Neuro-Oncology Neuro-Oncology 18(6), 863– 872, 2016 doi:10.1093/neuonc/nov285 Advance Access date 22 November 2015

Imaging and extent of surgical resection predict risk of meningioma recurrence better than WHO histopathological grade William L. Hwang, Ariel E. Marciscano, Andrzej Niemierko, Daniel W. Kim, Anat O. Stemmer-Rachamimov, William T. Curry, Fred G. Barker II, Robert L. Martuza, Jay S. Loeffler, Kevin S. Oh, Helen A. Shih, and Mykol Larvie Department of Medicine, Massachusetts General Hospital, Boston, Massachusetts (W.L.H.); Department of Radiation Oncology, Massachusetts General Hospital, Boston, Massachusetts (W.L.H., A.N., D.K., J.S.L., K.S.O., H.A.S.); Department of Radiology, Massachusetts General Hospital, Boston, Massachusetts (W.L.H., M.L.); Department of Radiation Oncology and Molecular Radiation Sciences, Johns Hopkins University, Baltimore, Maryland (A.E.M.); Harvard Business School Leadership Fellows Program, Boston, Massachusetts (D.K.); Department of Pathology, Massachusetts General Hospital, Boston, Massachusetts (A.O.S.-R.); Department of Neurosurgery, Massachusetts General Hospital, Boston, Massachusetts (W.T.C., F.G.B., R.L.M.) Corresponding Authors: Helen A. Shih, MD, Department of Radiation Oncology, Massachusetts General Hospital, 30 Fruit Street, Boston, MA, 02114 ([email protected]); Mykol Larvie, MD, PhD, Department of Radiology, Massachusetts General Hospital, 55 Fruit Street, Boston, MA, 02114 ([email protected]).

Background. Risk stratification of meningiomas by histopathological grade alone does not reliably predict which patients will progress/recur after treatment. We sought to determine whether preoperative imaging and clinical characteristics could predict histopathological grade and/or improve prognostication of progression/recurrence (P/R). Methods. We retrospectively reviewed preoperative MR and CT imaging features of 144 patients divided into low-grade (2007 WHO grade I; n ¼ 118) and high-grade (2007 WHO grades II/III; n ¼ 26) groups that underwent surgery between 2002 and 2013 (median follow-up of 49 months). Results. Multivariate analysis demonstrated that the risk factors most strongly associated with high-grade histopathology were male sex, low apparent diffusion coefficient (ADC), absent calcification, and high peritumoral edema. Remarkably, multivariate Cox proportional hazards analysis demonstrated that, in combination with extent of resection, ADC outperformed WHO histopathological grade for predicting which patients will suffer P/R after initial treatment. Stratification of patients into 3 risk groups based on non-Simpson grade I resection and low ADC as risk factors correlated with the likelihood of P/R (P , .001). The high-risk group (2 risk factors; n ¼ 39) had a 45% cumulative incidence of P/R, whereas the low-risk group (0 risk factors; n ¼ 31) had no P/R events at 5 years after treatment. Independent of histopathological grade, high-risk patients who received adjuvant radiotherapy had a lower 5-year crude rate of P/R than those without (17% vs 59%; P ¼ .04). Conclusions. Patients with non-Simpson grade I resection and low ADC meningiomas are at significantly increased risk of P/R and may benefit from adjuvant radiotherapy and/or additional surgery. Keywords: apparent diffusion coefficient, histopathological grade, meningioma, radiotherapy, Simpson grade.

Meningiomas are the most prevalent primary intracranial tumors in adults, accounting for up to one-third of cases.1 Based on the current 2007 WHO classification system, meningiomas are grouped into 3 histopathological grades.2 WHO grade I (benign) meningiomas typically follow an indolent course, while WHO grade II (atypical) and grade III (anaplastic/malignant) meningiomas are more locally aggressive, have higher rates of progression/ recurrence (P/R), and overall worse prognosis, even with definitive treatment.3 – 6 Adjuvant radiotherapy (RT) improves local control,

disease-free survival, and overall survival in high-grade meningiomas (WHO grades II and III), especially in the setting of subtotal resection.7 – 11 However, the role of adjuvant RT for low-grade meningiomas (WHO grade I) is unclear; therefore, current practice varies greatly among institutions,12 with most favoring surgical resection alone followed by long-term surveillance. Importantly, not all high-grade meningioma patients suffer P/R. Moreover, there is a subset of WHO grade I meningiomas that behaves aggressively, with P/R shortly after initial treatment,13 which suggests

Received 6 August 2015; accepted 20 October 2015 # The Author(s) 2015. Published by Oxford University Press on behalf of the Society for Neuro-Oncology. All rights reserved. For permissions, please e-mail: [email protected].

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Hwang et al.: Imaging and surgery predict meningioma recurrence

that histopathological grading alone is inadequate for optimal risk stratification. Per 2007 guidelines, WHO grade I meningiomas have ,4 mitotic cells per 10 high power fields, and ,3 of the following atypical features: increased cellularity, necrosis, prominent nucleoli, sheeting, and high nuclear-to-cytoplasmic ratio.2 We recently found that WHO grade I meningiomas with 1–2 atypical features and/or non-Simpson14 grade I surgical resections were at higher risk of P/R than those with no atypical features and Simpson grade I resections.15 Developing noninvasive, imaging-based techniques to accurately predict the aggressiveness of meningiomas as a surrogate for or complement to tissue diagnosis would be advantageous to better determine the risk of tumor P/R, inform personalized treatment decisions, and improve patient outcomes. Moreover, the compositional and temporal heterogeneity of tumors is more amenable to comprehensive characterization by imaging compared with histopathological examination, which often examines a limited fraction of the tumor tissue. Conventional MRI and CT serve as the standard imaging assessment tools for meningiomas. Prior investigations have identified aggressive imaging features that may be associated with high-grade meningiomas and increased risk of P/R, including heterogeneous contrast enhancement, peritumoral edema, invasion of brain parenchyma, intratumoral cystic change, and bone invasion, but the statistical power and characteristics identified as significant have varied tremendously from study to study, providing a confusing milieu of data that are difficult to adopt into clinical practice.16 – 20 Conventional MRI alone has limited ability to distinguish among histopathological grades and subtypes of meningiomas.21 On the other hand, diffusion-weighted imaging (DWI) and the related apparent diffusion coefficient (ADC) map yield microstructural information regarding cellular density and tumor matrix that may enhance the diagnostic and prognostic potential of imaging for meningiomas. However, the data thus far have been conflicting, with some studies finding that restricted diffusion is associated with higher Ki-67 and/or meningioma grade20,22 – 26, while other studies demonstrate no significant relationship.27 – 30 Importantly, many of these studies were underpowered and only examined the correlation between DWI/ADC and histopathological grade without investigating clinical outcomes. In this study, we sought to investigate whether a subset of imaging features and clinical characteristics (i) correlates with histopathological grade and/or (ii) predicts P/R of meningiomas after definitive treatment.

