Peritumoral Edema Research Articles

Regrowth factors of WHO grade I skull base meningiomas following incomplete resection

The role of adjuvant radiation therapy following incomplete resection of WHO grade I skull base meningiomas (SBMs) is controversial, and little is known regarding the behavior of residual tumors. The authors investigated the factors that influence regrowth of residual WHO grade I SBMs following incomplete resection. From 2005 to 2019, a total of 710 patients underwent surgery for newly diagnosed WHO grade I SBMs. The data of 115 patients (16.2%) with incomplete resection and without any adjuvant radiotherapy were retrospectively assessed during a mean follow-up of 78 months (range 27-198 months). Pre-, intra-, and postoperative clinical and molecular factors were analyzed for relevance to regrowth-free survival (RFS). Eighty patients were eligible for analysis, excluding those who were lost to follow-up (n = 10) or had adjuvant radiotherapy (n = 25). Regrowth occurred in 39 patients (48.7%), with a mean RFS of 50 months (range 3-191 months). Significant predictors of regrowth were Ki-67 proliferative index (PI) ≥ 4% (p = 0.017), Simpson resection grades IV and V (p = 0.005), and invasion of the cavernous sinus (p = 0.027) and Meckel's cave (p = 0.027). After Cox regression analysis, only Ki-67 PI ≥ 4% (hazard ratio [HR] 9.39, p = 0.003) and Simpson grades IV and V (HR 8.65, p = 0.001) showed significant deterioration of RFS. When stratified into 4 scoring groups, the mean RFSs were 110, 70, 38, and 9 months for scores 1 (Ki-67 PI < 4% and Simpson grade III), 2 (Ki-67 PI < 4% and Simpson grades IV and V), 3 (Ki-67 PI ≥ 4% and Simpson grade III), and 4 (Ki-67 PI ≥ 4% and Simpson grades IV and V), respectively. RFS was significantly longer for score 1 versus scores 2-4 (p < 0.01). Tumor consistency, histology, location, peritumoral edema, vascular encasement, and telomerase reverse transcriptase promoter mutation had no impact on regrowth. Ki-67 PI and Simpson resection grade showed significant associations with RFS for WHO grade I SBMs following incomplete resection. Ki-67 PI and Simpson resection grade could be utilized to stratify the level of risk for regrowth.

Predicting the grade of meningiomas by clinical-radiological features: A comparison of precontrast and postcontrast MRI.

Postcontrast magnetic resonance imaging (MRI) is important for the differentiation between low-grade (WHO I) and high-grade (WHO II/III) meningiomas. However, nephrogenic systemic fibrosis and cerebral gadolinium deposition are major concerns for postcontrast MRI. This study aimed to develop and validate an accessible risk-scoring model for this differential diagnosis using the clinical characteristics and radiological features of precontrast MRI. From January 2019 to October 2021, a total of 231 meningioma patients (development cohort n = 137, low grade/high grade, 85/52; external validation cohort n = 94, low-grade/high-grade, 60/34) were retrospectively included. Fourteen types of demographic and radiological characteristics were evaluated by logistic regression analyses in the development cohort. The selected characteristics were applied to develop two distinguishing models using nomograms, based on full MRI and precontrast MRI. Their distinguishing performances were validated and compared using the external validation cohort. One demographic characteristic (male), three precontrast MRI features (intratumoral cystic changes, lobulated and irregular shape, and peritumoral edema), and one postcontrast MRI feature (absence of a dural tail sign) were independent predictive factors for high-grade meningiomas. The area under the receiver operating characteristic (ROC) curve (AUC) values of the two distinguishing models (precontrast-postcontrast nomogram vs. precontrast nomogram) in the development cohort were 0.919 and 0.898 and in the validation cohort were 0.922 and 0.878. DeLong's test showed no statistical difference between the AUC values of the two distinguishing models (p = 0.101). An accessible risk-scoring model based on the demographic characteristics and radiological features of precontrast MRI is sufficient to distinguish between low-grade and high-grade meningiomas, with a performance equal to that of a full MRI, based on radiological features.

Peritumoral edema in meningiomas: pathophysiology, predictors, and principles for treatment.

Meningiomas is a tumor of the meninges and is among the most common intracranial neoplasms in adults, accounting for over a third of all primary brain tumors in the United States. Meningiomas can be associated with peritumoral brain edema (PTBE) which if not managed appropriately can lead to poor clinical outcomes. In this review, we summarize the relevant pathophysiology, predictors, and principles for treatment of PTBE. The results of various case-reports and case-series have found that meningioma-associated PTBE have patterns in age, tumor size, and hormone receptor positivity. Our study describes how increased age, increased tumor size, tumor location in the middle fossa, and positive expression of hormone receptors, VEGF, and MMP-9 can all be predictors for worse clinical outcomes. We also characterize treatment options for PTBE such as glucocorticoids and VEGF inhibitors along with the ongoing clinical trials attempting to alleviate PTBE in meningioma cases. The trends summarized in this review can be used to better predict the behavior of meningioma-associated PTBE and establish prognosis models to identify at risk patients.

