bluuebunny/crossref_metadata_2025_split huggingface dataset:
PATH-32. CONCORDANCE FOR CDKN2A/B LOSS AND TERT MUTATION IN WHO 2021 CLASSIFICATION GRADE 3 MENINGIOMAS: A RETROSPECTIVE STUDY
Authors: Yuen Carlen , Pan Peter , Teasley Damian , Miller Michael , Sun Yu , Canoll Peter , Joanta-Gomez Adela , Bargo Alicia , Iwamoto Fabio 
Published: November 2022

Abstract

BACKGROUND
The new WHO 2021 classification included CDKN2A/B loss and TERT mutation as new criteria for Grade 3 meningiomas, but excluded H3K27me3 loss. Malignant behavior may be influenced by DNA methyltransferases (DNMT3A). SUFU mutations may carry a predisposition for multiple meningiomas.

METHODS
In this retrospective study, 228 patients with Grade 2, Grade 3 or recurrent Grade 1 meningiomas with resections from 1990 to July 2021 at Columbia University Medical Center were assessed for recurrence, histologic features, and molecular alterations.

RESULTS
Of 228 patients with meningiomas, 9 were recurrent Grade 1, 9 were Grade 1 transformed to Grade 2, 109 were non-recurrent Grade 2, 77 were recurrent Grade 2, 13 were transformed Grade 2 to Grade 3, and 5 were non-recurrent Grade 3 and 6 were recurrent Grade 3. Median follow-up was 42.0 months. Of the recurrent/transformed tumors, 89 were radiation-resistant. Average mitotic counts for non-recurrent Grade 2 vs. recurrent/transformed Grade 2 and non-recurrent Grade 3 vs. recurrent Grade 3 meningiomas were 4 vs. 5, 24 vs. 27 mitoses/10HPF, respectively. Of 36 meningiomas evaluated with NGS, the most common alterations was NF2 (20/36). CDKN2A/B was lost in 5 meningiomas, three with Grade 2 that transformed to Grade 3 and two with recurrent disease. TERT was mutant in 3/36, 2 of which were Grade 2 that transformed to Grade 3 meningiomas. H3K27M me3 was tested by IHC in 4 patients, 3 with retained staining, all of whom did not recur and 1 with loss of staining in a Grade 1 transformed to Grade 2. DNMT3A was found in 2 tumors, both radiation-induced. SUFU occurred in 3/16, one of each grade, all solitary.

CONCLUSION
In our limited cohort, we observed concordance with the new WHO 2021 criteria for Grade 3 meningiomas
PATH-38. DISSEMINATED “MYXOID GLIONEURONAL TUMOR, PDGFRA P. K385-MUTANT” IN AN ADOLESCENT MANAGED WITH OBSERVATION AND WITHOUT ANY ADJUVANT THERAPY
Authors: Vanan Magimairajan Issai , Macdonald Patrick , Wachnian Cielle , Gianno Francesca , Drimes Tina , Sinha Namita , Hazrati Lili-Naz , Bonanni John 
Published: November 2022

Abstract

INTRODUCTION
Myxoid glioneuronal tumor, PDGFRA p. K385-mutant (MGNT) is a recently described central nervous system tumor entity typically arising from the septum pellucidum and molecularly defined by mutation of the PDGFRA oncogene. The tumor is clinically benign, can be disseminated at presentation and is managed by surgical resection with or without adjuvant therapy (Chemotherapy / Radiation). CASE REPORT: 16yr old female presented to the children’s emergency with 6-week history of increasing intensity of acute on chronic frontal headaches and single episode of seizure like activity. She did not have nausea, vomiting or any cognitive or visual disturbances. Neurological exam was normal with no evidence of papilledema. Magnetic Resonance imaging (MRI) of the brain showed a large intraventricular mass arising from the right lateral ventricle and the septum pellucidum with dissemination into the periventricular white matter, suprasellar region, right thalamus, genu and splenium of the corpus callosum and multiple foci seen in the inferior aspect of the brain stem involving the pons and medulla. There was no evidence of obstructive hydrocephalus and the spine was normal. After an initial endoscopic biopsy failed molecular testing, she underwent an open biopsy which confirmed the diagnosis of MGNT histologically and NGS testing of the tumor revealed mutation at codon 385 (leucine replacing lysine) in the PDGFRA oncogene (k385l). Since the tumor was disseminated and the headache was controlled with symptomatic treatment, she was managed with regular follow up without surgery, adjuvant chemotherapy or radiation. The patient is doing well at 8 months follow up without any symptoms and stable lesions on the MRI.

