Preoperative MRI Technology In Prediction Of Meningioma Biological Behavior And Differential Diagnosis

First Part:Preoperative MRI imaging scoring system to predict meningioma biological behavior and prognosisBackground:A subgroup of meningioma demonstrates clinical aggressive behavior. We set out to determine if the radiological parameters can predict histopathological aggressive meningioma, and propose a classification to predict survival and aggressive meningioma behavior.Meningiomas account for 20-32% of all the primary intracranial tumors. According tothe WHO 2007 classification system, the meningiomas are classified into 3 histological gradesand 15 subtypes. This histopathological classification is generally used to predict the clinicalcourse of meningioma. Most meningiomas are benign, well-circumscribed, slow growing tumors corresponding to WHO grade I and usually follows uneventful clinical course. Somemeningiomas, including WHO grade II (atypical) and grade III (anaplastic) tumors, are clinically and histologically aggressive. Grade II meningioma account for 4.7% to 7.2% and Grade III tumors comprises 1.0 to 2.8% of all the meningiomas; however much larger proportion,20% of the meningioma, demonstrates aggressive histological and/or clinical behavior.This suggests that a borderline group of grade I meningioma also exists which behaves aggressivelyand might have recurrent or progressive disease. Therefore, a histopathological gradingalone might not accurately correlate with the patient outcome. It is important to distinguish WHO-grade I meningiomas with aggressive behavior from their non-aggressivecounterparts. Several immunohistochemical parameters including Ki-67/MIB-1, MMP-9, PR,ER are used as an adjunct to the histopathological grading to predict the meningioma prognosis. Similarly, several radiological features are used in conjunction with histopathological grading to identify benign versus aggressive meningioma features. The loss of tumor-brain interface, presence of PTE, irregular tumor shape, heterogeneous enhancement on MRI, decreased apparent diffusion coefficient (ADC) in diffusion weighted imaging (DWI)and fluorodeoxyglucose F PET predicts the aggressive histological and clinical behavior of meningioma.Despite of the numerous studies determining the clinical,radiological and histological parameters associated with aggressive meningioma behavior;the accurate prediction of meningioma behavior is challenging. We set out to determine if theradiological parameters can predict histopathological aggressive meningioma, and based onthat propose a classification to predict survival and aggressive meningioma behavior.Methods:A retrospective review of medical records was conducted for patients who underwent surgical resection of their convexity meningioma. WHO-2007 grading was used for histopathological diagnosis. Preoperative radiologic parameters were analyzed, each parameter was scored 0 or 1. Signal intensity on diffusion weighted MRI (DWI) (hyperintensity=1), heterogeneity on T1-weighted gadolinium enhanced MRI (heterogeneity=1), disruption of arachnoid at brain-tumor interface=1and peritumoral edema (PTE) on T2-weighted MRI (presence of PTE=1) and tumor shape (irregular shape=1). Multivariate logistic regression analyses were conducted to find association of radiological parameters to histopathological grading. Cox regression and Kaplan-Meier models were used to find the association of scoring system to overall survival and progression free survival (PFS). Reliability of the classification was tested using Kappa co-efficient analysis.Between 2003 and 2006,246 patients with intracranial convexity meningiomas underwent surgery as the primary treatment at our institution. Patients underwent surgical resection without preoperative embolization. To nullify the effect of location (skull base versus convexity),extent of resectionand preoperative functional status of the patients, we only included patients with convexity meningioma, Karnofsky performance score (KPS) of 60 and in whom Simpson grade Ⅰ resection was achieved. Preoperative MRI, operative notes and surgical specimen were re-evaluated. The histopathology slides were re-evaluated and the histopathological diagnosis was classified based on the 2007 WHO classification system for meningioma.MRI examinations were performed using a 1.5-T machine for patients operated on before 2005and a 3-T machine for patients operated on after 2005(General Electric Signa Excite HD). The MRI protocol included the following sequences:T1-weighted images (TR/TE,436/21 msec),T2-weighted images, diffusion-weighted imaging and FLAIR images. Slice thickness was 5 mm, and the field of view varied between 18 and 30 cm. We also obtained axial, coronal, and sagittal T1-weighted images after administration of 0.1 mmol/kg of body weight of Gd-DTPA.According to the WHO 2007 classification system, increased cellularity, necrosis and braininvasion are the histological features associated with non-Grade Ⅰ tumor[3].Radiologicalappearance of these histological