bluuebunny/crossref_metadata_2025 huggingface dataset:
NIMG-11. IMPACT OF INVERSION TIME FOR FLAIR ACQUISITION ON THE T2-FLAIR MISMATCH DETECTABILITY FOR IDH-MUTANT, NON-CODEL ASTROCYTOMAS
Authors: Kinoshita Manabu , Arita Hideyuki , Takahashi Masamichi , Uda Takehiro , Fukai Junya , Ishibashi Kenichi , Kijima Noriyuki , Hirayama Ryuichi , Sakai Mio , Arisawa Astuko , Takahashi Hiroto , Nakanishi Katsuyuki , Kagawa Naoki , Ichimura Kouichi , Kanemura Yonehiro , Narita Yoshitaka , Kishima Haruhiko
Published: December 2020

PURPOSE

The current research tested the hypothesis that TI shorter than 2400 ms under 3T for FLAIR can improve the diagnostic accuracy of the T2-FLAIR mismatch sign for identifying IDHmt, non-CODEL astrocytomas.

EXPERIMENTAL DESIGN

We prepared three different cohorts; 94 MRI from 76 IDHmt, non-CODEL LrGGs, 33 MRI from 31 LrGG under the restriction of FLAIR being acquired with TI < 2400 ms for 3T or 2016 ms for 1.5T, and 103 MRI from 103 patients from the TCIA/TCGA dataset for LrGG. The presence or absence of the “T2-FLAIR mismatch sign” was evaluated, and we compared diagnostic accuracies according to TI used for FLAIR acquisition.

RESULTS

The T2-FLAIR mismatch sign was more frequently positive when TI was shorter than 2400 ms under 3T for FLAIR acquisition (p = 0.0009, Fisher’s exact test). The T2-FLAIR mismatch sign was positive only for IDHmt, non-CODEL astrocytomas even if we confined the cohort with FLAIR acquired with shorter TI (p = 0.0001, Fisher’s exact test). TCIA/TCGA dataset validated that the sensitivity, specificity, PPV, and NPV of the T2-FLAIR mismatch sign to identify IDHmt, non-CODEL astrocytomas improved from 31%, 90%, 79%, and 51% to 67%, 94%, 92%, and 74%, respectively if we acquired FLAIR with TI shorter than 2400 ms.

CONCLUSIONS

We revealed that TI for FLAIR impacts diagnostic accuracy of the T2-FLAIR mismatch sign and that FLAIR scanned with TI < 2400 ms in 3T is necessary for LrGG imaging.
NIMG-14. MACHINE LEARNING-BASED EVALUATION OF STATIC AND DYNAMIC FET-PET FOR THE DETECTION OF PSEUDOPROGRESSION IN PATIENTS WITH IDH-WILDTYPE GLIOBLASTOMA
Authors: Kebir Sied , Schmidt Teresa , Weber Matthias , Lazaridis Lazaros , Galldiks Norbert , Langen Karl-Josef , Kleinschnitz Christoph , Hattingen Elke , Herrlinger Ulrich , Lohmann Philipp , Glas Martin
Published: December 2020

BACKGROUND

Pseudoprogression (PSP) detection in glioblastoma has important clinical implications and remains a challenging task. With the significant advances provided by machine learning (ML) in health care, we investigated the potential of ML in improving the performance of PET using O-(2-[18F]-fluoroethyl)-L-tyrosine (FET) for differentiation of tumor progression from PSP in IDH-wildtype glioblastoma.

METHODS

We retrospectively evaluated the PET data of patients with newly diagnosed IDH-wildtype glioblastoma following chemoradiation. All patients presented imaging findings suspected of PSP/TP on contrast-enhanced MRI. For further diagnostic evaluation, patients underwent subsequently an additional dynamic FET-PET scan. The modified Response Assessment in Neuro-Oncology (RANO) criteria served to diagnose PSP. To develop a robust ML model, we trained a Linear Discriminant Analysis (LDA)-based classifier using FET-PET derived features on a training cohort and validated the results on a separate test cohort. The results of the ML model were compared with a conventional FET-PET analysis using the receiver-operating-characteristic (ROC) curve.

RESULTS

Of the 44 patients included in this study, 14 patients were diagnosed with PSP. The mean (TBRmean) and maximum tumor-to-brain ratios (TBRmax) were significantly higher in the TP group as compared to the PSP group (p=0.010 and p=0.047, respectively). The area under the ROC curve (AUC) for TBRmax and TBRmean was 0.68 and 0.74, respectively. Using the LDA-based algorithm, the AUC (0.93) was significantly higher than the AUC for TBRmax.

CONCLUSIONS

This study shows that in IDH-wildtype glioblastoma, ML-based PSP detection leads to better diagnostic performance compared to conventional ROC analysis.
NIMG-15. EVALUATING FLUCTUATING ENHANCEMENT IN OLIGODENDROGLIOMAS ON MAGNETIC RESONANCE IMAGING
Authors: Barbaro Marissa , Pan Peter , Pisapia David , Schwartz Theodore , Ramakrishna Rohan , Knisely Jonathan , Fine Howard , Chiang Gloria , Magge Rajiv
Published: December 2020

OBJECTIVE

To identify and characterize patterns of fluctuating contrast enhancement on magnetic resonance imaging (MRI) in patients with oligodendrogliomas.

INTRODUCTION

Gliomas, particularly oligodendrogliomas, can exhibit fluctuating enhancement (FE) on MRI that can make it difficult to differentiate between treatment effect and active tumor.

METHODS

We are conducting a single-center retrospective review of clinical and radiographic data for patients with oligodendrogliomas treated at Weill Cornell Medicine (WCM) from 2/2000-5/2018. We have identified patients with FE on MRI and tracked lesions > 5mm in at least one dimension to the resolution of the lesion or last available MRI. We have recorded time from initial diagnosis to development of FE, time from radiation to development of FE, and time from development to resolution of FE as well as molecular characteristics of each tumor.

