bluuebunny/crossref_metadata_2025_split huggingface dataset:
NIMG-25. LESION-NETWORK ANALYSIS TO IDENTIFY PREFERENTIALLY-ENGAGED NETWORKS IN EPILEPTOGENIC TUMORS
Authors: Mansouri Alireza , Boutet Alexandre , Elias Gavin , Germann Jurgen , Mithani Karim , Ibrahim George , Lozano Andres , Valiante Taufik 
Published: November 2019

Abstract

BACKGROUND
Lesion network mapping (LNM) is a method used to identify potential networks that can be ascribed to particular neurological functions/ deficits. LNM has yet to be implemented for large brain lesions such as tumors. OBJECTIVES: To apply LNM for potential identification of vulnerable epileptogenic networks in tumors causing medically-refractory epilepsy (MRE), compared with non-epileptogenic tumors.

METHODS
MRE and non-epileptogenic lesions were normalized to standard space for group analysis. These were used as a seed in high-resolution normative resting state fMRI, which was then transformed to t-maps and thresholded by t = 5.1; this corrected for multiple comparisons (Bonferroni corrections) across the whole brain at pcor < 0.05. The statistically-significant thresholded maps were binarized and summed connectivity maps were generated for both groups. This allowed computation of voxel-wise odds ratios (VORs) in order to identify voxels that were more likely associated with tumors that either did or did not result in MRE.

RESULTS
Twenty-seven patients were included. Eleven brain metastases with no history of seizures, M/F: 5/6, mean age 68.4+/-8.4 years, and 16 had MRE (10 low-grade glioma, 2 cavernoma, 3 “other”), M/F: 7:9, mean age 33.7 +/-12.2 years. Lesions causing MRE were preferentially located in the cingulate gyrus, calcarine fissure, parahippocampal gyrus and lateral temporal neocortex. The resting-state networks that were >1.5x likely to be connected with MRE lesions were the salience, executive control, and dorsal default mode networks.

CONCLUSION
In this proof of concept study, we have demonstrated that (1) in addition to stroke, tumors may also be amenable to LNM and (2) the underlying normative neural circuitry may in part explain the propensity of particular lesions toward development of MRE. This has ramifications in patient counseling and surgical management planning, as earlier surgery could be applied for lesions thought to be more prone to development of MRE.
NIMG-27. EVALUATING THE POTENTIAL OF 18F-FLUCICLOVINE POSITRON EMISSION TOMOGRAPHY TO DETECT WHOLE BRAIN TUMOR BURDEN: A PRECLINICAL STUDY
Authors: Scarpelli Matthew , Healey Debbie , Luna Melendez Ernesto , Mehta Shwetal , Quarles Chad 
Published: November 2019

Abstract

BACKGROUND
Accurately identifying the boundary of invasive brain tumors is critical for planning effective treatment. Conventional imaging includes T1-weighted contrast-enhanced MRI to identify regions where tumor angiogenesis has broken down the blood-brain barrier. However, conventional MRI has limited sensitivity for identifying invading tumor cells. Amino acid PET with 18F-fluciclovine may offer improved sensitivity. We investigate whether 18F-fluciclovine PET provides a superior measure of tumor burden than MRI.

METHODS
Rats were implanted with patient-derived glioblastoma xenografts that had been transduced to enable fluorescent imaging of the TdTomato protein. When the tumors grew to a sufficient size, the rats were scanned with 18F-fluciclovine PET followed immediately by contrast-enhanced MRI. Rats were sacrificed and whole brains were removed. Western blots were performed to measure amino acid transporter levels. Fluorescent imaging of optically cleared brain slices enabled visualization of the labelled tumor and determination of whole tumor burden. A methodology for registering in vivo PET/MRI slices to ex vivo fluorescent images of optically cleared brain slices (1-mm thickness) has been developed. Tumor volumes are manually segmented on all images.

