bluuebunny/crossref_metadata_2025 huggingface dataset:
PATH-09. THE IMPACT OF MISMATCH REPAIR DEFICIENCY ON GLIOMAS IN CHILDREN, ADOLESCENTS, AND YOUNG ADULTS; A MULTI-CENTRIC, COLLABORATIVE STUDY LED BY THE IRRDC AND GLIOMA TASKFORCE
Authors: Negm Logine , Chung Jiil , Nobre Liana Figueiredo , Bennett Julie , Fernandez Nicholas , Komosa Martin , Zhang Cindy , Ku Michelle , Johnson Monique , Bianchi Vanessa , Aronson Melyssa , Stengs Lucie , Lim-Fat Mary-Jane , Keith Julia , Tsang Derek , Gao Andrew , Munoz David , Nguyen Lananh , Das Sunit , Levine Adrian , Das Anirban , Resnick Adam , Robinson Giles W , Nichols Kim , Wheeler David A , Hawkins Cynthia , Tabori Uri
Published: November 2023

BACKGROUND

Primary mismatch repair deficiency (pMMRD) is a pan-cancer mechanism caused by somatic mutations or inherited as part of Lynch Syndrome (LS) or constitutional mismatch repair deficiency (CMMRD). PMMRD results in universal hypermutation and microsatellite instability leading to chemoradiation resistance but sensitivity to immunotherapy. The prevalence of pMMRD in gliomas of children, adolescents, and young adults (CAYA), and the impact of germline inheritance is unknown.

METHODS

We harnessed functional genomic tools across population-based (Toronto), and multiple institutional (SJ, CBTN) cancer databases (n=1276) to determine the prevalence, subgroups, and impact of germline mutations in pMMRD gliomas.

RESULTS

Data from Toronto, SJ and CBTN reveals prevalence of 10%, 5% and 5% in pediatric high-grade gliomas (HGG). Molecularly, pMMRD is absent in gliomas harboring pediatric-type fusions, BRAF-V600E, and histone mutations, but enriched in HGG harboring IDH and TP53 mutations. In AYA (n=660), pMMRD was detected in 5% of IDH-WT and IDH-mutant high-grade astrocytomas, but notably absent in all oligodendrogliomas and other low-grade gliomas. Across this entire CAYA dataset, all except one pMMRD gliomas harbored germline MMR mutations (97%). Strikingly, LS predominated over CMMRD with significant difference in age of glioma onset (LS: 29-years versus CMMRD: 11-years; p< 0.001, IRRDC dataset). Survival analysis (Kaplan-Meier) confirmed the poor overall survival (OS) for pMMRD and other pediatric subtypes of HGG (3-year OS < 25%). In contrast, IDH-mutant pMMRD HGG have significantly worse OS than IDH-mutant non-pMMRD counterparts. Remarkably, immunotherapy significantly improves survival not only in children, but also for AYA patients with refractory pMMRD HGG (3-year OS > 50%).

CONCLUSION

This large study demonstrates that pMMRD drives a significant proportion of HGG across CAYA with an alarming impact of germline predisposition. Specifically, unrecognized AYA LS patients with MMRD HGG. These findings support universal screening for MMRD in HGG to identify patients for surveillance and immunotherapy.
PATH-32. COMPARISON OF CLINICAL, RADIOGRAPHIC AND TUMOR GENOMIC ALTERATIONS BETWEEN CLASSIC AND MOLECULAR GLIOBLASTOMA (IDH WILDTYPE)
Authors: Lachance Daniel , Decker Paul , Kollmeyer Thomas , Praska Corinne , Kosel Matthew , Odukoya Lateef , Ida Cristine , Drucker Kristen , Panda Arijit , Conte Gian Marco , Moassefi Mana , Tobin W Oliver , Erickson Bradley , Galanis Evanthia , Eckel-Passow Jeanette , Jenkins Robert
Published: November 2023

INTRODUCTION

Prior to 2021, (classic) glioblastoma (GBM) required absence of IDH mutation and histologic features of hypercellularity, nuclear atypia, microvascular proliferation (MVP), and necrosis. Absence of histologic features can be a result of undersampling, with molecular, radiologic, and clinical features consistent with GBM. Accordingly, WHO 2021 defined molecular glioblastoma as diffuse glioma IDHwt, H3wt, with one or more of MVP, necrosis, TERT promoter mutation, EGFR gene amplification (EGFRamp), and/or +7/−10. We hypothesized that there is clinical and radiographic heterogeneity among tumors defined as molecular GBM.

METHODS

We identified 121 patients that met the criteria for molecular GBM. 121 Classic GBM, defined as IDHwt with hypercellularity, MVP or necrosis, were matched to molecular GBM cases by age, sex, and diagnosis date. All cases were reviewed for relevant histologic features and molecular features. Examined clinical variables included: first symptom, time from first symptom to date of pathological diagnosis, date of first MRI, tumor location, radiographic features of enhancement, diffusion or mass effect, time to progression and overall survival. Clinical, radiologic, and molecular features were compared between classic and molecular GBM.

RESULTS

Currently,160 cases have been reviewed. Preliminary results show that there is a longer time from first symptom to diagnosis for molecular GBM. Molecular GBM is significantly more likely to be discovered coincidentally, and without enhancement or radiographic necrosis. Classic GBM is significantly more likely to present with focal neurologic deficit as first symptom, regional mass effect on index imaging and have monosomy 10.