CONCLUSION
Based on our experience and literature review, MGNT with PDGFRA-k385l mutation is a clinically benign tumor even though it can be disseminated at presentation and can be managed conservatively without any adjuvant therapy.
PATH-45. INTRAEPIGLIOM - RAPID SEQUENCING-BASED DIAGNOSIS OF BRAIN TUMORS
Authors: Kubelt Carolin , Brändl Björn , van Bömmel Alena , Rohrandt Christian , Wang Gaojianyong , Evers Maximilian , Kolkenbrock Stephan , Wong Derek , Danso Dominik , Maicher Andre , Friedrichsen Sönke , Proescholdt Martin , Riemenschneider Markus , Jetzek Ulrich , Meissner Alexander , Yip Stephen , Kretzmer Helene , Synowitz Michael , Müller Franz-Josef 
Published: November 2022

Abstract
The intraoperative diagnosis of brain tumors remains a clinical challenge despite recent technological advances. The current clinical practice differentiates non-surgical brain tumors from those preferably treated with cytoreductive surgery employing intraoperative frozen section diagnostics. A detailed molecular diagnosis required for this classification task within the timeframe of a routine neurosurgical procedure is currently unavailable. We have analyzed a clinical cohort of several brain tumor entities using Nanopore long-read sequencing on two Oxford Nanopore Technologies sequencing platforms (MinION, PromethION). Since currently available molecular cancer classifiers such as the DKFZ methylation profiling classifier cannot be readily adapted to real-time sequencing analysis, we implemented a novel algorithm (MethyLYZR) to predict the underlying cancer type. Publicly available Illumina Infinium array data were used to train the classifier to distinguish 91 brain tumor classes. For validation of classification accuracy, we conducted a comprehensive validation strategy. Both nanopore platforms could sequence more than 5,000 pre-selected CpG within less than 20 minutes for most of our samples. When combining an optimized library preparation protocol with the time used for sequencing the minimal number of CpGs needed for classification, we saw sample-to-answer times of less than 1 hour – in many cases within 45 minutes - from receiving a fresh biopsy to a robust cancer type prediction. Comparing actual and predicted diagnoses resulted in a favorable error rate, indicating potentially highly clinical validity. Our real-time based molecular diagnostic algorithm enables, in most cases, a reliable diagnostic call within the timeframe of a typical neuro-oncological surgery. MethyLYZR as a predictive tool may allow us to adjust the surgical strategy and deliver the prognosis to our patients right after surgery, thus allowing for as-of-yet unexplored opportunities for the intraoperative application of individualized therapeutic modalities.
NIMG-04. LONGITUDINAL TRACKING OF PERITUMORAL EDEMA VOLUME USING PACS-INTEGRATED TOOLS PROVIDES CRITICAL INFORMATION IN TREATMENT ASSESSMENT OF NSCLC BRAIN METASTASES AFTER RADIOSURGERY
Authors: Kaur Manpreet , Petersen Gabriel Cassinelli , von Reppert Marc , Jekel Leon , de Santo Irene Dixe oliveira , Varghese Sunitha , Chiang Veronica , Aboian Mariam 
Published: November 2022

Abstract

PURPOSE
Brain metastases (BM) are the most common intracranial malignancies in adults and mostly originate from lung cancer. Gamma Knife (GK) has become standard of care for BM, however there is insufficient knowledge of the posttreatment volumetric changes of peritumoral edema of BM due to paucity of tools for volumetric segmentation in neuroradiology practice. Recently PACS-integrated tools have become available in select clinical practices facilitating the comparison of posttreatment peritumoral edema volume changes and 2D-based measurements of CE tumor core.

