bluuebunny/crossref_metadata_2025_split huggingface dataset:
NIMG-08. AN INTEGRATED INFORMATICS MODEL COMBINING CLINICAL FACTORS, RADIOMICS AND A NOVEL CONNECTOMICS FRAMEWORK TO DISTINGUISH PATHOLOGICALLY-PROVEN RADIONECROSIS FROM PROGRESSION IN TREATED BRAIN METASTASES
Authors: Lee Emerson , Cao Linda , Vishwa Parekh , Chen Scott , Redmond Kristin , Peng Luke , Michael Jacobs , Kleinberg Lawrence 
Published: November 2022

Abstract

PURPOSE/OBJECTIVE(S)
To distinguish radionecrosis (RN) from true progression (TP) in brain metastases treated with stereotactic radiosurgery (SRS), we apply machine learning to create a multi-domain model that incorporates clinical factors, multiparametric radiomics(mpRads), and tumor connectomics, a novel MRI-based complex graph theory framework that describes the intricate network of relationships within the tumor and surrounding tissue.

MATERIALS/METHODS
Metastases treated with SRS that had pathologic confirmation of RN vs. TP after imaging progression were included from a single institution. Regions of interest were manually segmented using the single largest diameter of the T1 post-contrast(T1C) lesion plus the corresponding area of T2 FLAIR hyperintensity. We developed an Integrated Radiomics Informatics System (IRIS) based on an isomap support vector machine (IsoSVM) model to classify TP from RN using leave-one-out cross-validation (LOOCV). Class imbalance was resolved using differential misclassification weighting during model training using IRIS. Area under the receiver operating characteristic (AUC-ROC) and AUC-PR (precision recall) analysis were performed.

RESULTS
We analyzed 135 lesions in 110 patients. There were 43 cases (31.9%) of RN and 92 cases (68.1%) of TP. The top-performing connectomics features were degree centrality (increased with RN) and average path length (decreased with RN), suggesting greater “connectivity” and increased similarity in intralesional features between the T1C and FLAIR signal regions in RN cases. The top-performing radiomics feature was multidimensional entropy (increased in TP), demonstrating greater heterogeneity in TP cases. Finally, the top-performing clinical features were prior RT before SRS, histology, and treated lesion size. The LOOCV IsoSVM model successfully classified TP from RN with an AUC-ROC of 0.84 (95% CI: 0.77-0.90) and AUC-PR of 0.90 (95% CI: 0.82-0.95). The F1 score was 0.89.

CONCLUSION
Our novel machine-learning framework was able to efficiently combine features from multiple domains (i.e., radiomics, connectomics, and clinical factors) to distinguish pathologically-proven TP from RN with excellent discrimination.
NIMG-24. LONGITUDINAL MR SPECTROSCOPY TO DETECT PROGRESSION IN PATIENTS WITH LOWER-GRADE GLIOMA IN THE SURVEILLANCE PHASE
Authors: Avalos Lauro , Luks Tracy , Gleason Tyler , Damasceno Pablo , Li Yan , Lupo Janine , Phillips Joanna J , Bush Nancy Ann Oberheim , Taylor Jennie , Chang Susan M , Villanueva-Meyer Javier 
Published: November 2022

Abstract

BACKGROUND
Monitoring lower-grade gliomas (LrGGs) for disease progression is made difficult by the limits of anatomical MRI to distinguish treatment-related tissue changes from tumor progression. MR spectroscopic imaging (MRSI) offers additional metabolic information that can help address these challenges. The goal of this study was to compare longitudinal changes in multiparametric MRI, including diffusion-weighted imaging, perfusion imaging, and 3D MRSI, for LrGG patients who progressed at the final time point and those who remained clinically stable.

METHODS
Forty-one patients with LrGG who were clinically stable were longitudinally assessed for progression. Changes in anatomical, diffusion, perfusion, and MRSI data were acquired and compared between patients who remained clinically stable and those who progressed.

RESULTS
Thirty-one patients remained stable, and 10 patients progressed. Over the study period, progressed patients had a significantly greater increase in normalized choline, choline-to-N-acetylaspartic acid index (CNI), normalized creatine, and creatine-to-N-acetylaspartic acid index (CRNI), than stable patients. CRNI was significantly associated with progression status and WHO type. Progressed astrocytoma patients had greater increases in CRNI than stable astrocytoma patients.

