bluuebunny/crossref_metadata_2025_split huggingface dataset:
DSAI-01 TUMOR EVOLUTION OF BRAIN-SPECIFIC TROPISM IN METASTATIC RENAL CELL CARCINOMA
Authors: Elias Roy , Kamson David , Feinaj Ardit , Pallavajjala Aparna , Yerrapragada Anirudh , Dreschner Max , Patel Sunil , Fertig Elana , Markowski Mark , Yegnasubramanian Srinivasan , Matoso Andres , Baraban Ezra , Bettegowda Chetan , Ged Yasser , Singla Nirmish 
Published: August 2024

Abstract

BACKGROUND
Herein, we describe the molecular landscape of renal cell carcinoma (RCC) brain metastases (BrMs).

METHODS
Panel-based DNA (DNAseq) and whole-transcriptome sequencing (RNAseq) were used to assess BrM, non-BrM and matched primary renal tumors (PRT) from RCC patients who underwent resection.

RESULTS
95samples (BrM=54, nBrM=14, PRT=27) from 53patients were included (85% clear-cell histology). DNAseq of 85 samples (50pts) identified common mutations in VHL (18pts, 36%), TP53 (24%), PBRM1 (24%), SETD2 (24%), and BAP1 (8%). MTOR-pathway mutations were enriched, with 25pts (50%) having at least one mutation in PTEN (12pts, 24%), TSC1 (8%), TSC2 (10%), or MTOR (18%). Copy number analyses revealed frequent deletions in chr14q21(34pts, 68%) and chr9p21 (70%) and gains in chr20q13 (62%) and chr7p15 (62%). At the sample-level, PTEN mutations were more common in BrM (11pts, 22.9%) versus non-BrM (0) and PRT (12%, p=0.124), as were deletions in chr13q22 (BrM=26.5% [13pts], non-BrM=8.3%, PRT=4%; p=0.036) and gains in chr20q13 (BrM=61.2% [30pts], non-BrM=33.3%, PRT=32%; p=0.03). Chr9p21 deletions were enriched in BrM (32pts, 65.3%) and non-BrM (66.7%) relative to PRTs (28%, p=0.006). Other copy number alterations and somatic mutations had similar distribution across sites. Analysis of 86 samples (51pts) identified 806 genes expressed differentially between BrM and PRT (adjusted p&lt;0.05), 399 between BrM and non-BrM (adj. p&lt;0.05). Gene set enrichment analysis of MSigDB Hallmark gene sets revealed upregulation of MTORC1 signaling, glycolysis, and MYC targets in BrM comparted to PRT and non-BrM (adj. p&lt;0.0001). Immune-related gene sets, e.g. interferon-alpha, interferon-gamma, TNF-alpha, were enriched in PRT relative to BrM (adj. p&lt;0.0001), but not non-BrM (adj. p &gt; 0.05). CIBERSORT cellular deconvolution analysis comparing BrM with PRT revealed increased proportions of M2 (p=0.0009), but decreased M1 macrophages (p=0.0003) and CD8+T-cells (p=0.0106).

CONCLUSIONS
RCC with BrM exhibit distinct MTOR-pathway enrichment and hyperactivation. The immunosuppressive milieu in BrM may be steroid-related. Further analyses are underway.
DSAI-04 AI-DRIVEN MR IMAGE FEATURES VERSUS RANO-BM CRITERIA IN DISTINGUISHING RECURRENT BRAIN METASTASES FROM RADIATION TREATMENT EFFECT: A COMPARATIVE, MULTI-INSTITUTIONAL STUDY
Authors: Um Hyemin , Ismail Marwa , Hill Virginia , Puri Sushant , Yu Jennifer , Lu Lan , Nayate Ameya , Rogers Lisa , Prasanna Prateek , Bardhan Mainak , Li Chengnan , Basree Mustafa , Baschnagel Andrew , McMillan Alan , Bhatia Ankush , Ahluwalia Manmeet , Veronesi Michael , Tiwari Pallavi 
Published: August 2024