features has been described as hyperintensity on diffusionweightedimaging (DWI), heterogeneous enhancement on T1-weighted gadolinium (Gd) enhanced MRI and cortical penetration or disappearance of arachnoid layer on T2-weightedMRI. Few studies have demonstrated that peritumoral edema (PTE) and tumorshape are associated with aggressive behavior or higher WHO grades. We evaluatedthe association of this five radiological parameters to the aggressive meningioma behavior;(1) signal intensity on DWI, (2) heterogeneity on T1-weighted Gd enhanced MRI, (3) Arachnoidlayer on T2-weighted MRI, (4) PTE on T2-weighted MRI, (5) Tumor shape.Radiological features were scored as:DWI signal intensity (hyperintense to grey matter=1,others=0); T1-weighted Gd-enhanced MRI (heterogeneity=1, homogeneity = 0); arachnoidlayer on T2-weighted MRI (disappeared or disintegrated=1, intact=0); PTE on T2-weightedMRI (tumor with edema=1, tumor without edema=0) and tumor shape (tumor with irregular shape, including mushroom shape or lobulated=1, tumor with regular shape, including globular shape=0). The lowest score was 0 and the highest was 5. Preoperative MRI was evaluated and total score was calculated for each patient. Based on their preoperative MRI scoring, all patients were classified into 3 groups:group one=0-1, group two=2-3 and group three 4-5. The survival time, progression free survival and overall survival (OS)rates of each group were analyzed. The survival outcome was evaluated as favorable if the patients were ali ve at the last follow-up and unfavorable if the status of patient was dead.Results:Hyperintensity on DWI, disruption of arachnoid at brain-tumor interface, PTE, heterogenicitiy on T1-weighted enhanced MRI and irregular tumor shape were independent predictors of non-grade I meningioma. Mean follow-up period was 94.6 months. Median survival and PFS in groups-I, II and III was 114.1±1.2 and 115.7± 0.8,88± 3.3 and 58.5±3.9,43.2± 5.1 and 18.2±1.7 months respectively. In cox regression analysis model, age, WHO non-grade-I meningioma, radiological classification groups II and III were independent predictors of unfavorable survival outcomes.Conclusions:Preoperative imaging gradehas a certain degree of consistency with pathological grade, and can predict the prognosis in patients with convexity meningioma. Preoperative radiological classification can be used as a supplement to the histopathological grading. Pathological diagnosis of WHOI level of meningioma, may actually be for grade II or higher level, the need for identification.Group-Ⅰ meningiomas demonstrate benign radiological, histopathological and clinical features; group-Ⅲ demonstrates aggressive features. Group-II meningiomas demonstrate intermediate features; the need for more aggressive follow-up and/or treatment should be further investigated.Second Part:Preoperative radiologic characters to predict hemangiopericytoma from angiomatous meningiomaBackground:Hemangiopericytoma is clinically difficult to be differentiated from angiomatous meningioma. We set out to determine if the preoperative MRI parameters can predict HPC from angiomatous meningioma.Introduction Hemangiopericytoma (HPC) is a rare tumor of vascular origin that was first described by Stout and Murray. In the central nervous system (CNS), HPC closely resembles angiomatous meningioma radiologically despite being a distinct histopathologicalentity. HPC deserves special attention because the intraoperative blood loss during its resection is large, and it is known to recurand metastasize. Angiomatous meningioma accounts for 2.1%of all meningiomas. It has features of a typical benign meningioma with many small or large vascular channels which may predominate over its meningothelial elements. Thus, preoperative differentiation of HPC and meningioma may be advantageous, as this information could be of help in surgical and treatment plan-ning. For this reason, we set out to determine if the preoperative MRI parameters can predict HPC from angiomatous meningioma.Methods:A retrospective review of medical records was conducted for 1217 angiomatous meningiomas.and 12 HPC patients. WHO-2007 grading was used for histopathological diagnosis. Preoperative radiologic parameters included tumor location, tumor size, tumor shape, T1-weighted signal, T2-weighted signal, T1-weighted Gd-enhanced image, ADC value, Flair signal, peritumoral edema (PTE), dural tail sign (DTS), vessel voids sign, arachnoid layer on T2-weighted MRI, tumor hemorrhage and necrosis were analyzed. Univariate analyses were conducted to examine the association between radiological or clinicaland histopathological features. Binary logistic regression model was used to evaluate if the parameters predict the occurrence of HPC.Patients from January 2005 to December 2014, the imaging data of29 patients in Nanfang Hospital were retrospectively reviewed. Preoperative MRI, operative notes and surgical specimenwere re-evaluated. Previously treated tumors were excluded. Thehistopathology slides were re-evaluated and the histopathological