bluuebunny/crossref_metadata_2025_split huggingface dataset:
NIMG-72. CONTRALATERAL PREDOMINANT BLOOD SUPPLY OF FALX AND PARASAGITTAL MENINGIOMA BASED ON ANGIOGRAPHIC ANALYSIS
Authors: Tamai Sho , Tanaka Shingo , Kamide Tomoya , Misaki Kouichi , Nakada Mitsutoshi 
Published: November 2023

Abstract

INTRODUCTION
Preoperative prediction of blood supply in meningiomas is important to avoid unexpected intraoperative bleeding. Herein, we investigated the relationship between the location of meningioma and the dominant side of feeding arteries. METHOD: Between January 2018 and December 2020, a total of 101 consecutive patients underwent craniotomy for meningioma at our hospital. Among them, 43 cases in which the lesions were clearly localized on the right or left sides received preoperative angiography including bilateral common or external carotid artery (ECA) imaging. A region of interest (ROI) was set at the most stained area in (X) meningioma and (Y) main trunk of the ECA. In each affected side (AS) and healthy side (HS), the ratio of ROI (X) value to ROI (Y) value; tumor / vessel ratio (TVR = 0 ~ 1) was calculated. Multivariate analysis was performed to compare TVR between AS and HS, and to analyze factors associated with TVR, such as site of origin (convexity, skull base and relating falx), age, gender, WHO grading, and tumor diameter.

RESULTS
TVR was significantly higher in AS (0.60; 0.41 - 0.91) than HS (0.47; 0.39 - 0.99) (p=0.0003). HS was superior to AS in 10 cases, all of which were falx (6 of 9 cases) or parasagittal (4 of 10 cases) meningioma. 53% of falx and parasagittal meningiomas showed HS predominant TVR. Concerning factors associated with the TVR of HS predominance, falx origin was extracted as an independent factor (p&lt; 0.0001).

DISCUSSION
The vessels crossing in the falx, which consist with particular anatomical structure, fusing the meningeal layers in each side of dura mater would contribute to this finding.

CONCLUSION
Falx and parasagittal meningiomas should consider the predominant influx of tumor feeding vessels from HS.
NIMG-74. COMPARING VOLUMETRIC GROWTH-RATE AND RANO CRITERIA IN DETERMINING THE RESPONSE OF MENINGIOMA TO BEVACIZUMAB THERAPY
Authors: Borenstein Sara , Amiel Alexandra , Siegal Tali , Gal Omer , Limon Dror , Eliahu Ruth , Yust-Katz Shlomit 
Published: November 2023

Abstract
Meningioma is the most prevalent primary tumor in the central nervous system (CNS). Although mostly benign, 15- 20% are aggressive and tend to recur and progress despite surgery and adjuvant radiation. Recent publications show that bevacizumab, a vascular endothelial growth factor inhibitor, effectively treats these refractory meningiomas. The standard method to monitor treatment’s effect on imaging is Response Assessment in Neuro-Oncology criteria (RANO). Recently, an alternative tool called 3D volumetric growth rate (3DVGR) has emerged. Our aim is to compare the effectiveness of conventional RANO criteria and the 3DVGR measure in evaluating the response to bevacizumab treatment in patients with refractory meningiomas. We will also assess their correlation with clinical outcomes over a period of up to 9 months. 68 MRI scans of 20 patients with aggressive meningiomas treated with bevacizumab were evaluated. For each tumor both RANO and 3DVGR were conducted in two subsequent head MRI studies acquired prior to the initiation of bevacizumab treatment and then in at least one exam within 6 months post-treatment. Measurements were obtained using PACS and BRAIN LAB software by two radiologists. A total of 43 lesions derived from 20 patients were included in the analysis. The mean age was 65.5; mean number of radiation treatments was 2.66; mean number of pre-surgical treatments was 2.7 and mean number of bevacizumab cycles was 22.7. All lesions showed a decrease or stabilization in growth rate compared to baseline. More specifically, 34 out of 43 lesions (79%) showed a negative growth rate value indicating decrease in tumor size. Comparison of treatment response using RANO criteria was not always in concordance with the 3DVGR measurement and showed inaccurate correlation with clinical outcome. 3DVGR measure seems to be more precise compared to RANO criteria. Furthermore, our results show great promise for treatment of refractory meningiomas with bevacizumab.
NIMG-76. A DEEP LEARNING ALGORITHM FOR FULLY AUTOMATED VOLUMETRIC MEASUREMENT OF MENINGIOMA BURDEN
Authors: Cleveland Mason , Kim Albert , Patel Jay , McCall Owen , Liu William , Ahmed Syed , Bearce Benjamin , Chang Ken , De Sauvage Magali , Hoebel Katharina , Larson Juliana , Nayyar Naema , Pulido Dagoberto , Singh Praveer , Summers Elizabeth , Kalpathy-Cramer Jayashree , Plotkin Scott R , Brastianos Priscilla , Bridge Christopher , Gerstner Elizabeth 
Published: November 2023