RESULTS

A total of 122 patients with oligodendrogliomas were identified. Thus far, fluctuating enhancement has been identified in 11 patients (5 men, 6 women) with 38 total fluctuating lesions. Isocitrate dehydrogenase-1 (IDH-1) mutation was present in 5 tumors, and 1p/19q co-deletion was present in 6. Mean time from initial diagnosis to development of FE was 44.6 months. In patients who developed FE after radiation, mean time from radiation to development of FE was 35.0 months. Twenty-seven lesions resolved, and mean time from onset to resolution of FE was 5.6 months, while mean time from start of radiation to resolution of FE was 41.0 months. Additionally, we will perform perfusion analysis on lesions > 5mm and identify patients who underwent surgical biopsy of FE with pathologic diagnosis.

CONCLUSIONS

FE has been identified in 11 patients thus far. We are expanding our analysis to identify a larger cohort of patients with FE. Characterizing patterns of FE may aid clinicians in differentiating FE due to treatment effect from active tumor.
NIMG-21. DIFFERENTIATING TUMOR TYPES BASED ON THE PERITUMORAL MICROENVIRONMENT USING CONVOLUTIONAL NEURAL NETWORKS
Authors: Samani Zahra Riahi , Parker Drew , Alappatt Jacob Antony , Brem Steven , Verma Ragini
Published: December 2020

PURPOSE

The differential diagnosis of glioblastoma (GBM) versus single brain metastasis (Met) is clinically important, and is undertaken with a clinical reading of MR images and/or tumor biopsy. We investigate whether Mets and GBMs can be differentiated based on the microstructure of the FLAIR-hyperintense peritumoral region measured by diffusion tensor imaging (DTI). We hypothesize that the peritumoral microstructure differs in extracellular water content, based on whether it is vasogenic edema or infiltrative. We use deep learning trained on DTI-based free-water volume fraction maps to discriminate between the peritumoral regions of Met and GBM neoplasms. Our results are also compared with mean diffusivity (MD), the most commonly used DTI metric.

METHOD

dMRI data of 143 patients with brain tumors (89 glioblastomas and 54 metastases, ages 19-87 years, 77 females and 66 males) were included. Free-water volume fraction maps were computed for the peritumoral regions (demarcated automatically). We developed a 7-layer convolutional neural network (CNN) architecture to distinguish microstructural patterns of Met and GBM tumors using 32 x 32 mm patches placed at random in the peritumoral area. The CNN was trained on patches from a training set of 113 patients and tested on the remaining 30 patients, where majority voting was applied to predict the tumor type for each patient. Although MD has been previously used in both tumor and peritumoral area for discriminating tumor type, we replicated the same process with MD only in the peritumoral area to provide a stronger comparison.

RESULT

We predicted tumor type with 93% accuracy, outperforming MD with 84% accuracy.

CONCLUSION

Our results demonstrate that deep learning with CNN on DTI-based free-water volume fraction map can be a promising tool for automatic distinction of tumor types, and has potential as a tumor biomarker.
NIMG-28. VALIDATION OF MODIFIED RESPONSE ASSESSMENT IN NEURO ONCOLOGY (mRANO) DETERMINED PFS AS A STRONG PREDICTOR OF OVERALL SURVIVAL IN RECURRENT GLIOBLASTOMA TREATED WITH A TARGETED IMMUNOTOXIN
Authors: Ellingson Benjamin , Chandhasin Chandtip , Coello Melissa , Merchant Nina , Merchant Fahar
Published: December 2020

INTRODUCTION

The current study compared the modified response assessment in neuro-oncology (mRANO)(1), iRANO (2), and standard RANO criteria (3) as well as quantified the association between progression-free (PFS) and overall survival (OS) in an immunotherapy trial in recurrent glioblastoma (rGBM).

METHODS

A total of 47 patients with rGBM were enrolled in a phase II convection-enhanced delivery of an IL4R-targeted immunotoxin (MDNA55-05, NCT02858895). Bidirectional tumor measurements were created by local sites and an independent radiologic faculty (IRF), then standard RANO, iRANO, and mRANO criteria were applied. Differences of PFS and the association between PFS and OS were evaluated.

RESULTS

41 of 47 patients were evaluable for response. Both local site and IRF-determined PFS was significantly shorter using standard RANO compared to iRANO (log-rank, P< 0.0001; HR=0.3) and mRANO (P< 0.0001; HR=0.3). No difference in PFS was observed between iRANO and mRANO (Local, P=0.67; IRF, P=0.59). In patients who died and had confirmed progression on standard RANO, no correlation was observed between PFS and OS (Local, P=0.47; IRF, P=0.34). Using the iRANO, a weak association driven by a few outliers was observed between confirmed PFS and OS via local site measurements (P=0.017), but not central IRF measurements (P=0.18). Importantly, 24 of 41 patients (59%) were censored using iRANO and not included because they did not have confirmation of progression 3 months after initial progression. A strong correlation was observed between mRANO PFS and OS for both local (R2=0.66, P< 0.0001) and IRF-determined reads (R2=0.57, P=0.0007).

CONCLUSION

No correlation between PFS and OS was observed for standard RANO or iRANO, but a strong correlation was identified between both locally-determined and centrally-determined PFS and OS using the mRANO criteria. Also, the iRANO criteria was difficult to implement due to need to confirm progression 3 months after initial progression, censoring more than half the patients.
NIMG-39. UTILITY OF PHYSIOLOGIC MR METRICS IN DISTINGUISHING TRUE-PROGRESSION FROM PSEUDOPROGRESSION IN GLIOBLASTOMAS STRATIFIED BY MGMT PROMOTER METHYLATION
Authors: Chawla Sanjeev , Wang Sumei , Nazem Amir , Burke Morgan , MacLean Nasrallah , Bagley Stephen , Brem Steven , Mohan Suyash
Published: December 2020

BACKGROUND

Methylation of O6-methyl-guanine-methyl transferase MGMT gene promoter is associated with favorable prognosis in glioblastoma (GBM) patients treated with surgery and chemoradiation therapy (CRT).

OBJECTIVE

To investigate potential of diffusion and perfusion MR imaging in distinguishing TP from PsP in GBM patients stratified by MGMT status.