METHODS
Patients with NSCLC BM ≥ 10 mm on T1c+ treated with GK had volumetric measurements for up to 7 follow-ups using a PACS-integrated tool that segments the FLAIR hyperintense region surrounding and including the CE lesion. The 2D and volumetric measurements were compared by creating treatment response curves with incorporation of clinical information including steroid timing.

RESULTS
50 NSCLC BM were included. The median pretreatment peritumoral volume was 8.5 cm3 (IQR 1–47 cm3, n= 36). The volume significantly decreased at 0–90 days (median 1.2 cm3, IQR 0.5–6.1 cm3, n= 31) and between 0-90 and 91-180 days (median 0.8 cm3, IQR 0.3-2.3 cm3, n= 26) post-GK. The time of peak median peritumoral volume increase was at &gt; 365 days (median 1.4 cm3, IQR 0.4–8.1 cm3, n= 19). There was a positive correlation between longest diameter (LD) and peritumoral edema volume (rs= .75, p&lt; .05). At 181–270 days post-GK 50% of BM showed incongruent response course for LD and peritumoral edema volume. The congruence/incongruence ratio of edema/enhancing portion of BM changed over follow-up time.

CONCLUSION
Half of the BM in our study did not show congruent response when comparing posttreatment peritumoral edema volume course to CE lesions in longitudinal assessment. Therefore, there is a critical need for quantitative tools that are incorporated into clinical practice to assess peritumoral edema treatment response.
NIMG-07. APPLYING A GLIOMA-TRAINED DEEP LEARNING AUTO-SEGMENTATION TOOL ON BM PRE- AND POST-RADIOSURGERY
Authors: Kaur Manpreet , Varghese Sunitha , Jekel Leon , Tillmanns Niklas , Merkaj Sara , Bousabarah Khaled , Lin MingDe , Bhawnani Jitendra , Chiang Veronica , Aboian Mariam 
Published: November 2022

Abstract

PURPOSE
Stereotactic radiosurgery (SRS) has become the mainstay to treat BM. Follow-up MRI provides important information on lesion treatment response and guides future therapy planning. Volumetric measurements of BM have shown promise over traditional uni- and two-dimensional measurements in more accurate and repeatable assessment. However, routine clinical use has yet to be achieved because the workflow is laborious. In previous work, we developed a PACS-integrated deep learning algorithm for automatic high- and low-grade glioma 3D segmentation. In this work, we applied this U-Net to segment BM on pre- and post-Gamma Knife (GK) MRI and evaluated the performance.

METHODS
10 pre- and post-GK studies were autosegmented in five randomly selected patients (melanoma n= 3, breast n= 2). The glioma trained algorithm segmented the “Whole Tumor” (tumor core+peritumoral edema on T2w-FLAIR) and “Tumor Core” (CE tumor core+necrosis on SPGR). The AI generated segmentation was then revised as needed by a board-certified neuroradiologist and the dice-similarity-coefficient (DSC) between the revised and automatic volumetric segmentations were calculated.

RESULTS
Four patients had multicentric (2-4 BM) lesions. The mean± SD DSC for Whole Tumor and Tumor Core were 0.92±0.06 and 0.46±0.30 for pretreatment, 0.84±0.09 and 0.41±0.25 for posttreatment BM, respectively. The tool detected lesions with a sensitivity of 45% (5/11) for pretreatment and 50% (3/6) for posttreatment lesions. Three pretreatment and all posttreatment lesions that were not detected by the autosegmentation tool showed a very faint hyperintense peritumoral edema in T2w-FLAIR.

CONCLUSION
Volumetric segmentation of edema on FLAIR using the glioma-trained segmentation algorithm on pre- and post-GK BM did not require major adjustment of segmentation if it detects the lesion. On the other hand, with low sensitivity of lesion detection and low DSC for enhancing component, dedicated training of the algorithm on annotated BM data will be needed.
NIMG-14. RADIOLOGIC ASSESSMENT OF BRAIN METASTASES UNDERGOING LASER INTERSTITIAL THERMAL THERAPY (LITT)
Authors: Sanvito Francesco , Nagaraj Raksha , Sayari Jessica T , Rana Shivam , Raymond Catalina , Cho Nicholas S , Mozaffari Khashayar , Unterberger Ansley , Yang Isaac , Ellingson Benjamin 
Published: November 2022

Abstract

BACKGROUND
Laser Interstitial Thermal Therapy (LITT) is a novel treatment for brain metastases (BMs), and data regarding radiologic changes and long-term efficacy is sparse. This study explored volumetric changes in responding and non-responding BMs and their associations with lesion-specific progression-free survival (PFS-L).