Abstract
A significant challenge in brain metastases (BM) management is distinguishing radiation-induced treatment effect (TE) from tumor recurrence (TR). TE mimics the appearance of TR on follow-up MRI, making radiographic diagnosis unreliable. The standardized Response Assessment in Neuro-Oncology for brain metastases (RANO-BM) is suboptimal due to high inter-reader variability. We compared the performance of artificial intelligence (AI)-driven MRI features with that of RANO-BM criteria in differentiating TE from TR. We hypothesize AI-features from routine MRI can capture the pathophysiologic differences between TE and TR, occult on structural MRI and hence overlooked in standard-of-care evaluation. A total of 261 lesions with pathologically-confirmed diagnoses in 189 patients were retrospectively analyzed. 201 lesions (111 TR,90 TE) from Cleveland Clinic and University Hospitals, Cleveland were used for training a machine learning model. 60 lesions (33 TR,27 TE) from University of Wisconsin–Madison were used for model testing. MRI (Gd-T1w, T2w, FLAIR) were preprocessed, and lesions were expertly segmented into enhancing lesion, edema, and necrosis. 856 texture features were extracted from each sub-compartment, and a random forest classifier was employed for 3-fold cross-validation. Top-performing features and RANO-BM criteria were evaluated on the test set. Results show T1 features from edema were most discriminatory in differentiating TR from TE (training-AUC=0.86, test-accuracy=71.7%, test-sensitivity=78.8%). Using RANO-BM, 9 cases were excluded due to lack of longitudinal imaging to estimate lesion growth. Additionally, since no lesions decreased in sum of longest diameter, none were classified as partial response while the remaining 51 cases were classified as stable disease (n=14, (8 TR,6 TE)) or TR (n=37, accuracy=54.1%). Interestingly, 78.6% of the stable lesions were accurately classified using our AI-model as TE or TR, missing only 3 cases (2 TR,1 TE). Our results suggest AI-driven models on clinical MRI scans may reliably distinguish TR from TE, demonstrating potential utility in clinical practice.
DSAI-05 THE BRAIN TUMOR SEGMENTATION (BRATS-METS) CHALLENGE 2023: BRAIN METASTASIS SEGMENTATION ON PRE-TREATMENT MRI
Authors: Tahon Nourel hoda , Ashraf Nader , Moawad Ahmed , Janas Anastasia , Baid Ujjwal , Saluja Rachit , Velichko Yuri , Ramakrishnan Divya , Krantchev Kiril , Rudie Jeffrey , Bakas Spyridon , Aboian Mariam 
Published: August 2024

Abstract

PURPOSE
Clinical monitoring of metastatic disease to the brain using magnetic resonance imaging (MRI) can be laborious and time-consuming, particularly when multiple small metastases are involved and assessments are performed manually.

METHODS AND MATERIALS
The BraTS-METS 2023 dataset is acquired from varying MRI imaging quality across different vendors. The scans are pre-processed using different algorithms refined by a pool of annotators with different expertise. Two independent board-certified neuroradiologists finally reviewed the dataset. The datasets are divided into Training, validation, and testing. ASNR-MICCAI BraTS-METS 2023 challenge was evaluated based on Dice scores and Hausdorff distance for each lesion, including the whole tumor, enhancing tumor, and tumor core.

RESULTS
We received &gt; 2500 multi-parametric MRIs from 12 different institutions, which underwent preprocessing to wipe out all PHI, reorient, and be consistent with all BraTS space and header. Initial raw data were pre-segmented with three different algorithms and fused together to get a consensus pre-segmentation file. A pool of 150 annotators (with different experience and training levels in radiology) and 50 board-certified attendees were recruited through ASNR mass calls for volunteer announcements, Segmentation workshops, and the ASNR annual meeting campaign. Studies are first assigned to annotators, reviewed by 1-2 board-certified neuroradiologists, and then reviewed by a single senior neuroradiologist for consistency and quality control final check. Finalized segmentation files underwent quantitative QC check to ensure harmonized imaging parameters, headers, and masks. Training and Validation datasets are made available to the public through the BraTS-METS 2023 website. The whole project is part of the TCIA/NCI moonshot program.

