution of overall tumor consistency scores was as follows: Grade 1, 4%; Grade 2, 9%; Grade 3, 43%; Grade 4, 44%; and Grade 5, 0%. Regions of Grade 5 consistency were reported only focally in 14% of heterogeneous tumors. Tumors were designated as homogeneous in 68% and heterogeneous in 32% of grades. The kappa analysis score for overall tumor consistency grade was 0.87 (SE 0.06, 95% CI 0.76-0.99), with 90% user agreement. Kappa analysis scores for minimum and maximum grades of tumor regions were 0.69 (agreement 72%) and 0.75 (agreement 78%), respectively. The kappa analysis score for tumor vascularity grading was 0.56 (agreement 76%). Overall consistency did not correlate with patient age, tumor location, or tumor size. A higher tumor vascularity grade was associated with a larger tumor diameter (p = 0.045) and with skull base location (p = 0.02). The proposed grading system provides a reliable, practical, and objective assessment of meningioma consistency and facilitates communication among providers. This system also accounts for heterogeneity in tumor consistency. With the proposed scale, meningioma consistency can be standardized as groundwork for future studies relating to surgical outcomes, predictability of consistency and vascularity using neuroimaging techniques, and effectiveness of various surgical instruments.

Predictors of meningioma consistency: A study in 243 consecutive cases

Meningioma is a common neoplasm primarily arising in the central nervous system. Its consistency is considered to be one of the critical prognostic factors for determining surgical resectability. The present study endeavored to investigate predictive factors associated with the tumor consistency. Two hundred and forty-three consecutive participants who underwent resective surgery of meningioma were examined. The authors designed an objective grading system for meningioma consistency and utilized it for assessing consistency among all cases. We focused on the relationship between preoperative tumor characteristics on neuroimaging studies and the consistency. The tumor attributes on T2-weighted image (T2WI) and fluid attenuated inversion recovery (FLAIR) image were significantly correlated with the tumor consistency (p = 0.004 and 0.045, respectively). The hypointense tumors on both MRI sequences tended to be hard, whereas the tumors showing hypersignal intensity were associated with soft consistency. There was no correlation between the consistency and age, gender, duration of neurologic symptoms, tumor location, size, calcification, cystic portion, en plague appearance, tumor-brain contact interface expressed by cerebrospinal fluid (CSF) cleft, perilesional vasogenic edema, bony status, features on T1-weighted image (T1WI) and pattern of contrast enhancement. In multiple logistic regression analysis, the tumor characteristics on T2WI and FLAIR image were independent factors significantly correlated with the tumor consistency (p = 0.005 and 0.041, respectively). The tumor consistency was also correlated with operative radicalness as evaluated by the Simpson criteria. Signal intensity on T2WI and FLAIR image can be used for insinuating meningioma consistency. Presurgical prediction of the consistency is highly valuable in operative planning, particularly in arduous cases.

Use of preoperative magnetic resonance imaging T1 and T2 sequences to determine intraoperative meningioma consistency

Background:Meningioma firmness is a critical factor that influences ease of resection and risk, notably when operating on tumors intimate with neurovascular structures such as the mesial sphenoid wing. This study develops a predictive tool using preoperative magnetic resonance imaging (MRI) characteristics to determine meningioma consistency.Methods:101 patients with intracranial meningioma (50 soft/51 firm) were included. MRI characteristics of 38 tumors (19 soft/19 firm) were retrospectively reviewed to identify preoperative imaging features that were then correlated with intraoperative description of the tumor as either “soft and/or suckable” or “firm and/or fibrous”. Criteria were developed to predict consistency and then blindly applied to the remaining 63 meningiomas (31 soft/32 firm).Results:The overall sensitivities for detecting soft and firm consistency were 90% and 56%, respectively (95% CI = 73–97% and 38–73%; P < 0.001). Compared to gray matter, meningiomas that were T2 hypointense were almost always firm. Soft meningiomas were hyperintense on T2 and hypointense on T1. Soft meningiomas were slightly larger and less likely to be associated with edema. There was a slight preponderance of firm meningiomas in the infratentorial compartment. Grade of meningioma was not predictive. Contrast enhancement, diffusion restriction, changes in overlying bone, intratumoral cysts, and angiographic features were not predictable.Conclusions:This tool using T1 and T2 series predicts meningioma consistency. Such knowledge should assist the surgeon in preoperative planning and counseling.