METHODS

A cohort of 92 patients demonstrating new/increasing enhancing lesions within six months of completion of CRT underwent 3T MR imaging. Median values of mean diffusivity (MD), fractional anisotropy (FA), anisotropy coefﬁcients [linear(CL), planar (CP), and spherical (CS)] and maximum relative cerebral blood volume (rCBVmax) were computed from enhancing lesions. Patients were classified as TP (n=65) and PsP (n=27) based on histopathology or follow-up MRI scans. Mann-Whitney, independent-sample T-tests and receiver operating characteristic (ROC) curve analyses were performed to distinguish TP from PsP. Of 92 patients, MGMT status was available from 60 patients [MGMT-methylated (n=23) and MGMT-unmethylated (n=37)]. Statistical analyses were also performed in distinguishing TP (n=15) and PsP (n=8) from MGMT-methylated and MGMT-unmethylated subgroups (TP=28; PsP=9). A p-value of 0.05 was considered significant.

RESULTS

Significantly higher rCBVmax and FA and a trend towards higher CP were observed in TP compared to PsP. Among these parameters, rCBVmax had the best sensitivity=62%, specificity=68% and accuracy=67% in distinguishing TP from PsP. ROC analysis revealed sensitivity=54%, specificity=78% and accuracy=68% after combination of these parameters. In MGMT methylated patients, only rCBVmax was significantly higher in TP than in PsP with sensitivity=79%, specificity=67% and accuracy=74% at a threshold rCBVmax value of 2.23. In MGMT unmethylated group, a trend towards higher rCBVmax was observed in TP than in PsP with sensitivity=67%, specificity=77%, accuracy=69%, threshold value=2.89.

CONCLUSION

Physiologic imaging parameters demonstrate variable diagnostic values for detecting PsP in GBM patients stratified by MGMT status. The best parameter in distinguishing TP from PsP was rCBVmax in patients demonstrating MGMT promoter methylation.
NIMG-40. RADIOGENOMIC SIGNATURES OF DRIVER GENES IN NEWLY DIAGNOSED GLIOBLASTOMA PATIENTS BASED ON PRE-OPERATIVE MULTI-PARAMETRIC MRI
Authors: Fathi Kazerooni Anahita , Toorens Erik , Bakas Spyridon , Akbari Hamed , Sako Chiharu , Mamourian Elizabeth , Ha Sung Min , Thakur Nina , Rosado Jennifer-Marie , Bagley Stephen , Ganguly Tapan , MacLean Nasrallah , Davatzikos Christos
Published: December 2020

PURPOSE

Non-invasive and quantitative biomarkers of somatic mutations derived from multi-parametric MRI (MP-MRI) could potentially help in predicting the response of patients to therapy, leading to development of targeted and personalized treatments. In this study, we developed radiogenomic signatures of multiple driver genes using artificial intelligence (AI) methods.

METHODS

In this study, 2740 radiomic features, including shape and volumetric measures computed for different tumorous regions, and characteristics derived from histograms and gray-level co-occurrence matrix (GLCM), were extracted from pre-operative MP-MRI (T1, T1Gd, T2, T2-FLAIR, DTI, and DSC-MRI) scans of 161 patients with newly diagnosed glioblastoma. The tumor samples, collected surgically from these patients, were sequenced using an in-house targeted next generation sequencing (NGS) panel of genes. We constructed quantitative imaging signatures of somatic mutations in several genes from 161 IDH-wildtype glioblastoma patients, including ATRX, FGFR2, EGFR, MET, NF1, PDGFRA, PIK3CA, PTEN, RB1, TP53, using cross-validated SVM classifiers.

RESULTS

The cross-validated classification performance for each signature was assessed by area under the receiver operating characteristic (ROC) curve (AUC), indicating the following results: PTEN (n = 69, AUC = 0.64), EGFR (n = 52, AUC = 0.72), TP53 (n = 51, AUC = 0.67), NF1 (n = 33, AUC = 0.74), ATRX (n = 22; AUC = 0.74), FGFR2 (n = 6, AUC = 0.82), MET (n = 26, AUC = 0.77), PDGFRA (n = 14, AUC = 0.82), PIK3CA (n = 14, AUC = 0.78), RB1 (n = 14, AUC = 0.81).

CONCLUSION

Using multi-parametric MRI, we developed quantitative non-invasive in vivo signatures with the potential for pre-operative assessment of a glioblastoma’s molecular characteristics. These non-invasive radiogenomic biomarkers may be useful for understanding the molecular composition of a glioblastoma prior to surgical resection, thus enabling earlier selection of patients for targeted therapy trials and possible neoadjuvant treatment.
NIMG-46. RADIOGENOMIC FEATURES PREDICT CLINICALLY RELEVANT GENOME-WIDE ALTERATION SIGNATURES IN GLIOBLASTOMA
Authors: Nuechterlein Nicholas , Li Beibin , Fink James , Haynor David , Holland Eric , Shapiro Linda , Cimino Patrick
Published: December 2020

BACKGROUND

Previously, we have shown that combined whole-exome sequencing (WES) and genome-wide somatic copy number alteration (SCNA) information can separate IDH1/2-wildtype glioblastoma into two prognostic molecular subtypes (Group 1 and Group 2) and that these subtypes cannot be distinguished by epigenetic or clinical features. However, the potential for radiographic features to discriminate between these molecular subtypes has not been established.

METHODS

Radiogenomic features (n=35,400) were extracted from 46 multiparametric, pre-operative magnetic resonance imaging (MRI) of IDH1/2-wildtype glioblastoma patients from The Cancer Imaging Archive, all of whom have corresponding WES and SCNA data in The Cancer Genome Atlas. We developed a novel feature selection method that leverages the structure of extracted radiogenomic MRI features to mitigate the dimensionality challenge posed by the disparity between the number of features and patients in our cohort. Seven traditional machine learning classifiers were trained to distinguish Group 1 versus Group 2 using our feature selection method. Our feature selection was compared to lasso feature selection, recursive feature elimination, and variance thresholding.

RESULTS

We are able to classify Group 1 versus Group 2 glioblastomas with a cross-validated area under the curve (AUC) score of 0.82 using ridge logistic regression and our proposed feature selection method, which reduces the size of our feature set from 35,400 to 288. An interrogation of the selected features suggests that features describing contours in the T2 abnormality region on the FLAIR MRI modality may best distinguish these two groups from one another.