METHODS
Patients with BMs treated with LITT were retrospectively enrolled. 3D volumes-of-interest of the contrast-enhancing BM tissue (CE) on pre-, post-LITT, and follow-up MRI scans were obtained. BMs were followed until progression or censoring. PFS-L was determined using the modified RANO criteria to assess treatment efficacy on each lesion.

RESULTS
Thirty-one BMs (from 30 patients) were preliminarily analyzed. 2 BMs had no follow-up scans. Median follow-up for 29 BMs was 248 days (range 28-2200). Median time to response was 430 days (responders n=7/29), median time to progression was 176 days (progressive disease n=7/29). Pre-LITT CE volume was a predictor of PFS-L (p=0.001), with BMs&gt; 2.5 cc being 14 times more likely to undergo progression. Differences in age and primary tumor site did not impact PFS-L, whereas PFS-L tended to be longer in females (p=0.059), and in frontal and deep grey matter BMs (p=0.11). Post-LITT CE volume was higher than pre-LITT (p&lt; 0.0001, median increase 59%), with no significant differences among responders, stable disease, and progressive disease. In each responding BM, the CE volume shrinkage over time was described by an exponential decay (R2 ranging 0.92-1.0 and half-life ranging 16.55-204 days). All responding BMs showed a pooled exponential decay with R2=0.88 and half-life=75.6 days.

CONCLUSIONS
Our data suggest that smaller BMs may have improved outcomes from LITT treatment. CE volumes may increase in the early post-procedural scans, possibly due to both inflammatory changes and thermal damage. The characterization of the volumetric changes across time for responding lesions may be useful for an early detection of BMs at risk for progression.
NIMG-18. A GROUND TRUTH COMPARISON OF PATHOLOGICALLY CONFIRMED GLIOBLASTOMA MARGINS TO CONTRAST ENHANCEMENT AT AUTOPSY
Authors: Lowman Allison , Bobholz Samuel , Brehler Michael , Duenweg Savannah , Kyereme Fitzgerald , Cochran Elizabeth , Coss Dylan , Connelly Jennifer , Mueller Wade , Agarwal Mohit , Banerjee Anjishnu , LaViolette Peter 
Published: November 2022

Abstract

PURPOSE
Glioblastoma is one of the most common and deadly adult brain tumors. Current standard treatment is surgical resection followed by radiation and concomitant chemotherapy (chemoRT). Glioblastoma progression is monitored using MRI, primarily relying on post-contrast T1-weighted imaging (T1C). Unfortunately, tumor invasion is known to extend beyond traditional contrast enhancement. T1-subtraction (T1S) maps have been introduced as a better tumor volume estimate. In this study we compare T1S map derived tumor annotations to a radiologist for identifying histologically confirmed tumor in patients with differing treatment histories at autopsy.

METHODS
Ten patients with autopsy confirmed glioblastoma and MRI within 1 month of death were recruited for this study. Seven patients received chemoRT combined (chemoRT+) and three patients received no treatment beyond surgery (chemoRT-). Patient’s brains were sliced axially in the same orientation as their final MRI using a patient-specific slicing jig. Large tissue samples were taken, processed, embedded in paraffin, stained for hematoxylin and eosin, and digitized at 40x resolution. Digital images were annotated for infiltrative tumor, pseudopalisading necrosis, and necrosis without palisading cells. T1S and radiologist annotations were created for each patient using their final MRI (mean 18 days prior to death). The annotated histology images were aligned and resampled into MRI space using custom software and the overlap of pathologically confirmed tumor and MRI derived annotations was compared.

RESULTS
T1S maps alone were significantly better at identifying areas of histologically confirmed tumor in chemoRT+ patients compared to chemoRT- patients (p=0.043). T1S derived annotations overlapped with 52% of histologically confirmed tumor in the chemoRT- patients and 78% in the chemoRT+. The radiologist drawn tumor masks were more accurate in chemoRT+ patients, identifying 61% confirmed tumor (trending, p=0.097, chemoRT+=61%).