Methods Patient Selection We retrospectively reviewed the records of patients with histologically confirmed intracranial meningiomas (WHO grades I, II, and III) who underwent surgical resection at our institution between 2002 and 2013 and had routine preoperative brain MRI performed with DWI and/or head CT (not all patients had both types of imaging performed). We excluded patients with prior cranial radiotherapy, neurofibromatosis type 2 (NF2), only outside hospital preoperative imaging, or ,1 year of clinical and radiological follow-up at our institution. A total of 144

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patients were stratified by WHO 2007 histopathological grade into 2 cohorts: low grade (WHO grade I; n ¼ 118) and high grade (WHO grades II and III; n ¼ 26). In certain instances, the low-grade meningiomas were further substratified into a low-grade with atypia group (n ¼ 58) with 1 –2 atypical histopathological features defined as increased cellularity, sheeting, prominent nucleoli, necrosis, and/or high nucleus-to-cytoplasm ratio and a low-grade without atypia group (n ¼ 60) that lacked any of these atypical features. All of the data employed were obtained for routine clinical care according to current clinical practice at our institution. This study was conducted with institutional review board approval.

Parameters Assessed Multiple patient and baseline tumor factors were evaluated for potential association with histopathological grade and P/R. Age at diagnosis was defined as age at the time of radiologically suspected meningioma that had been subsequently confirmed by histopathology. Each patient’s sex was documented. Karnofsky performance status (KPS) was determined through clinical notes. The date of P/R was defined as the date of radiologic evidence of P/R by MRI and confirmed by clinical review. Simpson grade of surgical resection was determined by review of operative notes, imaging studies, and best clinical judgment in cases where it was not explicitly stated. CT and MR imaging were performed on a variety of GE and Siemens scanners according to standard institutional protocols. Multiplanar reformats along axial, sagittal, and coronal axes were created for review. Isotropic technique and automated voltage/current adjustment technique were routinely employed to obtain clinical quality scans. The majority of MRI scans were acquired using 3T scanners, and the minority were obtained with 1.5T scanners. MRI examinations included T2-weighted, susceptibility-weighted, diffusion-weighted, and pre- and postcontrast T1-weighted imaging. Precontrast T1-weighted images were obtained with a spin echo sequence. Postcontrast T1-weighted images were typically acquired using both a spin echo sequence and a high-resolution isotropic sequence (eg, BRAVO or MPRAGE). Diffusion imaging was performed using a 2D echo planar sequence with 30 gradient orientations, b ¼ 1000 mm2/s, and 5 mm slice thickness spaced at 1 mm intervals. Preoperative MRI and CT studies were analyzed by a neuroradiologist blinded to the clinical data associated with each patient (Fig. 1). Tumor location was grouped as nonskull base (parasagittal/falx, convexity, tentorium) versus skull base (anterior fossa, middle fossa, posterior fossa). Tumor volume was determined by the largest diameters in the anterior-posterior (x), superior-inferior (y), and transverse (z) dimensions using the formula for nonspherical tumor volume ¼ [(p/6)*x*y*z]. All tumor features were treated as binary variables unless otherwise indicated. Conventional MRI sequences were used to characterize T2 hyperintensity relative to gray matter, brain parenchymal invasion, heterogeneity of enhancement (heterogeneities due to calcifications or cystic change were excluded), capsular enhancement, intratumoral cystic change, intratumoral necrosis, peritumoral edema in 2 categories of extent and degree (based on comparing volume of edema to volume of tumor), bone invasion, and dural tails. Noncontrast CT was

Hwang et al.: Imaging and surgery predict meningioma recurrence

Fig. 1. Examples of imaging analysis. (A– E) Case 1: low-grade meningioma with nonskull base location demonstrating (A) high apparent diffusion coefficient (ADC) ¼ 1.1×1023 mm2/s (ADC map); (B) calcification (CT); (C) low edema (T2-fluid-attenuated inversion recovery); (D) homogeneous enhancement (presurgical T1-postcontrast); and (E) Simpson grade II resection (postsurgical T1-postcontrast). (F – J) Case 2: high-grade meningioma with nonskull base location demonstrating (F) low ADC ¼ 0.79 ×1023 mm2 /s; (G) no calcification; (H) high edema; (I) heterogeneous enhancement; and (J) Simpson grade I resection.

used to assess tumor calcification and reactive hyperostosis. Representative regions of interest (ROIs; 20 – 500 mm2) were drawn within each tumor on apparent diffusion coefficient (ADC) maps derived from DWI sequences. Mean ADC values were measured per previously established protocols 24,25,28 (Fig. 1). The variation in ROI size was tailored to tumors of different shapes and sizes. ROIs were selected to avoid tumor borders and calcified, cystic, or necrotic regions.

