bluuebunny/crossref_metadata_2025_split huggingface dataset:
GCT-14. TREATMENT APPROACH FOR METASTATIC INTRACRANIAL GERMINOMA: A MULTI-INSTITUTIONAL EXPERIENCE
Authors: Power^ Phoebe C , Liu^ Kevin X , Chi Susan N , Wright Karen D , Marcus Karen J , Haas-Kogan Daphne A , Ebb David , Yock Torunn I , MacDonald* Shannon M , Yeo* Kee Kiat 
Published: June 2024

Abstract

BACKGROUND
Germinoma is the most common CNS germ cell tumor in children. Treatment with 24Gy craniospinal irradiation (CSI) with boost to 40Gy alone results in excellent survival irrespective of disease stage. For localized germinoma, recent studies have demonstrated the efficacy of neoadjuvant chemotherapy in decreasing the field/dose of radiation therapy (RT) needed for cure. For metastatic germinoma however, the optimal RT approach when combined with chemotherapy is unclear. Herein, we present our experience in treating patients with metastatic germinoma.

METHODS
We performed a retrospective, IRB-approved study of patients with metastatic germinoma diagnosed between 2001-2023 at Boston Children’s Hospital, Dana-Farber Cancer Institute, Brigham and Women’s Hospital, and Mass General Hospital. Clinical features, treatment plan, and outcomes were collected and analyzed using the Kaplan-Meier method and Fisher’s exact test.

RESULTS
Twenty-eight patients with metastatic germinoma were identified. Median age at diagnosis was 15.9 years (range:6.2-25.9). Metastasis was intracranial in 20, craniospinal in three and CSF-only in five patients. Six patients received CSI only. Twenty-two patients received neoadjuvant chemotherapy and CSI. Median number of chemotherapy cycles was 4 (range:3-6). Seventeen patients had complete response, four patients had partial response, and one patient had progressive disease with chemotherapy. All patients went on to receive CSI, with median dose of 21Gy (range:18-36Gy) with median IF boost to 36Gy (range:30-51.6Gy). Median duration of follow-up was 11 years (range:0.3-25.3). There were no recurrences or deaths within the cohort. Analysis of long-term outcomes data revealed no significant differences in frequency of endocrinopathies, CNS vasculopathies, or memory loss between the doses of RT.

CONCLUSIONS
Our data show that neoadjuvant chemotherapy followed by CSI is associated with excellent overall survival in patients with metastatic germinoma. Importantly, our experience suggests that in combination with neoadjuvant chemotherapy, 21Gy CSI may be sufficient as a curative dose in this patient population.
GCT-24. ISOLATED PITUITARY STALK THICKENING
Authors: Bennett Julie , Nobre Liana , Bouffet Eric , Maguire Bryan , Amirabadi Afsaneh , Hawkins Cynthia , Abla Oussama , Wasserman Jonathan , Ertl-Wagner Birgit , Bartels Ute 
Published: June 2024

Abstract

BACKGROUND
Few studies have examined predictive factors and outcome of isolated pituitary stalk thickening (iPST) in children. We aim to describe our institutional cohort to determine predictors of future proliferative disease.

METHODS
A search of the radiology, endocrinology and neuro-oncology databases was performed to identify patients with iPST diagnosed between January 2000 and June 2019. Clinical data was collected along with detailed radiology review of MRIs in a blinded fashion.