CONCLUSIONS
LrGG patients in surveillance with tumors that progressed had significantly increasing choline and creatine metabolite signals on MRSI, with a trend of increasing T2 FLAIR volumes, compared to LrGG patients who remained stable. These data show that MRSI can be used in conjunction with anatomical imaging studies to gain a clearer picture of LrGG progression, especially in the setting of clinical ambiguity.
NIMG-32. POSTPROGRESSION SURVIVAL AND MRI FEATURES AT PROGRESSION IN MGMT-METHYLATED GLIOBLASTOMA FOLLOWING TEMOZOLOMIDE (TMZ) OR CCNU/TMZ THERAPY - AN ANALYSIS OF THE CETEG/NOA-09-TRIAL
Authors: Zeyen Thomas , Paech Daniel , Weller Johannes , Schäfer Niklas , Tzaridis Theophilos , Duffy Cathrina , Nitsch Louisa , Schneider Matthias , Steinbach Joachim , Hau Peter , Schlegel Uwe , Seidel Clemens , Krex Dietmar , Grauer Oliver , Goldbrunner Roland , Zeiner Pia , Tabatabai Ghazaleh , Galldiks Norbert , Stummer Walter , Hattingen Elke , Glas Martin , Radbruch Alexander , Herrlinger Ulrich , Schaub Christina 
Published: November 2022

Abstract

INTRODUCTION
In the randomized CeTeG/NOA-09 trial, combined CCNU/TMZ was superior to TMZ therapy regarding overall survival (OS) in newly diagnosed patients with MGMT-methylated glioblastoma. Using modified RANO criteria, however, progression-free survival (PFS) and pseudoprogression rates were similar in both arms. Exploring the hypothesis of undetected pseudoprogressions being accountable for this discrepancy, we analyzed patterns of postprogression survival (PPS) and MRI features at RANO-defined progression.

METHODS
86 CeTeG/NOA-09 patients with progression (modified RANO criteria) and MRI evaluable for standardized T1 and FLAIR volumetry at baseline and progression were included. Patients were further subdivided to short PPS (&lt; 24 months) or long PPS (&gt; 24 months) and a PPS/PFS ratio was calculated.

RESULTS
In the CCNU/TMZ arm, long PPS patients (n=10) tended to a shorter PFS (median 7.3 months) than short PPS patients in the same arm (n=33, 14 months, p=0.089, logrank test) and long PPS patients in the TMZ arm (n=9, 12.7 months, p=0.21). The mean PPS/PFS ratio in the long PPS group was markedly higher in the CCNU/TMZ arm (5.8) compared to the TMZ arm (3.3, p=0.043, Mann-Whitney test). Patients with long PPS of the CCNU/TMZ arm showed a nonsignificant tendency to a stronger volumetric increase in T1 enhancement (mean delta 6184,86 vs. 697.5 mm³) and FLAIR–T1-enhancement (mean delta 42671 vs 16860 mm³) at progression as compared to long PPS patients of the TMZ arm.

CONCLUSION
Combining a substantially increased PPS/PFS ratio (long OS despite particularly short PFS according to RANO) with indications for increased contrast enhancement and FLAIR volume at progression, the patients with long PPS in the CCNU/TMZ arm appear to differ from those in the TMZ arm. These observations support the hypothesis that this group (~25% of CCNU/TMZ-treated patients) contained patients with pseudoprogression undetected by modified RANO criteria.
NIMG-34. QUANTIFICATION OF GLYCOLYTIC FLUX REDUCTION IN RECURRENT GLIOBLASTOMA AFTER EGFR INHIBITION USING MOLECULAR MR-PET
Authors: Ellingson Benjamin , Nathanson David , Yao Jingwen , Hagiwara Akifumi , Raymond Catalina , Salamon Noriko , Pope Whitney , Lai Albert , Nghiemphu Phioanh L , Cloughesy Timothy 
Published: November 2022