CONCLUSION
: The MICCAI-ASNR BraTS-METS Challenge is an important initiative for developing accurate segmentation algorithms to detect small brain metastasis. It includes multi-institutional and international datasets in order to develop a general model applied to all patients with brain metastasis.
DSAI-07 DATA-DRIVEN MODELING OF EMERGING TRENDS AND COLLABORATIVE NETWORKS ACROSS BRAIN METASTASES RESEARCH: THE PAST DECADE OF INNOVATION
Authors: Durrani Sulaman , Cote Ian , Carpintieri Sabrina , Martinez Joseph , Metzler Ashley , Graciolli Joacir , Shah Ashish , Oermann Eric , Komotar Ricardo , Ivan Michael , Benjamin Carolina , Sheehan Jason , Kondziolka Douglas , Tecle Najib El 
Published: August 2024

Abstract
With recent significant growth in brain metastases literature output, more comprehensive research is necessary to understand emerging trends and novel methods of diagnosis and treatment. We aimed to address this by providing a contemporary systematic global analysis of emerging brain metastases research in the last decade while visually depicting the international collaborative environment among its researchers. Data mining was performed on all brain metastases publications across the last decade indexed in Elsevier’s Scopus database. Our Scopus search revealed 6,362 publications from 1,184 sources from 2013-2022. Of those, 252 were identified as high-impact articles with an annual citation rate (CR) &gt; 10. The compounded annual growth rate (CAGR) of brain metastases publications was 7.2% per year since 2013. There was an acceleration of scientific production, from 5.9% CAGR across 2013-2018 to 9.6% across 2019-2022. Authors per document increased from 7.2% to 8.5% while international co-authorships increased from 16.6% to 18.3% in the same periods, respectively. Recent trending topics were noted to be artificial intelligence, understanding the brain microenvironment, exosomes, novel mechanisms of diagnosis (such as circulating tumor cells), and targeted treatments. High-impact articles tended to revolve around specific therapies or biomarkers as opposed to general synopses. Clustering analysis revealed three separate pivotal collaborative communities centered around Brown PD/Sahgal A, Ahluwalia MS, and Wang Y, with Brown PD as most notable for high impact research. While the top institutional collaborative group centered around Mayo Clinic, the highest impact research centered around the Dana-Farber Cancer Institute. Sub-analyses revealed that studies involving multiple countries tended to have a higher impact. The median overall survival of brain metastases, by primary source, was illustrated across the last five decades. Overall, significant growth in scientific production is driven by the integration of novel technologies (such as artificial intelligence), interdisciplinary approaches, and collaboration across global communities.
IMUN-08 DURABLE RESPONSE TO IPILIMUMAB-NIVOLUMAB (IPI-NIVO) IN ANTI-PD1 REFRACTORY MERKEL CELL CARCINOMA WITH LEPTOMENINGEAL DISEASE PROGRESSION
Authors: Kennedy Lucy Boyce , Diaz Claudia Marcela , Cordova Christine , Dhawan Andrew , Balagamwala Ehsan , Koyfman Shlomo , You Jee Young , Chao Samuel , Suh John , Angelov Lilyana , Isaacs James , Ko Jennifer , Chan Timothy , Truong Thach-Giao 
Published: August 2024

