bluuebunny/crossref_metadata_2025_split huggingface dataset:
DSAI-06 TECHNICAL AND ADMINISTRATIVE CHALLENGES FOR OPEN SCIENCE; REAL-LIFE EXPERIENCE FROM ASNR-MICCAI-BRATS-METS 2023 SEGMENTATION CHALLENGE DATASET
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
1-Highlighting the Brain Tumor Segmentation (BraTS) challenge; the past, present and the future. 2- Emergence of ASNR-MICCAI BraTS-METS 2023 challenge with discussing our experience. 3-Discussing BraTS-METS 2023 challenge and how to overcome it. 4- Highlighting administrative and technical challenges for sharing data.4- Reviewing educational initiatives for the challenge.

CLINICAL RELEVANCE/APPLICATION
Brain Tumor Segmentation (BraTS) challenge: History of BraTS challenge and evolution of its opensource datasets, The challenge and its components. The challenge workflow. How we used the cumulative experience to run the brain metastasis challenge with &gt; 2000 subjects. Administrative challenges in managing large multi-institutional dataset: Paperwork acquisition, including Data transfer agreement, IRB, and Licensing. Organizing &gt; 2000 MRI scans from 12 different institutions and forming a pipeline for receiving and assigning data. Recruiting trainees, medical students, attendings by ASNR call for volunteers. Mentoring ~ 150 trainees and medical students and providing incentives and awards. Communication with ~ 50 neuroradiology experts. Educational effort to increase training and confidence level of trainees and medical students. Technical challenges for ASNR-MICCAI BraTS 2023 brain metastasis challenge: Inconsistent data extraction workflow. Availability of computational power for preprocessing large high-resolution MR images.Using tailored segmentation algorithms for automated pre-segmentation. Performance of publicly available algorithms and their problems, including tiny, hemorrhagic, and post-therapy cases. Educational initiative for medical students and trainees: Lectures and workshops for segmentation software and dealing with common mistakes. Segmentation Hackathon for any difficult cases. Live lectures by experts about different appearances of brain metastasis and post-treatment changes. Future vision of BraTS-METS 2023: Building a consortium of brain metastasis cases. Recruiting more institutions with diverse patient populations and more diverse vendors. Stay tuned for BraTS-METS 2024 challenge.
DSAI-08 MIXED-EFFECTS DEEP-LEARNING BASED QUANTITATIVE RADIOMIC ANALYSIS OF LONGITUDINAL MAGNETIC RESONANCE IMAGING OF BRAIN METASTASES PREDICT PRIMARY TUMOR ORIGIN
Authors: Panchawagh Suhrud 
Published: August 2024

Abstract

BACKGROUND
Brain metastases, secondary brain tumors originating from cancers elsewhere in the body, can present with focal neurologic deficits without systemic symptoms and are usually evaluated using magnetic resonance imaging (MRI). Multimodal imaging methods are usually used to determine the primary cancer source. Radiomic analysis involves extracting quantitative features from medical images using data-characterization algorithms. Recent advances in deep learning and radiomics, which quantitatively analyze imaging data, offer the potential for improved prediction of primary tumor origin through MR imaging analysis. Using longitudinal MRI data, we developed and validated a mixed-effects neural network model for predicting the primary origin of brain metastases.

METHODS
We used the open-source dataset from 5 different institutions made available by Ocaña-Tienda et al. (2023) to build the model. Radiomic feature selection was performed, followed by building a novel quantitative radiomic approach that uses mixed-effects deep learning to analyze longitudinal radiomic data of brain metastases from MRI scans. Model performance was evaluated using receiver operating characteristic curve (ROC) analysis.

RESULTS
Our mixed-effects model demonstrated high accuracy (90.5%), precision (92.7%), recall (87.8%), and F1 score (90.2%), with an area under the ROC (AUC-ROC) curve of 0.944 in identifying the primary tumor site. The nested mixed-effects model was superior to the fixed-effects model with an AUC-ROC of 0.719.