Abstract
In recently published work, we demonstrated that acute inhibition of the EGFR – the most frequently altered oncogene in GBM – can rapidly reduce glycolysis in a subset of GBM. To quantify this effect, we propose a new combination metabolic MR-PET imaging biomarker that combines 18F-FDG PET, DSC perfusion MRI, diffusion MRI, and pH- and oxygen-sensitive amine CEST-SAGE-EPI. Specifically, this “glycolytic index” or GI, can be defined as elevated glucose uptake (18F-FDG standard uptake value), elevated tumor acidity (MTRasym@3ppm), and lower oxygen utilization (relative cerebral metabolic rate of oxygen, rCMRO2, defined as R2’ x rCBF/rCBV from oxygen-sensitive SAGE-EPI and DSC perfusion), normalized to cell density (using ADC from diffusion MRI). In the current study, we explored the use of Tagrisso® (Osimertinib or AZD9291), which has very high brain to plasma ratios (&gt; 1) and has proven effective in CNS metastasis of EGFR mutant lung cancer, as a potential treatment for EGFR amplified recurrent GBM. We have conducted a clinical trial (NCT03732352) to determine whether we observe similar metabolic imaging changes in EGFR mutated or amplified recurrent glioblastoma patients after treatment with osimertinib. Consistent with prior in vitro and in vivo results, treated patients exhibited a reduced glycolytic flux as indicated by reduction in 18F-FDG PET uptake (-3% change in SUV), tumor acidity (-19% change in MTRasym@3ppm) on pH-weighted CEST MRI, and glycolytic index (GI) (-25% change) in EGFR amplified recurrent GBM within 24 hours of treatment. Preliminary data suggests early change in GI correlates with and predicts both PFS (Pearson correlation, R2=0.3463, P=0.0441; Log-rank, P=0.0467) and OS (R2=0.6368, P=0.0019; Log-rank, P=0.0192). These preliminary data establish the scientific premise that a “glycolytic index” created using 18F-FDG PET, DSC perfusion, diffusion MRI, and pH- and oxygen-weighted amine CEST-SAGE-EPI may be an important tool for quantifying and visualizing glycolytic flux in GBM.
NIMG-50. ASSOCIATION BETWEEN SALINITY, ACIDITY, DIFFUSIVITY, AND HYPOXIA IN HUMAN GLIOMAS USING MULTI-NUCLEAR MRI
Authors: Cho Nicholas S , Thakuria Shruti , Sanvito Francesco , Hagiwara Akifumi , Wang Chencai , Nagaraj Raksha , Lu Jianwen , Oshima Sonoko , Raymond Catalina , Cloughesy Timothy , Liau Linda M , Everson Richard G , Nghiemphu Phioanh L , Lai Albert , Ellingson Benjamin 
Published: November 2022

Abstract

INTRODUCTION
Sodium MRI has been recently explored in brain tumors to potentially reveal complementary information with proton MRI about the tumor microenvironment. However, there remains limited investigation combining sodium and quantitative proton MRI techniques. This pilot study explored the associations of sodium MRI with diffusion-, pH-, and hypoxia-weighted MRI biomarkers in gliomas.

METHODS
Eleven patients with gliomas (n=8 IDH-wild-type; n=3 IDH-mutant) who obtained sodium, anatomical, diffusion-, pH-, and hypoxia-weighted MRI were studied. All images were obtained on a 3T Siemens Prisma with a dedicated multi-nuclear head coil. Regions-of-interest were segmented on the contrast-enhancing (CE) (n=10), FLAIR (n=11), and necrotic regions (n=9). Sodium values were normalized to the mean values of the eyes. Median sodium, apparent diffusion coefficient (ADC), ADC(L) from bimodal histogram analyses, MTRasym (acidity), and R2’ (hypoxia) values were obtained.

RESULTS
There was increased sodium in necrosis compared to FLAIR regions (mean difference=0.24; P/i&gt;&lt; 0.05) and compared to CE regions (mean difference=0.17; P/i&gt;=0.07). There were significant positive correlations between sodium and ADC in CE (R=0.94; P/i&gt;&lt; 0.0001) and FLAIR regions (ρ=0.77; P/i&gt;&lt; 0.01), but not in necrosis (R=0.44; P/i&gt;=0.24). There was also a significant positive correlation with ADC(L) in CE regions (R=0.90; P&lt; 0.001) but not in FLAIR regions (ρ=0.50; P/i&gt;=0.12). Furthermore, there was a significant positive correlation between sodium and MTRasym in necrosis (R=0.74; P/i&gt;&lt; 0.05) and a positive trend in CE regions (R=0.55; P=0.10). There was also a negative trend between sodium and R2’ in FLAIR regions (ρ=-0.58; P/i&gt;=0.11).