RESULTS
Forty-seven patients were identified, with 40 meeting criteria for inclusion. Median age of baseline MRI was 9.6 years (range 0.9-17.5). Twenty-five (63%) were female. Median follow up time was 5.2 years (range 0.3-18.6). Indication for MRI was symptoms of diabetes insipidus (DI) in 29 patients followed by concerns for anterior endocrine disturbance (6), headache (1) or visual impairment (1). Thirty-four (85%) subjects had pituitary dysfunction, including 31 with DI however DI was not predictive of future development of proliferative disease (69% with presumed hypophysitis vs 93% with proliferative disease, p=0.12). Fourteen (35%) patients developed proliferative disease, with germinoma (8), Langerhans cell histiocytosis (5) and lymphoma (1) at median of 1.3 years (range 0.3-4.0), 2.2 years (range 0.3-9.4) and 1.1 years after initial MRI respectively. Lumbar puncture was performed in 24 patients with elevated white blood cell count (&gt;5 x 106/L) found in 6 (75%) patients with germinoma, 1 (100%) patient with lymphoma, 0 patients with LCH and 3 of 11 (27%) patients with presumed hypophysitis (p=0.015). Thickening of the entire stalk at time of diagnosis and radiographic progression were more likely to be seen in those that developed proliferative disease.

CONCLUSION
In this cohort 35% of children with PST were eventually diagnosed with a proliferative disease. Importantly, central DI was not associated with risk of proliferative disease. Several radiographic features and elevated CSF WBC were predictive of this outcome.
HGG-08. DIFFUSE HEMISPHERIC GLIOMA, H3 G34-MUTANT: A MULTI-INSTITUTIONAL EXPERIENCE
Authors: Tlais Dana , Roach Jordan T , Tinkle Christopher L , Zhang Qunyu , Li Xiaoyu , Lin Tong , McNall-Knapp Rene Y , Rush Sarah Z , Le Brian H , Sinno Sara , Agarwal Apeksha , Ginn Kevin F , Green Richard M , Onar-Thomas Arzu , Bag Asim K , Chiang Jason 
Published: June 2024

Abstract

BACKGROUND
Diffuse hemispheric glioma (DHG), H3 G34-mutant, is a rare, aggressive brain tumor molecularly defined by mutations in the H3-3A gene. Our study explored the association between patient outcomes and key molecular findings, resection extent, and temozolomide (TMZ) use.

METHODS
Multi-institutional chart and molecular analysis of 32 patients with H3 G34-mutant DHG.

RESULTS
The median patient age was 14 (10-28 years), with a M/F ratio of 1.4. The 1-year, 2-year, and 5-year PFS were 40.4% (23.7%, 57.1%), 22.1% (9.0%, 38.7%), and 11.0% (1.9%, 33.7%), respectively. The 1-year, 2-year, and 5-year OS were 82.5% (63.2%, 92.3%), 49.3% (28.7%, 66.3%), and 29.6% (9.1%, 50.6%), respectively. Patients who underwent a gross total resection (GTR) had improved PFS (p=0.0105) and OS (p=0.0184) compared to non-GTR patients. 22 patients (68.8%) received concurrent and/or adjuvant TMZ and had improved PFS (p=0.0278) compared to patients who did not receive front-line TMZ. Disease recurrence in relation to the radiation therapy (RT) field was analyzed in 17 patients; 5 recurred locally within the high-dose RT field, 5 recurred distantly, and 7 had both local and distant recurrences. There was no significant association between MGMT promoter methylation status (18 evaluable cases), PDGFRA amplification (N=6), and CDKN2A homozygous deletion (N=10) and survival outcomes. MGMT promoter methylation was not associated with increased TMZ efficacy (N=8 with MGMT silencing, N=4 without).

CONCLUSIONS
In our cohort, MGMT promoter methylation was not a favorable prognostic factor, in distinction from prior reports in adult and pediatric high-grade gliomas. Resection extent and the use of TMZ were associated with improved survival outcomes. As most treatment failures occurred within the high-dose RT field, extended fields do not appear warranted. Our findings may guide prognostic and therapeutic decisions in patients with H3 G34-mutant DHG and support the need for prospective efforts to improve outcomes in this patient population.
HGG-22. LINKS BETWEEN M6A RNA METHYLATION, R-LOOPS AND DNA DAMAGE IN PAEDIATRIC HIGH-GRADE GLIOMAS
Authors: Walker Lauryn , Radhi Masar , Knight Helen , Smith Stuart 
Published: June 2024

Abstract

BACKGROUND
Paediatric high-grade gliomas (pHGG) are aggressive malignant tumours of the central nervous system that unfortunately carry poor prognoses. R-loops, which are DNA:RNA hybrids, are a known source of genomic instability in eukaryotic cells. The RNA strand of R-loops can be m6A methylated at double-strand break sites in order to facilitate DNA repair. Therefore, we investigated whether dysregulation of m6A methylation and R-loop homeostasis at DNA damage sites deregulates DNA repair pathways in pHGG.

