bluuebunny/crossref_metadata_2025 huggingface dataset:
PATH-47. AGE-, SEX-, AND GRADE-ASSOCIATED MOLECULAR DIFFERENCES IN A MULTI-INSTITUTIONAL COHORT OF CHOROID PLEXUS TUMORS
Authors: Williams Erik , Hickman Richard , Gultekin Sakir , Juratli Tareq
Published: November 2024

BACKGROUND

Choroid plexus tumors (CPT) are central nervous system tumors where prognosis has been correlated to histologic grade, with aggressive clinical behavior and reduced survival rate in higher grade cases. Here, we present a genomic survey of a large multi-institutional cohort of CPTs across all grades.

MATERIAL AND METHODS

Fifty-eight CPT samples were analyzed by comprehensive genomic profiling (CGP) by a hybrid capture-based DNA sequencing platform (FoundationOne®CDx). Pathology reports, histopathology reviews, and patient clinical data were assessed.

RESULTS

Our cohort included 11 choroid plexus papillomas (CPP; grade 1), 16 atypical CPP (grade 2), and 31 choroid plexus carcinomas (CPC; grade 3). Males were slightly more affected than females (31 vs. 27 cases). Median patient age at tissue sampling was 11 years (range: 1–72 years). Median age of patients with CPC was younger at 3 years compared CPP at 34 years (p < 0.01). Genomic analyses identified three frequent, mutually exclusive mutations in TP53, TERTp, and DAXX. TP53 mutations (n = 15, 26%) were significantly more prevalent in CPC (n=14 CPC, p=0.0003), and were identified predominantly in children (n=12 CPC at <20 years). By contrast, TERT promoter mutations (TERTp; n = 5, 8.6%) were identified exclusively in CPP (p=0.019), predominantly grade 2 (4 of 5 cases), and exclusively in adult patients, with a median age of 48 years. DAXX mutations (n=4, 6.9%) were more common in CPC (n=3). Other alterations included PTEN (n=4, all adults) and MYCN amplification (n=3, all children <6 years), both exclusively in CPC. In 21 cases, including 9 out of the 11 Grade 1 CPP, no known cancer mutation was detected.

CONCLUSION

This study provides comprehensive genomic profiling of CPTs, highlighting distinct genetic alterations associated with different histological grades and patient demographics. These findings may inform future research and therapeutic strategies targeting specific molecular pathways in CPTs.
PATH-51. CENTRAL NERVOUS SYSTEM METASTASES ARE GENOMICALLY DIVERGENT FROM THEIR RESPECTIVE EXTRACRANIAL SITES
Authors: Huang David , Bergagnini Isabella , Hajiyeva Sabina , Akerman Meredith , Wong Tamika , Boockvar Randy D’Amico John , Vojnic Morana
Published: November 2024

INTRODUCTION

Next-generation sequencing (NGS) has become standard of care in establishing the diagnosis and guiding treatment of cancers. Our understanding of genomic evolution of brain metastases (BM) and leptomeningeal disease (LMD) from solid tumor malignancies remains limited. Here we present updated data from our pilot study.

METHODS

We prospectively collected clinical data and NGS of seventeen patients undergoing craniotomy for symptomatic BM from solid tumor malignancies or cerebrospinal fluid (CSF) sampling for LMD. Matched systemic and CNS analyses were performed using a research-based NGS assay. When extracranial disease tissue was unavailable, liquid NGS served as a surrogate.

RESULTS

CNS metastases were present at initial diagnosis in 10/17 and 11/17 patients had not received systemic therapy prior to CNS tissue sampling. The predominant cancer type was NSCLC (n=11), followed by breast cancer (n=3), ovarian high grade serous carcinoma (n=1), GEJ adenocarcinoma (n=1), and basosquamous carcinoma of skin (n=1). The mean tumor mutational burden in extracranial samples was 3.65 (SD 3.34; SEM 0.97), in contrast to CNS samples 21.63 (SD 26.47; SEM 7.64). Concordant mutations in matched sampling had an increase in CNS variant allele frequency (VAF) (27.8% vs 17.3%; arithmetic difference = 10.5, p=0.054) and CNS gene copy number alterations (CNA) (2.4 copies vs 0.8 copies; arithmetic difference = 1.6, p=0.171). Known driver alterations in EGFR, KRAS and PIK3CA were retained. LMD was present in 4/17 patients, with two present at enrollment and two developing during the study.

CONCLUSIONS

Matched sequencing reveals CNS metastases to harbor a significantly higher TMB, retention of primary driver alterations with a trend towards higher VAF and CNA of concordant mutations. While limited by small sample size, these data indicate genetic evolution in CNS metastases regardless of prior treatment status.
PATH-53. DNA MUTATION SEQUENCING AND METHYLATION ANALYSIS OF SOMATICNF1 MUTANT IDH-WILDTYPE GLIOBLASTOMA IDENTIFIES THREE EPIGENETIC GROUPS ANDCDKN2A/B LOSS AS A NEGATIVE PROGNOSTIC BIOMARKER
Authors: Mirchia Kanish , Pan Sixuan , Payne Emily , Liu John , Peeran Zain , Shukla Poojan , Young Jacob , Gupta Rohit , Wu Jasper , Pak Joanna , Seo Kyounghee , Ozawa Tomoko , Na Brian , Reddy Alyssa , Braunstein Steve , Phillips Joanna , Chang Susan , Solomon David , Perry Arie , Raleigh David , Berger Mitchel , Abate Adam , Vasudevan Harish
Published: November 2024