MRI Radiomics Signature of Pediatric Medulloblastoma Improves Risk Stratification Beyond Clinical and Conventional MR Imaging Features.

Prognostic evaluation is important for personalized treatment in children with medulloblastoma (MB). Limited data are available for risk stratification using a radiomics-based model. To evaluate the incremental value of an MRI radiomics signature in stratifying the risk of pediatric MB in terms of overall survival (OS). Retrospective. A total of 111 children (mean age 5.82 years) with pathologically confirmed MB divided into training and validation cohorts (77 and 34 children, respectively). A 3 T, contrast-enhanced T1-weighted imaging with inversion recovery. The study endpoint was OS defined as the time between the preoperative MRI study and death or last follow-up. The radiomics signature model and a clinical-MRI model were developed for personalized OS prediction. An integrative model, which combined the radiomics signature and clinical-MRI features, was also built using multivariable Cox regression model. The performance of the three models was evaluated with the C-index. The performance of integrative model was assessed by calibration curve and decision curve analysis (DCA). Independent T-test, Mann-Whitney U test, Fisher's exact tests or chi-square test, logistic regression analysis, Kaplan-Meier survival analysis, C-index, intraclass correlation coefficients (ICC). P < 0.05 was considered statistically significant. The media OS was 2.83 years (3.87 ± 1.85 years). Two clinical and one conventional MR imaging features (remnant, adjuvant treatment, and peritumoral edema) were selected for clinical-MRI model building. The integrative model evaluated OS (C-index 0.823) better than either the radiomics signature (C-index 0.702) or the clinical-MRI model (C-index 0.771). And it also showed good performance in the validation cohort (C-indices: 0.786, 0.756, 0.721), which was validated by the good calibration (P >0.05) and more benefit. This study demonstrated that the integrative model, which combined radiomics signature, clinical, and conventional MRI features, showed best performance in OS evaluation for children with MB. The radiomics signature may confer incremental value over clinical-MRI features. 3. Stage 2.

Comparison of 20% mannitol and 3% hypertonic saline for intraoperative brain relaxation during supratentorial brain tumour craniotomy in patients with a midline shift

Purpose of the studyA prospective, randomized, double-blind study was designed to assess differences in brain relaxation between 20% mannitol and 3% hypertonic saline (HS) during elective supratentorial brain tumour surgery in patients with midline shift. Material and methodsSixty patients undergoing supratentorial craniotomy for tumour resection were enrolled to receive either 5mL/kg of 20% mannitol (n=30) or 3% HS (n=30) administered at skin incision. PCO2 in arterial blood was maintained within 35–40mmHg and arterial blood pressure was controlled within baseline values ±20%. The primary outcome was the proportion of satisfactory brain relaxation. The surgeon assessed brain relaxation on a four-point scale (1=excellent with no swelling, 2=minimal swelling, 3=serious swelling not requiring treatment, 4=severe swelling requiring treatment). Postsurgical intracranial changes determined by imaging techniques, postoperative complications, PACU and hospital stay, and mortality at 30 days were also recorded. Appropriate statistical tests were used for comparison; P<0.05 was considered as significant. This trial was registered in Eudract.ema.europa.eu (#2021-006290-40). ResultsThere was no difference in brain relaxation: 2.00 [1.00–2.00] and 2.00 [1.75–3.00] for patients in mannitol and HS groups, respectively (P=0.804). Tumour size (OR: 0.99, 95% CI: 0.99–1.01; P=0.371), peritumoral oedema classification (OR: 0.57, 95% CI: 0.11–2.84; P=0.493), mass effect (OR: 0.86, 95% CI: 0.16–4.87; P=0.864), anaesthesia (OR: 4.88, 95% CI: 0.82–28.96; P=0.081) and midline shift (OR: 5.00, 95% CI: 0.84–29.70; P=0.077) did not have a significant influence on brain swelling in patients treated with either mannitol or HS. No significant differences in perioperative outcomes, mortality and length of PACU and hospital stay were observed. Conclusions5mL/kg of 20% mannitol or 3% HS result in similar brain relaxation scores in patients undergoing craniotomy for supratentorial brain tumour with midline shift.