RESULTS
The ratio of tumor to normal brain uptake (TNB) of 18F-fluciclovine peaked ten minutes post-injection (mean value 7.1) and was followed by a continual decrease in the TNB ratio (mean value 4.6 at fifty minutes post-injection). The mean percentage of MRI segmented tumor volume that was inside the PET segmented tumor volume was 95%. The mean percentage of PET segmented tumor volume that was inside the MRI segmented tumor volume was 40%. Tumors with the highest level of amino acid transporters had the highest 18F-fluciclovine uptake.

CONCLUSIONS
The majority of 18F-fluciclovine PET identified tumor regions were not identified using conventional MRI, indicating the potential of this approach to detect invasive tumor cells and provide a more robust assessment of whole tumor burden.
NIMG-28. VALIDATION OF SINGLE-DOSE DSC-MRI PROTOCOLS FOR ROBUST PERFUSION ASSESSMENT IN BRAIN TUMORS
Authors: Quarles Chad , Bell Laura , Semmineh Natenael , Fuentes Alberto , Prah Melissa , Nespodzany Ashley , Alhilai Lea , Karis John , Rand Scott , Dardis Chris , Braun Kelly , Connelly Jennifer , Zhou Yuxiang , Schmainda Kathleen , Hu Leland , Boxerman Jerry , Stokes Ashley 
Published: November 2019

Abstract
Dynamic susceptibility contrast (DSC) MRI measures of brain tumor cerebral blood volume (CBV) are able to predict grade, overall survival and response to treatment. Wide-spread acceptance of DSC-MRI has been challenged by the need to balance contrast agent dose and CBV accuracy. The goal of this study was to identify and validate single-dose, BTIP compliant, DSC-MRI protocols. Using a validated, patient-based DRO, we evaluated CBV accuracy across a range of acquisition parameters (field strength, TR, TE, flip angle, multi-echo acquisitions, dosing protocols) and post-processing steps. To validate the optimal protocols, we next collected DSC-MRI data following ASFNR’s recommended “double – dose” approach, where a single-dose preload (to minimize T1 effects) is given prior to a second bolus injection (for DSC-MRI data acquisition). The single-dose DSC-MRI data was collected during the preload bolus injection. Consistency of the derived CBV data, visual agreement and data characteristics (e.g. CNR) was statistically evaluated. When using a single-dose and routine single-echo pulse sequence, the DRO analysis found that a low flip angle (LFA = 30o) and 30ms TE provided the highest CBV accuracy (concordance correlation coefficient (CCC) = 0.92) and precision (coefficient of variation (CV) = 8.2%)). For comparison, the maximum accuracy found with the DRO utilizes a double-dose injection protocol and yielded a CCC of 0.98 and CV of 6.8%. Single-dose, multi-echo acquisitions provided higher accuracy than the LFA data and matched that found with the double-dose approach. In patients (data collection ongoing), the agreement between single-dose LFA (n > 40) or multi-echo (n > 40) based CBV values and the reference double-dose approach was very high (CCC > 0.94) and were statistically equivalent. Optimized single-dose DSC-MRI protocols provide highly accurate CBV data, use lower doses of contrast agent, and simplify scan procedures, indicating their potential for robust use in clinical practice and trials.
NIMG-31. BRAIN CONNECTIVITY PATTERNS CHARACTERIZE COGNITIVE IMPAIRMENT IN LONG-TERM SURVIVORS OF LOW-GRADE GLIOMA (LGG) USING RESTING-STATE FUNCTIONAL MRI (rs-fMRI)
Authors: Wang Chencai , Van Dyk Kathleen , Raymond Catalina , Heimberg Brandon F , Choi Justin , Lai Albert , Cloughesy Timothy , Leia Nghiemphu P , Ellingson Benjamin 
Published: November 2019