1H-MRS of intracranial meningiomas: What it can add to known clinical and MRI predictors of the histopathological and biological characteristics of the tumor?

Objective The main goal of the present study was evaluation of proton magnetic resonance spectroscopy ( 1H-MRS) in diagnosis of histopathologically aggressive intracranial meningiomas. Methods Single-voxel 1H-MRS of 100 intracranial meningiomas was performed before their surgical resection. Investigated metabolites included mobile lipids, lactate, alanine, N-acetylaspartate (NAA), and choline-containing compounds (Cho). According to criteria of World Health Organization (WHO) 82 meningiomas were assigned histopathological grade I, 11 grade II, and 7 grade III. The MIB-1 index varied from 0% to 27.3% (median, 1.6%). In 43 cases tight adhesion of the tumor to the pia mater or brain tissue was macroscopically identified at surgery. The consistency of 49 meningiomas was characterized as soft, 26 as hard, and 25 as mixed. Results No one metabolic parameter had statistically significant association with histopathological grade and subtype, invasive growth, and consistency of meningioma. Univariate statistical analysis revealed greater 1H-MRS-detected Cho content ( P = 0.0444) and lower normalized NAA/Cho ratio ( P = 0.0203) in tumors with MIB-1 index 5% and more. However, both parameters lost their statistical significance during evaluation in the multivariate model along with other clinical and radiological variables. It was revealed that non-benign histopathology of meningioma (WHO grade II/III) is mainly predicted by irregular shape ( P = 0.0076) and large size ( P = 0.0316), increased proliferative activity by irregular shape ( P = 0.0056), and macroscopically invasive growth by prominent peritumoral edema ( P = 0.0021). Conclusion While 1H-MRS may be potentially used for the identification of meningiomas with high proliferative activity, it, seemingly, could not add substantial diagnostic information to other radiological predictors of malignancy in these tumors.

Prediction of meningioma consistency using fractional anisotropy value measured by magnetic resonance imaging

Preoperative planning for meningiomas requires information about tumor consistency as well as location and size. In the present study the authors aimed to determine whether the fractional anisotropy (FA) value calculated on the basis of preoperative magnetic resonance (MR) diffusion tensor (DT) imaging could predict meningioma consistency. In 29 patients with intracranial meningiomas, MR DT imaging was performed preoperatively, and the FA values of the tumors were calculated. Tumor consistency was intraoperatively determined as hard or soft, and the histological diagnosis of the tumor was established. Of the 29 tumors, 11 were classified as hard and 18 as soft. The FA values of fibroblastic meningiomas were significantly higher than those of meningothelial meningiomas (p = 0.002). The FA values of hard tumors were significantly higher than those of soft tumors (p = 0.0003). Logistic regression analysis demonstrated that the FA value was a significant independent predictor of tumor consistency (p = 0.007). The FA value calculated from preoperative MR DT imaging predicts meningioma consistency.

Prediction of meningioma consistency using fractional anisotropy value measured by magnetic resonance imaging

Object Preoperative planning for meningiomas requires information about tumor consistency as well as location and size. In the present study the authors aimed to determine whether the fractional anisotropy (FA) value calculated on the basis of preoperative magnetic resonance (MR) diffusion tensor (DT) imaging could predict meningioma consistency. Methods In 29 patients with intracranial meningiomas, MR DT imaging was performed preoperatively, and the FA values of the tumors were calculated. Tumor consistency was intraoperatively determined as hard or soft, and the histological diagnosis of the tumor was established. Results Of the 29 tumors, 11 were classified as hard and 18 as soft. The FA values of fibroblastic meningiomas were significantly higher than those of meningothelial meningiomas (p = 0.002). The FA values of hard tumors were significantly higher than those of soft tumors (p = 0.0003). Logistic regression analysis demonstrated that the FA value was a significant independent predictor of tumor consistency (p = 0.007). Conclusions The FA value calculated from preoperative MR DT imaging predicts meningioma consistency.