CONCLUSION

While pathologic undersampling accounts for a significant proportion of molecular GBM, our data suggest that there are significant clinical, radiographic, and outcome differences between classical and molecular GBM. Final analysis of the entire cohort will help better define this clinical spectrum.
PATH-44. INTRA-OPERATIVE ANALYSES OF GENETIC ALTERATIONS IN THE CENTRAL NERVOUS SYSTEM TUMORS USING RAPID QUANTITATIVE PCR DEVICE
Authors: Ohka Fumiharu , Maeda Sachi , Yamaguchi Junya , Shimizu Hiroki , Motomura Kazuya , Takeuchi Kazuhito , Nagata Yuichi , Nishikawa Tomohide , Kibe Yuji , Takido Yuhei , Saito Ryuta
Published: November 2023

Recent comprehensive molecular analyses of central nervous system (CNS) tumors identified several diagnostic or prognostic markers. IDH mutation, TERT promoter (pTERT) mutation and CDKN2A homozygous deletion in adult-type diffuse gliomas, BRAF p.V600E mutation in circumscribed astrocytic gliomas, histone H3 gene mutations in pediatric-type diffuse high-grade gliomas or MYD88 mutation in primary CNS lymphoma (PCNSL) are quite important markers. Intra-operative identification of these molecular alterations could be effective for decision-making of tumor removal strategy. In this study, we established intra-operative gene analysis method using rapid quantitative PCR device, GeneSoC, by which we could obtain genotype of these important genes for 20 minutes in an operating room. Using GeneSoC, we could perform 50 cycles of quantitative PCR for approximately 12 minutes. We established rapid gene analyses of mutations of IDH1 p.R132H, pTERT C225T, pTERT C250T, H3 K27M, BRAF p.V600E and homozygous deletion of CDKN2A for diffuse gliomas and circumscribed astrocytic tumors and MYD88 p.L265P for PCNSL. For elution of DNA, we incubated at least 1mg of tumor tissue at 95°for 5 minutes. Combined this boiling method with GeneSoC, we could obtain those genetic alterations for 20 minutes after collection of tumor tissue. For 42 glioma cases and 10 PCNSL cases, we could obtain accurate genetic alterations (IDH1 p.R132H, pTERT C225T, pTERT C250T for gliomas or MYD88 p.L265P for PCNSL) in all cases, using this method. For detection of CDKN2A homozygous deletion, sensitivity and specificity are 100% and 83% in analyzed 50 cases, respectively. In this study, we could obtain the genotype of important molecular markers intra-operatively, not only during tumor removal but even during tumor biopsy, using GeneSoC device. This rapid genetic analysis might be effective not only for intra-operative diagnosis but also for detection of boundary between tumor and normal tissue.
NIMG-12. SPATIALLY MAPPING TREATMENT-EFFECT IN RECURRENT GLIOMA WITH PHYSIOLOGIC MRI AND DEEP LEARNING
Authors: Ellison Jacob , Tran Nate , Hanna Rany , Phillips Joanna , Shai Anny , Nair Devika , Molinaro Annette , Pedoia Valentina , Li Yan , Luks Tracy , Villanueva-Meyer Javier , Berger Mitchel , Hervey-Jumper Shawn , Aghi Manish , Chang Susan , Lupo Janine
Published: November 2023

INTRODUCTION

Discriminating between glioma tumor recurrence (rTumor) and treatment-induced effects (TxE) from chemo and radiotherapy using MRI is an ongoing challenge in neuro-oncology. Although deep learning has been used to characterize suspicious lesions, these models typically do not account for lesions that are comprised of mixtures of rTumor and TxE components. We hypothesize that using an approach that includes using tissue samples with known location on MRI, incorporating perfusion-weighted and diffusion-weighted with anatomical MRI, self-supervised pretraining, and a novel ensembling strategy will improve performance and attain spatial maps of rTumor and TxE for determining subsequent treatment.

METHODS

Using 218 pathology confirmed tissue samples with coordinates on multi-parametric MRI from 111 patients with suspected tumor progression, we developed a deep learning approach to spatially map intratumoral regions of rTumor and TxE. Our model leveraged 10mm isotropic cubes centered on the tissue sample coordinates that includes Diffusion-Weighted and Dynamic Susceptibility-Contrast Perfusion MRI and large amounts of pathologically unlabeled data from the lesion in self-supervised pretraining. The multiple networks of the ensemble were generated through repeated constrained cross validation (RC-CV) which enabled unique repetitions of training with more variation in class proportions.

RESULTS

Our best classifier performed with a RC-CV/test AUROC of 0.85/0.81 and was able to generate maps of tumor probability as well as ensenble variance and uncertainty. Ensemble variance was significantly higher in prediction failures of rTumor (P=.006) and epistemic uncertainty was significantly higher (P=.002) in prediction failures of TxE in training. Test Performance dropped by 14.7% when removing self-supervised pretraining, 21.3% when removing physiological imaging contrasts, and 1.2% when ensembling across standard 4-fold CV.

CONCLUSION

The AUROC of .81 supports the feasibility of discriminating between TxE and rTumor within a single lesion non-invasively. Physiologic MRI, pretraining on pathology unlabeled data, and ensembling networks, improve performance and help characterize model failures.
NIMG-14. AUTOPSY-BASED RADIO-PATHOMIC MAPS REVEAL DEMOGRAPHIC FACTORS IMPACT THE PRESENCE OF TUMOR OUTSIDE CONTRAST ENHANCEMENT IN GLIOMA PATIENTS
Authors: Bobholz Samuel , Lowman Allison , Duenweg Savannah , Winiarz Aleksandra , Stebbins Margaret , Flatley Michael , Nath Biprojit , Kyereme Fitzgerald , Connelly Jennifer , Coss Dylan , Krucoff Max , Banerjee Anjishnu , LaViolette Peter
Published: November 2023