CONCLUSIONS

We successfully trained a machine learning model that allows for relevant targeted feature extraction from standard MRI to accurately predict molecularly-defined risk-stratifying IDH1/2-wildtype glioblastoma patient groups. This algorithm may be applied to future prospective studies to assess the utility of MRI as a surrogate for costly prognostic genomic studies.
NIMG-50. INITIAL EXPERIENCE: DETECTION OF ABERRANT HYPERPOLARIZED [1-13C]PYRUVATE METABOLISM IN PATIENTS WITH GBM PRIOR TO RESECTION
Authors: Autry Adam , Gordon Jeremy , LaFontaine Marisa , Chen Hsin-Yu , Villanueva-Meyer Javier , Chang Susan , Clarke Jennifer , Xu Duan , Lupo Janine , Larson Peder , Vigneron Daniel , Li Yan
Published: December 2020

INTRODUCTION

Detecting radiological response or resistance to treatment in patients with GBM is difficult with conventional MRI. In response to this challenge, hyperpolarized carbon-13 (HP-13C) MRI techniques were developed to probe real-time [1-13C]pyruvate metabolism.

METHODS

Dynamic HP-13C MRI was acquired pre-operatively from 6 patientswith recurrent GBM following intravenous injection of HP [1-13C]pyruvate. Five were confirmed with tumor progression and one had treatment effects without progression. Frequency-selective echo-planar imaging (8 slices, 3s temporal resolution, 3.38 cm3 spatial resolution, 60s acquisition) captured [1-13C]pyruvate metabolism to [1-13C]lactate and [1-13C]bicarbonate in the brain. Proton imaging included 3-D FLAIR, T1-weighted post-Gd IRSPGR, and spectroscopy. Carbon-13 voxels with non-enhancing lesion (NEL) or contrast-enhancing lesion (CEL) were identified for subsequent analysis. Temporally-summed HP-13C metabolite data within the CEL and NEL were evaluated using the pyruvate-to-lactate ratio; a modified ratio that takes into account vascular contributions of pyruvate; and parameter percentile ranks over the entire brain. Proton spectroscopy data were processed to obtain choline-to-NAA index (CNI) maps, which provide z-scores of relative tissue abnormality.

RESULTS

All of the anatomic lesions displayed abnormal CNI with maximum values of 3.22-6.35. The 5 patients with CEL lesions demonstrated 87th– 98thpercentile levels of pyruvate in the brain; and 95th-100thpercentile levels of lactate in 4 progressed patients and 60thpercentile in the patient presenting with treatment effects. For the patient with an exclusively non-enhancing lesion, percentile levels of pyruvate and lactate were 66thand 88thin the brain, respectively. The mean+/-SD percentile of the lactate-to-pyruvate and modified ratios were 75+/-22, 86+/-23 and 60+/-3, 71+/-12 in the progressed and non-progressed patients, respectively.

CONCLUSION

These data importantly demonstrate aberrant [1-13C]pyruvate metabolism in patients with GBM in both contrast-enhancing and non-enhancing lesions. Ongoing studies will further characterize the utility of HP imaging markers.
NIMG-61. UNUSUAL PRESENTATION OF NEUROSARCOIDOSIS: A CASE SERIES
Authors: Kleinschmidt-Demasters B K , Ormond David , Winograd Evan
Published: December 2020

INTRODUCTION

Neurosarcoidosis is a rare diagnosis, and even with known systemic disease or history, often remains a diagnosis of exclusion. Typical imaging findings of neurosarcoidosis include white matter lesions coupled with meningeal enhancement, or “sugarcoating” near the skull base. Occasionally, imaging can be quite unusual and mimic other entities. Other diagnoses to rule out include neoplastic, autoimmune, or infectious pachymeningitis, neoplastic lesions, neurosyphilis or tuberculosis.

METHODS

Our neuropathology database was queried for neurosarcoidosis from January 2008 until December 2019. These cases were then reviewed for cases with unusual presentations for further review and discussion.

RESULTS

Here we present 16 cases of neurosarcoidosis with histories and/or imaging that did not conform to the typical appearance of neurosarcoidosis. Along with a rare radiographic presentation, these cases also lacked CSF, laboratory, or systemic findings to suggest a diagnosis of neurosarcoidosis. 15 of these cases presented intracranially while 1 case presented within the spinal cord.

CONCLUSIONS

Neurosarcoidosis presentations can vary greatly. A better understanding of some unique patient presentations can help improve noninvasive diagnosis, although biopsy often remains necessary for confirmation.
NIMG-68. MATHEMATICAL MODELING OF THERMAL DAMAGE ESTIMATE VOLUMES IN MAGNETIC RESONANCE-GUIDED LASER INTERSTITIAL THERMAL THERAPY
Authors: Liang Allison , Munier Sean , Danish Shabbar
Published: December 2020

BACKGROUND

Magnetic resonance-guided laser interstitial thermal therapy is a minimally invasive procedure that produces real-time thermal damage estimates of ablation (TDE). Orthogonal TDE-MRI slices provides an opportunity to mathematically estimate ablation volume.

OBJECTIVE

To mathematically model TDE volumes and validate with post-24 hours MRI ablation volumes.

METHODS

Ablations were performed with the Visualase Laser Ablation System (Medtronic). Using ellipsoidal parameters determined for dual-TDEs from orthogonal MRI planes, TDE volumes were calculated by two definite integral methods (A and B) implemented in Matlab (MathWorks). Post 24-hours MRI ablative volumes were measured in OsiriX (Pixmeo) by two-blinded raters and compared to TDE volumes via paired t-tests and Pearson’s correlations.

RESULTS

Twenty-two ablations for 20 patients with various intracranial pathologies were included. Average TDE volumes calculated with Method A was 3.44 ± 1.96 cm3 and with Method B was 4.83 ± 1.53 cm3. Method A TDE volumes were significantly different than post-24 hours volumes (P < 0.001). Method B TDE volumes were not significantly different than post-24 hours volumes (P = 0.39) and strongly correlated with each other (r = 0.85, R2 = 0.72, P < 0.0001). A total of 8/22 (36%) method A versus 17/22 (77%) method B TDE volumes were within 25% of the post 24-hours ablative volume.