Statistical Analysis Univariate logistic regression analysis was used to identify the variables that were significantly associated with histopathological grade; these variables were then used to develop several multivariate models, which were compared on the basis of the receiver operating characteristic (ROC) curve, Akaike information criterion (AIC), and Bayesian information criterion (BIC). Time to progression/recurrence was analyzed using univariate and multivariate Cox proportional hazards methods. The predictive power of several multivariate risk stratification models was assessed using Harrell’s C concordance statistic, AIC, and BIC. The log-rank test was used to compare KaplanMeier curves for various risk strata. Given the retrospective nature of this study and the lack of a uniform protocol for preoperative imaging, 64 of 144 patients did not have a complete set of preoperative imaging parameters available. However, statistical evaluation showed that the missing data were distributed randomly, enabling the application of a validated multiple imputation approach to incorporate subjects with

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missing data into the analyses described above.31 For defining the 3-tier risk stratification scheme discussed below, Simpson grade of resection had no missing values, while ADC was missing for 21 of 144 patients (predictive mean matching was used such that ADC was regressed on histology, age at diagnosis, and P/R outcome). All P values were 2-tailed. A value of P , .05 was considered statistically significant.

Results Analysis of Histopathological Grade All patients had surgical resection, with 46% of the low-grade group achieving Simpson grade I resection compared with 35% of the high-grade group. Adjuvant radiotherapy (upfront as opposed to salvage) was administered to 6% of low-grade patients and 65% of high-grade patients. The median follow-up time was 49 months for the low-grade cohort versus 51 months for the high-grade cohort. On univariate logistic regression analysis, histopathological grade was significantly associated with sex, KPS, tumor location, tumor volume, ADC, calcification, and peritumoral edema (Table 1). Male sex was associated with high-grade histopathology with an odds ratio (OR) of 5.1 (95% CI, 2.1–12.4; P , .001). A slightly higher KPS score was seen in patients with highgrade meningiomas (OR, 1.06; 95% CI, 1.01–1.11; P ¼ .03). Larger tumors were associated with high-grade histopathology (OR, 1.01; 95% CI, 1.00 – 1.03; P ¼ .01). Tumors located in the skull base were less frequently high grade (OR, 0.31; 95% CI,

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Univariate Analysis

Sex (fraction male) KPS (0–100) Age at diagnosis (y) Volume (cm3) Location (fraction skull base) ADC (x1023 mm2/s) log(ADC) ADC binary (dichotomized at median of 0.88 ×1023 mm2/s; fraction high ADC) Calcification High peritumoral edema T2 hyperintensity (relative to gray matter) Parenchymal invasion Heterogeneous tumor enhancement Capsular enhancement Cystic change Necrosis Reactive hyperostosis Bone invasion Dural tails

Multivariate Analysis

LG (frac feat or mean+SEM)

HG (frac feat or mean+SEM)

Odds ratio (95% CI) for HG

P value

Logistic regression coefficient

Odds ratio (95% CI) for HG

P value

0.21 82+1 55+1 27+3 0.49 0.99+0.03 20.02+0.01 0.57

0.58 87+3 58+3 49+8 0.23 0.78+0.03 20.11+0.01 0.14

5.07 (2.07 – 12.4) 1.06 (1.01 – 1.11) 1.02 (0.985 –1.05) 1.01 (1.003 –1.026) 0.310 (0.116 –0.828)

,.001a .028a .278 .012a .019a

+1.2

3.46 (1.15 – 10.4)

.028a

0.009 (0.0004– 0.221) 0.170 (0.050 –0.579)

.004a .005a

26.7

0.001 (2×1025 –0.069)

.001a

0.47 0.31 0.64 0.04 0.31 0.09 0.10 0.05 0.37 0.16 0.66

0.05 0.54 0.69 0.04 0.50 0.12 0.12 0.12 0.32 0.14 0.73

0.157 (0.031 –0.803) 2.56 (1.07 – 6.10) 1.45 (0.729 –2.90) 1.35 (0.134 –13.5) 2.03 (0.849 –4.83) 1.20 (0.305 –4.71) 1.13 (0.288 –4.47) 2.09 (0.482 –9.11) 0.892 (0.345 –2.30) 0.885 (0.240 –3.27) 1.44 (0.553 –3.73)

.026a .035a .288 .800 .112 .795 .857 .324 .813 .855 .457

22.5 +1.6

0.083 (0.01 –0.547) 4.75 (1.42 – 15.9)

.010a .011a

Univariate analysis and multivariate logistic regression model of histopathological grade optimized based on maximizing the receiver operating characteristic (see Fig. 2) and minimizing the Akaike information criterion and Bayesian information criterion. Low-grade (LG) ¼ WHO grade I (n ¼ 118). High-grade (HG) ¼ WHO grades II or III (n ¼ 26). Abbreviations: ADC, apparent diffusion coefficient; KPS, Karnofsky performance scale score; SEM, standard error of the mean; 95% CI, 95% confidence interval; frac feat, fraction of tumors with the feature of interest. a Meets significance criteria.