Gliomas are vastly heterogenous tumors with wide-ranging pathological signatures; as such, there is a pressing need to understand how individualized factors affect tumor growth patterns to develop treatment plans and improve prognosis. This study used autopsy-based radio-pathomic maps of tumor probability to test the hypothesis that differences in patient sex and age impact the presence of non-enhancing tumor. This study used pre-surgical imaging and demographic data from 501 glioma patients from the UCSF-PDGM dataset. Specifically, T1, T1C, FLAIR, and ADC images were used to generate maps of tumor probability using a previously validated model. This model used autopsy tissue aligned to imaging as ground truth to develop models sensitive to identifying areas of non-enhancing tumor outside of traditional imaging signatures. Thresholded maps were used to delineate areas of tumor presence, and the non-enhancing tumor volume was computed for each patient as the predicted high probability tumor volume within non-enhancing FLAIR hyperintensity. A general linear model was then fit to assess the effect of age and sex on non-enhancing tumor volumes, using tumor grade and contrast-enhancing volume as covariates. Male patients trended towards greater non-enhancing tumor volumes compared to female patients (B=5676.6, p=0.053). Older patients were also found to have less non-enhancing tumor volume compared to younger patients (B=-261.1, p=0.015). These results suggest that demographic characteristics influence the progression of tumor beyond the angiogenic tumor mass and may therefore influence treatment efficacy and prognoses. Future research is essential to understanding how these sex differences relate to the worse prognosis historically observed for males with glioma, and how the reduced presence of non-enhancing tumor in older patients relates to a reduction in plasticity-induced tumor propagation.
NIMG-17. TOWARDS IMAGE - BASED PERSONALIZATION OF GLIOBLASTOMA THERAPY: A COMPREHENSIVE VALIDATION STUDY OF A NOVEL, DEEP LEARNING - DRIVEN TUMOR GROWTH MODEL FOR INDIVIDUALIZED RADIOTHERAPY
Authors: Metz Marie-Christin , Griessmair Michael , Ezhov Ivan , Peeken Jan , Weidner Jonas , Menze Bjoern , Wiestler Benedikt
Published: November 2023

BACKGROUND

The diffuse growth pattern of glioblastoma is one of the main challenges for accurate treatment planning. Computational tumor growth modeling has emerged as a promising tool to guide personalized therapy by estimating the tumor cell density in the whole brain. Here, we performed biological and clinical validation of a novel growth model, aiming to close the gap between the experimental state and clinical implementation.

METHODS

124 patients from The Cancer Genome Archive (TCGA) and 397 patients from the UCSF Glioma Dataset were assessed for significant correlations between clinical data, genetic pathway activation maps (generated with PARADIGM; TCGA only), and infiltration (Dw) as well as proliferation (ρ) parameters stemming from a Fisher-Kolmogorov growth model that is adjusted to the patient’s anatomy using deep learning. To further evaluate clinical potential, we performed the same growth modeling on preoperative MRI data from 30 patients of our institution and compared model-derived tumor volumes (that serve as alternative clinical target volumes) and recurrence coverage with standard radiotherapy plans.

RESULTS

The parameter ratio Dw/ρ (p < 0.05 in TCGA) as well as the simulated tumor volume (0.5 tumor cell density) (p < 0.05 in TCGA/UCSF) were significantly inversely correlated with overall survival. We found a significant correlation between 11 proliferation pathways and the estimated proliferation parameter ρ, proving its biological plausibility. Depending on the cutoff value for tumor cell density, we observed significant improvement of recurrence coverage without significantly increased total radiation volume utilizing model-derived target volumes instead of standard radiation plans. More precisely, a cutoff value of 0.5 tumor cell density yielded the best results here.

CONCLUSIONS

Identifying a significant correlation between computed growth parameters, and clinical and biological data, we highlight the potential of tumor growth modeling for individualized therapy of glioblastoma. This might improve accuracy of radiation planning in the near future.
NIMG-39. BENCHMARKING MULTI-LABEL PREDICTION OF TARGET GENE MUTATION STATUS IN GLIOBLASTOMA USING RADIOGENOMICS AND MULTI-PARAMETRIC MR IMAGING
Authors: Yu Fanyang , Guo Jun , Kazerooni Anahita Fathi , Akbari Hamed , Toorens Erik , Sako Chiharu , Mamourian Elizabeth , Bagley Stephen J , Binder Zev , Lustig Robert A , Brem Steven , O'Rourke Donald M , Ganguly Tapan , Bakas Spyridon , Nasrallah MacLean P , Chaudhari Pratik , Davatzikos Christos
Published: November 2023

PURPOSE

In vivo imaging-based prediction of gene mutation status can significantly contribute to the diagnosis and treatment of glioblastoma. Radiogenomics provides a non-invasive approach to capturing the phenotypical characteristics of molecular alterations. We build machine learning (ML) models on radiogenomics and MR imaging data for benchmarking the prediction of multiple target genes in a single institution dataset.

METHODS

Multi-parametric MRI scans (T1, T1-Gd, T2, T2-FLAIR, DSC, DTI) of 286 individuals with glioblastoma were used to extract radiomics features, including histograms, morphological and textural descriptors. Genetic markers were obtained through a targeted next generation sequencing panel. We built ML models to predict mutation status in two settings: (a) 4 frequently-occurring mutations (EGFR, PTEN, NF1, TP53), (b) 13 mutations including some that are infrequent (PDGFRA, MET, FGFR2, PIK3CA, PIK3R1, BRAF, MDM4, CDKN2A). The models include k-nearest neighbor classifiers, fully-connected neural networks w/o dimensionality reduction trained on radiomics data, convolutional (CNN) and self-attention-based (ViT) networks trained on MR imaging data. All models were trained with 5-fold cross validation on discovery cohort (n=257) and tested on replication cohort (n=29).

RESULTS

Multi-label prediction models achieved highest accuracies of 75.9% / 88.6% for 4 / 13 mutations using radiomics features. Models trained with radiomics features have a marginally better average F1 score than CNNs and ViTs trained on MR imaging data (by 4.1% / 4.6% for 4 / 13 mutations).