CONCLUSIONS
Because ADC and ADC(L) are inversely related to cell density, increased sodium in gliomas may reflect increased extracellular space stemming from lower cell density, as sodium concentration is higher extracellularly. Positive associations between sodium and acidity as well as negative associations between sodium and hypoxia may reflect alterations in coupled sodium-pH and sodium-hypoxia homeostasis in gliomas.
NIMG-74. RADIOIMMUNOMIC SIGNATURES IN PEDIATRIC LOW-GRADE GLIOMA BASED ON MULTIPARAMETRIC MRI SCANS
Authors: Kazerooni Anahita Fathi , Kraya Adam A , Kim Meen Chul , Khalili Nastaran , Arif Sherjeel , Jin Run , Rathi Komal , Familiar Ariana , Madhogarhia Rachel , Haldar Debanjan , Bagheri Sina , Anderson Hannah , Shaikh Ibraheem Salman , Haldar Shuvanjan , Ware Jeffrey B , Vossough Arastoo , Storm Philip B , Resnick Adam C , Davatzikos Christos , Nabavizadeh Ali 
Published: November 2022

Abstract
Understanding the immune microenvironment in pediatric low-grade glioma (pLGG) patients may help in identification of the patients who benefit from anti-tumor immunotherapies. However, surgical resection is not feasible for many pLGG tumors in certain anatomical locations. Therefore, developing non-invasive tools that characterize the tumor microenvironment prior to therapeutic interventions could contribute to stratification and enrollment of the patients into relevant clinical trials. In this work, we derived radiomic signatures of immune profiles (radioimmunomics) based on machine learning (ML) analysis of readily available conventional MRI scans. Transcriptomic data for a cohort of 197 subjects was retrospectively collected from Open Pediatric Brain Tumor Atlas (OpenPBTA). The patients were categorized into three groups (Group1-3) based on their immunological profiles using consensus clustering algorithm. This analysis revealed greater immune cell infiltration in non-BRAF mutated pLGGs. Group1 showed more enrichment in M1 macrophages, and microenvironment and immune scores compared to Group2 and Group3. Elevated tumor inflammation score (TIS), as a predictor of clinical response to anti-PD-1 blockade, was observed in Group1 compared to Group2 (p= 1.4e-7) and Group3 (p= 0.0054). Radiomic features, including volumetric, morphologic, histogram, and texture descriptors, were extracted from the segmented tumor regions on multiparametric MRI (mpMRI) scans of 71 (of 197) patients. Multivariate ML models were trained to predict the three immunological groups based on radiomic features using cross-validated random forest classifier along with recursive feature elimination, which yielded AUC of 0.72 for this multi-class classification problem. Our findings indicate the presence of distinct immunological groups in pLGG tumors, with possibly more favorable response to immunotherapies in Group1 tumors. Furthermore, we developed radioimmunomic signatures based on pre-operative conventional mpMRI that can potentially stratify the patients based on their immune tumor microenvironment. Based on these initial promising results, we are exploring additional features to increase the accuracy of radioimmunomics model.
NIMG-82. RADIOGENOMIC SIGNATURES OF KEY DRIVER GENES IN GBM REVEAL MOLECULAR HETEROGENEITY OF THE TUMOR MICROENVIRONMENT LINKED TO SPATIAL DISTRIBUTION: IMPACT ON THE TRAJECTORY OF GLIOMA EVOLUTION
Authors: Kazerooni Anahita Fathi , Akbari Hamed , Toorens Erik , Grigoriadis Dimitris , Hu Xiaoju , Sako Chiharu , Mamourian Elizabeth , Bagley Stephen , Binder Zev A , Lustig Robert , Brem Steven , O'Rourke Donald , Ganguly Tapan , De Subhajyoti , Hatzigeorgiou Artemis , Bakas Spyridon , Nasrallah MacLean , Davatzikos Christos 
Published: November 2022