The tumor suppressor NF1 is frequently mutated in IDH-wildtype glioblastoma. However, the molecular subgroups and clinically relevant biomarkers within somatic NF1 mutant, IDH-wildtype glioblastomas remain incompletely understood. Here, we combine methylation arrays and targeted DNA sequencing to identify epigenetic subgroups and clinical biomarkers within non-syndromic NF1 mutant IDH-wildtype glioblastoma. We identified 186 patients treated at the University of California San Francisco between 2016-2024 with newly diagnosed IDH-wildtype glioblastoma containing a somatic pathogenic NF1 mutation on a CLIA certified targeted DNA sequencing assay. Illumina EPIC DNA methylation arrays (n=129 patients) were processed using the minfi package and Heidelberg random forest classifier (v12.8). Downstream analyses including hierarchical clustering and survival analyses were performed in R. DNA sequencing identified 12 recurrently altered genes in greater than 10% of cases across cell cycle regulators (CDKN2A/B, TP53, RB1), PI3K signaling (PTEN, PIK3R1, PIK3CA), epigenetic modifiers (ATRX, SETD2), and growth factor signaling (EGFR, PDGFRA, PTPN11). DNA methylation analysis revealed three epigenetic subgroups. Group 1 showed lower median patient age and significantly increased TP53 co-mutation rate. Group 2 contained a significantly higher proportion of male patients and was significantly enriched for RB1 and TERT promoter alterations, with a majority of tumors classified as GBM-MES using the Heidelberg classifier. Group 3 showed a significantly higher proportion of female patients and was significantly enriched for homozygous CDKN2A/B deletion. Homozygous CDKN2A/B loss was associated with significantly worse overall survival across the entire non-syndromic NF1 mutant glioblastoma cohort but not in a propensity score matched NF1 wildtype glioblastoma cohort. DNA methylation profiling revealed three epigenetic subgroups characterized by distinct clinical features, co-mutation patterns, and reference DKFZ methylation classifier identities. CDKN2A/B loss may be a negative prognostic biomarker specifically in NF1 mutant glioblastomas; future multi-institutional studies are required to validate these findings and their therapeutic implications in a larger, representative cohort.
PATH-54. HIGH-THROUGHPUT SINGLE NUCLEAR DNA SEQUENCING OF HUMAN SPORADICNF1 MUTANT IDH-WILDTYPE GLIOBLASTOMAS REVEALS PATTERNS OF TUMOR EVOLUTION AND RECURRENCE
Authors: Mirchia Kanish , Pan Sixuan , Payne Emily , Agoglia Rachel , Arribas-Layton Marc , Vasudevan Harish
Published: November 2024

The advent of single cell techniques has advanced our understanding of glioblastoma (GBM) evolution and cell lineage relationships. However, study of mutational co-occurrence and clonal phylogeny has been hampered by limitations in single cell genotyping. Here, we perform semi-automated, rapid single nuclear dissociation followed by targeted single nucleus DNA sequencing (snDNA-seq) of eleven retrospectively identified somatic NF1 mutant IDH-wildtype glioblastomas. Bulk DNA sequencing was performed as part of routine clinical care using a CLIA-certified targeted sequencing panel. For snDNA-seq, tissue cores with greater than 30% tumor were dissociated on a S2 genomics S100 Singulator followed by snDNA-seq using a targeted 361 amplicon panel (Tapestri, Mission Bio, USA) to sequence for recurrently observed single nucleotide substitutions and copy number alterations. A mean of 3,661 cells were recovered per sample with a mean of 96 reads per cell per amplicon and 87% mean panel uniformity. SnDNA-seq validated point mutations and copy number alterations observed in bulk DNA-sequencing and revealed novel alterations and subclonal copy number alterations not detected on bulk analysis. Within individual samples, snDNA-seq based phylogenetic reconstruction identified mutually exclusive patterns of mutation between NF1 and PI3K signaling alterations, suggesting these events may occur in distinct tumor subclones. With regard to copy number alterations (CNAs), snDNA-seq demonstrated intra-tumoral heterogeneity for chromosome 9p loss, chromosome 7 gain, and chromosome 10 monosomy. Subclonal CNA clones not detected by bulk sequencing were identified in 5 samples. Analysis of a matched primary-recurrent tumor pair revealed expansion of a specific mutational clone (loss of 9p, 10p, gains of 1p, 7, 15, and 19q) at recurrence. SnDNA-seq recapitulated bulk DNA sequencing alterations and identified distinct patterns of mutational co-occurrence, CNAs, and tumor evolution over time. Reconstructing GBM phylogeny at single cell resolution has potential translational implications for understanding tumor evolution and treatment resistance.
PATH-60. AUTOMATED QUANTIFICATION OF KI-67 PROLIFERATION INDEX BASED ON WHOLE SLIDE IMAGES IN PEDIATRIC BRAIN TUMORS
Authors: Familiar Ariana M , Kazerooni Anahita Fathi , Kim Meen Chul , Kraya Adam , Storm Phillip J , Oldridge Derek , Viaene Angela , Resnick Adam C , Nabavizadeh Ali
Published: November 2024