CONCLUSION

We present the first iteration of a viable mathematical method that integrates dual-plane TDEs to calculate volumes resembling 24 hours post-operative volumes. Future iterations of our algorithm will need to determine additional calculated variables that improve the performance of volumetric calculations.
PATH-02. CHARACTERIZATION OF FUNCTIONAL NETWORK EFFECTS IN THE CEREBRAL CORTEX DURING BRAIN TUMORIGENESIS IN THE MOUSE
Authors: Cramer Samuel , Popa Laurentiu , Haley Samuel , Dhawan Sanjay , Carter Russell , Ning Jianfang , Aronson Justin , Kodandaramaiah Suhasa , Ebner Timothy , Chen Clark
Published: December 2020

INTRODUCTION

Neuro-cognitive decline is near universal in glioblastoma patients and negatively impacts the quality of life for afflicted patients. Yet, there is little information on longitudinal effects of brain tumor growth on cerebral cortical function and network connectivity.

OBJECTIVE

To address this knowledge gap, we examined in vivo Ca2+ flux imaging in a transgenic murine glioblastoma model.

METHODS

Mesoscopic Ca2+ imaging was performed after implant of GL261 glioblastoma cells into a transgenic mice strain (Thy1-GCaMP6f) that expresses the fast calcium indicator GCaMP6f in Layer II/III and Layer V pyramidal neurons. Independent component analysis (ICA), correlation matrix and graph theory approaches were used to assess changes in network connectivity.

RESULTS

ICA defined canonical cerebral network consisting of nodal convergence and connectivity between nodes. The overall network structure remained unaltered after tumor implant. A decrease in the strength of connectivity was observed immediately following tumor implant. This temporary suppression was followed by progressive, global increase in the strength of nodal connectivity (p < 0.0001). By two weeks post-tumor implant, 50% of the nodes exhibited increased connectivity compared to baseline. Progressive activation of select nodes was also observed in the weeks following tumor implant (p < 0.01). In aggregate, these results suggest that activation of select network nodes as well as enhanced connectivity as means to compensate for the deleterious effects of glioblastoma growth.

CONCLUSIONS

Our results indicate that focal brain tumor growth induces a reorganization of both local and remote cortical activity. The finding bear pertinence to the pathogenesis of neuro-cognitive decline and tumor associated epilepsy.
PATH-06. ASSESSMENT OF CIRCULATING TUMOR DNA IN CEREBROSPINAL FLUID BY WHOLE EXOME SEQUENCING TO DETECT GENOMIC ALTERATIONS OF GLIOBLASTOMA
Authors: Duan Hao , He Zhenqiang , Chen Zhenghe , Mou Yonggao
Published: December 2020

Cerebrospinal fluid (CSF) has been demonstrated as a better source of circulating tumor DNA (ctDNA) than plasma for brain tumors. However, it is unclear whether whole exome sequencing (WES) is qualified for detection of ctDNA in CSF. The aim of this study was to determine if assessment of ctDNA in CSF by WES is a feasible approach to detect genomic alterations of glioblastoma. CSFs of ten glioblastoma patients were collected pre-operatively at the Department of Neurosurgery, Sun Yat-sen University Cancer Center. ctDNA in CSF and genome DNA in the resected tumor were extracted and subjected to WES. The identified glioblastoma-associated mutations from ctDNA in CSF and genome DNA in the resected tumor were compared. Due to the ctDNA in CSF was unqualified for exome sequencing for one patient, nine patients were included into the final analysis. More glioblastoma-associated mutations tended to be detected in CSF comparing with the corresponding tumor tissue samples (3.56±0.75 vs. 2.22±0.32, P=0.097), while the statistical significance was limited by the small sample size. The average mutation frequencies were similar in CSF and tumor tissue samples (74.12% ± 6.03% vs. 73.83% ± 5.95%, P = 0.924). The R132H mutation of isocitrate dehydrogenase 1 and the G34V mutation of H3F3A which had been reported in the pathological diagnoses were also detected from ctDNA in CSF by WES. Patients who received temozolomide chemotherapy previously or those whose tumor involved subventricular zone tended to harbor more mutations in their CSF. Assessment of ctDNA in CSF by WES is a feasible approach to detect genomic alterations of glioblastoma, which may provide useful information for the decision of treatment strategy.
PATH-19. MOLECULAR, HISTOLOGIC AND CLINICAL CHARACTERISTICS OF OLIGODENDROGLIOMAS: A MULTI-INSTITUTIONAL RETROSPECTIVE STUDY
Authors: Dono Antonio , Alfaro-Munoz Kristin , Yan Yuanqing , Lopez-Garcia Carlos , Soomro Zaid , Williford Garret , Takayasu Takeshi , Robell Lindsay , Majd Nazanin , de Groot John , Esquenazi Yoshua , Kamiya-Matsuoka Carlos , Ballester Leomar Y
Published: December 2020

In the 2016 WHO classification of CNS tumors, oligodendrogliomas are molecularly defined by IDH1 or IDH2 mutations and 1p/19q co-deletion. Some reports suggest that PI3K pathway alterations may confer increased risk of progression and poor prognosis in oligodendroglioma. However, factors that influence prognosis in molecularly defined oligodendroglioma (mOGD) have not been thoroughly studied. Also, the benefits of adjuvant radiation and temozolomide in mOGDs remain to be determined. 107 mOGDs diagnosed between 2008-2018 at the University of Texas Health Science Center at Houston (n= 39) and MD Anderson Cancer Center (n= 68) were included. A retrospective review of the demographic, clinical, histologic, molecular, and outcomes were performed. Median age at diagnosis was 37 years and 61 (57%) patients were male. There were 64 (60%) WHO Grade 2 and 43 (40%) WHO Grade 3 tumors. Ninety-five (88.8%) tumors were IDH1-mutant and 12 (11.2%) were IDH2-mutant. Eighty-two (77%) patients were stratified as high-risk: older than 40-years and/or subtotal resection (RTOG 9802). Gross-total resection was achieved in 47 (45%) patients. Treatment strategies included observation (n= 15), temozolomide (n= 11), radiation (n= 13), radiation with temozolomide (n= 62) and other (n= 6). Our results show a benefit of temozolomide vs. observation in progression-free survival (PFS). However, no benefit in PFS or overall survival (OS) was observed when comparing radiation vs. radiation with temozolomide. PIK3CA mutations were detected in 15 (14%) cases, and patients with PIK3CA-mutant mOGDs showed worse OS (10.7-years vs 15.1-years, p= 0.009). Patients with WHO Grade 3 tumors had shorter PFS but no significant difference in OS was observed compared to grade 2. Our findings suggest that mOGDs harboring PIK3CA mutations have worse OS. Except for an advantage in PFS in temozolomide treated patients, adjuvant treatment with radiation or the combination of both, showed no significant advantage in terms of OS.
PATH-25. EXPERIENCE WITH AN RNA FUSION TRANSCRIPT PANEL FOR DETECTION OF POTENTIAL THERAPEUTIC TARGETS IN GLIOMAS
Authors: Kothari Shawn , Bagley Stephen , Desai Arati , Morrisette Jennifer , Sussman Robyn , MacLean Nasrallah
Published: December 2020