Hwang et al.: Imaging and surgery predict meningioma recurrence

866 Table 1. Logistic regression analysis of histopathological grade

Hwang et al.: Imaging and surgery predict meningioma recurrence

0.12–0.83; P ¼ .02). The presence of any calcification also lowered the odds of high-grade histopathology (OR, 0.2; 95% CI, 0.03-0.80; P ¼ .03). Finally, high peritumoral edema was associated with high-grade meningiomas (OR, 2.6; 95% CI, 1.1-6.1; P ¼ .04). ADC was inversely correlated with tumor grade. High-grade meningiomas showed more diffusion restriction (lower ADC) than low-grade meningiomas (mean ADC +SEM ¼ 0.78+0.03× 1023 mm2/s vs 0.99+0.03× 1023 mm2/s; P , .001). Moreover, higher ADC values (less restricted diffusion) lowered the odds of high-grade histopathology, and this association was significant for both the logarithm of ADC (OR, 0.009; 95% CI, 0.0004-0.22; P ¼ .004) and binary ADC dichotomized about the median value of 0.88× 1023 mm2/s (OR, 0.17; 95% CI, 0.050-0.58; P ¼ .005). Interestingly, further subdivision of the 118 low-grade (WHO grade I) patients into the 58 benign tumors with 1–2 features of atypia and 60 benign tumors with no features of atypia demonstrated that ADC was also able to distinguish between low-grade meningiomas with and without atypia (mean ADC+SEM ¼ 0.93+0.03× 1023 mm2/s vs 1.05+ 0.03× 1023 mm2/s; P ¼ .04). Age and other imaging features such as T2 hyperintensity relative to gray matter, parenchymal invasion, heterogeneous tumor enhancement, capsular enhancement, intratumoral cystic change, intratumoral necrosis, reactive hyperostosis, bone invasion, and dural tails were not associated with tumor grade (Table 1). Since numerous variables were associated with histopathological grade on univariate analysis, several multivariate logistic regression models were investigated. We compared these potential models and selected the model that maximized the area under the ROC curve and minimized AIC and BIC (to penalize for model complexity). The preferred model for histopathological grade included sex, log(ADC), calcification, and high peritumoral edema as the explanatory variables (Table 1) and is given by Equation 1:   p ln = −6.7 × log(ADC) − 2.5 × calcification + 1.6 1−p × edema + 1.2 × sex − 4.4

(1)

where p ¼ probability of high-grade meningioma. For this model, the area under the ROC curve is 0.91 (Fig. 2).

Analysis of Progression/Recurrence The cumulative incidence of P/R at 5 years was 21% for lowgrade meningiomas and 40% for high-grade meningiomas. Given that some tumors undergo P/R after initial treatment, whereas others do not irrespective of histopathological grade, we next examined whether any imaging or clinical features were associated with risk of P/R across all grades. On univariate Cox proportional hazards analysis of P/R, the parameters significantly associated with P/R were sex, Simpson grade of resection, and ADC, while histopathological grade was borderline significant (Table 2). Male sex was associated with increased risk of P/R, with a hazard ratio (HR) of 2.1 (95% CI, 1.0-4.4; P ¼ .05). Surgical resection achieving Simpson grade I was strongly associated with decreased risk of P/R (HR, 0.13; 95% CI, 0.038-0.42; P ¼ .001). Only 4.8% (3/63) of patients with a Simpson grade I resection had P/R during the follow-up period

Neuro-Oncology

Fig. 2. Receiver operating characteristic (ROC) curve for multivariate logistic regression model of histopathological grade (see Table 1).

compared with 35% (28/81) of patients who had a Simpson grade II-IV resection. Higher ADC values (less restricted diffusion) lowered the risk of P/R, and this association was significant for both log (ADC) (HR, 0.12; 95% CI, 0.021 –0.65; P ¼ .01), and binary ADC dichotomized about the median value of 0.88 × 1023 mm2/s (HR, 0.34; 95% CI, 0.14-0.83; P ¼ .02). High-grade histopathology showed a trend towards increased risk of P/R but this did not reach statistical significance (HR, 2.0; 95% CI, 0.93-4.3; P ¼ .08). Age, KPS, and other imaging features such as tumor volume, tumor location, calcification, peritumoral edema, T2 hyperintensity relative to gray matter, parenchymal invasion, heterogeneous tumor enhancement, capsular enhancement, intratumoral cystic change, intratumoral necrosis, reactive hyperostosis, bone invasion, and dural tails were not associated with P/R (Table 2). Since 3 variables were associated with P/R on univariate analysis, several multivariate Cox proportional hazards models were investigated. We compared these potential models based on Harrell’s C concordance statistic (HC), AIC, and BIC. The 2 best models involved either (Model 1) Simpson grade of resection alone (HC, 0.68; AIC, 247; BIC, 250), or (2) Simpson grade combined with binary ADC dichotomized at the median value (HC, 0.73; AIC, 244; BIC, 250). Model 1 is superior based on HC, Model 2 is favored based on AIC, and both models are comparable in terms of BIC. While Simpson grade of resection is the dominant predictor, ADC is borderline significant when added to Simpson grade of resection (Table 2), so we selected Model 2 for its greater predictive power at the cost of slightly increased model complexity.

Risk Stratification Model for Progression/Recurrence The multivariate Cox proportional hazards model in the previous section (Table 2) enables the creation of 3 risk groups based on having 0 (low), 1 (moderate), or 2 (high) risk factors (nonSimpson grade I resection, low ADC dichotomized at the median value; Fig. 3). The cumulative incidences of P/R at 1 year/5 years were low-risk (0%/0%), moderate risk (4.04%/21.6%), and high risk (18.7%/45.4%). The log-rank test for trend (P , .001) was statistically significant, indicating that the risk of P/R increases

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Hwang et al.: Imaging and surgery predict meningioma recurrence

Table 2. Cox proportional hazards analysis of progression/recurrence Univariate Analysis Hazard ratio (95% CI) for P/R Sex (1 ¼ F, 2 ¼ M) KPS Age at diagnosis (y) Simpson grade I resection log(ADC) (x1023 mm2/s) ADC binary (dichotomized at median of 0.88×1023 mm2/s) High-grade histopathology Volume (cm3) Location (1 ¼ nonskull base, 2 ¼ skull base) Calcification High peritumoral edema T2 hyperintensity (relative to gray matter) Parenchymal invasion Heterogeneous tumor enhancement Capsular enhancement Cystic change Necrosis Reactive hyperostosis Bone invasion Dural tails

2.09 (1.00–4.35) 0.982 (0.951–1.01) 1.01 (0.979–1.04) 0.126 (0.038–0.415) 0.117 (0.021–0.646) 0.341 (0.140–0.831) 2.01 (0.929–4.33) 1.007 (0.998–1.015) 1.62 (0.780–3.38) 0.845 (0.367–1.94) 1.218 (0.569–2.61) 1.55 (0.806–2.98) 0.757 (0.100–5.73) 1.20 (0.553–2.62) 0.597 (0.142–2.52) 0.944 (0.284–3.13) 1.87 (0.544–6.45) 1.02 (0.473–2.20) 1.56 (0.624–3.88) 2.02 (0.768–5.30)