Abstract

PURPOSE
Meningiomas are the most common primary central nervous system tumor. A subset of these tumors is multiply recurrent despite aggressive treatment with surgery or radiation and causes significant morbidity and mortality. Longitudinal measurement of meningioma burden on post-contrast MRI is the basis of treatment response assessment. As per Response Assessment in Neuro-Oncology (RANO), estimates of tumor size are based on the product of bidirectional diameters of enhancing tumor. However, these 2D segmentations as well as manual volumetric segmentations have high rates of intra- and inter-rater variability, which prohibits accurate longitudinal assessment of tumor size. A rapid and reproducible quantitative method for determining meningioma volume is needed to expedite response assessment in clinical trials. To address this unmet need, we developed a deep learning algorithm that enables fully automated 3D segmentation and volumetric assessment of meningioma burden.

METHODS
351 post-contrast T1-weighted brain MRIs from 86 patients with meningioma were obtained from Massachusetts General Hospital and Dana-Farber Cancer Institute. The cohort was unique compared to prior DL segmentation models as it encompassed diverse clinical scenarios (e.g., meningioma of all grades, post-operative and post-radiated meningioma). The MRIs were resampled to 1 mm isotropic resolution and preprocessed using N4 bias field correction and zero-mean intensity normalization. The dataset was split 70%/15%/15% for training/validation/testing on a per patient level. The training data were used with manually generated tumor segmentations to train a convolutional neural network (CNN) with a U-Net architecture and the Dice loss function.

RESULTS
The median Dice score was 0.6758 on the test set. Additional work is ongoing to optimize performance, with primary focus directed toward improved data preprocessing and ground truth segmentation as the variability in segmentation quality contributed to the lower Dice score, highlighting the need to develop a less biased and more reliable tool to segment meningiomas.
NIMG-77. EARLY DIAGNOSIS OF NEUROCUTANEOUS MELANOSIS MASQUERADING AS SUBARACHNOID HEMORRHAGE
Authors: Chen Hsien-Chung , Yang Shun-Tai 
Published: November 2023

Abstract
A 50-year-old male presented to the emergency room with a sudden onset right upper limb facial numbness and dysphasia, soon followed by full-recovery. Brain computed tomography revealed hyperdense lesions within the left frontal sulcus, highly suspicious of subarachnoid hemorrhage. T1-weighted magnetic resonance imaging showed multiple leptomeningeal enhancement in the left frontal area.The digital subtraction angiography indicated an absence of vascular lesions. One-month after, the lesions progressed in the occipital area, when left sixth nerve palsy developed. Multiple giant nevus over the legs, trunk, and scalp had attracted attention. Owing to the suspicious symptomatic leptomeningeal lesions, open biopsy was performed. Surprisingly, diffuse, thick, black-colored tissue infiltration of the subarachnoid space, involving prominent cortical vessels, was noted. Pathology confirmed meningeal melanocytosis. Neurocutaneous melanosis is characterized by giant congenital or multiple satellite nevi and melanocytic tumors of the leptomeninges. Early disease diagnosis is crucial. Once the patient develops neurological symptoms, prognosis could quickly worsen.
NIMG-79. DIFFERENTIATION OF SUBTYPES IN AFULLY AUTOMATED DEEP LEARN TUMORS USING PREOPERATIVEM RIMAGES ING APPROACH FOR ACCURATE PRIMARY INTRACRANIAL
Authors: Li Yanong 
Published: November 2023

Abstract

BACKGROUND
Intracranial germ cell tumors (iGCTs) are divided into germinomas (GEs) and nongerminomatous germ cell tumors (NGGCTs), each having distinct treatments and prognoses. However, predictive biomarkers for differentiation are limited. Here, we aim to develop a deep learning (DL) model that can automatically differentiate GEs from NGGCTs using preoperative magnetic resonance (MR) images and analyzing how our model improved clinical decision making among five physicians. METHODS: This multicenter study included patients with pathology-confirmed iGCTs for the developed set (total n = 280), which was split into training (n = 200) and testing datasets (n= 80), and three independent validation datasets (n = 64), respectively. We developed a DL model based on 3D nnU-Net and preoperative MR images to differentiate GEs from NGGCTs. To evaluate the clinical value of the DL model, five physicians' accuracy and level of consistency in identifying tumor types were compared in the testing and three validation datasets, with and without referring to the DL model’s output.