Abstract
Somatic genomic alterations acquired during GBM growth enhance adaptation of tumor cells to their microenvironment and give rise to molecular heterogeneity. Radiogenomics could facilitate exploration of the underlying pathobiology of tumor growth in specific microenvironments and thereby, promote precision medicine for the patients. We derived radiogenomic signatures of key driver genes and evaluated molecular compositions of tumor groups with predisposition to specific brain regions. Pre-operative multiparametric conventional MRI scans of 357 IDH-wildtype GBM patients with available targeted NGS data were jointly segmented and registered into a common template. We constructed spatial distribution atlases for tumors harboring mutations in driver genes and identified four distinct groups of tumor locations with predilection to the left frontal cingulate region (Group1), right temporal (Group2), right parietal (Group3), and occipital pole (Group4). Evaluation of the differences in molecular features of the tumor groups included: (1) exploring similarities of genomic profiles across all four groups by evaluating cosine similarity metric (CSM) between mutational signatures; (2) quantification of molecular heterogeneity based on Mutant Allele Tumor Heterogeneity (MATH) scores; and (3) inference of the evolutionary trajectories. Groups 1 and 4 were the most different, and Groups 2 and 3 were the most similar tumors, molecularly. The mutational signatures between Groups 1 and 4 revealed a CSM of 0.35. Group1 showed significantly lower MATH score (less heterogeneity) compared to Group4 (p&lt; 0.05). Evaluation of evolutionary patterns suggested NF1 mutation as an early event in Group1, without subsequent gain of function or mutation in EGFR. In contrast, in Group4, EGFR mutations were early events triggering PTEN mutations later in the evolutionary trajectory. Radiogenomic signatures revealed distinct molecular underpinnings for the tumors with predilection towards specific brain regions that may suggest existence of different tumor microenvironments in different brain regions that cause intra- and inter-patient heterogeneity in the molecular tumor composition.
NIMG-94. A RARE CASE OF INFRATENTORIAL CEREBELLAR VERMIS MULTINODULAR AND VACUOLATING NEURONAL TUMOR
Authors: Lomax Jerica , Kuoy Edward , Kong Xiao-Tang 
Published: November 2022

Abstract

INTRODUCTION
Multinodular and vacuolating neuronal tumor (MVNT) is a rare entity that was first recognized by the World Health Organization Classification of Tumors of the Central Nervous System in 2016. The majority of MVNT cases reported were supratentorial in location and only a small subset of cases included infratentorial involvement. In the supratentorial, MVNT is often a nidus for seizure and surgical resection is for seizure control. Infratentorial MVNT lesions are typically not or only mildly symptomatic; thus, surgical intervention may not be warranted. Here we describe the clinical course of a patient who was found to have a cerebellar vermis lesion that consistent with infratentorial MVNT.

CASE REPORT
A 41-year-old man sought care due to new onset headache. A brain magnetic resonance imaging (MRI) exam revealed a coalescence of bubble-like cystic lesions in the cerebellar vermis that were T1 hypointense, T2/Flair hyperintense without contrast enhancement. Initially, the lesions were attributed to neurocysticercosis but work-up was not supporting the diagnosis. MRA of head and neck found no cerebral stenosis or vascular malformation. The unique MRI features support infratentorial MVNT diagnosis. Disease course, work-up and MRI features are not consistent with low grade glioma, subacute ischemia infarct, demyelinating disease or chronic fungal or parasite infection. Brain MRI surveillance has completed every 6 months; no interval change to the cerebellar vermis lesions has been seen over past two years. Clinically, the patient has been doing well and his headache has resolved.