CONCLUSION

We had modest success in finding highly distinct MR signatures of multiple target mutations in glioblastoma using multi-label ML methods, presumably because of the small sample size and the molecular, the spatial heterogeneity of the tumor, and the difficulty of simultaneously learning multiple imaging signatures. This highlights the importance of pooling and harmonizing radiogenomics data from multiple institutions to increase the sample size, and of incorporating biological domain knowledge into ML models.
NIMG-52. CORRELATION OF BIDIMENSIONAL AND VOLUMETRIC TUMOR SIZING IN NEWLY DIAGNOSED AND RECURRENT GLIOBLASTOMA
Authors: Kim John , Nelson Thomas , Youssef Gilbert , Rahman Rifaquat , Arnaout Omar , Bi Wenya Linda , Cagney Daniel , Chang Yuh-Shin , DeSalvo Matthew , Flood Thomas , Gerstner Elizabeth , Castro Luis Nicolas Gonzalez , Guenette Jeffrey , Kim Albert , Lee Eudocia , McFaline-Figueroa Jose Ricardo , Potter Christopher , Reardon David , Wen Patrick , Huang Raymond Y
Published: November 2023

BACKGROUND

Glioblastoma (GBM) is the most common malignant primary nervous system tumor and remains incurable with a poor prognosis despite current therapy. The standard for monitoring response to treatment, as defined by the Response Assessment in Neuro-Oncology (RANO) criteria, relies on a bidimensional (2D) measurement product of T1-gadolinium enhancing disease. However, due to the variability of bidimensional tumor characterization, there is considerable interest in volumetric segmentation to assess tumor burden, which could be implemented using machine learning models offering workflow automatization.

METHODS

In this study, we evaluate a commercially available automated tumor segmentation tool and correlate its volumetric output to the manual assessment of bidimensional 2D enhancing tumor burden by experts. MRI examinations during systemic treatment for two retrospective cohorts of patients with either newly diagnosed (nGBM) or recurrent GBM (rGBM) were assessed. The 2D diameter product in cm^2 of enhancing tumor was determined by blinded readers and volumetric segmentations in cm^3 were automatically generated. Spearman's correlation between the manual 2D and automated volume measurements was calculated for each cohort.

RESULTS

315 patients with nGBM, and 482 with rGBM were evaluated, comprising 3073 total brain MRIs in the nGBM cohort and 2439 MRIs in the rGBM cohort. Spearman's correlation between the manual 2D and automated volumetric measurements was 0.7463 (0.730, 0.762) in the nGBM cohort and 0.8598 (0.849, 0.870) in the rGBM cohort.

CONCLUSION

Automated segmentation tools have the potential to revolutionize radiology workflows and increase sensitivity to subtle changes on imaging. However, the differential performance of this volumetric assessment confirms the need for further refinement and customization of such automated tools to account for tumor- and patient-specific factors.
NIMG-56. GENERATIVE ADVERSARIAL NETWORKS FOR BRAIN MRI SYNTHESIS: IMPACT OF TRAINING SET SIZE ON CLINICAL APPLICATIONS
Authors: Zoghby Marc , Erickson Bradley , Conte Gian Marco
Published: November 2023

Incomplete MRI exams reduce the possibility of applying AI models. We previously trained two generative adversarial networks (GANs) on 135 subjects from the BraTS-2017 dataset to generate T1 from post-contrast T1 and FLAIR from T2 sequences (baseline models). To test the impact of the training set size, here, we trained the same models using 1251 subjects from the BraTS-2021 dataset. We used the same architecture and hyperparameters from the baseline models: batch size of 1, learning rate 2x10-4, Adam optimizer, cross-entropy and L1-loss. We trained two versions of the updated models: one stopped at an early checkpoint (early models) and one after 50 epochs (late models). We tested all models on institutional MRIs from 487 IDH-wt gliomas. Synthetic MRIs were compared to the originals using the structural-similarity-index (SSI) and MSE. We simulated scenarios where either the T1, FLAIR, or both were missing and used their synthetic version as inputs of a segmentation model. We compared the segmentations using the dice score (DSC) and used Friedman and Dunn’s test to compare the scores and correct for multiple comparisons. Median SSI for the T1 were 0.957, 0.947, 0.947, and median MSE were 0.006, 0.014, 0.008 for the baseline, early, and late models. For the FLAIR, median SSI were 0.924, 0.908, 0.915, and median MSE were 0.016, 0.016, 0.019 for the baseline, early, and late models. The DSC ranges for the baseline and updated models were (0.655 - 0.953), (0.420 - 0.952), and (0.610 - 0.952). The baseline and late models showed no statistically significant differences in DSC, but both performed significantly better than the early models. We show that GANs trained to synthesize brain MRIs on a small cohort perform similarly to those trained on an x10-larger cohort, making them a viable option for rare diseases or institutions with limited resources.
NIMG-57. PERFORMANCE OF DEEP LEARNING IN MGMT PROMOTER METHYLATION STATUS PREDICTION USING BRAIN MRI: RESULTS FROM A LARGE COHORT OF IDH-WILDTYPE GLIOMAS TESTED BY A SINGLE METHYLATION ASSAY
Authors: Conte Gian Marco , Moassefi Mana , Faghani Shahriar , Sanvito Francesco , Decker Paul , Kizilbash Sani H , Eckel-Passow Jeanette , Ida Cristine , Erickson Bradley
Published: November 2023

There have been several attempts to predict the MGMT promoter methylation status of gliomas using deep learning (DL), with mixed results. These studies did not account for IDH mutation status and did not utilize a uniform methylation assay, introducing potential confounders in the experimental design. We assessed the performance of DL applied to brain MRI to predict the MGMT promoter methylation status of IDH-wildtype gliomas tested with a standardized assay. We included 539 IDH-wildtype gliomas tested with real-time methylation-specific PCR from 2017-2022; 205 (38%) were MGMT promoter methylated. The assay targets 8 downstream MGMT CpG sites using ACTB as control; methylation status is determined based on the difference of PCR crossing-point values: methylated if difference < 5, unmethylated if difference > 7, indeterminate otherwise. We used post-contrast T1 and T2 MRIs as inputs for our models trained using stratified 5-fold cross-validation, 400 epochs, batch size of 16, a learning rate scheduler starting at 10-3, weighted binary cross-entropy loss, and AdamW optimizer. We repeated the experiments using two 3D DL architectures (DenseNet121 and EfficientNetB0) and two image preprocessing pipelines: the BraTS protocol and one that uses padding instead of registration to an MRI atlas, keeping constant other experimental variables. For Densenet121, the best cross-validation AUROCC and F1-score (median, median absolute deviation) were 0.67 (0.06), 0.59 (0.02) using the BraTS protocol, and 0.67 (0.06), 0.58 (0.01) using padding. For EfficientNetB0, were 0.67 (0.02), 0.66 (0.01) using the BraTS protocol and 0.67 (0.01), 0.68 (0.01) using padding. Our findings suggest that it is unlikely that DL models trained on brain MRI can predict the MGMT promoter methylation of IDH-wildtype gliomas. Importantly, our study is the first to focus on an IDH-wildtype adult diffuse glioma cohort tested with a single, standardized MGMT methylation assay, eliminating the variability introduced by different assays and IDH status.
NIMG-59. RADIOMIC FEATURE CLUSTER ANALYSIS OF IDH-MUTANT GLIOMA SUBTYPES
Authors: Willms Klara , Chadha Saahil , von Reppert Marc , Ramakrishnan Divya , Lost Jan , Tillmanns Niklas , Jekel Leon , Merkaj Sara , Aboian Mariam
Published: November 2023