Abstract
Advanced multimodality treatments that have led to longer survival rates for patients with low-grade gliomas (LGGs) have also resulted in significant changes in cognition and quality of life (QoL). These changes remain poorly understood, largely due to the lack of multifactorial and in-depth studies on cognitive impairment in patients with LGG. Resting-state functional MRI (rs-fMRI) has been widely used as a reliable imaging biomarker to evaluate the treatment outcome by characterizing the cerebral networking alteration associated with a patient’s neurological status. In this preliminary report of an active study, we investigated the cognitive function and cerebral networking connectivity via rs-fMRI in survivors who had completed treatment for LGG within the past 10 years. Survivors were administered a battery of standardized neuropsychological tests. Of the 20 participants enrolled to date (mean age 43 ± 11), 10 participants were categorized as cognitively impaired based on the International Cognition and Cancer Task Force (ICCTF) guidelines, with recommended adjustments considering the number of tests in the battery. Compared to cognitively unimpaired participants, functional connectivity in cognitively impaired patients was lower between memory, visuospatial processing, and primary sensorimotor regions. These preliminary observations suggest there is a potential link between overall cognitive impairment and functional connectivity of various networks as measured using resting-state fMRI.
NIMG-34. MULTI-PARAMETRIC MR-PET IMAGING PREDICTS PHARMACOKINETICS AND CLINICAL RESPONSE TO GDC-0084 IN HUMAN RECURRENT HIGH-GRADE GLIOMA
Authors: Ellingson Benjamin , Yao Jingwen , Raymond Catalina , Nathanson David , Simpson Jeremy , Garner James , Olivero Alan , Mueller Lars , Rodon Jordi , Gerstner Elizabeth , Cloughesy Timothy , Wen Patrick 
Published: November 2019

Abstract
Alterations in the PI3K pathway are found in the majority of malignant gliomas, but lack of efficacy has caused investigators to question the viability of this target, particularly due to lack of brain penetration. GDC-0084 was specifically optimized to penetrate the brain, targeting both PI3K and mTOR. Since these two targets alter tumor vascularity and metabolism, respectively, we hypothesized that multi-parametric MR-PET could be used to quantify the response, estimate pharmacokinetic (PK) parameters, and predict progression-free survival (PFS) in patients with recurrent malignant gliomas. In this first-in-man, multicenter, phase I, dose-escalation study (NCT01547546), we show in 47 patients that the measured maximum concentration (Cmax) of GDC0084 was associated with a decrease in enhancing tumor volume (P=0.0287) and an increase in fractional anisotropy (FA) (P=0.0418). Post-treatment tumor volume, 18F-FDG uptake, Ktrans, and relative cerebral blood volume (rCBV) were all correlated with Cmax. A linear combination of change in 18F-FDG PET uptake, apparent diffusion coefficient (ADC), FA, Ktrans, vp, and rCBV were able to estimate both Cmax (R2=0.4113, P< 0.0001) and drug exposure (AUC) (R2=0.3481, P< 0.0001). Using this composite multi-parametric MR-PET imaging response biomarker to predict PK, patients with an estimated Cmax >0.1 uM and AUC > 1.25 uM*hr demonstrated significantly longer PFS compared with patients with a lower estimated concentration and exposure (P=0.0039 and P=0.0296, respectively). Results from the current study suggest composite biomarkers created from multi-parametric MR-PET imaging targeting metabolic and/or physiologic processes specific to the drug mechanism of action may be useful for subsequent evaluation of treatment efficacy for larger phase II-III studies.
NIMG-37. PREDICTING SEIZURE IN GLIOMA PATIENTS USING A RANDOM FOREST CLASSIFIER TRAINED ON SEX-SPECIFIC AND MIXED COHORTS
Authors: Khurana Aditya , Johnston Sandra , Whitmire Paula , Ranjbar Sara , Sharma Akanksha , Hawkins-Daarud Andrea , Rubin Joshua , Porter Alyx , Canoll Peter D , Egan Kathleen , Hu Leland , Mrugula Maciej , Kumthekar Priya , Swanson Kristin 
Published: November 2019

Abstract

PURPOSE
Brain tumor related epilepsy (BTE) is a major co-morbidity in patients with glioma. It is difficult to determine whether the use of anti-epileptic drugs is necessary. We attempted to build a machine-learning model to predict the probability of seizure presentation (SP) with glioma.