CT and MRI findings of intra-parenchymal and intra-ventricular schwannoma: a series of seven cases

ObjectiveTo analyze the computed tomography (CT) and magnetic resonance imaging (MRI) features of patients with intra-parenchymal and intra-ventricular schwannoma.MethodsThe CT and MRI features of seven cases with intra-parenchymal and intra-ventricular schwannoma were analyzed retrospectively.ResultsThere were four men and three women (median age, 25 years; range, 12–42 years) in this study. The median tumor size was 4.4 cm (range, 3.1–6.5 cm). The mass was, respectively, round in four cases (57.1%), lobulated in two cases (28.6%) and oval in one case (14.3%). All tumors were well-circumscribed. Septa in the mass could be observed in three cases (42.9%), and nodular calcification was observed in two cases (28.6%), which peritumoral edema (n = 3, 42.9%) and hydrocephalus (n = 3, 42.9%) could be observed. Most of these lesions (n = 6) presented iso-hypointensity on T1-weighted images and iso-hyperintensity on T2-weighted images, except one lesion showing low intensity on T2WI. In addition, a fluid–fluid level was observed in one case. After contrast agents’ injection, all masses illustrated heterogeneously moderate to marked enhancement.ConclusionsA well-defined solid and cystic mass with calcification and moderate to marked delayed enhancement may be an objective account of intra-parenchymal or intra-ventricular schwannoma.

NIMG-03. PREOPERATIVE DEXAMETHASONE LEADS TO SIGNIFICANT REDUCTIONS IN PERITUMORAL EDEMA FOR PATIENTS WITH BRAIN METASTASES

Abstract INTRODUCTION Corticosteroids are commonly used preoperatively in patients with brain metastases to mitigate symptoms related to vasogenic peritumoral edema (PTE). Though these tumors are highly prevalent, surprisingly few studies have examined the effect of steroids on PTE evident on MRI. We investigated whether steroid administration was associated with greater reduction in PTE in brain metastasis patients compared to steroid-naïve patients. Additionally, we sought to determine if PTE reductions reflect preoperative neurologic improvement and whether an association existed between change in PTE and preoperative steroid dosing. METHODS We identified 27 patients with brain metastases and two pre-operative MRIs—one pre- and one post-steroid administration. PTE and tumor volume was calculated from FLAIR or T2 sequences using 3D Slicer. PTE was quantified with Edema Index (EI). Pertinent demographic, clinical, and dexamethasone dosing data were extracted from patient charts. Descriptive statistics were performed to compare demographic, clinical, and radiographic data between patient strata. A Pearson's R correlation was performed to assess for an association between percent change in PTE and dexamethasone dosing. All statistics were computed in R with a threshold of α= 0.05. RESULTS Patients that received preoperative dexamethasone demonstrated significantly greater percent reduction in PTE compared to their steroid naïve counterparts (p = 0.02). This finding was despite similar time elapsed between MRI studies across both groups. Similar PTE changes were observed in those with and without preoperative neurologic improvement. No significant correlation was found between percent-change in PTE and dexamethasone dosing. CONCLUSIONS We are the first to demonstrate that preoperative dexamethasone administration significantly reduces PTE in patients with brain metastases when compared to a steroid naïve reference group. Curiously, a superior reduction in PTE was not reflective of neurologic improvement. The clinical significance of this merits further study.

NIMG-04. LONGITUDINAL TRACKING OF PERITUMORAL EDEMA VOLUME USING PACS-INTEGRATED TOOLS PROVIDES CRITICAL INFORMATION IN TREATMENT ASSESSMENT OF NSCLC BRAIN METASTASES AFTER RADIOSURGERY

Abstract PURPOSE Brain metastases (BM) are the most common intracranial malignancies in adults and mostly originate from lung cancer. Gamma Knife (GK) has become standard of care for BM, however there is insufficient knowledge of the posttreatment volumetric changes of peritumoral edema of BM due to paucity of tools for volumetric segmentation in neuroradiology practice. Recently PACS-integrated tools have become available in select clinical practices facilitating the comparison of posttreatment peritumoral edema volume changes and 2D-based measurements of CE tumor core. METHODS Patients with NSCLC BM ≥ 10 mm on T1c+ treated with GK had volumetric measurements for up to 7 follow-ups using a PACS-integrated tool that segments the FLAIR hyperintense region surrounding and including the CE lesion. The 2D and volumetric measurements were compared by creating treatment response curves with incorporation of clinical information including steroid timing. RESULTS 50 NSCLC BM were included. The median pretreatment peritumoral volume was 8.5 cm3 (IQR 1–47 cm3, n= 36). The volume significantly decreased at 0–90 days (median 1.2 cm3, IQR 0.5–6.1 cm3, n= 31) and between 0-90 and 91-180 days (median 0.8 cm3, IQR 0.3-2.3 cm3, n= 26) post-GK. The time of peak median peritumoral volume increase was at &amp;gt; 365 days (median 1.4 cm3, IQR 0.4–8.1 cm3, n= 19). There was a positive correlation between longest diameter (LD) and peritumoral edema volume (rs= .75, p&amp;lt; .05). At 181–270 days post-GK 50% of BM showed incongruent response course for LD and peritumoral edema volume. The congruence/incongruence ratio of edema/enhancing portion of BM changed over follow-up time. CONCLUSION Half of the BM in our study did not show congruent response when comparing posttreatment peritumoral edema volume course to CE lesions in longitudinal assessment. Therefore, there is a critical need for quantitative tools that are incorporated into clinical practice to assess peritumoral edema treatment response.