The use of AI methods with histopathological images (pathomics) has strong potential to aid pathologists in pediatric brain cancer diagnosis and prognosis given the morphological and molecular heterogeneity of these tumors. However, use of pathomics in this context has been relatively limited. One example is the IHC-based tumor proliferation index (percentage of Ki-67 positive cells amongst all malignant cells) which is often routinely reviewed by pathologists clinically but remains to be objectively quantified or reported in a standardized manner. As a result, analysis of this marker across patients at-scale and in data-driven methods remains largely hindered. Here, we explore the extension of an automated deep learning AI tool (DeepLIIF), originally trained and validated with adult breast/prostate/liver data, for quantification of Ki-67 index from digitized whole slide images of a cohort of pediatric brain tumors from the Children’s Brain Tumor Network (N=834). We find that derived Ki-67 scores largely agreed with neuropathologist-reported Ki-67 activity in original clinical notes and could be used to successfully stratify glioma/astrocytoma patients (N=200) into low- and high-grade groups (LGG: M=11.6; SEM=1.2; HGG: M=18.7; SEM=2; p=0.001). Ki-67 scores were also related to the survival status of the patients (Alive: M=11.8; SEM=1.1; Deceased: M=18.8; SEM=2.2; p=0.003). Summary statistics across tumor types (glioma, astrocytoma, medulloblastoma, ATRT, ependymoma, etc.) and molecularly defined subtypes are also compared, providing direct insights into distributional properties between these groups that has not previously been feasible. Our results show the ability of AI-powered methods to quantify routine histopathology metrics with little human input, allowing objective comparisons between patients and opening the door for precision medicine approaches with predictive analytics in clinical contexts.
PATH-63. M6A REGULATOR-BASED MOLECULAR CLASSIFICATION AND HUB GENES ASSOCIATED WITH IMMUNE INFILTRATION CHARACTERISTICS AND CLINICAL OUTCOMES IN DIFFUSE GLIOMAS
Authors: Lu Jie , Chen Siyu , Li Depei , Mou Yonggao
Published: November 2024

BACKGROUND

m6A methylation modification is a new regulatory mechanism involved in tumorigenesis and tumor-immunity interaction. However, its impact on glioma immune microenvironment and clinical outcome remains unclear.

METHODS

Comprehensive expression profiles of 18 m6A regulators were used to identify molecular subtypes exhibiting distinct m6A modification patterns in 1673 glioma samples sourced from public datasets. A multi-genes signature was constructed for predicting clinical outcome and response to immunotherapy in glioma patients. Immunohistochemistry and cellular experiments were performed for validation.

RESULTS

Two m6A subtypes of gliomas were identified. The m6A-low-risk subtype was characterized by paucity of immune infiltrates; Whereas the m6A-high-risk subtype had higher abundances of multiple immune cells including lymphocyte and macrophage as well as increased expression of PD-L1, corresponding to an immunosuppressive phenotype. The m6A-high-risk subtype had poorer survival than the m6A-low-risk subtype in both the glioblastoma and lower grade gliomas cohorts. Eight m6A-related hub genes of high prognostic significances were identified and selected for developing a scoring signature termed as m6Ascore. Elevated m6Ascore indicated worse survival for glioma patients under standard care, but showed enhanced response to immunotherapy. Moreover, we demonstrated that overexpression of FTO, a m6A demethylase, inhibited the expressions of m6A-related hub genes (PTX3, SPAG4), impaired glioma cell viability and reduced macrophage chemotaxis.

CONCLUSION

This work develops an immune- and clinical-relevant m6A subtyping and a scoring model, which enhances our understanding of the role of m6A modification in regulating immune infiltration microenvironment in gliomas and helps to identify patients who are more likely to benefit from immunotherapy.
PATH-64. UNDERSTANDING MECHANISTIC UNDERPINNINGS OF MOLECULAR SUBGROUPS OF MENINGIOMA
Authors: Nitturi Vijay , Lau Sean , Ledbetter Elizabeth , Nouri Shervin Hosseingholi , Klisch Tiemo , Patel Akash
Published: November 2024

Meningiomas are the most common intracranial tumors. In the past, they were thought to be indolent and could be treated by resection. The current standard of care utilizes WHO histopathological grading to identify malignant potential. Our lab identified three molecular groups (MenG A, B, and C) using CNVs, methylation, and/or expression profiling with different biological characteristics. These groups were independently validated and predicted recurrence more reliably than WHO grade. MenG A is genomically stable but harbors tumors with point mutations, mainly in TRAF7, KLF4, and AKT1. On the other hand, MenG B and C tumors have chromosome 22q arm deletion or loss of merlin, the protein product of the NF2 gene. Moreover, MenG B is characterized by DNA hypomethylation, while MenG C tumors show DNA hypermethylation and have additional chromosomal losses, most notably in chromosome 1p. Lastly, while MenG A/B are indolent, MenG C – comprising approximately 28% of meningiomas – recur frequently and are refractory to radiotherapy and/or surgery. How can two groups of tumors with the same driver mutation behave so differently? Hence, our lab is interested in (1) what molecular pathway/factor(s) are necessary for becoming any meningioma, and (2) what mechanisms are critical for the aggressiveness of MenG C. Here, we investigate the role of TRAF7 in meningioma biology. Toward this end, we study interactors, modulators, and individual mutations in cell culture. In addition, we use published exome sequencing and expression data to reveal possible connections between chromatin state and individual genes. In conclusion, a variety of underlying mechanisms drive meningioma tumorigenicity and aggressiveness. Elucidating these mechanisms could provide future therapeutic targets for currently untreatable meningiomas.
PATH-67. THE ROLE OF STATUS OF HER-2, ESTROGEN-RECEPTOR, BRCA 1, AND BRCA 2, IN THE INCIDENCE OF BRAIN METASTASIS IN BREAST CANCER
Authors: Altaf Ahmed , Gilani Ahmed , Azan Ali , Enam Ather
Published: November 2024