METHODS
We trained a random forest classifier using the following variables: volumetric data of pre-treatment MR images (T1Gd and T2-FLAIR sequences), patient demographics (age; sex), and measurements of tumor proliferation (log(ρ)), invasiveness (log(D)) and their relative ratio (log(ρ/D)). Our cohort consisted of 221 patients total. Using an 80-20 ratio, we used 176 patients (76 SP, 100 nSP) for training and the remaining 45 patients (19 SP, 26 nSP) were used for testing. We also trained on male-only and female-only cohorts to evaluate any sex differences in prediction. For training, 108 males (53 SP, 55 nSP) were used and 28 for testing (14 SP, 14 nSP). We used 72 females (21 SP, 49 nSP) for training and 15 (7 SP, 8 nSP) for testing. We corrected for class imbalance in the female cohort before training. Using 10-fold cross-validation and a separate testing set, we measured performance by ROC curve (AUC), accuracy, sensitivity, and specificity of predictions (average of folds in cross validation).

RESULTS
The female model achieved the highest AUC (0.853) followed by the mixed model (0.726) and the male model (0.651). In the validation set, the accuracy/sensitivity/specificity of the three cohorts were as follows: mixed (0.726/0.696/0.750), female (0.853/0.830/0.875), and male (0.651/0.577/0.722). The performance of the testing set, in terms of accuracy/sensitivity/specificity were: mixed (0.733/0.74/0.73), female (0.8/0.57/1), and male (0.714/0.64/0.79).

CONCLUSION
We found a negative correlation between seizure probability and size and invasiveness of tumors. Our model shows promising performance on testing set data. Further cohort studies and training is warranted.
NIMG-39. REVEALING THE TUMOR-IMMUNE LANDSCAPE THROUGH SPATIALLY-RESOLVED RADIOMICS: CASE STUDIES
Authors: Hawkins-Daarud Andrea , Yoon Hyunsoo , Monie Dileep , Singleton Kyle , Ranjbar Sara , Tran Nhan , Badie Behnam , Rockne Russell , Brown Christine E , Hu Leland , Bruce Jeff , Canoll Peter D , Li Jing , Swanson Kristin 
Published: November 2019

Abstract

BACKGROUND
Conventional magnetic resonance imaging (MR) guides patient care in GBM. However, there is mounting awareness that MR enhancement is non-specific reflecting either tumor progression or non-tumoral inflammatory changes. Histological evaluation of GBM is held as the gold standard for disease assessment. However, the invasiveness of this methodology and the sample sparsity limit its usefulness. Methods to infer histological underpinnings of MRI are needed to improve clinical care.

METHODS
A transfer learning mixed effects model based on T1Gd and FLAIR MR voxel based image features trained and cross-validated to predict FPKM values of CD68, CASP3, CD8A and IL13RA2. Training data included RNAseq from 38 image-localized biopsies from 15 newly-diagnosed GBM patients. These models were then applied to two independent patients, chosen based on therapy and the quality of image registration, at three different time points, just prior to receiving IL13RA2 targeted CAR-T therapy for rGBM, after 2 cycles and after 4 cycles, resulting in a voxel-based prediction of the relative expression levels of these genes.

RESULTS
Cross-validation of the proposed machine learning models demonstrated a Pearson Correlation coefficient between predicted and observed FPKM values of 0.89 (CD68), 0.92 (CASP3), 0.93 (CD8A), and 0.88 (IL13RA2). When the models were applied to the two CAR-T patients, CD68-modeled expression levels were seen to increase throughout therapy for one patient, while remaining stable for the other. Survival from first CAR-T infusion was, respectively, 412 and 83 days suggesting that the increased CD68 was indicative of therapeutic effectivity. Further, the spatial activity predictions were consistent with expected therapeutic action as the correlation coefficient between CASP3 and the product of IL13R2 and CD8A expression was 0.81, suggesting the T-cells targeting IL13RA2 were inducing cell death.