METHODS
Immunocytochemistry was performed to assess global m6A, R-loop, γH2AX and several DNA repair protein levels in pHGG cell lines compared to human astrocytes. Colocalisation between m6A and R-loops, R-loops and γH2AX, m6A and γH2AX, R-loops and 53BP1, R-loops and PARP1, R-loops and total ATM, and R-loops and phosphorylated ATM was assessed in pHGG cell lines and human astrocytes.

RESULTS
Immunocytochemistry analysis revealed that levels of global m6A, R-loop, γH2AX and several DNA repair proteins were generally higher in pHGG cell lines, thereby indicating that cellular homeostasis is dysregulated. Furthermore, a high degree of colocalisation between m6A and R-loops was observed. R-loops were found to colocalise with γH2AX, and m6A was found to colocalise with γH2AX, thereby corroborating the notion that m6A methylated R-loops are likely present at DNA damage sites. Finally, R-loops were also found to colocalise with a variety of DNA repair proteins, including 53BP1, PARP1, total ATM, and phosphorylated ATM, where different Pearson’s correlation coefficient values were obtained, thereby suggesting that R-loops associate with DNA repair proteins to different extents.

CONCLUSIONS
The link between m6A methylation, R-loops and DNA damage in relation to the pathogenesis of pHGG is currently being investigated. Experiments are also being performed where we are investigating m6A readers to see whether their aberrant expression contributes to disease pathogenesis via deregulating DNA repair pathways.
HGG-35. SIGNIFICANT RESPONSE TO LAROTRECTINIB AS FIRST LINE THERAPY IN INFANT WITH INFANT-TYPE HEMISPHERIC GLIOMA
Authors: Rocco Abbey , Brossier Nicole M , Shatara Margaret , Abdelbaki Mohamed , Strahle Jennifer , Cluster Andrew S 
Published: June 2024

Abstract

BACKGROUND
Infant-type hemispheric gliomas represent a recent WHO classification of high grade pediatric brain tumors that are often characterized by NTRK, ROS1, MET or ALK fusions. Novel agents may target their driver mutations but are not yet considered front line therapy.

METHODS
Patient data was reviewed retrospectively through chart review.

RESULTS
A 7 day old male infant who presented with vomiting, shaking and a full fontanelle was found to have a 8.7 x 7.2 x 9.3 cm solid and cystic mass with internal hemorrhage in the right parietal and occipital lobes associated with significant mass effect and midline shift. He underwent VP shunt placement and tumor biopsy, but later developed seizures and declining mental status. Cyst decompression was used as stabilizing measure. Due to his very small size and tenuous clinical status full tumor resection was not feasible at that time. Pathology revealed an infant-type hemispheric glioma with ETV6-NTRK3 fusion. Although cytogenetic testing for NTRK alterations was negative, the fusion was confirmed by NGS. Given his age and the risks for electrolyte imbalances and cytopenias in a patient with recent hemorrhage, we elected to treat with Larotrectinib instead of traditional cytotoxic chemotherapy. He had notable disease response within 8 weeks and remains on drug 18 months later with continued response. His tumor now measures 2 x 1.5 x 1.6 cm. He has had one grade 3 toxicity with neutropenia, which was likely impacted by viral bone marrow suppression. He is currently meeting most developmental milestones but does have orthotics and sees speech therapy.