Multivariate Analysis P value

Hazard ratio (95% CI) for P/R

P value

0.143 (0.043– 0.474)

.001a

0.426 (0.173– 1.05)

.063b

a

.050 .260 .628 .001a .014a .018a .076b .140 .195 .692 .611 .190 .787 .641 .482 .924 .320 .957 .343 .154

Univariate analysis and multivariate Cox proportional hazards model of progression/recurrence optimized based on minimizing the Harrell’s C concordance statistic, Akaike information criterion, and Bayesian information criterion. Abbreviations: ADC, apparent diffusion coefficient; 95% CI, 95% confidence interval; KPS, Karnofsky performance scale score; P/R, progression/ recurrence. a Meets significance criteria. b Borderline significance.

moderate-risk (47/6/11%), and high-risk (25/14/36%). Note that 64% of the high-risk meningiomas are actually low-grade (WHO grade I). Of the 39 high-risk cases (non-Simpson grade I resection, low ADC), 12 received adjuvant RT, and only 2 of these patients (17%) experienced P/R. In contrast, 16 of the 27 high-risk cases (59%) with no adjuvant RT suffered P/R. The Kaplan-Meier plot comparing high-risk cases with and without adjuvant RT (Fig. 4) demonstrates a significant difference in P/R between the 2 groups (log-rank test, P ¼ .04).

Discussion

Fig. 3. Stratification of patients into 3 risk groups based on the multivariate Cox proportional hazards analysis model that includes non-Simpson grade I resection and low apparent diffusion coefficient as risk factors (see Table 2). Kaplan-Meier plot of progression/recurrence for 3 risk groups. Log-rank test for trend achieves significance (P , .001).

progressively from the low-risk to the high-risk group (Fig. 3). The breakdown by histology for each risk group is as follows: (# low-grade/# high-grade/% high-grade): low-risk (29/2/6%),

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Much of the focus of personalized medicine has been centered on molecular characterization using genomic and proteomic technologies. However, these approaches require invasive procedures to extract tissue samples, and typically only small portions can be analyzed that may not fully capture the compositional, spatial, and temporal heterogeneity of the tumor. In contrast, noninvasive imaging has great potential to aid in risk stratification and treatment guidance because it is more amenable to a comprehensive view of the entire tumor and can provide ongoing monitoring for response to therapy and P/R.32 Although histopathological grade correlates on average with clinical outcomes, there are some high-grade meningiomas that behave more like their benign counterparts and low-grade

Hwang et al.: Imaging and surgery predict meningioma recurrence

Fig. 4. Kaplan-Meier plot of progression/recurrence (P/R) for high-risk patients (non-Simpson grade I resection and low apparent diffusion coefficient) substratified based on adjuvant radiotherapy. Log-rank test demonstrates that the 2 P/R curves are significantly different (P ¼ .04).

meningiomas that behave aggressively and progress/recur after initial treatment,13 indicating that histopathological grading by itself is insufficient for optimal risk stratification. Adjuvant radiotherapy (RT) has demonstrated efficacy for high-grade (WHO grades II and III) meningiomas in several retrospective series.7 – 11 However, the role for adjuvant RT for low-grade (WHO grade I) meningiomas is unclear due to the lack of prospective randomized data.12,33,34 Since upfront RT may unnecessarily expose patients to potential toxicities,35 the development of better risk stratification models to identify the patients at greatest risk for P/R is paramount. In this study, we examined a broad range of preoperative imaging features for meningiomas using conventional MRI, CT, and DWI and looked for associations with histopathological grade and P/R after initial treatment. We discovered on univariate analysis that male sex, higher KPS score, nonskull base location, larger tumor volume, lower ADC, lack of calcification, and high peritumoral edema were associated with high-grade histopathology (Table 1). Several multivariate logistic regression models were developed from these parameters and compared based on their predictive power and model complexity. The preferred model was based on 4 variables: sex, logarithm of ADC, calcification, and peritumoral edema. Of these, the logarithm of ADC was the strongest predictor of histopathological grade (Table 1 and Fig. 2). In contrast, we found on univariate analysis that only male sex, non-Simpson grade I resection, and lower ADC were significantly associated with P/R (Table 2). Interestingly, there was only a borderline significant association between histopathological grade and P/R. We compared several multivariate Cox proportional hazards models of P/R based on maximizing predictive power and minimizing model complexity. The optimal model was based on 2 variables: extent of surgical resection (Simpson grade) and ADC (dichotomized at median value of 0.88 × 1023 mm2/s) (Table 2). Thus, we have shown that the combination of preoperative ADC and Simpson grade is superior to histopathological grade alone or in combination with Simpson grade in predicting which patients