CONCLUSIONS
Our mixed-effects neural network model accurately predicts the primary origin of brain metastases with high internal and external validity. Using advanced radiomic feature selection and deep learning techniques. Our model achieved high-performance metrics, thus providing a promising tool for enhancing diagnostic capability and tailoring patient-specific management strategies. Further research could explore adding more data from other institutions and studying the effect of integrating this model in clinical workflows to optimize patient care.
DSAI-09 APPLYING CONSENSUS QUALITY OF CARE MEASURES FOR BRAIN METASTASES (BMETS-QC) TO PATIENT EHR DATA, A PILOT STUDY
Authors: Anderson Roger , Bonilla Gloribel , Fadul Camilo 
Published: August 2024

Abstract

PURPOSE
Optimal management of patients with brain metastases requires coordinated, interprofessional care, that is well-documented in their electronic health record (EHR). There are unquantified inconsistencies and gaps in the care for this complex medical diagnosis. We explored the feasibility of applying a peer-reviewed set of 29 quality of care (QOC) consensus measures to commercially available aggregated, limited EHR data. These measures address care planning, treatment timing, assessment of QoL, referrals to palliative care and hospice, and survival.

METHODS
Patients with BMETS were selected (N=43) from a an EHR data warehouse sourced from IQVIA’s collaboration with the Guardian Research Network (GRN). Data extraction followed curation rules developed by the study team and performed by GRN. Patients’ EHR data was manually reviewed by trained staff. Both structured data and unstructured text notes were reviewed and coded. Dates of diagnosis, medical services, and death were masked by indexing to birth date. For each indicator, a patient’s EHR data was coded as done (+), not done(-), or inconclusive (missing).

RESULTS
Of 29 indicators, 23 could be ascertained in &gt; 85% of cases. Instances of lower ascertainment occurred for patients lost to follow-up, missing dates of service, no information on planned or actual dose, or missing prognostic scores. BMETS-QC processes ascertained as not performed (-) mostly involved a lack of documented patient-centered care (i.e., shared decision-making, patient education, and psychosocial support). Finally, 12 indicators required the use of unstructured data and required data curation with manual review or NLP.

CONCLUSION
Most BMETS-QC indicators appear feasible to collect in EHR data with curation processes. An important finding is that providers may fail to document key elements of patient-centered care or timely prognostic information. To handle missing data, patients must have their BMETS care recorded within a single EHR system.
MMOD-13 PREVALENCE, TREATMENT PATTERNS, AND SURVIVAL OUTCOMES OF PATIENTS WITH BRAIN METASTASES FROM SMALL CELL LUNG CANCER: A RETROSPECTIVE COHORT STUDY FROM 2013-2023 USING THE TRINETX ONCOLOGY DATABASE
Authors: Parker Megan , Kalluri Anita , Jiang Kelly , Materi Joshua , Azad Tej D , Murray Joseph , Ha Jinny Suk , Kamson David O , Kleinberg Lawrence R , Redmond Kristin J , Brahmer Julie R , Hann Christine , Ye Xiaobu , Bettegowda Chetan , Rincon-Torroella Jordina 
Published: August 2024

Abstract
Brain metastases (BM) portend increased morbidity and mortality in patients with small cell lung cancer (SCLC), yet nationwide reporting of BM is lacking. We aimed to characterize the prevalence, timing, treatment patterns, and survival outcomes of BM associated with SCLC over the past decade. Data from 4,014 patients with histologically confirmed SCLC were extracted from the TrinetX Oncology database. Clinical and demographic variables were compared between patients with and without BM using and Chi-squared and t-tests. Kaplan-Meier and Cox regression analyses were used to evaluate overall survival (OS), after propensity score matching cohorts for age at diagnosis of lung/bronchus cancer, sex, cancer stage at diagnosis, extracranial metastases, and cancer-directed therapy. Among 4,014 patients with SCLC, 34.98% had BM (9.89% synchronous, 21.18% metachronous, 3.91% precocious) At SCLC diagnosis, 0.75% had stage 0, 5.78% stage 1, 3.69% had stage 2, 20.35% had stage 3 cancer, and 48.75% had stage 4 cancer. Patients who developed BM were younger (p&lt;0.001) at diagnosis of SCLC, more likely Black/African American (p= 0.0068), and presented with more advanced cancer stages (p&lt;0.001) than patients who did not develop BM. The median BM-free survival from the time of SCLC diagnoses was 27.9 months. Patients with BM received significantly higher rates of cancer-directed therapies compared to those without BM. Synchronous BM were associated with lower OS than metachronous BM after the diagnosis of SCLC (HR[95%CI] = 1.56[1.32-1.83]), but there was no difference in OS after the BM diagnosis. OS did not differ significantly between patients with BM and patients with extracranial metastases only, following the diagnosis of BM or extracranial metastases, respectively. Our findings underscore the ongoing challenges in treating SCLC patients with BM and support routine intracranial screening as well as the development of interventions to prevent the development of BM in this population.
MMOD-14 IMPACT OF SYSTEMIC THERAPY ACTIVITY ON BRAIN METASTASIS OUTCOMES IN A FEMALE AND HISPANIC-DOMINANT LUNG CANCER COHORT TREATED WITH STEREOTACTIC RADIOSURGERY
Authors: La Rosa Alonso , Yarlagadda Sreenija , Kutuk Tugce , Akdemir Eyub Y , Gal Omer , Albretch Federico , Kaywin Paul , Press Robert H , Hall Matthew D , Mehta Minesh P , Kotecha Rupesh 
Published: August 2024