CONCLUSIONS
Targeted agents may represent a viable front line therapy to decrease tumor mass and temporize very young patients until they can undergo definitive resection and therapy. Future clinical trials will need to compare efficacy to current standards of care.
IMG-02. USING MRI RADIOMICS AND MACHINE LEARNING TO PREDICT OVERALL SURVIVAL FOR PEDIATRIC DIFFUSE MIDLINE GLIOMAS
Authors: Liu Xinyang , Jiang Zhifan , Roth Holger R , Anwar Syed M , Bonner Erin R , Packer Roger J , Kazerooni Anahita F , Bornhorst Miriam , Linguraru Marius George 
Published: June 2024

Abstract

BACKGROUND
Pediatric diffuse midline gliomas (DMG) are aggressive central nervous system tumors with a median overall survival (OS) of less than one year from diagnosis. There is no curative therapy for DMG, and radiation therapy (RT) is the standard treatment. Magnetic resonance imaging (MRI) is the common noninvasive tool for DMG diagnosis and monitoring of tumor response to therapy. We developed an automatic pipeline to segment subregions of DMG and select MRI features that predict patient OS.

METHODS
We acquired diagnostic and post-RT multisequence MRI (T1, T1ce, T2, T2 FLAIR) and manual segmentations of pediatric DMG patients from two centers: 53 from Children’s National Hospital (internal) and 16 from Children’s Hospital of Philadelphia (external). We pretrained a deep learning model on a public adult brain tumor dataset, and finetuned the model to segment tumor core (TC) and whole tumor (WT) of DMG. We used PyRadiomics and sequential feature selection to select discriminative features based on the segmented volumes. Two machine learning models were trained on our internal cohort to predict patient 1-year survival from diagnosis. One model used only diagnostic tumor features and the other used both diagnostic and post-RT features.

RESULTS
For segmentation, Dice score (mean [median]±SD) was 0.91 (0.94)±0.12 and 0.74 (0.83)±0.32 for TC, and 0.88 (0.91)±0.07 and 0.86 (0.89)±0.06 for WT for internal and external cohorts, respectively. For OS prediction, accuracy was 77% and 81% at time of diagnosis, and 85% and 78% post-RT for internal and external cohorts, respectively. Heterogeneous WT intensity in baseline T2 FLAIR and smaller post-RT TC/WT volume ratio indicate longer OS.

CONCLUSIONS
Our method accurately predict OS for DMG patients and can be extended to other rare pediatric brain tumors. With automated and standardized analysis, early prognostication of OS can guide patient risk stratification and clinical decisions.
IMG-13. PREDICTION OF PEDIATRIC MEDULLOBLASTOMA SUBGROUPS USING CLINICO-RADIOMIC ANALYSIS
Authors: Familiar Ariana M , Kazerooni Anahita Fathi , Kraya Adam , Rathi Komal , Khalili Nastaran , Gandhi Deep , Anderson Hannah , Mahtabfar Aria , Ware Jeffrey B , Vossough Arastoo , Storm Phillip B , Resnick Adam C , Nabavizadeh Ali 
Published: June 2024

Abstract

BACKGROUND
Pediatric medulloblastoma is an aggressive brain tumor and tailored treatment has the potential to lead to better patient outcomes. The WHO 2021 classification of medulloblastoma involves an integrated diagnosis that incorporates genetically defined characteristics, including molecular subgroups (WNT-activated, SHH-activated TP53 wildtype, SHH-activated TP53-mutant, and non-WNT/non-SHH). Clinically acquired radiology (MRI) imaging characteristics could provide a non-invasive, pre-treatment biomarker for such subgroups faster than standard methylation-based turn-around times, and for use in countries where methylation is not available.

METHODS
Herein, we utilize a multi-institutional dataset of multi-parametric, clinical MRIs of pediatric medulloblastoma patients from the Children’s Brain Tumor Network (median age = 8.9 years) to assess the predictive value of patient-level radiomic and clinical factors. 89 subjects with treatment-naïve T1w/T1w contrast-enhanced/T2w/FLAIR images and molecular subgroups (derived from methylation profiling or RNA sequencing) were included (SHH=18, WNT=10, non-SHH/WNT=61). Radiomic features were extracted from a radiologist-defined volumetric (3D) segmentation for each subject separately (including solid tumor, cystic, and peritumoral edema regions). Clinical variables included sex, age at diagnosis, and metastatic disease. 20 top performing features were selected based on an ANOVA between features/classes and subsequently used to train and evaluate three separate classification models based on radiomic, clinical, or clinico-radiomic features (Linear SVM; leave-one-subject-out cross-validation).