Neuro-Oncology

will suffer from P/R. This conclusion is further supported by the observation that 64% of high-risk meningiomas in the optimal model exhibited low-grade histopathology (WHO grade I). The observed association between male sex and high-grade histopathology is consistent with prior studies showing a predominance of high-grade meningiomas in males.36,37 On the other hand, we did not observe a significant association between age at diagnosis assessed as a continuous variable and histopathological grade. Previous literature is divided on whether advanced age is a risk factor for meningiomas with increased proliferative potential and high-grade histopathology, with some studies finding an association,19,38 while others do not.16,20,36,39 An underlying factor in these disparate results is the variation in thresholds. For example, a recent study by Lin et al19 found that age ≥75 years was a risk factor for highgrade histopathology. Applying this threshold to our data, we observed a trend towards an association between age ≥75 years and high-grade histopathology (OR, 3.7; 95% CI, 0.78-17.7; P ¼ .08) that does not reach significance. It is surprising that higher KPS was associated with high-grade meningiomas on univariate analysis; however, the effect was not strong (OR, 1.06; 95% CI, 1.01-1.11) and was no longer significant after controlling for other covariates. Nonskull base tumor location was associated with highgrade histopathology, which is in agreement with previous observations.36,37 Genomic analysis has revealed that meningiomas arising adjacent to the cerebral and cerebellar hemispheres are more frequently high-grade and more commonly contain NF2 gene mutations and/or chromosome 22 loss with concomitant genomic instability.40 Larger tumor volumes also correlated with high-grade histopathology, which is consistent with the greater proliferative potential of high-grade tumors as discussed in the following. High tumor proliferative potential, as demonstrated by indices such as MIB-1/Ki-67, have been correlated with high-grade histopathology and increased risk of recurrence after resection.41 – 44 DWI detects differences in cellular density and nucleus-to-cytoplasm ratio, with ADC negatively correlated with both; therefore, it seems plausible that ADC would be associated with increased proliferative potential and a more aggressive tumor. Indeed, some studies have demonstrated that restricted diffusion is associated with higher Ki-67 and/or meningioma grade,20,22 – 26 but others found no significant relationship.27 – 30 To our knowledge, this study is the first to show that not only can the ADC parameter differentiate between low-grade (WHO grade I) and high-grade (WHO grades II and III) meningiomas but also between low-grade tumors with and without features of atypia. Underscoring the significance of this finding is our recent discovery that WHO grade I tumors with features of atypia are more likely to progress/recur than those without features of atypia.15 Moreover, while most prior studies have been limited to examining the potential association between ADC and histopathological grade, we extended our analysis to directly examine the relationship between ADC and risk of P/R and found that low ADC is also predictive of P/R. Absence of tumor calcification was associated with highgrade meningiomas but not an increased risk of P/R. Indeed, lack of calcification has been shown to correlate with high MIB-1 index, suggesting that noncalcified tumors may have higher proliferative potential than calcified tumors. 39,45,46

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Peritumoral edema also showed a significant association with tumor grade but not with P/R. The development of peritumoral edema has been ascribed to multiple potential factors including interruption of the physiological barrier between the tumor and adjacent brain parenchyma, vascularity, venous stasis, and tumor size.47 – 49 Prior studies have been ambiguous, with some showing a significant association between peritumoral edema and histopathological grade/tumor aggressiveness, 19,20,50 while others did not.17,39 However, these previous negative investigations typically differentiated only between the presence or complete absence of edema. We observed that a significant proportion of low-grade meningiomas have some peritumoral edema, but the extent of edema on average was much less than that of high-grade tumors. Hence, we segregated tumors into low- and high-edema groups, as described in the Methods, and found a significant correlation between high edema and high-grade histopathology. Heterogeneous contrast enhancement is thought to indicate a heterogeneous distribution of dividing cells as well as intratumoral necrosis and has been linked to high-grade meningiomas.18 – 20 However, heterogeneous enhancement can also be caused by calcification and intratumoral cystic change, which has not been accounted for by prior investigations. In this study, we did not consider tumors with calcification and/ or intratumoral cystic change as exhibiting heterogeneous enhancement unless there were also uninvolved regions that displayed heterogeneity. While 50% of high-grade tumors exhibited heterogeneous enhancement compared with only 31% of low-grade tumors, this difference did not reach statistical significance (OR, 2.0; 95% CI, 0.85-4.8; P ¼ .1). Using the model for P/R discussed above (Table 2), we stratified patients into 3 risk groups based on the presence of 0, 1, or 2 risk factors (non-Simpson grade I resection, low ADC). The crude rate of P/R in the high-risk group (2 risk factors) over a 5-year follow-up period was 45.4% compared with 0% for the low-risk group (0 risk factors), and the log-rank test of trend among the risk groups was highly significant (Fig. 3; P , .001). These high-risk patients (regardless of histopathological grade) would likely benefit from a more aggressive treatment approach from the outset, such as repeat resection to achieve Simpson grade I (if possible) and/or adjuvant RT. This recommendation is supported by the observation that 59% of highrisk patients with no adjuvant RT suffer P/R compared with only 17% of those with adjuvant RT (Fig. 4; P ¼ .04), suggesting that adjuvant RT at least significantly delays P/R for this subset of patients. For low-risk patients, periodic clinical and imaging surveillance is likely sufficient with repeat resection and/or salvage RT offered in the event of P/R. The approach for moderate-risk patients should weigh heavily on other patient factors and preferences, balancing the risks and benefits of active surveillance versus repeat resection and/or adjuvant RT. Limitations of this study include its retrospective nature at a single institution and the relatively small number of subjects in the high-grade cohort, which limits our statistical power to detect potential associations between some imaging features and histopathological grade/clinical outcomes. Moreover, some patients had an incomplete set of preoperative imaging parameters due to the absence of a uniform preoperative imaging protocol for meningiomas. The missing data was assumed to be missing at random (the probability a variable was missing

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depended only on the available information), which enabled application of the validated multiple imputation approach to incorporate subjects with missing data.31 In conclusion, we identified low ADC, absent calcification, and high peritumoral edema as the preoperative imaging features most predictive of advanced histopathological meningioma grade. The preferred model for P/R risk after initial treatment was based on a combination of Simpson grade of resection and dichotomized ADC. We developed a novel risk stratification model that divides patients into 3 risk groups based on these 2 parameters. The high-risk patients (45% cumulative incidence of P/R at 5 years of follow-up) are those who harbor tumors with restricted diffusion (low ADC) and nonSimpson grade I resection. Adjuvant RT at least significantly delays the onset of P/R in these high-risk cases regardless of histopathological grade. These findings suggest that the incorporation of preoperative imaging characteristics into the WHO criteria for meningioma grading may be warranted and should be further investigated with prospective trials. Moreover, future radiogenomic investigations to uncover novel correlations between cellular genomics and tissue-scale imaging will further our understanding of the biological underpinnings of meningiomas and how to best approach treatment of this common intracranial tumor. The results of such inquiries may have implications beyond diagnosis and management, such as the identification of molecular targets for therapeutic intervention, which could lead to systemic therapy that is currently unavailable for meningiomas.