Abstract
We analyzed the impact of systemic therapy on lung cancer (LC) patients treated with stereotactic radiosurgery (SRS) for brain metastasis (BM) in terms of objective response, intracranial progression-free survival (iPFS), and overall survival (OS). Response was calculated using chi-square analysis with adjusted residuals, while iPFS and OS were computed using the Kaplan-Meier method. A total of 426 BMs in 91 LC patients from 01/2017-07/2022 were included. The median age was 66 years (interquartile range [IQR] 58-73), in our predominantly female (57.1%) and Hispanic (76.9%) population. The median number of BMs was 4 (IQR: 2-8). Systemic therapy was grouped as no switch (no change; 15 patients, 34 BMs) or switch (change from pre- to post-SRS), with the latter classified as a switch-up (increased CNS activity; 76 patients, 392 BMs) or switch-down (decreased CNS activity; 0 patients). At first radiographic evaluation, rates of complete response, partial response, stable disease, or progressive disease were similar (switch-up [%]/no switch [%]) in 32.7%/50.0%, 23.0%/11.8%, 38.3%/32.4%, and 6.1%/5.9%, p&lt;0.05). With a median follow-up of 18 months (IQR: 5-28), the estimated iPFS (95% CI) for the switch-up group was 7.0 months (4.5-9.5), and the no switch group was 10.0 months (2.5-17.5) (p=0.37). However, the estimated OS for the switch-up group was 21.0 months (18.5-23.5) vs. 19.0 months (15.0-23.0), for no switch (p=0.04). Multivariate analysis identified KPS, lesion number, burden of disease, and prescription dose as predictors for iPFS, and age, lesion number, KPS, and disease status (p&lt;0.05) for OS. In conclusion, upgrading systemic therapy based on intracranial activity combined with SRS for BMs from LC is associated with a statistically significant improvement in OS, without impacting iPFS or first response, implying considerable potential for developing next-generation agents with better intracranial activity.
MMOD-15 SURGICAL RESECTION AND STEREOTACTIC RADIOSURGERY IN COMBINATION FOR LOCAL THERAPY OF BRAIN METASTASES
Authors: Fadrus Pavel , Vybihal Vaclav , Juran Vilem , Pukova Andrea Sprlakova , Kerkovsky Milos , Kren Leos , Lakomy Radek , Kazda Tomas , Hynkova Ludmila , Vecera Marek , Hermanova Marketa , Jancalek Radim , Sana Jiri , Slaby Ondrej , Slampa Pavel , Smrcka Martin 
Published: August 2024

Abstract

OBJECTIVES
Complex local treatment of BM combining surgical resection and radiosurgery provides the possibility of adequate local control while maintaining a satisfactory quality of life.

METHODS
Patients after surgical resection and postoperative radiotherapy treated between 2007-2023 were evaluated. Local control was assessed separately at the site of the operated MM (localPFS) and separately in other parts of the brain (distalPFS).

RESULTS
A total of 158 patients were enrolled (70 with WBRT), 56% were women, the median age was 61 years, the median performance status Karnofsky 78%. The most common primary tumor was lung carcinoma (39/118, 33%). Targeted stereotactic radiotherapy was significantly more often indicated in operations performed after 2016 (p &lt;0.001). In the period 2013-2019, gross total resection was achieved significantly more often (88 vs 64%; p = 0.061). The median follow-up is 51 months. The median overall survival (OS) is 9,5 months (6.2 - 12), the median localPFS 24 months (14 - unattainable), median distPFS 12 months (6.8 - 27 months), median extracranialPFS 13 months (5.9 - 15). Stratification of patients according to the prognostic index brainmetgpa.com led to significant separation of patients for OS (p = 0.00017). In a multivariate analysis, stereotactic radiotherapy was statistically significant positive prognostic factor for OS compared to WBRT (median OS 18 vs. 6,1 months, HR 0.59, p = 0.018) with no effect on localPFS.