RESULTS
The combined clinico-radiomic model had the top performance (AUC=0.83) followed by radiomic (0.78) and clinical (0.5) for predicting SHH/WNT vs. non-SHH/WNT groups. Predictive radiomic features included intensity-based statistics (T1w, T2w, T1w-CE), texture (T2w), and morphological shape characteristics.

CONCLUSIONS
Our findings show potential for early prediction of molecular subgroups using baseline imaging that could lend to faster decision-making in patient treatment planning. Future work aims to evaluate the inclusion of histological characteristics for a full integrated diagnostic approach as well as assessment of prognostic value of the combined multi-omic features.
IMG-15. A STRATEGIC FLOWCHART FOR PREOPERATIVE IMAGING IN PEDIATRIC POSTERIOR FOSSA TUMORS
Authors: Gonçalves Fabrício G , Marecha Mario , Cerron-Vela Carmen , Yildiz Harun , Dias Tassiana Cristhina S , Bathia Aashim 
Published: June 2024

Abstract

BACKGROUND
This comprehensive study delves into pediatric posterior fossa tumors (PFTs), focusing on both common and rare types, including pseudoneoplasms. The aim is to understand the diagnostic challenges of these less typical tumors, enhancing knowledge beyond usual pathologies. A detailed flow chart has been created to aid in accurate preoperative diagnoses.

METHODS
The study examines neuroimaging data, primarily from MRI and CT scans, collected from various clinical studies and case reports. It concentrates on identifying unique imaging characteristics of rare PFTs and pseudoneoplasms. The flow chart considers lesion location in various anatomical areas of the posterior fossa and factors such as lesion localization, MRI details (including DWI), and patient age. It also emphasizes the identification of cells in the posterior fossa that can lead to tumors, including osseous tissue cells, dura mater cells, arachnoid cells, pia mater cells, various glial cells, neurons, and choroid plexus cells.

RESULTS
The study reveals distinct imaging features of less common PFTs and pseudoneoplasms, critical for differentiating them from more common tumors. Advanced imaging techniques are highlighted as essential for improving diagnostic accuracy, impacting clinical management and treatment decisions. The review also discusses the varied presentation of tumors and the challenges this poses to standard diagnostic methods.

CONCLUSIONS
Understanding the imaging characteristics of rare PFTs and pseudoneoplasms, especially in children, is vital. This thorough analysis enhances diagnostic accuracy and influences treatment approaches, potentially improving patient outcomes. The study underscores the necessity of combining clinical observations with advanced imaging for precise diagnoses in atypical cases. This approach is crucial for healthcare professionals managing pediatric PFTs, leading to better clinical decisions and advancing pediatric neuro-oncology.
IMG-25. PREDICTING ANATOMICAL TUMOR GROWTH IN PEDIATRIC HIGH-GRADE GLIOMAS VIA DENOISING DIFFUSION MODELS
Authors: Laslo Daria , Monzon Maria , Ramakrishnan Divya , von Reppert Marc , Stoller Schuyler , Stücklin Ana Sofia Guerreiro , Gerber Nicolas U , Rauschecker Andreas , Nazarian Javad , Mueller Sabine , Jutzeler Catherine R , Brüningk Sarah C 
Published: June 2024

Abstract

BACKGROUND
Pediatric diffuse midline glioma (DMG) has a poor prognosis with radiotherapy as the standard of palliative care. Radiation strategies using individual geometric doseshaping have the potential to maximize patient benefit. This study aimed to establish a proof-of-principle to generate clinically relevant anatomical representations of the progression of pediatric DMG magnetic resonance image (MRI) slices through denoising diffusion implicit models (DDIM).