NIMG-102. RAPNO-DEFINED SEGMENTATION AND VOLUMETRIC ASSESSMENT OF PEDIATRIC BRAIN TUMORS ON MULTI-PARAMETRIC MRI SCANS USING DEEP LEARNING; A ROBUST TOOL WITH POTENTIAL APPLICATION IN TUMOR RESPONSE ASSESSMENT

Abstract Volumetric measurements of whole tumor and its components on MRI scans, facilitated by automatic segmentation tools, are essential to reduce inter-observer variability in monitoring tumor progression and response assessment for pediatric brain tumors. Here, we present a fully automatic segmentation model based on deep learning that reliably delineates the tumor components recommended by the Response Assessment in Pediatric Neuro-Oncology (RAPNO) working group for evaluation of treatment response. Multi-parametric MRI (mpMRI) scans (T1-pre, T1-post, T2, and T2-FLAIR), acquired on multiple MRI scanners with different field strengths and vendors, for a cohort of 218 pediatric patients with a variety of histologically confirmed brain tumor subtypes were collected. The mpMRI scans were co-registered and manually segmented by experienced neuroradiologists in consensus to identify the tumor subregions including the enhancing tumor (ET), non-enhancing tumor (NET), cystic components (CC), and peritumoral edema (ED) regions. A convolutional neural network model based on DeepMedic architecture was trained using mpMRI scans as the inputs for segmentation of the whole tumor and subregions. The trained model showed excellent performance in segmentation of the whole tumor, as suggested by median dice of 0.90/0.85 for validation (n = 44)/independent test (n = 22) sets. ET and non-enhancing components (union of NET, CC, and ED) were segmented with median dice scores of 0.78/0.84 and 0.76/0.74 for validation/test sets, respectively. The automated and manual segmentations demonstrated strong agreement in estimating VASARI (Visually AcceSAble Rembrandt Images) MRI features with Pearson’s correlation coefficient R &amp;gt; 0.75 (p &amp;lt; 0.0001) for ET, NET, CC, and ED components. Our proposed automated segmentation method developed based on MRI scans acquired with different protocols, equipment, and from a variety of brain tumor subtypes, shows potential application for reliable and generalizable volumetric measurements which can be used for treatment response assessment in clinical trials.

NIMG-07. APPLYING A GLIOMA-TRAINED DEEP LEARNING AUTO-SEGMENTATION TOOL ON BM PRE- AND POST-RADIOSURGERY

Abstract PURPOSE Stereotactic radiosurgery (SRS) has become the mainstay to treat BM. Follow-up MRI provides important information on lesion treatment response and guides future therapy planning. Volumetric measurements of BM have shown promise over traditional uni- and two-dimensional measurements in more accurate and repeatable assessment. However, routine clinical use has yet to be achieved because the workflow is laborious. In previous work, we developed a PACS-integrated deep learning algorithm for automatic high- and low-grade glioma 3D segmentation. In this work, we applied this U-Net to segment BM on pre- and post-Gamma Knife (GK) MRI and evaluated the performance. METHODS 10 pre- and post-GK studies were autosegmented in five randomly selected patients (melanoma n= 3, breast n= 2). The glioma trained algorithm segmented the “Whole Tumor” (tumor core+peritumoral edema on T2w-FLAIR) and “Tumor Core” (CE tumor core+necrosis on SPGR). The AI generated segmentation was then revised as needed by a board-certified neuroradiologist and the dice-similarity-coefficient (DSC) between the revised and automatic volumetric segmentations were calculated. RESULTS Four patients had multicentric (2-4 BM) lesions. The mean± SD DSC for Whole Tumor and Tumor Core were 0.92±0.06 and 0.46±0.30 for pretreatment, 0.84±0.09 and 0.41±0.25 for posttreatment BM, respectively. The tool detected lesions with a sensitivity of 45% (5/11) for pretreatment and 50% (3/6) for posttreatment lesions. Three pretreatment and all posttreatment lesions that were not detected by the autosegmentation tool showed a very faint hyperintense peritumoral edema in T2w-FLAIR. CONCLUSION Volumetric segmentation of edema on FLAIR using the glioma-trained segmentation algorithm on pre- and post-GK BM did not require major adjustment of segmentation if it detects the lesion. On the other hand, with low sensitivity of lesion detection and low DSC for enhancing component, dedicated training of the algorithm on annotated BM data will be needed.