CONCLUSION
Our results of comprehensive local treatment of BM are comparable with the results presented by important foreign studies from prestigious oncology centers. We described targeted stereotactic postoperative radiotherapy as an independent positive prognostic factor after brain metastasectomy. The study was supported by Ministry of Health, Czech Republic-conceptual development of research organization (FNBr, 65269705).
MMOD-18 THE IMPACT OF CONTRAST CLEARANCE ANALYSIS-GUIDED REPEAT SRS ON SURVIVAL IN PATIENTS WITH BRAIN METASTASES
Authors: Madhugiri Venkatesh , Goulenko Victor , Recker Matthew , Prasad Dheerendra , Plunkett Robert 
Published: August 2024

Abstract

PURPOSE
Adverse radiation effects (ARE) including pseudoprogression are known toxicities associated with radiation for intracranial lesions. ARE are often difficult to differentiate from tumor progression. Delay in identification of tumor progression or misidentification of progression as ARE can lead impact patient survival. In this study, we demonstrate the utility of Contrast Clearance Analysis® (CCA) in differentiating ARE from progression and the impact of CCA-guided decision making on patient survival.

METHODS
Fifty-seven consecutive patients who had been diagnosed with brain metastasis and treated with Gamma Knife Radiosurgery (GKRS) and had presented with suspicious lesion growth on follow-up MRI scans underwent CCA to distinguish between treatment effect and tumor progression. Lesions considered to have recurrence were retreated with repeat GKRS. Survival analyses were carried out to evaluate the impact of early CCA-guided retreatment on survival.

RESULTS
The most common primary disease was non-small cell lung cancer (40%), followed by breast cancer (12%) and melanoma (11%). The use of CCA indicated ARE in 24 lesions and 35 to be pseudoprogression. The total follow-up period was of 72 months. Kaplan-Meir Survival Analyses showed that retreated patients had better survival than the general cohort of patients who did not have CCA-informed retreatments (p&lt; 0.05).

CONCLUSION
CCA is a promising tool to distinguish between tumor progression and ARE in the setting of radiosurgical treatment. Early differentiation allows early retreatment and improvement of the patient survival.
NIRL-05 DIFFERENTIATING RADIATION NECROSIS FROM TUMOR RECURRENCE IN BRAIN METASTASIS USING MRF– A FEASIBILITY STUDY
Authors: Gongala Sree , Zhao Walter , Vempati Prashant , Hodges Tiffany , Newton Herbert , Ma Dan , Badve Chaitra 
Published: August 2024

Abstract

INTRODUCTION
Current imaging modalities are limited in accurately differentiating between tumor recurrence (TR) and radiation necrosis (RN) in brain metastasis (BM) patients. This can affect the ability to treat these patients in an effective and timely manner. Magnetic Resonance Fingerprinting (MRF) is an imaging modality that provides quantitative relaxation times and information about tissue properties. In this study, we explore the ability of MRF to differentiate between TR and RN in BM patients.

METHODS
This is a retrospective IRB approved cross-sectional analysis of 13 BM patients (4 new metastases; NM, 3 TR and 6 RN). MRF and multiparametric MRI images w/wo contrast were acquired for all the patients. Diagnosis was established by histopathology or brain tumor board consensus. Image preprocessing was performed using Cancer Imaging Phenomics Toolkit (CaPTk) and Deepmedic. For MRF, the pre-contrast T1, post-contrast T1, pre-T2, post-T2, ΔT1 and ΔT2 maps were generated. Voxel based analysis was performed across three groups using Kruskal Wallis test.

RESULTS
There are significant differences in median pre-T1 (Median values in ms; NM = 1638.03, RN = 1824, TR = 1282.2), post- T1 (Median values in ms; NM = 1116.7, RN = 577.9, TR = 892.9), pre-T2 (Median values in ms; NM = 74.6, RN = 75.6, TR = 80.6) and post-T2 (Median values in ms; NM = 74.6, RN = 75.6, TR = 80.6) across NM, RN and TR patient groups. Particularly, these differences were larger, and the density plots were visibly different on T1 dependent maps as compared to T2. Consequently, the ΔT1 and ΔT2 values were also significantly different across these three groups.