RESULTS
The DL model achieved AUCs of 0.950, 0.921, 0.869, and 0.905 in the testing and three validation datasets, respectively, which is superior to using conventional information including MR features and clinical information (AUC=0.768, P=0.009). The physicians’ diagnostic performance improved from an average AUC of 0.695 without reference to the DL output to 0.842 using the DL output in the testing and independent validation datasets (21.2% improvement, P=0.014).

CONCLUSIONS
We developed and validated a DL model using a large dataset to accurately differentiate GEs from NGGCTs using preoperative MR images.
NIMG-81. ASSOCIATION OF THE ORIGIN OF CRANIOPHARYNGIOMA WITH OPTIC TRACT EDEMA
Authors: Kodama Takuma , Akiyama Osamu , Shimizu Yuzaburo , Suzuki Mario , Teramoto Shinichiro , Kondo Akihide 
Published: November 2023

Abstract

OBJECTIVE
Optic tract edema (OTE) is a useful finding in the diagnosis of craniopharyngioma (CP). However, the pathogenesis of OTE is not fully understood. In this study, we investigated the presence of OTE depending on the site of origin of CP.

METHODS
We reviewed 48 patients with CP who underwent surgical treatment at Juntendo University Hospital between March 2010 and February 2023 and investigated their size, location, presence of OTE, pathological subtypes, and genetic abnormalities. Tumors were classified into four groups based on their origin: retrochiasmatic (RC) type, prechiasmatic (PC) type, intrasellar (IS) type, and intra-third-ventricle (ITV) type.

RESULTS
Forty-eight cases were included in this study. The number of cases of RC, PC, IS, and ITV types were 29, 8, 3, and 8, respectively. OTE was shown in 21 cases. Among them, RC type was the most common location (18 cases, 86%) with significant differences. The cystic component of the tumor was in contact with the optic tract in 15 cases, which was more common than the solid component.

DISCUSSION
Possible causes of OTE include cytotoxic edema associated with inflammation, angiogenic edema due to leakage of serum components from the tumor, leakage of fluid components from the cyst, and enlargement of the Virchow-Robin space in the optic disc. In this study, many of the cases with OTE have cystic components in contact with the optic tract, suggesting leakage of fluid components from the cyst as the pathogenesis of OTE. The presence of OTE can be a new factor to determine the surgical approach since CP with OTE is thought to extend posteriorly to the optic chiasm.

CONCLUSIONS
OTE is often associated with RC type CP and is thought to be caused by leakage of fluid from the cyst.
NIMG-83. ELUCIDATING INTRA-TUMORAL HETEROGENEITY AND DISTINCT RADIOMIC FEATURES IN GLIOBLASTOMA METHYLATION SUBCLASSES
Authors: Matsumoto Yuji , Garcia Jose , Kazerooni Anahita Fathi , Abdullaev Zied , Singh Omkar , Davatzikos Christos , Aldape Kenneth , Nasrallah MacLean P 
Published: November 2023

Abstract
Glioblastoma, IDH-wildtype (GBM), is characterized by the inter- and intra-tumoral molecular heterogeneity. Genome-wide DNA methylation profiling has recently emerged as a promising tool offering complementary value to the classification of central nervous system tumors. In adult GBM patients, the most common methylation subclasses comprise RTK I, RTK II, and MES. We hypothesize that quantification of intricate and spatially complex radiomic features extracted from multi-parametric MRI (mpMRI) is informative to non-invasively determining characteristics of GBM methylation subclasses and their heterogeneity. In this study, mpMRI scans (T1, T1-Gd, T2, T2-FLAIR, DSC, DTI) of newly diagnosed 23 GBM patients were retrospectively collected. We derived 6339 radiomic features, including histograms, morphologic and textural descriptors. For each case, 3-4 multiple samplings from different parts of the tumor were conducted. DNA was extracted from FFPE for each of sample and analyzed for genome-wide DNA methylation patterns using the Illumina EPIC array. Classification of methylation subclasses was performed using the MNP brain tumor classifier v12b6 of the DKFZ. Analysis of variance (ANOVA) with Bonferroni correction was employed to extract subclass-specific radiomic features. Of the 23 patients, 7 indicated intra-tumoral heterogeneity in methylation subclasses. We identified 68 radiomic features (p&lt; 0.05) and 12 radiomic features (p&lt; 0.01) that showed statistically significant differences among the methylation subclasses as determined by ANOVA with Bonferroni correction. A heatmap illustrating the relationships between subclasses and extracted radiomic features displayed distinct trends among subclasses and between heterogeneous and homogeneous cases within the same subclass. Our findings suggest the presence of heterogeneity within methylation subclasses and distinctive imaging patterns for each subclass. These findings potentially pave the way for a more personalized approach to glioblastoma management, highlighting the importance of further validation through the analysis of additional cases.
NIMG-85. EVALUATING THE PERFORMANCE OF A DEEP LEARNING GLIOMA SEGMENTATION MODEL USING COMBINED PRE- AND POST-TREATMENT MRI TRAINING DATA
Authors: Ranjbar Sara , Singleton Kyle , Curtin Lee , Paulson Lisa , Clark-swanson Kamala , Hawkins-daarud Andrea , Mitchell J Ross , Jackson Pamela , Swanson Kristin 
Published: November 2023