Funding W.L.H. acknowledges support from the National Institute of General Medical Sciences (T32GM007753).

Conflict of interest statement. Helen A. Shih: writer, UpToDate; senior editor: International Journal of Radiation Oncology † Biology † Physics. Andrzej Niemierko: statistics editor, International Journal of Radiation Oncology † Biology † Physics. Anat O. Stemmer-Rachamimov: editorial board member, Brain Pathology. William T. Curry Jr: consultant, Stryker CMF. All other authors report no conflict of interest concerning the materials or methods used in this study or the findings specified in this paper.

References 1.

Ostrom QT, Gittleman H, Farah P, et al. CBTRUS statistical report: primary brain and central nervous system tumors diagnosed in the United States in 2006– 2010. Neuro Oncol. 2013;15(ii):1 –56.

2.

Louis DN, Ohgaki H, Wiestler OD, et al. The 2007 WHO classification of tumours of the central nervous system. Acta Neuropathol. 2007;114(2):97– 109.

3.

Goyal LK, Suh JH, Mohan DS, Prayson RA, Lee J, Barnett GH. Local control and overall survival in atypical meningioma: a retrospective study. Int J Radiat Oncol Biol Phys. 2000;46(1): 57–61.

4.

Ja¨a¨skela¨inen J, Haltia M, Servo A. Atypical and anaplastic meningiomas: radiology, surgery, radiotherapy, and outcome. Surg Neurol. 1986;25(3):233– 242.

Hwang et al.: Imaging and surgery predict meningioma recurrence

5.

Ko K-W, Nam D-H, Kong D-S, Lee J-I, Park K, Kim J-H. Relationship between malignant subtypes of meningioma and clinical outcome. J Clin Neurosci. 2007;14(8):747– 753.

23.

Tan LA, Boco T, Johnson AK, et al. Magnetic resonance imaging characteristics of typical and atypical/anaplastic meningiomas case series and literature review. Br J Neurosurg. 2014;29(1):77–81.

6.

Palma L, Celli P, Franco C, Cervoni L, Cantore G. Long-term prognosis for atypical and malignant meningiomas: a study of 71 surgical cases. J Neurosurg. 1997;86(5):793– 800.

24.

Tang Y, Dundamadappa SK, Thangasamy S, et al. Correlation of apparent diffusion coefficient with Ki-67 proliferation index in grading meningioma. Am J Roentgenol. 2014;202(6):1303 – 1308.

7.

Aghi MK, Carter BS, Cosgrove GR, et al. Long-term recurrence rates of atypical meningiomas after gross total resection with or without postoperative adjuvant radiation. Neurosurgery. 2009; 64(1):56 – 60; discussion 60.

25.

Toh CH, Castillo M, Wong aMC, et al. Differentiation between classic and atypical meningiomas with use of diffusion tensor imaging. Am J Neuroradiol. 2008;29(9):1630– 1635.

26.

8.

Boskos C, Feuvret L, Noel G, et al. Combined proton and photon conformal radiotherapy for intracranial atypical and malignant meningioma. Int J Radiat Oncol Biol Phys. 2009;75(2):399– 406.

Watanabe Y, Yamasaki F, Kajiwara Y, et al. Preoperative histological grading of meningiomas using apparent diffusion coefficient at 3T MRI. Eur J Radiol. 2013;82(4):658 –663.

27.

9.

Dziuk TW, Woo S, Butler EB, et al. Malignant meningioma: an indication for initial aggressive surgery and adjuvant radiotherapy. J Neurooncol. 1998;37(2):177–188.

Ginat DT, Mangla R, Yeaney G, Wang HZ. Correlation of diffusion and perfusion MRI with Ki-67 in high-grade meningiomas. Am J Roentgenol. 2010;195(6):1391 – 1395.

28.

10.

Goldsmith BJ, Wara WM, Wilson CB, Larson DA. Postoperative irradiation for subtotally resected meningiomas. A retrospective analysis of 140 patients treated from 1967 to 1990. J Neurosurg. 1994;80(2):195–201.

Pavlisa G, Rados M, Pazanin L, Padovan RS, Ozretic D, Pavlisa G. Characteristics of typical and atypical meningiomas on ADC maps with respect to schwannomas. Clin Imaging. 2008;32(1):22–27.

29.

Kaur G, Sayegh ET, Larson A, et al. Adjuvant radiotherapy for atypical and malignant meningiomas: a systematic review. Neuro Oncol. 2014;16(5):628–636.

Santelli L, Ramondo G, Della Puppa A, et al. Diffusion-weighted imaging does not predict histological grading in meningiomas. Acta Neurochir (Wien). 2010;152(8):1315–1319.

30.

12.

Maclean J, Fersht N, Short S. Controversies in radiotherapy for meningioma. Clin Oncol. 2014;26(1):51– 64.

Sanverdi SE, Ozgen B, Oguz KK, et al. Is diffusion-weighted imaging useful in grading and differentiating histopathological subtypes of meningiomas? Eur J Radiol. 2012;81(9):2389–2395.

31.

13.

Perry A, Stafford SL, Scheithauer BW, Suman VJ, Lohse CM. Meningioma grading: an analysis of histologic parameters. Am J Surg Pathol. 1997;21(12):1455–1465.

Hayati Rezvan P, Lee KJ, Simpson JA. The rise of multiple imputation: a review of the reporting and implementation of the method in medical research. BMC Med Res Methodol. 2015; 15(1):1– 14.

14.

Simpson D. The recurrence of intracranial meningiomas after surgical treatment. J Neurol Neurosurg Psychiatry. 1957;20(1): 22 –39.

15.

Marciscano AE, Stemmer-Rachamimov AO, Niemierko A, et al. Benign meningiomas (WHO Grade I) with atypical histological features: correlation of histopathological features with clinical outcomes. J Neurosurg. 2015:1– 9.

11.

16.