Breast cancer (BC) is the most diagnosed tumor in women and the second-leading cause of brain metastasis (BM), with a prevalence ranging from 10-36%. According to the Epidemiological Strategy and Medical Economics research program, advanced BC patients face an estimated 25% risk of developing BM within 2-3 years after the initial diagnosis. The frequency of BM is significantly increased by the primary tumor profile, including larger tumors, higher nuclear grade, HER-2 positivity, estrogen-receptor negativity, and triple-negative status. A gap remains in the classification of the BM site relative to primary tumor biomarkers, and the absence of multimodality treatment methodologies poses challenges to survival rates and quality of life in BC patients. This retrospective cross-sectional study at Aga Khan University Hospital identified 52 cases of brain metastasis secondary to breast cancer over a 10-year period. The median age of patients was 55 years, ranging from 32 to 78 years. Primary breast tumors were predominantly high-grade ductal carcinomas (65%), followed by lobular carcinomas (25%) and other rare histological types (10%). Secondary brain metastases were primarily located in the cerebrum (60%), cerebellum (25%), and brainstem (15%). Tumor profiles indicated a significant correlation between HER-2 positivity and the development of brain metastasis, with 70% of HER-2 positive patients presenting with extensive brain metastasis. Tumor progression varied, with a median time to brain metastasis of 2.5 years from the initial breast cancer diagnosis. Despite aggressive multimodality treatments, including surgery, radiation, and chemotherapy, the overall prognosis remained poor. The study found that early detection of HER-2 positive and triple-negative tumors could potentially delay the progression of brain metastasis through targeted therapies. Mortality rates in this cohort were high, with a median survival of 8 months following the diagnosis of brain metastasis. These findings underscore the need for improved diagnostic, preventive, and therapeutic strategies to manage brain metastasis in breast cancer patients.
NIMG-01. RADIOMIC DATA ANALYSIS WITH ENSEMBLE MACHINE LEARNING TECHNIQUES PREDICT GRADE, HISTOPATHOLOGIC SUBTYPE, AND 1P/19Q CO-DELETION STATUS IN PATIENTS WITH LOW-GRADE GLIOMAS
Authors: Panchawagh Suhrud
Published: November 2024

Low-grade gliomas (LGGs) are a diverse group of primary brain tumors characterized by their variable prognosis and treatment response. Traditionally, the management of LGGs has relied on histopathological analysis, which sometimes offers limited insight into tumor behavior and treatment outcomes. Recent advances in radiomics have enabled the extraction of detailed quantitative features from routine imaging, providing a non-invasive method to assess tumor characteristics. These radiomic features can capture underlying tumor heterogeneity more comprehensively than conventional methods. Integrating radiomic data with ensemble machine learning techniques offers a promising approach to enhance the prediction of tumor grade, histopathologic subtype, and genetic alterations such as 1p/19q co-deletion status in LGGs, potentially leading to more tailored therapeutic strategies. We combined radiomic-genomic data from 159 magnetic resonance imaging (MRI) scans from the updated LGG-1p19qDeletion dataset (Erickson 2020) and 114 MRI scans from the ReMIND dataset (Juvekar 2024). Expert radiologists performed segmentations. A total of 2446 extracted radiomic features were initially extracted. Feature selection was performed using wrapper- and filter-based techniques with cross-validation. Prediction models were built using machine learning techniques, including random forest and extreme gradient boosting. Using Random Forest, we achieved high accuracy in predicting histopathologic subtype (88.14%, AUC 96.68%) with precision of 87.86% and Dice score of 87.88%. For grade prediction (accuracy 76.19%, AUC 91.84%), precision was 73.91%, and the Dice score was 77.27%. For 1p/19q co-deletion status (accuracy 75.61%, AUC 82.74%), precision was 77.78%, and the Dice score was 73.68%. Our study establishes a robust radiomic workflow to predict tumor grade, histopathologic subtype, and 1p/19q co-deletion status in low-grade gliomas, enhancing diagnostic accuracy and treatment personalization. This methodology can be applied clinically to improve the stratification of treatment plans for low-grade gliomas, potentially leading to effective, personalized therapy options. Using multicentric data potentially improved external validity, something which past research lacked. Future research should focus on validating and deploying this model using observational multicentric study designs.
NIMG-03. USE OF ARTERIAL SPIN LABELING TO DIFFERENTIATE ICTAL PHENOMENON FROM TUMOR PROGRESSION IN HIGH GRADE ASTROCYTOMA
Authors: Zahid Anza , Thatikonda Nithisha , Dubey Prachi , Tremont-Lukats Ivo
Published: November 2024

A 39-year-old female with grade-3 left parietal IDH-mutant astrocytoma following resection presented with convulsive status. EEG showed electrographic seizures arising from the left parietal region. MRI-brain showed the left temporoparietal post-treatment bed without any contrast enhancement (Fig-1A). Arterial spin labeling (ASL) – MR perfusion showed markedly increased cerebral blood flow (CBF) in the left temporoparietal lobe (Fig-1 C, D) with corresponding diffusion restriction (Fig-1B). Repeat imaging two weeks after the seizure control showed complete resolution (Fig-2) suggesting the imaging abnormalities to be a peri-ictal phenomenon.1 ASL-MR perfusion is a highly sensitive marker of increased CBF with its emerging application in distinguishing tumor progression (increased CBF) from post-treatment changes such as radiation necrosis (reduced CBF).1,2 This case highlights the utility of ASL-MR perfusion in differentiating peri/post-ictal phenomenon (increased CBF without T1-contrast enhancement) from tumor progression (increased CBF with T1-contrast enhancement) when employed routinely in clinical oncology practice.
NIMG-10. THE ROLE OF FIBROBLAST ACTIVATION PROTEIN IN GLIOBLASTOMA AND GLIOSARCOMA – A COMPARISON OF TISSUE, 68GA-FAPI-46 POSITRON EMISSION TOMOGRAPHY AND SURVIVAL DATA
Authors: Oster Christoph , Kessler Lukas , Blau Tobias , Keyvani Kathy , Pabst Kim M , Fendler Wolfgang P , Costa Pedro Fragoso , Lazaridis Lazaros , Schmidt Teresa , Feldheim Jonas , Pierscianek Daniela , Schildhaus Hans-Ulrich , Sure Ulrich , Ahmadipour Yahya , Kleinschnitz Christoph , Guberina Nika , Stuschke Martin , Deuschl Cornelius , Scheffler Björn , Herrmann Ken , Kebir Sied , Glas Martin
Published: November 2024

BACKGROUND

Despite their unique histological features,gliosarcomas belong to the group of glioblastomas and are treated according to the same standards. Fibroblast-activation-protein(FAP) is a component of a tumor-specific subpopulation of fibroblasts that play a critical role in tumor growth and invasion.However,the prognostic impact of FAP in glioblastoma and gliosarcoma is unclear.