INTRODUCTION

IDH-mutant glioma subtypes share similarities on MRI and histopathology but have distinct differences in survival based on their molecular subtypes. Radiomic features provide novel analysis of glioma imaging phenotypes that may not appear in clinical evaluations. We evaluated whether clustering of radiomic features of IDH-mutant gliomas could identify different subtypes based on the 2021 WHO classification.

METHODS

We extracted up to 5,763 radiomic features per case from pretreatment FLAIR and T1 post-contrast tumor segmentations of 206 patients with IDH-mutant gliomas WHO grade 2-4 using a standardized Pyradiomics 3.1.0 pipeline. Segmentations were performed using a semiautomatic workflow with a UNETR algorithm trained on the BRaTS 2021 dataset. To visualize high-dimensional feature space, we evaluated the following unsupervised clustering algorithms to differentiate tumor subtypes: PCA, t-SNE, UMAP, and PHATE. We performed redundancy reduction by calculating a Pearson correlation-matrix, and removed highly correlated features above a threshold of 0.7. Significant features were selected using the L1-norm regularization (LASSO).

RESULTS

The dataset of 206 patients included 19 grade 4, 28 grade 3, and 36 grade 2 astrocytomas as well as 23 grade 3 and 58 grade 2 oligodendrogliomas. The UNETR algorithm performed with a 0.85 Dice score on the segmentations. Clustering of the extracted 2D radiomic features from FLAIR and T1postgad using PCA, tSNE, UMAP, and PHATE did not identify distinct classes. To further analyze the two tumor entities, we applied XGBOOST, RandomForest, and KNN classifiers and found them to have AUCs < 0.5.

CONCLUSIONS

We showed that the spectrum of imaging features of IDH-mutant gliomas has a significant overlap on FLAIR and T1 post-contrast imaging. We propose that standard anatomical imaging does not provide sufficient information on these two sequences. To further identify specific subtypes of IDH-mutant gliomas, additional sequences, such as T2, ADC, SWI, and T1, can provide additional information.
NIMG-80. SKULL BASE CHORDOMA: CORRELATION OF18F-FDG PET/CT FINDINGS WITH PATHOLOGICAL FEATURES AND CLINICAL COURSE
Authors: Sakaguchi Yusuke , Tanaka Shota , Takami Hirokazu , Shin Masahiro , Hasegawa Hirotaka , Takao Hidemasa , Takayanagi Shunsaku , Saito Nobuhito
Published: November 2023

OBJECTIVE

This study aimed to evaluate 18F-fluorodeoxyglucose (FDG)-PET/CT findings, histopathological results, and clinical outcomes in patients with skull base chordoma.

METHODS

This retrospective study included patients who underwent first or repeat excision/biopsy for skull base chordoma at our institution between 2010 and 2019, with preoperative FDG-PET/CT. We assessed the SUVmean, SUVmax, lesion to white matter SUVmax/SUVmean ratio (L/N ratio), MIB-1 index, and occurrence of postoperative recurrence and metastasis. Statistical analysis was performed using Spearman's rank correlation coefficient and the Mann-Whitney U test.

RESULTS

Of the 17 participants, 52% were male, with a median age of 49 years (Interquartile Range: IQR 32-69). Among them, 41% were primary cases, and the median follow-up period was 51 months (IQR 32-77). The median SUVmax was 5.2 (IQR 3.9-6.2), SUVmean was 3.6 (IQR 3.1-5.1), L/N ratio was 1.5 (IQR 1.2-2.3), and MIB-1 index was 7.5% (IQR 2-10). Only SUVmax demonstrated a significant positive correlation with the MIB-1 index (ρ=0.556, p=0.021). Out of the 16 surgeries, 11 (69%) resulted in recurrence, while 4 of the total 17 cases (24%) showed metastasis. There were no significant differences in SUVmax, SUVmean, L/N ratio, and MIB-1 index between recurrence and non-recurrence groups. However, the MIB-1 index showed significant difference between metastasis and non-metastasis groups (p=0.0055).

CONCLUSION

In skull base chordoma, there was a significant correlation between the SUVmax on FDG-PET and the MIB-1 index. The MIB-1 index was significantly higher in the metastasis group. However, no significant correlation was found between SUVmax and distant metastasis, possibly due to the small sample size.
NIMG-87. PEDIATRIC BRAIN TUMOR SEGMENTATION INITIATIVE AT CHILDREN’S BRAIN TUMOR NETWORK (CBTN); PROJECT UPDATE ON IMPROVED PERFORMANCE AND FUTURE PROSPECTS
Authors: Kazerooni Anahita Fathi , Khalili Nastaran , Haldar Debanjan , Viswanathan Karthik , Familiar Ariana , Bagheri Sina , Anderson Hannah , Mahtabfar Aria , Storm Phillip , Davatzikos Christos , Resnick Adam , Ware Jeffrey B , Vossough Arastoo , Nabavizadeh Ali
Published: November 2023