Next-generation sequencing to identify fusion proteins is increasingly employed across oncology to identify therapeutic targets.1 The clinical relevance of detecting fusion transcripts is well described in the pediatric glioma population, but similar reports for adult patients are scant.2 The University of Pennsylvania Health System (UPHS) has implemented routine use of an RNA fusion transcript panel (ArcherDX, Boulder, CO) on resected brain tumors since August 2017. Here we report the results of this analysis for adult patients with gliomas and highlight potentially targetable fusions. Over the period of August 2017 through December 2019, fusion analysis was performed on resected gliomas of over 200 patients. Ninety-seven patients were found to have a detected fusion protein. Eighty-three of the 97 patients (86%) had glioblastoma and 14 (14%) had lower grade gliomas. A total of 26 unique fusions were found. The most common (n=55) was EGFRvIII. NTRK fusions were of special interest as FDA-approved agents are available for patients harboring this genetic alteration.3 We identified 8 patients (8%) with NTRK fusions including ARHGEFF2:NTRK1, BNA: NTRK1, BCR: NTRK2, PDE5A/NTRK2, SKAP2/NTRK2, and STRN: NTRK2. Several of these patients went on to receive TRK kinase inhibitors with clinical benefit. Of the 97 patients with a detected fusion, 24 (25%) were found to have a potentially targetable fusion other than EGFRvIII, with inhibitors available in clinical trials or as off-label therapy. These fusions included BRAF (n=5; BRAF: LHFPL3, KIAA1549:BRAF), FGFR (n=9; FGFR3:BRAP, FGFR3:RENBP, FGFR3:TACC3), MET (n=7; CAPZA2-MET, KLF12:MET, PTPRZ1:MET, ST7:MET), and ROS1 (n=3; DLL: ROS1, GOPC: ROS1). In sum, routine clinical use of an RNA-based fusion transcript panel for adult patients with glioma may allow for detection of therapeutically targetable alterations in a meaningful proportion of cases. Prospective trials are needed to determine whether targeting specific fusions is beneficial for adult patients with glioma.
PATH-28. EXTENT AND PROGNOSTIC VALUE OF MGMT PROMOTOR METHYLATION DEPEND ON IDH MUTATION AND 1p19q CO-DELETION IN GLIOMA WHO GRADE II
Authors: Karschnia Philipp , Teske Nico , Siller Sebastian , Dorostkar Mario M , Weller Jonathan , Herms Jochen , Baehring Joachim M , von Baumgarten Louisa , Tonn Joerg-Christian , Thon Niklas
Published: December 2020

INTRODUCTION

Methylation of the promotor region of the O6-methylguanin-DNA-methyltransferase (MGMT) gene is associated with increased survival in low- and high-grade glioma. It is unknown whether this association also applies to the 2016 WHO categories of glioma WHO grade II.

MATERIAL AND METHODS

We retrospectively searched the institutional database of the Center for Neuro-Oncology for patients with glioma WHO grade II. Patients were assigned to one of three groups according to the 2016 WHO classification system: 1. 1p19q co-deleted oligodendroglioma, IDH mutant; 2. 1p19q non-codeleted astrocytoma, IDH mutant; 3. 1p19q non-codeleted astrocytoma, IDH wild-type. MGMT methylation status was analysed using Sanger sequencing of the CpG sites 74-98 within the MGMT promotor region. The total number of methylated CpG sites was calculated for each patient.

RESULTS

155 patients with glioma WHO grade II were encountered, including 81 1p19q co-deleted, IDH mutant oligodendrogliomas; 54 IDH mutant astrocytomas; and 20 IDH wild-type astrocytomas. The mean number of methylated CpG sites among oligodendrogliomas was significantly higher when compared to IDH mutant astrocytomas (18.9 ± 0.4 vs. 16.3 ± 0.6; p = 0.001). In turn, the number of methylated CpG sites among IDH mutant astrocytomas was higher when compared to IDH wild-type astrocytomas (16.3 ± 0.6 vs. 12.3 ± 1.9; p = 0.007). Median follow-up was estimated at 35 months. Median time to malignant progression was 87 months for all patients, and median overall survival was not reached. In the entire cohort, a larger number of methylated CpG sites was prognostic of overall survival and time to malignant progression. When analysed separately for the three WHO subgroups, a similar association was only retained in IDH wild-type astrocytoma.

CONCLUSION

In our series of WHO II gliomas, MGMT promotor methylation appeared strongly associated with 1p19q codeletion and IDH mutations. MGMT promotor methylation was only prognostic in IDH wild-type astrocytoma.
PATH-31. ARTIFICIAL INTELLIGENCE IN GLIOMA PATHOLOGY IMAGE ANALYSIS FOR RISK PREDICTION
Authors: Chunduru Pranathi , Phillips Joanna , Molinaro Annette
Published: December 2020

