Moritz Scherer, Christine Jungk, Alexander Younsi, Philipp Kickingereder, Simon Müller and Andreas Unterberg
In this analysis, the authors sought to identify variables triggering an additional resection (AR) and determining residual intraoperative tumor volume in 1.5-T intraoperative MRI (iMRI)-guided glioma resections.
A consecutive case series of 224 supratentorial glioma resections (WHO Grades I–IV) from a prospective iMRI registry (inclusion dates January 2011–April 2013) was examined with univariate and multiple regression models including volumetric data, tumor-related, and surgeon-related factors. The surgeon's expectation of an AR, in response to a questionnaire completed prior to iMRI, was evaluated using contingency analysis. A machine-learning prediction model was applied to consider if anticipation of intraoperative findings permits preoperative identification of ideal iMRI cases.
An AR was performed in 70% of cases after iMRI, but did not translate into an accumulated risk for neurological morbidity after surgery (p = 0.77 for deficits in cases with AR vs no AR). New severe persistent deficits occurred in 6.7% of patients. Initial tumor volume determined frequency of ARs and was independently correlated with larger tumor remnants delineated on iMRI (p < 0.0001). Larger iMRI volume was further associated with eloquent location (p = 0.010) and recurrent tumors (p < 0.0001), and with WHO grade (p = 0.0113). Greater surgical experience had no significant influence on the course of surgery. The surgeon's capability of ruling out an AR prior to iMRI turned out to incorporate guesswork (negative predictive value 43.6%). In a prediction model, AR could only be anticipated with 65% accuracy after integration of confounding variables.
Routine use of iMRI in glioma surgery is a safe and reliable method for resection guidance and is characterized by frequent ARs after scanning. Tumor-related factors were identified that influenced the course of surgery and intraoperative decision-making, and iMRI had a common value for surgeons of all experience levels. Commonly, the subjective intraoperative impression of the extent of resection had to be revised after iMRI review, which underscores the manifold potential of iMRI guidance. In combination with the failure to identify ideal iMRI cases preoperatively, this study supports a generous, tumor-oriented rather than surgeon-oriented indication for iMRI in glioma surgery.
Moritz Scherer, Christine Jungk, Michael Götz, Philipp Kickingereder, David Reuss, Martin Bendszus, Klaus Maier-Hein and Andreas Unterberg
In WHO grade II low-grade gliomas (LGGs), early postoperative MRI (epMRI) may overestimate residual tumor on FLAIR sequences. Consequently, MRI at 3–6 months follow-up (fuMRI) is used for delineation of residual tumor. This study sought to evaluate if integration of apparent diffusion coefficient (ADC) maps permits an accurate estimation of residual tumor early on epMRI.
From a consecutive cohort, 43 cases with an initial surgery for an LGG, and complete epMRI (< 72 hours after resection) and fuMRI including ADC maps, were retrospectively identified. Residual FLAIR hyperintense tumor was manually segmented on epMRI and corresponding ADC maps were coregistered. Using an expectation maximization algorithm, residual tumor segments were probabilistically clustered into areas of residual tumor, ischemia, or normal white matter (NWM) by fitting a mixture model of superimposed Gaussian curves to the ADC histogram. Tumor volumes from epMRI, clustering, and fuMRI were statistically compared and agreement analysis was performed.
Mean FLAIR hyperintensity suggesting residual tumor was significantly larger on epMRI compared to fuMRI (19.4 ± 16.5 ml vs 8.4 ± 10.2 ml, p < 0.0001). Probabilistic clustering of corresponding ADC histograms on epMRI identified subsegments that were interpreted as mean residual tumor (7.6 ± 10.2 ml), ischemia (8.1 ± 5.9 ml), and NWM (3.7 ± 4.9 ml). Therefore, mean tumor quantification error between epMRI and fuMRI was significantly reduced (11.0 ± 10.6 ml vs −0.8 ± 3.7 ml, p < 0.0001). Mean clustered tumor volumes on epMRI were no longer significantly different from the fuMRI reference (7.6 ± 10.2 ml vs 8.4 ± 10.2 ml, p = 0.16). Correlation (Pearson r = 0.96, p < 0.0001), concordance correlation coefficient (0.89, 95% confidence interval 0.83), and Bland-Altman analysis suggested strong agreement between both measures after clustering.
Probabilistic segmentation of ADC maps facilitates accurate assessment of residual tumor within 72 hours after LGG resection. Multiparametric image analysis detected FLAIR signal alterations attributable to surgical trauma, which led to overestimation of residual LGG on epMRI compared to fuMRI. The prognostic value and clinical impact of this method has to be evaluated in larger case series in the future.
Andrej Paľa, Jan Coburger, Moritz Scherer, Hajrullah Ahmeti, Constantin Roder, Florian Gessler, Christine Jungk, Angelika Scheuerle, Christian Senft, Marcos Tatagiba, Michael Synowitz, Christian Rainer Wirtz, Bernd Schmitz and Andreas W. Unterberg
The level of evidence for adjuvant treatment of diffuse WHO grade II glioma (low-grade glioma, LGG) is low. In so-called “high-risk” patients most centers currently apply an early aggressive adjuvant treatment after surgery. The aim of this assessment was to compare progression-free survival (PFS) and overall survival (OS) in patients receiving radiation therapy (RT) alone, chemotherapy (CT) alone, or a combined/consecutive RT+CT, with patients receiving no primary adjuvant treatment after surgery.
Based on a retrospective multicenter cohort of 288 patients (≥ 18 years old) with diffuse WHO grade II gliomas, a subgroup analysis of patients with a confirmed isocitrate dehydrogenase (IDH) mutation was performed. The influence of primary adjuvant treatment after surgery on PFS and OS was assessed using Kaplan-Meier estimates and multivariate Cox regression models, including age (≥ 40 years), complete tumor resection (CTR), recurrent surgery, and astrocytoma versus oligodendroglioma.
One hundred forty-four patients matched the inclusion criteria. Forty patients (27.8%) received adjuvant treatment. The median follow-up duration was 6 years (95% confidence interval 4.8–6.3 years). The median overall PFS was 3.9 years and OS 16.1 years. PFS and OS were significantly longer without adjuvant treatment (p = 0.003). A significant difference in favor of no adjuvant therapy was observed even in high-risk patients (age ≥ 40 years or residual tumor, 3.9 vs 3.1 years, p = 0.025). In the multivariate model (controlled for age, CTR, oligodendroglial diagnosis, and recurrent surgery), patients who received no adjuvant therapy showed a significantly positive influence on PFS (p = 0.030) and OS (p = 0.009) compared to any other adjuvant treatment regimen. This effect was most pronounced if RT+CT was applied (p = 0.004, hazard ratio [HR] 2.7 for PFS, and p = 0.001, HR 20.2 for OS). CTR was independently associated with longer PFS (p = 0.019). Age ≥ 40 years, histopathological diagnosis, and recurrence did not achieve statistical significance.
In this series of IDH-mutated LGGs, adjuvant treatment with RT, CT with temozolomide (TMZ), or the combination of both showed no significant advantage in terms of PFS and OS. Even in high-risk patients, the authors observed a similar significantly negative impact of adjuvant treatment on PFS and OS. These results underscore the importance of a CTR in LGG. Whether patients ≥ 40 years old should receive adjuvant treatment despite a CTR should be a matter of debate. A potential tumor dedifferentiation by administration of early TMZ, RT, or RT+CT in IDH-mutated LGG should be considered. However, these data are limited by the retrospective study design and the potentially heterogeneous indication for adjuvant treatment.