Pediatric brain tumors (PBT) exhibit significant heterogeneity, and accurate assessment of tumor response is crucial for patient management. While bidimensional measurements of tumor size are commonly used, they may underestimate tumor dimensions. Our group previously developed a multi-institutional, and multi-histology model on the Children’s Brain Tumor Network (CBTN) imaging dataset to segment tumor subregions, recommended by the Response Assessment in Pediatric Neuro-Oncology (RAPNO) working group. In the most recent update, we utilized a self-configuring deep learning architecture called nnU-Net on a large dataset of well-annotated PBTs (233 training, and 60 withheld internal and 46 external test sets). The model was trained and validated on multiparametric MRI sequences and differentiated various tumor subregions, including enhancing tumor (ET), nonenhancing tumor (NET), edema (ED), and cystic component (CC) and the whole tumor (WT) regions. Clinical validity was assessed by comparing the volumes of tumor subregions predicted by the model with expert manual segmentations, demonstrating strong agreement, with statistically significant Pearson’s correlation coefficients of 0.93/0.69 for ET, 0.94/0.93 for NET, 0.78/0.93 for CC, and 0.94/0.50 for ED subregions (p< 0.001) for the internal/external test cohorts. The trained model showed excellent performance for the withheld internal test set and decent accuracy for the external test set. Median Dice scores for internal/external test sets were 0.94±0.10/0.90±0.07 for WT, 0.85±0.33/0.84±0.30 for ET, 0.80±0.32/0.64±0.31 for NET, 0.79±0.37/0.67±0.33 for CC, 0.70 ±0.42/0.37±0.43 for ED, and 0.86±0.19/0.80±0.21 for all nonenhancing components (combination of NET, CC, and ED), respectively. The proposed automated segmentation method provides accurate and reproducible volumetric measurements of RAPNO-defined subregions in PBTs. It exhibits robust performance and potential generalization to external datasets and the accuracy is higher compared to the previous DeepMedic model. We will continue to improve the model by constantly adding new training data to further improve the performance and sustain model robustness.
NIMG-88. THALLIUM 201 SINGLE PHOTON EMISSION CT (TI-SPECT) FOR DIFFERENTIATION OF MALIGNANT VERSUS BENIGN NERVOUS SYSTEM SPACE OCCUPYING LESIONS: A RETROSPECTIVE STUDY, SYSTEMATIC REVIEW, AND META-ANALYSIS
Authors: Mondia Mark Willy , Alonto Anisah Hayaminnah , Pang Nicole Girlyn , Resma Francis Manuel , Gacula John Kenneth , Pauco Arnel , Chua Annabell , Batara Julette Marie
Published: November 2023

Importance Thallium-201 single-photon emission computed tomography (TI-SPECT) imaging has been used historically to distinguish malignant cerebral neoplasms from infectious etiologies. Objectives Our study aims to review existing literature and conduct a retrospective study and meta-analysis on the use of TI-SPECT to differentiate malignant from non-malignant nervous system lesions. Data Sources A retrospective study on use of TI-SPECT in differentiating malignant versus benign nervous system masses was conducted in two tertiary hospitals in the Philippines. Systematic review of relevant studies regarding TI-SPECT for brain and spinal cord lesions was also done. Meta-analysis was performed to generate pooled sensitivity and specificity. Study Selection All study types published in the English language were included – randomized controlled trials (RCTs), prospective/retrospective cohort studies, and case series and reports; abstract only studies were excluded. Studies that involved either pediatric and adult cases were considered. Data Extraction and Synthesis The study complied with the Meta-analysis of Observational Studies in Epidemiology (MOOSE) and Preferred Reporting Items for Systematic reviews and Meta-analyses (PRISMA) Guidelines. Main Outcome and Measure The primary outcome was sensitivity and specificity of TI-SPECT. This involved getting correlation of positive and negative thallium scan uptake with either biopsy results (if available) or diagnosis via clinical response to treatment (i.e. whether cases that were managed as infection or demyelination showed improvement on follow-up). RESULTS: Thirty-two (32) articles were qualitatively described and 25 datasets were subjected to meta-analysis. Pooled sensitivity and specificity were 0.89 (95% CI: 0.82-0.94) and 0.82 (95% CI: 0.74-0.88), respectively with an area under the curve (AUC) for diagnostic accuracy of 0.92. CONCLUSION: and Relevance Thallium scans may be utilized to discriminate malignant from benign nervous system lesions, especially, in cases with a >80% pre-test probability. Further studies are needed to validate this findings.
NCMP-08. TREATMENT OF PITUITARY METASTASIS: A SINGLE CENTER EXPERIENCE AND SYSTEMATIC LITERATURE REVIEW
Authors: Begley Sabrina , Yang Kaiyun , Ye Vincent , Lynch Daniel , Gutierrez Enrique , Bernstein Mark , Zadeh Gelareh , Shultz David , Kongkham Paul
Published: November 2023

PURPOSE

To understand the natural history and optimal treatment strategy for pituitary gland metastasis.

METHODS

We performed both a retrospective chart review of patients treated at our institution and a scoping review of the topic.

RESULTS

The retrospective review identified seven patients with an average age of 59.6. Primary histologies included breast cancer (4), melanoma (1), renal carcinoma (1), and sarcoma (1). Two patients had anterior pituitary endocrine dysfunction, one of whom was the only patient with visual symptoms. All patients were treated with radiosurgery and two also underwent surgical resection. Overall survival ranged from 6.5 – 117 months. We identified 166 patients from 71 studies in our literature review. The most common primary cancer was lung (27.7%), followed by breast (18.7%) and renal (14.5%) cancer. 107 presented with endocrine dysfunction; with 41 cases of diabetes insipidus and 55 cases of hypopituitarism. 110 presented with visual compromise. 107 patients received radiotherapy, 96 underwent surgical resection and 44 received systemic chemotherapy/immunotherapy. Surgery was significantly associated with an increased likelihood of vision improvement and a decreased likelihood of endocrine normalization. Radiographic regression predicted visual improvement. Median overall survival was 9.9 months (range: 0.2 – 96).