Abstract
Identification of key phenotypic regions such as necrosis, contrast enhancement, and edema on magnetic resonance imaging (MRI) is important for understanding disease evolution and treatment response in patients with glioma. Manual delineation is time intensive and not feasible for a clinical workflow. Automating phenotypic region segmentation overcomes many issues with manual segmentation, however, current glioma segmentation datasets focus on pre-treatment, diagnostic scans, where treat-ment effects and surgical cavities are not present. Thus, existing automatic segmenta-tion models are not applicable to post-treatment imaging that is used for longitudinal evaluation of care. Here, we present a comparison of three-dimensional convolutional neural networks (nnU-Net architecture) trained on large temporally defined pre-treatment, post-treatment, and mixed cohorts. We used a total of 1563 imaging timepoints from 854 patients curated from 13 different institutions as well as diverse public data sets to understand the capabilities and limitations of automatic segmenta-tion on glioma images with different phenotypic and treatment appearance. We as-sessed the performance of models using Dice coefficients on test cases from each group comparing predictions with manual segmentations generated by trained techni-cians. We demonstrate that training a combined model can be as effective as models trained on just one temporal group. The results highlight the importance of a diverse training set, that includes images from the course of disease and with effects from treatment, in the creation of a model that can accurately segment glioma MRIs at multiple treatment time points.
NIMG-89. CNS-ISOLATED RICHTER’S TRANSFORMATION: THE FALLIBILITY OF NEURO-IMAGING AND THE CRITICAL ROLE OF BRAIN BIOPSY IN A CHALLENGING DIAGNOSIS
Authors: Lee Sean , Hurbon Audriana , Aboul-Nasr Ahmed , Salazar Dory Arevalo , Wakefield Chelby , Halder Ritika , Krishnadasan Ravitharan 
Published: November 2023

Abstract

INTRODUCTION
An 81-year-old male was admitted for acute encephalopathy and failure to thrive. Workup revealed a lymphocyte-predominant leukocytosis, prominent axillary and mediastinal lymphadenopathy on CT, and multiple supra-tentorial FLAIR-hyperintense lesions that were homogenously contrast-enhancing. Axillary lymph node biopsy demonstrated small lymphocytic lymphoma (SLL), a variant of CLL. Despite concern for CNS malignancy, brain biopsy was initially deferred since the patient’s brain lesions were attributed to SLL metastasis. However on hospital day 15, he developed partial seizures, prompting stereotactic biopsy which revealed DLBCL.

DATA/DISCUSSION
Our case highlights the pitfalls of relying solely upon neuro-imaging to diagnose Richter’s transformation (RT) isolated to the CNS. First, MRI does not differentiate CNS metastasis of systemic lymphoma from CNS RT. A review of 35 biopsy or LP-proven cases of CNS-isolated RT showed imaging characteristics consistent with primary and metastatic CNS lymphoma. When parenchymal lesions are present, all are T2/FLAIR hyper-intense; 60% are unifocal (40% multifocal); and 95% homogenously enhance. Second, CNS-isolated RT is at least 3 times rarer than CNS metastases of CLL. Among patients with CLL, ~1% will eventually exhibit CNS metastasis but &lt; 0.3% will develop CNS-isolated RT. In patients with known CLL and no evidence of high-grade transformation, it is reasonable to attribute brain lesions to CNS metastasis of CLL as opposed to RT, absent a definitive tissue diagnosis.