CONCLUSIONS
Preliminary results with our model highlights the potential of spatially resolved radiomic maps to provide insight into regional therapeutic effectivity.
NIMG-42. RECURRENT TUMOR AND TREATMENT-INDUCED EFFECTS HAVE DIFFERENT MR SIGNATURES IN CONTRAST ENHANCING AND NON-ENHANCING LESIONS OF HIGH-GRADE GLIOMAS
Authors: Cluceru Julia , Nelson Sarah , Molinaro Annette , Alcaide-Leon Paula , Olson Marram , Berger Mitchel , Chang Susan , Phillips Joanna , Nair Devika , Wen Qiuting , Villanueva-Meyer Javier , Chunduru Pranathi , Cha Soonmee , Lupo Janine 
Published: November 2019

Abstract

INTRODUCTION
It is estimated that 25 to 35% of patients experience treatment-induced effects that can mimic recurrent high-grade gliomas. This diagnostic challenge is complicated by the coexistence of treatment-related changes and recurrent tumor within the same lesion which limits the accuracy of classification based on summary metrics of multi-parametric MRI. This study aimed to determine whether different MR features were relevant for distinguishing pathological features of recurrent tumor from the effects of treatment in the contrast enhancing and non-enhancing lesions of recurrent high-grade gliomas.

METHODS
Leveraging our unique dataset of image-guided tissue samples that directly maps pathology to MR characteristics, we analyzed 291 tissue samples (222 recurrent tumor; 69 treatment effect) with known coordinates on imaging from 139 patients that underwent preoperative 3T MRI and surgery for a suspected high-grade recurrent tumor. 8 MR parameter values from perfusion-weighted, diffusion-weighted, and MR spectroscopic imaging at each tissue sample location were tested for association with histopathological outcome using univariate and multivariate generalized estimating equation models for enhancing and non-enhancing tissue samples. Individual cutoff values were determined and evaluated using ROC-Curve analysis with 5-fold cross-validation.

RESULTS
In tissue samples obtained from contrast-enhancing lesions, elevated relative cerebral blood volume (rCBV) was significantly associated with the presence of recurrent tumor (p< 0.03), while increases in normalized choline (nCho) and choline-to-NAA index (CNI) were significantly associated with the presence of recurrent tumor in non-enhancing tissue samples (p< 0.008). Cutoff values of 1.6(rCBV), 2.7(CNI), and 2.1(nCho) had the highest performance.

CONCLUSION
Our results confirm the utility of rCBV in distinguishing the effects of treatment from recurrent tumor within the contrast enhancing lesion. We report a novel finding that metabolic parameters can differentiate recurrent tumor from treatment-related changes in the non-enhancing lesion of high-grade gliomas. These results will help improve future management of patients with suspected recurrence.
NIMG-46. IMPACT OF FET PET ON MULTIDISCIPLINARY NEUROONCOLOGICAL TUMOR BOARD DECISIONS IN PATIENTS WITH BRAIN TUMORS
Authors: Ceccon Garry , Werner Jan-Michael , Ruge Maximilian , Hampl Jürgen , Grau Stefan , Goldbrunner Roland , Celik Eren , Reinhardt Christian , Kabbasch Christoph , Borggrefe Jan , Bauer Elena , Wollring Michael , Rosen Jurij , Tscherpel Caroline , Fink Gereon , Langen Karl-Josef , Galldiks Norbert 
Published: November 2019

Abstract

BACKGROUND
Following neurooncological treatment of brain tumors, neurooncologists are frequently confronted with equivocal MRI findings (e.g., treatment-related changes, nonmeasurable (speckled) contrast-enhancing lesions, increase of T2/FLAIR signal alterations, pseudoresponse). Especially in Europe, amino acid PET is increasingly being integrated into multidisciplinary neurooncological tumor boards (MNTB) to overcome these diagnostic uncertainties as well as to improve patient management. We here evaluated the correctness of MNTB decisions, in which amino acid PET findings were taken into account.