CONCLUSIONS

Our scoping review showed that both radiosurgery and surgical resection have been frequently used to treat pituitary metastases with good response. Vision improvement is more likely to happen following surgical resection. Despite treatment and radiographic response, patient survival remains less than a year.
NCMP-09. THE CURRENT LANDSCAPE OF SPINE ONCOLOGY SURGICAL TRIALS AND FUTURE OPPORTUNITIES
Authors: Schupper Alexander , Patel Shrey , Steinberger Jeremy , Germano Isabelle
Published: November 2023

BACKGROUND

Clinical trials have allowed the discovery of successful therapeutic intervention for cancer patients. The current number of cancer patients in the US has increased with an incidence of 442/100,000 population and yet with decreased yearly mortality rate. Spine metastatic disease occurs in approximately 90% of patients with cancer. The aim of this study is to analyze the current landscape of spine oncology trials to identify future opportunities.

METHODS

To assess active and ongoing clinical trials in the treatment of metastatic spinal disease, the authors queried https://clinicaltrials.gov/ under the searches “Spine Metastases” and “Spine Tumor.” Only clinical trials designated as “Recruiting” were included. Parametric and non-parametric statistical analysis was performed.

RESULTS

Our initial search yielded to 100 total studies; 18 clinical trials met entry criteria. Trial type was 16/18 therapeutic, 2/18 observational and trial design 6/18 (33%) randomized. All 18 trials were single center. Trials were were based in the United States (90%) and British Columbia, Canada. Across US geographical quadrants, a significant higher number of therapeutic trials was found in the South quadrant (12/16) compared to the other quadrants, (p< 0.001; Midwest: N=3/16, Northeast: N=1). The most common therapeutic focus included radiosurgery, followed by vertebral body augmentation and/or radiofrequency ablation, and laser interstitial thermal therapy (LITT).

CONCLUSION

Clinical trials are a cornerstone for the advancement oncological treatment. Our study shows that currently there is an ample opportunity to design clinical trials for our growing population of metastatic spine disease patients. Successful strategies to enhance the needed portfolio of spinal oncology trials, include focusing on including all US geographic quadrants. As new trials are designed, continued efforts devoted to data entry in national registry remains important.
NCMP-22. FLUDARABINE NEUROTOXICITY IN PATIENTS UNDERGOING CAR T-CELL THERAPY - A REPORT OF 2 CASES
Authors: Li Yi , Drappatz Jan , Mantica Megan
Published: November 2023

Fludarabine is a purine analog used in the treatment of chronic lymphocytic leukemia (CLL) and as part of immunosuppressive/lymphodepleting regimens in allogeneic stem cell transplant and chimeric antigen receptor (CAR) T-cell therapy. It induces cellular cytotoxicity through multiple mechanisms, ultimately leading to the inhibition of DNA synthesis. Although myelosuppression is the primary dose-limiting side effect of fludarabine, there have been reported cases of delayed-onset neurological symptoms, such as progressive visual impairments, dementia, ataxia, hemiparesis, quadriparesis, and blindness. These symptoms have been observed in patients receiving fludarabine alone or as part of preconditioning treatments for CAR T-cell therapy. The neurological abnormalities are characterized by leukoencephalopathies and can manifest as posterior reversible encephalopathy (PRES), acute toxic leukoencephalopathy (ATL), or other leukoencephalopathy (OLE). We present two cases of patients who underwent fludarabine conditioning before CAR T-cell therapy, exhibiting late-onset and progressive changes in vision and encephalopathy. These symptoms differ in timing and pattern from the neurotoxicities commonly associated with CAR T-cell therapy. Nonetheless, given the overlapping neurological toxicities seen with both CAR-T cell therapy and fludarabine, it is important to consider implementing thorough screening measures to modify preconditioning fludarabine dose intensity, particularly for patients with advanced disease, renal insufficiency, or other risk factors to limit fludarabine-associated adverse effects.
NCMP-25. TUMOR-RELATED EPILEPSY IN PATIENTS WITH BRAIN TUMORS (PBT): AN ACADEMIC INSTITUTION EXPERIENCE
Authors: Cabrera Nynoshka Bassatt , Nasany Ruham Alshiekh , Zhao Kehan , Elwan Sherif , Rusnak Rebecca , Rasekhi Roozbeh Tarighati , Izadyar Shahram
Published: November 2023

BACKGROUND

Brain tumors are the second most common cause of intractable focal epilepsy. Seizures can be the presenting symptom of PBT or develop later in the disease course, impacting morbidity and quality of life. Despite the high prevalence of PBT-related epilepsy, there is a scarcity of literature to help better identify its unique features and characterizations that can guide medical management and reach a standardized approach for it. We present a retrospective review of a cohort of PBT-related epilepsy cases at a single academic institution.

METHODS

Records of patients with PBT seen at Upstate Medical University between 2012 and 2022 were reviewed. Inclusion criteria were: 18 years of age and older at the time of diagnosis and having at least one seizure that thought to be related to a PBT. Patients with history of previous epilepsy or psychogenic non-epileptic seizures were excluded.

RESULTS

Of the 1103 reviewed records, 293 patients (26.56%) met the inclusion criteria. Mean age at tumor diagnosis was 57.7 years +/- 16.6, and mean follow-up after tumor diagnosis was 17.9 months. Seizures were the initial presentation of the brain tumor in 166 (56.66%) patients. The most common tumor was grade 4 glioma in 45% of patients. Anti-seizure medications were started in 92.1%, and the most commonly used medication was levetiracetam in 75%. Number of patients who underwent total resection of the tumor was 123 (42.4%). On the last follow-up visit, 56% of patients remained seizure-free.