METHODS

In a retrospective analysis,patients diagnosed with glioblastoma without sarcomatous differentiation and gliosarcoma were enrolled.Histological examination was performed using immunohistochemical FAP-staining and quantitative analysis with a standardized FAP-score.In a subset of patients,FAPI46-PET has been performed.The SUV-values are planned to be correlated with FAP-expression in the tumor tissue.Data obtained from immunohistochemical analysis and SUV-values are planned to be brought into perspective with clinically relevant prognostic factors,including survival estimates.

RESULTS

We enrolled 61 patients,including 13 diagnosed with gliosarcoma.Our analysis revealed that gliosarcomas exhibit significantly higher FAP-expression (median FAP-score: 3) compared to glioblastomas without sarcomatous differentiation (median FAP-score: 0.5, p<0.0001),where FAP was predominantly observed in the perivascular space.In gliosarcomas,FAP was also expressed by neoplastic cells.Moreover,a significant relationship was established between the immunohistochemical FAP-scores and the SUVmean and SUVpeak values on PET,suggesting that the PET tracer uptake accurately reflects the tumor’s FAP-expression.However,the differential expression of FAP suggests its potential as both a diagnostic marker and a therapeutic target.This hypothesis is further supported by the application of 68Ga-FAPI-46-PET in a 66-year-old female patient with recurrent gliosarcoma,alongside immunohistochemical analysis of tumor tissue.Both methods identified elevated FAP-expression and uptake,underscoring the feasibility of FAP as a target for nuclear medicine therapies in brain tumors.

CONCLUSIONS

Our study establishes a significant correlation between SUVmean/SUVpeak in 68Ga-FAPI-46 PET scans and FAP-expression in glioblastoma.Gliosarcomas express significantly more FAP than other glioblastomas. These insights suggest FAP’s potential as a theranostic target.We plan to investigate the effectiveness of FAP-specific tracers in treating recurrent gliosarcoma,aiming to open new therapeutic avenues.
NIMG-17. PREDICTIVE VALUE OF THE BRAIN TUMOR REPORTING AND DATA SYSTEM SCORE (BT-RADS) ON FUNCTIONAL OUTCOMES AND PROGRESSION-FREE SURVIVAL IN GLIOBLASTOMA PATIENTS
Authors: Persico Michele , Assaye Tsion , Essien Michael , Weinberg Brent
Published: November 2024

The Brain Tumor Reporting and Data System Score (BT-RADS) is a novel eight-point classification system that standardizes magnetic resonance imaging (MRI) reporting in glioblastoma (GB) patients. While previous studies have demonstrated BT-RADS predictive value in the prognosis and overall survival of high-grade glioma patients, its association with functional outcomes and progression-free survival (PFS) in GB patients is unclear. We aim to evaluate the BT-RADS predictive value on functional outcomes assessed through the Karnofsky Performance Scale (KPS) at one year post-diagnosis and on PFS. BT-RADS from MRI ~3 months post-diagnosis after chemo-radiation therapy (BT-RADS_1), and ~6 months post-diagnosis after the 6-month maintenance temozolomide (TMZ) cycle (BT-RADS_2) were analyzed. BT-RADS was classified as low (BT-RADS score 0-3a) and high (BT-RADS score 3b-4). In a univariate logistic regression analysis, BT-RADS_1 was a significant predictor (p=0.04) in discriminating an unfavorable KPS from a favorable one. In a multivariate logistic regression, in which the best model fit was the model containing BT-RADS_1 and MGMT tumor status (model p value=0.03), the ROC analyses indicate that BT-RADS_1 is not better than chance in differentiating an unfavorable KPS from a favorable one (model AUC=0.65; 95% CI=0.55, 0.76). The discriminatory ability of BT-RADS scores alone in predicting KPS outcomes was modest, as indicated by the AUC. This underscores the need for larger sample sizes. In a final model of BTRADS_1 and BT-RADS_2, accounting for MGMT tumor status, the risk of tumor progression was 50% lower (p value=0.003) with a low BT-RADS (0-3a) in the BT-RADS _1 group and 38% lower (p value=0.03) with a low BT-RADS (0-3a) in the BT-RADS_2 group. Considering the above-discussed findings, BT-RADS may represent a new tool in the clinical management of glioblastoma patients by informing on disease progression, prognosis, and quality of life.
NIMG-19. DEUTERIUM METABOLIC IMAGING INTERROGATES THE HISTONE H3K27M MUTATION AND PROVIDES AN EARLY READOUT OF RESPONSE TO THERAPY IN DIFFUSE MIDLINE GLIOMAS
Authors: Taglang Celine , Batsios Georgios , Udutha Suresh , Gillespie Anne Marie , Lau Benison , Ji Sunjong , Mueller Sabine , Phoenix Timothy , Venneti Sriram , Koschmann Carl , Viswanath Pavithra
Published: November 2024