METHODS
In a single university center, we retrospectively evaluated 114 MNTB decisions concerning 99 patients with malignant glioma (n=81) (glioblastoma, n=54; anaplastic glioma, n=26; gliosarcoma, n=1) or brain metastases (n=18) secondary to NSCLC, melanoma, breast cancer, or colorectral cancer, presenting with equivocal MRI findings following neurooncological treatment. All patients underwent amino acid PET imaging using O-(2-[18F]-fluoroethyl)-L-tyrosine (FET) as an adjunct for decision-making. Additionally, the patients’ clinical status, pretreatment, and multimodal MRI findings were considered for decision-making. Presence of neoplastic tissue in PET was considered if the mean FET uptake as assessed by tumor-to-brain ratios was >2. The decisions’ diagnostic performance was evaluated by 2x2 contingency tables using the neuropathological results or clinicoradiological follow-up.

RESULTS
In the majority of MNTB decisions (n=102; 89%), FET PET results were integrated into the decision-making with considerable impact on the clinical management. In particular, 85% of MNTB decisions (n=87) prompted a treatment change (i.e., resection, radiotherapy, chemotherapy, or combinations thereof, as well as palliative therapy), or, in the case of suspected treatment-related changes, the continuation of the initial treatment regimen (15%; n=15). The MNTB decisions were validated using neuropathological data in 38% (n=39) or clinicoradiological information in 62% (n=63) and yielded a diagnostic accuracy of 88% (sensitivity, 89%; specificity, 75%; P=0.008).

CONCLUSIONS
Our results suggest that the integration of FET PET derived information significantly aids MNTB decisions.
NIMG-47. VOLUMETRIC ANALYSIS OF PHASE 2 AND 3 TRIALS IN RECURRENT GLIOBLASTOMA TREATED WITH VB-111 WITH OR WITHOUT BEVACIZUMAB OR BEVACIZUMAB MONOTHERAPY
Authors: Ellingson Benjamin , Raymond Catalina , Yao Jingwen , Goldman Jodi , Schlossman Jacob , Tran Caleb , Brenner Andrew , Butowski Nicholas , Wen Patrick , Rachmilewitz Minei Tamar , Cohen Yael , Harats Dror , Cloughesy Timothy 
Published: November 2019

Abstract
VB-111 is a non-replicating adenovirus carrying a pro-apoptotic transgene for TNFR1/Fas under the control of a modified murine promoter to pre-proendothelin 1. The transgene is expressed only in angiogenic endothelial cells, and therefore VB-111 results in targeted apoptosis of neovascular vessels. The current study characterizes the quantitative radiographic results and impact on OS in phase 2 and 3 trials of recurrent glioblastoma (GBM) patients treated with VB-111 with or without bevacizumab (BV) or BV monotherapy. MRI data from a phase 2 (NCT01260506) and randomized, double arm, controlled phase 3 (GLOBE; NCT02511405) trial of VB-111 in recurrent GBM were used in current study: Arm A) VB-111 monotherapy until progression followed by combination VB-111 and bevacizumab (BV) (“Primed Combination”; Phase 2; N=24); Arm B) VB-111 in combination with BV (“Unprimed Combination”; Phase 3; N=124); Arm C) BV monotherapy (“Control”; Phase 3; N=120). Contrast enhanced T1-weighted digital subtraction was used to quantify tumor volume at all time points. Baseline tumor volume was prognostic for OS in all treatment groups when controlling for therapy and age (Cox, P< 0.001, HR=1.02). In patients with smaller tumors (< 25mL), the “primed combination” cohort (Arm A) from the phase 2 trial had a significant OS advantage compared to both upfront combination of VB-111 and BV (Arm B; P=0.0094, HR=0.53; median OS = 7 vs. 15mo) as well as BV alone (Arm C; P=0.025, HR=0.58; median OS=8.5 vs. 15mo). Patients with a radiographic response (>65% reduction) had a significant survival difference from non-responders when controlling for age, baseline tumor volume, and treatment arm (P=0.0014, HR=0.58). Responders to VB-111 monotherapy or combination therapy after priming with VB-111 exhibited characteristic, expansive areas of necrosis in areas of initial disease.