Abstract
Leptomeningeal disease (LMD) is a rare complication of Merkel cell carcinoma (MCC), which has been described in limited case reports, none of which describe outcomes with IPI-NIVO. Here we describe a patient with PD-1 refractory MCC LMD with durable response to IPI-NIVO. A 69-year-old male diagnosed with stage IIIA MCC underwent left groin dissection and radiation. He developed recurrence in distant lymph nodes and started pembrolizumab (PEMBRO). Seven months after starting PEMBRO, he developed lower extremity weakness. Spine MRI showed LMD involving cauda equina. CSF testing detected tumor cells. Imaging did not show any recurrence aside from LMD. He received radiation to L1-S2 followed by IPI-NIVO. His LMD has remained clinically and radiographically stable 10 months after starting IPI-NIVO. Longitudinal circulating tumor DNA (ctDNA) monitoring demonstrated clearance both after starting PEMBRO and IPI-NIVO. ctDNA was detectable 5 weeks after starting PEMBRO and 5 months after starting IPI-NIVO and became undetectable 10 weeks after starting PEMBRO and again 8 months after starting IPI-NIVO. We prospectively collected peripheral blood at baseline prior to PEMBRO, when LMD developed, with cycle 3 IPI-NIVO, when he developed pneumonitis 4 months from cycle 1, and following CNS and systemic tumor clearance at 7 months from cycle 1 of IPI-NIVO with patient on maintenance NIVO alone. Peripheral flow cytometry, quantitative proteomics, and serum cytokines were used to characterize immune cell numbers and phenotypes in this exceptional responder. Kinetics of immune correlates, including CD33+HLADRlo, CD15+CD14-MDSC, CD57+ CD8+ T cells, showed distinctive changes during the clinical course. This case demonstrates unique response to IPI-NIVO with durable neurologic stability and confirmatory ctDNA clearance in a patient with PD-1 refractory MCC and less common CNS progression with documented LMD. Although the prognosis of MCC LMD is poor, this patient achieved an objective CNS response, and we reversed PD-1 resistance with IPI-NIVO.
MMOD-04 LASER INTERSTITIAL THERMAL THERAPY (LITT) AND IMMUNOTHERAPY SYNERGY FOR RECURRENT BRAIN CANCER: A SYSTEMATIC REVIEW AND META-ANALYSIS
Authors: Sharma Eshita , Sahin Oguz Kagan , Łajczak Paweł , Ahmed Aisha Rizwan , Silva Yasmin Picanço , Ayesha Ayesha , Chatterjee Anoushka , Raake Mohammed , Petry Iago Nathan Simon 
Published: August 2024

Abstract

BACKGROUND
The confluence of laser interstitial thermal therapy (LITT) with immunotherapeutic approaches represents a promising avenue for the management of recurrent brain metastases and glioblastoma. However, the potential synergy between these modalities prompts a thorough examination of their adverse effects. This meta-analysis seeks to evaluate the literature to elucidate the adverse effects associated with the combined use of LITT and immunotherapy in treating recurrent gliomas.

METHODS
Thorough systematic searches were performed on PubMed, Embase, and Web of Science databases using predefined search terms to identify pertinent studies. Inclusion criteria comprised case-control studies, cohort studies, and randomized controlled trials investigating the combined utilization of laser interstitial thermal therapy (LITT) with immunotherapy, among adult patients diagnosed with recurrent brain metastases and recurrent glioblastoma. Our analysis specifically targeted adverse events (AEs) as the primary outcome of interest.

RESULTS
Our systematic review included four studies, including one randomized controlled trial (RCT), one case-control study, and two prospective cohort studies, with a total of 162 patients. Utilizing a random effects model in STATA, we performed a single-arm analysis of adverse events experienced by 56 patients across 3 studies and reported the combination of LITT with immunotherapy for managing recurrent gliomas demonstrated no significant proportion of adverse effects (Proportion= 0.11, 95% CI= -0.02-0.25, P=0.09).

CONCLUSION
When evaluating adverse effects, the combined approach of LITT with immunotherapy in managing recurrent brain metastases and glioblastoma showed no notable significant percentage of patients incurring adverse events, thereby implying a potential comparable safety profile to conventional treatment modalities. However, further research is warranted to test differences in the incidence of adverse events from LITT with immunotherapy versus a control.
MMOD-05 THE IMPACT OF EGFR VARIANTS ON INTRACRANIAL PROGRESSION FREE SURVIVAL AND OVERALL SURVIVAL IN NSCLC PATIENTS WITH BRAIN METASTASES UNDERGOING STEREOTACTIC RADIOSURGERY
Authors: Burner Danielle , Leng Jim , Carpenter David , Chen Mark , Vaios Eugene , Alder Laura , Clarke Jeffrey , Green Michelle , Kelsey Christopher , Floyd Scott , Kirkpatrick John , Reitman Zachary , Mullikin Trey 
Published: August 2024