Diffuse midline gliomas (DMGs) are lethal primary brain tumors in children that are driven by recurrent lysine 27 to methionine mutations in histone H3 (H3K27M). Radiation is standard of care and the imipridones ONC201 and ONC206 have emerged as promising therapies for DMG patients. Although magnetic resonance imaging (MRI) is the mainstay for patient management, it does not reliably assess response to therapy. Therefore, the goal of this study was to identify metabolic alterations induced by H3K27M that can be leveraged for non-invasive metabolic imaging of DMGs. Using patient-derived (BT245, SF8628, SF7761, SU-DIPG-6, DIPG7, SU-DIPG-13) and syngeneic (26-B7, 26-C2) models, we show that the H3K27M mutation upregulates glucose metabolism via glycolysis to lactate. Silencing the H3K27M mutation reduces glycolytic capacity and depletes lactate, an effect that is associated with downregulation of rate-limiting glycolytic enzymes and transporters (SLC2A1, HK2, PFKFB3, PGK1, SLC16A3). Deuterium metabolic imaging (DMI) is a novel, clinical stage method of tracing glucose metabolism in vivo. Our studies show that lactate production from [6,6-2H]-glucose is spatially localized to tumor vs. normal brain in mice bearing intracranial BT245, SF8628 or 26-B7 xenografts at clinical magnetic field strength (3T). Lactate production from [6,6’-2H]-glucose is reduced in patient-derived (BT245, SF8628, SF7761) or syngeneic (26-B7) cells treated with radiation, ONC201 or ONC206. Importantly, lactate production is reduced at an early timepoint (5 days) following treatment with ONC206, when changes cannot be detected by MRI, in mice bearing intracranial BT245 or SF8628 xenografts. Collectively, our studies link the H3K27M mutation with elevated glycolysis and identify [6,6’-2H]-glucose as a safe, orally administered contrast agent for visualizing the metabolically active lesion and for imaging early response to therapy in DMGs in vivo. Clinical translation of our studies will provide physicians with a much-needed tool to determine whether DMG patients are responding to standard and experimental therapies under development.
NIMG-20. DWIBS FOR PRIMARY CANCER DETECTION IN INTRACRANIAL METASTASIS: TWO CASE REPORTS
Authors: Koyahara Yuki , Saito Norihiko , Hirai Nozomi , Hiramoto Yu , Fujita Satoshi , Nakayama Haruo , Hayashi Morito , Ito Keisuke , Iwabuchi Satoshi
Published: November 2024

INTRODUCTION

Diffusion Weighted Whole Body Imaging with background body signal Suppression (DWIBS) is an imaging technique that encompasses comprehensive imaging of the entire body through diffusion-weighted imaging (DWI). In recent years, it has been increasingly utilized for investigating the etiology of fever or primary cancer. Here we present two cases of DWIBS for searching for primary cancer in patient with intracranial metastasis.

CASE PRESENTATION

Case1: A 60-year-old man presented with headache and diplopia and was admitted to our hospital. MRI revealed a tumor in the clivus exhibiting contrast enhancement. Endoscopic transsphenoidal surgery confirmed the diagnosis of squamous cell carcinoma. DWIBS demonstrated high intensity in a region similar to the esophagus seen on contrast-enhanced CT, leading to the diagnosis of brain metastasis from esophageal cancer. Case 2: A 50-year-old man presented with left facial paralysis and left hemiplegia and was admitted to our hospital. MRI revealed a tumor in the right middle frontal gyrus. Craniotomy confirmed the diagnosis of adenocarcinoma. Although the primary cancer remained unidentified upon initial examination, subsequent investigations revealed it originated from the lung. DWIBS showed high intensity in a region similar to the lung.

DISCUSSION

While FDG-PET is commonly utilized for cancer detection, its invasiveness and limitations prompt consideration of alternative modalities such as DWIBS. Recently there are some studies that have shown DWIBS to be superior to FDG PET in detecting esophageal and lung cancers. Thus, DWIBS may serve as a viable option for primary cancer screening in hospitals or communities where access to FDG PET is limited.

CONCLUSION

Its non-invasive nature makes DWIBS an appealing option for primary cancer detection, and further advancements are anticipated.
NIMG-26. GLIOBLASTOMA TISSUE INVASION MAPPING WITH NOVEL HYPOXIA-TARGETED BLOOD OXYGENATION-LEVEL DEPENDENT MRI
Authors: Stumpo Vittorio , Bellomo Jacopo , van Niftrik Christiaan Hendrick Bas , Sebök Martina , Kulcsar Zsolt , Weller Michael , Bink Andrea , Regli Luca , Fierstra Jorn
Published: November 2024

BACKGROUND

Glioblastoma is a devastating incurable malignant primary brain tumor exhibiting an erratic growth pattern and brain tissue invasion exceeding the typically depicted contrast-enhancing lesion on MRI. This behaviour is strongly associated with the presence of aberrant vasculature. Advanced clinical neuroimaging techniques, however, have not provided convincing imaging markers to determine glioblastoma tissue infiltration and monitor treatment effects. We investigated a new imaging technique based on blood oxygenation-level dependent (BOLD) MRI contrast with precise hypoxic respiratory targeting in order to better determine tumor tissue invasion not restricted to the typically depicted focal glioblastoma lesion on contrast-enhanced MRI.

METHODS

A computer-controlled gas blender was used to induce transient and standardized hypoxic stimulus in isocapnic conditions during echo-planar-imaging acquisition in patients with brain tumors.8,9 Data were preprocessed using SPM and in-house written MATLAB scripts. The induced BOLD signal changes were used to calculate %BOLD signal change during hypoxic stimulus with respect to the baseline, contrast to noise (CNR) ratio and goodness-of-fit (Rsquared) for each voxel in the whole-brain and automatically segmented region of interest (contrast-enhancement, necrosis, edema) and overlayed using color-maps onto anatomical high resolution T1.

RESULTS

Hypoxic targeting during gas modulation could be performed with high reproducibility, caused no discomfort in patients with brain tumors and was able to induce strong signal change during hypoxic stimulus with high contrast-noise ratio and Rsquared. In particular, when compared with other tumors, BOLD hypoxia glioblastoma tissue invasion maps show very distinct hypoxic signal responses in some cases extending beyond the focal -contrast-enhancing- glioblastoma lesion.