NIMG-53. DELTA RELAXOMETRY WITH CONTRAST ENHANCED MAGNETIC RESONANCE FINGERPRINTING: INITIAL APPLICATION TO DIFFERENTIATE BRAIN METASTASES AND GLIOBLASTOMA

Abstract PURPOSE The utility of post-contrast magnetic resonance fingerprinting (MRF) for brain tumor assessment has not been assessed. The aim of this work is to report differences in MRF-derived delta-relaxometry metrics between brain metastases and glioblastoma, offering a new strategy for tumor differentiation. METHODS Post- and pre-contrast MRF (T1, T2 and proton density maps) were acquired from 29 patients (14 brain metastases (Met), 15 glioblastoma (GB)) along with conventional MRI (T1w, T1w-Gd, T2w, T2w-FLAIR, and ADC). Post-contrast MRF was skull-stripped and non-linearly co-registered with pre-contrast MRF. Delta relaxometry metrics (ΔR1/ΔR2 ratio, ΔR1, ΔR2, and normalized ΔR1/ΔR2) were calculated in the native image space (1.2x1.2x3.0 mm3). Tumor regions were segmented using DeepMedic into necrotic core (NC), enhancing tumor (ET), and peritumoral edema (ED). ROI-averaged means of delta relaxometry metrics were compared using paired t-test for ET and ED regions in Met vs GB. Voxel-wise ΔR1/ΔR2 ratios (log transformed) were compared using unpaired two-tailed t-test with Bonferroni correction to quantify distribution differences in delta relaxometry between Met and GB. RESULTS Across all voxels of all patients in each group, ΔR1/ΔR2 ratios between Met and GB were different (0.272±0.61 vs 0.247±0.66 in ED, p &amp;lt; .001; 0.278±0.69 vs 0.264±0.67 in ET, p &amp;lt; .001). On a per-patient basis, the median, 75th percentile, and 90th percentile of ΔR1/ΔR2 ratios were different between ET and ED regions (p &amp;lt; .001). Within-ROI (NC, ET, and ED) averaged mean ΔR1/R2 ratios were not significantly different between Met and GB. CONCLUSION Voxel-wise distribution of ΔR1/ΔR2 ratios was different between tumor types (Met and GB) in both ET and ED regions. ROI-averaged ΔR1/ΔR2 ratios were different between ET and ED regions, but not specific for tumor type. Delta relaxometry provides a unique tumor-specific contrast and shows potential for solid tumor as well as peritumoral edema differentiation between Met and GB.

BIOM-48. HOXD12 IS AN INDEPENDENTLY PROGNOSTIC AGE-ASSOCIATED INDICATOR FOR POOR SURVIVAL IN OLIGODENDROGLIOMA

Abstract BACKGROUND Oligodendroglioma, IDH-mutant and 1p/19q-codeleted has variable outcomes that are strongly influenced by patient age. This study aimed to discover novel molecular biomarkers that may characterize an aggressive subgroup of oligodendroglioma that is associated with, but independently prognostic of patient age. METHODS Differential gene expression analysis, gene ontology analysis, and gene set enrichment analysis were conducted on TCGA RNA-seq data (N=169) to identify genes and pathways that differ significantly between older and younger patients. Genes whose expression was associated with age and survival in multivariate analyses were further studied using DNA methylation (N=171). The prognostic value of their expression and methylation profiles was then compared to known genomic biomarkers, radiographic features, and histopathologic features. RNA-seq and DNA methylation validation data were obtained from the CGGA (N=44) and a cohort published by Capper et al. (N=144), respectively. RESULTS Highly activated pathways in older oligodendrogliomas were linked to developmental transcription factors. Overexpression of HOXD12 was associated with patient age and survival in the TCGA (FDR&amp;lt; 0.01, FDR=1e-5) and the CGGA (p=0.03, p&amp;lt; 1e-3). Hypermethylation of HOXD12 was associated with age, tumor grade, and survival in the TCGA (p&amp;lt; 1e-5, p&amp;lt; 0.001, p&amp;lt; 1e-3) and with age and tumor grade in Capper et al. (p&amp;lt; 0.02, p=0.001). In the TCGA, HOXD12 hypermethylation and overexpression were independently prognostic of NOTCH1 and PIK3CA mutations, loss of 15q, and MYC activation as well as mitotic figures, Ki-67 index, microvascular proliferation, and necrosis. HOXD12 overexpression was also independently prognostic of T1-post contrast enhancement, whole tumor volume, and peritumoral edema volume. We developed a risk-stratification nomogram predicting 5- and 10-year overall survival using patient age, HOXD12 methylation, and WHO grade. CONCLUSIONS HOXD12 overexpression and hypermethylation are associated with an aggressive subtype of oligodendroglioma and may serve as superior prognostic biomarkers than previously reported genomic, radiographic, and histopathologic features.