Pathological evaluation of tumor tissue images stained with hematoxylin and eosin (H&E) is pivotal in diagnosis and predictive of outcome, yet only a small fraction of the rich phenotypic information on the slide is currently used for clinical care. In this study, we developed a computational approach based on deep learning to predict overall survival within distinct molecular subtypes of glioma patients and to extract prognostic biomarkers from microscopic images of tissue biopsies. Whole-slide images from 766 unique patients [IDH: 336 IDH-wildtype, 364 IDH-mutant, 1p/19q: 142 1p/19q-codeleted, 620 1p/19q-non-codeleted] were obtained from The Cancer Genome Atlas (TCGA). Sub-images that were free of artifacts and that contained viable tumor with descriptive histologic characteristics were extracted, which were used for training and testing the deep neural-network. Our unified survival deep learning framework (SDL) uses a residual CNN network integrated with a traditional survival model to predict patient risk from digitized whole-slide images. We employed statistical sampling techniques and randomized transformation of images to address challenges in learning from histology images. Univariable and multivariable Cox proportional-hazards regression models were used to evaluate the significance of predicted patient risk with and without controlling for known prognostic factors. The integrated SDL framework showed substantial prognostic power achieving a median c-index of 0.79 [95 % CI 0.77 - 0.81]. In multivariable Cox regression analysis, SDL risk was significantly associated with overall survival (hazard ratio of 1.65, 95% CI 1.49-1.83, p < 0.001) after adjusting for age, grade, IDH status, ATRX status, 1p19q codeletion and CDKN2A/2B status. Only IDH-status and age were also significant in the multivariable model. Preliminary findings highlight the emerging role of AI in precision medicine and suggest the utility for computational analysis of tumor tissue images for objective and accurate prediction of outcome for glioma patients and also for risk stratification for targeted clinical therapy.
PATH-33. EPIGENOMIC ANALYSIS OF SPINAL EPENDYMOMA
Authors: Yamazawa Erika , Tanaka Shota , Genta Nagae , Hiroko Meguro , Umeda Takayoshi , Hana Taijun , Takami Toshihiro , Nakanishi Yuta , Taniguchi Makoto , Takai Keisuke , Komori Takashi , Ichimura Kouichi , Fukuoka Kohei , Takayanagi Shunsaku , Aburatani Hiroyuki , Saito Nobuhito
Published: December 2020

BACKGROUND

Ependymomas commonly occur in the fourth ventricle and the spinal cord. Gross total resection, age and WHO grade are known prognostic factors. Ependymomas are currently classified into 9 distinct subgroups by DNA methylation profile analysis. Spinal cord ependymoma is distinct from other subgroups. To investigate heterogeneity within spinal cord ependymoma, we examined DNA methylation profiles.

MATERIALS AND METHODS

We used Infinium MethylationEPIC array (illumina) to obtain DNA methylation data from frozen specimens of spinal ependymoma resected at the University of Tokyo, Osaka City University, and Tokyo Metropolitan Neurological Hospital. Japan Pediatric Molecular Neuro-Oncology Group provided methylation data for 11 reported cases. Cluster analysis was performed using Cluster3.0.

RESULTS

We analyzed 34 patients, 21 male and 13 female, aged from 18 to 76 years (median 50.5 years), including 2 cases with neurofibromatosis type 2. WHO grade was grade_3 in 2 cases and grade_2 in others. Clustering of the DNA methylation data showed that WHO grade_3 cases tended to be classified into a subgroup distinct from other cases.

CONCLUSION

This is the largest DNA methylation profiling study on spinal cord ependymoma to date. The study may suggest a new subgroup correlated with higher WHO grade.
PATH-34. GENETIC PROFILING OF AGGRESSIVE MENINGIOMAS REVEAL DIVERSE SPECTRUM OF ACCOMPANYING ALTERATIONS BEYOND NF2 INACTIVATION
Authors: Schulte Jessica , Magill Stephen , Nguyen Minh , Bush Nancy Ann Oberheim , Villanueva-Meyer Javier , Theodosopoulos Philip , McDermott Michael , Butowski Nicholas , Bollen Andrew , Tihan Tarik , Lee Julieann , Pekmezci Melike , Perry Arie , Raleigh David , Solomon David
Published: December 2020

BACKGROUND

Meningiomas are the most common primary central nervous system tumor in adults. The majority are clinically indolent and WHO grade I. However, 20-30% are WHO grade II and 1-3% are WHO grade III, which have shorter progression-free (PFS) and overall survival. A subset of grade I meningiomas also follow an aggressive course, requiring serial resection and/or radiotherapy, similar to high-grade meningiomas. The objective of this study was to characterize the genetic alterations in meningiomas with an aggressive clinical course.

METHODS

Targeted next-generation sequencing (NGS) of 40 aggressive meningiomas was performed using the UCSF500 cancer panel, which assesses ~500 cancer-related genes. Information on patient demographics, tumor histopathology, and treatment history was also collected.

RESULTS

Meningiomas analyzed included 15 (38%) WHO grade I, 11 (28%) WHO grade II, and 13 (33%) WHO grade III. At the time of genetic profiling, 71% of patients had received prior treatment (68% surgery, 48% fractionated radiotherapy, 23% radiosurgery). The most commonly altered gene was NF2, with 71% of tumors demonstrating biallelic inactivation. Other common alterations included biallelic CDKN2A/B deletion (15%) and TERT amplification or promoter mutation (13%). Other recurrent alterations involved SUFU (8%), and ARID1A, ATM, BAP1, DMD, KDM6A, and PTEN (each 5%). Genes which are commonly altered in indolent WHO grade I meningiomas, such as AKT1, KLF4, PIK3CA, SMO, and TRAF7, were intact in this cohort.

CONCLUSIONS

The additional genetic alterations beyond NF2 inactivation that drive aggressive meningiomas are diverse and include homozygous deletion of CDKN2A (negative regulator of cyclin-dependent kinases 4/6), inactivating mutations in SUFU (a negative regulator of Hedgehog signaling), homozygous deletion of PTEN (a negative regulator of mTOR signaling), and mutations/deletions in epigenetic regulatory factors (e.g. ARID1A, KDM6A). Clinical trials are needed to assess the efficacy of therapeutics targeting these specific pathways in patients with meningiomas refractory to conventional treatments.
QOLP-07. HEALTH-RELATED QUALITY OF LIFE AND SYMPTOM BURDEN IN PATIENTS WITH NEWLY DIAGNOSED GLIOBLASTOMA TREATED WITH BEVACIZUMAB BEYOND PROGRESSION: A PROSPECTIVE TRIAL
Authors: Tanaka Shota , Narita Yoshitaka , Mukasa Akitake , Nagane Motoo , Aoki Tomokazu , Wakabayashi Toshihiko , Uzuka Takeo , Nakamura Hideo , Arakawa Yoshiki , Suehiro Satoshi , Nakada Mitsutoshi , Morita Satoshi , Kato Mamoru , Ichimura Kouichi , Nishikawa Ryo
Published: December 2020

BACKGROUND

In BIOMARK trial, patients with newly diagnosed glioblastoma were treated with standard chemoradiotherapy combined with first-line bevacizumab; a subset of patients continued bevacizumab beyond progression (BBP). Neurocognitive function (NCF), symptom burden, and health-related quality of life (HRQoL) were examined as secondary endpoints.