CONCLUSION

Patients with PBT often develop epilepsy that, at times, can be intractable. More than half of our patients experienced a seizure as the presenting symptom. Even though more than 90% were started on anti-seizure medications, only 56% remained seizure-free on follow-ups. Since seizures dramatically affect the quality of life, managing seizures in this patient population warrants further studies.
NCOG-05. TREATMENT STRATEGY AND SURVIVAL ANALYSIS OF PATIENTS WITH PRIMARY ADULT-TYPE DIFFUSE GLIOMA IN THE MOLECULAR ERA: A PROSPECTIVE COHORT STUDY FROM THE CGGA NETWORK
Authors: Zhang Kenan , Li Guanzhang , Fang Shengyu , Zhang Wei , Wang Anxin , Jiang Tao
Published: November 2023

IMPORTANCE

The fifth edition of the WHO Classification of Tumors of the Central Nervous System (CNS) marks the entry of the diagnosis and treatment of diffuse glioma into the molecular era. The clinical implications of this landmark change in primary adult-type diffuse glioma need to be revealed.

OBJECTIVE

To reveal the clinical prognostic factors of adult diffuse glioma under the WHO CNS 5 classification.

DESIGN, SETTING, AND PARTICIPANTS

In this clinical-based prospective observational registration study, 3,308 glioma patients from 3 major neurosurgical centers were enrolled between Mar. 2005 to Jun. 2021. After excluding patients who did not meet the inclusion criteria, 1,099 primary adult-type diffuse glioma patients were eligible for inclusion in this study. Student t-test, Chi-squared test, and ANOVA were used for differential analysis. Kaplan-Meier curve and univariate and multivariate Cox regression analyses were used for survival analysis.

MAIN OUTCOMES AND MEASURES

Totally, 1,099 patients diagnosed with primary adult-type diffuse glioma were included in this study. The male-to-female ratio is about 1.4-1.5 to 1. The mean age at diagnosis for astrocytoma, IDH-mutant, oligodendroglioma, IDH-mutant and 1p/19q-codeleted and glioblastoma, IDH-wildtype were 39.0, 40.0, and 53.0 years, respectively. In astrocytoma, preoperative epilepsy, WHO grade, MGMT promoter methylation status, the extent of resection, and postoperative comprehensive treatment were independently associated with overall survival. For oligodendroglioma, gender, WHO grade, and extent of resection were associated with overall survival. As for glioblastoma patients, gender, age at diagnosis, preoperative KPS, preoperative epilepsy, the extent of resection, and postoperative comprehensive treatment were prognostically correlated.

CONCLUSIONS AND RELEVANCE

Patients in distinct molecular subtypes showed different epidemiological features and were associated with different clinical prognostic factors.
NCOG-08. BEVACIZUMAB ALONE VERSUS BEVACIZUMAB PLUS IRINOTECAN IN PATIENTS WITH RECURRENT GLIOBLASTOMA: A NATIONWIDE POPULATION-BASED STUDY
Authors: Lee Yeonhu , Roh Tae Hoon , Kim Se-Hyuk
Published: November 2023

INTRODUCTION

There is no established treatment for recurrent glioblastoma. For the treatment of recurrent glioblastoma, the antiangiogenic antibody, bevacizumab, is used either alone or in combination with Irinotecan. This study aimed to compare the survival of patients receiving bevacizumab monotherapy (BEV) and those receiving bevacizumab plus irinotecan combination therapy (B+I) in recurrent glioblastoma (GBM), using a nationwide population-based dataset.

METHODS

Patients matching the ICD code C71.x were screened from the national database. From January 2008 to November 2021, 846 patients who had undergone surgery or biopsy and received concurrent chemoradiotherapy with Temozolomide were included. Of these, 450 received BEV, while 396 received B+I. The patients' demographic characteristics, inpatient stay duration, prescription frequency, and survival outcomes were compared between the two groups.

RESULTS

The BEV group was older and had a higher percentage of females compared to the B+I group. The survival analysis revealed no significant difference in survival times between the two groups in the univariate and multivariate analysis. Younger age, female gender, and having surgery rather than biopsy were associated with better prognosis.

CONCLUSION

This study found no significant difference in overall survival between bevacizumab monotherapy and bevacizumab plus irinotecan combination therapy in patients with recurrent GBM. Considering the additional potential toxicity associated with irinotecan, bevacizumab monotherapy may be a suitable treatment option.
NCOG-11. PREOPERATIVE NANO SCORE AS A PREDICTOR FOR SURVIVAL IN GLIOBLASTOMA
Authors: Mireles Eduard Mendoza , Blakstad Hanne Kristin , Skaga Erlend , Helseth Eirik , Rønning Pål , Vik-Mo Einar
Published: November 2023

BACKGROUND

Age, molecular features, extent of resection, and adjuvant treatment are well established prognostic factors for patients with glioblastoma. Neurological Assessment in Neuro-Oncology (NANO) Scale was designed as a tool to provide an objective clinician-reported outcome of neurologic and complements the radiological evaluation of the Response Assessment in Neuro-Oncology (RANO) criteria. Despite the generally detrimental prognosis associated with severe new neurological deficits after surgery, a comprehensive understanding of the impact of pre- and postoperative neurological status remains limited. This study explores the potential of the NANO scale to predict survival when applied immediately before and after surgery.

METHODS

This retrospective study examined adult patients in South-Eastern Norway who underwent resection for IDH wildtype glioblastoma between January 2020 and December 2021. We used Kaplan Meier curve calculate median overall survival and chi-square and log rank test were used to compare groups.

RESULTS

The study included 187 patients, with a median overall survival was 14.9 months. Patients with a preoperative NANO-score of 0-2 had a median survival of 17.4 months, compared to 11.3 months for patients scoring 3 or more points (p< 0.001). Neither Postoperative NANO scores nor changes in NANO scores in pre- to postoperative score were found to be significant predictors for survival.

CONCLUSIONS

This study indicates that a low preoperative NANO were predictive for a longer median survival, whereas postoperative NANO scores didn’t show the same impact. Surprisingly, an increase in the postoperative NANO score, indicating new, or worsening of the neurological deficits, didn′t correlate with a shorter median survival.