CONCLUSION

The ability to map at voxel level BOLD hypoxia signal patterns may determine a novel therapeutic imaging marker based on structural vascular alterations in the tumour tissue infiltration zone before these become appreciable with standard neuroimaging. This may support a refinement and tailoring of tumor resection and improve follow-up after resection and during treatment i.e. chemoradiotherapy.
NIMG-38. DIAGNOSIS AND TREATMENT OF BRAIN TUMORS USING METHIONINE PET
Authors: Shiba Yoshiki , Maeda Sachi , Yamaguchi Junya , Deguchi Shoichi , Ohka Fumiharu , Saito Ryuta
Published: November 2024

INTRODUCTION

The usefulness of methionine PET examination in diagnosing brain tumors is widely recognized, and it is a frequently used examination method for distinguishing primary tumors from non-neoplastic lesions and recurrent lesions from radiation necrosis. In addition, during surgery, it has the property of being taken up by actively dividing tumor cells, which is useful for identifying the extent of resection. Method: Methionine PET examination was performed in 228 consecutive cases in our department from January 2021 to April 2023, and medical records and genetic analysis data were retrospectively analyzed.

RESULTS

Of the 228 cases, 146 cases provided useful data for clinical practice, such as the diagnosis of tumors and the differentiation of recurrent tumors from necrosis. On the other hand, there were 9 cases in which the pathological diagnosis of the resected specimen was “tumor” despite the lack of significant methionine accumulation. The details were astrocytoma, cavernous hemangioma, spinal ependymoma, etc. On the other hand, 26 cases were finally diagnosed as “non-neoplastic disease”. Of these, 13 cases had methionine accumulation. The details of the cases that were finally diagnosed as “non-neoplastic disease” were multiple sclerosis, cerebral infarction, dural arteriovenous fistula, inflammatory disease, etc. There were 12 cases in which a diagnosis of “neoplastic disease” was not revealed after methionine PET examination, and the patient was continuously observed. None of these 12 cases had an acute or malignant course.

CONCLUSION

Although methionine PET is considered useful for diagnosing neoplastic disease, there are cases in which there is no uptake, especially in astrocytoma, and a certain number of cases in which uptake was observed even in non-neoplastic diseases, so caution is required. In addition, in terms of treatment, it is possible to aim to improve surgical accuracy by integrating methionine PET images with intraoperative MRI and intraoperative molecular analysis techniques, and we report an example of this.
NIMG-40. RADIOMICS-BASED DIFFERENTIATION OF GLIOBLASTOMA AND METASTATIC DISEASE: DOES DIFFERENCE IN TYPE OF T1-CONTRAST ENHANCED SEQUENCE MATTER?
Authors: soni Neetu , Zamboni Camila , Agarwal Amit , Larson Nicholas B , Sonka Milan , Bathla Girish
Published: November 2024

BACKGROUND

To evaluate the radiomics-based model performance for differentiation between glioblastoma (GB) and intracranial metastatic disease (IMD) using magnetization prepared rapid gradient echo (MPRAGE) and volumetric interpolated breath-hold examination (VIBE) T1-contrast enhanced sequences.

MATERIALS AND METHODS

T1-CE MPRAGE and VIBE sequences acquired in 108 patients (31 GBs and 77 IMD) during the same MRI session were retrospectively evaluated. Post standardized image pre-processing and segmentation, radiomics features were extracted from necrotic and enhancing tumor components. A total of 90 machine learning (ML) pipelines were evaluated using a five-fold cross-validation. Performance was measured by mean AUC, Log-loss, and Brier scores. Pearson correlation analysis of radiomics features from tumor subcomponents was also performed.

RESULTS

The mean AUC across the top-ten pipelines varied between 0.890-0.851 with T1-CE MPRAGE and 0.907-0.869 with T1-CE VIBE sequence. Top performing models for the MPRAGE sequence commonly used support vector machines, while those for VIBE sequence used either support vector machines or random forest. Common feature reduction methods for top-performing models included linear combination filter and least absolute shrinkage and selection operator (LASSO) for both sequences. Only three of the top ten models used the same combination of feature reduction-ML algorithm pipeline. A feature-wise comparison showed that the radiomic features between sequences were strongly correlated, with the highest correlation for shape-based features.

CONCLUSION

Radiomics features derived from T1-CE MPRAGE and VIBE sequences may have similar overall classification performance for differentiating GB from IMD, albeit often using different feature selection-ML algorithm pipelines.
NIMG-42. ANALYSIS OF TUMOR RELAPSE PROBABILITY AND OVERALL SURVIVAL PREDICTION FOLLOWING TEMOZOLOMIDE CHEMORADIATION USING FET PET INCLUDING RADIOMICS IN PATIENTS WITH GLIOBLASTOMA
Authors: Stetter Isabelle , Werner Jan-Michael , Wollring Michael , Ceccon Garry , Lohmann Philipp , Ciantar Keith George , Stoffels Gabriele , Mottaghy Felix M , Fink Gereon R , Langen Karl-Josef , Galldiks Norbert
Published: November 2024

BACKGROUND

Early after surgery and completion of first-line concomitant chemoradiation with temozolomide, the evaluation of tumor relapse probability and overall survival prediction is of considerable interest for the management of patients with glioblastoma

METHODS

Sixty-three newly diagnosed patients with glioblastoma (age range, 19-82) who received static and dynamic PET imaging using the radiolabeled amino acid O-(2-[18F]fluoroethyl)-L-tyrosine (FET) after surgery or biopsy and completion of concomitant chemoradiation with temozolomide were evaluated. Static FET PET parameters such as maximum and mean tumor-to-brain ratios (TBRmax, TBRmean) and metabolic tumor volumes (MTV), and the dynamic FET PET parameter time-to-peak (TTP) were obtained. Additionally, FET PET radiomics features (n=1,303) were extracted for each patient and a test-retest analysis was performed to identify robust features prior to feature selection. The prognostic value of FET PET parameters and radiomics features was evaluated using receiver-operating-characteristic (ROC) analyses with regard to a significantly prolonged progression-free and overall survival (PFS, OS). Subsequently, univariate and multivariate survival estimates were performed to assess the prognostic value of these parameters to predict a significantly longer PFS and OS