DDEL-14. SYSTEMIC THERAPY USE FOR THE TREATMENT OF MENINGIOMA: A SYSTEMATIC REVIEW

Abstract INTRODUCTION Meningiomas are the most common primary central nervous system tumor. Many studies have investigated systemic therapy agents for treating meningiomas, but no study has systematically evaluated the various agents used while comparing outcomes. The goal of this study was to investigate the recent systemic therapy agents used to treat meningioma tumors and to compare relevant clinical outcomes such as progression-free survival and overall survival in patients with meningioma tumors receiving systemic therapy agents as part of their care.Materials and METHODS A systematic literature review was performed to investigate systemic therapy agents used to treat meningioma tumors. The PubMed database was used for this review and articles published from 7/4/2011 to 7/4/2021 were evaluated. The exclusion criteria included the following: animal and cell line studies, case reports, review articles, articles in a foreign language (other than English), as well as articles not related to meningioma or to systemic therapy agents. RESULTS 163 articles were initially evaluated. After excluding 152 articles using the exclusion criteria for our study, a total of 11 articles exploring 14 different systemic therapy agents were ultimately included and compared, mainly focusing on the two clinical outcomes of progression-free survival and overall survival. The study findings suggest that Bevacizumab may have the most promising results for reducing peri-tumoral edema and extending progression-free survival, with the highest observed progression-free survival at six months of 86% compared to lower progression-free survival for other systemic therapy agents. CONCLUSION This systematic review study evaluated systemic therapy agents used to treat meningioma tumors. Bevacizumab was found to have the most promising results overall. However, further studies are now needed to evaluate the efficacy and possible side effects of Bevacizumab amongst a larger population of patients with different meningioma tumor grades, locations, and treatment responses.

NIMG-104. PRE-OPERATIVE LANGUAGE FUNCTIONAL MRI (FMRI) FOR LOCALIZATION OF THE RIGHT VENTRAL PREMOTOR CORTEX (VPMC) IN COMPARISON WITH DIRECT CORTICAL STIMULATION

Abstract PURPOSE To assess the concordance of pre-operative language functional MRI (fMRI) for localization of the right ventral premotor cortex (vPMC) in comparison with Direct Cortical Stimulation. METHODS AND MATERIALS Prospective analysis was performed for 11 (n=11) patients with right-sided tumors who underwent language mapping by fMRI, followed by awake neurosurgery and intra-operative mapping by Direct Cortical Stimulation (DCS). Multi-paradigm language fMRI was performed using a standard 3-paradigm language protocol, with additional tongue movement paradigm on a Phillips Ingenia, 1.5T Scanner. The vPMC was identified as BOLD signal activation seen in at least two paradigms anterior to and discrete from the motor orofacial cortex. Pre-operative fMRI findings were validated intra-operatively using DCS with the intra-operative responses of anarthria (speech arrest) and dysarthria recorded separately. RESULTS We obtained moderate concordance (sensitivity) of 72.2% (n=8) for anarthria (speech arrest). The vPMC was the site of speech arrest in 75% cases (n=6), followed by the oro-facial motor cortex in the remainder (n=2, 25%). Higher frequency of vPMC activation was seen with Tongue Movement and Number Counting paradigms, while that of Broca’s area with Verb Generation. Tumour size &amp;gt;5cm, presence of peritumoral edema and intra-tumoral haemorrhage were some of the features associated with fMRI-DCS discordance. CONCLUSIONS vPMC detection by fMRI shows good concordance (sensitivity) with anarthria responses on Direct Cortical Stimulation. Thus, fMRI serves as a useful non-invasive tool in pre-operative planning for maximal safe resection of brain tumors.

BIOM-52. DIAGNOSTIC POTENTIAL OF EXTRACELLULAR VESICLES IN MENINGIOMA PATIENTS

Abstract Standard monitoring after meningioma resection relies on serial MRI examinations, which are time-consuming, expensive and provide no information on molecular alterations that may indicate progression towards a more aggressive tumor. Extracellular vesicles (EVs) secreted by tumor cells play an important role in cell-cell communication, and tumor-derived EVs circulating in patient blood can serve as biomarkers. We investigated the potential role of plasma EVs in meningioma patients for tumor detection and determined whether EVs secreted by meningioma cells reflect epigenetic, genomic and proteomic alterations of original tumors. EV concentrations were quantified in patient plasma (n = 46). Short-term meningioma cultures were established (n = 26) and secreted EVs were isolated. Methylation and copy number profiling was performed using 850k arrays, and mutations were identified by targeted gene panel sequencing. Differential quantitative mass spectrometry was employed for proteomic analysis. We found that the levels of circulating EVs were significantly elevated in meningioma patients compared to healthy individuals, and that plasma EV concentrations correlated with malignancy grade and extent of peritumoral edema. Postoperatively, EV counts dropped to normal levels, and the magnitude of the postoperative decrease was associated with extent of tumor resection (Simpson grade). Methylation profiling of EV-DNA allowed correct tumor classification as meningioma in all investigated cases, and accurate methylation subclass assignment in nearly all cases. Copy number variations present in tumors, as well as tumor-specific mutations were faithfully reflected in meningioma EV-DNA. Proteomic EV profiling did not permit original tumor identification but revealed tumor-associated proteins such as desmoplakin that could potentially be utilized to enrich meningioma EVs from biofluids. In conclusion, elevated EV levels in meningioma patient plasma may aid in tumor diagnosis and assessment of treatment response. Meningioma EV-DNA mirrors genetic and epigenetic tumor alterations and facilitates molecular tumor classification.