Hashiba T, Hashimoto N, Maruno M, et al. Scoring radiologic characteristics to predict proliferative potential in meningiomas. Brain Tumor Pathol. 2006;23(1):49 – 54.

17.

Hsu C-C, Pai C-Y, Kao H-W, Hsueh C-J, Hsu W-L, Lo C-P. Do aggressive imaging features correlate with advanced histopathological grade in meningiomas? J Clin Neurosci. 2010; 17(5):584–587.

18. Kawahara Y, Nakada M, Hayashi Y, et al. Prediction of high-grade meningioma by preoperative MRI assessment. J Neurooncol. 2012;108(1):147–152. 19. Lin B-J, Chou K-N, Kao H-W, et al. Correlation between magnetic resonance imaging grading and pathological grading in meningioma. J Neurosurg. 2014;121(5):1201 –1208. 20. Liu Y, Chotai S, Chen M, Jin S, Qi S-T, Pan J. Preoperative radiologic classification of convexity meningioma to predict the survival and aggressive meningioma behavior. Plos One. 2015;10(3): e0118908.

32. Aerts HJWL, Velazquez ER, Leijenaar RTH, et al. Decoding tumour phenotype by noninvasive imaging using a quantitative radiomics approach. Nat Commun. 2014;5:4006. 33.

Rogers L, Mehta M. Role of radiation therapy in treating intracranial meningiomas. Neurosurg Focus. 2007;23(4):E4.

34. Stafford SL, Pollock BE, Foote RL, et al. Meningioma radiosurgery: tumor control, outcomes, and complications among 190 consecutive patients. Neurosurgery. 2001;49(5):1029–1037. 35.

Wenkel E, Thornton AF, Finkelstein D, et al. Benign meningioma: partially resected, biopsied, and recurrent intracranial tumors treated with combined proton and photon radiotherapy. Int J Radiat Oncol Biol Phys. 2000;48(5):1363– 1370.

36. Kane AJ, Sughrue ME, Rutkowski MJ, et al. Anatomic location is a risk factor for atypical and malignant meningiomas. Cancer. 2011; 117(6):1272– 1278. 37.

Liang R-F, Xiu Y-J, Wang X, et al. The potential risk factors for atypical and anaplastic meningiomas: clinical series of 1,239 cases. Int J Clin Exp Med. 2014;7(12):5696–5700.

38.

Maillo A, Orfao A, Sayagues JM, et al. New classification scheme for the prognostic stratification of meningioma on the basis of chromosome 14 abnormalities, patient age, and tumor histopathology. J Clin Oncol. 2003;21(17):3285– 3295.

39. Kasuya H, Kubo O, Tanaka M, Amano K, Kato K, Hori T. Clinical and radiological features related to the growth potential of meningioma. Neurosurg Rev. 2006;29(4):293– 296.

21. Maiuri F, Iaconetta G, de Divitiis O, Cirillo S, Di Salle F, De Caro ML. Intracranial meningiomas: correlations between MR imaging and histology. Eur J Radiol. 1999;31(1):69 –75.

40.

Clark VE, Erson-Omay EZ, Serin A, et al. Genomic analysis of non-NF2 meningiomas reveals mutations in TRAF7, KLF4, AKT1, and SMO. Science. 2013;339(6123):1077 –1080.

22.

41.

Bruna J, Brell M, Ferrer I, Gimenez-Bonafe P, Tortosa A. Ki-67 proliferative index predicts clinical outcome in patients with atypical or anaplastic meningioma. Neuropathology. 2007;27(2): 114– 120.

Filippi CG, Edgar MA, Ulux AM, Prowda JC, Heier LA, Zimmerman RD. Appearance of meningiomas on diffusion-weighted images: correlating diffusion constants with histopathologic findings. Am J Neuroradiol. 2001;22(1):65 –72.

Neuro-Oncology

871

Hwang et al.: Imaging and surgery predict meningioma recurrence

42.

Ho DM-T, Hsu C-Y, Ting L-T, Chiang H. Histopathology and MIB-1 labeling index predicted recurrence of meningiomas: a proposal of diagnostic criteria for patients with atypical meningioma. Cancer. 2002;94(5):1538–1547.

47. de Vries J, Wakhloo AK. Cerebral oedema associated with WHO-I, WHO-II, and WHO-III-meningiomas: correlation of clinical, computed tomographic, operative and histological findings. Acta Neurochir (Wien). 1993;125(1 – 4):34–40.

43. Matsuno A, Fujimaki T, Sasaki T, et al. Clinical and histopathological analysis of proliferative potentials of recurrent and non-recurrent meningiomas. Acta Neuropathol. 1996;91(5):504 –510.

48. Inamura T, Nishio S, Takeshita I, Fujiwara S, Fukui M. Peritumoral brain edema in meningiomas – influence of vascular supply on its development. Neurosurgery. 1992;31(2):179– 185.

44.

Torp SH, Lindboe CF, Grønberg BH, Lydersen S, Sundstrøm S. Prognostic significance of Ki-67/MIB-1 proliferation index in meningiomas. Clin Neuropathol. 2005;24(4):170 –174.

49.

45.

Kuratsu J, Kochi M, Ushio Y. Incidence and clinical features of asymptomatic meningiomas. J Neurosurg. 2000;92(5):766–770.

Salpietro FM, Alafaci C, Lucerna S, Iacopino DG, Todaro C, Tomasello F. Peritumoral edema in meningiomas: microsurgical observations of different brain tumor interfaces related to computed tomography. Neurosurgery. 1994;35(4): 638 – 641.

50.

Ide M, Jimbo M, Yamamoto M, Umebara Y, Hagiwara S, Kubo O. MIB-1 staining index and peritumoral brain edema of meningiomas. Cancer. 1996;78(1):133– 143.

46. Niiro M, Yatsushiro K, Nakamura K, Kawahara Y, Kuratsu J. Natural history of elderly patients with asymptomatic meningiomas. J Neurol Neurosurg Psychiatry. 2000;68(1):25 –28.

872