PATIENTS AND METHODS

In the primary protocol, newly diagnosed glioblastoma patients aged 20-75 received standard 6-week radiotherapy combined with temozolomide and bevacizumab followed by 4-week cycles of temozolomide plus bevacizumab, and then 2-3-week cycles of bevacizumab monotherapy. Upon recurrence, patients were subjected to the secondary protocol with 2-3-week cycles of bevacizumab monotherapy with or without other chemotherapeutic agents. NCF tests (Hopkins verbal learning test-revised, trail making test, and controlled oral word association), EORTC QLQ-C30/BN20, and MDASI-BT were completed by the patients. Time to deterioration (TTD) was defined as the time from randomization until a pre-specified change from baseline without further improvement or death. The Kaplan-Meier method and the log-rank test were used to assess TTD for each subscale of the above tests.

RESULTS

Overall, 94 patients were enrolled in the study. Analyses were based on the full analysis set cohort (N=90), excluding non-glioblastoma diagnosis by central review. The median overall survival (OS) and progression-free survival (PFS) were 25.0 and 14.9 months, respectively. Baseline HRQoL and symptom burden subscales (emotional functioning, symptom severity score, affective factor, and focal factor) were significantly associated with PFS. The median TTD was 8.7, 7.5, 8.1 months for global health status/QoL, symptom severity score, interference score, respectively. Among patients who experienced recurrence, disease progression was apparently preceded by deterioration in terms of symptom burden.

CONCLUSIONS

Detailed analysis of HRQoL and symptom burden may aid care of glioblastoma patients throughout the disease trajectory.
QOLP-11. QUALITY OF END-OF-LIFE CARE IN PATIENTS WITH HIGH GRADE GLIOMAS
Authors: Ou Alexander , Harrison Rebecca , Liu Diane , Naqvi Mujtaba , Naqvi Syed Mussadiq , O’Brien Barbara , Weathers Shiao-Pei , de Groot John , Bruera Eduardo
Published: December 2020

BACKGROUND

Patients with high-grade gliomas (HGG) face unique challenges toward the end of life (EoL), given their aggressive disease trajectory and progressive neurologic deterioration. The discipline of supportive care (SC) has been beneficial in improving quality of EoL care in patients with non-CNS cancers, however data on its contribution to EoL care in patients with HGG is lacking.

METHODS

We retrospectively reviewed charts of MDA patients from 2010-2017 to compare the demographic factors and clinical and quantitative EoL outcomes between patients with HGG--who were either referred (n=54) or not referred (n=85) to SC--and patients with non-CNS cancers who were referred to SC (n=72). A composite score for poor EoL quality outcomes was used with the following variables: death in hospital, chemotherapy within 14d of death, ≥2 hospitalizations, ≥2 ER visits, ICU admission and >14 days hospitalization within the last 30 days of life. Patients were eligible for SC based on poor/declining performance status, < 6 month prognosis, or recurrent GBM.

RESULTS

Patients with HGG had similar EoL quality regardless of SC referral, and these patients in general had better EoL quality than patients with non-CNS cancers (p=0.005). EoL quality was significantly worse in HGG patients who received late versus early SC referrals (p=0.0066). Both weakness (OR=1.27, p=0.0289) and number of disease progressions (OR=2.618, p=0.001) at the time of eligibility for SC were predictive of poorer quality of EOL. The majority of HGG patients (61.2%) eligible for SC were not referred.

CONCLUSIONS

EoL outcomes in patients with malignant gliomas are overall better than those of patients with non-CNS cancer, however certain clinical features and later SC referral remain significantly associated with poorer EoL quality. Our data suggest that the role of SC in improving EoL outcomes in our patient population warrants further evaluation.
QOLP-12. EMBEDDING OUTPATIENT PALLIATIVE CARE INTO NEURO-ONCOLOGY CLINIC – RESULTS FROM A ONE YEAR PILOT
Authors: Taylor Jennie , Rabow Michael , Chang Susan , Butowski Nicholas , Clarke Jennifer , Page Margaretta , Rossi Rosemary , Shibley W Patrick , Calton Brook
Published: December 2020

BACKGROUND

Glioblastoma (GBM) patients fall within NCCN and ASCO guidelines for early palliative care (PC). However, data suggests they are less likely than systemic cancers to be referred to PC and often later in their illness. This results in potential missed opportunities, both for improving symptom control and earlier completion of important tasks, like advance care planning. Data on how to best incorporate comprehensive PC into routine neuro-oncology (NO) patient care is needed.

METHODS

We piloted a program embedding a PC physician into UCSF’s NO clinic one half-day per week. NO physicians were encouraged to refer GBM patients within 3 months of diagnosis and other patients with PC needs. PC visits were offered in-person, by telemedicine, or at home. PC physician and NO social worker made joint visits when possible; chaplaincy support was available by telemedicine. Data was collected using Palliative Care Quality Network (PCQN) database and patient satisfaction survey.

RESULTS

To date, 37 patients have been referred resulting in 103 visits (average 2.8 visits/person): 25% in-person; 68% telemedicine; 6% at home. PC physician and NO social worker met jointly with 46% visits. Median age was 58 years, 41% female, 81% non-Hispanic white, 84% GBM, median 9 months from diagnosis, and 73% receiving first line treatment. Interventions addressed across visits: 94% non-pain symptoms, 76% psychosocial needs; 71% pain; and 70% GOC. Results from satisfaction survey demonstrated 79% would recommend seeing PC embedded in NO to others and highest benefits were attention to practical considerations to staying healthy at home, discussing preferences for future medical care, and help with coping.

CONCLUSIONS

Embedding PC into NO clinics is a unique model for addressing symptoms and GOC early, is well received by patients and caregivers, and provides opportunities for collaboration and PC physicians to specialize in caring for needs of NO patients.