Differentiation of fibroblastic meningiomas from other benign subtypes using diffusion tensor imaging

To differentiate fibroblastic meningiomas, usually considered to be of a hard consistency, from other benign subtypes using diffusion tensor imaging (DTI). From DTI data sets of 30 patients with benign meningiomas, we calculated diffusion tensors and mean diffusivity (MD) and fractional anisotropy (FA) maps as well as barycentric maps representing the geometrical shape of the tensors. The findings were compared to postoperative histology. The study was approved by the local ethics committee, and informed consent was given by the patients. According to one-way analysis of variance (ANOVA), FA was the best parameter to differentiate between the subtypes (F=32.2; p<0.0001). Regarding tensor shape, endothelial meningiomas were represented by spherical tensors (80%) corresponding to isotropic diffusion, whereas the fibroblastic meningiomas showed a high percentage (43%) of nonspherical tensors, indicating planar or longitudinal diffusion. The difference was highly significant (F=28.4; p<0.0001) and may be due to the fascicular arrangement of long spindle-shaped tumor cells and the high content of intra- and interfascicular fibers as shown in the histology. In addition, a capsule-like rim of the in-plane diffusion surrounded most meningiomas irrespective of their histological type. If these results correlate to the intraoperative findings of meningioma consistency, DTI-based measurement of FA and analysis of the shape of the diffusion tensor is a promising method to differentiate between fibroblastic and other subtypes of benign meningiomas in order to get information about their "hard" or "soft" consistency prior to removal.

Prediction of Consistency of Meningiomas with Preoperative Magnetic Resonance Imaging

Background The consistency of a meningioma is one of the important factors in determining the surgical outcome. If the surgeon is aware of the consistency of a meningioma preoperatively, the surgical plans will be influenced. A few papers have described the correlation between consistency of meningiomas and their magnetic resonance imaging (MRI) findings. However, prediction of consistency with MRI is still difficult. We have tried to predict the consistency of meningiomas with MRI findings more precisely. Methods and Results Fifty patients diagnosed as having intracranial meningiomas were studied with 1.5 Tesla MRI. We compared the MRI findings with tumor consistency. The intensities of the tumors were categorized into three grades (low, iso, and high) compared to that of the gray matter. T 1-weighted images had no specifics, but T 2-weighted images and proton density images were useful for the prediction of tumor consistency. Hyperintensity on protein density (PD) and T 2-weighted images was a sign of a soft tumor. Conclusion We presume that T 2 and PD are useful for predicting consistency of meningiomas, and their water content is one of the main factors in their consistency. Histology may be one of the factors helpful in defining the consistency of a tumor. In this series, we found no relationship between histology and MRI findings, nor between histology and consistency. If the meningioma is believed to be hard, preoperative endovascular embolization is beneficial, which will induce necrosis of the meningioma and make it soft enough to be removed more easily and safely.

Meningiomas: correlation between MRI characteristics and operative findings including consistency.

The findings on magnetic resonance imaging (MRI) in 73 surgically verified intracranial meningiomas were correlated with their histology and consistency during resection. T 1-weighted imaging was least useful since most of the tumours were iso-intense, similar to cortical grey matter regardless of histology or tumour consistency. The signal intensity on T2-weighted images was found to best correlate with both the histology and consistency of the meningioma. Generally, the low intensity portion of the tumour on T2-weighted images indicated a more fibrous and harder character, while the higher intensity portions indicated a more soft character. Most of the fibroblastic meningiomas showed the features of a hard tumour while angioblastic tumours showed the features of soft tumours. Tumours predicted to be harder on MR imaging generally took longer to resect than softer ones, and this relationship was shown best for the larger tumours. Using linear regression analysis, it appears that operative time for soft tumours is more affected by factors other than tumour consistency. Blood loss during surgery was also unrelated to the consistency of the tumour. These results suggest that the histology and consistency of meningiomas may be predictable from findings on T2-weighted imaging, and this may also predict the difficulty and time required for resection.

Comparison of consistency of meningiomas and CT appearances.

Computed tomograms of meningiomas in which the consistency of the tumour had been specifically noted at surgery were reviewed. Those showing diffuse calcification or evidence of marked cystic or necrotic changes were excluded, leaving 77 tumours of which 46 were hard and 31 soft. Ninety per cent of the hard tumours were of increased attenuation; the other 10% were isodense with brain. Forty-nine per cent of the soft meningiomas were of high attenuation, but 35% were isodense and 16% were of lower than brain attenuation. There was a greater incidence of marked intracerebral oedema around the hard tumours. All hypodense tumours enhanced to greater than brain attenuation; mean enhancement was relatively less in the tumours of high plain scan attenuation regardless of consistency and there was no relationship between degree of enhancement and either the consistency or with the amount of vascularity as estimated by the surgeon or histologist.