CONCLUSION
These results demonstrate the difficulty of identifying pathologically confirmed tumor outside contrast enhancement in glioblastoma patients, even in the untreated state.
NIMG-19. IMAGE-BASED MODELING MAP OF EDEMA IS CORRELATED WITH MULTIPLE BLOOD-BRAIN-BARRIER PERMEABILITY RELEVANT TRANSCRIPTOMIC MARKERS IN BRAIN TUMOR PATIENTS
Authors: Jackson Pamela , Ranjbar Sara , Curtin Lee , Bond Kamila , Singleton Kyle , Hawkins-Daarud Andrea , Li Jing , Canoll Peter , Hu Leland , Tran Nhan , Swanson Kristin 
Published: November 2022

Abstract
Brain tumor associated edema is a significant cause of patient morbidity and mortality often requiring continual treatment with differing levels of success across patients. Edema is a broad term that can indicate increased local water as well as diffusely infiltrating tumor cells. Edema is visualized as hyperintense regions on T2-weighted (T2W) magnetic resonance imaging (MRI) and is typically associated with blood-brain barrier (BBB) breakdown and tumor aggressiveness. Understanding the molecular mechanisms driving imaging patterns of “edema” could provide insights into clinical imaging interpretation. We have an ongoing image-guided biopsy study that allows us to link biopsy molecular markers with locoregional MRI patterns of edema. Further, we previously developed a physics-based method to estimate edema abundance (i.e., edema map) from T2W MRIs. Our goal was to identify connections between BBB-associated molecular factors and edema abundance in brain tumors. Our cohort included 38 patients (female: 15, male: 23) with 129 image-guided biopsies (female: 62, male: 67). We correlated image-localized edema map values with the mean transcriptional frequency for 57 genes related to BBB function. Additionally, we examined correlations separately according to patient reported sex (i.e., male and female) and imaging phenotype (i.e., ENH: enhancing and NE: non-enhancing). We utilized multiple comparisons corrections with a 5% false discovery rate to determine significance. For the overall cohort, we observed significant positive correlations for the HIF1A (p&lt; 0.001) and SOX2 markers with edema. For NE samples, significant correlations included APOE (p=0.001), HIF1A (p&lt; 0.001), PIK3CA (p&lt; 0.001), PTCH1 (p&lt; 0.001), and SOX2 (p&lt; 0.001). Amongst female samples, a significant correlation with PTCH1 (p=0.002) was observed. There were no significant correlations noted for male and enhancing sub-cohorts. Significant correlations between molecular markers of BBB and edema map values could lead to clinical biomarkers for edema or tumor aggressiveness.
NIMG-21. INTERIM ANALYSIS OF A PHASE II STUDY OF MULTIPARAMETRIC MR-GUIDED HIGH-DOSE RESPONSE-ADAPTIVE RADIOTHERAPY WITH CONCURRENT TEMOZOLOMIDE IN PATIENTS WITH NEWLY DIAGNOSED GLIOBLASTOMA
Authors: Kim Michelle , Aryal Madhava , Rosen Benjamin , Parmar Hemant , You Daekeun , Junck Larry , Leung Denise , Umemura Yoshie , Heth Jason , Al-Holou Wajd , Hollon Todd , Wahl Daniel , Lawrence Theodore , Cao Yue 
Published: November 2022

Abstract

BACKGROUND
Biologically-informed radiotherapy (RT) targeting an adversely prognostic hypercellular/hyperperfused imaging phenotype in patients with newly diagnosed glioblastoma (GBM) may improve outcomes by identifying emerging regions of treatment resistance associated with survival (OS), and is under investigation in an ongoing Phase II trial (NCT04574856) of individualized, response-adaptive RT.