Abstract
Outcomes for patients with brain metastases (BM) from targetable epidermal growth factor receptor (EGFR) mutated non-small cell lung cancer (NSCLC) have been improved with tyrosine kinase inhibitors (TKIs). However, outcomes following stereotactic radiosurgery (SRS) for NSCLC BM patients with other pathogenic EGFR mutations and variants remain uncertain. We sought to characterize outcomes for NSCLC BM patients with pathogenic variants (PV) or variants of uncertain significance (VUS) in EGFR following SRS. We retrospectively identified 600 NSCLC BM patients who underwent an initial course of SRS during 2015- 2020. Demographic, clinical, genomic, and treatment characteristics were recorded. Intracranial progression-free survival (ICP-FS) and overall survival (OS) were estimated via the Kaplan Meier method. Median follow up was 9.6 months. 155 (25.8%) patients had actionable mutations, including in EGFR (112). Of those with EGFR mutations, next-generation sequencing (NGS) data was available for 65 patients. In patients with targetable EGFR mutations, 39 received pre-SRS and 69 received post-SRS treatment with a TKI, typically with a 1st/2nd generation TKI. Most patients (n=12/13) with EGFR VUS received (chemo)immunotherapy. OS was significantly better for patients with any EGFR mutation/variant compared to patients without a detected variant (median 21.1 mos vs 8.1 mos, p&lt;0.0001), however, there was no difference in ICP-FS. Patients with EGFR VUS had improved OS and ICP-FS compared to EGFR PVs (median 56.3 mos vs 19 mos, p=0.022) and (median 53.1 mos vs 7.7 mos, p=0.041), respectively. While patients with EGFR mutation/variants demonstrated improvement in OS, ICP-FS was likely limited by use of early generation TKIs with SRS. Notably, there was compelling improvement in OS and ICP-FS associated with EGFR VUS, which is hypothesis generating and requires a larger cohort for further examination.
MMOD-11 RADIATION NECROSIS AFTER CONCOMITANT EGFR-TKI AND RADIATION: A CASE SERIES AND CONSIDERATION FOR FUTURE PATIENTS
Authors: Fritz Kelly , Malani Rachna 
Published: August 2024

Abstract
Optimal timing of radiation therapy (RT) for brain metastases (BM) and leptomeningeal disease (LMD) from novel targeted systemic therapy is largely unknown, as well as the long-term adverse effects of combination therapy. We describe the clinical course of two patients who developed radiation necrosis (RN) after RT and treatment with EGFR-TKIs. The first patient is a 79-year-old woman with EGFR L858R-mutated metastatic non-small cell lung cancer (NSCLC) who developed progressive BM after being on osimertinib therapy for 3 years. She received stereotactic radiosurgery (SRS) to 5 lesions. Osimertinib was held for 3 days surrounding SRS, and resumed at 80 mg/day. Four months post SRS, the patient developed progressive neurologic symptoms with neuroimaging consistent with RN. She was initiated on dexamethasone however after a 6 week taper, she experienced neurologic decline with repeat neuro-imaging demonstrating worsening RN. She started on therapy with bevacizumab with minimal clinical and radiographic benefit. The second a patient is a 63-year-old man with EGFR L858R-mutated NSCLC with BM. He received concurrent RT and osimertinib at diagnosis and continued osimertinib 80 mg/day for 2 years. Upon progression with LMD he was started on alectinib and received proton craniospinal irradiation. Seven months later he had neurologic decline with neuro-imaging most consistent with RN. He initiated bevacizumab and had clinical and radiographic improvement. The approval and use of novel targeted agents has outpaced the available data surrounding long term risks of combining these therapies with radiation, especially in those patients with BM and LMD. These cases illustrate the challenges of treating patients in the modern era and the need for a multimodal team approach to determine the risk and benefit of combination therapy. Addition of a clinical pharmacist to the decision can help provide expertise in the individual drug pharmacokinetics and dynamics for these complex cases.
MMOD-17 INTEGRATION OF MULTIMODAL ADVANCED MOLECULAR TESTING TO CLASSIFY METASTASES OF UNKNOWN PRIMARIES – A CASE OF A PATIENT WITH NO KNOWN MEDICAL HISTORY
Authors: Primdahl Ditte , Smith Heather , Jean Jeffrey , Duckett Drew , Vormittag-Nocito Erica , Nezami Behtash G , Jennings Lawrence J , Santana-Santos Lucas , Ahrendsen Jared , Castellani Rudolph J , Sukhanova Madina , Jamshidi Pouya 
Published: August 2024