METHODS
Based on the BraTS23 data, we analyzed the generation of MRIs with enlarged tumor sizes starting from a baseline scan. Models were pre-trained on adult glioblastoma (GBM) prior to transfer learning on pediatric high-grade glioma. Test set performance was evaluated using the Frechet Inception Distance (FID), and Structural Similarity Index (SSIM). Qualitative evaluation involved visual classification of real vs generated images by two independent radiology trainees. The optimized network was tested to forecast anatomical tumor growth in five DMG patients from an independent dataset comprising longitudinal T2-FLAIR images.

RESULTS
We obtain high-fidelity generated images, supported by an FID of 12.4 and 0.8 SSIM on the adult test set. Despite the smaller pediatric BraTS dataset yielding a 34.8 FID and 0.84 SSIM, human observers failed to distinguish generated from real MRIs (mean recall and precision of 0.51). The generated anatomical predictions also closely resemble the observed longitudinal tumor progression in the pediatric DMG subset. Notably, the direction and extent of tumor growth align while the surrounding brain anatomy is preserved. Quantitatively, the mean DICE score between segmentations of generated and real tumors was 0.8.

CONCLUSIONS
Our model produces high-quality images that conform to growth patterns of pediatric DMGs. Further quantitative validation on larger longitudinal datasets is required, to ensure the method’s robustness. The proposed method enables a personalized approach for defining target regions in radiation therapy which could translate to improved clinical outcomes.
IMG-28. AUTOMATIC BRAIN TUMOR VOLUMETRIC ANALYSIS IN MAGNETIC RESONANCE IMAGING GENERALIZABLE TO PEDIATRIC NEURO-ONCOLOGY
Authors: Jiang Zhifan , Capellán-Martín Daniel , Parida Abhijeet , Liu Xinyang , Van Lam  , Nisar Hareem , Tapp Austin , Ledesma-Carbayo María J , Anwar Syed Muhammad , Linguraru Marius George 
Published: June 2024

Abstract

BACKGROUND
The prognosis of brain tumors is variable in clinical practice if it only relies on human interpretation of magnetic resonance imaging (MRI). The automatic segmentation of brain tumors in MRI enables quantitative analysis in support of clinical trials and personalized patient care. We developed benchmarked deep learning-based tools that are generalizable to the volumetric quantification of various tumor types across diverse populations.

METHODS
We participated in the well-established international brain tumor segmentation challenge (BraTS 2023) and benchmarking competition. The challenge made available 4,500 multi-national brain tumor cases with multi-sequence MRIs, including pediatric high-grade gliomas (PED), i.e., high-grade astrocytoma and diffuse midline glioma, and adult gliomas, brain metastases (MET) and intracranial meningiomas (MEN). Each case comprises four MRI volumes: T1, contrast-enhanced T1, T2, and T2-FLAIR. Manual segmentations were provided to establish ground truth for enhancing tumor (ET), tumor core (TC), and whole tumor (WT). Our framework used a model ensemble strategy based on two state-of-the-art deep learning models: a convolutional neural network (nnU-Net) and a vision transformer (Swin UNETR) and was tested for broader applicability across multiple tumor types. The framework was trained on 99, 1,000, and 165 cases and validated on 45, 141, and 31 unseen cases for PED, MEN, and MET, respectively. Automatic segmentations were evaluated by lesion-wise volume overlap (Dice similarity score, DSC) and Hausdorff distance (HD).

RESULTS
In the evaluation on independent unseen test datasets, our automatic tool was ranked first for PED, third for MEN, and fourth for MET volumetric analysis. Our method resulted in PED lesion-wise DSC of 0.733, 0.782, 0.817 and HD (mm) of 75.93, 25.54, 24.18 for ET, TC, and WT, respectively.

CONCLUSIONS
These brain tumor volumetric analysis tools are readily available to be efficiently tested on diverse datasets. Automatic MRI analysis provides consistent quantitative data for multi-institutional protocols and clinical trials.