Alterations in white matter fiber density associated with structural MRI and metabolic PET lesions following multimodal therapy in glioma patients.

In glioma patients, multimodality therapy and recurrent tumor can lead to structural brain tissue damage characterized by pathologic findings in MR and PET imaging. However, little is known about the impact of different types of damage on the fiber architecture of the affected white matter. This study included 121 pretreated patients (median age, 52 years; ECOG performance score, 0 in 48%, 1-2 in 51%) with histomolecularly characterized glioma (WHO grade IV glioblastoma, n=81; WHO grade III anaplastic astrocytoma, n=28; WHO grade III anaplastic oligodendroglioma, n=12), who had a resection, radiotherapy, alkylating chemotherapy, or combinations thereof. After a median follow-up time of 14 months (range, 1-214 months), anatomic MR and O-(2-[18F]fluoroethyl)-L-tyrosine (FET) PET images were acquired on a 3T hybrid PET/MR scanner. Post-therapeutic findings comprised resection cavities, regions with contrast enhancement or increased FET uptake and T2/FLAIR hyperintensities. Local fiber density was determined from high angular-resolution diffusion-weighted imaging and advanced tractography methods. A cohort of 121 healthy subjects selected from the 1000BRAINS study matched for age, gender and education served as a control group. Lesion types differed in both affected tissue volumes and relative fiber densities compared to control values (resection cavities: median volume 20.9 mL, fiber density 16% of controls; contrast-enhanced lesions: 7.9 mL, 43%; FET uptake areas: 30.3 mL, 49%; T2/FLAIR hyperintensities: 53.4 mL, 57%, p<0.001). In T2/FLAIR-hyperintense lesions caused by peritumoral edema due to recurrent glioma (n=27), relative fiber density was as low as in lesions associated with radiation-induced gliosis (n=13, 48% vs. 53%, p=0.17). In regions with pathologically increased FET uptake, local fiber density was inversely related (p=0.005) to the extent of uptake. Total fiber loss associated with contrast-enhanced lesions (p=0.006) and T2/FLAIR hyperintense lesions (p=0.013) had a significant impact on overall ECOG score. These results suggest that apart from resection cavities, reduction in local fiber density is greatest in contrast-enhancing recurrent tumors, but total fiber loss induced by edema or gliosis has an equal detrimental effect on the patients' performance status due to the larger volume affected.

Programmed death ligand 1 and tumor-infiltrating CD8+ T lymphocytes are associated with the clinical features in meningioma

ObjectiveTo investigate the expression of programmed death ligand-1 (PD-L1) and the levels of CD8+ tumor-infiltrating lymphocytes (TILs) in meningioma as well as determine the association between their levels and the clinical outcomes.MethodsWe performed a retrospective case-control study on 93 patients with meningioma. The patients showed tumor recurrence and were matched with the control patients without recurrence in their age, gender, admission time, tumor sites, tumor volume, peritumoral brain edema (PTBE), Simpson grade resection, WHO grade, postoperative radiotherapy, and the follow-up duration. We reviewed the clinical data of patients and performed immunohistochemistry analysis to investigate the PD-L1 expression and the levels of CD8+ TILs. Multivariate logistic regression was performed to analyze the association between clinical features and immune markers. The conditional logistic regression models were used to calculate the odds ratios (ORs) with 95% confidence intervals (CIs), and Kaplan–Meier analysis was performed to analyze tumor recurrence.ResultsTumor volume was correlated with the PD-L1 expression (P = 0.003, HR = 5.288, 95%CI, 1.786–15.651). PTBE served as an independent predictor of CD8+ TIL levels (P = 0.001, HR = 0.176, 95%CI 0.065–0.477). The levels of CD8+ TILs were associated with tumor recurrence (P = 0.020, OR = 0.325, 95%CI, 0.125–0.840).ConclusionTumor volume was associated with PD-L1 expression, and PTBE was an independent predictor of CD8+ TIL levels in meningioma. CD8+ TIL levels correlated with tumor recurrence in meningioma.

MRI findings to differentiate musculoskeletal dedifferentiated liposarcoma from atypical lipomatous tumor.