Abstract
Metastases are the most common diagnosed brain tumors in adults. In up to 15% of brain metastases, the source of primary malignancy remains unknown despite a thorough workup. Here, we present a case of a 25-year-old male who presented with intracranial hemorrhage and a mass in the left occipital lobe. At the time, his past medical history was unknown to all care providers. He underwent emergent craniotomy for resection of the tumor. Multimodal advanced molecular diagnostic testing, including next-generation sequencing (NGS), chromosomal copy number analysis, and DNA methylation profiling using Northwestern Memorial Hospital’s Cancer of Unknown Primary (CUP) classifier were performed to classify the neoplasm and identify the primary source for his metastatic tumor. Histopathologic sections showed brain parenchyma with acute hemorrhage intermixed with small fragments of a primitive neoplasm. The immuno-profile of the tumor was suggestive of germ cell differentiation. The tumor harbored multiple molecular and cytogenetic alterations including amplification of CCND2 and 12p, gain of chromosomes X,1q, 7 and 8 and loss of chromosomes Y, 1p, 16 and 22. DNA methylation profiling did not match (i.e. score &gt;0.9) with any tumor entity on the CUP classifier, however the tumor clustered closest to non-seminomatous testicular germ cell tumors on the t-distributed stochastic neighbor embedding (t-SNE) plot. This case highlights the value of utilizing multimodality advanced molecular testing when facing a diagnostically challenging case. While none of the molecular tests performed was independently diagnostically conclusive, in concert, they pointed to a definitive diagnosis. Upon diagnosis, imaging revealed a surgically absent left testicle and multiple lung metastases. Patient confirmed diagnosis of a testicular cancer few years prior to his current presentation. He is undergoing
NIRL-03 REGRESSION ANALYSIS OF NON-CATEGORICAL IMAGING PARAMETERS IN PATIENTS WITH BRAIN METASTASES
Authors: Paruchuri Venkata , Patel Dhaval , Hafeez-Baig M Ahmed 
Published: August 2024

Abstract

BACKGROUND
Estimating survival of patients who have brain metastases (BM) based on risk factors and properties of the metastasis would be useful in clinical practice. Imaging data routinely provides significant variables such as volumes of the tumor, surrounding necrosis, and associated edema. These values could be used to create models that could predict patient survival. Our work applied regression analysis to see how imaging parameters correlated to survival in BM patients.

METHODS
The open-access dataset Pretreat-MetsToBrain-Masks1,2 from the Yale Department of Radiology and Biomedical Imaging featuring 200 BM patients was accessed through the Cancer Imaging Archive. We utilized the Analysis TookPak in Microsoft Excel to perform regression analysis of all non-categorical variables with respect to survival. We performed multivariate regression between survival, edema volume, and necrosis volume. Patients with missing data were omitted from the regression analysis.

RESULTS
There is low correlation between survival and the individual parameters of necrosis ratio (R = 0.12), edema ratio (R = 0.06), necrosis volume (R = 0.02), edema volume (R = 0.06), enhancing tumor (ET) volume (R = 0.18), number of edema lesions (R = 0.10), number of necrotic lesions (R = 0.07), or number of ET lesions (R = 0.05). However, the relationship between enhancing tumor volume and survival does show significance (p = 0.01). The multivariate regression between survival, edema volume, and necrosis volume showed low correlation (0.05) and no statistical significance.

CONCLUSION
There is a significant need to estimate survival in BM patients. However, based on our analysis, we did not find utility in the assessed imaging parameters to estimate survival via a linear model. Still, ET volume was shown to have a significant relationship with survival, and a different model needs to be used to evaluate that relationship.