RESULTS

ROC analyses revealed that the parameter TBRmax was a powerful parameter to predict both a significantly longer PFS (20.3 vs. 8.9 months; P=0.002; threshold, 2.75) and OS (34.9 vs. 18.7 months; P=0.005; threshold, 2.75). MTV had a similar prognostic value for both PFS (16.7 vs. 7.2 months; P=0.002; threshold, 34.0 mL) and OS (30.6 vs. 14.8 months; P=0.002; threshold, 32.6 mL). After feature selection, 3 of 15 selected radiomics features predicted a significantly longer PFS and OS in univariate analyses. TBRmax, MTV, and one of 15 radiomics features remained significant in multivariate survival analysis (all P≤0.03)

CONCLUSION

Our results suggest that FET PET and radiomics parameters were highly prognostic in this group of patients at an early stage of first-line therapy.
NIMG-46. UNDERSTANDING PERMEABILITY CHANGES IN VESTIBULAR SCHWANNOMAS AS PART OF THE DYNAMIC RESPONSE TO RADIOSURGERY USING GOLDEN-ANGLE RADIAL SPARSE PARALLEL IMAGING, A RETROSPECTIVE STUDY
Authors: Meng Ying , Lee Matthew D , Berger Assaf , Wiggins Roy , O’Callaghan James , Bernstein Kenneth , Santhumayor Brandon , Block Kai Tobias , Fatterpekar Girish , Kondziolka Douglas
Published: November 2024

Vestibular schwannomas demonstrate different responses after stereotactic radiosurgery (SRS), commonly including a transient loss of internal enhancement on post contrast T1-weighted MRI thought to be due to an early reduction in tumor vascularity. We used dynamic contrast-enhanced based golden-angle radial sparse parallel (GRASP) MRI to characterize the vascular permeability changes underlying this phenomenon, with correlations to long-term tumor regression. Consecutive patients with vestibular schwannoma who underwent SRS between 2017-2019, had a transient loss of enhancement after SRS, and had long-term longitudinal GRASP studies (6, 12, and 24-36 months) were included in this retrospective cohort analysis (n = 19). Using GRAVIS, an analysis pipeline for GRASP studies, we extracted the key parameters normalized to the venous sinus from a region of interest within the tumor. The peak, area under the curve (AUC), and wash-in phase slope were significantly reduced at 6, 12, and 24 months after SRS (corrected p < 0.05), even while the internal enhancement returned in the tumors. Larger pre-SRS tumors were more likely to have a greater reduction in peak (p = 0.013) and AUC (p = 0.029) at 6 months. In a subset of patients (N = 13) with long-term follow-up, the median percentage reduction in tumor volume was 58% at median 62 months. These patients showed a strong correlation between changes in peak, AUC, and wash-in phase slope at 6 months and tumor volume at last follow-up. After SRS and loss of internal contrast uptake within the vestibular schwannomas, a slow vascular permeability dynamic found on GRASP studies persisted, suggesting the internal development of scar tissue. Moreover, the degree of reduction in GRASP parameters at 6 months positively predicted the degree of tumor regression long-term.
NIMG-55. DEVELOPING A COMPUTATIONAL PIPELINE TO FORECAST AND SPATIALLY MAP HIGH-GRADE GLIOMA RESPONSE TO RADIOTHERAPY USING BIOPHYSICAL MODELS AND DATA-DRIVEN STATISTICAL ANALYSIS
Authors: Ty Sophia , Kowalski-Muegge Jeanne , Farhat Maguy , Panthi Bikash , Langshaw Holly , Shankar Mihir D , Talpur Wasif , Thrower Sara , Goldman Jodi , Custer James , Yankelov Thomas E , Chung Caroline , Hormuth, II David A
Published: November 2024

High-grade glioma (HGG) presents significant treatment challenges, particularly in identifying less responsive tumor areas to target with adaptive radiotherapy (RT). This study introduces a patient-specific computational pipeline designed to predict and spatially map HGG response to RT, focusing on regions demonstrating resilience to RT. Our computational pipeline is centered around a family of 3D biophysical models describing tumor cell invasion, proliferation, and response to RT which can be personalized for individual patients using longitudinal multiparametric MRI data. Utilizing longitudinal multiparametric MRI data reporting on cell density (diffusion weighted MRI) and the extent of disease (T2-FLAIR and contrast-enhanced T1-weighted MRIs) from 21 patients, ranging from baseline to three weeks into RT, we calibrated a family of biophysical models to forecast tumor cell density up to the final week of RT and one-month follow-up. By employing pareto tail analysis on empirical cumulative distribution function fits of voxel-wise changes in apparent diffusion coefficient maps (ΔADC) between the future images (end of RT, one-month follow-up) and pre-treatment images, we identified areas of increased tumor cellularity on both the ground truth and model predicted cellularity maps. The analysis differentiated tumor voxels into “non-responding” and “responding” categories, based on cutoffs determined through ROC analysis across various conditions—including assessments of both enhancing and non-enhancing tumor regions at different time points. Optimal ΔADC cutoffs for predicted and measured data were established, leading to high area under curve (AUC; ranging from 0.803 to 0.934) values and significant Youden’s index scores (ranging from 0.526 to 0.765) across all conditions. Our findings demonstrate the feasibility of this novel pipeline in delineating biologically relevant RT targets, offering a potential tool for enhancing the efficacy of adaptive RT strategies in treating HGG.