CONCLUSIONS
In this ongoing study, our preliminary results show the ability of MRF in differentiating RN from TR in BM patients. Larger datasets will be accrued in the future to further test this relationship.
NIRL-08 AUTOMATED LONGITUDINAL TRACKING OF BRAIN METASTASES INTEGRATED IN A USER-ORIENTED SOFTWARE
Authors: Emiliani Ramon D , Chartrand Gabriel , Son Edward , Pawlowski Sophie A , Rajakesari Selvan , Cengarle-Samak Alexandre , Lavoie Jeremi , Ducharme Simon , Roberge David 
Published: August 2024

Abstract
The burden of detection and segmentation of brain metastases (BM) for treatment planning and response assessment has been found to be alleviated by machine learning methods. However, tracking individual lesions over time remains tedious and would benefit from automated assistance for complex cases. We developed a software solution combining an AI-based BM segmentation method with an automated pairing algorithm allowing to track BM across longitudinal scans. The proposed tracking method comprises two steps: identifying lesions in each scan and pairing identified findings across scans. Identification and segmentation of BM is done with our previously published neural network based algorithm. Tracking of BM is achieved by progressively assigning a lesion ID to individual findings. For each series, individual findings are co-registered using image registration to a reference series which defines the initial set of lesions. A matching function then computes a score for each possible finding-lesion pair based on diameter similarity and inter-centroid distance. Findings from highest scoring pairs are sequentially assigned their matched lesion ID, while pairs scoring under a given threshold are assigned a new lesion ID. Series are processed as such until all findings are dispatched. Assignment accuracy was assessed using adjusted rand index (ARI) on a synthetic noisy dataset simulating registration error and misdetections. Findings from 10 to 20 lesions on 5 series of dimension 100 mm per side were randomly generated for 100 synthetic patients each. With a simulated registration error range of 0-2 deg and 0-5mm, the average per patient ARI was 0.94 +/- 0.05, while an error range of 0-4 deg and 0-10mm lowered ARI to 0.87 +/-0.08. Results support the validity of our software solution for automated detection and longitudinal tracking of BM, which can alleviate the burden of follow-ups in the context of stereotactic radiosurgery.
NIRL-10 LEPTOMENINGEAL ENHANCEMENT WITH PARANEOPLASTIC CEREBELLAR DEGENERATION: AUTOIMMUNE OR METASTASES?
Authors: Shah Trusha , Prince Alaina , Venur Vyshak , Graber Jerome 
Published: August 2024

Abstract
Enhancement has been occasionally reported in patients with paraneoplastic cerebellar degeneration but metastases can also occur in these patients and standard imaging and cerebrospinal cytology lack sensitivity and specificity. Among a retrospective case series of 31 patients with paraneoplastic cerebellar degeneration, 4 patients had enhancement at some point of their MRI. We report a series of four patients with paraneoplastic cerebellar degeneration with enhancement and possible concurrent or subsequent leptomeningeal metastases and review the literature. Patient 1 was a 66 year old man with merkel cell carcinoma who had subacute onset of ataxia with nausea. Initial MRI showed non enhancement cerebellar FLAIR changes. Paraneoplastic panel was negative in blood and CSF and seronegative PCD was diagnosed without response to immunosuppression. Eight months later he developed progressive cerebellar symptoms and diffuse leptomeningeal enhancement was found in the cerebellum and spine consistent with leptomeningeal metastates. Patient 2 is a 50 year old woman with HER2+ breast cancer who developed acute cerebellar symptoms with focal cerebellar enhancement and PCA1 antibody was present. Her symptoms stabilized with immune suppression and enhancement resolved, but CSF showed atypical cells suggestive of concurrent leptomeningeal metastases. Patients 3 and 4 both had serous ovarian carcinoma and subacute onset of cerebellar symptoms with cerebellar enhancement and PCA1 antibody with negative CSF cytology. Both stabilized with immune suppression but within months developed more diffuse widespread CNS nodular enhancement considered to be leptomeningeal enhancement. Enhancement is uncommon but not rare in paraneoplastic cerebellar degeneration, occurring in more than 10% of patients in this retrospective series. Others have reported enhancement in paraneoplastic cerebellar degeneration related to autoimmune process alone, but metastases can also occur and may be difficult to distinguish, creating a diagnostic and therapeutic dilemma.