METHODS
In this single-arm phase II study, patients with newly diagnosed GBM following resection undergo dose-intensified chemoradiation targeting the residual hypercellular (TVHCV, mean contralateral normal brain+2SD) and hyperperfused tumor volume (TVCBV, contralateral normal frontal grey matter+1SD) identified using high b-value diffusion-weighted and dynamic contrast-enhanced perfusion MRI. The combination of TVHCVCBV (TVHCVCBV) is treated to 50 Gy in 20 fractions (2.5 Gy/fraction), and following mid-RT reassessment, the persistent and developing TVHCVCBV is treated to 30 Gy in 10 fractions (3 Gy/fraction). The primary endpoint is improvement in OS, with planned interim safety analysis.

RESULTS
Since October 2020, 16 of 30 patients have been enrolled. Median age was 58 years (range, 29-75) and 69% were male. No patient underwent biopsy only, and 50% had gross total resection; 23% had MGMT methylated tumors. Median TVHCV/TVCBV was 6.9 cc (range, 1.9-42.8) pre-RT and 30% (range, 1-72%) was nonenhancing. By mid-RT, TVHCVCBV was reduced to 4.2 cc (range, 0.8-34.3) and 47% (range, 3-74%) was nonenhancing. The TVHCVCBV persisting from pre- to mid-RT was 2.3 cc (range, 0-24.2), with an additional 1.8 cc (range, 0.3-20.6) newly developing outside the initial region. All patients underwent adaptive replanning for boost without interruption. Planned interim analysis determined an acceptable rate of neurologic toxicity and safety to continue enrollment.

CONCLUSION
Individualized, response adaptive RT using an advanced imaging biomarker to assess emerging and especially non-enhancing regions of treatment resistance in patients with GBM is feasible, with short term safety in an early cohort and longer-term efficacy outcomes anticipated with ongoing accrual.
NIMG-22. AN AI-BASED COORDINATE SYSTEM ELUCIDATES RADIOGENOMIC HETEROGENEITY OF GLIOBLASTOMA VIA DEEP LEARNING AND MANIFOLD EMBEDDINGS
Authors: Yu Fanyang , Kazerooni Anahita Fathi , Toorens Erik , Akbari Hamed , Sako Chiharu , Mamourian Elizabeth , Bagley Stephen , Binder Zev A , Lustig Robert A , Brem Steven , O’Rourke Donald M , Ganguly Tapan , Bakas Spyridon , Nasrallah MacLean , Chaudhari Pratik , Davatzikos Christos 
Published: November 2022

Abstract

PURPOSE
There is evidence that molecular heterogeneity of glioblastoma is associated with heterogeneity of MR imaging signatures. Modern machine learning models, such as deep neural networks, provide a tool for capturing such complex relationships in high-dimensional datasets. This study leverages recent advances in visualizing neural networks to construct a radiogenomics coordinate system whose axes reflect the expression of imaging signatures of genetic mutations commonly found in glioblastoma.

METHODS
Multi-parametric MRI (mpMRI) scans (T1, T1-Gd, T2, T2-FLAIR, DSC, DTI) of 254 subjects with glioblastoma were retrospectively collected. Radiomics features, including histograms, morphologic and textural descriptors, were derived. Genetic markers were obtained through next generation sequencing (NGS) panel. A multi-label classification deep neural network was trained for predicting mutation status in key driver genes, EGFR, PTEN, NF1, TP53 and RB1. We utilized a nonlinear manifold learning method called Intensive Principal Component Analysis (InPCA), to visualize the output probability distributions from the trained model. The first three principal components (PCs) were selected for constructing the coordinate system.

RESULTS
The axes derived from InPCA analysis were associated with molecular pathways known to be implicated in glioblastoma: (1) Increasing values of PC1 were associated with primary involvement of P53 then RB1 then MAPK then RTK/PI3K; (2) Increasing values of PC2 were associated with primary involvement of RTK then RB1/P53/MAPK then PI3K; (3) Increasing values of PC3 were associated with primary involvement of MAPK then RB1/P53/RTK/PI3K. Imaging features significantly associated with each of three PCs (p&lt; 0.05) were identified by Pearson correlation analysis.

CONCLUSION
Deep learning followed by nonlinear manifold embedding identifies a radiogenomics coordinate system spanned by three components which were associated with different molecular pathways of glioblastoma. The heterogeneity of radiogenomic signatures captured by this coordinate system offers in vivo biomarkers of the molecular heterogeneity of glioblastoma.