This study aimed to assess the efficacy of using MRI findings for differentiating musculoskeletal dedifferentiated liposarcoma (DDLP) from atypical lipomatous tumor (ALT). This study included 22 patients with histopathologically proven DDLP and 35 with ALT in the musculoskeletal areas. All DDLPs were immunohistochemically positive for MDM2. MRI findings for both pathologies were retrospectively reviewed and compared. The maximum lesion diameter was significantly lower in DDLPs than in ALTs (p < 0.01). Ill-defined margin, peritumoral edema, and tail sign were more frequently observed in DDLPs than in ALTs (p < 0.01, respectively). The fatty component was less frequently observed in DDLPs than in ALTs (27 vs. 100%; p < 0.01), whereas the non-fatty component was more frequently observed in DDLPs than in ALTs (100 vs. 11%; p < 0.01). The occupation rate by non-fatty components was significantly higher in DDLPs than in ALTs (p < 0.01). No significant differences were observed in imaging findings associated with fatty component; however, necrosis within the non-fatty component on the contrast-enhanced image was more frequently observed in DDLPs than in ALTs (72 vs. 0%, p < 0.05). DDLPs always had a non-fatty component, whereas ALTs always had fatty component. Ill-defined margin, peritumoral edema, tail sign, and necrosis within non-fatty components were useful MRI features for differentiating musculoskeletal DDLP from ALT.

Correlation of morphologic findings and apparent diffusion coefficient values with Ki-67 proliferation index in patients with glioblastoma

Objectives: Glioblastoma is the most common primary neoplasm of the central nervous system (CNS) and has a very poor prognosis. Ki-67 proliferative index is a value that reflects the mitotic index of the tumor and is associated with poor prognosis. The radiological features of the tumors can predict the course of the disease. The aim of this study is to evaluate the relationship between the morphology and the apparent diffusion coefficient (ADC) values of the tumor with the Ki-67 index on preoperative magnetic resonance imaging (MRI). Methods: Preoperative MRI images of 52 patients with pathological diagnosis of glioblastoma were evaluated retrospectively. A score ranging from 1 to 3 was assigned to each of the morphological features of the tumors (peritumoral edema, necrosis, contrasting pattern, heterogeneity, hemorrhage, mass effect, tumor contour irregularity), and was added up to obtain the total score. In addition, the ADC values of each tumor were measured at the workstation. ADC value and total score of each tumor, and Ki-67 values obtained histopathologically were compared. Results: There was a negative correlation between Ki-67 index of tumors and ADC values (r=-0.895, p = 0.0001). A significant positive correlation was found between the morphological features of the tumors and their total scores (r=0.772, p = 0.0001). A statistically significant negative correlation was found between total score and ADC values (r=-0.780, p = 0.0001). Heterogeneity and necrosis were the features most closely associated with Ki-67. These were followed by mass effect, hemorrhage and contour irregularity, respectively. Conclusions: The morphological findings and ADC values obtained from preoperative MRI are related to the Ki-67 value, and thus can be used to predict prognosis and guide treatment in the early period.

A Subregion-Based Survival Prediction Based on Multi-Parametric MRIs for Glioblastoma

<h3>Purpose/Objective(s)</h3> To predict the survival of GBM patients by using multi-parametric MR images, we developed a novel framework of subregion-based radiomic analysis. This study aims to search for the best combinations among tumor subregions and various MRI sequences for GBM survival prediction. <h3>Materials/Methods</h3> 119 GBM patients provided by BraTS 2020 were used in the study. 100 cases were used for training and evaluating under 5-fold cross-validation and the external 19 cases were used for independent testing. For each tumor subregion, we used open-source software to extract 680 subregional radiomic features from one MRI sequence for subsequent analysis. We proposed a novel algorithm to uncover an optimal MRIs combination from multiple MRI sequences. By a one-to-one matching relation between 4 sequences MRIs (T1/T1ce/T2/FLAIR) and 3 tumor subregions (gadolinium-enhancing tumor (ET), peritumoral edema (ED), and non-enhancing tumor core (NET)), we evaluated the 64 (4³) kinds of subregional radiomic features combinations (680 × 3) based on the evaluation of maximizing the performance of survival stage classification between long-stage (>365 days) and short-stage (<365 days) groups using the SVC (Support Vector Classification) classifier. The best combination with a quarter size compared to the initial imaging data (680 × 12) can be determined and achieved precisely prediction. <h3>Results</h3> As shown in table, the specific matching relation of NET-FLAIR, ED-T1ce, ET-T2 which used 3-sequence resulted in the highest AUCs of 0.998 and 0.983 on the training and independent test cohort respectively. The model generated from optimized 3 MR sequences of features was superior to those models using one single-sequence, 2-sequence, other combinations of 3-sequence and 4-sequence MRIs. <h3>Conclusion</h3> We demonstrated the efficacy of a novel subregion-based framework for survival prediction of GBM by using multi-parametric MRIs. The proposed approach effectively combined multiple MR images and achieved survival prediction precisely.