diagnosis was classified based on the 2007 WHO classification system. This retrospective study was approved by Nanfang Hospital Medical Ethics Committee. Patient records/information was anonymized and de-identified prior to analysis. The clinical records of participants in this study were de-identified prior to analysis.MRI examinations were performed using a 3-T machine fo rall patients (General Electric Signa Excite HD). The MRI protocol included the following sequences: Tl-weighted images, T2-weighted images and FLAIR images. DWMR imaging was acquired in the axial plane by using b-values of 1000 s/mm2with section thickness of 5 mm. ADC values were measured automatically using the Func Tool software program (GE Medical Systems). The ADC was determined by manually placing the regions of interest (ROIs) in the respective tumor sites on the ADC maps of b= 1000 by the coauthors who were blind to the tumor grade. All consecutive slices that included the solid portion of the tumors were initially selected. ROIs were purposely placed at the center of tumors to avoid volume-averaging with vessel voids, cys-tic, necrotic, and hemorrhagic regions that might influence the ADC values, and to avoid capsule-lesions. Based on 3-5 ROIs on the ADC maps, the ADC values of each tumor were calculated. Slice thickness was 5 mm, and the field of view varied between 18 and30 cm. We also obtained axial, coronal, and sagittal T1-weighted images after administration of 0.1 mmol/kg of body weight of Gd-DTPA.Preoperative MRI parameters analyzed in this study included:tumor location (skull base or convexity), tumor size (maximum diameter), tumor shape (tumor with irregular shape, including mushroom shape or lobulated, tumor with regular shape,including globular shape), T1-weighted signal (hyper, hypo or iso-intense compared with gray matter), T1-weighted Gd-enhanced image (heterogeneity or homogeneity), ADC value,Flair signal (hyper, hypo or iso-intense compared with gray matter), peritumoral edema (PTE), dural tail sign (DTS), vessel voidssign, arachnoid layer on T2-weighted MRI, tumor hemorrhage and necrosis. Necrotic components were differentiated on contrast enhanced Tl-weighted images as the interior non-enhancing parts of enhanced lesions. Hemorrhagic lesions were differentiated onnon-enhanced T1-weighted MR images as hyperintensity sites andT2-weighted MR images as focal hypointensity sites-Results:12 cases of HPCs and 17 cases of angiomatous meningiomas were confirmed by two pathologists who were blinded to the diagnosis. The mean age of HPC patients was younger than that of meningioma patients, and the mean largest diameter of HPC was not differ-ent from that of meningioma. The gender between angiomatous meningiomas and HPC patients was different. The tumor location and tumor shape was not different between angiomatous meningiomasand HPC patients.There were, respectively,0,6,6 patients with HPC demon-strating hyper-intensity, iso-intensity and hypo-intensity on Tlimage, while the number for patients with meningioma was 0,5,12. There were, respectively,6,6,0 patients with HPC demonstrating hyper-intensity, iso-intensityand hypo-intensity on T2 image, while the number for patients with meningioma was 4,13, 0.There were, respectively, 4,8,0 patients with HPC demonstrating hyper-intensity, iso-intensity and hypo-intensity on FLAIR image,while the number for patients with meningioma was 11,6,0.66.7%of patients with HPC showed heterogeneity on T1-weighted gadolinium enhanced MRI and 23.5% of patients with meningioma showed hetero-geneity on T1-weighted gadolinium enhanced MRI; 50% of patients with HPC had disruption of arachnoid on T2-weighted MRI while the rate was 29.4% in patients with meningioma;50%of patients with HPC had PTE on T2-weighted MRI while the ratewas 47.1% in patients with meningioma; 50% of patients with HPC had irregular shape while the rate was 17.6% in patients with meningioma; 66.7 of patients with HPC had necrosisin MRI while the rate was 23.5% in patients with meningioma; 66.7 of patients with HPC had vessel voids sign in MRI while the rate was 70.6% inpatients with meningioma; 33.3% of patients with HPC had dural tail sign in MRI while the rate was 64.7% in patients with meningioma; 8.3% of patients with HPC had tumor hemorrhage in MRI while no patients with meningioma showed hemorrhage. The mean ADC in angiomatous meningioma was lower than in HPC. The five parameters, included age, gender, ADC value, necrosis and T1 enhancement, which was found significantly different between two types after univariate analyses was further analyzd by binary logistic regression model to evaluate if the parameters predict the occurrence of HPC. ADC value was the sole independent predictor of HPC.Conclusions:ADC value may be used as a simple and useful optional tool in differentiating primary intracranial HPC from angiomatous meningioma. The combination of ADC value with the data acquired from pre and post-contrast MR scans may further help improve the reliability in the differential diagnosis.