DISCUSSION
MRI features of MVNT are predominantly mixed solid and cystic, bubble-like, T2/Flair-hyperintense, T1 hypointense lesions in the deep cortical region and superficial white matter without contrast enhancement. This case demonstrates that although no specific criteria to diagnose MVNT, neurologists and neuro-oncologists should be aware of the distinguishing radiographic features, which can help patients avoid unnecessary testing and potentially harmful interventions.
NIMG-97. A FULLY AUTOMATED MRI-BASED DEEP-LEARNING ALGORITHM FOR CLASSIFYING GERMINOMAS AND NONGERMINOMATOUS GERM CELL TUMORS
Authors: Li Yanong , Qiu Xiaoguang 
Published: November 2022

Abstract
Intra-cranial germ cell tumors (iGCTs) are classified into two pathological subtypes Germinomas (GEs) and nongerminomatous germ cell tumors (NGGCTs). Accurate preoperative determination of iGCT subtypes is essential to guide clinical decision making and prognosis assessment. This study aims to develop a deep-learning algorithm to automatically segment iGCTs and classify subtypes using preoperative T2-weighted (T2W) images. Brain MR imaging and corresponding pathologic information were retrospectively obtained from 594 subjects including 269 GEs and 325 NGGCTs from Beijing Tiantan Hospital between January 1, 2008, and October 31, 2020, and subdivided into training (n=416) and test (n=178) sets for iGCTs segmentation, and classification using 3D nnU-Net based on T2W images. An internal validation cohort (including 56 GEs and 17 NGGCTs) and two external validation cohorts (Center 1 including 13 GEs and 12 NGGCTs；Center 2 including 17 GEs and 12 NGGCTs) were prospectively designed as an independent sets for testing the iGCT-net. Dice scores were computed to assess tumor segmentation. Accuracy and area under the curve (AUC) were calculated to assess the GEs and NGGCTs classification. Additionally, sensitivity analysis of different tumor location (suprasellar, pineal and basal ganglia regions) was performed to access the classification accuracy. The iGCT-net for tumor segmentation achieved a mean dice score of 0.80 in all cohorts. For tumor classification, the iGCT-net achieved the mean accuracy of 90.96% of all cohorts, which was superior to that using demographics and morphologic features (mean = 67.50%, p&lt; 0.01). For different tumor location (suprasellar region, pineal region, and basal ganglia region), the iGCT-net showed an mean accuracy of 87.94%, 89.38% and 65.74% in test set, internal validation set and external validation cohorts. A fully automatic deep learning algorithm to segment iGCT and discriminate GEs and NGGCTs with high accuracy based on only T2W images from a large dataset is successfully developed.
NIMG-100. THE MEDIAN NERVE STIMULATION INDUCES LONG LATENCY GAMMA MODULATIONS IN THE PRIMARY SOMATOSENSORY CORTEX, WHICH DIFFERENTIATES THE CONSCIOUS STATE
Authors: Asman Priscella , Pellizzer Giuseppe , Sudhakar Tummala , Bastos Dhiego , Prabhu Sujit , Ince Nuri 
Published: November 2022

Abstract

OBJECTIVE
While the intraoperative assessment of the short-latency somatosensory evoked potentials (SSEPs) phase reversal in electrocorticogram (ECoG) is routinely used to locate the central sulcus (CS), its spatial-spectral patterns in the primary sensorimotor cortex and the relation to consciousness is not well characterized. Our goal was to evaluate the functional utility of using median nerve stimulation-induced ECoG sub-band modulations in pre-and post-CS to differentiate between anesthetized and awake states. Method: SSEPs were recorded from the sensorimotor cortex with ECoG during routine intraoperative cortical mapping of 8 patients in the anesthetized and awake states. We conducted a time-frequency analysis on the SSEP trace in each state to extract the spectral modulations up to 900Hz and contrasted their intensity in M1 and S1 to discern awake from anesthetized states.

RESULTS
We observed late gamma activity ranging from 60-250Hz, starting approximately 50ms after stimulation onset and extending up to 250ms. The late gamma activity was suppressed in the anesthetized state in both M1 (p&lt; 0.01) and S1 (p=0.0369). Whiles in the awake state, the late gamma power increased significantly with respect to baseline both in M1 (p=0.0180) and S1 (p&lt; 0.01). The difference in late gamma power between the anesthetized and the awake state was highly significant for M1 (p&lt; 0.01) and for S1 (p&lt; 0.01).

CONCLUSION
The results show that besides CS delineation, SSEPs long latency gamma modulations can serve as an additional biomarker to monitor the level of consciousness in neurosurgical practice.