CONCLUSION
These data emphasize the importance of biopsy in the workup of CNS lymphoma, especially since treatment differs based on histopathological subtype. Given its chronic indolent course, SLL is typically managed expectantly, whereas the aggressive nature of DLBCL warrants more intensive chemotherapy. Our case also shows that in patients with suspicious CNS lesions, presence of systemic malignancy does not eliminate the need for brain biopsy, and that clinical deterioration should prompt biopsy if not already performed.
NCMP-02. BIOPSY OUTCOMES OF PATIENTS WITH SUSPECTED LEPTOMENINGEAL CARCINOMATOSIS: A RETROSPECTIVE CASE SERIES
Authors: Blazek Audrey , Carabenciov Ivan 
Published: November 2023

Abstract

BACKGROUND
Leptomeningeal carcinomatosis is commonly considered when patients present with meningeal enhancement on magnetic resonance imaging (MRI), even without a known primary malignancy. In practice, some clinicians advocate for early meningeal biopsy to expedite diagnosis, citing lack of specificity of other testing, such as cerebrospinal fluid (CSF) analysis.

METHODS
We identified a cohort of patients with meningeal enhancement that underwent biopsy for diagnostic purposes between 2010 and 2022. Presenting symptoms, physical exam, enhancement pattern on MRI, other imaging findings, CSF parameters, other laboratory results, final diagnosis, and recommended treatment were recorded when available.

RESULTS
Out of nearly 100 cases included, the majority were autoimmune or inflammatory in etiology. Only 13 patients were diagnosed with malignancy-related enhancement, and 10 of these cases were felt to be true carcinomatosis. Nine out of the 13 patients were diagnosed with lymphoma. Four of these lymphomas were diagnosed on systemic biopsy, with meningeal biopsies negative for malignant cells. The other malignancies included systemic adenocarcinoma, oligodendroglioma, and a rare hematologic cancer. Nearly all 13 patients had abnormal CSF parameters, notably pleocytosis, but none had malignant cells in the fluid. Most frequent presenting symptoms were encephalopathy, vision changes, and strength/sensory changes. MRI often showed cranial nerve or general cerebral and cerebellar involvement, and physical exam often showed cranial nerve, strength, and sensory deficits. All patients proceeded with chemotherapy after diagnosis.

CONCLUSIONS
When leptomeningeal carcinomatosis is considered based on MRI enhancement, the clinical approach should continue to revolve around indirect testing such as CSF analysis, serum studies, and other imaging techniques to consider alternative biopsy sites before pursuing direct sampling with meningeal biopsy. With this approach, many patients with suspected carcinomatosis can avoid undergoing meningeal biopsy and decrease the chance of treatment delay.
NCMP-05. INTRACTABLE HEADACHE IN NEWLY DIAGNOSED AML WITH MIGRAINES AND CHIARI MALFORMATION- UNVEILING A COMPLEX SYMPTOM
Authors: Austin Hannah , Singla Laveena 
Published: November 2023

Abstract
Acute Myeloid Leukemia (AML) involvement in central nervous system (CNS) is poorly understood in pathophysiology, with reported incidence rates ranging from 1-33% of patients with relapsed AML. CNS involvement is uncommon in the early stages of AML. FLT3-ITD, chromosome 11 abnormalities, and inv(16) cytogenetics are known to have more potential to invade the CNS. A 28-year-old woman with recently diagnosed AML (FLT D835 mutation with deletion in the long arm of chromosome 11) and migraines was admitted for HIDAC consolidation #3. On day two, she started experiencing headaches in the bifrontal and bitemporal regions associated with photophobia, phonophobia, and nausea. Treatment for status migrainous provided little relief. MRI brain showed progression of Chiari malformation (CM) with tonsillar herniation from 16 to 19 mm, which precluded a lumbar puncture. On day 4, she was noted to have grade III papilledema and bilateral cranial nerve IV palsy with non-enhancing patchy increased FLAIR signal in dorsal pons, bilateral cerebral and middle cerebellar peduncles, without diffuse restriction on imaging. The patient underwent sub-occipital craniotomy and C1 laminectomy for decompression for chiari. On day 5, she developed cranial nerve palsies involving nerves VII, IV, and XII. Lumbar puncture (LP) performed after decompression demonstrated elevated opening pressure and 98% abnormal myeloid blast population, confirming CNS involvement of AML. 4 days before starting intrathecal chemotherapy, the patient was found to be in asystole (unclear etiology). This case highlights the range of differential diagnoses for headaches in a patient with multiple comorbidities, including obesity, migraine, Chiari malformation with tonsillar herniation, and cancer. It underscores the necessity for proactive screening of CNS invasion in AML patients with high-risk mutations and neurological symptoms. Moreover, it emphasizes the need to consider CNS involvement in AML patients with headaches, even if standard imaging does not show typical signs of leptomeningeal spread.